Pub Date : 2026-02-11DOI: 10.1016/j.ymssp.2026.114004
Casper Aaskov Drangsfeldt, Luis David Avendaño-Valencia, Marie Lützen
{"title":"A sequential bayesian operational mode classification for SHM under discrete operational variability","authors":"Casper Aaskov Drangsfeldt, Luis David Avendaño-Valencia, Marie Lützen","doi":"10.1016/j.ymssp.2026.114004","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.114004","url":null,"abstract":"","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"207 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-11DOI: 10.1016/j.ymssp.2026.113988
Chenshuo Xie, Huijie Li, Yejun Zhu, Maohua Xiao, Dongfang Li, Ze Liu
{"title":"Dual-loop control system of composite motion parameters for a self-excited vibratory rotary tiller blade oriented to tillage depth fluctuation suppression","authors":"Chenshuo Xie, Huijie Li, Yejun Zhu, Maohua Xiao, Dongfang Li, Ze Liu","doi":"10.1016/j.ymssp.2026.113988","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113988","url":null,"abstract":"","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"32 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vibration isolation systems for ultra-precision instruments are strongly influenced by internal resonances, leading to an increase in vibration transmissibility of up to 10–30 dB at the resonance frequencies. The dual-chamber air-floating vibration isolation system exhibits an extremely low natural frequency. However, the presence of the expansion chamber introduces internal resonance problems at mid-to-high frequencies. To enhance the vibration isolation performance of the dual-chamber air-floated isolation system, this paper proposes an adaptive control strategy tailored to such systems to address internal resonance beyond the natural frequency. The dual-chamber air-floated isolation system is accurately modeled and systematically analyzed in this paper. The results reveal that the fundamental cause of internal resonance in the dual-chamber isolation system is Helmholtz resonance. To address this issue, a novel orthogonal basis function infinite impulse response (OBF-IIR) controller is designed in this paper to efficiently compensate for vibrations induced by the dual-chamber Helmholtz resonance effect. On this basis, a fast, accurate online adaptive algorithm is developed to update the controller zeros in real time, enabling adaptive, synchronous compensation of internal resonances in the dual-chamber isolation system. The proposed OBF-IIR controller not only suppresses internal resonances induced by the spring–damper model and the dual-chamber Helmholtz resonance effect, but also compensates for resonances arising from other sources. The proposed adaptive control strategy demonstrates faster convergence and higher accuracy, reducing the vibration transmissibility of the isolation system by 10–30 dB in the 2–100 Hz range and decreasing the cumulative power spectral density at 100 Hz by 23.8%–84.9%.
{"title":"Ultra-low frequency air flotation vibration isolation system with a dual-chamber structure using adaptive control strategy","authors":"Tianyi Li, Shilong Guo, Zhendong Lan, Bo Zhao, Jiubin Tan, Chenglong Yu","doi":"10.1016/j.ymssp.2026.113987","DOIUrl":"10.1016/j.ymssp.2026.113987","url":null,"abstract":"<div><div>Vibration isolation systems for ultra-precision instruments are strongly influenced by internal resonances, leading to an increase in vibration transmissibility of up to 10–30 dB at the resonance frequencies. The dual-chamber air-floating vibration isolation system exhibits an extremely low natural frequency. However, the presence of the expansion chamber introduces internal resonance problems at mid-to-high frequencies. To enhance the vibration isolation performance of the dual-chamber air-floated isolation system, this paper proposes an adaptive control strategy tailored to such systems to address internal resonance beyond the natural frequency. The dual-chamber air-floated isolation system is accurately modeled and systematically analyzed in this paper. The results reveal that the fundamental cause of internal resonance in the dual-chamber isolation system is Helmholtz resonance. To address this issue, a novel orthogonal basis function infinite impulse response (OBF-IIR) controller is designed in this paper to efficiently compensate for vibrations induced by the dual-chamber Helmholtz resonance effect. On this basis, a fast, accurate online adaptive algorithm is developed to update the controller zeros in real time, enabling adaptive, synchronous compensation of internal resonances in the dual-chamber isolation system. The proposed OBF-IIR controller not only suppresses internal resonances induced by the spring–damper model and the dual-chamber Helmholtz resonance effect, but also compensates for resonances arising from other sources. The proposed adaptive control strategy demonstrates faster convergence and higher accuracy, reducing the vibration transmissibility of the isolation system by 10–30 dB in the 2–100 Hz range and decreasing the cumulative power spectral density at 100 Hz by 23.8%–84.9%.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"248 ","pages":"Article 113987"},"PeriodicalIF":8.9,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146147125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-10DOI: 10.1016/j.ymssp.2026.113984
Xiaowei Zhang, Xiaopeng Wang, Yingrui Ye
Symmetry is commonly used in engineering design for its simplicity and structural stability. Conventional locally resonant metastructures with strict spatial symmetry exhibit only one active mode, limiting modal diversity and dynamic performance. To overcome this constraint, we introduce spatial stiffness asymmetry, enabling three-dimensional dynamic responses. Such asymmetric design induces coupling between translational and rotational degrees of freedom, allowing multiple resonant modes to be excited by a single-directional input. Leveraging this mechanism, we design a metastructure that achieves vertical vibration isolation through three distinct coupled modes generated by a single resonator. A theoretical model is developed to describe the asymmetric self-coupling behavior, and vibration-table experiments confirm the predicted multi-band isolation performance. This work provides a new strategy for enhancing modal utilization in resonant systems and offers practical guidance for compact, multi-band vibration control.
{"title":"Asymmetric design enables self-coupled locally resonant metastructure for multi-modal vibration isolation","authors":"Xiaowei Zhang, Xiaopeng Wang, Yingrui Ye","doi":"10.1016/j.ymssp.2026.113984","DOIUrl":"10.1016/j.ymssp.2026.113984","url":null,"abstract":"<div><div>Symmetry is commonly used in engineering design for its simplicity and structural stability. Conventional locally resonant metastructures with strict spatial symmetry exhibit only one active mode, limiting modal diversity and dynamic performance. To overcome this constraint, we introduce spatial stiffness asymmetry, enabling three-dimensional dynamic responses. Such asymmetric design induces coupling between translational and rotational degrees of freedom, allowing multiple resonant modes to be excited by a single-directional input. Leveraging this mechanism, we design a metastructure that achieves vertical vibration isolation through three distinct coupled modes generated by a single resonator. A theoretical model is developed to describe the asymmetric self-coupling behavior, and vibration-table experiments confirm the predicted multi-band isolation performance. This work provides a new strategy for enhancing modal utilization in resonant systems and offers practical guidance for compact, multi-band vibration control.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"248 ","pages":"Article 113984"},"PeriodicalIF":8.9,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.ymssp.2026.113964
Weijia Liu, Changhai Zhai, Weiping Wen, Kun Liu
Traditional structural health monitoring relies on sensor deployment but is constrained by high installation costs, insufficient monitoring network coverage, and noise interference in complex seismic scenarios, limiting its application. Leveraging existing surveillance cameras in buildings for non-contact monitoring emerges as a promising solution. This study proposes a finite element model updating method integrating computer vision with time-domain signal autocorrelation sensitivity. This method deeply integrates visual displacement data from surveillance videos with structural mechanics models, employing the autocorrelation function of time-domain signals for effective noise reduction. It enhances the identification of local stiffness changes, thereby significantly improving the accuracy and robustness of model updating. This study first conducts model updating through numerical simulation methods. The displacement autocorrelation sensitivity method is employed, systematically accounting for measured response noise, seismic motion noise, and uncertainties in seismic motion (including spectral characteristics, duration, and peak ground acceleration). Numerical simulation results demonstrate that, under structural response and seismic motion noise conditions with a signal-to-noise ratio (SNR) as low as 20 dB, the displacement autocorrelation sensitivity method achieves a parameter updating error within 5%, validating its high adaptability and robustness in complex disturbance environments. For far-field non-impulsive seismic motions, the displacement autocorrelation sensitivity method exhibits higher precision and stability compared to traditional displacement sensitivity methods. For engineering feasibility assessment, shaking table tests were conducted on a three-story steel frame, integrating displacement time histories from indoor/outdoor camera videos with ground motion data from IMU sensors for model updating. Test results show Pearson correlation coefficients of 0.91, 0.94, and 0.97 for displacement time history predictions versus measured values from the top to the first story, with peak displacement relative errors below 6% for all stories. This method can efficiently utilize existing building surveillance videos to complete model updates within minutes in post-earthquake environment, providing reliable support for damage assessment and emergency response.
{"title":"Model updating method based on computer vision and autocorrelation sensitivity: Deep integration of visual information and physical mechanisms","authors":"Weijia Liu, Changhai Zhai, Weiping Wen, Kun Liu","doi":"10.1016/j.ymssp.2026.113964","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113964","url":null,"abstract":"Traditional structural health monitoring relies on sensor deployment but is constrained by high installation costs, insufficient monitoring network coverage, and noise interference in complex seismic scenarios, limiting its application. Leveraging existing surveillance cameras in buildings for non-contact monitoring emerges as a promising solution. This study proposes a finite element model updating method integrating computer vision with time-domain signal autocorrelation sensitivity. This method deeply integrates visual displacement data from surveillance videos with structural mechanics models, employing the autocorrelation function of time-domain signals for effective noise reduction. It enhances the identification of local stiffness changes, thereby significantly improving the accuracy and robustness of model updating. This study first conducts model updating through numerical simulation methods. The displacement autocorrelation sensitivity method is employed, systematically accounting for measured response noise, seismic motion noise, and uncertainties in seismic motion (including spectral characteristics, duration, and peak ground acceleration). Numerical simulation results demonstrate that, under structural response and seismic motion noise conditions with a signal-to-noise ratio (SNR) as low as 20 dB, the displacement autocorrelation sensitivity method achieves a parameter updating error within 5%, validating its high adaptability and robustness in complex disturbance environments. For far-field non-impulsive seismic motions, the displacement autocorrelation sensitivity method exhibits higher precision and stability compared to traditional displacement sensitivity methods. For engineering feasibility assessment, shaking table tests were conducted on a three-story steel frame, integrating displacement time histories from indoor/outdoor camera videos with ground motion data from IMU sensors for model updating. Test results show Pearson correlation coefficients of 0.91, 0.94, and 0.97 for displacement time history predictions versus measured values from the top to the first story, with peak displacement relative errors below 6% for all stories. This method can efficiently utilize existing building surveillance videos to complete model updates within minutes in post-earthquake environment, providing reliable support for damage assessment and emergency response.","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"45 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.ymssp.2026.113977
Lubing Wang, Ying Chen, Zhengbo Zhu, Xufeng Zhao
In prognostics and health management for mechanical systems, the uncertainty of remaining useful life (RUL) assessment caused by noise interference and measurement errors is often overlooked, which may lead to inaccurate maintenance results. To solve these challenges, this study presents a predictive maintenance framework that integrates uncertainty-aware RUL estimation to support maintenance decisions and spare parts management. We first introduce a hybrid model that combines bidirectional gated recurrent units with an integrated global and local multi-head sparse attention mechanism to capture long-term dependencies and transient patterns, while employing Monte Carlo dropout for quantifying RUL uncertainty. Using RUL uncertainty estimation, three distinct predictive maintenance models and spare parts ordering models are formulated. These models integrate estimated mean RUL, lower bounds, and maintenance costs to dynamically determine the optimal maintenance time and spare parts ordering time during periodic inspections. Validated on aero-engine and industrial machine datasets, the method outperforms existing strategies, achieving effective fault prevention and reducing the maintenance cost rate by over 50%. This work provides a practical solution for reliable and cost-effective mechanical systems by linking uncertainty-aware RUL estimation with maintenance decisions.
{"title":"Dynamic predictive maintenance framework for mechanical systems via uncertainty-aware RUL estimation","authors":"Lubing Wang, Ying Chen, Zhengbo Zhu, Xufeng Zhao","doi":"10.1016/j.ymssp.2026.113977","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113977","url":null,"abstract":"In prognostics and health management for mechanical systems, the uncertainty of remaining useful life (RUL) assessment caused by noise interference and measurement errors is often overlooked, which may lead to inaccurate maintenance results. To solve these challenges, this study presents a predictive maintenance framework that integrates uncertainty-aware RUL estimation to support maintenance decisions and spare parts management. We first introduce a hybrid model that combines bidirectional gated recurrent units with an integrated global and local multi-head sparse attention mechanism to capture long-term dependencies and transient patterns, while employing Monte Carlo dropout for quantifying RUL uncertainty. Using RUL uncertainty estimation, three distinct predictive maintenance models and spare parts ordering models are formulated. These models integrate estimated mean RUL, lower bounds, and maintenance costs to dynamically determine the optimal maintenance time and spare parts ordering time during periodic inspections. Validated on aero-engine and industrial machine datasets, the method outperforms existing strategies, achieving effective fault prevention and reducing the maintenance cost rate by over 50%. This work provides a practical solution for reliable and cost-effective mechanical systems by linking uncertainty-aware RUL estimation with maintenance decisions.","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"6 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.ymssp.2026.113928
Ye Lu, Xiaomei Li, Zhijiang Xie, Haolan Jia, Zhenjun Su, Xiaoliang Hu
To investigate the coupling effects of clearance and flexible components on dynamic performance of pushrod-driven actuator, this study proposes a hybrid contact force model suitable for large loads with an adaptive restitution coefficient, and a modified transitional lubrication force model. Considering the influence of flexible components, a rigid-flexible coupling dynamics model of the actuator incorporating lubrication clearance is established. Subsequently, effects of clearance size, driving speed, dynamic viscosity and load on system’s dynamics and chaos are then analyzed. Finally, experimental validation confirms the model’s effectiveness. The results show that the choice of clearance size and drive speed significantly influences system stability, and that high dynamic viscosity lubricants can lower the output vibration frequency and amplitude. Under large loads, the lubricant film thickness at clearance approaches zero, intensifying clearance collisions and wear. This increases the output vibration frequency, and substantially reduces the lubricant’s mitigating effects on clearance and flexible factors. This study provides theoretical support for the design of high-performance rudder actuators.
{"title":"Rigid-flexible coupling modeling and nonlinear analysis of rudder actuator with lubrication clearance","authors":"Ye Lu, Xiaomei Li, Zhijiang Xie, Haolan Jia, Zhenjun Su, Xiaoliang Hu","doi":"10.1016/j.ymssp.2026.113928","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113928","url":null,"abstract":"To investigate the coupling effects of clearance and flexible components on dynamic performance of pushrod-driven actuator, this study proposes a hybrid contact force model suitable for large loads with an adaptive restitution coefficient, and a modified transitional lubrication force model. Considering the influence of flexible components, a rigid-flexible coupling dynamics model of the actuator incorporating lubrication clearance is established. Subsequently, effects of clearance size, driving speed, dynamic viscosity and load on system’s dynamics and chaos are then analyzed. Finally, experimental validation confirms the model’s effectiveness. The results show that the choice of clearance size and drive speed significantly influences system stability, and that high dynamic viscosity lubricants can lower the output vibration frequency and amplitude. Under large loads, the lubricant film thickness at clearance approaches zero, intensifying clearance collisions and wear. This increases the output vibration frequency, and substantially reduces the lubricant’s mitigating effects on clearance and flexible factors. This study provides theoretical support for the design of high-performance rudder actuators.","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"46 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.ymssp.2026.113978
Yuegang Luo, Ning Liu, Songsong Xiao, Wanlei Wang
Rolling bearings are assembled on the shaft through interference fit. The presence of shaft cracks directly affects bearing operation and may even induce defects. Conversely, bearing defects may also exacerbate shaft damage. Currently, research on the bearing defect-shaft crack coupled faults remains insufficient and requires further exploration. This paper proposes an inner raceway extension defect model that incorporates the motion trajectory of the rolling elements. A dynamic model of a rotor-bearing-pedestal system with bearing extension defect and shaft crack is established. The dynamic characteristics of defects, cracks, and coupled faults are systematically analyzed, and the coupling mechanism is further investigated. The simulation and experimental results indicate that for inner raceway defect-shaft crack coupled fault, an increase in crack depth amplifies the bearing fault characteristics, especially when the crack is located near the bearing support or at the midspan of the shaft. The extension of the defect also exacerbates the damage caused by the crack to the shaft. For outer raceway defect-crack coupled fault, shallow cracks suppress the bearing fault frequency. However, once the crack depth exceeds a certain threshold, this suppression transitions to amplification. Cracks located at the midspan of the shaft enhance the bearing fault characteristics. The extension of the outer raceway defect primarily affects the bearing fault frequency and the overall vibration amplitude. The findings of this study are expected to provide a valuable theoretical basis for diagnosing and predicting bearing defect-shaft crack coupled faults.
{"title":"Dynamic behaviors of a rolling bearing-rotor system with bearing extended defect and shaft crack: simulation and experimental investigation","authors":"Yuegang Luo, Ning Liu, Songsong Xiao, Wanlei Wang","doi":"10.1016/j.ymssp.2026.113978","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113978","url":null,"abstract":"Rolling bearings are assembled on the shaft through interference fit. The presence of shaft cracks directly affects bearing operation and may even induce defects. Conversely, bearing defects may also exacerbate shaft damage. Currently, research on the bearing defect-shaft crack coupled faults remains insufficient and requires further exploration. This paper proposes an inner raceway extension defect model that incorporates the motion trajectory of the rolling elements. A dynamic model of a rotor-bearing-pedestal system with bearing extension defect and shaft crack is established. The dynamic characteristics of defects, cracks, and coupled faults are systematically analyzed, and the coupling mechanism is further investigated. The simulation and experimental results indicate that for inner raceway defect-shaft crack coupled fault, an increase in crack depth amplifies the bearing fault characteristics, especially when the crack is located near the bearing support or at the midspan of the shaft. The extension of the defect also exacerbates the damage caused by the crack to the shaft. For outer raceway defect-crack coupled fault, shallow cracks suppress the bearing fault frequency. However, once the crack depth exceeds a certain threshold, this suppression transitions to amplification. Cracks located at the midspan of the shaft enhance the bearing fault characteristics. The extension of the outer raceway defect primarily affects the bearing fault frequency and the overall vibration amplitude. The findings of this study are expected to provide a valuable theoretical basis for diagnosing and predicting bearing defect-shaft crack coupled faults.","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"1 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-09DOI: 10.1016/j.ymssp.2026.113967
Hanqiao Sun, Jingfeng Lu, Jiawen Xu, Ruqiang Yan
Impedance signals for structural health monitoring are often sparse and difficult to acquire in damaged conditions. Increasing the damage categories would significantly reduce accuracy. In this study, we propose a Conv-Transformer model that is capable of multi-task structural health monitoring, addressing the complexities of small sample datasets while handling multiple fault detection tasks, including mass loss and bolt loosening. The model enhances feature extraction by combining convolutional layers and multi-head attention within the Transformer encoder, focusing on the relative location of the peaks and the local feature of each peak in the impedance signals. These advantages enable highly accurate multi-task SHM with small samples of impedance signals. The proposed model is first trained on a large amount of data in mixed conditions and then fine-tuned with small sample data for an eight-class fault classification task. Experimental results show that the model demonstrates strong learning ability and cross-condition transferability, achieving an accuracy of 92.12% for multi-task damage identification, a 4.49% improvement over a conventional Transformer baseline. The proposed method can be applied to health conditions identification of buildings, bridges, and trusses.
{"title":"Conv-Transformer based few-shot learning for highly accurate multi-task structural health monitoring via piezoelectric impedance","authors":"Hanqiao Sun, Jingfeng Lu, Jiawen Xu, Ruqiang Yan","doi":"10.1016/j.ymssp.2026.113967","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113967","url":null,"abstract":"Impedance signals for structural health monitoring are often sparse and difficult to acquire in damaged conditions. Increasing the damage categories would significantly reduce accuracy. In this study, we propose a Conv-Transformer model that is capable of multi-task structural health monitoring, addressing the complexities of small sample datasets while handling multiple fault detection tasks, including mass loss and bolt loosening. The model enhances feature extraction by combining convolutional layers and multi-head attention within the Transformer encoder, focusing on the relative location of the peaks and the local feature of each peak in the impedance signals. These advantages enable highly accurate multi-task SHM with small samples of impedance signals. The proposed model is first trained on a large amount of data in mixed conditions and then fine-tuned with small sample data for an eight-class fault classification task. Experimental results show that the model demonstrates strong learning ability and cross-condition transferability, achieving an accuracy of 92.12% for multi-task damage identification, a 4.49% improvement over a conventional Transformer baseline. The proposed method can be applied to health conditions identification of buildings, bridges, and trusses.","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"60 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cutting force modeling and machinability analysis for ultrasonic vibration-assisted thread milling of SiCp/Al composites","authors":"Ziyang Zhang, Daohui Xiang, Chaosheng Song, Shuaikun Yang, Yanqin Li, Peicheng Peng, Bo Li, Guofu Gao, Yanyan Yan, Jinglin Tong","doi":"10.1016/j.ymssp.2026.113973","DOIUrl":"https://doi.org/10.1016/j.ymssp.2026.113973","url":null,"abstract":"","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"1 1","pages":""},"PeriodicalIF":8.4,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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