IEEE Transactions on Instrumentation and Measurement最新文献_第7页

Endogenous Noise-Expanded Multivariate Empirical Mode Decomposition and Its Application to Mechanical Compound Fault Diagnosis

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544739

Shibo Sun;Jing Yuan;Qian Zhao;Huiming Jiang;Jun Zhu

{"title":"Endogenous Noise-Expanded Multivariate Empirical Mode Decomposition and Its Application to Mechanical Compound Fault Diagnosis","authors":"Shibo Sun;Jing Yuan;Qian Zhao;Huiming Jiang;Jun Zhu","doi":"10.1109/TIM.2025.3544739","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544739","url":null,"abstract":"Mechanical compound fault diagnosis is a great challenge of current multivariate signal parallel processing methods. In response, endogenous noise-expanded multivariate empirical mode decomposition (ENMEMD) is proposed. First, cyclic attractor tensor construction by the phase space reconstruction is designed to maximize feature information saturation degree in high-order space. Second, a multivariate noise synchronous estimation strategy is established to synchronously estimate the multivariate inherent noises from original signals by high-order singular value decomposition (HOSVD) with the dispersion entropy (DE) technique. Third, an endogenous noise-expanded model is proposed for the utilization of the estimated multivariate noises to improve the input data model of multivariate empirical mode decomposition (MEMD). The model enhances the estimation accuracy of a multivariate envelope mean, which achieves the purpose of reducing mode mixing, frequency scale alignment of multivariate intrinsic mode functions (IMFs), and denoising. Eventually, all multivariate kernel IMFs are output to achieve complete fault feature extraction. The effectiveness and feasibility of ENMEMD are verified by repeatable simulations and engineering cases with various comparison methods. Particularly, tensor construction methods with different information saturation for final feature extraction effects are discussed by simulations. The results show that ENMEMD is an effective method for mechanical compound fault diagnosis.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Moment of Inertia and Load Torque Identification Based on Adaptive Extended Kalman Filter for Interior Permanent Magnet Synchronous Motors

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544728

Yanping Zhang;Zhonggang Yin;Ruijie Tang;Jing Liu

{"title":"Moment of Inertia and Load Torque Identification Based on Adaptive Extended Kalman Filter for Interior Permanent Magnet Synchronous Motors","authors":"Yanping Zhang;Zhonggang Yin;Ruijie Tang;Jing Liu","doi":"10.1109/TIM.2025.3544728","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544728","url":null,"abstract":"The moment of inertia (MI) is an essential parameter in the speed loop controller and is unknown. Manual trial-and-error tuning of the speed loop controller is unattractive due to its haphazard, lengthy, and non-optimal. And the load torque plays a vital role in improving the dynamic performance. To attack these problems, this article proposes an adaptive extended Kalman filter (AEKF) to identify the MI and load torque of the interior permanent magnet synchronous motor (IPMSM). The real-time MI identified by the proposed AEKF method is used as the input of the speed loop self-tuning PI controller to solve the impact of the change of MI on the speed loop PI controller. Additionally, the load torque identified by the proposed AEKF method is used as the torque feed-forward compensation, thereby improving the torque-boosting capability of the system and further improving the dynamic performance of the IPMSM drive system. Compared with the extended Kalman filter (EKF), the AEKF identification method shows better performance, and the effectiveness of the algorithm is validated by simulations and experiments.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A High-Generalization Variational Denoising Autoencoder for Micronewton Thrust Signal Noise Removal and Step Reconstruction

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3545169

Xingyu Chen;Liye Zhao;Jiawen Xu;Zhikang Liu;Zhuoping Dai;Luxiang Xu;Ning Guo;Hong Zhang

{"title":"A High-Generalization Variational Denoising Autoencoder for Micronewton Thrust Signal Noise Removal and Step Reconstruction","authors":"Xingyu Chen;Liye Zhao;Jiawen Xu;Zhikang Liu;Zhuoping Dai;Luxiang Xu;Ning Guo;Hong Zhang","doi":"10.1109/TIM.2025.3545169","DOIUrl":"https://doi.org/10.1109/TIM.2025.3545169","url":null,"abstract":"Removing noise and recovering the micronewton thrust signal are of great significance in high-precision static thrust measurements. Typically, the micronewton thrust signal is in the shape of a staircase signal. Existing methods have limitations in decoupling sharp step edges and flat regions from noisy signals while ensuring the accuracy of step amplitude reconstruction. In this study, we have developed a novel generative denoising method, named variational denoising autoencoder (VDAE), based on a unique deep-learning-based Bayesian framework. Specifically, the encoder-parameterized approximate posterior maps the distribution of essential features (i.e., thrust step amplitudes) of limited training samples to a latent space with a Gaussian distribution. This distribution transformation gives the latent space the ability to describe complete continuous step amplitudes. VDAE inherits the excellent generalization ability of the generative model and greatly improves the amplitude accuracy of the denoised signals. In addition, considering the different scale features in the clean staircase signal, a trend feature disentangler (TFD) is introduced in the encoder. The TFD adaptively extracts ultrahigh-frequency sharp step edge features and ultralow-frequency flat region features. Furthermore, to address the issue of recovering sharp step edges, total variation (TV) sparse representation is introduced into the loss function, guiding the decoder to reconstruct the thrust step. Extensive simulations and experiments were carried out to demonstrate the effectiveness and superiority of the proposed method in micronewton thrust step reconstruction and measurement noise removal.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143564221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Measurement and Matching Recognition Algorithm of Multiple Projectile Dispersion Positions Using a Linear Array CCD and a Sky Screen Fusion

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3545155

Hanshan Li;Xiaoqian Zhang;Junchai Gao

{"title":"A Measurement and Matching Recognition Algorithm of Multiple Projectile Dispersion Positions Using a Linear Array CCD and a Sky Screen Fusion","authors":"Hanshan Li;Xiaoqian Zhang;Junchai Gao","doi":"10.1109/TIM.2025.3545155","DOIUrl":"https://doi.org/10.1109/TIM.2025.3545155","url":null,"abstract":"To obtain the dispersion positions of multiple projectiles of multibarrel weapon with high-frequency continuous firing modes, this article proposes a new measurement method and projectile position matching recognition algorithm using a linear array CCD and a sky screen fusion and establishes a new mathematical calculation model of multiple projectile positions with four different detection screens. According to the established spatial geometry relationship of four detection screens and the time value dataset for each detection screen, we use each time value of the output signal of each detection screen to construct a time dataset of the multiple projectiles passing through the four detection screens, utilize any time combination data of the established time dataset to calculate the multiple projectile coordinates in each detection screen, and obtain the coordinate dataset, and then, based on the criterion that only one straight line will be formed when each projectile passes through the four detection screens, we use the spatiotemporal constraint relation of four detection screens to match projectile position, determine the actual coordinates of the same projectile, and obtain the real multiple projectile positions. Through testing and analysis, we verify the feasibility and test accuracy of the proposed method and the projectile position matching recognition algorithm by comparing with other test methods.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Frequency-Domain Deconvolution Adaptive Noise Cancellation DOA Estimation Algorithm Based on Matched Filtering

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544718

Yanan Geng;Wenshu Dai;Guojun Zhang;Lili Wu;Jie Zhang;Li Jia;Jiangjiang Wang;Hang Zhao;Zhengyu Bai;Zhaoxing Zhou;Yuangang Zhang;Wendong Zhang

{"title":"Frequency-Domain Deconvolution Adaptive Noise Cancellation DOA Estimation Algorithm Based on Matched Filtering","authors":"Yanan Geng;Wenshu Dai;Guojun Zhang;Lili Wu;Jie Zhang;Li Jia;Jiangjiang Wang;Hang Zhao;Zhengyu Bai;Zhaoxing Zhou;Yuangang Zhang;Wendong Zhang","doi":"10.1109/TIM.2025.3544718","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544718","url":null,"abstract":"Aiming at the problems of low azimuth estimation accuracy and wide beamwidth of single-vector hydrophone in a low signal-to-noise ratio (SNR) environment, this article proposes an azimuth estimation algorithm based on matched filter sound pressure frequency deconvolution adaptive noise cancellation (MF-FDAC). This method uses the frequency-domain output signal of each channel of the micro-electro-mechanical system (MEMS) vector hydrophone after matched filtering and finds that the two velocity components still show the sine and cosine weighting characteristics of the sound pressure propagation direction in the expression. By convoluting the frequency-domain signal and using the residual energy difference between the output of the adaptive canceller on the target azimuth and the non-target azimuth, the target azimuth is estimated. The simulation results show that the root-mean-square error (RMSE) of the proposed algorithm is about 9° and the detection probability is 0.45 when the SNR is −10 dB. The experimental results show that the maximum error of direction-of-arrival (DOA) estimation is 2° when the SNR is −7 dB. In summary, compared with conventional beam forming (CBF), multiple signal classification (MUSIC), and other algorithms, the proposed method has higher resolution, lower azimuth estimation error, and more robust azimuth estimation ability under low SNR conditions.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3-D Measurement and Reconstruction of Space Target Based on RAW Images

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544706

Yuandong Li;Qinglei Hu;Zhenchao Ouyang;Fei Dong;Dongyu Li

{"title":"3-D Measurement and Reconstruction of Space Target Based on RAW Images","authors":"Yuandong Li;Qinglei Hu;Zhenchao Ouyang;Fei Dong;Dongyu Li","doi":"10.1109/TIM.2025.3544706","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544706","url":null,"abstract":"The 3-D surface measurement and reconstruction of noncooperative targets are critical prerequisites for subsequent complex tasks such as target locking, tracking, rendezvous, docking, and landing. The space environment has a single light source and lacks atmospheric diffuse reflection effects, which makes observation challenging. Moreover, imaging modes that simulate human visual perception convert high dynamic range (HDR) RAW images into more storage-efficient standard red green blue (sRGB) formats, resulting in the loss of significant details. Therefore, neural implicit surface methods that use sRGB images often result in significant errors in such scenarios. To solve the above problems, this article proposes a 3-D surface measurement and reconstruction framework based on RAW images—RAWSurf. First, the HDR information in RAW images is used for supervision to enhance measurement and reconstruction accuracy. Moreover, to mitigate the impact of large magnitude spans of RAW images and low signal-to-noise ratio (SNR) of underexposed areas on reconstruction accuracy, a soft weight coefficient mapping is adopted. Meanwhile, use a progressive sampling (PS) strategy to ensure that the model focuses more on the spatial area. Then, by integrating three different state-of-the-art (SOTA) models with our framework, the average Chamfer distance error was reduced by 74%, the average Hausdorff distance error was reduced by 63%, and the average <inline-formula> <tex-math>$F{1}$ </tex-math></inline-formula>-score (%) was increased by 11.8. The code is publicly available at <uri>https://github.com/liyuandong145619/rawsurf</uri>.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cycloidal Gear Faults’ Detection of Industrial Robot Joint Based on IAS Signal Under Operating

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544734

Xingchao Yin;Yu Guo;Jiawei Fan;Haipeng Wang

{"title":"Cycloidal Gear Faults’ Detection of Industrial Robot Joint Based on IAS Signal Under Operating","authors":"Xingchao Yin;Yu Guo;Jiawei Fan;Haipeng Wang","doi":"10.1109/TIM.2025.3544734","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544734","url":null,"abstract":"Conventional approaches to fault detection in industrial robot joints predominantly utilize vibration sensors. However, spatial constraints and intricate wiring requirements often hinder the application and significantly escalate detection costs. Furthermore, the dynamic and nonstationary operating conditions of robot joints are characterized by directional reversals, variable speeds, and incomplete cycles. To overcome these issues, this study proposes an encoder signal-based fault detection method. The methodology encompasses several key steps: first, the separation of instantaneous angular speed (IAS) signals based on rotation direction; second, the removal of trend components and amplitude modulation effects induced by variable speeds; and third, the reconstruction of complete fault cycles from fragmented signal segments. To enhance diagnostic precision, the narrowband demodulation technique is employed to detect specific fault types, including tooth wear and tooth-root cracks, in cycloidal gears. The validity of the proposed method is substantiated through simulations and experimental evaluations.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-9"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143570820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Semi-Supervised Enhanced Fault Diagnosis Algorithm for Complex Equipment Assisted by Digital Multitwins

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544698

Sizhe Liu;Dezhi Xu;Chao Shen;Yujian Ye;Bin Jiang

{"title":"A Semi-Supervised Enhanced Fault Diagnosis Algorithm for Complex Equipment Assisted by Digital Multitwins","authors":"Sizhe Liu;Dezhi Xu;Chao Shen;Yujian Ye;Bin Jiang","doi":"10.1109/TIM.2025.3544698","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544698","url":null,"abstract":"The accuracy of fault diagnosis technology is crucial for the reliable operation of complex machinery. However, traditional diagnostic methods often rely on large amounts of labeled data, making it difficult to address the challenge of scarce labeled data in real industrial environments. To tackle this issue, this article proposes a three-stage semi-supervised fault diagnosis method that combines digital multitwins and lightweight multiscale attention (MSA) mechanisms. By leveraging digital multitwins technology, we build a triplex pump mechanism simulation model in Simscape to obtain operational data for various typical fault modes. Additionally, a deep data twin (DDT) approach is employed for self-supervised data augmentation, effectively expanding the sample space and enhancing the model’s generalization capabilities. Furthermore, we design a lightweight multiscale attention network (LMAN), which utilizes multiscale convolution and channel attention mechanisms to enhance the extraction of fault features, thereby improving diagnostic accuracy. Under the framework of a three-stage semi-supervised strategy, labeled and unlabeled data are gradually integrated to boost the accuracy of the fault diagnosis model. Experimental results demonstrate that this method exhibits excellent classification capability across different labeling ratios, achieving a significant performance improvement, particularly in scenarios with limited labeled data. This study provides an efficient semi-supervised learning solution for fault diagnosis of complex machinery, offering strong potential for industrial applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PCI Reverberation Suppression Method for Boiler Tube Leakage Based on Acoustic Signal Correlation

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3544729

Chao Wang;Qiuyu Wang;Yaran Wang;Hao Liu;Da Liu

{"title":"PCI Reverberation Suppression Method for Boiler Tube Leakage Based on Acoustic Signal Correlation","authors":"Chao Wang;Qiuyu Wang;Yaran Wang;Hao Liu;Da Liu","doi":"10.1109/TIM.2025.3544729","DOIUrl":"https://doi.org/10.1109/TIM.2025.3544729","url":null,"abstract":"The safe and economical operation of boiler units is adversely affected by boiler tube leakages, making the accurate localization of leakage points crucial. In the confined space of the boiler, the precision of time delay estimation is challenged by the interference from the superposition of boiler tube leakage sounds and reverberations, which affects the acoustic localization accuracy of leakage sources. To address this issue, the principal component inverse (PCI) method is employed to suppress the reverberation in boiler tube leakage sounds, and a PCI rank selection method based on the correlation of leakage sound signals is proposed, leveraging their similarity. The superiority of the proposed method in reverberation suppression is proved by comparing the time delay estimation results of the generalized cross-correlational (GCC) method based on the maximum likelihood (ML) weighting function, the GCC method based on the smoothed coherence transform (SCOT) weighting function, the PCI threshold method, and the PCI rank selection method based on signal correlation. The minimum and average absolute error (AE) for time delay estimation are reported as 0.014 and 0.136 ms, respectively.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-6"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143570661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analytical Modeling and Experimental Validation of Triboelectric Behavior in Kirigami Flexible Capacitive Sensors

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-02-24 DOI: 10.1109/TIM.2025.3545197

Laura Morelli;Vinicius Grando Sirtoli;Ghyslain Gagnon;Ricardo J. Zednik

{"title":"Analytical Modeling and Experimental Validation of Triboelectric Behavior in Kirigami Flexible Capacitive Sensors","authors":"Laura Morelli;Vinicius Grando Sirtoli;Ghyslain Gagnon;Ricardo J. Zednik","doi":"10.1109/TIM.2025.3545197","DOIUrl":"https://doi.org/10.1109/TIM.2025.3545197","url":null,"abstract":"Flexible capacitive sensors have attracted extensive attention in recent years, especially in their application for biomedical electrophysiological sensing, as they improve comfort and flexibility while being more robust to some types of motion artifacts (MAs). Due to their contactless nature, they are still susceptible to triboelectrification which, because of their flexibility, appears to be stronger and more unpredictable compared to their rigid counterparts. In this work, we propose a novel analytical model to predict and physically justify the triboelectric behavior of flexible capacitive sensors applied to nonflat surfaces. In particular, we consider the general case of an electrode conforming to a spherical surface, which loses contact because of a transversal motion. The model takes into account both the effect of the triboelectric voltage and the varying coupled capacitance, describing the different phases of the movement. Finally, electrical measurements were performed on the sensor, reproducing the same setup and dynamics in the laboratory. The results were compared to the analytical model and discussed: both the analytical and experimental results exhibit similar trends and voltage characteristics, with spike duration for each speed of 4.1, 2.1, and 0.9 s for the modeled effect and 4.6, 2.5, and 1.1 s for the corresponding experimental results. The presented analytical model was revealed to be accurate in describing the MAs caused by the considered motion and represents an important tool for describing and predicting similar artifacts for flexible capacitive sensors.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-8"},"PeriodicalIF":5.6,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143570824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0