2019 IEEE International Conference on Prognostics and Health Management (ICPHM)最新文献

Calculating the Contact Forces at Imperfect Surfaces Considering Elastohydrodynamic Lubrication Effects in Rolling Element Bearings 考虑弹流润滑作用的滚动轴承非完美表面接触力计算

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819428

Linkai Niu, Fengtao Wang, Guoyan Li, Chenguang Niu, Yuan Lan, Xiaoyan Xiong

{"title":"Calculating the Contact Forces at Imperfect Surfaces Considering Elastohydrodynamic Lubrication Effects in Rolling Element Bearings","authors":"Linkai Niu, Fengtao Wang, Guoyan Li, Chenguang Niu, Yuan Lan, Xiaoyan Xiong","doi":"10.1109/ICPHM.2019.8819428","DOIUrl":"https://doi.org/10.1109/ICPHM.2019.8819428","url":null,"abstract":"The contact forces largely affect the vibrations of rolling element bearings with geometrical imperfections, such as pits, spalls, etc. In the current paper, a novel method to calculate the contact force of rolling element at imperfect race surfaces in rolling element bearings is proposed considering the elastohydrodynamic lubrication effect. In the proposed method, the oil film thickness, the oil film pressure and the elastic deformation are determined by solving the Reynolds equation, the oil film thickness equation, the viscosity-pressure equation, the density-pressure equation and the force balance equation simultaneously. The geometrical imperfection is considered by modifying the oil film thickness equation. The above equations are solved iteratively until satisfy the balance relationship of oil film thickness, elastic deformation and geometrical interaction. Finally, the contact force is calculated by integrating the oil film pressure in the entire contact region. Results show that the geometrical imperfection would largely affect the oil film thickness and the oil film pressure, and thus affect the contact force. The current investigation could provide a theoretical tool to calculate the contact force in dynamic models of rolling element bearings with imperfect surfaces. Meanwhile, the current method can also be used in the calculation of the contact force at textured surfaces in rolling element bearings.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124558003","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: 2

Prognostics of polygonalization of high-speed railway train wheels using a generalized additive model smoothed by spline-backfitted kernel 用样条背拟合核平滑的广义加性模型预测高速铁路列车车轮多面化

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819407

Zhexiang Chi, Lijian Yang, Jing Lin, Simin Huang

引用次数: 1

Visual explanation of neural network based rotation machinery anomaly detection system 基于神经网络的旋转机械异常检测系统可视化说明

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819396

Mao Saeki, Jun Ogata, M. Murakawa, Tetsuji Ogawa

引用次数: 11

Fault Detection and Isolation in Industrial Networks using Graph Convolutional Neural Networks 基于图卷积神经网络的工业网络故障检测与隔离

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819403

H. Khorasgani, Arman Hasanzadeh, Ahmed K. Farahat, Chetan Gupta

{"title":"Fault Detection and Isolation in Industrial Networks using Graph Convolutional Neural Networks","authors":"H. Khorasgani, Arman Hasanzadeh, Ahmed K. Farahat, Chetan Gupta","doi":"10.1109/ICPHM.2019.8819403","DOIUrl":"https://doi.org/10.1109/ICPHM.2019.8819403","url":null,"abstract":"Industrial networks represent large-scale systems that consist of several interacting components. In this paper, we present a solution for Fault Detection and Isolation (FDI) in industrial networks with same type of components (electrical, mechanical, etc.) such as power grids, and water supply networks. Traditional FDI algorithms are trained to detect and isolate faults on the level of a single component by considering features from this component and sometimes from nearby components. These algorithms are sub-optimal as they are independently applied to individual components without explicitly taking into consideration the dependency between the several components that co-exist in industrial network. The interaction between the components makes fault isolation challenging. An operation change or a fault in a component can affect the neighboring components. This negatively impact the diagnosis accuracy when we design an independent diagnoser for each component. On the other hand, designing a global diagnoser without considering the network structure can lead to overfitting which can degrade the diagnosis performance significantly specially when the training data is limited. Moreover, because of the large number of components in these systems, the single fault assumption may not stand. This increases the complexity of the problem. In order to solve this problem, we first model the industrial network as a weighted undirected graph structure. The graph structure represents the connected components. The weights quantify these connections. We then apply Graph Convolutional Neural Networks (GCNN) to detect and isolate faulty components in these systems. In the case study, we apply our solution to a simulated industrial network with 100 components. The case study shows that GCNN outperforms several baseline algorithms.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127132010","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: 15

A Measurement Frequency Estimation Method for Failure Prognosis of an Automated Tire Condition Monitoring System 轮胎状态自动监测系统故障预测的测量频率估计方法

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819422

R. Meissner, H. Meyer, F. Raddatz

{"title":"A Measurement Frequency Estimation Method for Failure Prognosis of an Automated Tire Condition Monitoring System","authors":"R. Meissner, H. Meyer, F. Raddatz","doi":"10.1109/ICPHM.2019.8819422","DOIUrl":"https://doi.org/10.1109/ICPHM.2019.8819422","url":null,"abstract":"The ongoing digitalization allows operators and manufacturers to constantly gain new insights about their asset’s performance and degradation status. This information could potentially help to reduce operating and maintenance costs. Although significant amount of research has been spent in determining Remaining Useful Lifetimes (RUL) of various systems, these efforts often implicitly assume an unrestricted availability of measurement data. However, the amount of acquired data significantly drives the necessary investment cost or is sometimes even impossible to obtain in required frequencies in reality. In this paper, we will investigate the changes of the precision for the RUL prognosis on the example of a Tire Pressure Indication System (TPIS). After a possible layout with sensor requirements for a fully automated condition monitoring system has been developed in theory, we describe necessary data cleansing steps to account for environmental impacts on the system’s performance and to derive the system’s health status. With the help of a Monte Carlo (MC) simulation, we evaluate the system’s sensitivity towards changes in precision of the RUL for different measurement frequencies, prognostic models, and parameter settings. The results allow an estimation of the minimum pressure measurement frequency for a fully automated TPIS in order to obtain the required prognostic performance and to maximize cost efficiency.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127433010","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: 2

A New Anomaly Detection Method Based on Multi-dimensional Condition Monitoring Data for Aircraft Engine 基于航空发动机多维状态监测数据的异常检测新方法

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819410

Shaowei Chen, Meng Wu, Shuai Zhao, Pengfei Wen, Dengshan Huang, Yan Wang

{"title":"A New Anomaly Detection Method Based on Multi-dimensional Condition Monitoring Data for Aircraft Engine","authors":"Shaowei Chen, Meng Wu, Shuai Zhao, Pengfei Wen, Dengshan Huang, Yan Wang","doi":"10.1109/ICPHM.2019.8819410","DOIUrl":"https://doi.org/10.1109/ICPHM.2019.8819410","url":null,"abstract":"Identifying the degradation state of aircraft engine accurately and carrying out suitable maintenance is significant for the safe and reliable operation of the aircraft system. In this paper, an anomaly detection system is proposed for multi-dimensional time series for aircraft engine. To represent the degradation degree of the device, the degradation index is proposed utilizing the Dynamic Time Warping algorithm (DTW) which possesses good similarity measure quality and can capture the changing characteristics of the indicator well. On the basis of the degradation index, three decision-making strategies including the Cumulative Sum algorithm (CUSUM), the Youden Index, and the Impact Factor are applied to determine the threshold values. For the threshold, two detection time points are obtained to discriminate different degradation stages in the device, in which the former refers to the initiation of degradation and the latter time point indicates that the device suffers from the anomaly. The experimental results demonstrate that all three decision strategies are able to detect system performance effectively before the device fails, which facilitates the incipient fault warning of aircraft engine in order to keep the equipment safe and reliable.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134540706","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

An FBG based smart clamp fabricated by 3D printing technology and its application to incipient clamp looseness detection 基于FBG的3D打印智能夹具及其在夹具早期松动检测中的应用

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819399

Zechao Wang, Mingyao Liu, Yongzhi Qu, Qin Wei, Zude Zhou, Yuegang Tan, Liu Hong, Jun Zhang

{"title":"An FBG based smart clamp fabricated by 3D printing technology and its application to incipient clamp looseness detection","authors":"Zechao Wang, Mingyao Liu, Yongzhi Qu, Qin Wei, Zude Zhou, Yuegang Tan, Liu Hong, Jun Zhang","doi":"10.1109/ICPHM.2019.8819399","DOIUrl":"https://doi.org/10.1109/ICPHM.2019.8819399","url":null,"abstract":"Distributed block clamps are widely used in hydraulic piping systems to fix the pipeline and to adjust the natural frequencies of pipes. However, the clamps may get loosen due to wear over time, and if not detected, it will lead to catastrophic failures. Piezoelectric lead Zirconate Titanate (PZT) based active sensing methods have been widely used to monitor the looseness of the bolted structures. However, this method bears some drawbacks, e.g., saturation, electromagnetic interference and high cost. Therefore, Fiber Bragg Grating (FBG) based sensing technology, which is robust to electromagnetic interference and easy for multiplexing, has been employed to design smart bolts and washers to monitor the preload of the bolted structures in existing literatures. However, the applications of those structures are limited due to specific customization, e.g. the distributed feature of the smart bolt is limited by the blind hole structure and the smart washer can only be used to the bolted connections with big-diameter bolts. To address these issues, a smart clamp is presented in present study. Moreover, the 3D printing technology is also investigated to fabricate FBG based smart clamps in a flexible and cost-effective way. A novel FBG based smart clamp is proposed in this work. The influence of different print layer heights, 0.15mm and 0.2mm on the sensitivity of clamp is also evaluated. It is shown that the 0.2mm height leads to a higher sensitivity than the 0.15mm height. Its application to incipient clamp looseness detection is further performed in an industrial piping system.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124097910","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

Formulation and Solution for the Predictive Maintenance Integrated Job Shop Scheduling Problem 预测性维修综合作业车间调度问题的提出与解决

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819397

S. Zhai, Alexander Rieß, G. Reinhart

{"title":"Formulation and Solution for the Predictive Maintenance Integrated Job Shop Scheduling Problem","authors":"S. Zhai, Alexander Rieß, G. Reinhart","doi":"10.1109/ICPHM.2019.8819397","DOIUrl":"https://doi.org/10.1109/ICPHM.2019.8819397","url":null,"abstract":"Predictive Maintenance has gained a lot of attention in recent years due to the development of improved sensors and intelligent algorithms. These allow for monitoring the health condition of production machinery and predict its future deterioration. In order to generate added value for industrial use cases, two more steps are required: considering the machine’s time-varying operational conditions and integrating its dependent deterioration prediction in a holistic scheduling approach. This publication identifies a shortage of deterioration estimation frameworks under time-varying operational conditions as well as a lack of Predictive Maintenance integrated scheduling problems in the literature. Subsequently, a new conceptual framework to model future machine deterioration under time-varying operational conditions and its application in production scheduling is introduced. The Operation Specific Stress Equivalent (OSSE) represents the load of a future production job on the machine and supports a general formulation of the maintenance integrated job shop scheduling problem (MIJSSP). This formulation is presented together with benchmark instances and corresponding sample data. Finally, the formulation is tested with the help of a genetic algorithm that illustrates the potential of using new objective functions for decision support, such as the Reliability Weighted Makespan CmaxR.","PeriodicalId":113460,"journal":{"name":"2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124306415","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: 10

Load sharing analysis of compound planetary gear set with cracked sun gear 含裂纹太阳齿轮的复合行星齿轮组载荷分担分析

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819401

Guoyan Li, Linkai Niu, Liang Ma, Dehao Dong

引用次数: 2

A Multivalued Test and Diagnostic Strategy Optimization Method for Aircraft System Fault Diagnosis 飞机系统故障诊断的多值测试与诊断策略优化方法

2019 IEEE International Conference on Prognostics and Health Management (ICPHM) Pub Date : 2019-06-17 DOI: 10.1109/ICPHM.2019.8819388

Yan Su, Xuerui Liang, Chenxuan Gu, Varun Khemani, M. Pecht

引用次数: 1