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Alternative TitleFault Detection of AUV Resource Exploration System Based on Multi-block Information Extraction
郭大权1,2,4; 杨宗圣1,2,3,4; 周晓锋1,2,4; 李帅1,2,3,4; 徐春晖1,2
Source Publication控制与决策
Contribution Rank1
Funding Organization国家重点研发计划资助(2017YFC0306800)
KeywordAUV 主元分析 故障检测 信息提取 多块建模


Other Abstract

Aiming at the problems of AUV of Qianlong 2 in the actual navigation process, such as multi-variable correlation, multiple fault types, large numerical variation influenced by operation status and environmental changes, and strong noise, a new PCA fault detection method based on block information extraction is proposed. Firstly, according to the multiple correlations among variables, the correlation information between variables is extracted by sliding window and correlation coefficient method; secondly, according to the basic stable characteristics of change rate in different operating states and environments, for different types of faults, the cumulative error information of each order statistics of change rate information and change rate information is extracted separately; Finally, three sub-blocks are built based on the extracted feature information, and PCA model is built and tested for each sub-block respectively. After de-noising by median filtering, the detected results are fused by Bayesian inference. The validity of the method is verified by testing the actual operation data of Qianlong 2.

Document Type期刊论文
Corresponding Author周晓锋
Recommended Citation
GB/T 7714
郭大权,杨宗圣,周晓锋,等. 基于多块信息提取的AUV资源勘查系统故障检测[J]. 控制与决策,2021,36(4):790-800.
APA 郭大权,杨宗圣,周晓锋,李帅,&徐春晖.(2021).基于多块信息提取的AUV资源勘查系统故障检测.控制与决策,36(4),790-800.
MLA 郭大权,et al."基于多块信息提取的AUV资源勘查系统故障检测".控制与决策 36.4(2021):790-800.
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