| 贾 嵘,洪 刚,武 桦,薛建辉.基于IPSO优化LSSVM的水轮发电机组振动故障诊断[J].水利学报,2011,42(3): |
| 基于IPSO优化LSSVM的水轮发电机组振动故障诊断 |
| Vibration fault diagnosis of hydroelectric generating unit by Least Squares Support VectorMachine based on Improved Particle Swarm Optimization |
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| DOI： |
| 中文关键词: 水轮发电机组 振动 故障诊断 最小二乘支持向量机 改进粒子群算法 |
| 英文关键词: hydroelectric generating unit vibration faults diagnosis least squares support vector ma?
chine improved particle swarm optimization algorithm |
| 基金项目: |
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| 摘要点击次数: 3517 |
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| 中文摘要: |
| 提出改进的粒子群算法，并与最小二乘支持向量机相结合，得到基于IPSO-LSSVM的水轮发电机组故障诊断方法。改进后的粒子群算法能较好地调整算法在全局与局部搜索能力之间的平衡，将其应用于LSSVM的参数优化，可以提高故障诊断的精度和效率。实例分析结果表明，本文模型不仅能够取得良好的分类效果，而且诊断速度与精度均高于采用BP神经网络、LSSVM以及PSO-LSSVM等方法，适合在实际工程中应用。 |
| 英文摘要: |
| In order to diagnosis the vibration faults of hydroelectric generating unit quickly and accurately，an Improved Particle Swarm Optimization （IPSO） algorithm is proposed. The new method of fault diagnosis was combined with the Least Squares Support Vector Machine （LSSVM） to form the IPSO-LSSVM algorithm. The algorithm can adjust the balance between global and local search capabilities suitably，which optimize the parameters of LSSVM to improve the precision and efficiency of the faults diagnose. The comparison with experiment result shows that the IPSO-LSSVM method not only has attained good classification results，but also the precision and rate of diagnostic is better than BP network，LSSVM and PSO-LSSVM.Consequently，the IPSO-LSSVM model is a proper alternative for vibration fault diagnosis of hydroelectric generating unit. |
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