Reliability Engineering & System Safety最新文献

{"title":"An integrated dual-scale similarity-based method for bearing remaining useful life prediction","authors":"Wenjie Li ,&nbsp;Dongdong Liu ,&nbsp;Xin Wang ,&nbsp;Yongbo Li ,&nbsp;Lingli Cui","doi":"10.1016/j.ress.2024.110787","DOIUrl":"10.1016/j.ress.2024.110787","url":null,"abstract":"<div><div>As a pivotal technology of Prognostic and Health Management, the remaining useful life (RUL) prediction techniques significantly contribute to predictive maintenance and ensure the safe operation of mechanical equipment. Nevertheless, the current similarity-based prediction (SBP) methods face challenges in effectively utilizing the degradation information encapsulated within a limited number of degradation samples. Therefore, an integrated dual-scale similarity-based prediction (IDS-SBP) method is proposed bearing RUL prediction, which can fully mine the degradation information of the samples from two distinct time scales. Specifically, a whole lifecycle dynamic model is constructed to describe the various long-term degradation processes for bearings, which enriches the variety of the performance degradation samples. Subsequently, the dual-scale matching strategy is designed to extract the degradation information from two different time scales. Meanwhile, the designed lifetime calibration technique can calibrate the lifetime of samples by considering the degradation rate. Finally, the uncertainty analysis is conducted to integrate the prediction results at different time scales, thereby achieving the comprehensive evaluation of test bearings. Several sets of experimental data are applied to verify the prediction performance of the proposed method, and prediction results confirm that the proposed method achieves great prediction accuracy and superior generalization ability.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110787"},"PeriodicalIF":9.4,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148909","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 imperfect maintenance model for multi-component systems","authors":"Victor Hugo Resende Lima ,&nbsp;Lucas Frederico Alves Ribeiro ,&nbsp;Cristiano Alexandre Virgínio Cavalcante ,&nbsp;Phuc Do","doi":"10.1016/j.ress.2024.110768","DOIUrl":"10.1016/j.ress.2024.110768","url":null,"abstract":"<div><div>This paper introduces a model for managing imperfect maintenance in multi-component systems, and addresses the Selective Maintenance Problem with the inclusion of perfect preventive and corrective actions. Another significant contribution is our proposal of a heuristic that aims to provide nearly optimal solutions to this intricate problem. Our model prioritizes efficient resource utilization, taking into account positive economic and structural dependencies among system components. Furthermore, we introduce a virtual age reduction model that uses real age, historical imperfect actions, and the ratio of imperfect to perfect actions. Additionally, a cutting-edge system performance indicator is perfectly aligned with the multi-mission approach, and aims at sustained long-term efficiency. Effectiveness is measured by a metric that integrates post-maintenance reliability and maintenance cost, showcasing resilience in evaluating the performance of selective maintenance. To address the problem's complexity, we introduce a heuristic algorithm that produces compelling outcomes, with a relative error of less than 0.25 % in most instances.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110768"},"PeriodicalIF":9.4,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148912","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":"Optimal activation of components exposed to individual and common shock processes in asynchronous multi-phase missions","authors":"Gregory Levitin ,&nbsp;Liudong Xing ,&nbsp;Yuanshun Dai","doi":"10.1016/j.ress.2024.110789","DOIUrl":"10.1016/j.ress.2024.110789","url":null,"abstract":"<div><div>Many real-world systems operate in random shock environments, where system components may be exposed to different individual shock processes and some shocks may affect and deteriorate multiple components simultaneously. The existing studies typically considered either individual or common shock processes, but not both. This paper makes contribution by modeling and optimizing a multi-attempt multi-phase mission system subject to both individual and common shocks. System components are functionally equivalent, but heterogeneous in performance, cost, and shock resistance. Thus, their activation schedule may impact the mission success probability (MSP) and expected mission losses (EML). An optimization problem is formulated and solved, which finds the optimal component activation schedule (CAS) to minimize the EML. The solution method encompasses a new numerical recursive algorithm of evaluating the MSP and EML and an implementation of the genetic algorithm based on a proposed CAS solution representation. The proposed model is demonstrated using a case study of a cargo delivery mission performed by multiple aerial vehicles flying along different routes undergoing different shock processes during different phases. Effects of the mission failure penalty, allowed mission time, and common shock rate on mission performance and on the optimal CAS solutions are also examined using the case study.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110789"},"PeriodicalIF":9.4,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148930","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 two-stage Weibull-gamma degradation model with distinct failure mechanism initiation and propagation stages","authors":"Jian Zhou ,&nbsp;Zhanhang Li ,&nbsp;Hani Nassif ,&nbsp;David W. Coit","doi":"10.1016/j.ress.2024.110773","DOIUrl":"10.1016/j.ress.2024.110773","url":null,"abstract":"<div><div>Degradation models have become important analytic tools for industrial systems. In this paper, a new two-stage stochastic degradation model is introduced with separate failure mechanism initiation and propagation stages. The new degradation model represents an important advancement in degradation modelling by considering the degradation initiation stage or delay before active degradation propagation is observed. The new model consists of a time-to-event distribution that describes failure initiation or delay in the first stage, concluding when the degradation propagation stage is initiated, which indicates the beginning of the second stage, where degradation is modelled using a stochastic process. The combination of a time-to-event distribution and a stochastic degradation model is realistic and is presented considering three different scenarios: degradation with no residual degradation during Stage 1 or no alarm-threshold, degradation with a deterministic alarm-threshold, and degradation with a random alarm-threshold. A Weibull distribution is adopted for the first degradation initiation stage, and a gamma process is used for the second degradation stage. This model is consistent with many physical failure mechanisms, where there is a time delay before the failure process begins to propagate. This is not surprising because designers often introduce design preventions (e.g., protective coatings) to delay the onset of degradation. In our model, both degradation stages can be accelerated by increasing stresses which are then modelled using a set of covariates and acceleration factors. To demonstrate the model, a bridge steel rebar case study is presented and discussed. Based on extensive experiments and data, reliability analysis and accelerated failure mechanism investigation are performed using the proposed model. The results demonstrate that the new model provides advantages for estimating reliability and physically describing the two stages. It can be concluded that the proposed model is useful for reliability assessment and accelerated degradation test planning.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110773"},"PeriodicalIF":9.4,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143149546","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":"Resilience-based seismic safety evaluation of pile-supported overhead transmission lines under depth-varying spatial ground motions","authors":"Juncai Liu ,&nbsp;Qingtong Jin ,&nbsp;You Dong ,&nbsp;Li Tian ,&nbsp;Zinan Wu","doi":"10.1016/j.ress.2024.110783","DOIUrl":"10.1016/j.ress.2024.110783","url":null,"abstract":"<div><div>Despite the persistent emphasis on the significance of soil-structure interaction (SSI) in the seismic analysis of overhead transmission lines (OTLs), Previous studies on seismic safety of OTLs have typically utilized base-fixed constraints and uniform ground motion inputs, which may result in unreasonable estimations. In light of this observation, this paper aims to evaluate the SSI effect on the seismic safety of a pile-supported OTL exposed to depth-varying spatial ground motions (DVSGMs) from a resilience perspective. Initially, a refined finite element (FE) model is developed for the OTL, meticulously incorporating the buckling and post-buckling effects of steel members. Subsequently, a suite of three-dimensional DVSGMs is stochastically generated considering layered soil properties and ground motion propagation laws. Through systematic exploration, this study investigates the SSI effect on the dynamic responses, fragility probabilities, and resilience metrics of the OTL under DVSGMs. The findings highlight that compared to scenarios where tower legs are directly fixed to the ground, incorporating SSI can yield adverse responses of the OTL and contribute to an increasing uncertainty in its seismic resilience with higher excitation intensities. This research advocates for the integration of SSI and depth-varying spatial effect into the seismic resilience assessment of OTLs.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110783"},"PeriodicalIF":9.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143149551","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":"Domain adaptation method based on pseudo-label dual-constraint targeted decoupling network for cross-machine fault diagnosis","authors":"Congying Deng ,&nbsp;Hongyang Tian ,&nbsp;Jianguo Miao ,&nbsp;Zihao Deng","doi":"10.1016/j.ress.2024.110786","DOIUrl":"10.1016/j.ress.2024.110786","url":null,"abstract":"<div><div>In recent years, domain adaptation methods have gained widespread traction for addressing domain-shift problems caused by distribution discrepancy across different domains in fault diagnosis. Nonetheless, the significant variations in data distribution among cross-machine scenarios present obstacles to extracting domain-invariant features, ultimately leading to suboptimal recognition performance. To tackle this issue, a novel domain adaptation method based on pseudo-label dual-constraint targeted decoupling network is proposed. Initially, the targeted decoupling network (TDNet) is presented, employing a decoupling strategy that integrates convolutional feature channel separation with feature-targeted constraints. This strategy aims to extract domain-invariant features while alleviating the directional biases introduced by excessive constraints. Subsequently, the pseudo-label dual-constraint feature alignment (PDFA) method is introduced to effectively utilizes pseudo-label information. The PDFA minimizes confusion in pseudo-labels within the target domain while enforcing alignment constraints on concatenated pseudo-label features, ensuring efficient and precise cross-domain alignment while preserving inter-class discriminability. Additionally, batch attention (BA) is introduced to learn the intricate interdependencies among samples from the same batch, enriching feature representations to facilitate effective knowledge transfer. Experimental results based on twelve cross-machine tasks demonstrate the superiority of the proposed method in cross-machine fault diagnosis in comparison to existing domain adaptation techniques.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110786"},"PeriodicalIF":9.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148902","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 algorithm to search for multi-state minimal cuts in multi-state flow networks containing state heterogeneous components","authors":"Shuai Zhang ,&nbsp;Guanghan Bai ,&nbsp;Junyong Tao ,&nbsp;Yang Wang ,&nbsp;Bei Xu","doi":"10.1016/j.ress.2024.110774","DOIUrl":"10.1016/j.ress.2024.110774","url":null,"abstract":"<div><div>The reliability and resilience of multi-state flow networks (MFNs) are crucial for the safe operation of complex network systems, with the multi-state minimal cut (<em>d</em>-MC) method being fundamental for evaluating these metrics. Existing research mainly focuses on <em>d</em>-MC in MFNs with state weakly homogeneous components (SWHCs), where the state space consists of continuously increasing integers. However, real-world MFNs often include state heterogeneous components (SHCs). This study presents an algorithm to search for all multi-state minimal cuts (<em>d</em>-MC*) in MFNs with SHCs. The algorithm first defines <em>d</em>-MC* and its generation model, along with two methods to reduce candidates. A definition-based verification method for <em>d</em>-MC* candidates is also proposed. Then, a comprehensive comparison is conducted with existing approaches through both theoretical analysis and numerical experiments, illustrating the significant advantages of the new algorithm in terms of accuracy and efficiency for processing MFNs containing SHCs. Additionally, the selection of the optimal max-flow algorithm among three popular choices is analyzed. Finally, the practicality of the proposed <em>d</em>-MC* algorithm is demonstrated on a real-world network. This study fills the gap in existing research on MFNs containing SHCs and provides important theoretical support and guidance for the design, operation, and maintenance of network systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110774"},"PeriodicalIF":9.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148383","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":"Enhancing bearing life prediction: Sparse Gaussian process regression approach based on sequential ensemble and residual reduction for degradation prediction","authors":"WanJun Hou ,&nbsp;Yizhen Peng","doi":"10.1016/j.ress.2024.110788","DOIUrl":"10.1016/j.ress.2024.110788","url":null,"abstract":"<div><div>Bearings are critical components of wind turbines, and predicting their remaining useful life is essential for ensuring safe and reliable operation of wind power generators. However, the degradation of wind turbine bearings exhibits distinct multi-stage characteristics, and full-lifecycle degradation samples are rarely available. This lack of samples makes it challenging to accurately predict the service life of bearings. Therefore, we propose a residual-reduction sequential ensemble sparse Gaussian process regression model to enhance bearing life prediction. The proposed model introduces a primary learner based on a Gaussian process regression serial ensemble strategy, effectively simulating the multi-stage dynamic bearing degradation process. Building on this learner, the model constructs a secondary learner within the gradient-boosting framework by applying residual-reduction techniques to further increase predictive accuracy. The proposed method is applied to a public dataset and a real wind turbine bearing degradation dataset, and its superiority is validated through comparisons with existing methods.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110788"},"PeriodicalIF":9.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143148903","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":"Graph embedded patch-sense autoencoder with prior knowledge for multi-component system anomaly detection","authors":"Shen Liu ,&nbsp;Jinglong Chen ,&nbsp;Zijun Liu ,&nbsp;Jun Wang ,&nbsp;Z. Jane Wang","doi":"10.1016/j.ress.2024.110784","DOIUrl":"10.1016/j.ress.2024.110784","url":null,"abstract":"<div><div>For large-scale integrated systems, efficient anomaly detection is crucial in monitoring complex equipment. Interdependency among multiple components hinders the establishment of trust in system decision-making within multivariate time series. In this work, we propose a prior knowledge graph embedded patch-sense autoencoder (GEPAE), aiming to enable unsupervised anomaly detection in large-scale systems and provide a reference for anomaly localization. The proposed method learns from multi-source normal condition data to attain efficient and reliable anomaly detection. Diverging from pointwise reconstruction and evaluation, the proposed method employs unit-level patch embedding in the encoding module and patch correction in the decoding module, aiming to preserve data structure information by learning the global relationships among patches. System decision-making and component anomaly localization are subsequently conducted by Gaussian mixture density estimation of the patch embedding results. Meanwhile, prior knowledge of the physical entity structure and multi-sensor deployment is generalized and utilized for the model to obtain convincing decision-making. The proposed method is tested on two real-world data sets of liquid rocket engine systems and two fault simulation data sets of subway train transmission systems, and promising results demonstrate its validity and generality.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110784"},"PeriodicalIF":9.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143149548","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":"Modeling and vulnerability analysis of UAV swarm based on two-layer multi-edge complex network","authors":"Yuheng Yang ,&nbsp;Xing Guo ,&nbsp;Xingshuo Hai ,&nbsp;Qiang Feng ,&nbsp;Bo Sun ,&nbsp;Zili Wang","doi":"10.1016/j.ress.2024.110779","DOIUrl":"10.1016/j.ress.2024.110779","url":null,"abstract":"<div><div>Swarm systems of unmanned aerial vehicles (UAVs) have emerged as a popular subject of research on the Internet of Things owing to their higher flexibility, efficiency, and reliability than single UAVs. However, little research has been devoted to investigating the vulnerability of UAV swarms, and the traditional network model cannot fully and synchronously characterize their communication-based and mission-based relationships. This study proposes a two-layer multi-edge complex network model to characterize the UAV swarm by considering its status of communication and collaboration for the given mission. The model contains a communication layer and a function layer. In addition, we consider the area of coverage of the UAV swarm, provide the definitions and methods of calculation of three factors influencing its performance, and use them to develop a method to assess its performance for the three typical missions of attack, reconnaissance, and jamming. Furthermore, we propose a framework for the vulnerability analysis of the UAV swarm that can analyze its process of failure and measure its vulnerability. Finally, we use a swarm consisting of 10 UAVs as a case to verify the effectiveness and accuracy of the proposed model.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"256 ","pages":"Article 110779"},"PeriodicalIF":9.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143149547","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}