Mechanical Systems and Signal Processing最新文献

New methodology for adaptive sliding mode control with self-tuning threshold based on chattering detection 基于抖振检测的自适应滑模控制新方法

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-03 DOI: 10.1016/j.ymssp.2025.112854

Jonathan Rodriguez , Vincent Lechappe , Simon Chesne

引用次数: 0

Model selection in damage identification using approximate Bayesian computations 基于近似贝叶斯计算的损伤识别模型选择

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-03 DOI: 10.1016/j.ymssp.2025.112867

Michael L.M. de Souza , N. Roitman , Daniel A. Castello

{"title":"Model selection in damage identification using approximate Bayesian computations","authors":"Michael L.M. de Souza , N. Roitman , Daniel A. Castello","doi":"10.1016/j.ymssp.2025.112867","DOIUrl":"10.1016/j.ymssp.2025.112867","url":null,"abstract":"<div><div>The formulation of damage identification strategies based on the Bayesian framework is an interesting strategy, conjugating prior information, computational models and measured data. However, it demands the specification of the likelihood function, which can be cumbersome depending on the features chosen to be used as measurements in observation models. These scenarios may be handled by the use of Approximate Bayesian Computations, where the computation of the likelihood function is replaced by a suitable discrepancy metric. Therefore, this paper proposes a damage identification strategy based on Approximate Bayesian Computation in which an adaptive schedule for the tolerance error used in the acceptance criterion stages is proposed. The effectiveness of the present approach is assessed using measured data from an elastic beam instrumented with accelerometers. The damage/anomaly in the beam is physically simulated by positioning lumped masses along its length. The main quantities adopted as discrepancy metrics are the natural frequency and modal assurance criterion (MAC). A set of feasible models is considered for inverse analyses. The scarcity of spatial information is also explored through mode shape expansion. The proposed strategy provided unimodal marginal posterior densities encompassing the true values of magnitude and position for results based on MAC.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112867"},"PeriodicalIF":7.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195496","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}

引用次数: 0

A trustworthy lightweight multi-expert wavelet transformer for rotating machinery fault diagnosis 一种可信赖的轻型多专家小波变换旋转机械故障诊断方法

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-03 DOI: 10.1016/j.ymssp.2025.112945

Yutong Dong, Hongkai Jiang, Mingzhe Mu, Xin Wang

{"title":"A trustworthy lightweight multi-expert wavelet transformer for rotating machinery fault diagnosis","authors":"Yutong Dong, Hongkai Jiang, Mingzhe Mu, Xin Wang","doi":"10.1016/j.ymssp.2025.112945","DOIUrl":"10.1016/j.ymssp.2025.112945","url":null,"abstract":"<div><div>Rotating machinery plays a crucial role in industrial applications, making reliable fault diagnosis essential for operational efficiency and system safety. Current deep learning approaches face challenges in trustworthiness, computational efficiency, and limitations in training with small datasets. To address these issues, this paper proposes a trustworthy lightweight multi-expert wavelet transformer (TLMW-former) for fault diagnosis. The TLMW-former incorporates a multi-wavelet sparse representation denoising (MSRD) layer to effectively suppress background noise, enhancing fault features of signals. A wavelet linear self-attention (WLSA) mechanism is designed to improve global feature mining and model interpretability, while a stride inverted residual module is introduced to enhance local feature extraction and downsampling. Additionally, a multi-expert feedback layer is developed to strengthen decision-making reliability and performance through collaborative expert mechanisms. Experimental evaluations on four datasets demonstrate the superiority of TLMW-former, achieving 96.86%, 88.32%, 92.16%, and 90.88% accuracy, respectively, while requiring significantly fewer computational resources than most baseline models. The results highlight the performance and trustworthiness of the model and suitability for deployment in complex industrial environments.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112945"},"PeriodicalIF":7.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195498","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}

引用次数: 0

Bayesian method for force identification within transfer path analysis 传递路径分析中力识别的贝叶斯方法

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-03 DOI: 10.1016/j.ymssp.2025.112874

Weihan Shen , Andreas Schuhmacher , Wookeun Song , Ester Creixell-Mediante , Frieder Lucklum , Jonas Brunskog

{"title":"Bayesian method for force identification within transfer path analysis","authors":"Weihan Shen , Andreas Schuhmacher , Wookeun Song , Ester Creixell-Mediante , Frieder Lucklum , Jonas Brunskog","doi":"10.1016/j.ymssp.2025.112874","DOIUrl":"10.1016/j.ymssp.2025.112874","url":null,"abstract":"<div><div>In Transfer Path Analysis (TPA), accurate estimation results always rely on an appropriate treatment of the matrix inversion. While mainstream approaches, such as overdetermining the system and utilizing regularization techniques, are commonly applied, each method has its own limitations. Overdetermining the system requires additional indicators, further complicating the measurement procedure, and is impractical in scenarios with limited sensor mounting space. Regularization, on the other hand, is frequently criticized for instability. Its accuracy often depends on the specific problem, making it difficult to achieve satisfactory results without tailored approaches. This paper introduces a Bayesian framework to enhance the performance of classical TPA, offering a data-driven approach to handle the mentioned challenges. The feasibility of the Bayesian model is evaluated through both experimental setups that mimic an excitation source mounted on a suspension with resilient connections and corresponding numerical simulations. Moreover, to explore the possibility of applying TPA to smaller structures, we also assess the Bayesian TPA when relaxing the typically required overdetermined constraints. The results show that the Bayesian model can provide more insight into the uncertainty and model-appropriateness within the TPA estimation process and give more accurate and robust outputs in underdetermined system scenarios.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112874"},"PeriodicalIF":7.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195663","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}

引用次数: 0

Non-synchronous measurement of rotating sound source based on matrix completion 基于矩阵补全的旋转声源非同步测量

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-03 DOI: 10.1016/j.ymssp.2025.112870

Hongjie Hou , Fangli Ning , Deyu Jia , Juan Wei

{"title":"Non-synchronous measurement of rotating sound source based on matrix completion","authors":"Hongjie Hou , Fangli Ning , Deyu Jia , Juan Wei","doi":"10.1016/j.ymssp.2025.112870","DOIUrl":"10.1016/j.ymssp.2025.112870","url":null,"abstract":"<div><div>Conventional rotating sound source beamforming is susceptible to interference from wide main lobes and high-amplitude sidelobes due to limitations of the microphone array aperture and microphone layout density. The non-synchronous measurement of rotating sound sources can reduce the main lobe width, suppress side lobes, and meet spatial sampling requirements. Due to the time-varying characteristics of the transfer function of rotating sound sources and the Doppler effect, conventional stationary non-synchronous measurement cannot be directly applied to the localization of rotating sources. This work extends a non-synchronous measurement algorithm from static sources to rotating sound sources. First, the cross-spectral matrix (CSM) of missing elements is obtained based on the mode composition beamforming algorithm in vector form. Then, the matrix completion is performed based on the spatial basis of the frequency-domain modal transfer function to obtain the full CSM. Finally, the complete non-synchronous measurement results are obtained. Simulation results demonstrate the effectiveness of this method in accurately localizing rotating sound sources, reducing main lobe width, and suppressing sidelobe levels. In experiments with actual simulated sound sources and UAV rotating blades, its performance in suppressing main lobe width and side lobe levels was also demonstrated.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112870"},"PeriodicalIF":7.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195661","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}

引用次数: 0

Surface roughness online prediction using parallel ensemble learning in robotic side milling for aluminum alloy 基于并行集成学习的铝合金机器人侧铣削表面粗糙度在线预测

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-03 DOI: 10.1016/j.ymssp.2025.112932

Ci Song, Zhibing Liu, Xibin Wang, Tianyang Qiu, Zhiqiang Liang, Wenhua Shen, Yuhang Gao, Senjie Ma

{"title":"Surface roughness online prediction using parallel ensemble learning in robotic side milling for aluminum alloy","authors":"Ci Song, Zhibing Liu, Xibin Wang, Tianyang Qiu, Zhiqiang Liang, Wenhua Shen, Yuhang Gao, Senjie Ma","doi":"10.1016/j.ymssp.2025.112932","DOIUrl":"10.1016/j.ymssp.2025.112932","url":null,"abstract":"<div><div>Robotic machining has the advantages of large workspace and high flexibility, and the acquisition of high surface quality parts has become the research focus. To realize surface roughness online prediction in robotic side milling for aluminum alloy, an intelligent model driven by cutting vibration was adopted. Combined with variational modal decomposition (VMD) and fast fourier transformation (FFT), a rough and fine two-layer decomposition strategy of stable cutting vibration signals was proposed, which can effectively avoid the adverse effects of modal aliasing and endpoint action on the extraction of high-sensitivity features. Based on support vector machine (SVM), random forest (RF) and extreme learning machine (ELM), weighted reconstruction and voting selection were introduced to form a parallel ensemble learning model. Considering the posture influence in the sample construction, the machining system vibration state within common range was fully reflected by orthogonal cutting experiments at the corresponding postures of envelope zone vertices. For the setting process parameters, the obtained surface roughness was within 1.62–2.90 μm. Experiments under the testing postures showed the root mean square error (RMSE) and mean absolute error (MAE) of the model were 0.087 μm and 0.076 μm. The average relative error of 3.57 % and maximum relative error of 8.65 % had shown that the model obtained better surface roughness prediction ability. Finally, the influence significance and the factor action trend between cutting parameters and surface roughness were explored by range analysis, which has been proved by experiments that they can provide guidance for the dynamic regulation of cutting parameters.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112932"},"PeriodicalIF":7.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195662","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}

引用次数: 0

Equivalent circuit modeling for triboelectric energy harvesters 摩擦电能量采集器等效电路建模

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-02 DOI: 10.1016/j.ymssp.2025.112916

Zicheng Liu , Guobiao Hu , Xin Li , Chaoyang Zhao , Yaowen Yang

{"title":"Equivalent circuit modeling for triboelectric energy harvesters","authors":"Zicheng Liu , Guobiao Hu , Xin Li , Chaoyang Zhao , Yaowen Yang","doi":"10.1016/j.ymssp.2025.112916","DOIUrl":"10.1016/j.ymssp.2025.112916","url":null,"abstract":"<div><div>The utilization of triboelectric transduction for vibration energy harvesting has garnered considerable attention owing to its manifold advantages. Researchers across diverse disciplines have endeavored to develop various theoretical models to investigate the properties of triboelectric energy harvesters (TEHs). Initially, material scientists formulated analytical models to explain triboelectric transduction’s electric energy generation process. Subsequently, experts in mechanical engineering devised dynamical models to describe the mechanical response of TEHs, often simplifying the energy extraction circuit (EEC) to a mere resistor. Conversely, researchers in electrical engineering derived models for intricate EECs but tended to oversimplify the harvesters’ mechanical response as sinusoidal motions. Consequently, the integration of models addressing both the electromechanical response of the harvesters and the practical EECs remains largely unaddressed due to the analytical challenges posed by such intricate systems. This article presents a novel technique to reconcile the disparity between the electromechanical and EEC models of TEHs by implementing an equivalent circuit model (ECM). Initially, the equivalent circuit parameters of the harvester are identified based on an electromechanical model of a cantilever-based harvester. Subsequently, an ECM encompassing both the mechanical and electrical responses is established. Finally, the ECM is experimentally validated, demonstrating its capability to simulate the harvester’s performance on a holistic system level. This proposed methodology serves as a crucial step towards comprehensive modeling and optimization of TEH systems for enhanced energy harvesting efficiency and applicability in various domains.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112916"},"PeriodicalIF":7.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189330","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}

引用次数: 0

Moving load identification in the presence of uncertainties in the computational model 计算模型中存在不确定性时的移动荷载识别

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-02 DOI: 10.1016/j.ymssp.2025.112866

Zakaria Bitro , Anas Batou , Huajiang Ouyang

{"title":"Moving load identification in the presence of uncertainties in the computational model","authors":"Zakaria Bitro , Anas Batou , Huajiang Ouyang","doi":"10.1016/j.ymssp.2025.112866","DOIUrl":"10.1016/j.ymssp.2025.112866","url":null,"abstract":"<div><div>Most standard methods for moving load identification make use of a deterministic computational or analytical models under strong modelling assumptions concerning the geometry of the supporting structure on which the moving loads are applied and the speed of these moving loads. Nevertheless, these quantities are in general not perfectly known (thus uncertain) and the identified moving loads, as well as the dynamic response of the structure, can be very sensitive to their values. It is therefore crucial to examine the effects of these uncertainties on the predictability of computational models and support decision-makers. This paper introduces a stochastic framework for modelling a vehicle-bridge interaction (VBI) system, accounting for uncertainties in the road profile and the speed of the moving loads yielding uncertainties in the geometry of the supporting structure and the position of the moving loads. The explicit form of the Newmark-<span><math><mi>β</mi></math></span> method is utilised to establish an inverse model and identify the moving loads, and the Monte Carlo simulation method is used to build the statistics of the identified moving loads.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112866"},"PeriodicalIF":7.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189332","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}

引用次数: 0

Dynamic detection mechanism model of acoustic emission for high-speed train axle box bearings with local defects 高速列车轴箱轴承局部缺陷声发射动态检测机制模型

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-02 DOI: 10.1016/j.ymssp.2025.112943

Defu Han , Hongyuan Qi , Dongming Hou , Shuangxin Wang , Jinzhen Kong , Xining Xu , Cuiping Wang

{"title":"Dynamic detection mechanism model of acoustic emission for high-speed train axle box bearings with local defects","authors":"Defu Han , Hongyuan Qi , Dongming Hou , Shuangxin Wang , Jinzhen Kong , Xining Xu , Cuiping Wang","doi":"10.1016/j.ymssp.2025.112943","DOIUrl":"10.1016/j.ymssp.2025.112943","url":null,"abstract":"<div><div>Acoustic emission (AE), as a promising technology, is suitable for the fault diagnosis and state monitoring of high-speed train axle box bearings (HSTABs). However, the mechanism of the correlation between bearing states and dynamic AE signals remains unclear. Existing studies have failed to explain the relationship between contact deformation energy and dynamic root-mean-square (RMS) of the AE signals generated by HSTABs, while also neglecting the asperity-induced dynamic displacement and local defect-induced transient elastic waves. Moreover, there is no study on the attenuation behavior of AE waves in complete HSTAB. This paper presents an AE dynamic detection mechanism model of the HSTAB state, revealing the generation mechanism of AE waves by rough contact and local defect impact and their propagation characteristics. First, based on the load pattern of the HSTAB, a dynamic model was established considering asperity contact, local defect impact, and lubrication oil, and the dynamic contact force of the rollers was determined. Second, a mathematical model of the rough contact with RMS was established jointly with the contact force. Further, the attenuation features of the AE waves in the HSTAB and its housing were investigated, and an AE dynamic mechanism model was established. The model not only resolves the dynamic RMS characterization of the AE signals from moving bearings but also describes the relationship between the dynamic RMS and running speed, bearing state, and time scale. Finally, with different defective HSTABs as examples, the correctness of the model was verified by performing experiments on a full-size high-speed train test rig, providing a theoretical basis for the application of the AE technology in the diagnosis and quantitative analysis of bearing faults.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112943"},"PeriodicalIF":7.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189331","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}

引用次数: 0

A digital twin-based framework for reliability estimation in ultrasonic guided wave structural health monitoring systems with temperature variations 温度变化下超声导波结构健康监测系统可靠性估计的数字孪生框架

IF 7.9 1区工程技术

Mechanical Systems and Signal Processing Pub Date : 2025-06-02 DOI: 10.1016/j.ymssp.2025.112848

Panpan Xu , Georgios Sarris , Robin Jones , Peter Huthwaite

{"title":"A digital twin-based framework for reliability estimation in ultrasonic guided wave structural health monitoring systems with temperature variations","authors":"Panpan Xu , Georgios Sarris , Robin Jones , Peter Huthwaite","doi":"10.1016/j.ymssp.2025.112848","DOIUrl":"10.1016/j.ymssp.2025.112848","url":null,"abstract":"<div><div>The reliability estimation of ultrasonic guided wave structural health monitoring (SHM) systems is crucial yet challenging due to the need to represent practical conditions that evolve over a system’s lifespan. These conditions include various variables and uncertainties in measurements, which must be captured through experimental data collection or numerical data generation. This paper proposes and validates a novel digital twin-based framework that provides tailored reliability estimations throughout an SHM system’s lifecycle, accounting for specific measurement conditions, particularly temperature variations. The framework develops a digital twin model reflecting real-time measurement conditions using installed SHM measurements, from which key simulation parameters affected by environmental temperatures are updated. Laboratory experiments demonstrate the model’s ability to generate high-fidelity guided wave signals, effectively capturing temperature effects and noise levels. The framework’s reliability estimation performance is verified by comparing probability of detection (POD) analyses with the established superposition method. The paper further illustrates the framework’s capability to provide more accurate reliability assessments compared to traditional model-assisted POD methods by offering progressive, time-evolving performance evaluations that effectively account for dynamic temperature variations and changes in transducer performance over time. This approach represents a significant advancement in SHM reliability estimation, providing a feasible solution with improved accuracy and adaptability to real-world conditions through the dynamic development of the digital twin model.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"235 ","pages":"Article 112848"},"PeriodicalIF":7.9,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195659","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}

引用次数: 0