机构

• 自动化研究所 [2]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [3]

内容类型

• 期刊论文 [2]
• 会议论文 [1]

发表日期

• 2023 [1]
• 2022 [1]
• 2006 [1]

学科主题

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Local Linear Generalized Autoencoder-Based Incipient Fault Detection for Electrical Drive Systems of High-Speed Trains 期刊论文  OAI收割 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 页码: 9 作者:  Cheng, Chao;  Ju, Yunfei;  Xu, Shuiqing;  Lv, Yisheng;  Chen, Hongtian   |  收藏  |  浏览/下载：20/0  |  提交时间：2023/11/17 Incipient fault  fault detection (FD)  manifold learning  generalized autocoder (GAE)  electrical drive systems  high-speed trains   Distributed Fault-Tolerant Consensus Tracking of Multi-Agent Systems Under Cyber-Attacks 期刊论文  OAI收割 IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 6, 页码: 1037-1048 作者:  Chun Liu;  Bin Jiang;  Xiaofan Wang;  Huiliao Yang;  Shaorong Xie   |  收藏  |  浏览/下载：38/0  |  提交时间：2022/05/30 Cyberattacks  fault-tolerant consensus tracking  incipient and abrupt actuator faults  nonlinear multi-agent systems  unknown input observer   Abrupt sensor fault diagnosis based on wavelet network (EI CONFERENCE) 会议论文  OAI收割 2006 IEEE International Conference on Information Acquisition, ICIA 2006, August 20, 2006 - August 23, 2006, Weihai, Shandong, China 作者:  Li W.;  Li W.;  Zhang H.;  Zhang H. 收藏  |  浏览/下载：17/0  |  提交时间：2013/03/25 The possible faults of a sensor may be classified as abrupt (sudden) faults and incipient (slowly developing) faults. This paper focuses on the abrupt faults of a sensor. Due to the limited number of scales  a single wavelet amplitude map has not enough scales to describe all details of the signal. The sampling grid in the scale direction is rather sparse  Some of the fault information will be leaked under such sparse grid. To make up for the deficiency of scalar orthogonal wavelet transform in the application of abrupt fault diagnosis  multiwavelet packets transform was introduced into the field of abrupt fault diagnosis. The distribution differences of the signal energy on decomposed multiwavelet scales of the signal before and after the fault occurring are extracted as the fault feature and used as the input of multi-dimensional wavelet network. A new model-free diagnostic method for isolating abrupt sensor faults is developed based on a proposed algorithm of multi-dimensional wavelet network constructing. The method has been proved to be quite effective in the detection of sensor abrupt fault. 2006 IEEE.