Mechanical Systems and Signal Processing最新文献

{"title":"Frequency response data-based feedforward control strategy for ultra-precision tool servo diamond turning of freeform surfaces","authors":"Hao Wu ,&nbsp;YiXuan Meng ,&nbsp;DingKun Meng ,&nbsp;Rui Wang ,&nbsp;ZhiWei Zhu ,&nbsp;MingJun Ren ,&nbsp;XinQuan Zhang ,&nbsp;LiMin Zhu","doi":"10.1016/j.ymssp.2025.112706","DOIUrl":"10.1016/j.ymssp.2025.112706","url":null,"abstract":"<div><div>Tool servo diamond turning faces significant challenges when machining freeform surfaces at relatively high speeds, primarily due to tracking errors caused by the limited bandwidth of the servo axis. Integrating an additional feedforward controller with existing controllers is often necessary to enhance tracking performance. However, the design of a closed-loop inversion-based feedforward controller generally relies on an accurate transfer function of the controlled system, which is frequently compromised by unavoidable modeling errors. To address this issue, this paper proposes a novel frequency response data (FRD)-based feedforward control strategy for trajectory modification in tool servo diamond turning. This strategy directly utilizes the FRD to design a flexible-order finite impulse response filter that approximates the inverse behavior of the servo axis. A constrained optimization problem is formulated to obtain a flat amplitude and phase frequency response within the interested bandwidth, with the differential evolution algorithm adopted to determine the optimal filter parameters. Experimental validation on a commercial ultra-precision lathe confirms the effectiveness of the proposed strategy. Comparative results reveal a substantial enhancement in the form accuracy of the machined freeform surfaces, achieving a 70% reduction in the PV error and a 96% reduction in the RMS error compared to those obtained without the feedforward controller. The simplicity and efficiency of this strategy make it well-suited for industrial ultra-precision machining applications.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"232 ","pages":"Article 112706"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820308","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 antenna based on arbitrarily curved coding metasurface for three-dimensional beamforming","authors":"Xing-Yue Du ,&nbsp;A-Li Chen ,&nbsp;Yue-Sheng Wang","doi":"10.1016/j.ymssp.2025.112710","DOIUrl":"10.1016/j.ymssp.2025.112710","url":null,"abstract":"<div><div>Acoustic antennas with arbitrarily curved configurations have demonstrated flexibility and conformal adaptation in many applications, which are difficult to be matched with planar metasurfaces. Avoiding the constraints imposed by the high design cost of complex feed systems for conventional acoustic antennas, we propose here a design approach for coding metasurfaces with arbitrarily curved configurations to realize beamforming in arbitrary directions. The digitalization and programmability of coding notions provides a more convenient and intelligent approach for metasurface design and allows for the flexible modulation of the wavefield with only a limited variety of units. The three-dimensional (3D) far-field radiation form of the arbitrarily curved coding metasurface (ACCM) is derived theoretically, which characterizes the relationship between the expected radiation and coding patterns. The discrete particle swarm optimization (DPSO) algorithm is used as a reverse design channel for the coding patterns to realize the specific wavefield. Full wave simulations for ACCMs are implemented by the finite element method. The influences and advantages of the curved configurations for metasurface are discussed. Experimental verifications are also performed for the ACCM. The results show that the ACCM implements the acoustic wave antenna well by combining the coding concept with the reverse optimization design. The present study provides an important theoretical guidance for design of novel acoustic antenna devices.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"232 ","pages":"Article 112710"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817068","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":"Subwavelength resolution imaging of ultrasonic total focusing method by decoupling overlapped signals through back propagation neural network","authors":"Li Lin ,&nbsp;Haoyang Shen ,&nbsp;Siqi Shi ,&nbsp;Donghui Zhang ,&nbsp;Dongxin Fu ,&nbsp;Zhiyuan Ma","doi":"10.1016/j.ymssp.2025.112724","DOIUrl":"10.1016/j.ymssp.2025.112724","url":null,"abstract":"<div><div>The resolution, defined as the ability to distinguish two closely spaced defect, is one key criterion for evaluating ultrasonic imaging systems. The ultimate resolution of ultrasonic images is in the order of wavelength <em>λ</em> due to the Rayleigh criterion. In this paper, a Back Propagation Neural Network-Total Focusing Method (BPNN-TFM) is proposed for achieving subwavelength resolution imaging. In this method, the BPNN is trained to decouple overlapping signals from adjacent defect by predicting the times of arrival (ToAs) of defect waves, and the TFM performs delay-and-sum beamforming. Experimental data is collected through full matrix capture (FMC) from the aluminum alloy specimens that contain adjacent side-drilled holes (SDHs) with central distances ranging from 0.5<em>λ</em> to 1.0<em>λ</em>, and simulation models are established for data augmentation, totaling 54 sets of 55,296 A-scan signals. Twelve multi-domain features, commonly used in ultrasonic testing, are extracted from each A-scan signal as the input of the network. The prediction of ToAs for adjacent SDHs and reconstruction of high-resolution A-scan signals for TFM imaging are sequentially accomplished through BPNN optimized by genetic algorithm. The results demonstrate that the SDHs with a minimum central distance 0.5<em>λ</em> can be identified, and the resolution of BPNN-TFM is superior to the existing super-resolution imaging algorithms. Moreover, Shapley additive explanation (SHAP) is introduced to quantitatively analyze the relationship between twelve features and ToAs, and six high-contribution features are further selected. Finally, based on the simulation data, the ultimate resolution of BPNN-TFM in aluminum alloy is explored, and the applicability of the method is discussed by taking two SDHs with depth aberration and three SDHs arranged horizontally with 0.5<em>λ</em> central distances as case studies.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112724"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816741","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":"Study on the SOTIF of the intelligent heavy-duty truck localization module","authors":"Chao Chen ,&nbsp;Long Chen ,&nbsp;Le Zhou ,&nbsp;Jialong He ,&nbsp;Chuyan Xu ,&nbsp;Wenwen Chen ,&nbsp;Bang Jin ,&nbsp;Yuxin Zhang","doi":"10.1016/j.ymssp.2025.112719","DOIUrl":"10.1016/j.ymssp.2025.112719","url":null,"abstract":"<div><div>Safety of the Intended Functionality (SOTIF) refers to reducing unacceptable risks due to design inadequacies or performance limitations of intelligent systems. The localization module is a crucial component of the intelligent heavy-duty truck (HDT) automated driving (AD) system. Ensuring the SOTIF of this module is very important for HDT. Therefore, this paper conducts an in-depth SOTIF analysis of the localization module by identifying the performance limitations and triggering conditions of the Inertial Measurement Unit (IMU), Light Detection and Ranging (LiDAR), and Global Positioning System (GPS) within the module. Based on this analysis, a SOTIF model for the localization module is proposed. Using the KAIST dataset, abnormal signal injection methods are employed to simulate abnormal data signals caused by sensor performance limitations. The designed SOTIF model is compared with the federated Kalman multi-sensor fusion localization module model. The results demonstrate that the SOTIF model outperforms the federated Kalman multi-sensor fusion model in terms of performance and meets the SOTIF requirements. This is significant for ensuring the SOTIF of the localization modules in AD systems.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"232 ","pages":"Article 112719"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820306","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 recurrent neural network-based monitoring system using time-sequential molten pool images in wire arc directed energy deposition","authors":"Fengyang He ,&nbsp;Lei Yuan ,&nbsp;Haochen Mu ,&nbsp;Junle Yang ,&nbsp;Donghong Ding ,&nbsp;Huijun Li ,&nbsp;Zengxi Pan","doi":"10.1016/j.ymssp.2025.112733","DOIUrl":"10.1016/j.ymssp.2025.112733","url":null,"abstract":"<div><div>Directed energy deposition (DED) is a widely utilized additive manufacturing technique, with wire arc directed energy deposition (WA-DED) being a notable variant, particularly for producing medium to large-sized metal parts in industries such as aerospace and maritime. However, due to the inherent instability of the WA-DED process, even with optimized deposition parameters, subtle internal defects that significantly impact part structural integrity may still occasionally occur. To ensure the quality and reliability of high-end and high-valued parts, developing an effective monitoring system to detect defects and eliminate substandard products is a significant research focus. Thus, this research proposes a novel monitoring system for WA-DED, utilizing recurrent neural network algorithmic structures and time-sequential molten pool images. The system consists of three critical modules: (i) data pre-processing, using fast Fourier transform and low-pass filter for noise reduction; (ii) data augmentation, employing a time-sequential image data augmentation algorithm with vector quantized variational autoencoder (VQVAE) for feature extraction and conditional generative adversarial network (CGAN) for generating new datasets; (iii) classifier construction, developing an algorithm based on the convolutional long short-term memory (ConvLSTM) algorithmic structure to construct a classifier. The proposed monitoring system demonstrates near real-time performance with an average monitoring latency of approximately 0.02 s per time-sequential image group. The effectiveness of the proposed monitoring system is validated by its application in defect detection within a real-world aircraft winglet part. The defect spectrums of each case are generated based on the detection results, which intuitively show the category and location of the potential defects. The detection accuracies on internal defects and severe defects are 94.25% and 93.76% respectively. The result demonstrates the system’s superior ability to identify various types of defects with high accuracy and reliability in fabricating complex parts.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"232 ","pages":"Article 112733"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820305","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":"Analysis of gas foil thrust bearing considering manufacturing errors: Modeling and experiments","authors":"Jianhua Chu ,&nbsp;Siyu Wu ,&nbsp;Jiyu Wang ,&nbsp;Yuanding Wang ,&nbsp;Songtao Wang ,&nbsp;Fangcheng Xu","doi":"10.1016/j.ymssp.2025.112698","DOIUrl":"10.1016/j.ymssp.2025.112698","url":null,"abstract":"<div><div>The performance of gas film thrust bearings (GFTBs) can be affected significantly by manufacturing errors. However, there is a lack of systematic quantification methods and numerical models for these errors. This paper aims to address this situation. A simple yet effective approach has been proposed to represent the manufacturing error − pad thickness − based on real measurements of 15 sets of GFTBs. A numerical correction model has been developed to analyze the effect of the pad thickness difference on the static characteristics of GFTBs. The findings indicate that discrepancies in pad thickness can significantly reduce the bearing load capacity. Additionally, experiments were conducted to verify the accuracy of the model and to analyze the correlation among pad thickness, wear, and surface roughness. The results demonstrate a significant enhancement in pad thickness uniformity after the tests, along with an effective reduction in surface roughness, even to within 0.2 μm. This work presents a new approach to improve the accuracy of numerical modelling of GFTBs.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"232 ","pages":"Article 112698"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817067","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 dynamic load identification method with unknown load locations using modal force reconstruction and iterative optimization","authors":"Zhengshu Wang,&nbsp;Jinhui Jiang","doi":"10.1016/j.ymssp.2025.112721","DOIUrl":"10.1016/j.ymssp.2025.112721","url":null,"abstract":"<div><div>Accurately determining the location and magnitude of dynamic loads on a structure is crucial for solving or optimizing vibration issues. However, identifying the source of vibration through direct measurement is extremely challenging. Therefore, developing a rapid and accurate method for dynamic load location identification is essential. However, achieving rapid localization of multi-point excitation in continuous systems has been challenging due to the coupling relationship of their contributions to the response. This paper presents a novel method that can simultaneously identify the location and magnitude of dynamic loads acting on the structure under multi-point excitation. A “Modal-based Dynamic Load Location Identification” framework is proposed, analyzing the influence of dynamic load locations on the structural dynamic response. The relationship between system acceleration response and modal loads is constructed using numerical integration through the Newmark explicit method, thereby determining the modal loads of various orders in the vibration system. By converting the relationship between physical space loads and modal loads, a modal load residual fitness function is established. The fitness function is iteratively optimized using genetic algorithm to determine the load location, achieving rapid localization of dynamic loads under multi-point excitation. Subsequently, the computational efficiency of dynamic load identification is analyzed. Simulation results indicate that this method reduces the identification time of dynamic loads under the condition of unknown load locations to the same order of magnitude as when the load location is known, significantly improving the computational efficiency of load location identification. Moreover, it can be effectively applied to various types of load conditions, demonstrating high accuracy and excellent robustness to noise. To further verify the performance of the algorithm in practical engineering, experimental studies on dynamic load identification were conducted on a simply supported beam system, and the results confirm that the algorithm is effective. Additionally, the influence of measurement locations and Newmark parameters on the identification accuracy is discussed.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112721"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816744","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":"Nonlinear vibration energy harvesting-suppressing simulating and experimental research of a two-layer beam system by utilizing a vibration energy harvesting-suppressing module","authors":"Yuhao Zhao ,&nbsp;Xiaohong Mi ,&nbsp;Cunhong Yin ,&nbsp;Mingfei Chen ,&nbsp;Hangyu Wu","doi":"10.1016/j.ymssp.2025.112731","DOIUrl":"10.1016/j.ymssp.2025.112731","url":null,"abstract":"<div><div>Beams and their coupling structures are inevitably subjected to undesirable vibrations. Investigating vibration harvesting and suppression technologies for beams is crucial for addressing vibration-related issues encountered in engineering applications. This study explores the potential of using nonlinear energy sinks for both harvesting and suppressing the vibration energy of complex beam structures. A novel nonlinear vibration energy harvesting-suppressing module was designed for this purpose, with a coupling nonlinear energy sink as its key component. The experimental investigation, guided by theoretical analysis and the characteristics of the designed module, evaluates the vibration suppression and energy harvesting capabilities of a two-layer beam system. The results indicate that the designed module exhibits notable nonlinear behavior. Theoretical analysis reveals that the vibration energy harvesting-suppressing module can be classified into two types of devices, with their specific operational characteristics, roles, vibration suppression, and energy harvesting effects determined by the parameters of the key component. Experimental findings confirm the feasibility of the module, demonstrating its ability to simultaneously suppress and harvest vibration energy from the two-layer beam system. In conclusion, this research presents a novel vibration energy harvesting-suppressing module, offering an innovative solution for integrated vibration suppression and energy capture in engineering applications.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112731"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816743","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":"High-Dimensional Bayesian inference for model updating with neural likelihood approximator powered by dimensionality-reducing flow-based generative model","authors":"Jice Zeng ,&nbsp;Wang-Ji Yan","doi":"10.1016/j.ymssp.2025.112688","DOIUrl":"10.1016/j.ymssp.2025.112688","url":null,"abstract":"<div><div>Bayesian model updating provides a principled approach to approximating the posterior probability density function (PDF) of model parameters using incomplete and noisy data. However, the likelihood function is usually intractable, and evaluating it remains computationally prohibitive, especially for high-dimensional structural models. In this study, a novel Bayesian model updating framework is proposed that integrates a neural likelihood approximator (NLA) with a dimensionality-reduction flow-based generative model. The aim is to efficiently estimate the PDF of model parameters. The framework employs a masked autoregressive flow combined with a surjective neural network to map high-dimensional modal data into a simpler latent space. This transformation allows for the representation of the complex likelihood function with high accuracy and reduced computational cost. Specifically, the NLA learns the mapping between a multivariate standard Gaussian distribution and complex modal data through a sequence of invertible transformations conditioned on model parameters. This task is particularly challenging in structural dynamics because modal shapes can be highly sensitive to slight changes in model parameters and are often high-dimensional, making it difficult to capture their intricate relationships with the underlying physical system. Additionally, by enabling rapid computation of the log-likelihood, the framework significantly accelerates posterior estimation through the learned NLA combined with a prior distribution via Markov Chain Monte Carlo (MCMC). The proposed method is validated through case studies on an 18-story shear building and a steel pedestrian bridge, where modal data with dimensions of 342 and 220, respectively, are predicted, and the posterior distributions of 18 and 15 model parameters are estimated. The results demonstrate the capability of the proposed method to predict complex modal shapes and provide accurate posterior estimates.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112688"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816746","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":"Transformer model combining cross-attention and self-attention guided by damage index for pipeline damage localization based on helical guided waves","authors":"Hong Zhang ,&nbsp;Guoxiang Wang ,&nbsp;Feiyu Teng ,&nbsp;Shanshan Lv ,&nbsp;Lei Zhang ,&nbsp;Faye Zhang ,&nbsp;Mingshun Jiang","doi":"10.1016/j.ymssp.2025.112669","DOIUrl":"10.1016/j.ymssp.2025.112669","url":null,"abstract":"<div><div>The structural health monitoring technology based on ultrasonic guided waves (UGW) has broad application prospects in pipeline structural damage detection. This paper proposes a Transformer model based on damage index (DI) guidance and fusion of cross- attention and self-attention (DCAS-Transformer). Firstly, based on the principle of damage and guided waves, the DI representing the correlation between healthy signals and damaged signals is calculated and used as a weight to guide subsequent model training. This step enhances the correlation between signals and space. Secondly, based on cross-attention mechanism, a channel attention module is constructed to jointly input DI and signals into the module, achieving feature fusion and further emphasizing information related to damage. Finally, in the transformer module, based on its unique spatial attention mechanism, deep damage information extraction is achieved and damage localization is completed. The results show that the average localization error is 9.6 mm and the relative error is 1.92 %, and the proposed method performs well under different sensor layouts and noise levels. Compared with other deep learning methods, the proposed method has more stable performance and better generalization.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112669"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816742","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}