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Multi-feature spatial distribution alignment enhanced domain adaptive method for tool condition monitoring 刀具状态监测的多特征空间分布对齐增强域自适应方法
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-09-05 DOI: 10.17531/ein/171750
Zhendong Hei, Bintao Sun, Gaonghai Wang, Yongjian Lou, Yuqing Zhou
{"title":"Multi-feature spatial distribution alignment enhanced domain adaptive method for tool condition monitoring","authors":"Zhendong Hei, Bintao Sun, Gaonghai Wang, Yongjian Lou, Yuqing Zhou","doi":"10.17531/ein/171750","DOIUrl":"https://doi.org/10.17531/ein/171750","url":null,"abstract":"Transfer learning (TL) has been successfully implemented in tool condition monitoring (TCM) to address the lack of labeled data in real industrial scenarios. In current TL models, the domain offset in the joint distribution of input feature and output label still exists after the feature distribution of the two domains is aligned, resulting in performance degradation. A multiple feature spatial distribution alignment (MSDA) method is proposed, Including Correlation alignment for deep domain adaptation (Deep CORAL) and Joint maximum mean difference (JMMD). Deep CORAL is employed to learn nonlinear transformations, align source and target domains at the feature level through the second-order statistical correlations. JMMD is applied to improve domain alignment by aligning the joint distribution of input features and output labels. ResNet18 combining with bidirectional short-term memory network and attention mechanism is developed to extract the invariant features. TCM experiments with four transfer tasks were conducted and demonstrated the effectiveness of the proposed method.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125210545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A genetic algorithm-based approach for flexible job shop rescheduling problem with machine failure interference 基于遗传算法的机械故障干扰柔性作业车间重调度问题
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-09-05 DOI: 10.17531/ein/171784
Zhongyuan Liang, Peisi Zhong, Chao Zhang, Wenlei Yang, Wei Xiong, Shihao Yang, Jing Meng
{"title":"A genetic algorithm-based approach for flexible job shop rescheduling problem with machine failure interference","authors":"Zhongyuan Liang, Peisi Zhong, Chao Zhang, Wenlei Yang, Wei Xiong, Shihao Yang, Jing Meng","doi":"10.17531/ein/171784","DOIUrl":"https://doi.org/10.17531/ein/171784","url":null,"abstract":"Rescheduling is the guarantee to maintain the reliable operation of production system process. In production system, the original scheduling scheme cannot be carried out when machine breaks down. It is necessary to transfer the production tasks in the failure cycle and replan the production path to ensure that the production tasks are completed on time and maintain the stability of production system. To address this issue, in this paper, we studied the event-driven rescheduling policy in dynamic environment, and established the usage rules of right-shift rescheduling and complete rescheduling based on the type of interference events. And then, we proposed the rescheduling decision method based on genetic algorithm for solving flexible job shop scheduling problem with machine fault inter-ference. In addition, we extended the \"mk\" series of instances by introducing the machine fault interference information. The solution data show that the complete rescheduling method can respond effectively to the rescheduling of flexible job shop scheduling problem with machine failure interference.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124405080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Process machining allowance for reliability analysis of mechanical parts based on hidden quality loss 基于隐性质量损失的机械零件加工余量可靠性分析
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-08-28 DOI: 10.17531/ein/171594
Jingang Wang, Xintian Liu, Xu Wang, Kai Jin
{"title":"Process machining allowance for reliability analysis of mechanical parts based on hidden quality loss","authors":"Jingang Wang, Xintian Liu, Xu Wang, Kai Jin","doi":"10.17531/ein/171594","DOIUrl":"https://doi.org/10.17531/ein/171594","url":null,"abstract":"The machining allowance variation is significant for the reliability of a part during the machining process. Usually, when the machining allowance of a part increases, the machining and production cost also increase. When the machining allowance decreases, the machining surface will have defects. The parts will produce many scraps and reliability will decrease. The machining allowance of a part consists of multiple process machining allowances. To analyze the impact caused by machining allowance variation, the hidden quality loss and process machining allowance are combined through the process capability index (PCI). Then the asymmetric quadratic quality loss function (AQF) and quadratic exponential function (QEF) are used to analyze them. A prediction model of hidden quality loss of process machining allowance is proposed. On the premise that the quality characteristic value obeys normal function distribution, a numerical model is given and used to obtain process machining allowance-inherent reliability of the product. The actual case is used to compare and verify the two models.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129604778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","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 method of health indicator construction and remaining useful life prediction based on deep learning 基于深度学习的健康指标构建与剩余使用寿命预测新方法
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-08-26 DOI: 10.17531/ein/171374
Xianbiao Zhan, Zixuan Liu, Hao Yan, Zhenghao Wu, Chiming Guo, Xisheng Jia
{"title":"A novel method of health indicator construction and remaining useful life prediction based on deep learning","authors":"Xianbiao Zhan, Zixuan Liu, Hao Yan, Zhenghao Wu, Chiming Guo, Xisheng Jia","doi":"10.17531/ein/171374","DOIUrl":"https://doi.org/10.17531/ein/171374","url":null,"abstract":"The construction of health indicators (HI) for traditional deep learning requires human training labels and poor interpretability. This paper proposes an HI construction method based on Stacked Sparse Autoencoder (SSAE) and combines SSAE with Long short-term memory (LSTM) network to predict the remaining useful life (RUL). Extracting features from a single domain may result in insufficient feature extraction and cannot comprehensively reflect the degradation status information of mechanical equipment. In order to solve the problem, this article extracts features from time domain, frequency domain, and time-frequency domain to construct a comprehensive original feature set. Based on monotonicity, trendiness, and robustness, the most sensitive features from the original feature set are selected and put into the SSAE network to construct HI for state partitioning, and then LSTM is used for RUL prediction. By comparing with the existing methods, it is proved that the prediction effect of the proposed method in this paper is satisfied.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130561042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Key fault propagation path identification of CNC machine tools based on maximum occurrence probability 基于最大发生概率的数控机床关键故障传播路径识别
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-07-30 DOI: 10.17531/ein/169887
Yingzhi Zhang, Yutong Zhou, Fang Yang, Zhiqiong Wang, Mo Sun
{"title":"Key fault propagation path identification of CNC machine tools based on maximum occurrence probability","authors":"Yingzhi Zhang, Yutong Zhou, Fang Yang, Zhiqiong Wang, Mo Sun","doi":"10.17531/ein/169887","DOIUrl":"https://doi.org/10.17531/ein/169887","url":null,"abstract":"In order to revise the deviation caused by ignoring the dynamic character of fault propagation in traditional fault propagation path identification methods, a method based on the maximum occurrence probability is proposed to identify the key fault propagation path. Occurrence probability of fault propagation path is defined by dynamic importance, dynamic fault propagation probability and fault rate. Taking the fault information of CNC machine tools which subject to Weibull distribution as an example, this method has been proven to be reasonable through comparative analysis. Result shows that the key fault propagation path of CNC machine tools is not unique, but changes with time. Before 1000 hours, key fault propagation path is electrical component (E) to mechanical component (M); after 1000 hours, key fault propagation path is auxiliary component (A) to mechanical component (M). This change should be taken into account when developing maintenance strategies and conducting reliability analysis.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132021698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis 通过热成像和边缘处理揭示感应电机状态:迈向可解释故障诊断的一步
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-07-29 DOI: 10.17531/ein/170114
M. Piechocki, T. Pajchrowski, Marek Kraft, M. Wolkiewicz, P. Ewert
{"title":"Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis","authors":"M. Piechocki, T. Pajchrowski, Marek Kraft, M. Wolkiewicz, P. Ewert","doi":"10.17531/ein/170114","DOIUrl":"https://doi.org/10.17531/ein/170114","url":null,"abstract":"Equipment condition monitoring is essential to maintain the reliability of the electromechanical systems. Recently topics related to fault diagnosis have attracted significant interest, rapidly evolving this research area. This study presents a non-invasive method for online state classification of a squirrel-cage induction motor. The solution utilizes thermal imaging for non-contact analysis of thermal changes in machinery. Moreover, used convolutional neural networks (CNNs) streamline extracting relevant features from data and malfunction distinction without defining strict rules. A wide range of neural networks was evaluated to explore the possibilities of the proposed approach and their outputs were verified using model interpretability methods. Besides, the top-performing architectures were optimized and deployed on resource-constrained hardware to examine the system's performance in operating conditions. Overall, the completed tests have confirmed that the proposed approach is feasible, provides accurate results, and successfully operates even when deployed on edge devices.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114038633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Failure modeling and reliability analysis for motion mechanism with clearance joints under plastic deformation and wear 带间隙关节运动机构塑性变形磨损失效建模及可靠性分析
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-07-26 DOI: 10.17531/ein/169920
Jingyi Liu, Shilong Xue, Kaichao Zhang, H. Pang
{"title":"Failure modeling and reliability analysis for motion mechanism with clearance joints under plastic deformation and wear","authors":"Jingyi Liu, Shilong Xue, Kaichao Zhang, H. Pang","doi":"10.17531/ein/169920","DOIUrl":"https://doi.org/10.17531/ein/169920","url":null,"abstract":"The performance failure and reliability of motion mechanism has a significant effect on industry reliability, operation safety and production economy. Motion precise is one of the typical performance indicators especially for motion mechanism with multibody and joints. Size of joint clearance degenerates with usage such as wear and deformation. Repeated start-stop lead to impact stress and plastic deformation for clearance joint particularly for mechanism with high load and long working cycles. This study attempts to investigate the wear process and performance failure model of multibody mechanism with clearance joints considering plastic deformation and wear. Quantification of plastic deformation caused by repeated impact stress of joints is studied by formulation. Then, a novel wear process model is established, after which performance failure indicator is conducted. A linkage motion mechanism with multi revolution joints is studied to demonstrate proposed methods. This study provides valuable guidelines for degeneration prediction and reliability analysis of motion mechanism.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124025579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting the overall equipment efficiency of core drill rigs in mining using ANN and improving it using MCDM 利用人工神经网络对矿山岩心钻机整体设备效率进行预测，并用MCDM对其进行改进
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-07-22 DOI: 10.17531/ein/169581
K. Balakrishnan, Ilangkumaran Mani, Durairaj Sankaran
{"title":"Predicting the overall equipment efficiency of core drill rigs in mining using ANN and improving it using MCDM","authors":"K. Balakrishnan, Ilangkumaran Mani, Durairaj Sankaran","doi":"10.17531/ein/169581","DOIUrl":"https://doi.org/10.17531/ein/169581","url":null,"abstract":"In this manuscript, an attempt has been made to predict and improve the overall equipment effectiveness of core drill rigs. A combined Box–Jenkins and artificial neural network model was used to develop a three parameter model (drill pushing pressure, drill penetration rate & average pillar drill pit cycle time) for predicting effectiveness. the overall equipment efficiency of core drill rigs. The values of mean average percentage error, root mean square error, normalized root mean square error, men bias error, normalized mean biased error and coefficient of determination values were found to be 9.462%, 17.378%, 0.194, 0.96%, 0.0014 and 0.923. Empirical relationships were developed between the input and output parameters and its effectiveness were evaluated using analysis of variance. For attaining 74.9% effectiveness, the optimized values of pushing pressure, penetration rate and average pillar drill pit cycle time were predicted to be 101.7 bar, 0.94 m/min and 272 min, which was validated. Interactions, perturbations and sensitivity analysis were conducted.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125303497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reliability and availability modelling of a retrofitted Diesel-based cogeneration system for heat and hot water demand of an isolated Antarctic base 为满足一个孤立的南极基地的热能和热水需求而改造的柴油热电联产系统的可靠性和可用性建模
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-07-22 DOI: 10.17531/ein/169779
Miguel Coronado, B. Kadoch, J. Contreras, F. Kristjanpoller
{"title":"Reliability and availability modelling of a retrofitted Diesel-based cogeneration system for heat and hot water demand of an isolated Antarctic base","authors":"Miguel Coronado, B. Kadoch, J. Contreras, F. Kristjanpoller","doi":"10.17531/ein/169779","DOIUrl":"https://doi.org/10.17531/ein/169779","url":null,"abstract":"The reduction of greenhouse gas emissions is a relevant challenge for a sustainable development. Waste heat could be used to produce hot water by using a recovery system. This article studies the availability of a combined heat and power systems (CHP) in extreme area (Antarctic) through the integration of a waste heat recovery system with a diesel generator to produce hot water. The reliability and availability principles are incorporated to explore how the profile of hot water consumption and the hot water storage tank size affect system availability. Different combined heat and power systems are thus classified, and their availability indexes modelled by adopting the continuous Markov approach and the state space model. The results indicate that the CHP systems availability is strongly influenced by the daily hot water demand profile. As a useful recommendation, one of the considerations for increasing availability, reducing costs and greenhouse gas emissions with the CHP system is to include a hot water tank in the analysis.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123287298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Mathematical Calculation of Material Reliability Using Surface Roughness Feature Based on Plasma Material Interaction Experiment Results 基于等离子体材料相互作用实验结果的表面粗糙度特征材料可靠性数学计算
Eksploatacja i Niezawodność – Maintenance and Reliability Pub Date : 2023-07-21 DOI: 10.17531/ein/169815
A. Pahsa, Y. Aydoğdu, Fahrettin Göktaş
{"title":"Mathematical Calculation of Material Reliability Using Surface Roughness Feature Based on Plasma Material Interaction Experiment Results","authors":"A. Pahsa, Y. Aydoğdu, Fahrettin Göktaş","doi":"10.17531/ein/169815","DOIUrl":"https://doi.org/10.17531/ein/169815","url":null,"abstract":"The choice of reactor structural material design must take into account the TOKAMAK fusion reactors' structural reliability. Due to their high levels of heat and energy, fusion reactions have significant deformation effects, which reduce the efficiency of energy production in reactors. Material selection, erosion and damage, heat and stress management, reliability analysis, maintenance, and inspection are crucial elements in determining how reliable fusion reactors are. The focus of this work is on material selection and reliability analysis based on these parameters. The most common wall materials used in fusion reactors are tungsten, beryllium, steel, or graphite. It is advised to utilize aluminum because harmful Beryllium dust limits the study of this element. For this purpose, a target of aluminum samples is established with a plasma of He ions created by glow discharge. The dependability of the samples is determined by calculating the Weibull Distribution and measuring the roughness of the sample surfaces following exposure.","PeriodicalId":335030,"journal":{"name":"Eksploatacja i Niezawodność – Maintenance and Reliability","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114158221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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