Search Results (99)

Impact wrenches are widely used in construction and automotive industries, yet they generate harmful vibrations that pose health risks to operators and reduce tool usability. This paper develops a practical, low-order bond-graph model of impact-wrench dynamics that captures interactions among the motor, hammer, anvil, and hand/arm constraints, and validates it against measurements during bolt tightening into a steel plate. Predictions match measured RMS accelerations and spectral modes up to 200 Hz with a maximum relative RMS error of 11%. The analysis attributes dominant vibration sources to rotational and translational impacts between the hammer and anvil; notably, the translational (z-axis) impact contributes substantially to felt vibration while not being required for bolt tightening. The model provides physical insight into vibration origins and supports actionable design decisions, such as reducing the linear (z-axis) impact and adding rotational damping or control, consistent with standardized testing practice. Full article

Objective: Investigate alterations in the expression of specific and sensitive biomarkers of oxidative stress (OS) in blood and in nerves during hand–arm vibration syndrome (HAVS) progression. Methods: Fifty workers with vibration-induced white finger (VWF) symptoms and exposure to hand vibration were selected from a Chinese factory by judgment sampling. Fifty workers not exposed to hand vibration served as a control group. Expression of OS-related indices in blood was measured. The same method was used to select 40 workers separately for the determination of neurological indicators. Blood samples were collected from participants, and expression of indicators in plasma was measured by ELISAs. Results: The receiver operating characteristic (ROC) curves of OS-related indices and neurological indices were analyzed to assess their diagnostic sensitivity to VWF. Among OS indices, the area under the ROC curve (AUC) of malondialdehyde (MDA), superoxide dismutase (SOD), glutathione (GSH), and glutathione peroxidase (GSH-PX) was >0.9. With regard to the neurological indices, the AUC of S100β, interleukin (IL)-10, creatine kinase (CK), and growth differentiation factor (GDF)-15 was 0.7–0.9. Conclusions: MDA, SOD, GSH, GSH-PX, S100β, IL-10, CK, and GDF-15 could be diagnostic markers for VWF. Full article

In contemporary semiconductor manufacturing, wafer-handling robots are essential for achieving high-speed and high-precision wafer transportation. However, the demand for rapid motion and lightweight design introduces flexible transmission components that are prone to residual vibrations, which degrade positioning accuracy and system stability. To address this challenge, this paper proposes a vibration-suppression trajectory planning method based on the Gray Goose Optimization (GGO) algorithm. The proposed algorithm integrates grouped global search with local optimization capabilities, making it well suited for solving multi-objective optimization problems. Comparative tests conducted on eight randomly selected multimodal benchmark functions from the CEC2013 test suite verify the effectiveness and robustness of the GGO algorithm. Establishing a multi-objective function that considers both motion time and vibration energy enables the GGO algorithm to determine the switching time points of an S-shaped velocity profile, thereby generating smooth trajectories with continuous velocity and acceleration. By varying different initial conditions, the trade-off between motion time and vibration energy is systematically analyzed with respect to angular displacement, initial acceleration, and time-weighting factors. Simulation results indicate that the planned trajectories exhibit negligible displacement variation under zero-mean disturbances. The velocity error remains within 0.1 deg·s⁻¹, and the acceleration error is confined within 0.2 deg·s⁻². Consequently, Pareto-optimal solutions are successfully obtained with respect to both motion time and residual vibration energy. Full article

This paper investigates the effect of tactile feedback on the power efficiency and timing of controlling a remote robotic arm using a custom-built haptic glove. The glove integrates flex sensors to monitor finger movements and vibration motors to provide tactile feedback to the user. Communication with the robotic arm is established via the ESP-NOW protocol using an Arduino Nano ESP32 microcontroller (Arduino, Turin, Italy). This study examines the impact of tactile feedback on task performance by comparing precision, completion time, and power efficiency in object manipulation tasks with and without feedback. Experimental results demonstrate that tactile feedback significantly enhances the user’s control accuracy, reduces task execution time, and enables the user to control hand movement during object grasping scenarios precisely. It also highlights its importance in teleoperation systems. These findings have implications for improving human–robot interaction in remote manipulation scenarios, such as assistive robotics, remote surgery, and hazardous environment operations. Full article

Bone drilling is a widely encountered process in orthopedic surgeries and keyhole neuro surgeries. We are developing a sensor-integrated smart end-effector for drilling for robotic surgical applications. In manual surgeries, surgeons assess tool wear based on experience and force perception. In this work, we propose a machine-learning (ML)-based tool condition monitoring system based on multi-sensor data to preempt excessive tool wear during drilling in robotic surgery. Real-time data is acquired from the six-component force sensor of a collaborative arm along with the data from the temperature and multi-axis vibration sensor mounted on the bone specimen being drilled upon. Raw data from the sensors may have noises and outliers. Signal processing in the time- and frequency-domain are used for denoising as well as to obtain additional features to be derived from the raw sensory data. This paper addresses the challenging problem of identification of the most suitable ML algorithm and the most suitable features to be used as inputs to the algorithm. While dozens of features and innumerable machine learning and deep learning models are available, this paper addresses the problem of selecting the most relevant features, the most relevant AI models, and the optimal hyperparameters to be used in the AI model to provide accurate prediction on the tool condition. A unique framework is proposed for classifying tool wear that combines machine learning-based modeling with multi-sensor data. From the raw sensory data that contains only a handful of features, a number of additional features are derived using frequency-domain techniques and statistical measures. Using feature engineering, we arrived at a total of 60 features from time-domain, frequency-domain, and interaction-based metrics. Such additional features help in improving its predictive capabilities but make the training and prediction complicated and time-consuming. Using a sequence of techniques such as variance thresholding, correlation filtering, ANOVA F-test, and SHAP analysis, the number of features was reduced from 60 to the 4 features that will be most effective in real-time tool condition prediction. In contrast to previous studies that only examine a small number of machine learning models, our approach systematically evaluates a wide range of machine learning and deep learning architectures. The performances of 47 classical ML models and 6 deep learning (DL) architectures were analyzed using the set of the four features identified as most suitable. The Extra Trees Classifier (an ML model) and the one-dimensional Convolutional Neural Network (1D CNN) exhibited the best prediction accuracy among the models studied. Using real-time data, these models monitored the drilling tool condition in real-time to classify the tool wear into three categories of slight, moderate, and severe. Full article

Heavy-load collaborative robots are increasingly used in fields such as industrial handling and precision assembly. With the increase in the end load of the robotic arm and the acceleration of its movement speed, after the robotic arm completes a preset trajectory, due to factors such as inertia, the flexibility of the robotic arm’s rods and the harmonic reducer materials at the joints, there will still be residual vibration for a period of time after the robotic arm reaches the end point. On the one hand, residual vibration will have an adverse impact on the high-precision and high-performance operations of the robotic arm, affecting the operation accuracy and thus the production quality. On the other hand, many operations need to wait until the robotic arm completely stops before proceeding. In practical applications, the time spent waiting for the robotic arm to stop significantly affects efficiency. Therefore, effectively suppressing residual vibration is crucial to improving the performance of the robotic arm. To solve the problem of end residual vibration in heavy-load six-axis collaborative robots, this paper conducts research on input shaping and the estimation of robot end vibration parameters in arbitrary poses. The innovation is that vibration parameters in arbitrary poses are estimated based on the established vibration parameter model. An input shaper is designed according to the derived design method of the input shaper, achieving a certain suppression effect on the residual vibration of the robot end. When the parameter identification error is small, the optimized vibration suppression effect reaches more than 70%, realizing rapid and robust vibration suppression. This research is of great significance for enhancing the application value of collaborative robots in precision manufacturing and heavy-duty handling. Full article

Background: Hand–arm vibration syndrome (HAVS) is a well-recognized occupational condition resulting from prolonged exposure to hand-transmitted vibration (HTV), characterized by vascular, neurological, and musculoskeletal impairments. While vibration exposure is a known risk factor for HAVS, less is understood about the role of personal risk factors and, particularly regarding neurosensory dysfunction. This study aimed to examine the association between vibrotactile (VPT) and thermotactile perception thresholds (TPT) and individual risk factors and comorbidities in HTV-exposed workers. Methods: A total of 235 male HTV workers were evaluated between 1995 and 2005 at the University of Trieste’s Occupational Medicine Unit. Personal, occupational, and health-related data were collected, and sensory function was assessed in both hands. VPTs at 31.5 and 125 Hz and TPTs (for warm and cold) were measured on fingers innervated by the median and ulnar nerves. Results: Multivariable regression analysis revealed that impaired VPTs were significantly associated with age, higher daily vibration exposure (expressed as 8 h energy-equivalent A(8) values), BMI ≥ 25, smoking, vascular/metabolic disorders, and neurosensory symptoms. In contrast, TPTs showed weaker and less consistent associations, with some links to smoking and alcohol use. Conclusions: These findings suggest that, in addition to vibration exposure, individual factors such as aging, overweight, smoking, and underlying health conditions significantly contribute to neurosensory impairment and may exacerbate neurosensory dysfunction in a context of HAVS. The results underscore the importance of including personal health risk factors in both clinical assessment and preventive strategies for HAVS and may inform future research on its pathogenesis. Full article

The transmission of vibrations generated by high-powered machines to the hands can lead to serious health problems and various work-related difficulties for the operators. These issues result in a loss of workforce and increased operational costs due to compensation payments made to affected workers. Exposure to hand–arm vibration can be controlled through the use of vibration damping gloves. In this study, the hand–arm vibration exposure of operators using a jackhammer in three different mines was measured with and without gloves, and the vibration damping ratio of each glove was calculated. One-way analysis of variance was performed to determine the difference between the vibration damping ratios (%) obtained from three separate field measurements of 12 different gloves, and significant differences were detected. In addition, vibration exposure was measured with and without gloves for operators using a vibrating sieve set with standard vibration in a laboratory environment. From both the field and laboratory measurements, the gloves made of chloroprene rubber provide the most effective protection. Full article

Vibration can have a significant impact on long-term health, driver comfort, and vehicle performance. With a focus on steering wheel vibrations, this study examines both general and local vibrations that affect the driver. Under real-world conditions, a series of controlled test drives were conducted, with high-precision accelerometers mounted on the driver’s seat and steering wheel recording vibration data. The measurements were conducted in accordance with ISO 5349 and ISO 2631-1, which guaranteed a consistent assessment of vibration exposure. The results suggest that the daily vibration exposure for general vibrations at the driver’s seat is significantly lower than the legal limit, as evidenced by the presence of significant frequencies in the vertical (Z) axis. Nevertheless, steering wheel vibrations may cause pain due to their proximity to the resonance frequencies of the human hand–arm system, which have frequency maxima at approximately 35 Hz and harmonic 70 Hz. Additionally, the vibration intensity was elevated at vehicle velocities between 70 and 80 km/h, suggesting the potential presence of a resonance effect within the suspension or powertrain. The results emphasize the significance of advanced vibration reduction strategies in enhancing driver comfort and safety, including the implementation of a well-designed steering system and enhanced seat absorption. This research offers valuable insights for automotive engineers and ergonomics specialists who are interested in minimizing long-term health risks and vibration-induced fatigue. The aim of this study is to indicate the areas of the drive system fault that have a direct impact on the vibrations of the body structure. The article presents an analysis of the recorded vibration results based on which of the areas of change in the comfort of using the vehicle were selected. Full article

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) and harvesting without winch assistance (NTW), a field study using a Ponsse Scorpion King harvester and an Ecoforst T-winch traction winch was conducted. Vibrations were measured at three locations inside the cabin (seat, seat base/floor, control lever), while noise exposure was recorded both inside and outside the cabin. WBV exposure during work time operations was highest in the Y-direction, both on the seat (0.49–0.87 m/s²) and on the floor (0.41–0.84 m/s²). The WBV and HAV exposure levels were highest while driving on the forest and skid road. Exposure during the main productive time was significantly influenced by the harvesting system, diameter at breast height (DBH), and tree species. Noise exposure was higher, while WBV and HAV exposures on the seat, floor and control lever were lower during non-work time than during work time. The daily vibration exposure on the seat exceeded the EU action value, while LC_peak noise exposure surpassed the limit value of 140 dB(C) on all measured days. Noise and vibration exposure were constantly higher during TW than NTW harvesting but differences were small. Compared to other studies, the results show that harvesting on steep terrain increases noise and vibration exposure, while non-work time has the opposite effect on vibration and noise exposure. Full article

Ensuring comfort in light mobility is a crucial aspect for supporting individuals’ well-being and safety while driving scooters, riding bicycles, etc. In fact, factors such as the hand grip on the handlebar, positions of the wrist and arm, overall body posture, and affecting vibrations play key roles. Wearable systems offer the ability to noninvasively monitor physiological parameters, such as body temperature and heart rate, aiding in personalized comfort assessment. In this context, user positions while driving or riding are, on the other hand, more challenging to monitor ecologically. Developing effective smart gloves as a support for comfort and movement monitoring introduces technical complexities, particularly in sensor selection and integration. Light and flexible sensors can help in this regard by ensuring reliable sensing and thus addressing the optimization of the comfort for the driver. In this work, a novel wireless smart glove is proposed, integrating four bend sensors, four force-sensitive sensors, and one inertial measurement unit for measuring the finger movements, hand orientation, and the contact force exerted by the hand while grasping the handlebar during driving or riding. The smart glove has been proven to be repeatable (1.7%) and effective, distinguishing between different grasped objects, such as a flask, a handlebar, a tennis ball, and a small box. Additionally, it proved to be a valuable tool for monitoring specific actions while riding bicycles, such as braking, and for optimizing the posture during the ride. Full article

This paper presents research on the impact of vibrations on the hand–arm and body system of agricultural tractor operators as ergonomic indicators in relation to certain operational parameters. The measurements were conducted on a LANDINI POWERFARM 100 tractor on agricultural production areas and access roads of the Agricultural and Veterinary School in Osijek. The measurements followed the ISO 5008:2015 standard, which describes the creation of test tracks: a smooth track of 100 m in length and a rough track of 35 m in length. Body vibration measurements were conducted according to the prescribed standards HRN ISO 2631-1: 1999/A1:2019 and HRN ISO 2631-4:2010. Hand–arm system vibration measurements were performed according to the prescribed standards HRN ISO 5349-1:2008 and HRN ISO 5349-2:2008/A1:2015. After the measured data were processed, a three-factor analysis of variance was performed, where some operational parameters were designated as A—agrotechnical surfaces (6 types), B—tractor speed (6 speeds), and C—tire air pressure (3 pressures), along with multiple regression analysis and the AHP (analytical hierarchical process). This research determined that none of the measured hand–arm system vibrations exceeded the warning (2.5 ms⁻²) or limit (5 ms⁻²) values of daily exposure. Furthermore, vibrations affecting the operator’s body in the x-axis at higher speeds and pressures C2 and C3, in the y-axis at higher speeds and pressures C1 and C2, and in the z-axis at the highest speed and pressures C1 and C2 were found to exceed the daily exposure warning value of 0.5 ms⁻². It was concluded that the operator’s health is at risk, and it is recommended that the seat’s air suspension system be inspected to prevent further complications in a timely manner. Full article

To quantify the effect of frequency-range-specific hand–arm vibration (FRS-HAV) exposure on the risk of musculoskeletal disorders of the upper limb (UMSDs), we performed an analysis among the study sample of the German Hand–Arm Vibration Study. In total, 206 cases and 609 controls were included in this analysis. Cases were new patients with UMSDs. Controls were a random sample of people with compensable occupational injuries. Standardized personal interviews were performed among cases and controls. In addition to leisure activities and comorbidities, detailed work histories were obtained from all participants. To quantify FRS-HAV exposures, a database of vibration measurements of over 700 power tools was used. This database allows detailed quantification of vibration exposure over long periods of time. A dose–response relationship between FRS-HAV exposure and UMSDs was quantified using conditional logistic regression analyses. After adjustment for relevant confounders, consistent and statistically significant exposure–response relationships were observed between cumulative vibration exposure and UMSDs. The effect of vibration exposure on the risk of UMSDs is mainly concentrated in the frequency range ≤ 50 Hz. This suggests that the current ISO frequency-weighting curve for quantifying hand–arm vibration exposure is reasonable and can be used for vibration-related risk assessment, especially for musculoskeletal disorders. Full article

This paper aims to review researchers’ concerns over time (from the 1980s to the present) regarding the transmission of mechanical vibrations in the workplace to the limbs, with a preponderant focus on the hand–arm system and some of the effects over time. These concerns are strictly approached from the point of view of their effects on different races, types of jobs, and forms of tools handled in the workplace. In this regard, when we refer to unwanted vibrations (harmful to a person) in the industrial environment, these are vibrations that can produce harmful effects on an individual’s health, leading to occupational diseases such as white finger syndrome. Some of the terms specific to the studies reviewed, such as vibration perception and biodynamic force, among others, are explained in this paper as needed. Studies in the field have shown that vibrations are transmitted differently when the arm is bent at the elbow joint compared to when it is outstretched; also, the transmission of vibrations is influenced by other factors, such as the temperature of the working environment, the gender and age of the person who is using the vibrating devices, and last but not least, the time of their use and the frequency. The conclusions presented by the specialized literature often refer to existing standards, in particular SR EN ISO 5349/2003. Finally, in this paper, conclusions are drawn regarding how to analyze the transmission of vibrations over time, and some recommendations are given for avoiding or minimizing them, which can be added to the already-existing standards. Full article

This study investigated muscle activation, shocks, and vibrations of the upper extremities during tennis serves between junior and adult tennis players. Thirty-five well-trained tennis players (15 juniors and 20 adults) performed 10 maximal successful tennis serves. Two triaxial accelerometers recorded the shock and vibration on the racket and the hand on the dominant side. Eight surface EMG electrodes were also used to measure the arm muscles’ activities. Linear mixed models were used to test the fixed effect of age on muscular activation and vibration. Statistical non-Parametric Mapping was employed to make statistical inferences on the EMG and accelerometer data obtained from the continuous wavelet transform. Comparing EMG parameters between junior and adult players reveals similar upper limb intermuscular coordination. The junior players experienced lower racket and hand vibration amplitudes, which were partially explained by a lower ball velocity. This study revealed that young players showed no difference in EMG parameters in the tennis serve but were as exposed to shocks and vibrations as adults when compared based on a given speed and a given handgrip force. These vibrations apply to an immature skeleton, which can increase the risk of injuries caused by overuse. In addition, differences in the racket vibration frequency provide original knowledge to engineers who need to develop innovative sports equipment for tennis. Full article