Editor’s Choice Articles

In the production and manufacturing industry, factors such as rolling equipment and processes may cause various defects on the surface of the steel plate, which greatly affect the performance and subsequent machining accuracy. Therefore, it is essential to identify defects in time and improve the quality of production. An intelligent detection system was constructed, and some improved algorithms such as dataset enhancement, annotation and lightweight convolution neural network are proposed in this paper. (1) Compared with the original YOLOV5 (You Only Look Once), the precision is 0.924, and the inference time is 29.8 ms, which is 13.8 ms faster than the original model. Additionally, the parameters and calculations are also far less than YOLOV5. (2) Ablation experiments were designed to verify the effectiveness of the proposed algorithms. The overall accuracy was improved by 0.062; meanwhile, the inference time was reduced by 21.7 ms. (3) Compared with other detection models, although RetinaNet has the highest accuracy, it takes the longest time. The overall performance of the proposed method is better than other methods. This research can better meet the requirements of the industry for precision and real-time performance. It can also provide ideas for industrial detection and lay the foundation for industrial automation. Full article

Scientifically and accurately predicting the state of health (SOH) and remaining useful life (RUL) of batteries is the key technology of automotive battery management systems. The selection of the health indicator (HI) that characterizes battery aging affects the accuracy of the prediction model construction, which in turn affects the accuracy of SOH and RUL estimation. Therefore, this paper analyzes the current status of HI selection for lithium-ion batteries by systematically reviewing the existing literature on the selection of HIs. According to the relationship between HI and battery aging, battery HI can be divided into two categories: direct HI and indirect HI. The capacity and internal resistance of the battery can directly represent the aging degree of the battery and are the direct HIs of the battery. Indirect HIs refer to characteristic parameters extracted from battery charge and discharge data that can characterize the degree of battery aging. This paper analyzes and summarizes the advantages and disadvantages of various HIs and indirect HIs commonly used in current research, providing useful support and reference for future researchers in selecting HIs to characterize battery aging. Finally, in view of the capacity regeneration phenomenon in the aging process of the battery, the selection direction of future HI is proposed. Full article

Rehabilitation and mobility assistance using robotic orthosis or exoskeletons have shown potential in aiding those with musculoskeletal disorders. Artificial muscles are the main component used to drive robotics and bio-assistive devices. However, current fabrication methods to produce artificial muscles are technically challenging and laborious for medical staff at clinics and hospitals. This study aims to investigate a printhead system for material extrusion of helical polymer artificial muscles. In the proposed system, an internal fluted mandrel within the printhead and a temperature control module were used simultaneously to solidify and stereotype polymer filaments prior to extrusion from the printhead with a helical shape. Numerical simulation was applied to determine the optimal printhead design, as well as analyze the coupling effects and sensitivity of the printhead geometries on artificial muscle fabrication. Based on the simulation analysis, the printhead system was designed, fabricated, and operated to extrude helical filaments using polylactic acid. The diameter, thickness, and pitch of the extruded filaments were compared to the corresponding geometries of the mandrel to validate the fabrication accuracy. Finally, a printed filament was programmed and actuated to test its functionality as a helical artificial muscle. The proposed printhead system not only allows for the stationary extrusion of helical artificial muscles but is also compatible with commercial 3D printers to freeform print helical artificial muscle groups in the future. Full article

To realize tomato growth period monitoring and yield prediction of tomato cultivation, our study proposes a visual object tracking network called YOLO-deepsort to identify and count tomatoes in different growth periods. Based on the YOLOv5s model, our model uses shufflenetv2, combined with the CBAM attention mechanism, to compress the model size from the algorithm level. In the neck part of the network, the BiFPN multi-scale fusion structure is used to improve the prediction accuracy of the network. When the target detection network completes the bounding box prediction of the target, the Kalman filter algorithm is used to predict the target’s location in the next frame, which is called the tracker in this paper. Finally, calculate the bounding box error between the predicted bounding box and the bounding box output by the object detection network to update the parameters of the Kalman filter and repeat the above steps to achieve the target tracking of tomato fruits and flowers. After getting the tracking results, we use OpenCV to create a virtual count line to count the targets. Our algorithm achieved a competitive result based on the above methods: The mean average precision of flower, green tomato, and red tomato was 93.1%, 96.4%, and 97.9%. Moreover, we demonstrate the tracking ability of the model and the counting process by counting tomato flowers. Overall, the YOLO-deepsort model could fulfill the actual requirements of tomato yield forecast in the greenhouse scene, which provide theoretical support for crop growth status detection and yield forecast. Full article

This paper presents a novel model-based structural optimization approach for the efficient electromechanical development of hexapod robots. First, a hexapod-design-related analysis of both optimization objectives and relevant parameters is conducted based on the derived dynamical model of the robot. A multi-objective optimization goal is proposed, which minimizes energy consumption, unwanted body motion and differences between joint torques. Then, an optimization framework is established, which utilizes a sophisticated strategy to handle the optimization problems characterized by a large set of parameters. As a result, a satisfactory result is efficiently obtained with fewer iterations. The research determines the optimal parameter set for hexapod robots, contributing to significant increases in a robot’s walking range, suppressed robot body vibrations, and both balanced and appropriate motor loads. The modular design of the proposed simulation model also offers flexibility, allowing for the optimization of other electromechanical properties of hexapod robots. The presented research focuses on the mechatronic design of the Szabad(ka)-III hexapod robot and is based on the previously validated Szabad(ka)-II hexapod robot model. Full article

This paper is based on the “Fast Pneumatic Mesh Driver” (FPN) used to couple a silicone rubber soft body with a rigid skeleton. A rigid-flexible coupling soft-body human-like finger design scheme is proposed to solve the problem of low load on the soft-body gripping hand. The second-order Yeoh model is used to establish the statics model of the soft humanoid finger, and the ABAQUS simulation analysis software is used for correction and comparison to verify the feasibility of the soft humanoid finger bending. The thickness of the driver cavity and the confining strain layer were determined by finite element simulation. The mold casting process is used to complete the preparation of human-like fingers and design a pneumatic control system for experiments combined with 3D printing technology. The experimental results show that the proposed rigid-flexible coupling soft body imitating the human finger structure can realize the corresponding actions, such as the multi-joint bending and side swinging, of human fingers. Compared with the traditional pure soft-body finger, the fingertip output force is significantly improved. The optimal design and simulation analysis of the human gripper and the feasibility of the application have practical guiding significance. Full article

With the expansion of the cyber-physical system (CPS) application area, its importance has become more and more prominent. As one of the typical applications of CPS, the anomaly detections of mobile robots have attracted the attention of all parties. As part of the CPS, mobile robots face the problem that conventional residual-based detection methods cannot identify stealthy anomalies. The conventional residual-based detection methods mainly use the residual signal calculated from the control signal and measure output for detection, which is widely used in fault diagnosis. Still, it is difficult to be useful in deceptive stealthy anomalies purposefully imposed on mobile robots, which are designed to evade the conventional detections by tampering with measure output. Furthermore, they can control the system to deviate from the expected operations, causing degradation of control performance or even damage without being detected. Based on this, by analyzing the system model of CPS and the stealthy conditions of anomalies, the improved residual-based detection method is proposed in this paper. Moreover, three stealthy anomalies purposefully imposed on an omnidirectional mobile robot (OMR) are detected by using the conventional residual-based methods and the improved residual-based method. Finally, the experimental results show that the method proposed can effectively detect the stealthy anomalies purposefully imposed on the OMR. Full article

The thermal design of electrical machines has numerous influencing factors. This paper compares different cooling methods, their volume flow rates and other machine parameters with regard to the continuous power of a PMSM. Understanding the characteristics of different heat sinks depending on their operating point is important for an expedient design in order to avoid derating due to overtemperatures. As a design guideline, this contribution shows the influence of stator cooling jackets, rotor shaft cooling and direct end winding cooling for different machine lengths and volume flow rates. Both water and oil are investigated as coolants. With increasing machine dimensions, end winding cooling becomes less effective for heat sources in the center of the machine while the heat transferred in the cooling jacket increases. A sensitivity study of other machine parameters, such as the maximum allowed magnet temperature or the coolant inlet temperature, improves the understanding of the reader as to how the continuous power of a PMSM can be increased when the rotor temperature limits the performance. Full article

In this paper, a complementary and simplified scheme to diagnose electrical faults in a three-phase induction motor using the parity equations approach during steady state operation bases on the stator current reference frame is presented. The proposed scheme allows us to identify the motor phase affected due to faults related to the stator side, such as current sensors, voltage sensors, and resistance. The results obtained in this work complement a detection system that uses the DQ model of the three-phase induction motor and parity equations focused on the synchronous reference frame, which can detect stator-side faults but cannot locate the affected phase. In addition, considering practical and operational aspects, the residual detection set obtained is simplified to three simple algebraic equations that are easy to implement. The simulation results using the PSIM simulation software and the experimental test allow us to validate the proposed scheme. Full article

In the research and development of a passive exoskeleton, the body–exoskeleton coupling mode is a key point to reduce the interaction force and realize the efficient assistance of the exoskeleton. The purpose of this paper was to explore a cooperative movement mode between human and passive exoskeleton for reducing the body–exoskeleton interaction force. Firstly, through the research of the body–exoskeleton interactive mode, we analyzed the kinematic and dynamic constraint of the exoskeleton and established a dynamic model of the body–exoskeleton system. On this basis, the characteristic of the body–exoskeleton interaction force was analyzed; then, we put forward a mode that uses human gravity and load weight to maintain the stability of the exoskeleton’s movement to achieve the goal of reducing the interaction force. Based on the human–exoskeleton integrated mode, we constructed a mechanical model and simulated the change in interaction force in this mode; the simulation results showed that the interaction force at the lower leg was 98.5% less than that of the pure mechanical exoskeleton. Finally, we developed a prototype that was made of plastic parts and finished the experiment by walking with a load of 30 kg. The experimental results showed that this mode reduced the body–exoskeleton interaction force by 65.1%, which verified the effectiveness of the body–exoskeleton coupling mode preliminarily. The research results provided a new analytical approach for the design of a passive exoskeleton, and its improvement effect could be extended from the lower leg of the body–exoskeleton to the thigh or trunk, and guide the design of a passive exoskeleton. Full article

If sufficient historical failure life data exist, the failure distribution of the system can be estimated to identify the system initial hazard function. The conventional proportional covariate model (PCM) can reveal the dynamic relationship between the response covariates and the system hazard rate. The system hazard rate function can be constantly updated by the response covariates through the basic covariate function (BCF). Under the circumstances of sparse or zero failure data, the key point of the PCM reliability assessment method is to determine the proportional factor between covariates and the hazard rate for getting BCF. Being devoid of experiments or abundant experience of the experts, it is very hard to determine the proportional factor accurately. In this paper, an improved PCM (IPCM) is put forward based on the logistic regression model (LRM). The salient features reflecting the equipment degradation process are extracted from the existing monitoring signals, which are considered as the input of the LRM. The equipment state data defined by the failure threshold are considered as the output of the LRM. The initial reliability can be first estimated by LRM. Combined with the responding covariates, the initial hazard function can be calculated. Then, it can be incorporated into conventional PCM to implement the reliability estimation process on other equipment. The conventional PCM and the IPCM methods are respectively applied to aero-engine rotor bearing reliability assessment. The comparative results show that the assessing accuracy of IPCM is superior to the conventional PCM for small failure sample. It provides a new method for reliability estimation under sparse or zero failure data conditions. Full article

In recent years, the study of robotic systems for agriculture, a modern research field often shortened as “precision agriculture”, has become highly relevant, especially for those repetitive actions that can be automated thanks to innovative robotic solutions. This paper presents the kinematic model and a motion planning pipeline for a mobile manipulator specifically designed for precision agriculture applications, such as crop sampling and monitoring, formed by a novel articulated mobile base and a commercial collaborative manipulator with seven degrees of freedom. Starting from the models of the two subsystems, characterized by an adjustable position and orientation of the manipulator with respect to the mobile base, the linear mapping that describes the differential kinematics of the whole custom system is expressed as a function of the input commands. To perform pick–and–place tasks, a motion planning algorithm, based on the manipulator manipulability index mapping and a closed form inverse kinematics solution is presented. The motion of the system is based on the decoupling of the base and the arm mobility, and the paper discusses how the base can be properly used for manipulator positioning purposes. The closed form inverse kinematics solution is also provided as an open-source Matlab code. Full article

Transfer learning is a topic that has attracted attention for the intelligent fault diagnosis of bearings since it addresses bearing datasets that have different distributions. However, the traditional intelligent fault diagnosis methods based on transfer learning have the following two shortcomings. (1) The multi-mode structure characteristics of bearing datasets are neglected. (2) Some local regions of the bearing signals may not be suitable for transfer due to signal fluctuation. Therefore, a multi-domain weighted adversarial transfer network is proposed for the cross-domain intelligent fault diagnosis of bearings. In the proposed method, multi-domain adversarial and attention weighting modules are designed to consider bearing multi-mode structure characteristics and solve the influence of local non-transferability regions of signals, respectively. Two diagnosis cases are used to verify the proposed method. The results show that the proposed method is able to extract domain invariant features for different cross-domain diagnosis cases, and thus improves the accuracy of fault identification. Full article

Studying the motion and load-bearing characteristics of the planetary roller screw mechanism is the basis for the structural design and performance optimisation of the mechanism. The mechanical structures and working principles of different kinds of planetary roller screw mechanisms are summarised. Published papers on kinematic, load-bearing and dynamic models of the planetary roller screw mechanism are reviewed. Based on the slip state in point contacts at the screw–roller and the nut–roller interfaces, the kinematic models are divided into three types. The finite element method and numerical theory are the two main methods used to develop the load-bearing models. Current dynamic models differ mainly concerning whether they take the rotation of the screw into consideration. In this work, each kind of model is presented in detail along with relevant literature. The main conclusions for each type of model are discussed, and an overview of the future evolution of motion and load-bearing characteristics of the planetary roller screw mechanism are given. Full article

Recently, even though 3D bioprinting has made it possible to fabricate 3D artificial tissues/organs, it still faces several significant challenges such as cell sedimentation and aggregation. As the essential element of 3D bioprinting, bioink is usually composed of biological materials and living cells. Guided by the initially dominant gravitational force, cells sediment, resulting in the non-uniformity of the bioink and the decrease in the printing reliability. This study primarily focuses on the quantification of cell sedimentation-induced cell concentration change and cell aggregation within the bioink reservoir during inkjet-based bioprinting. The major conclusions are summarized as follows: (1) with 0.5% (w/v) sodium alginate, after around 40-min printing time, almost all the cells have sedimented from the top region. The cell concentration at the bottom is measured to be more than doubled after 60-min printing time. On the contrary, due to the slow cell sedimentation velocity with 1.5% and 3% (w/v) sodium alginate, the uniformity of the bioink is still highly maintained after 60-min printing; and (2) more cell aggregates are observed at the bottom with the printing time, and severe cell aggregation phenomenon has been observed at the bottom using 0.5% (w/v) sodium alginate starting from 40-min printing time. With the highest cell concentration 2 × 10⁶ cells/mL, 60.9% of the cells have formed cell aggregates at 40-min printing time. However, cell aggregation is dramatically suppressed by increasing the polymer concentration. Full article

This paper deals with the modification of the mechanical system of the needle bar. The purpose of this work is to reduce the vibration and noise of the sewing machine for creating a decorative stitch. A special floating needle is used to sew this stitch, in which two mechanical systems of needle bars handover through the sewn material, so that a perfect imitation of a hand stitch is created. The original system, which controls the release of the needle at the handover location by abruptly stopping the needle bar control element, could be replaced by a new system that uses magnetic force to release the needle. In addition to the usual design procedure, numerical simulations of the attractive force of the electromagnet are also used in the design of a suitable electromagnet. At the same time, an electrical circuit is also designed to allow the needle to be released and gripped quickly. The advantages of the new system lie not only in reducing vibrations and the associated increase in the operation speed of the machine, but also in making it easier for the machine to switch to possible automated or semi-automated production. Full article

This paper focuses on the system design and control strategies of a hydraulic hexapod robot (HHR) ZJUHEX01 with a two-stage supply pressure hydraulic system (TSS). Firstly, a brief introduction is given, including the mechanical structure, the onboard hydraulic system, and the control system architecture. Secondly, the kinematics model and hydraulic system model are built in preparation for the controller design. Then a sliding mode repetitive controller (SMRC) for the separate meter in and separate meter out (SMISMO) hydraulic system is proposed, as well as the valve configuration, to help HHR get better control performance and smaller tracking errors. Furthermore, a high order sliding mode differentiator (HOSMD) is developed to obtain the joint angular velocity and acceleration. Finally, the ADAMS and MATLAB/Simulink co-simulation model is established to verify the effectiveness of the control strategy. Also, the energy consumption of TSS is compared with that of one-stage supply pressure hydraulic system (OSS) to show a great energy-saving effect of 51.94%. Full article

Due to the workforce shortage caused by the declining birth rate and aging population, robotics is one of the solutions to replace humans and overcome this urgent problem. This paper introduces a deep learning-based object detection algorithm for empty-dish recycling robots to automatically recycle dishes in restaurants and canteens, etc. In detail, a lightweight object detection model YOLO-GD (Ghost Net and Depthwise convolution) is proposed for detecting dishes in images such as cups, chopsticks, bowls, towels, etc., and an image processing-based catch point calculation is designed for extracting the catch point coordinates of the different-type dishes. The coordinates are used to recycle the target dishes by controlling the robot arm. Jetson Nano is equipped on the robot as a computer module, and the YOLO-GD model is also quantized by TensorRT for improving the performance. The experimental results demonstrate that the YOLO-GD model is only 1/5 size of the state-of-the-art model YOLOv4, and the $mAP$ of YOLO-GD achieves 97.38%, 3.41% higher than YOLOv4. After quantization, the YOLO-GD model decreases the inference time per image from 207.92 ms to 32.75 ms, and the $mAP$ is 97.42%, which is slightly higher than the model without quantization. Through the proposed image processing method, the catch points of various types of dishes are effectively extracted. The functions of empty-dish recycling are realized and will lead to further development toward practical use. Full article

This paper designed a fuzzy adaptive proportional integral differential (PID) control algorithm to optimize the overshoot of speed and torque, fuel consumption and exhaust emissions of the traditional PID control strategy in the process of working condition switching of an extended range electric vehicle. The simulation was carried out in Matlab/Simulink, and the optimization of the control strategy was verified by a bench test. The results show that the fuzzy adaptive PID control strategy effectively reduced the speed overshoot in the process of working condition switching compared with the traditional PID control strategy. The bench test proved that the fuzzy adaptive PID control strategy could effectively optimize the switching process, especially in the speed and torque reduction switching process, and the speed overshoot rate of the fuzzy PID control was greatly reduced to 0.7%, far less than that of the traditional PID control with 6.6%, while the torque overshoot rate was within 0.8%. Additionally, the fuzzy adaptive PID control could effectively reduce the fuel consumption, especially in the switching process of increasing the speed and torque, where the fuel consumption of the fuzzy adaptive PID control was 2.1% and 0.5% lower than that of the traditional PID control, respectively. Additionally, the fuzzy adaptive PID control could also reduce the particulate emissions, especially in the process of increasing the speed and torque, where the number of particles of the fuzzy PID control was 11% and 19% less than that of the traditional PID control, respectively. However, the NOx emissions based on the fuzzy PID control were slightly higher than those of the traditional PID control due to the smooth operation and improved combustion. Full article

To improve the accuracy of tracking the trunk center-of-mass (CoM) trajectory and foot-end trajectory in a fully electrically driven quadruped robot, an efficient and practical new trajectory tracking control method is designed. The proposed trajectory tracking method is mainly divided into trunk balance controller (TBC) and swing leg controller (SLC). In TBC, a quadruped robot dynamics model is developed to find the optimal foot-end force that follows the trunk CoM trajectory based on the model predictive control (MPC) principle. In SLC, the Bessel curve is planned as the desired trajectory at the foot-end, while the desired trajectory is tracked by a virtual spring-damping element driving the foot-end, meanwhile, the radial basis function neural network (RBFNN) is applied for supervisory control to improve the control performance for the system. The experimental results show that the control method can modify the robot’s foot-end trajectory tracking effect, so that the stability error can be eliminated and the robustness of the controller can be improved, meanwhile, the linear and circular trajectory for CoM can be tracked accurately and quickly. Full article

The geometric accuracy of a workpiece represents one of the key parameters defining its quality, and it is affected by the appropriate selection of the machine tool, control system, NC program and cutting conditions. Up-to-date control systems contain advanced compensation functions, which increase the volumetric accuracy of the machine tools. Nevertheless, these functions use correction data measurements within the machine tool’s periodic maintenance plan. This paper introduces a method for ad hoc correction data modification. This modification is based on the difference between the real and nominal workpiece geometries, which are evaluated on a coordinate-measuring machine as a standard process in high-accuracy workpiece production. Correction data are compiled in the form of a three-dimensional structured mesh, where nodes of the mesh contain such correction values that interpolations within the mesh suppress workpiece geometric deviations. The correction mesh calculations are based on the assumption that the nodes are connected by imaginary springs and that they are initially in force equilibrium. Force disbalance is introduced by workpiece geometric deviations evaluated at arbitrary points. Then the new position of force-balanced nodes is calculated. Experimental results on a three-axis machining center have verified the proposed method, where geometric accuracy of the workpiece increased more than 85% without any negative effect on surface quality. The approach presented is efficient for increasing workpiece accuracy without the need for NC program modification. Full article

When primary resonance occurs, even a small external disturbance can abruptly excite large amplitude vibration and deteriorate the working performance of a flexible manipulator. Most active control methods are effective for non-resonant vibration but not for primary resonance. In view of this, this paper puts forward a new nonlinear saturation-based control method to suppress the primary resonance of a flexible manipulator considering complicated rigid-flexible coupling and modal coupling. A vibration absorber with variable stiffness/damping is designed to establish an energy exchange channel for saturation. A novel idea of modal coupling enhancement is suggested to improve saturation performance by strengthening the coupling relationship between the mode of the vibration absorber and the controlled mode of the flexible manipulator. Through stability analysis on the primary resonance response of the flexible manipulator with the vibration absorber, the saturation mechanism is successfully established and the effectiveness of the saturation control algorithm is validated. On this basis, several important indexes are extracted and employed to optimize saturation control. Finally, a series of virtual prototyping simulations and experiments are conducted to verify the feasibility of the suggested saturation-based control method. This research will contribute to the primary resonance suppression of a flexible manipulator under a complex external excitation environment. Full article

Optimizing electromagnetic performance and vibration noise performance simultaneously is important when designing the drive motor for electric vehicles (EVs). This has not been fully explored, and there are only a few relevant studies. To achieve simultaneous optimization, this paper proposes an equivalent structural network (ESN) of stator assembly to calculate the modal distribution and harmonic response transfer functions. Based on the ESN model, the motor’s electromagnetic vibration noise harmonic response, such as acceleration and equivalent radiated power level (ERPL), can be quickly calculated. The feasibility of the established ESN model is verified by structural-field finite-element method (FEM) and modal hammer tests. Based on the modern optimization algorithm and the ESN model, an improved multi-physics and multi-objective optimization design approach is proposed for an optimized design of a 30 kW interior permanent-magnet synchronous machine (IPMSM). The motor’s maximum output torque and ERPL were selected as optimization objectives, and then the ERPL and acceleration were recalculated using structural-field FEM to validate the accuracy of the optimal design. Finally, vibration acceleration tests were carried out on a manufactured prototype motor to verify the feasibility and validity of the proposed optimization design method. Full article

In the field of Diagnostics, the fundamental task of detecting damage is basically a binary classification problem, which is addressed in many cases via Novelty Detection (ND): an observation is classified as novel if it differs significantly from reference, healthy data. ND is practically implemented summarizing a multivariate dataset with univariate distance information called Novelty Index. As many different approaches are possible to produce NIs, in this analysis, the possibility of implementing a simple classifier in a reduced-dimensionality space of NIs is studied. In addition to a simple decision-tree-like classification method, the process for obtaining the NIs can result as a dimension reduction method and, in turn, the NIs can be used for other classification algorithms. In addition, a case study will be analyzed thanks to the data published by the Prognostics and Health Management Europe (PHME) society, on the occasion of the Data Challenge 2021. Full article

To help people with impairment of lower extremity movement regain the ability to stand and walk, and to enhance limb function, this study proposes an anthropomorphic design of an electrically driven, lower-limb exoskeleton rehabilitation robot. The angular range of the robot’s motion was determined according to the characteristics of the targeted lower-limb joints; the robot was given an active–passive anthropomorphic design with 12 degrees of freedom. The multi-degree-of-freedom hip exoskeleton, bionic artificial knee exoskeleton and passive rigid-flexible coupling ankle exoskeleton can assist patients in rehabilitation exercises with better wear comfort and exercise flexibility. A kinetic model of the seven-rod lower-limb exoskeleton rehabilitation robot was built, and data analysis of the dynamically captured motion trajectory was conducted. These provided a theoretical basis for gait planning and the control system of the lower-limb exoskeleton rehabilitation robot. The results show that the lower-limb exoskeleton rehabilitation robot system possesses sound wearing comfort and movement flexibility, and the degree of freedom of movement of the exoskeleton robot matches well with that of human movement. The robot can thus provide effective assistance to patients’ standing and walking rehabilitation training. Full article

Inspired by rodents’ free navigation through a specific space, RatSLAM mimics the function of the rat hippocampus to establish an environmental model within which the agent localizes itself. However, RatSLAM suffers from the deficiencies of erroneous loop-closure detection, low reliability on the experience map, and weak adaptability to environmental changes, such as lighting variation. To enhance environmental adaptability, this paper proposes an improved algorithm based on the HSI (hue, saturation, intensity) color space, which is superior in handling the characteristics of image brightness and saturation from the perspective of a biological visual model. The proposed algorithm first converts the raw image data from the RGB (red, green, blue) space into the HSI color space using a geometry derivation method. Then, a homomorphic filter is adopted to act on the I (intensity) channel and weaken the influence of the light intensity. Finally, guided filtering is used to process the S (saturation) channel and improve the significance of image details. The experimental results reveal that the improved RatSLAM model is superior to the original method in terms of the accuracy of visual template matching and robustness. Full article

An advanced LKS (lane keeping system) for use on curving roads is presented to maintain autonomous vehicle driving within the target lane, without unintentional lane departure. There are the following two main objectives in designing this system: one is performing perfect lane keeping and the other is ensuring the dynamic stability of the vehicle, especially when driving on a curving and low-friction road with time-varying high speed. In this paper, a combined vehicle model, consisting of a lane keeping model and a vehicle lateral dynamic model, is firstly introduced. Then, a novel adaptive-weight predictive controller is used to calculate the desired steering angle and the additional yaw moment which provide coordinated control forlane keeping and dynamic stability control. Meanwhile, a square-root cubature Kalman filter-based vehicle sideslip angle observer, with a strong tracking theory modification (ST-SRCKF), is established to estimate the sideslip angle during the driving process. Finally, HIL (hardware-in-the-loop) tests and field tests are constructed, and the results show the effectiveness of our proposed LKS controller and ST-SRCKF sideslip angle estimation. Full article

Additive manufacturing (AM) is a key technology for advancing many fields, including electrical machines. It offers unparalleled design freedom together with low material waste and fast prototyping, which is why it has become to focus of many researchers. For electrical machines, AM allows the production of designs with optimized mechanical, electromagnetic and thermal parameters. This paper attempts to give the reader an overview of the existing research and thermal solutions which have been realized with the use of AM. These include novel heat sink and heat exchanger designs, solutions for cooling the machine windings directly, and additively manufactured hollow windings. Some solutions such as heat pipes, which have been produced with AM but not used to cool electrical machines, are also discussed, as these are used in conventional designs and will certainly be used for additively manufactured electrical machines in the future. Full article

The dynamical evolution of electrical discharge machining (EDM) has drawn immense research interest. Previous research on mechanism analysis has discussed the deterministic nonlinearity of gap states at pulse-on discharging duration, while describing the pulse-off deionization process separately as a stochastic evolutionary process. In this case, the precise model describing a complete machining process, as well as the optimum performance parameters of EDM, can hardly be determined. The main purpose of this paper is to clarify whether the EDM system can maintain consistency in dynamic characteristics within a discharge interval. A nonlinear self-maintained equivalent model is first established, and two threshold conditions are obtained by the Shilnikov theory. The theoretical results prove that the EDM system could lead to chaos without external excitation. The time series of the deionization process recorded in the EDM experiments are then analyzed to further validate this theoretical conclusion. Qualitative chaotic analyses verify that the autonomous EDM process has chaotic characteristics. Quantitative methods are used to estimate the chaotic feature of the autonomous EDM process. By comparing the quantitative results of the autonomous EDM process with the non-autonomous EDM process, a deduction is further made that the EDM system will evolve towards steady chaos under an autonomous state. Full article

Bearing stiffness, as one of the most important service characteristics for ball bearing, plays a crucial role in the bearing design and rotor dynamic analysis. To rapidly and accurately calculate the stiffness matrix of ball bearing under the arbitrary load conditions, a 5-DOF analytical model for bearing stiffness matrix analysis has been established by the ball–raceway contact analysis, implicit/explicit differential method, and matrix operations. The model has been validated comparing with the previous methods and experimental results. Based on this, the model has been used to investigate the influences of the load and operation conditions, the structural parameters variation on stiffness of ball bearing. The results show that property increasing axial preload can inhibit the attenuation of speed-varying stiffness, and the contact states between balls and raceways also have significant influence on the change in the stiffness of ball bearings. Besides, a larger curvature coefficient of inner raceway and a small curvature coefficient of outer raceway can effectively improve the stiffness of ball bearing at high speed. Therefore, the proposed method can be a useful tool in bearing optimize design and performance analysis of ball and rotor system under various load conditions. Full article

In the fabrication process of thin-walled micro-parts, both micro-cutting tools and thin-walled micro-parts have the characteristics of small size and low stiffness. Therefore, the regenerative chatter during the machining process cannot be ignored. The influence of the tool runout error and actual trochoidal trajectories of the cutting edge on micro-milling forces should also be considered comprehensively. In this paper, the tool runout error in the micro-milling process is first analysed, and an instantaneous undeformed chip thickness model is established considering the runout error. On this basis, the dynamic deformation of the micro-cutting tool and thin-walled micro-part is studied, and an instantaneous, undeformed, chip-thickness model is proposed with the consideration of both the runout error and dynamic deformation. The dynamic parameters of the machining system are obtained using the receptance coupling method. Finally, thin-walled micro-part machining experiments are carried out, and the obtained results of micro-milling force simulation based on the proposed model are compared with the experimental results. The results indicate that the micro-milling force modelling, by taking the influence of machining dynamics into account, has better prediction accuracy, and the difference between the predicted resultant forces and the experimental results is less than 11%. Full article

Spherical parallel robots (SPR) are widely used in industries and robotic rehabilitation. Designing such systems for better balance properties is still a challenge. This paper presents a work to minimize the shaking moment for a fully force-balanced SPR by combining the counterweight (CW) and adjusting the kinematic parameters (AKP). An approximate model of the shaking moment of the SPR is proposed for computational efficiency (specifically allowing for a gradient-based optimization algorithm available in MATLAB) yet without the loss of much accuracy. The effectiveness of the proposed approach has been confirmed based on simulation, especially with the software system SPACAR due to its high reliability and easy availability. Specifically, the simulation result shows that compared with the unbalanced SPR, the shaking moment of the balanced SPR can decrease by more than 90%. It is worth mentioning that the AKP approach is an excellent example of mechatronics by combining the capability of re-planning the joint motion from the end-effector motion and adjusting the kinematic parameters to redistribute the mass of the whole robot for canceling the shaking force and shaking moment—inertia-induced force and moment to the ground. In short, the main contributions of this paper are: (1) a combined CW and AKP approach to the partial moment balancing of the SPR enhanced with a simplified mathematical model of the shaking moment of the SPR, and (2) a new design of the SPR which can be fully force balanced yet partially moment balanced. A note is taken that the simplified model is under the condition that the parameters of the link have certain geometric relations, which is a limitation of our approach. Full article

Multiphase drives offer enhanced fault-tolerant capabilities compared with conventional three-phase ones. Their phase redundancy makes them able to continue running in the event of faults (e.g., open/short-circuits) in certain phases. Moreover, their greater number of degrees of freedom permits improving diagnosis and performance, not only under faults affecting individual phases, but also under those affecting the machine/drive as a whole. That is the case of failures in the dc link, resolver/encoder, control unit, cooling system, etc. Accordingly, multiphase drives are becoming remarkable contenders for applications where high reliability is required, such as electric vehicles and standalone/off-shore generation. Actually, the literature on the subject has grown exponentially in recent years. Various review papers have been published, but none of them currently cover the state-of-the-art in a comprehensive and up-to-date fashion. This two-part paper presents an overview concerning fault tolerance in multiphase drives. Hundreds of citations are classified and critically discussed. Although the emphasis is put on fault tolerance, fault detection/diagnosis is also considered to some extent, because of its importance in fault-tolerant drives. The most important recent advances, emerging trends and open challenges are also identified. Part 1 provides a comprehensive survey considering numerous kinds of faults, whereas Part 2 is focused on phase/switch open-circuit failures. Full article

The reverse-salient permanent magnet synchronous motor (RSPMSM) is a competitive candidate for electric vehicles due to its high torque density and high efficiency. This paper proposes an optimized RSPMSM by adopting a segmented permanent magnet structure. First, the structure, electromagnetic torque, and current control laws of the RSPMSM are introduced in detail. Second, the optimization design method of the RSPMSM is proposed by taking the torque and constant-power speed range as optimized objectives, with the saliency ratio as a constraint. The optimized model of the RSPMSM is determined using the genetic algorithm (GA). Further performance analysis and comparisons are made between the initial motor and the optimized motor. Finally, a prototype is manufactured, and the performance of the RSPMSM is verified through the finite element method (FEM) and experiments. Full article

Bone defects caused by bone diseases and bone trauma need to be implanted or replaced by surgery. Therefore, it is of great significance to design and prepare a tibial implant with good biocompatibility and excellent comprehensive mechanical properties. In this paper, with 316L stainless steel powder as the main material, a personalized artificial tibia design and processing method based on laser powder bed fusion is proposed. Firstly, the personalized model of the damaged part of the patient is reconstructed. Then, the porous structure of human tibia is manufactured by selective laser melting technology. To research the factors affecting the quality of selective laser melting porous structure, a laser heat source model, heat transfer model and molten pool model of laser powder bed fusion process were constructed; then, by changing the laser process parameters (laser power, laser beam diameter, scanning speed, powder layer thickness, etc.) to conduct multiple sets of simulation experiments, it is obtained that when the “laser power is 180 W, the laser scanning speed is 1000 mm/s, the laser beam diameter is 80 μm, the powder layer thickness is 50 μm”, the porous stainless steel parts with better quality can be obtained. Finally, the porous structure was fabricated by selective laser processing, and its properties were tested and analyzed. The experimental results show that the cell side length of cube is 1.2 mm, the elastic modulus of octahedral porous structure with pillar diameter of 0.35 mm is about 17.88 GPa, which match well with tibial bone tissue. Full article

The impact of the illumination level on the quantitative indicators of mechanical damage of the rolled strip is investigated. To do so, a physical model experiment was conducted in the laboratory. The obtained images of defects at light levels in the range of 2–800 lx were recognized by a neural network model based on the U-net architecture with a decoder based on ResNet152. Two levels of illumination were identified, at which the total area of recognized defects increased: 50 lx and 300 lx. A quantitative assessment of the overall accuracy of defect recognition was conducted on the basis of comparison with data from images marked by an expert. The best recognition result (with Dice similarity coefficient DSC = 0.89) was obtained for the illumination of 300 lx. At lower light levels (less than 200 lx), some of the damage remained unrecognized. At high light levels (higher than 500 lx), a decrease in DSC was observed, mainly due to the fact that the surface objects are better visible and the recognized fragments become wider. In addition, more false-positives fragments were recognized. The obtained results are valuable for further adjustment of industrial systems for diagnosing technological defects on rolled metal strips. Full article

Fish can swim in a variety of states. For example, they look flexible and perform low-frequency undulatory locomotion when cruising, but they seem very powerful and stiff and perform high-frequency undulatory when hunting. In the process of changing the motion state, the stiffness of the fish body affects the swimming performance of the fish. In this article, we imitated the change of stiffness by superimposing rubber sheets and used experimental methods to test its swimming performance under different swing frequencies. A series of rubber fish tails were made according to the analysis of the swimming movement of real fish, providing different stiffness values and changing the curves of the body. In the prototype experiments, the base of the fish tail was fixed to a platform via a force sensor, which can oscillate at various speeds, so that the fish tail was able to swing and the thrust could be tested at different frequencies. According to the experimental results, we found that with the change of the swing frequency, there were different optimal stiffnesses that could make the thrust reach the maximum value, and with the increase of stiffness, the envelope interval of the swing curve gradually widened, the amplitude increased, and the hysteresis of the tail fin relative to the end decreased. Full article

Prognostics and health management (PHM) is a framework to identify damage prior to its occurrence which leads to the reduction of both maintenance costs and safety hazards. Based on the data collected in condition monitoring, the degradation of the part is predicted. Studies show that most failures are caused by faults in rolling element bearing, which highlights that a bearing is one of the most important mechanical components of any machine. Thus, it becomes important to monitor bearing degradation to make sure that it is utilized properly. Generally, machine learning (ML) or deep learning (DL) techniques are utilized to predict bearing degradation using a data-driven approach, where signals are captured from the machine. There should be a large amount of data to apply either ML or DL techniques, but it is difficult to collect that amount of data directly from any machine. In this study, health assessment is carried out using the correlation coefficient to divide the bearing life into two degradation stages. The raw signal is processed using discrete wavelet transform (DWT), where mutual information (MI) is used to rank and select the base wavelet, after which tabular generative adversarial networks (TGAN) are used to generate the artificial coefficients. Statistical features are calculated from the real data (DWT coefficients) and the artificial data (generated from TGAN). The constructed feature vector is then used as an input to train machine learning models, namely ensemble bagged tree (EBT) and Gaussian process regression with the squared exponential kernel function (SEGPR), to estimate bearing degradation conditions. Both the machine learning models were validated on the publicly available experimental data of FEMTO bearing. Obtained results showed that the developed EBT and SEGPR models accurately predicted the bearing degradation conditions with the average lowest RMSE value of 0.0045 and MAE value of 0.0037. Full article

The inspection of welding surface quality is an important task for welding work. With the development of product quality inspection technology, automated and machine vision-based inspection have been applied to more industrial application fields because of its non-contact, convenience, and high efficiency. However, challenging material and optical phenomena such as high reflective surface areas often present on welding seams tend to produce artifacts such as holes in the reconstructed model using current visual sensors, hence leading to insufficiency or even errors in the inspection result. This paper presents a 3D reconstruction technique for highly reflective welding surfaces based on binocular style structured light stereo vision. The method starts from capturing a fully lit image for identifying highly reflective regions on a welding surface using conventional computer vision models, including gray-scale, binarization, dilation, and erosion. Then, fringe projection profilometry is used to generate point clouds on the interested area. The mapping and alignment from 2D image to 3D point cloud is then established to highlight features that are vital for eliminating “holes”—large featureless areas—caused by high reflections such as the specular mirroring effect. A two-way slicing method is proposed to operate on the refined point cloud, following the concept of dimensionality reduction to project the sliced point cloud onto different image planes before a Smoothing Spline model is applied to fit the discrete point formed by projection. The 3D coordinate values of points in the “hole” region are estimated according to the fitted curves and appended to the original point cloud using iterative algorithms. Experiment results verify that the proposed method can accurately reconstruct a wide range of welding surfaces with significantly improved precision. Full article

The present paper describes a measurement setup and a related prediction of the electrical impedance of rolling bearings using machine learning algorithms. The impedance of the rolling bearing is expected to be key in determining the state of health of the bearing, which is an essential component in almost all machines. In previous publications, the determination of the impedance of rolling bearings has already been advanced using analytical methods. Despite the improvements in accuracy achieved within the calculations, there are still discrepancies between the calculated and the measured impedance, leading to an approximately constant off-set value. This discrepancy motivates the machine learning approach introduced in this paper. It is shown that with the help of the data-driven methods the difference between analytical prediction and measurement is reduced to the order of up to 2% across the operational range analyzed so far. To introduce the context of the research shown, first the underlying physics of bearing impedance is presented. Subsequently different machine learning approaches are highlighted and compared with each other in terms of their prediction quality in the results part of this paper. As a further aspect, in addition to the prediction of the bearing impedance, it is investigated whether the rotational speed present at the bearing can be predicted from the frequency spectrum of the impedance using order analysis methods which is independent from the force prediction accuracy. The background to this is that, if the prediction quality is sufficiently high, the additional use of speed sensors could be omitted in future investigations. Full article

When the Francis-type reversible pump-turbine runs under partial load, the pressure pulsation amplitude and frequency in vaneless space are high, posing a serious threat to the stability of unit operation. Water presents weak compressibility in a high-head pump-turbine, thereby affecting the amplitude–frequency characteristics of pressure pulsation. This study used numerical simulations in a model and prototype pump-turbine and particle image velocimetry (PIV) in a model pump-turbine to examine the internal flow field and pressure pulsation characteristics and determine the effect of the flow in the vaneless space on the amplitude–frequency characteristics of the pressure pulsation. The pressure pulsation amplitude–frequency characteristics were verified through prototype tests. The effects of the weak compressibility of the water on the propagation law of pressure pulsation throughout the flow passage of the prototype and model pump-turbine were roughly similar but exhibited certain differences. Considering the weak compressibility of water, the pressure pulsation fluctuations in each flow passage of the prototype and model pump-turbine exhibit varying degrees of improvement, which is more obvious at the prototype scale. Therefore, the pressure wave disturbance caused by the weak compressibility of the water has different effects on the prototype scale and model scale of the high-head Francis pump-turbine. Full article

The high-temperature superconductor (HTS) has been recognised as one of the most up-and-coming materials thanks to its superior electromagnetic performance (e.g., zero resistance). For a high-speed maglev, the HTS magnet can be the most crucial component because it is in charge of both the levitation and the propulsion of the maglev. Therefore, a fundamental study of HTS magnets for maglev is crucial. This article presents the fundamental design and modelling of the superconducting magnet for a high-speed maglev, including mechanics, electromagnetics, and loss analysis during instability. First, the measurements of the superconducting wire were performed. The HTS magnet was primarily designed and modelled to fulfil the basic electromagnetic requirements (e.g., magnetic field) in order to drive the maglev at a high speed. The modelling was verified by experimental tests on a scale-down HTS magnet. A more professional model using the H-formulation based on the finite element method (FEM) was built to further investigate some deeper physical phenomenon of the HTS magnet (e.g., current density and loss behaviours), particularly in situations where the high-speed maglev is in the normal steady state or encountering instability. Full article

An internal magnetic abrasive finishing process using a magnetic machining tool was proposed for finishing the internal surface of the thick tubes. It has been proved that this process is effective for finishing thick tubes, and it can improve the roundness while improving the roughness. However, the mechanism of improving the roundness is not clear, so it is necessary to study it theoretically. In this research, firstly, the roundness curve expression was derived using the principle of roundness measurement by the assumed center method, and the expression of roundness curve expanded by Fourier series was obtained. The influencing factors of roundness improvement were then analyzed. Secondly, the experiments were carried out on SUS304 stainless steel tubes. By confirming the mechanism analysis results and the experimental results, it was concluded that the internal magnetic abrasive finishing process using the magnetic machining tool was effective for improving the roundness of the thick tubes whose thickness is from 10 mm to 30 mm. As the thickness of the tube increased, the improvement in roundness decreased. Full article

One of the fundamental fields of research is motion planning. Mobile manipulators present a unique set of challenges for the planning algorithms, as they are usually kinematically redundant and dynamically complex owing to the different dynamic behavior of the mobile base and the manipulator. The purpose of this article is to systematically review the different planning algorithms specifically used for mobile manipulator motion planning. Depending on how the two subsystems are treated during planning, sampling-based, optimization-based, search-based, and other planning algorithms are grouped into two broad categories. Then, planning algorithms are dissected and discussed based on common components. The problem of dealing with the kinematic redundancy in calculating the goal configuration is also analyzed. While planning separately for the mobile base and the manipulator provides convenience, the results are sub-optimal. Coordinating between the mobile base and manipulator while utilizing their unique capabilities provides better solution paths. Based on the analysis, challenges faced by the current planning algorithms and future research directions are presented. Full article

Conventional lower-limb rehabilitation robots cannot provide in-time rehabilitation training for stroke patients in the acute stage due to their large size and mass as well as their complex wearing process. Aiming to solve the problems, first, a novel hybrid end-traction lower-limb rehabilitation robot (HE-LRR) was designed as the lower-limb rehabilitation requirement of patients in the acute stage, in this paper. The usage of (2-UPS + U)&(R + RPS)&(2-RR) hybrid mechanism and a mirror motion actuator had the advantages of compact structure, large working space and short wearing time to the HE-LRR. Then, the mobility of the HE-LRR was calculated and the motion property was analyzed based on screw theory. Meanwhile, the trajectory planning of the HE-LRR was carried out based on MOTOmed^® motion training. Finally, the motion capture and surface electromyography (sEMG) signal acquisition experiments in the MOTOmed motion training were performed. The foot trajectory experimental effect and the lower-limb muscle groups activation rules were studied ulteriorly. The experimental results showed that the HE-LRR achieved good kinematic accuracy and lower limb muscle groups training effect, illustrating that the HE-LRR possessed good application prospects for the lower-limb rehabilitation of patients in the acute stage. This research could also provide a theoretical basis for improving the standardization and compliance of lower-limb robot rehabilitation training. Full article

To solve the problem that fault features are difficult to extract and the time-frequency features cannot fully represent the state information, a novel method is proposed in this paper based on the whale optimization algorithm (WOA) and the kernel extreme learning machine (KELM). First, the vibration signals are processed by the ensemble empirical mode decomposition and sample entropy to obtain the feature vectors. Based on this, a KELM model for fault diagnosis is established. Then, the penalty factor and the kernel parameters in the KELM are optimized by WOA to improve the stability and classification accuracy. Taking faults of a ball-screw pair on a linear feed table as a case, the experimental results indicate that the proposed method can effectively extract the fault features of the ball-screw pair, and it can achieve higher classification accuracy, faster convergence speed, and greater convergence precision than the existing fault diagnosis methods. Full article

Hydraulic torque converter is a kind of high speed rotating machine using viscosity hydraulic oil as working medium, and its internal flow field is very complex. Thereby cavitation can occur easily in the working process, resulting in severe degradation of torque converter performance, noise, vibration and even failure. In order to reveal the effect of rotating speeds on the cavitation characteristics, a full flow passage geometry and a computational fluid dynamics (CFD) model with cavitation were developed to analyze the flow behavior in the torque converter. The results show that cavitation occurs when the speed difference between pump and turbine exceeds 1400 rpm for the basic model torque converter, which could be used as a useful indicator for the occurrence and degree of severity of flow cavitation. The increase of pump rotating speed or the decrease of speed ratio will intensify cavitation, which reduces the hydraulic transmission capacity and efficiency by over 20%, and seriously alters the shape, size, vapor volume fraction and region of cavitation bubbles. In extreme cases, more than 80% of the area on the suction side of the stator blade could be covered by cavitation bubbles. Moreover, the increase of pump rotating speed also changes the critical cavitation number and extends the cavitation range towards high speed ratio conditions not previously affected. These findings can provide guidance on how to choose the operating conditions of the hydraulic torque converter and how to improve its hydrodynamic performance and stability. Full article

Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb motor function and the daily behavior of patients with motor dysfunction. At present, the majority of upper limb rehabilitation robots can only move in the two-dimensional plane, and cannot adjust the assistance mode in real-time according to the patient’s rehabilitation needs. In this paper, according to the shortcomings of the current rehabilitation robot only moving in the two-dimensional plane, a type of bilateral mirror upper limb rehabilitation robot structure with the healthy side assisting the affected side is proposed. This can move in three-dimensional space. Additionally, an assist-as-needed (AAN) control strategy for upper limb rehabilitation training is proposed based on the bilateral upper limb rehabilitation robot. The control strategy adopts Gaussian Mixture Model (GMM) and impedance controller to maximize the patient’s rehabilitation effect. In the task’s design, there is no need to rely on the assistance of the therapist, only the patients who completed the task independently. GMM guides the rehabilitation robot to provide different assistance for the patients at different task stages and induces the patients to complete the rehabilitation training independently by judging the extent to which the patients can complete the task. Furthermore, in this paper, the effectiveness of the proposed control strategy was verified by three volunteers participating in a two-dimensional task. The experimental results show that the proposed AAN control strategy can effectively provide appropriate assistance according to the classification stage of the interaction between the patients and the rehabilitation robot, and thus, patients can better achieve the rehabilitation effect during the rehabilitation task as much as possible. Full article

Prognostics and health management (PHM) is an essential means to optimize resource allocation and improve the intelligent operation and maintenance (O&M) efficiency of marine systems and equipment (MSAE). PHM generally consists of four technical processes, namely health condition motoring (HCM), fault diagnosis (FD), health prognosis (HP), and maintenance decision (MD). In recent years, a large amount of research has been implemented in each process. However, there is not any systematic review that covers the technical framework comprehensively. This article presents a review of the framework of PHM in the marine field to fill the gap. First, the essential HCM methods, which are widely observed in the academic literature, are introduced systematically. Then, the commonly used FD approaches and their applications in MSAE are summarized, and the implementation process of intelligent methods is systematically introduced. After that, the technologies of HP have been reviewed, including the construction of health indicator (HI), health stage (HS) division, and popular remaining useful life (RUL) prediction approaches. Afterwards, the evolution of maintenance strategy in the maritime field is reviewed. Finally, the challenges of implementing PHM for intelligent ships are put forward. Full article

Gear wear is a progressive material removal process that gradually changes the tooth profile shape and dynamic mesh force, where the dynamic mesh force affects the tooth surface wear. To describe this process, a spur gear dynamic model that includes the mesh stiffness and unloaded static transmission error (STE) of the worn tooth profile is proposed for calculating the dynamic mesh force. Then, based on the finite element method (FEM), a dynamic contact analysis model that considers the dynamic mesh force is proposed for calculating the time-varying contact stress and relative sliding distance of the tooth surface mesh point. Finally, combined with the Archard wear model, a tooth wear depth calculation method that considers the worn tooth profile and the dynamic mesh force is proposed. In addition, the wear depth and dynamic characteristics under different wear times are studied. Full article