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改进信息熵和ELM-PSO算法及其仿真验证

Fault Diagnosis of Large Wind Turbines Based on Information Entropy and ELM-PSO
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摘要 利用ELM和经过PSO算法的模型优化后进行数据对比,发现ELM-PSO的精度在ELM之上,所以利用ELM-PSO可在一定精度上完全反映真实数据的变化。通过对风机振动异常的分析和处理,说明在振动异常情况下要采用先进的诊断技术,按照监测频谱图逐步诊断出振动异常的真正原因并做出评价,并根据诊断结果提出改进措施,达到实现预防性维护的目的。 Using ELM and the model optimization of PSO algorithm to compare the data,it is found that the accuracy of ELM-PSO is above ELM,so ELM-PSO can completely reflect the change of real data in a certain precision.Through the analysis and treatment of fan vibration anomaly,it is shown that advanced diagnosis technology should be adopted under the condition of vibration anomaly,the real cause of vibration anomaly should be diagnosed step by step according to the monitoring spectrum diagram,and the improvement measures should be put forward according to the diagnosis results,so as to achieve the purpose of preventive maintenance.
作者 赵丹华 张向锋 王致杰 于荷 姜慧楠 ZHAO Dan-Hua;ZHANG Xiang-Feng;WANG Zhi-Jie;YU He;JIANG Hui-Nan(College of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China)
出处 《新一代信息技术》 2019年第14期83-88,共6页 New Generation of Information Technology
关键词 故障诊断 定量定性分析 ELM-PSO 频谱图 Fault Diagnosis Quantitative Qualitative Analysis ELM-PSO Spectrogram
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