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| 摘要: |
| 针对模糊C均值聚类算法容易陷入局部极值和对初始值敏感的缺点，提出了一种粒子群优化模糊聚类算法，该算法利用粒子群优化算法寻找最优聚类中心，运用WFCM进行加权模糊聚类，能较大提高聚类的有效性；将该算法应用于煤气鼓风机组振动故障诊断中进行诊断仿真，结果表明：该算法较大提高了故障诊断的正确率。 |
| 关键词: 粒子群模糊聚类 煤气鼓风机组 故障诊断 |
| DOI： |
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| Application of PSO Fuzzy Clustering Algorithm to Fault Diagnosis of Gas Blower Group Vibration |
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ZHAO Xin
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| Abstract: |
| According to the fault that fuzzy C-means clustering algorithm is easily involved in loal extreme and is sensitive to initial value,a kind of PSO fuzzy clustering algorighm is proposed,this algorithm searches the optimal clustering center based on PSO algorithm,uses WFCW to conduct weighted fuzzy cluster and is able to relatively more largely improve the validity of the cluster.This algorithm is used in diagnosis simulation in the fault diagosis of gas blower group vibation and the results show that this algorithm can relatively more largely improve the accurate rate of fault diagnosis. |
| Key words: particle swarm optimization(PSO) gas blower group fault diagnosis |
