加权模糊相对熵在电机转子故障模糊识别中的应用

提出了一种基于加权模糊相对熵的电机转子故障模糊识别方法。该方法将加权思想引入到模糊相对熵,用于识别电机转子故障严重程度。加权方法的引入增加了信息量丰富的符号区间的模糊相对熵占全部区间模糊相对熵的比重,可以更充分、合理地利用该区间的故障信息进行故障识别。电机转子断条故障诊断仿真实验结果表明,提出的方法有效地实现了电机故障的定量分析,能够准确地识别出电机转子故障的严重程度,使算法的鲁棒性得到了改善,故障分类的可靠性及准确程度得到了提高。

A fuzzy recognition method based on weighted fuzzy relative entropy is proposed to recognize motor rotor fault,and it introduces weighting idea into fuzzy relative entropy to identify the fault severity level of motor rotor.With the introduction of the weighting method,the proportion of fuzzy relative entropy of the symbolic regions with abundant information would be increased among the fuzzy relative entropies of the whole region,and with the fault information included in symbolic regions with abundant inf...

国家863计划资助项目(2007AA041201); 中国科学院先进制造基地支持项目(CX07-03-003); 中国科学院沈阳自动化所知识创新工程青年人才领域前沿基金资助项目(2007AR005)