IEEE Transactions on Reliability最新文献_第3页

An Interpretable and Reliable Remaining Useful Life Prediction Approach Across Different Machines With Tensor Domain-Adversarial Regression Adaptation 基于张量域-对抗回归自适应的机器剩余使用寿命预测方法

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-25 DOI: 10.1109/TR.2025.3547426

Wentao Mao;Jiayi Wang;Wen Zhang;Yuan Li;Panpan Zeng;Zhidan Zhong

{"title":"An Interpretable and Reliable Remaining Useful Life Prediction Approach Across Different Machines With Tensor Domain-Adversarial Regression Adaptation","authors":"Wentao Mao;Jiayi Wang;Wen Zhang;Yuan Li;Panpan Zeng;Zhidan Zhong","doi":"10.1109/TR.2025.3547426","DOIUrl":"https://doi.org/10.1109/TR.2025.3547426","url":null,"abstract":"This article tries to address the concerns about remaining useful life (RUL) prediction across machines: 1) what data from source domain contributes more to transfer prediction? and 2) is the information transfer reliable enough? This article proposes a novel fault mode-oriented deep tensor domain-adversarial regression adaptation approach to achieve interpretable RUL transfer prediction across machines. First, by integrating fault mechanism and degradation characteristics, a new fault mode-oriented significance indicator (FSI) is constructed based on tensor representation to evaluate the importance of degradation data from source domain. Second, a multisubdomains adversarial regression adaptation network, in which each subsource domain corresponds to a fault mode, is constructed to purposefully transfer the degradation knowledge from source domain. The domain discriminator for each subsource domain is adaptively weighted by FSIs that are updated in each round of adversarial training. An alternating optimization algorithm is then designed to find the optimal knowledge representation and transfer effect. Moreover, an upper bound of prediction error is derived for the proposed approach, which offers a theoretical guarantee for cross-machine prognostic task. Experimental results on three benchmark datasets empirically validate the proposed approach under fixed and varying working conditions, and can reveal fault modes' significance for more trustworthy prediction.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"4076-4090"},"PeriodicalIF":5.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unconsciously Continuous Authentication Protocol in Zero-Trust Architecture Based on Behavioral Biometrics 基于行为生物识别的零信任体系结构无意识连续认证协议

IF 5 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-21 DOI: 10.1109/TR.2025.3541224

Jung-San Lee;Tzu-Hao Chen;Chit-Jie Chew;Po-Yao Wang;Yun-Yi Fan

{"title":"Unconsciously Continuous Authentication Protocol in Zero-Trust Architecture Based on Behavioral Biometrics","authors":"Jung-San Lee;Tzu-Hao Chen;Chit-Jie Chew;Po-Yao Wang;Yun-Yi Fan","doi":"10.1109/TR.2025.3541224","DOIUrl":"https://doi.org/10.1109/TR.2025.3541224","url":null,"abstract":"Zero-trust architecture has received massive attention globally and been a significant development in the field of cybersecurity. Within zero-trust architecture, the continuous authentication (CA) strategy has been proposed to counter the network security threats posed by traditional static authentication mechanisms. However, most studies have focused on either device-to-device authentication or user authentication. This limitation results in risks of identity spoofing or credential theft despite the implementation of the CA mechanism, thus concluding the parity in significance between authenticating users and devices. Furthermore, considering the CA of users, it is essential to face the issue posed by user authentication fatigue. In response to these challenges, this work aims to introduce an unconsciously CA protocol (UCAP) based on zero-trust concepts and behavior biometrics. UCAP utilizes the behavior of keystroke dynamics as a main factor in consistently evaluating the user trust level. This method enables the continual updating of communication keys to preserve robust authentication of both devices and users. The robustness of UCAP has been examined through formal tools, while the experimental outcomes have shown satisfactory performance.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 2","pages":"2591-2604"},"PeriodicalIF":5.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Unified Model of DC Traction Power Supply System and Stray Current Dissipation 直流牵引供电系统的统一模型及杂散电流耗散

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-18 DOI: 10.1109/TR.2025.3546090

Wei Liu;Feilong Liu;Zhe Pan;Zhuoxin Yang;Jianbang Niu

{"title":"A Unified Model of DC Traction Power Supply System and Stray Current Dissipation","authors":"Wei Liu;Feilong Liu;Zhe Pan;Zhuoxin Yang;Jianbang Niu","doi":"10.1109/TR.2025.3546090","DOIUrl":"https://doi.org/10.1109/TR.2025.3546090","url":null,"abstract":"The problem of dc interference caused by stray currents in dc traction power supply system (DPS) is becoming increasingly serious. In order to study the interference degree of stray currents, a unified model of DPS and stray current dissipation based on the direct boundary element method (UBEM) has been established. The stray current collection network (SCCN) polarization potential is an important index to evaluate the leakage level of stray current. In this article, the relationship between SCCN polarization potential and rail-to-earth resistance (RE), train headways and longitudinal resistance of SCCN is investigated. It provides a partial theoretical basis and calculation method for stray current protection and system optimization. Field tests and CDEGS software simulations prove that UBEM is effective. The results show that UBEM is within 6.07% of the CDEGS simulation results and within 11.45% of the field test results. Taking the actual metro project in China as an example, SCCN polarization potential is only affected by local stray current. When RE>7.35 Ω·km, The average value of the SCCN polarization potential drops below 0.5 V.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"4194-4206"},"PeriodicalIF":5.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Condition-Based Operation and Maintenance Strategy for Load-Sharing Systems Based on Wiener Process 基于Wiener过程的负荷共享系统状态运维策略

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-13 DOI: 10.1109/TR.2025.3545037

Wei Chen;Songhua Hao

{"title":"Condition-Based Operation and Maintenance Strategy for Load-Sharing Systems Based on Wiener Process","authors":"Wei Chen;Songhua Hao","doi":"10.1109/TR.2025.3545037","DOIUrl":"https://doi.org/10.1109/TR.2025.3545037","url":null,"abstract":"As a distinctive redundant form in various practical applications, load-sharing systems consist of stochastically dependent units bearing system load altogether. Conventional load-sharing systems usually operate under an equal load allocation policy, and the system load is evenly distributed among all working units. However, this static policy neglects the individual dynamic and heterogenous characteristics during unit degradation processes, and leads to nonnegligible individual differences between unit reliability and lifetime distributions. Faced with this problem, this article proposes a novel condition-based operation and maintenance strategy for two-unit load-sharing systems. Each unit undergoes nonmonotonic continuous degradation following the Wiener process, and the system reliability is evaluated by considering a possible two-phase degradation process of the surviving unit once one unit fails. At each periodic inspection time, the system load is dynamically allocated by minimizing the Jensen–Shannon divergence between unit remaining useful lifetime distributions. Furthermore, a condition-based maintenance model is established according to semi-renewal process characteristics, along with specific theoretical analysis for the stationary distribution of system states. Compared with traditional operation and maintenance strategies, the effectiveness of the proposed strategy is validated through numerical experiments, and a practical case study of a two-cell lithium-ion battery pack illustrates robust economic benefit in dynamically adjusting the battery cell loads.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"4402-4416"},"PeriodicalIF":5.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ENADL: Towards Performance Improvement of IoT Networks Using Deep Learning-Based Node Fault Prediction ENADL：使用基于深度学习的节点故障预测来提高物联网网络的性能

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-13 DOI: 10.1109/TR.2025.3540891

Shraddha Tripathi;Faheem Nizar;Om Jee Pandey;Tushar Sandhan;Rajesh M. Hegde

{"title":"ENADL: Towards Performance Improvement of IoT Networks Using Deep Learning-Based Node Fault Prediction","authors":"Shraddha Tripathi;Faheem Nizar;Om Jee Pandey;Tushar Sandhan;Rajesh M. Hegde","doi":"10.1109/TR.2025.3540891","DOIUrl":"https://doi.org/10.1109/TR.2025.3540891","url":null,"abstract":"The Internet of Things (IoT) has grown explosively with wireless technology integration. Several IoT applications require high data throughput, low data transmission latency, and high data gathering reliability. Since, the IoT network (IoTN) is generally dynamic and utilizes a multi-hop data transmission scheme for such applications, the throughput, latency, and network lifetime tend to degrade as the hops increase. Moreover, IoT devices (IoD) are low-cost, less computationally capable, and battery-limited, further impacting performance. A faulty IoD worsens network lifetime and throughput. Predicting faulty nodes and re-routing data can significantly enhance performance. This work proposes a node fault prediction framework to enhance data routing in dynamic IoTN, maximizing throughput and lifetime. The network is represented as a graph in which the IoD are the nodes. Then a novel deep learning model is proposed utilizing various node and edge features to predict the faulty IoDs. Particularly, the proposed edge and node features-accumulation deep learning (ENADL) method exploits features, such as Euclidean distance between nodes, residual energy level of nodes, and type and number of messages passed between edges to predict the forthcoming faulty IoD. Thereafter, data routing is performed over the updated network topology. Furthermore, to improve the network lifetime, the node's degree and betweenness centrality measures-based energy allocation method is also proposed. Finally, numerical results on simulated and real-field testbeds demonstrate the ENADL method.s effectiveness in predicting faulty nodes and re-routing data packets. This results in maximized network throughput and lifetime as compared to several existing methods.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"3514-3528"},"PeriodicalIF":5.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Extended Gamma Process for Accelerated Destructive Degradation Test: Modeling and Optimal Design 加速破坏性退化试验的扩展伽玛过程：建模和优化设计

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-11 DOI: 10.1109/TR.2025.3544545

Man Ho Ling;Suk Joo Bae;Shengxin Jin;Hon Keung Tony Ng

{"title":"An Extended Gamma Process for Accelerated Destructive Degradation Test: Modeling and Optimal Design","authors":"Man Ho Ling;Suk Joo Bae;Shengxin Jin;Hon Keung Tony Ng","doi":"10.1109/TR.2025.3544545","DOIUrl":"https://doi.org/10.1109/TR.2025.3544545","url":null,"abstract":"Accelerated destructive degradation testing (ADDT) has become an invaluable method in reliability analysis, especially for highly reliable products. A common characteristic in many degradation studies is the presence of randomness in the initial degradation levels of testing units. Products with poor initial degradation levels tend to fail earlier. This study proposes an extended gamma process model that accommodates the random initial degradation value to accurately describe the degradation process over time. Under this modeling approach, we propose approximation methods for the conditional mean-time-to-failure (MTTF) and conditional variance of failure times to evaluate the impacts of initial degradation levels on product quality and reliability. We adopt a maximum likelihood approach to estimate the model parameters and MTTF under normal use conditions. In addition, we determine the optimal initial degradation threshold for removing poor-quality products and the proportion of products below this threshold. Based on the proposed model, the optimal ADDT plan is derived by minimizing the asymptotic variance of estimated MTTF under normal use conditions. A Monte Carlo simulation is conducted to assess the performance of the proposed inferential methods. Finally, a real-world ADDT dataset is analyzed to illustrate the proposed model and methodologies for making informed decisions on quality and reliability management.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"4387-4401"},"PeriodicalIF":5.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial: Applied AI for Reliability and Cybersecurity 社论：将人工智能应用于可靠性和网络安全

IF 5 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-04 DOI: 10.1109/TR.2025.3541482

Winston Shieh

引用次数: 0

IEEE Reliability Society Information IEEE可靠性协会信息

IF 5 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-04 DOI: 10.1109/TR.2025.3542309

引用次数: 0

UNA: Improving Automated PL-NL System by A Unified Neural Architecture 用统一的神经结构改进自动化PL-NL系统

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-04 DOI: 10.1109/TR.2025.3541087

Dawei Yuan;Tao Zhang;He Jiang

{"title":"UNA: Improving Automated PL-NL System by A Unified Neural Architecture","authors":"Dawei Yuan;Tao Zhang;He Jiang","doi":"10.1109/TR.2025.3541087","DOIUrl":"https://doi.org/10.1109/TR.2025.3541087","url":null,"abstract":"With the extensive application of artificial intelligence (AI) technologies, automated programming language-natural language (PL-NL) systems have gained significant attention, driving a series of related tasks served for developers and users, such as code search and summarization. Currently, mainstream PL-NL systems regard PL-NL as bimodal data and utilize two individual neural architectures (e.g., recurrent neural network) to learn the representation of PL-NL and build their semantic relations, improving the effects of these tasks. However, there exist two issues that limit the ability of these service systems in representation learning: first, large vocabularies cause data sparsity problems and limit the learning ability of neural architectures; second, there is not always a one-to-one correspondence between source code and natural language. To address these two issues, in this article, we introduce the unified neural architecture (UNA) by building a unified vocabulary (Uni-Vocab) at the subword level, to provide high-quality PL-NL services. In the Uni-Vocab, we build a unified modal encoding for PL-NL, which allows us to effectively control the vocabulary size and solve the data sparsity problem. Afterward, our built UNA can learn the unified contextual representation of PL-NL, which helps build their unified semantic relations. To validate the effectiveness of the proposed UNA, we perform experiments on code search and code summarization, which are two PL-NL tasks for developers and users. Experimental results demonstrate UNA can obtain noteworthy performance improvement. In detail, the baseline approaches in these two tasks get improvements by up to 36.09% and 18.02% in terms of mean reciprocal rank and bilingual evaluation understudy, respectively.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"3585-3599"},"PeriodicalIF":5.7,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Lightweight Triple-Stream Network With Multisensor Fusion for Enhanced Few-Shot Learning Fault Diagnosis 基于多传感器融合的轻量级三流网络增强少射学习故障诊断

IF 5.7 2区计算机科学

IEEE Transactions on Reliability Pub Date : 2025-03-03 DOI: 10.1109/TR.2025.3540500

Haotian Peng;Wei Wang;Jie Gao;Yu Wang;Jinsong Du

{"title":"A Lightweight Triple-Stream Network With Multisensor Fusion for Enhanced Few-Shot Learning Fault Diagnosis","authors":"Haotian Peng;Wei Wang;Jie Gao;Yu Wang;Jinsong Du","doi":"10.1109/TR.2025.3540500","DOIUrl":"https://doi.org/10.1109/TR.2025.3540500","url":null,"abstract":"The application of multiple sensors significantly enhances the accuracy of industrial fault diagnosis, but existing algorithms are structurally complex and rely heavily on extensive training data. To optimize the efficiency of diagnosis, this article proposes a lightweight time-frequency-statistical domain fusion network. The model comprises three data streams that analyze the time-domain, frequency-domain, and statistical features of vibration signals, employing an improved channel attention mechanism for weighted fusion. In addition, two model-agnostic few-shot enhancement strategies are introduced, aiming to improve accuracy where training samples are scarce by reducing signal sample variations and optimizing the distribution of signals in the feature space. By combining these techniques, the proposed method exhibits superior performance in few-shot learning on two datasets compared to other multisensor fusion methods, while also achieving higher computational speed. The results of this research are of significant importance in enhancing the fault diagnostic capabilities of multisensor systems in practical industrial applications.","PeriodicalId":56305,"journal":{"name":"IEEE Transactions on Reliability","volume":"74 3","pages":"4062-4075"},"PeriodicalIF":5.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0