Mechanical Systems and Signal Processing最新文献

{"title":"Bayesian filtering based prognostic framework incorporating varying loads","authors":"Luc S. Keizers ,&nbsp;R. Loendersloot ,&nbsp;T. Tinga","doi":"10.1016/j.ymssp.2024.111992","DOIUrl":"10.1016/j.ymssp.2024.111992","url":null,"abstract":"<div><div>Unexpected system failures are costly and preventing them is crucial to guarantee availability and reliability of complex assets. Prognostics help to increase the availability and reliability. However, existing methods have their limitations: physics-based methods have limited adaptivity to specific applications, while data-driven methods heavily rely on (scarcely available) historical data, which reduces their prognostic performance. Especially when operational conditions change over time, existing methods do not always perform well. As a solution, this paper proposes a new framework in which loads are explicitly incorporated in a prognostic method based on Bayesian filtering. This is accomplished by zooming in on the failure mechanism on the material level, thus establishing a quantitative relation between usage and degradation rates. This relation is updated using a Bayesian filter and measured loads, but also allows accurate degradation predictions by considering future (changing) loads. This enables decision support on either operational use or maintenance activities. The performance of the proposed load-controlled prognostic method is demonstrated in an atmospheric corrosion use case, based on a public real data set constructed from annual corrosion measurements on carbon steel specimens. The developed load-controlled particle filter (LCPF) is demonstrated to outperform a method based on a regular particle filter, a regression model and an ARIMA model for this specific scenario with changing operating conditions. The generalization of the framework is demonstrated by two additional conceptual case studies on crack propagation and seal wear.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 111992"},"PeriodicalIF":7.9,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427414","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":"Causality-Augmented generalization network with cross-domain meta-learning for interlayer slipping recognition in viscoelastic sandwich structures","authors":"Rujie Hou ,&nbsp;Zhousuo Zhang ,&nbsp;Jinglong Chen ,&nbsp;Zheng Liu ,&nbsp;Lixin Tu","doi":"10.1016/j.ymssp.2024.112023","DOIUrl":"10.1016/j.ymssp.2024.112023","url":null,"abstract":"<div><div>Accurate interlayer slipping recognition in viscoelastic sandwich structures (VSSs) is critical for mechanical equipment’s safety and reliability. However, significant domain shifts exist in VSSs data under variable working conditions, and domain data under certain conditions cannot be directly accessed during training. This renders conventional domain adaptation methods ineffective. To address the problems, we proposed causality-augmented generalization network (CGN) without accessing target domains for VSSs’ slipping recognition. CGN comprises a swin-transformer feature extractor and a capsule network classifier with an FC decoder. The feature extractor aims to fully extract discriminative features of VSSs data and promote their domain invariance across multiple domains. Building on this foundation, the classifier further extracts the underlying causal features associated with the labels and performs slipping recognition, thereby enhancing the model’s generalization and stability across various domains. The decoder serves as a regularizer to assist in learning meaningful representations of input data. Moreover, cross-domain <em>meta</em>-learning strategy is incorporated into the generalized training process to further strengthen the model’s generalization ability. The experiments on VSSs’ cross-domain datasets illustrate that CGN can be trained on some domains and directly tested on multiple unknown domains with desirable results, showing its effective generalization and stability for slipping recognition.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 112023"},"PeriodicalIF":7.9,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427922","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":"Vibration-based estimation of bolt tension in non-slender bolts using Timoshenko beam theory","authors":"Marie Brøns","doi":"10.1016/j.ymssp.2024.111985","DOIUrl":"10.1016/j.ymssp.2024.111985","url":null,"abstract":"<div><div>Many industrial applications apply non-slender bolts, from small bolts in machinery to large bolts in offshore structures. Ensuring the correct tension in such bolts is a significant problem. Recent work suggests a vibration-based approach for estimating bolt tension. The idea is to assume the bolt is an Euler–Bernoulli beam and measure the bending natural frequencies. When tightening the bolt, the frequencies increase. For non-slender bolts, the Euler–Bernoulli assumption is no longer valid. Therefore, a tensioned Timoshenko beam model with flexible boundary conditions is derived in this work. Derivation and investigation of a tensioned Timoshenko beam with boundary mass, inertia, and flexible boundary conditions is not well described in the literature. Besides the purpose of estimating tension, the investigation provides a fundamental understanding of how boundary conditions influence natural frequencies in the Timoshenko formulation, offering novel insights that may be useful in other applications. The Timoshenko model is incorporated into a previously applied parameter estimation method and validated by testing numerical scenarios of tightened bolts. Despite finding that non-slender bolts’ natural frequencies depend relatively less on tension than slender bolts, it is still possible to make estimations with an average deviation of less than 2%. Finally, to test that the Timoshenko model is a valid assumption, experiments are performed on a non-slender M72 bolt.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 111985"},"PeriodicalIF":7.9,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427920","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":"A deep learning-based spatial gradient reconstruction method for efficient damage identification in composite with high-sparsity Lamb wavefield","authors":"Dingcheng Ji ,&nbsp;Jing Lin ,&nbsp;Fei Gao ,&nbsp;Jiadong Hua ,&nbsp;Wenhao Li","doi":"10.1016/j.ymssp.2024.112018","DOIUrl":"10.1016/j.ymssp.2024.112018","url":null,"abstract":"<div><div>The structural integrity and safety of carbon fiber reinforced plastics (CFRP) are vulnerable to delamination, which is often imperceptible to the naked eye. Although the Scanning Laser Doppler Vibrometer (SLDV) has shown promise in damage quantification of CFRP, its time-consuming measurement process limits its application in engineering scenarios. To address this, we introduce a novel damage index, the spatial gradient, which captures the interaction between delamination and the wavefield. We have also developed a neural network capable of reconstructing the spatial gradient directly from high-sparsity Lamb wavefield data obtained at an extremely low spatial sampling rate, thereby significantly reducing measurement time. To enhance the network’s capability to detect wavefield anomalies, we employ the cross-attention technique, allowing for the direct injection of shallow features representing local wavefield distortions caused by damage into the decoder. Additionally, we integrate multiple reconstruction layers to guide the wavefield reconstruction process, ensuring meaningful information is captured at each stage. Our method achieves substantial improvements in reconstruction accuracy, increasing from 70 % to 92 % in single-damage scenario and from 14 % to 72 % in multi-damage scenario compared to the previous state-of-the-art techniques. By using the reconstructed spatial gradient field for damage imaging through spatial covariance analysis, our approach demonstrates its feasibility and generalizability across various damage locations. This suggests its potential as a reliable solution for fast and accurate damage characterization, reducing the measurement burden and enhancing practical applicability.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 112018"},"PeriodicalIF":7.9,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427919","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":"Non-contact vision-based response reconstruction and reinforcement learning guided evolutionary algorithm for substructural condition assessment","authors":"Guangcai Zhang ,&nbsp;Jiale Hou ,&nbsp;Chunfeng Wan ,&nbsp;Jun Li ,&nbsp;Liyu Xie ,&nbsp;Songtao Xue","doi":"10.1016/j.ymssp.2024.112017","DOIUrl":"10.1016/j.ymssp.2024.112017","url":null,"abstract":"<div><div>Structural health monitoring of large-span bridges and high-rise buildings is crucial for ensuring safety and serviceability. However, accurately capturing motion in these structures using consumer-grade cameras is challenging due to their limited Field of Vision (FOV). To address this issue, in this study, a novel output-only substructural condition assessment framework based on the reinforcement learning-guided evolutionary algorithm and vision-based displacement response reconstruction technique is proposed. On the one hand, displacement responses of the target substructure are extracted from the vibration video using subpixel template matching algorithm with camera pose correction, which is suitable for integration with substructure strategy to detect elemental damage. A vision-based substructural displacement response reconstruction technique is developed based on transmissibility matrix and Tikhonov regularization. The measured and reconstructed displacements are utilized to established the objective function. On the other hand, to solve the optimization-based damage identification problem, a new reinforcement learning guided evolutionary algorithm, named sparse Q-learning guided evolutionary algorithm (SQEA), is proposed. In the proposed SQEA, sparse initial population is produced by reducing the dimension of unknown parameters to be identified. Six different search strategies, including DE/rand/1, DE/rand/2, DE/best/1, DE/best/2, Jaya mutation, perturbation with the Cauchy mutation, are used to construct a search strategy pool. A representative reinforced learning algorithm, Q-Learning algorithm is introduced to adaptively select the most suitable search strategy. Experimental tests on a steel frame structure and a three-span beam structure are performed to validate the accuracy, efficiency, and robustness of the proposed approach. Results demonstrate that the damage locations and extents can be accurately identified without the measurement of input forces, expanding the application of low-cost vision-based displacement measurement in substructural condition assessment. Furthermore, the performance of the improved L-curve method over traditional L-curve and Bayesian inference regularization, the superiority of the proposed SQEA over other state-of-the-art intelligent algorithms are investigated.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 112017"},"PeriodicalIF":7.9,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427918","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 anti-occlusion vision-based method for structural motion estimation","authors":"Jiale Hou ,&nbsp;Yi Zhang ,&nbsp;Xinzheng Lu ,&nbsp;Enjian Cai ,&nbsp;Kai Wei ,&nbsp;Min Luo ,&nbsp;Jing Guo ,&nbsp;Zhanxiong Ma ,&nbsp;Hoon Sohn ,&nbsp;Tong Guo","doi":"10.1016/j.ymssp.2024.112003","DOIUrl":"10.1016/j.ymssp.2024.112003","url":null,"abstract":"<div><div>Structural displacement is an important metric in structural health monitoring (SHM). Computer vision-based methods have been widely used for structural displacement recognition in laboratory settings. However, the movement of natural objects such as pedestrians, vehicles, and other unrelated objects, may obstruct the selected structural targets for tracking, therefore reducing the accuracy of estimated displacements. To address this challenge, this paper proposes an anti-occlusion computer vision-based method to estimate structural displacements with subpixel-level accuracy. The proposed method can be divided into three steps. First, the correlation filter is used to continuously track the selected target despite occlusion. Next, the Gaussian mixture model (GMM)-based target modeling method is proposed to identify the occluded segments in each frame. Finally, the selected target is divided into multiple patches, and the subpixel-level displacements of unobstructed patches are estimated by the subpixel patch matching algorithm. The advantages of the developed method over traditional approaches are demonstrated in simulated cases and a shaking table test of a five-story stone curtain wall structure. Additionally, the developed method is applied in a bridge construction practice.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 112003"},"PeriodicalIF":7.9,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427405","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":"Crack imaging of underwater concrete components using interfacial waves and transducer array","authors":"Zijian Wang ,&nbsp;Kui Wang ,&nbsp;Qiangqiang Han ,&nbsp;Jingyuan Ni ,&nbsp;Zhishen Wu","doi":"10.1016/j.ymssp.2024.111998","DOIUrl":"10.1016/j.ymssp.2024.111998","url":null,"abstract":"<div><div>Existing methods to detect cracks on underwater concrete components are mainly based on sonar scanning and visual inspection. However, these methods are fundamentally limited by low illustration, aquatic plants, and suspended sediments. Therefore, interfacial waves are used to image a 0.1-mm-wide crack on an underwater concrete slab for the first time. The wave scattering and mode conversion phenomena at a water-filled crack are investigated. The incidence of Scholte waves and their reflection in the form of Rayleigh waves dominate the wave field and are selected to detect the crack. An imaging algorithm is proposed based on the interfacial waves and a transducer array. The absolute errors of crack localization are less than 7 mm with a detectable range of 0.4 × 0.4 m of a single measurement. The proposed method can provide key techniques to evaluate the integrity of underwater concrete structures, such as water dams, bridge piers, and water pipelines.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 111998"},"PeriodicalIF":7.9,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427400","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":"Source reconstruction for acoustic emission signals clustering and events nature identification. Application to a composite pipe bending test","authors":"Arnaud Recoquillay,&nbsp;Maël Pénicaud,&nbsp;Valentin Serey,&nbsp;Cyril Lefeuve","doi":"10.1016/j.ymssp.2024.111954","DOIUrl":"10.1016/j.ymssp.2024.111954","url":null,"abstract":"<div><div>This article deals with the application of clustering to acoustic emission data. Although many results are available in the literature for small scale applications showing clustering linking the clusters to the physical nature of the events, the performances are in general limited in large structures due to the effect of propagation on the characteristics of acquired signals. We propose here a methodology coupling source reconstruction, compensating the propagation, and clustering to recover the physical nature of the events. The methodology is exemplified on data from a bending test of a composite pipe, enabling the identification of matrix cracking, fiber debonding and fiber breakage where clustering directly on the data leads to data clustered based on the source–sensor distance.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 111954"},"PeriodicalIF":7.9,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427401","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":"Real-time full-field inference of displacement and stress from sparse local measurements using physics-informed neural networks","authors":"Myeong-Seok Go,&nbsp;Hong-Kyun Noh,&nbsp;Jae Hyuk Lim","doi":"10.1016/j.ymssp.2024.112009","DOIUrl":"10.1016/j.ymssp.2024.112009","url":null,"abstract":"<div><div>In this study, we propose a method to infer the displacement and stress of the entire domain using physics-informed neural networks (PINNs), utilizing locally measured strain data from strain sensors. To achieve this, we employed PINNs to constrain the solution field, ensuring that the solutions satisfy the laws of physics, including the force equilibrium equation, strain–displacement relationship, constitutive equation, and displacement and traction boundary conditions into the loss function of PINNs, as well as the loss functions of measurement data. The PINNs were trained with input features in terms of coordinates and measured strain data and corresponding output features in terms of displacement and stress associated with the strain. Finally, by plugging the measured strain data at specific points into the trained PINN model, the full-field displacement and stress can be inferred in real time at the millisecond level without retraining, even for arbitrary measured strain data.</div><div>To demonstrate the superiority of the proposed method, we analyzed linear elastic problems involving a two-dimensional rectangular plate with a hole and a center-cracked plate. As a result, it has been confirmed that the proposed method allows for accurate inference of the displacement and stress of the entire domain in real time from a limited set of measured strain data. Furthermore, it is noted that the unknown applied load was accurately predicted through integration of the inferred stress field.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 112009"},"PeriodicalIF":7.9,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427398","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":"Application of thermoelasticity in the frequency-domain multiaxial vibration-fatigue criterion","authors":"Jaša Šonc,&nbsp;Klemen Zaletelj,&nbsp;Janko Slavič","doi":"10.1016/j.ymssp.2024.112002","DOIUrl":"10.1016/j.ymssp.2024.112002","url":null,"abstract":"<div><div>In vibration fatigue, high-spatial-density experimental damage identification is hard to conduct. Fatigue damage is typically localized (in time and space) and loads can change direction with time. Thermoelasticity studies the interaction between temperature changes and elastic deformations in materials: minute changes in temperature can be related to the sum of the normal stresses, providing information about the multiaxial stress state. This research discusses the application of thermoelasticity in multiaxial criterion resulting in the equivalent uniaxial load. In this research, the thermoelasticity-based equivalent uniaxial load is related to the established theory on vibration-fatigue damage estimation in the spectral domain. The introduced thermoelasticity-based criterion is compared to the Equivalent von Mises stress criterion. Building on theoretical, numerical, and experimental research, this work examines the limitations of thermoelasticity-based criterion. Where the surface shear stresses are significantly smaller than the normal stresses, the numerical and experimental research shows promising results.</div><div>Based on the introduced thermoelastic multiaxial criterion and with the recent progress in thermal imaging and signal processing, new possibilities for a close-to-real-time full-field fatigue-damage estimation open up.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"224 ","pages":"Article 112002"},"PeriodicalIF":7.9,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427402","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}