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

Machine learning-based outlier detection for pipeline in-line inspection data 基于机器学习的管道在线检测数据离群点检测

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-12 DOI: 10.1016/j.ress.2024.110553

Muhammad Hussain, Tieling Zhang

{"title":"Machine learning-based outlier detection for pipeline in-line inspection data","authors":"Muhammad Hussain, Tieling Zhang","doi":"10.1016/j.ress.2024.110553","DOIUrl":"10.1016/j.ress.2024.110553","url":null,"abstract":"<div><div>Pipeline companies are facing challenges in maintaining the integrity and reliability of their pipelines. They are working towards predictive maintenance using machine learning-based approaches to predicting anomalies. Training machine learning models requires sufficient data. Data quality is therefore becoming important because inaccurate data will lead to an inaccurate or wrong decision on pipeline condition assessment and the following management. This research paper intends to address the data quality issues of pipeline inspection data such as in-line inspection (ILI) data using machine learning models. Different machine learning models developed by random forest regression, linear regression, and nearest neighbors’ methods were tested to detect outliers in the ILI data. In this paper, the ILI data collected from an oil pipeline over a period of 22 years was applied to testing and analysis. To verify the outlier detection results of machine learning models, we used statistical analysis including Z-score method to check and find if there are any gaps in the analysis. It verifies that all these methods show almost the same or very similar results for the detection of the outliers. Hence, this study presents a robust method for the field applications in the pipeline industry.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"254 ","pages":"Article 110553"},"PeriodicalIF":9.4,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527450","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

Resilience-Based Restoration Model for Optimizing Corrosion Repair Strategies in Tunnel Lining 优化隧道衬砌腐蚀修复策略的复原力修复模型

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110546

Qian Zhang , Yaoqi Nie , Yanliang Du , Weigang Zhao , Shujie Cao

{"title":"Resilience-Based Restoration Model for Optimizing Corrosion Repair Strategies in Tunnel Lining","authors":"Qian Zhang , Yaoqi Nie , Yanliang Du , Weigang Zhao , Shujie Cao","doi":"10.1016/j.ress.2024.110546","DOIUrl":"10.1016/j.ress.2024.110546","url":null,"abstract":"<div><div>In tunnel engineering, the corrosion of steel rebar is a critical factor leading to structural degradation and failure, causing a decline in load-bearing capacity, deformation, and cracking. For decision-makers, identifying the optimal timing for tunnel maintenance and selecting effective repair strategies is of paramount importance. This study introduces a resilience-based restoration model to analyze tunnel failure due to corrosion throughout its service life and to optimize the timing and selection of maintenance strategies. The model generates time-variant failure curves by constructing limit equilibrium equations. The entropy weight method is employed to quantify and weight the impact of various failure modes, determining the timing for maintenance when the failure curve exceeds a predefined threshold. Additionally, the model's uncertainty is effectively reduced through regular inspections and Bayesian updating methods, enhancing prediction accuracy. The study further incorporates a resilience index and a benefit index to provide a quantitative assessment of maintenance plans, assisting decision-makers in selecting the optimal strategy. By exemplifying the model with a case study of steel rebar corrosion in a tunnel, this paper demonstrates the model's applicability and offers a new scientific approach for quantitative maintenance decision-making in tunnel engineering.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110546"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442856","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

Efficient reliability analysis of generalized k-out-of-n phased-mission systems 广义 k-out-of-n 相位任务系统的高效可靠性分析

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110581

Guizhuang Chen , Yuliang Hu , Chaonan Wang , Zhitao Wu , Wenjing Rong , Quanlong Guan

{"title":"Efficient reliability analysis of generalized k-out-of-n phased-mission systems","authors":"Guizhuang Chen , Yuliang Hu , Chaonan Wang , Zhitao Wu , Wenjing Rong , Quanlong Guan","doi":"10.1016/j.ress.2024.110581","DOIUrl":"10.1016/j.ress.2024.110581","url":null,"abstract":"<div><div>A <span><math><mi>k</mi></math></span>-out-of-<span><math><mi>n</mi></math></span> phased-mission system (PMS) is a PMS where the system structure is <span><math><mi>k</mi></math></span>-out-of-<span><math><mi>n</mi></math></span>: G in each phase. This paper investigates <span><math><mi>k</mi></math></span>-out-of-<span><math><mi>n</mi></math></span> PMSs with phase-<em>K</em>-out-of-<em>N</em> requirement, where the entire mission is successful if at least <em>K</em> out of the <em>N</em> phases achieve success. Such system is referred to as a generalized <span><math><mi>k</mi></math></span>-out-of-<span><math><mi>n</mi></math></span> PMS (<span><math><mi>k</mi></math></span>/<span><math><mi>n</mi></math></span>-GPMS). The <span><math><mi>k</mi></math></span>/<span><math><mi>n</mi></math></span>-GPMSs are prevalent in applications such as satellites, unmanned aerial vehicles (UAVs), wireless sensor networks and so on. In this paper, a novel method based on multi-valued decision diagram (MDD) is proposed to analyze the reliability of <span><math><mi>k</mi></math></span>/<span><math><mi>n</mi></math></span>-GPMSs, where the number of available components <em>n</em>, the required number of components <em>k</em>, and the components failure behaviors in different phases may vary. Distinguishing from the traditional phase-by-phase MDD generation method, the proposed method considers the behavior of all phases simultaneously and generates only one MDD model in a top-down manner. To illustrate the application of the proposed method, the reliability and the sensitivity of a four UAVs system which conducts supplies delivery mission is analyzed. The complexity analysis is performed. The correctness and efficiency are verified and demonstrated by several case studies. The proposed method is also compared with Monte Carlo simulation method.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110581"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446050","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 benchmark on uncertainty quantification for deep learning prognostics 深度学习预报学的不确定性量化基准

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110513

Luis Basora , Arthur Viens , Manuel Arias Chao , Xavier Olive

{"title":"A benchmark on uncertainty quantification for deep learning prognostics","authors":"Luis Basora , Arthur Viens , Manuel Arias Chao , Xavier Olive","doi":"10.1016/j.ress.2024.110513","DOIUrl":"10.1016/j.ress.2024.110513","url":null,"abstract":"<div><div>Reliable uncertainty quantification on RUL prediction is crucial for informative decision-making in predictive maintenance. In this context, we assess some of the latest developments in the field of uncertainty quantification for deep learning prognostics. This includes the state-of-the-art variational inference algorithms for Bayesian neural networks (BNN) as well as popular alternatives such as Monte Carlo Dropout (MCD), deep ensembles (DE), and heteroscedastic neural networks (HNN). All the inference techniques share the same inception architecture as functional model. The performance of the methods is evaluated on a subset of the large NASA N-CMAPSS dataset for aircraft engines. The assessment includes RUL prediction accuracy, the quality of predictive uncertainty, and the possibility of breaking down the total predictive uncertainty into its aleatoric and epistemic parts. Although all methods are close in terms of accuracy, we find differences in the way they estimate uncertainty. Thus, DE and MCD generally provide more conservative predictive uncertainty than BNN. Surprisingly, HNN achieve strong results without the added complexity of BNN. None of these methods exhibited strong robustness to out-of-distribution cases, with BNN and HNN methods particularly susceptible to low accuracy and overconfidence. BNN techniques presented anomalous miscalibration issues at the later stages of the system lifetime.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110513"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446047","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

An integrated method of extended STPA and BN for safety assessment of man-machine phased-mission system 用于人机相控任务系统安全评估的扩展 STPA 和 BN 综合方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110569

Xin Lu , Shengkui Zeng , Jianbin Guo , Wei Deng , Mingjun He , Haiyang Che

{"title":"An integrated method of extended STPA and BN for safety assessment of man-machine phased-mission system","authors":"Xin Lu , Shengkui Zeng , Jianbin Guo , Wei Deng , Mingjun He , Haiyang Che","doi":"10.1016/j.ress.2024.110569","DOIUrl":"10.1016/j.ress.2024.110569","url":null,"abstract":"<div><div>Man-Machine Phased-Mission System (MMPMS) usually demands the cooperation of operators with different responsibilities and machines to accomplish multi-phase missions. Its machine configuration and human organization structure may change across phases, and phase dependencies of machine failures and human errors may exist. In current studies, the safety of man-machine system is usually analyzed qualitatively by System Theoretic Process Analysis (STPA) and assessed quantitatively by the integration of STPA with Bayesian Networks (BN). These studies only focus on single-phase systems and conduct single-phase BN while cannot address the features of MMPMS. In this paper, a qualitative analysis and quantitative assessment method for phase dependencies is proposed and integrated into the method that combines STPA and BN. Firstly, four types of phase dependencies in MMPMS are identified. Secondly, new mapping rules for phase dependencies are proposed to integrate single-phase BN into a multi-phase BN. Thirdly, the quantitative assessment method for phase dependencies considering the effects of human organization structure changes are proposed to quantify the parameters of multi-phase BN. Fourthly, the safety of MMPMS can be assessed through multi-phase BN. Finally, an Unmanned Aerial Vehicle system with three-phase missions is presented as a case study to demonstrate the effectiveness of the proposed method.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110569"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442946","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

Spatial network disintegration based on spatial coverage 基于空间覆盖的空间网络分解

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110525

Ye Deng , Zhigang Wang , Yu Xiao , Xiaoda Shen , Jürgen Kurths , Jun Wu

{"title":"Spatial network disintegration based on spatial coverage","authors":"Ye Deng , Zhigang Wang , Yu Xiao , Xiaoda Shen , Jürgen Kurths , Jun Wu","doi":"10.1016/j.ress.2024.110525","DOIUrl":"10.1016/j.ress.2024.110525","url":null,"abstract":"<div><div>The problem of network disintegration, such as interrupting rumor spreading networks and dismantling terrorist networks, involves evaluating changes in network performance. However, traditional metrics primarily focus on the topological structure and often neglect the crucial spatial attributes of nodes and edges, thereby failing to capture the spatial functional losses. Here we first introduce the concept of spatial coverage to evaluate the spatial network performance, which is defined as the convex hull area of the largest connected component. Then a greedy algorithm is proposed to maximize the reduction of the convex hull area through strategic node removals. Extensive experiments verified that the spatial coverage metric can effectively quantify changes in the performance of spatial networks, and the proposed algorithm can maximize the reduction of the convex hull area of the largest connected component compared to genetic algorithm and centrality strategies. Specifically, our algorithm reduces the convex hull area by up to 30% compared to the best-performing strategy. These results indicate that the critical nodes influencing network performance are a combination of numerous peripheral spatial leaf nodes and a few central spatial core nodes. This study substantially enhances our understanding of spatial network robustness and provides a novel perspective for network optimization.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110525"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442857","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 multi-feature system based on hidden Markov model 基于隐马尔可夫模型的多特征系统复原力评估

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110561

Jiaying Liu , Jun Zhang , Qingfeng Tian , Bei Wu

引用次数: 0

Dynamic risk assessment for process operational safety based on reachability analysis 基于可达性分析的工艺运行安全动态风险评估

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110564

Yuchen Wang , Zuzhen Ji , Yi Cao , Shuang-Hua Yang

{"title":"Dynamic risk assessment for process operational safety based on reachability analysis","authors":"Yuchen Wang , Zuzhen Ji , Yi Cao , Shuang-Hua Yang","doi":"10.1016/j.ress.2024.110564","DOIUrl":"10.1016/j.ress.2024.110564","url":null,"abstract":"<div><div>The successful implementation of chemical production systems necessitates an effective mechanism for quantitatively assessing dynamic risk. Current methods predominantly evaluate the entire industrial process – from basic operations to the safety protection layer – and typically focus on the impact of fixed deviations in process parameters on the development of abnormal conditions. However, the cumulative impact of process disturbances on dynamic risk deserves attention, particularly in the context of abnormal operating conditions. To overcome the limitations of existing methodologies, this paper introduces a suite of novel dynamic operational risk indices based on reachability analysis, encapsulated within a comprehensive framework that includes identifying safety critical variables and quantifying uncertainties in set-form. The efficacy of the proposed method is demonstrated through applications to a tank system and a Continuous Stirred Tank Reactor (CSTR) system. This approach has the potential to enhance industry understanding of failure mechanisms and to foster the development of preventative and mitigative strategies.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110564"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442948","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 multi-valued decision diagrams-based method for reliability analysis of performance-sharing k-out-of-n: G system considering component degradation 基于多值决策图的性能共享 k-out-of-n. G 系统可靠性分析方法考虑组件退化的 G 系统

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-11 DOI: 10.1016/j.ress.2024.110531

Tianyuan Zhang , Liudong Xing , Yuchang Mo

{"title":"A multi-valued decision diagrams-based method for reliability analysis of performance-sharing k-out-of-n: G system considering component degradation","authors":"Tianyuan Zhang , Liudong Xing , Yuchang Mo","doi":"10.1016/j.ress.2024.110531","DOIUrl":"10.1016/j.ress.2024.110531","url":null,"abstract":"<div><div>This paper models the reliability of a performance-sharing <em>k</em>-out-of-<em>n</em>: G system with heterogeneous degrading components and a performance-redistributing common bus. Each component may behave at various performance levels to meet its random demand. If one component exhibits performance beyond its demand, the redundant performance is redistributed to components with deficit performance via the common bus with limited capacity. The system fails if the number of operating components is less than <em>k</em> after sharing the redundant performance. A new analytical method based on multi-valued decision diagrams (MDDs) is put forward, which comprises an efficient model generation algorithm leveraging top-down simplification rules and a new ordering heuristic for improving MDD generation efficiency. The MDD evaluation engages the continuous-time Markov Chains to compute the steady-state probabilities of system components considering the degradation effects. Case studies of a wind power generation system and a data processing system as well as benchmark studies are conducted to illustrate the applicability and efficiency of the proposed method. A comparative study with the universal generating function-based method is also provided to further demonstrate the efficiency of the proposed MDD-based method.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110531"},"PeriodicalIF":9.4,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530319","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

Research on Scenario Extrapolation and Emergency Decision-Making for Fire and Explosion Accidents at University Laboratories Based on BN-CBR 基于 BN-CBR 的大学实验室火灾和爆炸事故情景推断与应急决策研究

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-10 DOI: 10.1016/j.ress.2024.110579

Jie Liu , Fei Cai , Wanqing Wang , Haoyuan Zhu , Liangyun Teng , Xuehua Luo , Yi Chen , Chenwei Hao

{"title":"Research on Scenario Extrapolation and Emergency Decision-Making for Fire and Explosion Accidents at University Laboratories Based on BN-CBR","authors":"Jie Liu , Fei Cai , Wanqing Wang , Haoyuan Zhu , Liangyun Teng , Xuehua Luo , Yi Chen , Chenwei Hao","doi":"10.1016/j.ress.2024.110579","DOIUrl":"10.1016/j.ress.2024.110579","url":null,"abstract":"<div><div>To solve the problems of suddenness, uncertainty and untimely emergency decision-making related to fire and explosion accidents in university laboratories, a combined method of BN and CBR is introduced to analyze laboratory accidents. By summarizing the characteristics of 72 accident cases worldwide, four scenario elements with key roles are extracted by combining the public safety triangle theoretical model; a BN is established from the macro perspective, which is based on the construction of dynamic scenarios; the evolution path is analyzed via BN theory; and the probability of occurrence of accidents is quantified from the microscopic perspective, with a focus on the analysis of the accidental evolution process. A case similarity calculation is carried out via CBR, and the construction of a BN-CBR-assisted decision-making model is completed, verified and corrected in an case study. The results show that the BN-CBR model can quickly determine the accident evolution path and the most similar historical cases, and its quantitative probability calculation enables one to comprehensively grasp the real-time state of the whole accident and the emergency response in a timely manner, which provides a new way to approach emergency decision-making of accidents.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"253 ","pages":"Article 110579"},"PeriodicalIF":9.4,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420980","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