Reliability Engineering & System Safety最新文献_第10页

A robust source-free unsupervised domain adaptation method based on uncertainty measure and adaptive calibration for rotating machinery fault diagnosis 基于不确定性测量和自适应校准的鲁棒无源无监督域适应方法，用于旋转机械故障诊断

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-01 DOI: 10.1016/j.ress.2024.110516

{"title":"A robust source-free unsupervised domain adaptation method based on uncertainty measure and adaptive calibration for rotating machinery fault diagnosis","authors":"","doi":"10.1016/j.ress.2024.110516","DOIUrl":"10.1016/j.ress.2024.110516","url":null,"abstract":"<div><div>Unsupervised domain adaptation (UDA), usually trained jointly with labeled source data and unlabeled target data, is widely used to address the problem of lack of labeled data for new operating conditions of rotating machinery. However, due to the expensive storage costs and growing concern about data privacy, source-domain data are often not available, leading to the inapplicability of UDA. How to perform domain adaptation in scenarios without access to the source data has become an urgent problem to be solved. To this end, we propose a robust source-free unsupervised domain adaptation method based on uncertainty measure and adaptive calibration for fault diagnosis. The method only requires the use of the lightweight source model and unlabeled target data, which provides a new possibility to deploy domain adaptation models on resource-limited devices with good protection of data privacy. Specifically, based on proposed channel-level and instance-level uncertainty measures, adaptive calibration of source-domain model knowledge and target-domain risk samples during domain transfer is performed to attenuate the effect of negative transfer. Then, entropy minimization and target-domain diversity loss are introduced to redistribute the target samples and realize domain adaptation. Extensive cross-domain diagnostic experiments on two datasets demonstrate the effectiveness of the proposed method.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421430","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}

引用次数: 0

Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures 考虑不确定性和机组故障的分布式资源能源系统的随机两阶段多目标机组承诺

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-01 DOI: 10.1016/j.ress.2024.110520

{"title":"Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures","authors":"","doi":"10.1016/j.ress.2024.110520","DOIUrl":"10.1016/j.ress.2024.110520","url":null,"abstract":"<div><div>Compared to centralized generation technology, distributed energy resource systems are susceptible to energy risks caused by boundary uncertainties and unit failures. This study introduces a stochastic two-stage multi-objective optimization method to address reliability-based unit commitment issues. In the day-ahead stage, operational state and reserve capacity are determined to minimize prescheduled operation costs based on forecasted parameters. In the real-time stage, a decision-dependent stochastic reliability method is proposed to simulate outage scenarios. Reserve resources within available units are allocated to mitigate forecasting errors and unit failures. Additionally, the grid interaction ratio and penalty cost are added to restrict the depth and frequency access to the grid. Four comparative cases analyze the effects of the proposed methodology. This method innovatively achieves the simulation of stochastic multi-unit outages and delete faulty units in the operation scheme. The optimal results show that the risks of electricity and cooling supply are underestimated, while the risks of heating are overestimated, compared to N-1 reliability. Furthermore, Pareto analysis of the multi-objective problem enhances independent operational capacity through utilization of reserve resources. Grid dispatch pressure is reduced since purchased power can be used as day-ahead planning. Thus, the methodology achieves collaborative optimization of reliability with a reduction of operation costs, offering effective guidance for engineering applications.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421428","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}

引用次数: 0

Tensile capacity degradation of randomly corroded strands based on a refined numerical model 基于改进数值模型的随机腐蚀钢绞线抗拉能力退化研究

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-30 DOI: 10.1016/j.ress.2024.110512

{"title":"Tensile capacity degradation of randomly corroded strands based on a refined numerical model","authors":"","doi":"10.1016/j.ress.2024.110512","DOIUrl":"10.1016/j.ress.2024.110512","url":null,"abstract":"<div><div>In this study, we develop a sophisticated numerical model to analyze the axial tension behavior of seven-wire steel strands subjected to corrosion by employing the ANSYS finite element software. The axial tensile performance of steel strands subjected to random corrosion is examined, and the model's accuracy is validated by comparing it with experimental results. The corrosion degree in the steel strands is quantified by the mass loss rate <em>χ</em>, which denotes the ratio of the mass lost due to corrosion to the total mass. The reduction factor <em>θ</em> is employed to characterize the diminished axial tensile performance of the steel strands following corrosion. Two corrosion modes under random corrosion in steel strands were proposed, with lower bound formulas for the <em>θ-χ</em> distribution derived for each. In Mode I, the largest corrosion depth is prespecified. Mode II is characterized by destructive cross-sectional corrosion. As the corrosion intensifies, the corrosion pits can expand indefinitely across the wire's cross-section, potentially leading to significant loss or complete corrosion of a section of the steel strand. The finite element analysis indicates that the wire diameter and the corrosion pit depth affect <em>θ-χ</em>. The element size, steel strand length, and lay length have minimal impact.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421438","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}

引用次数: 0

Resilience evaluation of train control on-board system considering component failure correlations: Based on Apriori-Multi Layer-Copula Bayesian Network model 考虑组件故障相关性的列车控制车载系统弹性评估：基于 Apriori-Multi Layer-Copula Bayesian Network 模型

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-28 DOI: 10.1016/j.ress.2024.110514

{"title":"Resilience evaluation of train control on-board system considering component failure correlations: Based on Apriori-Multi Layer-Copula Bayesian Network model","authors":"","doi":"10.1016/j.ress.2024.110514","DOIUrl":"10.1016/j.ress.2024.110514","url":null,"abstract":"<div><div>The failure of complex system components is an important factor affecting system resilience, and it is not only affected by their own basic life parameters, but may also be affected by the failure of other components. In order to investigate the impact of component failure correlations on the resilience evaluation of Train Control on Board System (TCOBS), we propose the Apriori-Multi Layer-Copula Bayesian Network (AMLCBN) model. Firstly, the definition and evaluation function of TCOBS component resilience are provided. Then, build a TCOBS Bayesian Network and perform hierarchical processing on the network to clarify the position of Copula functions in the Bayesian Network. The Copula function is used to evaluate the correlations among component failures, and the Copula Bayesian Network is used to infer TCOBS resilience. We use Apriori to calculate the correlation coefficient matrix in the Copula function. Finally, a case study is conducted by taking CTCS-3OBS as an example, the results show that among the components of TCOBS, BTM Ant has low resilience and high importance. Considering the correlation among component failures, the TCOBS resilience evaluation results will increase, and those components with higher importance will become more important, while those with lower importance will become less important.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421437","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}

引用次数: 0

A novel cross-entropy-based importance sampling method for cumulative time-dependent failure probability function 基于交叉熵的重要度抽样新方法，适用于随时间变化的累积失效概率函数

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-28 DOI: 10.1016/j.ress.2024.110511

{"title":"A novel cross-entropy-based importance sampling method for cumulative time-dependent failure probability function","authors":"","doi":"10.1016/j.ress.2024.110511","DOIUrl":"10.1016/j.ress.2024.110511","url":null,"abstract":"<div><div>Cumulative time-dependent failure probability function (C-T-FPF) can reflect the effects of distribution parameters of random inputs and the upper bound of service time interval, which vary in their design domains, on time-dependent failure probability. However, solving C-T-FPF involves a time-consuming triple-layer framework. Thus, we propose an efficient method by combining cross-entropy-based importance sampling (IS) with adaptive Kriging model (CE-IS-AK). The innovations of CE-IS-AK include two aspects. Firstly, we construct a space augmented by both distribution parameters and the upper bound of service time interval, on which the triple-layer framework is decoupled to a single-layer one. And in the augmented space, an optimal IS density is proposed to reduce the required candidate sample size for estimating C-T-FPF. Secondly, we employ Gaussian mixture model (GMM) to approximate the optimal IS density, and the parameters in GMM are determined by minimizing the cross entropy of GMM and the optimal IS density. Moreover, to reduce the model evaluations in the proposed method, Kriging model is adaptively embedded to replace the actual model, and a first failure instant based learning function is proposed to train Kriging model adaptively. Due to the proposed single-layer framework and IS strategy assisted by the Kriging model, the efficiency is greatly improved for estimating C-T-FPF, which is validated by several examples.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420987","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}

引用次数: 0

Standby and inspection policy optimization in systems exposed to common and operational shock processes 优化受普通和运行冲击过程影响的系统的待机和检查策略

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-21 DOI: 10.1016/j.ress.2024.110509

{"title":"Standby and inspection policy optimization in systems exposed to common and operational shock processes","authors":"","doi":"10.1016/j.ress.2024.110509","DOIUrl":"10.1016/j.ress.2024.110509","url":null,"abstract":"<div><div>Motivated by practical applications like data storage, product defect detection, medical imagining, and sensing, this paper puts forward a new inspected standby system model where only one element can be online operating and only one element can stay in the standby mode at any time. Both operating and standby elements are exposed to random common shocks, causing their deterioration and even failures. The operating element may also be deteriorated by random operational shocks. The system undergoes periodic inspections to determine the refill of the operating or standby element. A new optimization problem is formulated and solved to determine the inspection and standby element addition policy with the objective to minimize the expected mission cost (EMC) attributed to factors including system downtime, number of inspections, element modes and failures, element activation and mode transitions. A new and efficient system state transition-based numerical algorithm is proposed to evaluate the EMC. A case study of a standby sensor system is provided to demonstrate the proposed model and impacts of several cost parameters as well as shock rates on the EMC and the optimal inspection and standby element addition policy, leading to insightful managerial guidelines for the system design and operation.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327517","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}

引用次数: 0

A study of neural network-based evaluation methods for pipelines with multiple corrosive regions 基于神经网络的多腐蚀区域管道评估方法研究

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-19 DOI: 10.1016/j.ress.2024.110507

{"title":"A study of neural network-based evaluation methods for pipelines with multiple corrosive regions","authors":"","doi":"10.1016/j.ress.2024.110507","DOIUrl":"10.1016/j.ress.2024.110507","url":null,"abstract":"<div><div>In recent years, significant developments have been made in methods for assessing the remaining strength of corroded pipelines. However, existing methods have limitations as they mainly focus on the local impact of corrosion defects. This study explores evaluation methods using neural networks to predict the ultimate resistance of pipelines containing multiple corrosive regions. Firstly, based on the validated method, the study generates a dataset comprising 3,000 corroded pipeline models and pixelates the corrosion information of these models via digital images. Then, three neural network evaluation frameworks are constructed: a Multilayer Perceptron (MLP) using the overall corrosion matrix, an MLP based on corrosion feature parameters, and Convolutional Neural Networks (CNN) based on corrosion images. Following this, the study analyzes the relationship between various corrosion parameters and failure pressure, compares the training effectiveness of the three neural network methods, and validates the accuracy and applicability of the proposed approach. The results indicated that various corrosion features should be considered when evaluating corroded pipelines, particularly depth. In addition, all three neural network-based methods show improved applicability and reliability compared to traditional evaluation methods, with CNN-image having the highest evaluation accuracy (correlation coefficient = 0.9564, average error = 3.46%).</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142310895","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}

引用次数: 0

A framework for post-windstorm functional recovery of non-residential buildings applied to hospitals 适用于医院的非住宅建筑风灾后功能恢复框架

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-19 DOI: 10.1016/j.ress.2024.110508

{"title":"A framework for post-windstorm functional recovery of non-residential buildings applied to hospitals","authors":"","doi":"10.1016/j.ress.2024.110508","DOIUrl":"10.1016/j.ress.2024.110508","url":null,"abstract":"<div><div>This study introduces a framework for recovery-based design in wind engineering. Currently, research is well advanced to implement this approach in earthquake engineering, with the scope of improving the resilience of structures and critical infrastructure, to achieve a durable and re-occupiable built environment after the occurrence of a disaster, and estimating downtimes and quantifying service disruption. The concept of interdependencies between the nonstructural components (building envelope) and a building’s functions is realized using Fault-Tree Analysis (FTA). Using this method allows the construction of fragility curves of systems of components and services using information as weights to reduce epistemic uncertainties, and a hypothetical recovery curve for the functionality of building services based on exposure to the hazard’s impact on the building envelope. The recovery process established here highlights the fundamental importance of accurate estimation of service losses. The methodology is applied to 4 hospitals located in different climatic regions in the United States surveyed using the database of EYP Architecture & Engineering. The analysis showed the importance of building design factors; such as the location of services relative to the envelope, number of stories, and the Window-to-Wall Ratio as significant influences on the risk of service disruption and recovery.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327518","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}

引用次数: 0

Joint optimization of production, inspection, and maintenance under finite time for smart manufacturing systems 智能制造系统有限时间内生产、检测和维护的联合优化

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-18 DOI: 10.1016/j.ress.2024.110490

{"title":"Joint optimization of production, inspection, and maintenance under finite time for smart manufacturing systems","authors":"","doi":"10.1016/j.ress.2024.110490","DOIUrl":"10.1016/j.ress.2024.110490","url":null,"abstract":"<div><p>Given the flexible and configurable characteristics of smart manufacturing systems with a limited time per manufacturing task, the assumption of infinite time for prostems is no longer applicable to the joint-control strategy. Consequently, a joint-control model that considers production, inspection, and maintenance within a finite-time scenario for smart manufacturing systems is proposed in this paper. The objective is to optimize overall production and maintenance functions to minimize the total system cost. Comparing the joint strategy under infinite time with the proposed finite-time approach reveals significant differences in unit costs between the two scenarios. To enhance the effectiveness of the model, a discrete iterative algorithm with multiple loops was developed. Through a case study, it was observed that 1) joint strategies implemented within a finite time horizon were more cost-effective than those under infinite time, thus emphasizing the need for business managers to develop strategies within a finite time frame; 2) different production planning and efficiency levels had varying effects on the final joint strategy, necessitating customized strategies based on different production durations. Overall, the research gap regarding joint strategies within a finite-time context was addressed in this research, serving as a methodological foundation for practitioners to develop various strategies that minimize total costs across diverse real-world scenarios.</p></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142241343","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}

引用次数: 0

Systems driven intelligent decision support methods for ship collision and grounding prevention: Present status, possible solutions, and challenges 防止船舶碰撞和搁浅的系统驱动智能决策支持方法：现状、可能的解决方案和挑战

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-09-17 DOI: 10.1016/j.ress.2024.110489

{"title":"Systems driven intelligent decision support methods for ship collision and grounding prevention: Present status, possible solutions, and challenges","authors":"","doi":"10.1016/j.ress.2024.110489","DOIUrl":"10.1016/j.ress.2024.110489","url":null,"abstract":"<div><p>Despite advancements in science and technology, ship collisions and groundings remain the most prevalent types of maritime accidents. Recent developments in accident prevention and mitigation methods have been bolstered by the rise of autonomous shipping, digital technologies, and Artificial Intelligence (AI). This paper provides an exhaustive review of the characteristics of fleets at risk over the past two decades, emphasizing the societal impacts of preventing collisions and groundings. It also delves into the key components of decision support systems from a ship's perspective and undertakes a systematic literature review on the foundations and applications of systems-driven decision support methods for ship collision and grounding prevention. The study covers risk analysis, damage evaluation, and ship motion prediction methods from 2002 to 2023. The conclusions indicate that modern ship science methods are increasingly valuable in ship design and maritime operations. Emerging multi-physics systems and AI-enabled predictive analytics show potential for future integration into intelligent decision support systems. The strategic research challenges include (1) underestimating the impacts of real operational conditions on ship safety, (2) the inherent limitations of static risk analysis and finite numerical methods, and (3) the need for rapid, probabilistic assessments of damage extents. The demands and trends suggest that leveraging big data analytics and rapid prediction methods, underpinned by digitalization and AI technologies, represents the most feasible way forward.</p></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0951832024005611/pdfft?md5=763730cc89b0d2cd9a7b51ad787ca26f&pid=1-s2.0-S0951832024005611-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142270808","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}

引用次数: 0