SIA OpenIR  > 数字工厂研究室
基于多块信息提取的AUV资源勘查系统故障检测
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
Department数字工厂研究室
Source Publication控制与决策
ISSN1001-0920
2020
Pages1-10
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
Abstract

针对“潜龙二号”AUV在实际航行过程中,资源勘查系统传感器数据有着多重变量相关性、故障类型多样、受运行状态和环境变化影响数值变化大以及噪声强等问题,提出一种新的基于多块信息提取的主元分析(PCA)故障检测方法.首先,针对变量之间的多重相关性,通过滑窗和相关系数的方法提取变量间相关性信息;然后,根据变化率在不同运行状态和环境下基本稳定的特点,对于不同类型故障,分别提取变化率信息和变化率信息的各阶统计量累积误差信息;最后,基于提取的特征信息建立3个子块,对每个子块分别建立PCA模型并进行检测,将检测的结果通过中值滤波去噪后,用贝叶斯推断进行融合.通过对“潜龙二号”实际运行数据进行检测,验证了该方法的有效性.

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.

Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/25955
Collection数字工厂研究室
Corresponding Author周晓锋
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院机器人与智能制造创新研究院
3.中国科学院网络化控制系统重点实验室
4.中国科学院大学
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,2020:1-10.
APA 郭大权,杨宗圣,周晓锋,李帅,&徐春晖.(2020).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,1-10.
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 (2020):1-10.
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