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Study on Mechanical Concurrent Fault Diagnosis Method Based on PSO-MRLSSVM

机译:基于PSO-MRLSSVM的机械并发故障诊断方法研究

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In view of those characteristics such as nonlinearity and high dimensional features for mechanical concurrent faults and any conventional classifier being not able to fit multi-output needs, a concurrent fault classification method based on PSO-MRLSSVM was put forward, where the simple and fast searching ability of PSO may be utilized to optimize the penalty and Kernel parameters for the MRLSSVM algorithm; thus, the aimlessness (manually specifying parameters) may be prevented and the prediction precision of MRLSSVM may be improved. Experimental results indicate that our mechanical concurrent fault diagnosis model based on PSO-MRLSSVMs works well for effective identification of concurrent fault types and diagnosis effects are good.
机译:鉴于这些特征,例如机械并发故障的非线性和高尺​​寸特征以及任何传统分类器无法拟合多输出需求,提出了一种基于PSO-MRLSSVM的并发故障分类方法,在其中简单快速地搜索PSO的能力可用于优化MRLSVM算法的惩罚和内核参数;因此,可以防止漫无目的性(手动指定参数),并且可以提高MRLSSVM的预测精度。实验结果表明,我们基于PSO-MRLSSVMS的机械并发故障诊断模型适用于有效识别并发故障类型和诊断效应。

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