计算机工程与应用2019，Vol.55Issue(20)：197-201,5.DOI:10.3778/j.issn.1002-8331.1903-0365
基于DPCA和改进证据理论的融合式故障诊断
Fusion Fault Diagnosis Using DPCA&Improved Evidence Theory
摘要
Abstract
In order to comprehensively and reasonably utilize multi-source information of equipments to improve the accu-racy of fault diagnosis, a method of fusion fault diagnosis is proposed based on Dynamic Principle Component Analysis (DPCA)and improved evidence theory. This method constitutes multi evidences to fault diagnosis at many levels by means of DPCA and revises the basic assignment probability according to the authoritative coefficients based on statisti-cal errors. The method of time authoritative conversion of evidence and conflict weighted assignment are proposed to improve evidence combination rules. The experimental results show that the weighted fusion treatment of multi-source information evidences can reduce the conflicts based on single information, which can increase reliability by 50% and greatly reduce uncertainty. The results also are unaffected by the decline of evidence authority. So the method can effec-tively improve the accuracy of fault diagnosis.关键词
动态主元分析/证据理论/故障诊断/多信息融合Key words
dynamic principle component analysis/evidence theory/fault diagnosis/multi-source information fusion分类
信息技术与安全科学引用本文复制引用
李果,马春阳,马建晓..基于DPCA和改进证据理论的融合式故障诊断[J].计算机工程与应用,2019,55(20):197-201,5.基金项目
国家自然科学基金(No.61306007) （No.61306007）
南阳师范学院博士专项基金(No.2018ZX024). （No.2018ZX024）
