Mechanical Systems and Signal Processing最新文献

{"title":"Moment equations and closure approximations for non-linear dynamic response of a guy line of a guyed tower to stochastic wind excitation","authors":"Anna Jabłonka ,&nbsp;Hanna Weber ,&nbsp;Radosław Iwankiewicz","doi":"10.1016/j.ymssp.2025.112382","DOIUrl":"10.1016/j.ymssp.2025.112382","url":null,"abstract":"<div><div>In the present paper the non-linear dynamic behavior of the guy line of a guyed tower under stochastic wind excitation is considered. The guy line is idealized as an isolated taut string wherein the moderate geometric non-linear effects (non-linear strain–displacements relationships) are taken into account. The main purpose of the paper is to determine approximately the mean value and variance of the guy line response to stochastic wind excitation. The point of attachment of the guy line to the tower, which is the displacement response of the tower to the wind excitation, is the base motion excitation for the string. The partial differential equations governing the axial and transverse non-linear vibrations of the string are derived from the Newton’s second law equation for the differential element of the string. The problem is converted into the one governed by ordinary differential equations using the Galerkin method. The response of a tower at the point of attachment of the guy line, regarded as a narrow-band stochastic process, is modeled as the response of the second-order linear filter to the input process, which is in turn the output of an auxiliary linear filter to the Gaussian white noise excitation. Equations for the statistical moments of the state variables are obtained with the aid of the Itô’s differential rule and cumulant-neglect closure and quasi-moment closure approximations are used to solve the equations for moments. Direct numerical Monte Carlo simulations is used to verify the approximate analytical results obtained by the proposed approach. The advantages and disadvantages of the presented method compared to the standard Monte Carlo simulation and the authors’ previous publications are discussed and summarized.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112382"},"PeriodicalIF":7.9,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077528","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":"An inverse-forward dynamics for real-time operational clamping force prediction of BLAC Motor","authors":"Seungin Oh ,&nbsp;Gyunam Park ,&nbsp;Yongbeom Cho ,&nbsp;Jongwha Lee ,&nbsp;Sangwon Park ,&nbsp;Taehwi Lee ,&nbsp;Jin-Gyun Kim","doi":"10.1016/j.ymssp.2025.112352","DOIUrl":"10.1016/j.ymssp.2025.112352","url":null,"abstract":"<div><div>This study presents an inverse-forward dynamics for clamping force prediction of brushless AC (BLAC) motor attached to motor driven power steering system (MDPS) in operational condition. The clamping force that is important to safety as well as NVH is difficult to experimentally measure during the operation, and electro-magnetic force that is a main loading condition of MDPS has also a lot of uncertainties in the system level. In this work, equivalent bearing force is employed as a replacement for the electromagnetic force, and it is indirectly predicted by using measurable acceleration data in the manner of inverse source identification. The clamping force between the BLAC motor and the supporting structure is then computed by the forward time integration algorithm. A new inverse-forward dynamic formulation combining implicit generalized-<span><math><mi>α</mi></math></span> time integrator and Tikhonov regularization is introduced to get the equivalent bearing forces and the clamping forces from noisy acceleration data. Model updating of the BLAC motor and the test bed is also necessary to accurately compute the force components through the proposed inverse-forward process. Among the various reduced-order modeling (ROM) techniques, Craig-Bampton component mode synthesis (CB-CMS) is employed. CB-CMS that has modal-nodal Degrees of Freedom (DOFs) in the reduced system matrices allows direct coupling between measured data and desired force data in the physical domain as well as efficient force computation. The accuracy and efficiency of the proposed process are evaluated through experiments with the BLAC motor test bed.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112352"},"PeriodicalIF":7.9,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077529","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":"Design of lightweight multifunctional honeycomb membrane-type acoustic metastructures for sound insulation","authors":"Xing-Yu Li ,&nbsp;Xiang-Yu-Han Wang ,&nbsp;Qian-Qian Wu ,&nbsp;Yang Jin ,&nbsp;Zhuang Lin ,&nbsp;Lin-Zhi Wu","doi":"10.1016/j.ymssp.2025.112364","DOIUrl":"10.1016/j.ymssp.2025.112364","url":null,"abstract":"<div><div>Honeycomb sandwich structures exhibit outstanding mechanical performance. However, their sound-insulation performance is typically unsatisfactory due to the sound-insulation mass law. In this study, a multilayer honeycomb membrane-type acoustic metastructure (MHMAM) is proposed by combining conventional honeycomb sandwich structures with membrane-type acoustic metamaterial. A theoretical model for calculating the sound transmission loss (STL) of the MHMAM is established using the space harmonic expansion method and the principle of virtual work. Subsequently, the validity and accuracy of the theoretical model are verified using a finite element model. The sound-insulation mechanism of the MHMAM is comprehensively examined from the perspectives of average normal displacement and energy transmission. The results show that, within the sound-insulation frequency band near the STL peak, the average normal displacement reaches a minimum and the power of energy transmission through the honeycomb wall and the air-facesheet pathways is reduced by more than tenfold. Moreover, the effects of membrane tension, membrane thickness, and honeycomb wall spacing on the sound-insulation performance are investigated analytically. Finally, sound-insulation experiments are conducted using an impedance tube system. The results indicate that the MHMAM can generate a higher STL than conventional honeycomb sandwich structures in the frequency range of 500–6300 Hz. Therefore, the MHMAM can simultaneously provide broadband sound-insulation and load-bearing capabilities, making it an effective lightweight multifunctional sound-insulation structure.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112364"},"PeriodicalIF":7.9,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077531","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 novel time-frequency analysis method of blade tip timing signals based on multiple measurement vectors","authors":"Yunyang Ma ,&nbsp;Baijie Qiao ,&nbsp;Yu Fu ,&nbsp;Jun Liang ,&nbsp;Kai Zhou ,&nbsp;Yanan Wang ,&nbsp;Bi Wen ,&nbsp;Xuefeng Chen","doi":"10.1016/j.ymssp.2025.112351","DOIUrl":"10.1016/j.ymssp.2025.112351","url":null,"abstract":"<div><div>Rotating blades are vital components in turbomachinery, and accurate vibration measurement is critical for fault diagnosis and early warning. Non-contact blade vibration measurement techniques, such as blade tip timing (BTT), have gained substantial attention in academia and industry. However, limitations in sensor deployment often result in BTT signals that fail to meet the Nyquist sampling theorem, leading to undersampling signals. Sparse reconstruction methods have emerged as a solution to extract comprehensive blade vibration information from undersampled signals. However, existing sparse reconstruction methods of BTT signals based on the single measurement vector (SMV), exhibit poor robustness, amplitude underestimation, and susceptibility to frequency aliasing. To address these limitations, this paper proposes a time–frequency analysis method of BTT signals based on joint sparsity to achieve blade natural frequency tracking and frequency spectrum reconstruction. The existing SMV sparse reconstruction model of BTT signals is extended to the multiple measurement vectors (MMV) framework by constructing a measurement matrix and an undersampled displacement matrix composed of multiple measurement snapshot vectors. The joint sparsity constraint is introduced to the coefficient matrix, promoting the same sparsity pattern across the representations of neighboring measurement snapshot vectors. This method leverages the inherent structural sparsity of the BTT signal frequency spectrum, thereby improving the accuracy of the frequency spectrum reconstruction and enhancing resistance to noise interference. To verify the effectiveness of the proposed method, numerical simulations are conducted under different signal-to-noise ratio (SNR) levels to compare the relative amplitude errors and the mean square error. Finally, experimental results from a spinning test rig further demonstrate that the method offers superior resistance to frequency aliasing, significantly improves blade natural frequency tracking accuracy, and enhances the robustness and precision of vibration frequency spectrum reconstruction compared to two existing methods based on SMV. Additionally, comparing computational efficiency reveals the advantages of the proposed method in batch processing of data.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112351"},"PeriodicalIF":7.9,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077532","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":"Adaptive data-driven method for modeling of frequency-dependent multiport systems","authors":"Xiang Xie ,&nbsp;Haijun Wu","doi":"10.1016/j.ymssp.2025.112381","DOIUrl":"10.1016/j.ymssp.2025.112381","url":null,"abstract":"<div><div>Frequency-dependent dynamical systems are commonly encountered in engineering applications, such as automobiles, high-speed trains, and aircraft fuselages. The equations of motion for these systems do not follow the standard second-order form typical for regular elastic structures. The frequency-dependent characteristics complicate the frequency sweep analysis of the underlying model, and also make the application of traditional projection-based model order reduction techniques difficult or even ineffective. In this work, a data-driven approach based on the Loewner realization framework combined with tangential interpolation is applied to reduce the high computational cost of numerical simulations of structural acoustic systems with multiple terminals, incorporating representative damping treatments. The entire construction process does not require information about the system matrices of the original full-order model and knowledge of the complex material properties; only frequency samples and the associated transfer functions between a given number of inputs and outputs are needed. Afterwards, a low-dimensional reduced model in the classical second-order form without a damping term is generated. Additionally, a bi-fidelity error indicator with a masking function is developed to iteratively determine the location of error-peak frequencies used in the next step, and to further minimize the total number of sample data required for convergence. The structural dynamics with add-on viscoelastic damping, exterior acoustic scattering problems modeled by the boundary element method, interior pure acoustic as well as vibro-acoustic systems with porous sound-absorbing materials are all investigated to demonstrate the simplicity, versatility, and efficiency of the proposed approach. This provides a unified data-driven framework to ease the computational complexity of frequency sweep analysis of multiport frequency-dependent dynamical systems.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112381"},"PeriodicalIF":7.9,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077549","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":"KDN: A class-added continual learning framework for cross-machine fault diagnosis with limited samples","authors":"Jipu Li ,&nbsp;Ke Yue ,&nbsp;Zhaoqian Wu ,&nbsp;Fei Jiang ,&nbsp;Canyang Jiang ,&nbsp;Weihua Li ,&nbsp;Shaohui Zhang","doi":"10.1016/j.ymssp.2025.112379","DOIUrl":"10.1016/j.ymssp.2025.112379","url":null,"abstract":"<div><div>Recently, data-driven methods have gained increasing prominence in the field of machinery intelligent fault diagnosis (IFD). Unfortunately, three main shortcomings of IFD models are exposed during the practical application process: (1) the new session necessitates a significant quantity of labeled fault samples; (2) the diagnostic model cannot maintain long-term diagnosis; (3) cross-machine fault diagnosis is not achievable. To overcome these drawbacks, a class-added continual learning framework based on Knowledge-informed Dual-branch Network (KDN) is proposed for continual fault diagnosis of mechanical equipment with limited samples. In particular, a category-knowledge distillation technique is employed to retain the diagnostic knowledge acquired from the previous session, while a knowledge-transfer regularization loss is applied to avoid overfitting of the diagnostic model. Furthermore, a self-adapting knowledge-weight allocation mechanism is introduced to automatically assign the relative weights of each loss function. In this way, the diagnostic model can continuously identify various fault categories, which substantially enhances its performance across different machines. Experiments on three rotating machinery datasets are conducted to validate the effectiveness and superiority of the proposed KDN. The experimental results demonstrate that the proposed KDN is capable of performing continual fault diagnosis on data from different machines, even with a limited number of samples in the new session.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112379"},"PeriodicalIF":7.9,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077550","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":"Bi-structural spatial–temporal network for few-shot fault diagnosis of rotating machinery","authors":"Zixu Chen ,&nbsp;J.C. Ji ,&nbsp;Qing Ni ,&nbsp;Benyuan Ye ,&nbsp;Xiaoxi Ding ,&nbsp;Wennian Yu","doi":"10.1016/j.ymssp.2025.112378","DOIUrl":"10.1016/j.ymssp.2025.112378","url":null,"abstract":"<div><div>Recently, many spatial–temporal diagnostic frameworks have been proposed to improve the few-shot diagnostic performance of rotating machinery through extracting inherent and generalized features. But most methods extract spatial and temporal features separately by stacking 1D convolution and temporal modules, which could decrease the spatial–temporal correlation and result in the loss of information. The emerging graph convolutional network (GCN) is adept at handling multi-channel data, providing a more powerful spatial feature extraction method. Therefore, it is worth extending spatial–temporal frameworks by incorporating GCN. However, the graphs in most GCN-based methods are constructed through single modeling strategy such as KNN-Graph or Radius-Graph, which may not exhibit high generalization in dealing with different datasets. To address these limitations and improve the diagnostic performance of rotating machinery in few-shot scenarios, a <strong>B</strong>i-<strong>S</strong>tructural <strong>S</strong>patial-<strong>T</strong>emporal <strong>N</strong>etwork (BS-STN) is proposed in this paper. Physic and function informed graphs with bi-structural inference paths, are introduced to obtain richer information through feature fusion. An adaptive inference fusion module is designed to dynamically adjust the contribution of fusion-view and single-view features to gradient descent, thereby avoiding potential overfitting caused by feature fusion. Multiple time-step graphs are connected by the same nodes to construct a temporal graph, which in combination with broadcast-based temporal and spatial embedding enable graph convolution to propagate temporal and spatial information synchronously, thus avoiding information loss and extracting inherent features. A thrust sliding bearing dataset is open-sourced, comprising multi-channel signals of normal, thrust pad wear and lubricating oil contamination. Experiments are conducted on two publicly available datasets and the self-collected sliding bearing dataset. The comparative analyses in different few-shot scenarios demonstrate the effectiveness and superiority of BS-STN. The source codes of the proposed method and the self-collected sliding bearing data are available at: <span><span>https://github.com/CQU-ZixuChen/BS-STN</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112378"},"PeriodicalIF":7.9,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077551","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":"3D-DIC full field experimental modal analysis of a demo airplane by using low-speed cameras and a reconstruction approach","authors":"Davide Mastrodicasa ,&nbsp;Emilio Di Lorenzo ,&nbsp;Simone Manzato ,&nbsp;Bart Peeters ,&nbsp;Patrick Guillaume","doi":"10.1016/j.ymssp.2025.112387","DOIUrl":"10.1016/j.ymssp.2025.112387","url":null,"abstract":"<div><div>Experimental Modal Analysis (EMA) has developed into a major technology for the study of structural dynamics in the past several decades. Through Experimental Modal Analysis, complex structure phenomena in structural dynamics can be represented using decoupled modes consisting of natural frequency, modal damping, and mode shapes. The dynamic properties of structures can be extracted from both forced and ambient vibration tests. Whether the object is a wind turbine blade rotating at a certain speed, a bridge sustaining traffic, or an airplane under wind excitation, Modal Analysis can be applied to provide insightful solutions. These tests are mainly performed using point-wise sensors connected to the structure. A limited number of transducers might not be able to comprehensively measure the dynamic response, especially when dealing with large-size or very small structures, lightweight components, or rotating structures. This is one of the reasons behind the development of image processing techniques, like Digital Image Correlation (DIC), to perform modal analysis. A particular field of interest in using DIC for vibration analysis is in using cheap, light, and low-speed cameras to detect a structure’s high-frequency behavior. Nevertheless, except for a few highly specialized and controlled scenarios, the effectiveness of camera-based EMA is constrained by the relatively low sampling frequency of cameras in contrast to accelerometers, strain gauges, and laser Doppler vibrometers. In this paper, we introduce an innovative acquisition method designed to estimate modal parameters beyond the Nyquist–Shannon limit (i.e., half of the camera’s frame rate). This is achieved through the utilization of periodic excitation and signal reconstruction techniques. As a result, it becomes feasible to reconstruct a high-sampled displacement signal using low-speed cameras. The accuracy of the methodology is numerically investigated by using a simple MDOFs system as a proof of concept. Furthermore, an experimental validation on a simple airplane mock-up is presented. The displacements are obtained using a stereo camera setup and then computed by DIC. Finally, they are combined with the force signal to compute the structure’s FRFs for the modal parameter estimation. Furthermore, the DIC estimated modal parameters are validated by using accelerometers mounted on the test structure, and a full field validation of the corresponding numerical model is presented.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112387"},"PeriodicalIF":7.9,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077534","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 new fully decoupled strategy for reliability optimization based on adaptive Kriging with improved efficient global optimization and weighted K-means clustering","authors":"Haizheng Song ,&nbsp;Huagang Lin ,&nbsp;Changcong Zhou ,&nbsp;Lei Li ,&nbsp;Zhufeng Yue","doi":"10.1016/j.ymssp.2025.112402","DOIUrl":"10.1016/j.ymssp.2025.112402","url":null,"abstract":"<div><div>Reliability-based design optimization (RBDO) is regarded as a more systematic approach to structural design that seamlessly combines reliability and design for optimization. However, the computational cost will be often substantial due to necessarily demanding reliability analysis during the optimization design procedure. This paper proposes a novel decoupling approach to effectively solve the RBDO problem. Based on the augmented reliability theory and Bayes’ rule, the failure probability function (FPF) is estimated through establishing a new adaptive Kriging model with an improved efficient global optimization (IEGO) and weighted K-means clustering (WKC). The WKC algorithm can effectively mitigate the clustering effect of the added sample points by partitioning original sample set into <em>K</em> clusters. Combined with IEGO, the sample points will be selected within each cluster that contribute the most to improving the Kriging model. This approach ensures the efficiency and accuracy of the adaptive Kriging model in estimating the FPF. The RBDO problem in which the probabilistic constraints are substituted using the estimated FPF can be fully decoupled into a deterministic optimization problem, and demonstrated as an enabling efficient solution. Thus, it is worth noting that the primary computational cost associated with the decoupling process arises from estimating the FPF. In this paper, the computational cost of solving the RBDO is significantly reduced by developing an adaptive Kriging model capable of estimating the FPF accurately and efficiently. One numerical example and three practical engineering applications are employed to demonstrate the accuracy and efficiency of the proposed method compared to other methods.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112402"},"PeriodicalIF":7.9,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077533","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":"Enhanced representation of the nonlinear dynamic characteristics of ball screw feed drive system through developing a three-state model","authors":"Min Wan ,&nbsp;Jia Dai ,&nbsp;Hui Tian ,&nbsp;Xue-Bin Qin ,&nbsp;Wei-Hong Zhang","doi":"10.1016/j.ymssp.2025.112371","DOIUrl":"10.1016/j.ymssp.2025.112371","url":null,"abstract":"<div><div>This paper develops a three-state model to represent the nonlinear dynamic characteristics of the ball screw feed drive system (BSFDS), including the impact of backlash during velocity reversal. The three states are distinguished as a rigid model during unidirectional motion, a rigid model capturing the backlash phenomenon during velocity reversal, and a flexible model capable of describing the torsional vibrations. Impact of backlash on friction and inertia is considered in the three-state model, with a special friction model established to depict the effect of backlash. To identify the parameters involved in the model, a recursive maximum likelihood (RML) algorithm is proposed, based on the distinct signals designed specially for exciting the three states. The accuracy of parameter identification is enhanced through the combined use of iterative learning (IL). Based on the identified friction results using the IL-based RML, the model parameters are finally determined through least squares fitting. Experiments and comparisons are conducted to verify the effectiveness of this work.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"227 ","pages":"Article 112371"},"PeriodicalIF":7.9,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077552","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}