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Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 19192

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Special Issue Editors

Prof. Dr. Yanlong Cao

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Guest Editor

School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
Interests: precision analysis and control; visual measurement; intelligent equipment and intelligent manufacturing

Prof. Dr. Nabil Anwer

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Guest Editor

Automated Production Research Laboratory, Paris-Saclay University, Ecole Normale Supérieure Paris-Saclay, 91400 Gif-sur-Yvette, France
Interests: digital twin; visual measurement; intelligent manufacturing
Special Issues, Collections and Topics in MDPI journals

Dr. Feng Gao

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Guest Editor

Department of Engineering and Technology, University of Huddersfield, Huddersfield HD1 3DH, UK
Interests: metrology; applied optics; measurement and instrumentation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the result of the deep integration of advanced manufacturing and information technology, intelligent manufacturing has become the development trend in the manufacturing industry. Precision analysis and measurement are important parts of intelligent manufacturing, which play an irreplaceable role in improving the quality of high-end equipment manufacturing and a decisive role in the quality control of the whole manufacturing process. Effective precision analysis and measurement must rely on high-efficiency and high-precision sensor technology. With the transformation of the traditional manufacturing production mode, sensors are also developing in the direction of precision, integration, and intelligence. Multimodal sensors can automatically analyze and synthesize the information and data from multiple sensors or different sources under certain criteria and output the required conclusions and signals. They can overcome the limitation of incomplete information of a single sensor and effectively improve the accuracy of precision analysis and measurement results. At present, multimodal sensors technology is attracting the interest of various researchers in the field. The topics of this Special Issue include but are not limited to the above research fields. All research articles on multimodal-sensors-based precision analysis and measurement in intelligent manufacturing will be appreciated.

Prof. Dr. Yanlong Cao
Prof. Dr. Nabil Anwer
Dr. Feng Gao
Guest Editors

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Keywords

intelligent manufacturing
precision analysis
measurement
multi-modal sensors
sensor fusion

Published Papers (7 papers)

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Research

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15 pages, 2808 KiB

Open AccessArticle

Evaluation of the Properties of Eddy Current Sensors Based on Their Equivalent Parameters

by Leszek Dziczkowski and Grzegorz Tytko

Sensors 2023, 23(6), 3267; https://doi.org/10.3390/s23063267 - 20 Mar 2023

Cited by 4 | Viewed by 1322

Abstract

This paper presents a practical way of using the method of evaluating the metrological properties of eddy current sensors. The idea of the proposed approach consists of employing a mathematical model of an ideal filamentary coil to determine equivalent parameters of the sensor and sensitivity coefficients of tested physical quantities. These parameters were determined on the basis of the measured value of the real sensor’s impedance. The measurements were carried out with an air-core sensor and an I-core sensor while they were positioned at different distances from the surface of tested copper and bronze plates. An analysis of the influence of the coil’s position in relation to the I core on the equivalent parameters was also carried out, and the interpretation of the results obtained for various sensor configurations was presented in a graphical form. When equivalent parameters and sensitivity coefficients of examined physical quantities are known, it is possible to compare even very different sensors with the employment of one measure. The proposed approach makes it possible to make a significant simplification of the mechanisms of calibration of conductometers and defectoscopes, computer simulation of eddy current tests, creating the scale of a measuring device, and designing sensors. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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21 pages, 5736 KiB

Open AccessArticle

Real-Time Laser Interference Detection of Mechanical Targets Using a 4R Manipulator

by Tingrui Liu, Zhongwei Ji, Yan Ding and Youfeng Zhu

Sensors 2023, 23(5), 2794; https://doi.org/10.3390/s23052794 - 3 Mar 2023

Cited by 1 | Viewed by 1402

Abstract

In this study, a laser interferometric sensing measurement (ISM) system based on a 4R manipulator system is developed to achieve detection of mechanical targets, which aims to realize the real-time, online detection of workpieces with high precision during processing. The 4R mobile manipulator (MM) system is flexible and can move in the workshop, aiming to preliminarily track the position of the workpiece to be measured and locate it at millimeter level. The reference plane of the ISM system is driven by piezoelectric ceramics with the spatial carrier frequency realized and the interferogram obtained by a charge coupled device (CCD) image sensor. The subsequent processing of the interferogram includes fast Fourier transform (FFT), spectrum filtering, phase demodulation, tilt elimination for wave-surface, etc., so as to further restore the surface shape of the measured surface and obtain the surface quality indexes. A novel cosine banded cylindrical (CBC) filter is used to improve the FFT processing accuracy, and a bidirectional extrapolation and interpolation (BEI) technique is proposed for the preprocessing operation of real-time interferograms before FFT processing. Compared with the results from a ZYGO interferometer, the real-time online detection results show the reliability and practicability of this design. The relative error of peak–valley value reflecting the processing accuracy can reach about 0.63%, with the root-mean-square value reaching about 1.36%. Some possible applications of this work include the surface of mechanical parts in the process of online machining, the end face of shaft-like structures, annular surfaces, etc. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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19 pages, 2129 KiB

Open AccessArticle

Research on Vibration Amplitude of Ultra-Precision Aerostatic Motorized Spindle under the Combined Action of Rotor Unbalance and Hydrodynamic Effect

by Wenbo Wang, Pengyun Song, Hechun Yu and Guoqing Zhang

Sensors 2023, 23(1), 496; https://doi.org/10.3390/s23010496 - 2 Jan 2023

Cited by 1 | Viewed by 1163

Abstract

In the working process of the gas bearings, the unbalanced force of the rotor will increase nonlinearly with the increase in the rotating speed, resulting in an increase in the rotor’s vibration amplitude. On the other hand, with the increase in the rotating speed, the hydrodynamic effect will increase, and the nonlinear increase in the gas film force and stiffness will inhibit the increase in the vibration amplitude. In order to deeply study the influence of the unbalanced force and nonlinear gas film force on the vibration amplitude of the ultra-precision aerostatic motorized spindle, taking the double slit throttling gas bearing as an example, according to the equilibrium equation of the rotor under the combined action of gravity, the gas film force, and the unbalanced force, a calculation program based on the finite difference method for solving the rotor’s equilibrium position is completed. The calculation results show that: the hydrodynamic effect can significantly increase the bearing capacity and cause the change of the static equilibrium position of the rotor, but the offset amplitude of the static equilibrium position of the rotor gradually slows down with the increase in the rotating speed. The hydrodynamic effect improves the stiffness near the static equilibrium position of the rotor, making the rotor vibration track tend to be more “round”. Although the unbalanced force of the rotor increases nonlinearly as the rotating speed increases, the maximum offset between the dynamic equilibrium position and the static equilibrium position of the rotor under the action of the rotating unbalanced force is approximately linear with the rotating speed. Compared with the air supply pressure, the rotor unbalance and rotating speed are the main factors affecting the rotor dynamic equilibrium position offset. This study has a reference role in the in-depth study of the influence of rotating speed and rotor unbalance on the rotor static equilibrium position and dynamic equilibrium position offset, as well as in the design of gas bearings and the prediction of rotor vibration amplitude. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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26 pages, 12895 KiB

Open AccessArticle

Metrology Benchmarking of 3D Scanning Sensors Using a Ceramic GD&T-Based Artefact

by Eduardo Cuesta, Víctor Meana, Braulio J. Álvarez, Sara Giganto and Susana Martínez-Pellitero

Sensors 2022, 22(22), 8596; https://doi.org/10.3390/s22228596 - 8 Nov 2022

Cited by 2 | Viewed by 2178

Abstract

The use of non-contact scanning equipment in metrology and in dimensional and geometric inspection applications is increasing due to its ease of use, the speed and density of scans, and the current costs. In fact, these technologies are becoming increasingly dominant in the industrial environment, thus moving from reverse engineering applications to metrological applications. However, this planned transfer requires actions to ensure the achievable accuracy by providing traceability of measurements. In the present study, a comparison between the devices is carried out and a specific standard artefact is designed, equipped with multiple ceramic optically friendly entities, and allowing a wide variety of geometric dimensioning and tolerancing (GD&T). Four different 3D scanning sensors are used in the experimentation. Three of them are based on laser triangulation, and the fourth is a structured blue light sensor (fringe pattern projection). The standard artefact is calibrated with a high accuracy, using a coordinate measuring machine (CMM) and probing sensors. With this CMM, reference values of multiple predefined GD&T are obtained. The evaluation methodology maximises the accuracy of each device in measuring the dimensions of the artefact due to the good dimensional (milling and turning), surface (control of machining variables), and the dimensional and spatial distribution characteristics. The procedure also includes the same treatment of the captured point clouds (trimming, filtering, and best-fit algorithm, etc.) in each of the four 3D scanning sensors considered. From this process, very reliable measurements of the maximum achievable accuracy of each device (deviations from the CMM measurements) are finally obtained, and a multi-characteristic comparison between the four sensors is performed, also with high reliability. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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17 pages, 11311 KiB

Open AccessArticle

Photometric-Stereo-Based Defect Detection System for Metal Parts

by Yanlong Cao, Binjie Ding, Jingxi Chen, Wenyuan Liu, Pengning Guo, Liuyi Huang and Jiangxin Yang

Sensors 2022, 22(21), 8374; https://doi.org/10.3390/s22218374 - 1 Nov 2022

Cited by 8 | Viewed by 2293

Abstract

Automated inspection technology based on computer vision is now widely used in the manufacturing industry with high speed and accuracy. However, metal parts always appear in high gloss or shadow on the surface, resulting in the overexposure of the captured images. It is necessary to adjust the light direction and view to keep defects out of overexposure and shadow areas. However, it is too tedious to adjust the position of the light direction and view the variety of parts’ geometries. To address this problem, we design a photometric-stereo-based defect detection system (PSBDDS), which combines the photometric stereo with defect detection to eliminate the interference of highlights and shadows. Based on the PSBDDS, we introduce a photometric-stereo-based defect detection framework, which takes images captured in multiple directional lights as input and obtains the normal map through the photometric stereo model. Then, the detection model uses the normal map as input to locate and classify defects. Existing learning-based photometric stereo methods and defect detection methods have achieved good performance in their respective fields. However, photometric stereo datasets and defect detection datasets are not sufficient for training and testing photometric-stereo-based defect detection methods, thus we create a photometric stereo defect detection (PSDD) dataset using our PSBDDS to eliminate gaps between learning-based photometric stereo and defect detection methods. Furthermore, experimental results prove the effectiveness of the proposed PSBBD and PSDD dataset. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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17 pages, 5089 KiB

Open AccessArticle

Multi-Sensor Image Fusion Method for Defect Detection in Powder Bed Fusion

by Xing Peng, Lingbao Kong, Wei Han and Shixiang Wang

Sensors 2022, 22(20), 8023; https://doi.org/10.3390/s22208023 - 20 Oct 2022

Cited by 2 | Viewed by 1809

Abstract

Multi-sensor defect detection technology is a research hotspot for monitoring the powder bed fusion (PBF) processes, of which the quality of the captured defect images and the detection capability is the vital issue. Thus, in this study, we utilize visible information as well as infrared imaging to detect the defects in PBF parts that conventional optical inspection technologies cannot easily detect. A multi-source image acquisition system was designed to simultaneously acquire brightness intensity and infrared intensity. Then, a multi-sensor image fusion method based on finite discrete shearlet transform (FDST), multi-scale sequential toggle operator (MSSTO), and an improved pulse-coupled neural networks (PCNN) framework were proposed to fuse information in the visible and infrared spectra to detect defects in challenging conditions. The image fusion performance of the proposed method was evaluated with different indices and compared with other fusion algorithms. The experimental results show that the proposed method achieves satisfactory performance in terms of the averaged information entropy, average gradient, spatial frequency, standard deviation, peak signal-to-noise ratio, and structural similarity, which are 7.979, 0.0405, 29.836, 76.454, 20.078 and 0.748, respectively. Furthermore, the comparison experiments indicate that the proposed method can effectively improve image contrast and richness, enhance the display of image edge contour and texture information, and also retain and fuse the main information in the source image. The research provides a potential solution for defect information fusion and characterization analysis in multi-sensor detection systems in the PBF process. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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Review

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20 pages, 1459 KiB

Open AccessReview

Intelligent Manufacturing Technology in the Steel Industry of China: A Review

by Dongdong Zhou, Ke Xu, Zhimin Lv, Jianhong Yang, Min Li, Fei He and Gang Xu

Sensors 2022, 22(21), 8194; https://doi.org/10.3390/s22218194 - 26 Oct 2022

Cited by 19 | Viewed by 8129

Abstract

Intelligent manufacturing, defined as the integration of manufacturing with modern information technologies such as 5G, digitalization, networking, and intelligence, has grown in popularity as a means of boosting the productivity, intelligence, and flexibility of traditional manufacturing processes. The steel industry is a necessary support for modern life and economic development, and the Chinese steel industry’s capacity has expanded to roughly half of global production. However, the Chinese steel industry is now confronted with high labor costs, massive carbon emissions, a low level of intelligence, low production efficiency, and unstable quality control. Therefore, China’s steel industry has launched several large-scale intelligent manufacturing initiatives to improve production efficiency, product quality, manual labor intensity, and employee working conditions. Unfortunately, there is no comprehensive overview of intelligent manufacturing in China’s steel industry. We began this research by summarizing the construction goals and overall framework for intelligent manufacturing of the steel industry in China. Following that, we offered a brief review of intelligent manufacturing for China’s steel industry, as well as descriptions of two typical intelligent manufacturing models. Finally, some major technologies employed for intelligent production in China’s steel industry were introduced. This research not only helps to comprehend the development model, essential technologies, and construction techniques of intelligent manufacturing in China’s steel industry, but it also provides vital inspiration for the manufacturing industry’s digital and intelligence updates and quality improvement. Full article

(This article belongs to the Special Issue Multi-Modal Sensors-Based Precision Analysis and Measurement in Intelligent Manufacturing)

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