Quality and Reliability Engineering International最新文献_第10页

A novel probabilistic modeling for multilateral random attacks in cyber‐physical system reliability analysis 网络物理系统可靠性分析中多边随机攻击的新型概率模型

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-21 DOI: 10.1002/qre.3533

Jiayue Huang, Jianfeng Yang, Zhoutao Zheng, Zhengxia Qiu

引用次数: 0

Zone‐based failure risk assessment of fatigue crack growth caused by initial defects in powder turbine disc 对粉末涡轮盘初始缺陷导致的疲劳裂纹增长进行基于区域的失效风险评估

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-21 DOI: 10.1002/qre.3542

Rongqiao Wang, Weihan Kong, Guanjie Cao, Xi Liu, Jianxing Mao, Haihe Sun, Dianyin Hu

引用次数: 0

A variable-speed-condition fault diagnosis method for crankshaft bearing in the RV reducer with WSO-VMD and ResNet-SWIN 利用 WSO-VMD 和 ResNet-SWIN 的 RV 减速器曲轴轴承变速条件故障诊断方法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-20 DOI: 10.1002/qre.3538

Guangqi Qiu, Yu Nie, Yulong Peng, Peng Huang, Junjie Chen, Yingkui Gu

{"title":"A variable-speed-condition fault diagnosis method for crankshaft bearing in the RV reducer with WSO-VMD and ResNet-SWIN","authors":"Guangqi Qiu, Yu Nie, Yulong Peng, Peng Huang, Junjie Chen, Yingkui Gu","doi":"10.1002/qre.3538","DOIUrl":"https://doi.org/10.1002/qre.3538","url":null,"abstract":"Due to the noise interference and the weak characterization ability of the fault vibration signal of rotation vector (RV) reducer crankshaft bearing, it is difficult to obtain satisfactory results for the available fault diagnosis methods. For that, this paper proposes a variable-speed-condition fault diagnosis method with WSO-VMD and ResNet-SWIN. A signal reconstruction method with WSO-VMD was carried out, Firstly, the performance of VMD algorithm is improved by using war strategy optimization algorithm to select parameters adaptively. Then the signal is reconstructed considering the fault characteristic frequency, so as to realize the noise reduction of the signal. By using the residual network module and attention mechanism to replace the first stage of the original SWIN model, a novel ResNet-SWIN fault diagnosis model is established to enhance the feature extraction ability for the weak signal. The experiments with the constant-operating-condition and the variable-operating-condition are carried out to verify the effectiveness of the proposed method. The results show that, whether at variable-speed or constant-speed conditions, WSO algorithm has been proven to be the fastest convergence speed compared with WOA, SSA, and NGO optimization algorithms, and by the signal reconstruction with WSO-VMD, the variance evaluation indicator of the reconstructed signal has 36%, 21%, 46%, and 40%, respectively. ResNet-SWIN model has achieved the optimal diagnosis accuracy compared with SWIN, VIT, and CNN-SVM models in both variable-speed and constant-speed conditions.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"65 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140182312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Dynamic modeling and reliability analysis of satellite antenna deployment mechanism based on parameter uncertainty 基于参数不确定性的卫星天线部署机制动态建模与可靠性分析

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-19 DOI: 10.1002/qre.3534

Ke Wang, Hua‐Ming Qian, Jinhua Mi, Tianlong Xu, Hong‐Zhong Huang

{"title":"Dynamic modeling and reliability analysis of satellite antenna deployment mechanism based on parameter uncertainty","authors":"Ke Wang, Hua‐Ming Qian, Jinhua Mi, Tianlong Xu, Hong‐Zhong Huang","doi":"10.1002/qre.3534","DOIUrl":"https://doi.org/10.1002/qre.3534","url":null,"abstract":"This study delves into the factors that affect the reliability of satellite antenna deployment mechanisms. It employs the Kolmogorov–Smirnov (K‐S) test to quantify uncertainty characteristics, leading to the acquisition of pertinent stochastic parameters. Subsequently, three‐dimensional models and finite element models of the satellite antenna deployment mechanism are established using SOLIDWORKS and ANSYS software. Modal distribution, harmonic response analysis, random vibration analysis, and deployment process simulation are conducted. Parameterized modeling of the deployment mechanism's dynamics simulation process is performed, taking into consideration parameter uncertainty. Finally, a Kriging surrogate model is utilized to formulate an approximate expression between the factors influencing the reliability of the antenna deployment mechanism and its dynamic response. Based on the general stress‐strength interference theory, a reliability analysis model is constructed. Combined with active learning algorithms, this approach achieves efficient and precise calculations of the reliability of the satellite antenna deployment mechanism.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"51 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140165770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Bayesian analysis of optimal burn-in policy for heterogeneous components with minimal repair 以贝叶斯方法分析具有最小修复功能的异构组件的最佳预烧策略

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-19 DOI: 10.1002/qre.3535

Xiaoliang Ling, Ruijie Yin, Ping Li

引用次数: 0

Reliability assessment models for competing failure processes with two types of correlative thresholds 具有两类相关阈值的竞争性故障过程的可靠性评估模型

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-19 DOI: 10.1002/qre.3529

Qingbiao Song, Jiayin Tang, Honglei Wei, Yong Li

{"title":"Reliability assessment models for competing failure processes with two types of correlative thresholds","authors":"Qingbiao Song, Jiayin Tang, Honglei Wei, Yong Li","doi":"10.1002/qre.3529","DOIUrl":"https://doi.org/10.1002/qre.3529","url":null,"abstract":"The two dependent competing risks are soft failure due to aging degradation and fragmentation caused by shocks and hard failure due to spring breakage caused by the same shock process. Considering the complexity of the product itself and the instability of the working environment, this study proposed a generalized reliability model for systems experiencing dependent competing failure processes (DCFPs) of degradation and random shocks, which considered two kinds of DCFP: (1) shock process could affect soft failure thresholds; (2) degradation process could affect hard failure thresholds. In case (1), we considered the effect that a cumulative number of shocks above a certain magnitude could have on the change in the soft failure threshold. In case (2), we considered not only the shock process's impact on the soft failure threshold but also the total degradation (including continuous degradation and sudden degradation caused by shock) on the hard failure threshold. The model captures the features that the shocks experienced by the system affect the degradation process, accelerating the system degradation and causing soft failures; the degradation process of the system affects the shock process, making the system more susceptible to failure from external shocks. Finally, an example using micro‐electro‐mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"150 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Failure prediction of mechanical system based on meta-action 基于元动作的机械系统故障预测

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-19 DOI: 10.1002/qre.3537

Yan Ran, Jingjie Chen, Nafis Jawyad Sagor, Genbao Zhang

{"title":"Failure prediction of mechanical system based on meta-action","authors":"Yan Ran, Jingjie Chen, Nafis Jawyad Sagor, Genbao Zhang","doi":"10.1002/qre.3537","DOIUrl":"https://doi.org/10.1002/qre.3537","url":null,"abstract":"Highly reliable mechanical systems can lead to significant losses in the event of failure, and the lack of comprehensive failure data presents challenges for developing techniques such as critical part identification and failure prediction. In light of this, this paper proposes a meta-action-based fault prediction method that effectively addresses the issue of limited fault data. Initially, the mechanical system is decomposed utilizing the “Function-Motion-Action” (FMA) methodology to derive individual meta-action units (MAUs). Subsequently, the limited sample of fault data from the mechanical system is combined with processed expert knowledge to construct the corresponding fault propagation-directed graph. Furthermore, the key MAUs are determined by applying the Decision–Making Trial and Evaluation Laboratory (DEMATEL) method. Last, the degradation data of the key MAUs is acquired by monitoring them, and a non-homogeneous discrete grey model (DNGM) integrated with an improved BP neural network is proposed to facilitate the fault prediction of MAUs. Using an industrial robot as a case study, the prediction results demonstrate the superiority of the method proposed in this paper over a single gray model and neural network, thereby providing a reliable prediction approach for anticipating the future trends of data-deficient mechanical systems.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"45 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140182313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Assessment of safety climate perception of maintenance workers during major overhauls, outages, shutdowns or turnarounds (MoOSTs) 评估维护工人在大修、停工、停产或周转期间（MoOSTs）对安全环境的看法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-19 DOI: 10.1002/qre.3532

Akilu Yunusa‐Kaltungo, Srija Ray, Shaikha AlSanad, Idowu Sokunbi, Patrick Manu, Clara Man Cheung, Saeed Reza Mohandes

{"title":"Assessment of safety climate perception of maintenance workers during major overhauls, outages, shutdowns or turnarounds (MoOSTs)","authors":"Akilu Yunusa‐Kaltungo, Srija Ray, Shaikha AlSanad, Idowu Sokunbi, Patrick Manu, Clara Man Cheung, Saeed Reza Mohandes","doi":"10.1002/qre.3532","DOIUrl":"https://doi.org/10.1002/qre.3532","url":null,"abstract":"Maintenance activities are used to sustain the reliability of physical industrial assets. However, studies indicate that some of the most devastating industrial accidents are attributable to poor safety perceptions of maintenance workers, especially during major overhauls, outages, shutdowns or turnarounds (MoOSTs). Typical MoOSTs involve the harmonisation of regular maintenance endeavours on a large scale, which in turn heighten risks of accidents and costs. Furthermore, MoOSTs are performed over short durations thereby necessitating parallel high‐risk activities by different organisations that have different perceptions of safety and possess different safety cultures. Understanding safety climate can immensely benefit MoOSTs organisations by improving the understanding of attitudes and perceptions that alleviate workplace incidents. This study aimed to establish safety climate that would boost safety culture and positively impact perceived safety performance during MoOSTs. Safety climate questionnaire survey was deployed to MoOSTs workers of leading cement plants in Nigeria. Through exploratory factor analysis, three underlying safety climate factors were identified, which helped to determine that factors such as ‛training and learning from incidents’, ‛commitment of senior management towards ensuring safety and its protocol development process’ and ‛effectiveness of incident reporting systems during MoOSTs’ were significant predictors of workers’ perceptions of safety performance. The findings also pointed out that the inter‐relationship between perceived safety performance, MoOSTs safety training and organisational commitment were positively correlated.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"27 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140169884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Web service reliability and scalability determination using optimized depth wise separable convolutional neural network 利用优化的深度可分离卷积神经网络确定网络服务的可靠性和可扩展性

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-16 DOI: 10.1002/qre.3530

Gokulakrishnan Dhakshnamoorthy, Jeyabal Sridhar, Ramakrishnan Ramanathan, Muruga Radha Devi Dharmalingam

{"title":"Web service reliability and scalability determination using optimized depth wise separable convolutional neural network","authors":"Gokulakrishnan Dhakshnamoorthy, Jeyabal Sridhar, Ramakrishnan Ramanathan, Muruga Radha Devi Dharmalingam","doi":"10.1002/qre.3530","DOIUrl":"https://doi.org/10.1002/qre.3530","url":null,"abstract":"Web service composition (WSC), a distributed architecture, creates new services atop existing ones. Ensuring trust and assessing performance and dependability in online services coordination is essential. In this paper, “Web Service Reliability and Scalability Determination Using Depth Wise Separable Convolutional Neural Network” (WSRS‐DWSCNN) is proposed to assess the trustworthiness of online service compositions, particularly focusing on performance and dependability. This work addresses the need to predict the reliability and scalability of Business Process Execution Language (BPEL) composite web services. The proposed approach transforms the BPEL specification into a Depth Wise Separable Convolutional Neural Network (DWSCNN) and annotates it with probabilistic properties for prediction. The DWSCNN model classifies the outcomes as correct or incorrect, and to enhances the prediction of web service composition scalability and reliability, we optimize the DWSCNN's weight parameters using the Adolescent Identity Search Algorithm (AISA). The proposed technique is activated in Python and its efficacy is analyzed under some metrics, such as reliability, scalability, accuracy, sensitivity, specificity, precision, F‐measure. The proposed method provides 12.36%, 45.39%, and 25.97% better reliability, 41.39%, 11.39%, 34.16% better accuracy compared with existing methods like, Web service reliability prediction depending on machine learning (WSRS‐K‐means), reliability prediction method for multiple state cloud/edge‐basis network utilizing deep neural network (WSRS‐DNN‐BO), and improving reliability of mobile social cloud computing utilizing machine learning in content addressable network (WSRS‐CAN), respectively.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"22 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Real‐time assessment on health state for bearing based on parallel encoder‐decoder observer 基于并行编码器-解码器观测器的轴承健康状态实时评估

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-03-14 DOI: 10.1002/qre.3531

Kunpeng Li, Jinhua Mi, Zhiguo Wang, Shengjie Yin, Libing Bai, Gen Qiu

{"title":"Real‐time assessment on health state for bearing based on parallel encoder‐decoder observer","authors":"Kunpeng Li, Jinhua Mi, Zhiguo Wang, Shengjie Yin, Libing Bai, Gen Qiu","doi":"10.1002/qre.3531","DOIUrl":"https://doi.org/10.1002/qre.3531","url":null,"abstract":"Bearings are foundational supporting components in diverse mechanical systems, essential for the reliable operation of these systems through real‐time monitoring and precise health state assessment. However, vibration signals from bearings in practical equipment often contain excessive noise and redundant information, complicating health state assessment. To address this challenge, this paper proposes a neural network‐based method named parallel encoder‐decoder (PED). This method features a parallel architecture that combines the long short‐term memory network and the temporal convolutional network for the encoder, along with a self‐attention module for the decoder. PED is adept at learning the temporal representations hidden in original signals and filtering vibration signals to remove noise and redundant information. Additionally, a multi‐objective loss function is developed to enhance the prediction results. A normalized Mahalanobis distance‐based metric is then employed to compare residual signals during bearing operation with those under normal conditions. The case study evaluates the PED observer's proficiency in accurately predicting vibration signals and assessing the performance of health indicator curves, demonstrating the proposed PED observer's superiority over conventional networks.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"85 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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