Shaokang Chen , Puyuan Cong , Dong F. Wang , Takahito Ono , Toshihiro Itoh
{"title":"A ‘multiple modes’ − ‘multiple parameters’ sensing methodology: Part I – Theoretical modelling","authors":"Shaokang Chen , Puyuan Cong , Dong F. Wang , Takahito Ono , Toshihiro Itoh","doi":"10.1016/j.ymssp.2025.112812","DOIUrl":"10.1016/j.ymssp.2025.112812","url":null,"abstract":"<div><div>This paper, the first of two companion papers, reports a sensing methodology for synchronous and successive detection of ‘multiple parameters’, via ‘multiple modes’ internal resonance in coupled oscillators.</div><div>Detection of ‘multiple parameters’ such as mass, force and damping, characterizing different kinds of perturbations such as weak forces, weak physical fields, trace pollutants or toxic, explosive substances and biological viruses, is crucial for nanotechnology, quantum computer, chemical production, public health and safety etc. with high engineering value.</div><div>However, quantitative detection of ‘multiple parameters’ is challenged by too many modes (i.e. more than three ones), intermittent detection, inevitable decoupling, as well as conditional parameter ratio in reported art works.</div><div>A ‘multiple modes’ − ‘multiple parameters’ sensing methodology, driven by ‘multiple modes’ internal resonance and supported by two theoretical models, is therefore proposed to address the above challenges with coupled oscillators.</div><div>The first theoretical model is established for ‘multiple modes’ internal resonance with 1:3 frequency ratios, while the second one is comprised of two nonlinear sensing theories with and without decoupling respectively, established for synchronous and successive detection of ‘multiple parameters’.</div><div>The proposed sensing methodology is physically universal and applicable to parameters, such as mass, force or damping, if convertible to or equivalent to any changes in vibrational coefficients of the oscillator.</div><div>The above theoretical models are generalized to different types of vibrational modes, such as flexural, shearing and torsional ones owing to their common characteristic in the higher order mode shapes.</div><div>While an experimental validation of the proposed sensing methodology will be discussed in part II.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112812"},"PeriodicalIF":7.9,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906550","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}
Xinming Li , Jiawei Gu , Meng Li , Xin Zhang , Lijun Guo , Yiyan Wang , Wenhan Lyu , Yanxue Wang
{"title":"Adaptive expert ensembles for fault diagnosis: A graph causal framework addressing distributional shifts","authors":"Xinming Li , Jiawei Gu , Meng Li , Xin Zhang , Lijun Guo , Yiyan Wang , Wenhan Lyu , Yanxue Wang","doi":"10.1016/j.ymssp.2025.112762","DOIUrl":"10.1016/j.ymssp.2025.112762","url":null,"abstract":"<div><div>Due to the complexity and variability of operating conditions, accurate fault diagnosis is crucial to ensure wind turbine efficiency and reduce maintenance costs. However, existing deep learning models for fault detection often struggle with distribution shifts caused by environmental changes, leading to unreliable predictions. In response, this paper proposes the GCI-ODG framework, an innovative approach based on Graph Causal Intervention (GCI) to enhance Out-Of-Distribution (OOD) generalization in intelligent fault diagnosis of wind turbines. The core innovations of this framework include a hierarchical graph representation that captures both local and global features of multi-condition time-series data, improving the model’s ability to detect intricate fault patterns. An adaptive expert ensemble mechanism is introduced, utilizing pseudo-environment labels inferred without explicit environmental data, enabling dynamic feature extraction and robust adaptation across diverse operating conditions. Additionally, the framework employs causal inference strategies, including backdoor adjustment, to isolate stable, environment-invariant features, effectively mitigating the impact of spurious correlations and distribution shifts. Extensive experiments across multiple benchmark datasets, including real-world wind turbine data, validate the effectiveness of the proposed GCI-ODG framework. The results indicate notable enhancements in both classification accuracy and model robustness under diverse conditions. The GCI-ODG framework demonstrates exceptional capability in handling significant distribution shifts, proving its value as a scalable and generalizable solution for intelligent diagnostics. These findings highlight its potential for reliable and efficient fault detection in complex industrial environments.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112762"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904522","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}
Miaomiao Wang , Hongsen He , Jingdong Chen , Jacob Benesty , Yi Yu
{"title":"A family of robust low-complexity adaptive filtering algorithms for active control of impulsive noise","authors":"Miaomiao Wang , Hongsen He , Jingdong Chen , Jacob Benesty , Yi Yu","doi":"10.1016/j.ymssp.2025.112779","DOIUrl":"10.1016/j.ymssp.2025.112779","url":null,"abstract":"<div><div>Active noise control (ANC) is a technique used to achieve noise cancellation in physical spaces and has a wide range of applications. A key challenge in ANC systems is designing an adaptive filter that balances noise cancellation performance with computational efficiency. This paper presents two sets of robust adaptive filtering algorithms to address this challenge. The first set involves decomposing the adaptive filter’s coefficient vector into a linear combination of two sets of shorter sub-filters using the Kronecker product. This decomposition reduces the size of the matrices and vectors involved in the ANC algorithm. To handle impulsive noise, we employ a class of robust estimators and define several cost functions under the recursive least-squares criterion, resulting in an adaptive control algorithm with two groups of alternately updating equations. We also analyze the low-rank property of the proposed adaptive filter in controlling impulsive noise. To further reduce computational complexity, we integrate the dichotomous coordinate descent scheme into the Kronecker product decomposition-based robust ANC method, forming a second set of algorithms. The effectiveness of the proposed algorithms is demonstrated through simulations.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112779"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906548","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":"A corrected circular graph-driven fault diagnosis method for tidal stream turbine blades","authors":"Yujie Xu, Xueli Wang, Tianzhen Wang","doi":"10.1016/j.ymssp.2025.112769","DOIUrl":"10.1016/j.ymssp.2025.112769","url":null,"abstract":"<div><div>Tidal stream turbine (TST) blades are susceptible to failure due to biofouling, accurate blade faults diagnosis is of great significance. However, the insignificance of multi-blade fault features reduce diagnosis accuracy, and the random swell effects further increase the fluctuations of multi-blade fault features. Therefore, a corrected circular graph-driven fault diagnosis (CCGFD) method is proposed to improve the multi-blade faults diagnosis accuracy under the swell effects. In this approach, a corrected circular graph construction (CCG) method is proposed to capture the multi-blade faults features, and the radius circular graph interactive network (RGN) is proposed for multi-blade faults classification. Specifically, the CCG method converts one-dimensional stator current signals into two-dimensional corrected circular graphs, and the correction of vector trajectory improves the discriminability of the blade fault features under the swell effects. Furthermore, the RGN method enriches the multi-blade fault features by fusing one-dimensional circular radius and two-dimensional corrected circular graph, which contains fine-grained fault features in both the time and angular domains. Finally, several experiments on a 230 W TST prototype verified the effectiveness and the robustness of the proposed method.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112769"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906549","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}
Yanding Qin , Jie Yuan , Haitao Wu , Bijan Shirinzadeh , Jianda Han
{"title":"Hysteresis compensation and decoupling control of a parallel XYΘ nanopositioning system in linear and angular coupled positioning","authors":"Yanding Qin , Jie Yuan , Haitao Wu , Bijan Shirinzadeh , Jianda Han","doi":"10.1016/j.ymssp.2025.112794","DOIUrl":"10.1016/j.ymssp.2025.112794","url":null,"abstract":"<div><div>Piezoelectric actuator actuated XYΘ nanopositioning system can provide in-plane 3 degrees-of-freedom (DOFs) actuation for micro/nano manufacturing. The challenges in the positioning control of this multi–input–multi–output (MIMO) system include the hysteresis of the actuators, the input couplings, and the output couplings. In this paper, a decoupling generalized predictive controller is proposed to account for the above hysteresis and couplings. First, an inverse Prandtl-Ishlinskii model is used to construct the feedforward compensator. Consequently, the compensated system can be treated as a linear MIMO system with input and output couplings. Subsequently, for the compensated system, a MIMO controller is constructed using generalized predictive control. Multi-DOF positioning results demonstrate that the proposed controller can effectively improve the transient and steady-state positioning performance of the XYΘ nanopositioning system.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112794"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904533","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}
Mengfei Su, Jingtao Du, Yang Liu, Zheng Dai, Xiao Liu
{"title":"Vibration and power flow analysis of a uniform beam coupled with an ABH beam with arbitrary angles","authors":"Mengfei Su, Jingtao Du, Yang Liu, Zheng Dai, Xiao Liu","doi":"10.1016/j.ymssp.2025.112810","DOIUrl":"10.1016/j.ymssp.2025.112810","url":null,"abstract":"<div><div>This study establishes a model of a uniform beam coupled with an Acoustic Black Hole (ABH) beam, considering arbitrary connection angles. Translational and rotational springs are used to simulate the connection stiffnesses as well as the elastic boundary conditions. Under the general Rayleigh-Ritz framework, a modified Fourier series is chosen as the admissible function for the flexural and longitudinal displacements of the ABH coupled beam. The modified Fourier series ensures the continuity of higher-order spatial derivatives across the entire solution domain, enabling the calculation of structural intensity and power flow within the ABH coupled beam. Accurate predictions of the modal characteristics and dynamic response of the system are verified through comparisons with results simulated from FEM or experimental data. Subsequently, numerical examples are presented to study the ABH effect and vibration energy transmission in the coupled system. The excellent energy focalization characteristic is observed, and the unfavorable ABH failure phenomenon is also confirmed. Two mechanisms of ABH failure are revealed through power flow analysis: energy localization and coupling node hindering effects. Finally, the effect of coupling angle variation on vibrational energy transmission in the system is investigated. The established theoretical model and the phenomenon presented in this work provide guidance for applying ABH in coupled beam structures and promote its use in complex systems.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112810"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906546","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}
Houyu Lu , Sergio Cantero Chinchilla , Brecht Rotsaert , Anthony Croxford , Konstantinos Gryllias , Dimitrios Chronopoulos
{"title":"Damage identification using ultrasonic Lamb waves with multi-scale adaptive attention Transformer-based unsupervised domain adaptation","authors":"Houyu Lu , Sergio Cantero Chinchilla , Brecht Rotsaert , Anthony Croxford , Konstantinos Gryllias , Dimitrios Chronopoulos","doi":"10.1016/j.ymssp.2025.112772","DOIUrl":"10.1016/j.ymssp.2025.112772","url":null,"abstract":"<div><div>In this paper, a novel unsupervised transfer learning method – the Multi-scale Adaptive Attention Transformer Domain Adaptation Network (MAAT-DAN) is proposed for structural damage identification in regression and classification tasks. MAAT-DAN comprises three main components: a feature extractor, a domain adapter, and a label predictor. The feature extractor, for the first time, introduces a novel dynamic adaptive weighting module that enhances multi-head attention by adjusting attention head weights based on the input. Additionally, a multi-scale feature extraction technique is employed to simultaneously extract damage features at three different scales from Lamb waves, a popular means in structural health monitoring. The label predictor is composed of multiple fully connected layers. MAAT-DAN’s domain adapter integrates a gradient reversal layer for managing high-dimensional data, maximum mean discrepancy for improved stability, and feature reconstruction techniques to support effective domain adaptation. MAAT-DAN’s performance is validated in both regression and classification tasks using two specially designed ultrasonic experiments: (1) for regression, an experiment on a reinforced aluminum plate using test beams of two different materials and Blu-Tack to simulate repeatable damage; (2) for classification, an experiment on a steel water tank deploying two pairs of sensors to collect data over two years. Its feature extractors and domain adapters are compared across customized metrics against five other methods using these datasets. Results show that MAAT-DAN achieved the highest prediction accuracy and consistent prediction stability in both tasks, demonstrating its effectiveness in unsupervised domain adaptation for damage identification.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112772"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906547","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}
Feng Ding, Sen Wang, Chang Liu, Tao Liu, Xiaoqin Liu, Aiping Shen
{"title":"Visual vibration measurement of rotating bodies with effective time–frequency characterization at constant and variable rotational speeds","authors":"Feng Ding, Sen Wang, Chang Liu, Tao Liu, Xiaoqin Liu, Aiping Shen","doi":"10.1016/j.ymssp.2025.112776","DOIUrl":"10.1016/j.ymssp.2025.112776","url":null,"abstract":"<div><div>Non-contact visual vibration measurement methods are gradually applied to vibration signal analysis of rotating bodies. However, the displacement fitting accuracy of existing visual methods needs to be improved in constant speed vibration measurement, and they are rarely used in variable speed vibration measurement. Aiming at the needs of rotating machinery condition monitoring, the paper proposes a non-contact vibration measurement method integrating deep learning technology. The method uses a high-speed industrial camera to capture rotor vibration images, and obtains vibration displacement under constant speed and variable speed conditions through instance segmentation network processing. By constructing a new instance segmentation network architecture, the target segmentation accuracy and vibration measurement accuracy are improved, and Feature Enhancement Module(FEM) and improved Protonet are introduced to further improve the measurement accuracy. Combining vibration displacement data with spectrum analysis enriches the vibration monitoring methods of rotating machinery. Experiments show that the method performs better than target detection and segmentation algorithms in constant speed and variable speed rotor vibration measurement, and has application potential in rotating machinery condition monitoring.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112776"},"PeriodicalIF":7.9,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904521","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}
Rongjian Sun , Conggan Ma , Yuanyuan Li , Chuyo Kaku , Yanyan Wang , Yu Zhang , Zheming Wen
{"title":"Experiment-driven identification approach of anisotropic damping behaviors and theoretical modal dynamic modelling of electric motors","authors":"Rongjian Sun , Conggan Ma , Yuanyuan Li , Chuyo Kaku , Yanyan Wang , Yu Zhang , Zheming Wen","doi":"10.1016/j.ymssp.2025.112737","DOIUrl":"10.1016/j.ymssp.2025.112737","url":null,"abstract":"<div><div>The modal dynamic behavior of the electrical motors (EMs) is a key determinant in accurately predicting vibration and noise. The natural frequency determines the frequency of structural resonance noise, making it a subject of extensive research. Notwithstanding the significant contributions of the damping ratios to the noise amplitude, this factor remains underexplored in the research field. Essentially, the anisotropic material damping of stator cores and windings remains unstudied. To address the existing research deficiency, an experiment-driven approach for calculating the damping ratios is put forward. Firstly, a theoretical modal dynamic model of the coupled structure consisting of the stator core, winding, and casing is developed. In particular, the hysteresis damping theory is employed to take the material damping behavior into account. Accordingly, the effect of anisotropic material damping of the stator core and windings on the structural damping ratios is thoroughly investigated. Subsequently, the anisotropic material parameters (AMPs) and anisotropic damping parameters (ADPs) of stator cores and windings are identified based on the proposed theoretical models and modal experiments. Finally, Natural frequencies and damping ratios are calculated utilizing the identified AMPs and ADPs. The absolute errors of the damping ratios of the stator core and stator assembly are within 0.14%, and the absolute errors of the stator system are within 0.25%. The proposed approach is of great significance for analyzing and controlling structural resonance noise of the EMs.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112737"},"PeriodicalIF":7.9,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898521","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}
Kaixin Shao , Zhijun Yao , Baiyang Shi , Yuhao Liu , Jian Yang
{"title":"Vibration energy transfer in nonlinear coupled near-identical systems","authors":"Kaixin Shao , Zhijun Yao , Baiyang Shi , Yuhao Liu , Jian Yang","doi":"10.1016/j.ymssp.2025.112786","DOIUrl":"10.1016/j.ymssp.2025.112786","url":null,"abstract":"<div><div>This study investigates the dynamic response and vibrational energy transfer characteristics of coupled near-identical systems, with a focus on coupled discrete oscillators and coupled cantilever beams. Using analytical approximations based on the averaging method and harmonic balance-alternating frequency time (HB-AFT), alongside numerical integration, the dynamic responses and vibration transfer behaviour are analysed. The influence of both linear and nonlinear coupling stiffness is thoroughly examined. Comprehensive experimental results and finite element analysis (FEM) are conducted, focusing on mode shape and frequency response under motion excitation. For the motion excitation analysis, our findings reveal that even minor variations in mass can disrupt symmetry, resulting in the emergence of an additional resonant peak and illustrating the unique frequency response behaviours of near-identical systems. Notably, power flow analysis indicates that energy is transferred from the lighter oscillator to the heavier one across different frequency ranges, with distinct patterns observed during both in-phase and out-of-phase oscillations. For the power transfer curves, both linear and nonlinear cubic coupling stiffness ratio controls the location of the second resonance frequencies. It is also shown that the second resonance peak bends to a higher frequency when the cubic stiffness ratio increases. The results offer valuable implications for the design and optimization of coupled systems in various engineering applications.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"234 ","pages":"Article 112786"},"PeriodicalIF":7.9,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143898520","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}