基于改进D-S的水电机组集成故障诊断研究  

Fault diagnosis based on improved D-S evidential theory for hydroelectric generator units

作　　者：程加堂[1] 艾莉[1] 段志梅[1] 熊燕[1] 

机构地区：[1]红河学院工学院,云南蒙自661199

出　　处：《水力发电学报》2014年第5期216-220,共5页Journal of Hydroelectric Engineering

基　　金：云南省教育厅科学研究基金(2012Y450)

摘　　要：针对常规水电机组振动故障诊断技术中易出现错判及诊断可靠性低等问题,提出了一种基于改进D-S证据理论的集成故障诊断方法。根据水电机组振动故障的频域信号,由模拟退火粒子群混合算法来处理证据理论的基本概率分配问题。再利用改进D-S理论来实现可信度分配的合理赋值,最后进行多信息的融合决策。实例表明,该方法可以在原始证据出现高度冲突以及相一致的情况下,都具有较高的诊断可信度,从而实现了对水电机组振动故障模式的有效识别。An integrated fault diagnosis method based on improved D-S evidence theory is presented for vibration faults of hydroelectric generator units to improve conventional diagnosis of low reliability. It applies a hybrid algorithm of simulation annealing-particle swarm optimization to basic probability assignment of evidence theory according to frequency domain signals of vibration faults, realizes reasonable probability assignment by improved D-S theory, and finally implements fusion decision of multi-source information. Case studies show that this method is reliable in vibration fault diagnosis whether the original evidences are in high conflict or consistent and it achieves effective recognition of vibration failure modes of hydroelectric generator units.

关 键 词：水电工程 故障诊断 信息融合 改进D-S证据理论 水电机组 

分 类 号：TM312[电气工程—电机]