Mechanical Systems and Signal Processing最新文献

{"title":"On-board identification of wheel polygonization of metro trains based on convolutional neural network regression analysis and angular-domain synchronous averaging","authors":"Wenjing Sun ,&nbsp;Xuan Geng ,&nbsp;David J. Thompson ,&nbsp;Tengfei Wang ,&nbsp;Jinsong Zhou ,&nbsp;Jin Zhang","doi":"10.1016/j.ymssp.2025.112587","DOIUrl":"10.1016/j.ymssp.2025.112587","url":null,"abstract":"<div><div>Wheel polygonization, a form of wheel out-of-roundness, has become a common problem on trains of urban rail transit systems in recent years. It results in a significant increase of the dynamic responses of both the vehicle and the track, high vibration and noise levels, and structural fatigue. This paper proposes an innovative method for identifying wheel polygonization orders and their effective values using convolutional neural network (CNN) regression analysis. First, the acceleration signal measured on the axle box has been processed with the angular-domain synchronous averaging (ADSA) method, effectively separating the characteristic information associated with wheel polygonization within the signal. To extract comprehensive wheel polygonization information, a feature fusion method is employed, integrating features from both the time and frequency domain. Then, a CNN regression model is established and trained, with validation conducted using measured data of vehicle vibration and the wheel polygonization measured during field tests. Comparative analysis with different identification methods is performed, including a comparison of different preprocessing methods and machine learning models, which demonstrates the effectiveness of the proposed method in this study. The verification results show that the proposed method achieves high identification accuracy for wheel polygonization up to the 25th order. The overall average root mean square error value is 2.0 <!--> <!-->dB. Finally, the influence of wheel polygonization conditions, track stiffness, and speed fluctuation on the identification accuracy is discussed. The results show the proposed method exhibits robust identification capacity under varying conditions, which indicates its wide application and accuracy in complex situations during train service. This research contributes to advancing the field of wheel polygonization detection, offering a reliable and effective solution for application in railway systems.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112587"},"PeriodicalIF":7.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-dimensional optimized trapezoid self-convolution window for enhancing Moiré-based lithography alignment","authors":"Feifan Xu ,&nbsp;Chengliang Pan ,&nbsp;Jin Zhang ,&nbsp;Weishi Li ,&nbsp;Haojie Xia","doi":"10.1016/j.ymssp.2025.112590","DOIUrl":"10.1016/j.ymssp.2025.112590","url":null,"abstract":"<div><div>Classical windows are widely used in image processing to suppress spectral leakage. However, their limited effectiveness constrains their application in high-precision measurement tasks, such as lithography alignment based on Moiré fringe phase analysis. To address this limitation, this paper introduces an innovative two-dimensional optimized trapezoid self-convolution window (2D-OTSCW). This novel class of windows is generated through multiple time convolutions of an optimized trapezoid window, designed to achieve a narrow main lobe width of 6.89π/N and an optimal peak sidelobe level of − 31.6 dB by tuning the upper-to-lower base ratio (γ = 16 %). Theoretical analyses confirm that increasing the convolution order enhances the sidelobe suppression capability of 2D-OTSCWs, thereby mitigating spectral leakage. Additionally, the performance of the 2D-OTSCWs is evaluated against two extreme self-convolution windows (SCWs) (i.e., triangular and rectangular SCWs). Simulation and experimental results demonstrate the superior performance of 2D-OTSCWs over classical windows, which significantly enhances the phase extraction accuracy. This improvement enables alignment precision at an impressive sub-2-nm (1.86 nm) level, meeting the stringent requirements of next-generation lithography. This study not only introduces a robust window function design strategy for spectral analysis but also establishes a foundation for advancing high-precision alignment in lithography and related fields.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112590"},"PeriodicalIF":7.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643418","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 semi-analytical coefficient of restitution model based on new characteristics length and time for the nonlinear colliding viscoelastic particles","authors":"Gengxiang Wang ,&nbsp;Zepeng Niu ,&nbsp;Fuan Cheng ,&nbsp;Yongjun Pan","doi":"10.1016/j.ymssp.2025.112575","DOIUrl":"10.1016/j.ymssp.2025.112575","url":null,"abstract":"<div><div>The coefficient of restitution (CoR) is a critical parameter for predicting the impact behavior of colliding particles. This investigation aims to develop a novel CoR model for viscoelastic particles by incorporating improved characteristic length and time parameters. Initially, a new characteristic length is defined by considering energy dissipation during the compression phase of the impact process, providing a foundation for deriving the characteristic time in cases of damped impact behavior. Subsequently, a new equation of motion of colliding particles is formulated based on two new characteristic length and time. The approximate analytical solution of the new equation of motion is solved using Taylor expansion when considering energy dissipation during the compression phase. Likewise, the proposed motion equation is solved simultaneously based on the inverse collision method. The impact velocity of colliding particles can be obtained by combining two different solutions from the new equation of motion. Therefore, a new CoR model can be derived based on the definition of the Newtonian’s CoR. Moreover, the dimensionless maximum contact time during the compression phase is obtained based on the energy conservation of the whole compression phase. However, the new CoR model encounters a limitation when the impact velocity is zero as the denominator, which depends on impact velocity and the dimensionless maximum contact time leads to an undefined value. An infinitesimal quantity ε is introduced to the dimensionless maximum contact time to remove this issue, ensuring the CoR model remains finite when the impact velocity approaches or equals zero. Finally, the advantages of the new CoR model are demonstrated in comparison to existing CoR models. A series of experimental data involving metallic and non-metallic contact materials validates the accuracy and reliability of the proposed model.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112575"},"PeriodicalIF":7.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642958","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 co-modulation and hybrid resolution strategy (CHRS) for fault diagnosis of planetary gearboxes","authors":"Mian Zhang ,&nbsp;Ruitong Xie ,&nbsp;Tianbo Kang ,&nbsp;Jiwei Chen ,&nbsp;Yongshan Wang ,&nbsp;Xu Feng ,&nbsp;Mengxiong Zhao","doi":"10.1016/j.ymssp.2025.112573","DOIUrl":"10.1016/j.ymssp.2025.112573","url":null,"abstract":"<div><div>Planetary gearboxes (PGs) serve as vital transmission links in rotating machinery, and diagnosing faults within them is crucial for effective maintenance. Traditional deep learning methods often operate as ”black boxes,” offering limited transparency in interpreting results, especially when analyzing the complex vibration signals of PGs. To address this issue, this paper proposes a co-modulation model combined with a hybrid resolution strategy (CHRS), leveraging amplitude modulation (AM) and frequency modulation (FM) intensities, to enhance the interpretability of fault diagnosis. First, a more comprehensive and adaptable expression of the co-modulation model is developed to describe gear faults. Second, CHRS links the model’s generated signal with the actual monitoring data, establishing an intrinsic connection between the mathematical model and the data. An updating mechanism based on partial differential analysis is established for model parameter estimation. A partial differential-based updating mechanism is employed for model parameter estimation, enabling the quantitative analysis of model coefficients (including AM and FM), even with a limited number of training samples. Finally, the support vector machine (SVM) is employed to train and test these model parameters, facilitating the identification of different fault types through experimental data, thus validating the effectiveness of CHRS. In summary, CHRS significantly improves the interpretability of PG fault diagnosis by enhancing both the modeling process and quantitative analysis of vibration signals.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112573"},"PeriodicalIF":7.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643415","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 matrix completion technique for blade tip timing signal","authors":"Jiahui Cao ,&nbsp;Zhibo Yang ,&nbsp;Hongfei Zu ,&nbsp;Bo Yan ,&nbsp;Xuefeng Chen","doi":"10.1016/j.ymssp.2025.112565","DOIUrl":"10.1016/j.ymssp.2025.112565","url":null,"abstract":"<div><div>Blade tip timing (BTT) is a potential non-contact vibration measurement for rotating blades. Identifying characteristic parameters or recovering the (power) spectrum of vibrations for condition monitoring from BTT data is a critical issue in the actual application. However, due to the measurement principle and installation restrictions, BTT signal is severely undersampled and then is hard to be analyzed by traditional signal processing methods. To clear the obstacle caused by undersampling on the application of BTT, we proposed an enhanced matrix completion technique (EMCT) for BTT signal post-processing. EMCT contains two procedures: covariance (matrix) reconstruction and followed by parameter estimations. First, based on the finding that the covariance matrix of BTT data is a low-rank and symmetric positive semidefinite Toeplitz matrix, we develop a matrix completion algorithm to reconstruct covariance. Then, based on the reconstructed covariance matrix, we extract frequency and amplitude/power parameters using root-MUSIC and least square algorithms. Due to dual structural prior, EMCT performs better than covariance-based methods relying on a single prior in estimation accuracy and precision. More importantly, EMCT also shows potential in reducing the number of probes. In addition, due to its gridless nature, EMCT is free from the basis mismatch issue and can achieve continuous parameter estimation. Finally, the effectiveness of EMCT has been repeatedly validated by both simulations and experiments.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112565"},"PeriodicalIF":7.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643416","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 tunable electromagnetic stiffness with bistable, hardening and softening characteristics","authors":"Maksymilian Bednarek ,&nbsp;Bipin Balaram ,&nbsp;Jan Awrejcewicz","doi":"10.1016/j.ymssp.2025.112577","DOIUrl":"10.1016/j.ymssp.2025.112577","url":null,"abstract":"<div><div>Nonlinear stiffness elements have acquired wide application in recent years to augment the performance of systems like vibration absorbers, vibration isolators and energy harvesters. Hardening, softening, quasi-zero, bistable and multi-stable stiffness characteristics have been shown to improve system performance in a variety of contexts. Still, the main challenge to the wide use of nonlinear stiffness remains the difficulty in physically realising stiffness mechanisms with the desired load–displacement relationship. Even though a wide variety of physical mechanisms have been proposed, they typically have the disadvantage that in order to change the force amplitude value or the character of load–displacement curve, one or more components of the mechanism have to be changed by dismantling the assembly. Electromagnetic stiffness mechanisms make it easier to tune the force amplitude but are usually limited to a single load–displacement curve. The present article proposes an electromagnetic stiffness mechanism, based on a particular arrangement of permanent magnet and current carrying coil, which can be tuned very easily by varying the polarity and value of current through the coil. Just by varying the current through the coil, the proposed mechanism exhibits linear, hardening, softening and bistable stiffness characteristics. The construction of the mechanism is detailed and different stiffness properties are experimentally demonstrated. A closed form expression for stiffness force, which is in very good agreement with experimental curve, is arrived at, with magnet-coil parameters and current as variables. Analytical expression for threshold current values at which softening to hardening and bistable transition happens are obtained and experimentally validated. The method of multiple scales is used to arrive at an asymptotic solution of the oscillator with the proposed electromagnetic stiffness. This solution is also shown to be in excellent agreement with experimental values. A numerical study of dynamic properties are also carried out and experimentally validated.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112577"},"PeriodicalIF":7.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642957","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":"Acoustic-structure interaction-based identification for subsurface voids in steel-concrete composite structure: Experimental study and numerical simulation","authors":"Shiyu Gan ,&nbsp;Xin Nie ,&nbsp;Hongbing Chen ,&nbsp;Yuanyuan Li","doi":"10.1016/j.ymssp.2025.112595","DOIUrl":"10.1016/j.ymssp.2025.112595","url":null,"abstract":"<div><div>Steel-concrete composite structure (SCCS) has gained wide application in infrastructures for its excellent mechanical properties and reasonable economy, the structural integrity and service performance of which, however, are threatened by interfacial defects between steel and concrete. The detection methods focusing on vibration characteristics have demonstrated preferable effectiveness in detecting subsurface voids in SCCS compared to other non-destructive testing methods. This study provides a comprehensive understanding of the impact response (IR) method for detection in this regard, integrating theoretical analysis, experimental study, and multi-physics coupled numerical simulation with particular emphasis on considering acoustic-structure interaction. This coupling effect is confirmed to correlate with three-dimensional sizes of void defects, facilitating the identification of subsurface voids. A specimen is specially designed and subjected to IR tests to furnish results for experimental validation. The simulation results reveal frequency-splitting phenomena and distinct distributions of acoustic fields inside voids, which are attributed to acoustic-structure interaction. Noteworthy influences of void depth on the vibration characteristics of the structure are also highlighted, including apparent frequency deviation and redistribution of damping effect in modal analysis, as well as beat phenomena in transient analysis. Moreover, the identification of subsurface voids along with their depth is attained in practice by the proposed data analysis strategy based on attenuation characteristics of vibration response and waveform fitting. The findings of this study also underscore the significance of considering acoustic-structure interaction when analyzing vibration characteristics during interfacial defect detection in SCCS.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112595"},"PeriodicalIF":7.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643413","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":"S-WhiteSVDD: A feature fusion approach for diesel engine performance degradation assessment using Multi-Source impulse signals","authors":"Anzheng Huang ,&nbsp;Zhiwei Mao ,&nbsp;Fengchun Liu ,&nbsp;Xiangxin Kong ,&nbsp;Shenxiao Chen ,&nbsp;Jinjie Zhang ,&nbsp;Zhinong Jiang","doi":"10.1016/j.ymssp.2025.112589","DOIUrl":"10.1016/j.ymssp.2025.112589","url":null,"abstract":"<div><div>Performance degradation assessment (PDA) is a critical component of predictive health management (PHM). The mixed multi-source impulse characteristics of diesel engine vibration signals make PDA more challenging compared to rotating machinery. To address the unique characteristics of diesel engine signals, this study proposes a Subspace-Whitening Support Vector Data Description (S-WhiteSVDD) feature fusion approach that combines knowledge-based features with deep learning features. The method tracks cross-cycle variations of multiple homologous impulses and constructs a feature subspace for each impulse. Whitening transformation ensures balanced stretching and compression of subspace data across all components, preventing features with large variances from dominating the decision boundary. This approach aligns more closely with the data manifold and enables precise control of anomaly boundaries. To overcome the challenge of significant health indicator (HI) fluctuations that hinder early fault detection, the method integrates the interpretability of knowledge-based features with the complex mapping capabilities of deep features. This fusion enhances the richness of feature representation, facilitating the detection of early fault onset. The effectiveness and superiority of the proposed method are demonstrated through both valve degradation simulations and nozzle degradation engineering case studies. The constructed HI effectively indicates component degradation. The proposed approach shows strong potential for practical engineering applications.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112589"},"PeriodicalIF":7.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642632","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":"Improved deep transfer learning and transmission error based method for gearbox fault diagnosis with limited test samples","authors":"Hongbo Yang ,&nbsp;Zeyu Wang ,&nbsp;Miao Xu ,&nbsp;Dongpo Yang ,&nbsp;Zhifen Zhao","doi":"10.1016/j.ymssp.2025.112593","DOIUrl":"10.1016/j.ymssp.2025.112593","url":null,"abstract":"<div><div>As an important component of mechanical transmission system, gearbox state is critical to system safety and efficiency. The fault diagnosis of gearbox is of great significance for monitoring its operation states and identifying potential problems. Firstly, to improve the generalization ability of traditional fault diagnosis model and reduce the diagnostic loss for similar faults occurred in different conditions, an improved deep transfer learning network model is established based on deep subdomain adaptation method and residual feature extraction network. Then, taking a heavy commercial vehicle gearbox as research object, a dynamic simulation model considering its fault state is established, and the transmission error bench test is designed to verify the correctness of the model with different load torque. Finally, under the condition of limited test samples, a gearbox fault diagnosis method based on improved network model and simulation data is proposed and its effectiveness is verified through different comparative experimental tasks and evaluation metrics. The results show that, by using dynamic simulation data of gearbox transmission error, the established deep transfer learning model and proposed gearbox fault diagnosis method can obtain excellent diagnostic performance with high diagnosis precision and low training loss, and excessive test resource investment can be avoided effectively.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112593"},"PeriodicalIF":7.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643414","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":"Evaluation of the first-passage probability of non-stationary non-Gaussian structural responses with linear moments and copulas","authors":"Chao-Huang Cai ,&nbsp;Li-Zhong Jiang ,&nbsp;Zhao-Hui Lu ,&nbsp;Yu Leng ,&nbsp;Chun-Qing Li","doi":"10.1016/j.ymssp.2025.112553","DOIUrl":"10.1016/j.ymssp.2025.112553","url":null,"abstract":"<div><div>The evaluation of the first-passage probability of non-stationary non-Gaussian structural responses remains a great challenge in the field of random vibrations. In the present paper, a novel method is proposed for evaluating this first-passage probability, whose main contribution is to construct the joint probability density function (PDF) of the structural response and its derivative process under the consideration of their non-Gaussianities and nonlinear correlations. Cubic polynomial models of Gaussian process are developed to characterize the non-Gaussianities of the structural response and its derivative process, whose polynomial coefficients at each instant time are explicitly determined from their corresponding first four linear moments. These linear moments are accurately evaluated using a proposed method combining Sobol sequence with polynomial smoothing. The marginal PDFs and cumulative distribution functions (CDFs) of the structural response and its derivative process are then derived from these polynomial models. Based on Akaike information criterion (AIC) and the marginal CDFs, the optimal copula function at each instant time is selected to capture the linear/nonlinear correlation between the structural response and its derivative process. And thus, the joint PDF is constructed and the first-passage probability is evaluated. The applicability of the proposed method is validated by several numerical examples. It can be concluded that the proposed method provides satisfactory results in evaluating the linear moments, fitting probability distributions, and estimating the first-passage probabilities of non-stationary non-Gaussian structural responses.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112553"},"PeriodicalIF":7.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636709","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}