基于加权D—S证据理论信息融合的故障诊断方法及其应用

针对新产品因故障概率数据掌握不充分使其故障诊断较为困难的问题，提出了一种基于加权D—S证据理论多源信息融合的故障诊断方法。该方法采用D-S证据融合，解决了缺乏故障概率分布模型或准确数学分析无效的问题，引入加权Ds证据理论融合方法进行故障诊断，用历史故障估计的正确率作为确定信息源当前检测估计值的置信程度调整，实现了故障诊断的历史数据对当前诊断结果的修正。对新型船舶气象仪故障诊断结果表明，该方法在故障概率和故障经验知识掌握不充分时，实现故障诊断是非常有效的。

Fault diagnosis method based on multi-information fusion with weighted D-S evidence theory and its application

Aiming at the difficulty in fault diagnosis caused by insufficiency of failure probability for the new product, a fault diagnosis method based on multi-information fusion with the weighted D-S evidence theory was proposed,which was used to deal with the problem of the lack of fault probability distribution model or the non-effective of the accurate mathematical analysis. In order to regulate confidence degree of the present fault diagnosis estimation by use of the past accuracy about the fault diagnosis,the weighted D-S evidence theory was applied. The modified fault diagnosis with the past fault diagnosis accuracy was fulfilled. The results of the fault diagnosis for the late model marine meteorological instrument show that the proposed method is feasible and efficacious while the fault probability and the knowledge are insufficient.