2019 Prognostics and System Health Management Conference (PHM-Qingdao)最新文献_第10页

Failure Analysis of Coupler Knuckle Considering Truncated and Censored Lifetime Data 考虑截短和截短寿命数据的耦合器转向节失效分析

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942964

Dongdong Li, Qi Li, E. Mingcheng, Zengqiang Jiang, Jing Ma

引用次数: 1

Hierarchical Health Assessment of Equipment with Uncertain Fault Diagnosis Result 故障诊断结果不确定的设备分层健康评估

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942943

Shigang Zhang, Xu Luo, Lei Li, Yongmin Yang

引用次数: 0

Investigation on the Influence of Dynamic Tooth Wear on Gear Dynamic Characteristics 动齿磨损对齿轮动态特性影响的研究

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942885

Li-sha Zhu, Haonan Chen, Zunling Du, Zi-Sheng Lin, Yonghui He, Hairong Han

引用次数: 1

A New Bearing Fault Diagnosis Framework With Deep Adaptation Networks For Industrial Application 基于深度自适应网络的轴承故障诊断框架

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8943033

Juan Wen, Bosong Pan, Luping Luo, Kewen Zhang, Quanhui Wu

{"title":"A New Bearing Fault Diagnosis Framework With Deep Adaptation Networks For Industrial Application","authors":"Juan Wen, Bosong Pan, Luping Luo, Kewen Zhang, Quanhui Wu","doi":"10.1109/phm-qingdao46334.2019.8943033","DOIUrl":"https://doi.org/10.1109/phm-qingdao46334.2019.8943033","url":null,"abstract":"In the past decades, a host of fault diagnosis methodologies have been designed and successfully used for bearings. However, most of them still have two deficiencies. (1) Traditional methods extract and select features manually according to a specific issue, but these features may be not appropriate for other tasks, leading to performance degradation of fault diagnosis. (2) Many studies assume that the dataset for model learning obey the uniform distribution as the testing dataset do, which seldom accords with the practice. To remedy these problems, we devise a novel framework for bearing fault diagnosis. First, the raw condition monitoring data are converted to 2D images with continuous wavelet transform. Then the classification model is learned with these 2D images, during which the transfer learning scheme, deep adaptation networks, is introduced for adapting the deep model trained with source data for use in new but related target domain. The presented approach is demonstrated with bearing condition monitoring information, and the results indicate it can identify bearing faults effectively under different operational conditions and has a higher accuracy than conventional approaches.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130566046","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

Extented Intelligent Recognition of Rolling Bearing Early Faults Using Multiscale Permutation Entropy 基于多尺度置换熵的滚动轴承早期故障扩展智能识别

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942825

Wang Chaobing, Wu Rongzhen, Zhang Long, Cai Binghuan, Yan Lewei, Yin Wenhao

{"title":"Extented Intelligent Recognition of Rolling Bearing Early Faults Using Multiscale Permutation Entropy","authors":"Wang Chaobing, Wu Rongzhen, Zhang Long, Cai Binghuan, Yan Lewei, Yin Wenhao","doi":"10.1109/phm-qingdao46334.2019.8942825","DOIUrl":"https://doi.org/10.1109/phm-qingdao46334.2019.8942825","url":null,"abstract":"Considering the diversity, complexity and uncertainty existing in bearing vibrations, an extended intelligent identification paradigm for bearing faults was proposed based on multiscale permutation entropy (MPE) and extension theory. MPE can reflect the random degree and detect the dynamic mutation of time series over subsequent scales, while extension theory provides an approach to address the extensibility and regularity of complicated problems. In the present paradigm, MPE was employed to compute the entropies over multiple scales as an original feature vector to represent bearing vibrations, which were then graded using Fisher ratio to choose the most informative features. The chosen features were exploited to determine the classical domain and joint domain of matter elements associated with various bearing health conditions. Bearing fault pattern was assigned to the one with maximum dependence degree among the afore-constructed matter elements. An experiment was conducted on an electrical motor involving four bearing conditions including normal, inner race, outer race and rolling element faults. The test was repeated 100 times with an averaged rate of 92.2% by the proposed method which outperforms the method using multiscale sample entropy and extension theory.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124660905","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

Glucose Level Prediction Based on Data Driven Method 基于数据驱动方法的血糖水平预测

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942886

Min Qian, Yan-Fu Li

引用次数: 0

An improved method for evaluating the preventive maintenance quality of buses 客车预防性维修质量评价的改进方法

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8943061

Zhigao Chen, R. Jiang, Yi-Rong Teng

引用次数: 0

A Recognition Method for Lightning Disturbance in Traction Power Supply System Based on Wavelet Energy Moment 基于小波能量矩的牵引供电系统雷电干扰识别方法

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942908

Liping Zhao, Lin Long, Shangxiao Yang, Sheng Lin

{"title":"A Recognition Method for Lightning Disturbance in Traction Power Supply System Based on Wavelet Energy Moment","authors":"Liping Zhao, Lin Long, Shangxiao Yang, Sheng Lin","doi":"10.1109/phm-qingdao46334.2019.8942908","DOIUrl":"https://doi.org/10.1109/phm-qingdao46334.2019.8942908","url":null,"abstract":"Traction power supply system (TPSS) is an important part of the electric railway. Lightning is one of the important factors that endanger the safe operation of TPSS. The impact of lightning on TPSS can be divided into lightning fault and lightning disturbance. Due to lightning disturbance also generates high-frequency components, which cause the relay protection mistrip in traction substation. In this paper, wavelet energy moment is used to recognition lightning disturbance of TPSS. Firstly, in order to obtain transient signals of TPSS, simulation model of the TPSS is built and it simulates three kinds of transient signals, such as normal signals, lightning fault signals and lightning disturbance signals. Then the wavelet transform is used to extract the energy moments of each frequency band of the three types of signals. Thus, wavelet energy moment statistical graphs of three types of signals are obtained, the wavelet energy moment statistical graph is analyzed and its distribution characteristics are analyzed. Based on this, the lightning disturbance recognition criterion is proposed. Finally, the recognition criterion is verified by the simulation signals. The results show that the recognition method can effectively recognize the lightning disturbance signal of the TPSS.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114968678","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

Clustering-based Travel Pattern Recognition in Rail Transportation System Using Automated Fare Collection Data 基于自动收费数据的轨道交通系统出行模式识别

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8943009

Yupeng Chen, Yang Zhao, K. Tsui

引用次数: 1

Condition-Based Maintenance Optimization with Safety Constraints under Imperfect Inspection 不完全检测下安全约束的状态维修优化

2019 Prognostics and System Health Management Conference (PHM-Qingdao) Pub Date : 2019-10-01 DOI: 10.1109/phm-qingdao46334.2019.8942853

Chiming Guo, Yongsheng Bai, R. Peng

引用次数: 3