机构

• 计算技术研究所 [1]
• 长春光学精密机械与物... [1]
• 重庆绿色智能技术研究... [1]
• 沈阳自动化研究所 [1]

采集方式

• OAI收割 [4]

内容类型

• 会议论文 [2]
• 期刊论文 [2]

发表日期

• 2016 [1]
• 2015 [1]
• 2011 [1]
• 2006 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4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 Nonlinear fault detection threshold optimization method for RAIM algorithm using a heuristic approach 期刊论文  OAI收割 GPS SOLUTIONS, 2016, 卷号: 20, 期号: 4, 页码: 863-875 作者:  He, Pan;  Liu, Gang;  Tan, Chun;  Lu, Yan-e   |  收藏  |  浏览/下载：36/0  |  提交时间：2018/03/15 Integrity monitoring  Fault detection  Optimization model  Genetic algorithm  GPS system  RAIM algorithm   Detection of soft errors in LU decomposition with partial pivoting using algorithm-based fault tolerance 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 2015, 卷号: 29, 期号: 4, 页码: 422-436 作者:  Yao, Erlin;  Zhang, Jiutian;  Chen, Mingyu;  Tan, Guangming;  Sun, Ninghui   |  收藏  |  浏览/下载：36/0  |  提交时间：2019/12/13 Soft error  error detection  LU Decomposition with Partial Pivoting  Algorithm-Based Fault Tolerance   Nonlinear system fault detection based on TLLE 会议论文  OAI收割 Guangzhou, China, September 16-18, 2011 作者:  Zhang W(张伟)   |  收藏  |  浏览/下载：15/0  |  提交时间：2012/06/06 Classical Methods  Euclidean Distance  Fault Detection Algorithm  Locally Linear Embedding  System Fault Detection  Tangent Space   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.