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提出了一种基于粒子群优化径向基神经网络的液压钻机故障诊断方法。该方法使用虚拟仪器及LabVIEW软件对液压钻机的特征信号进行采集,利用粒子群优化算法对径向基神经网络的径向基中心值、宽度以及权值进行优化,实现了液压钻机的故障诊断。结果表明,基于粒子群优化径向基神经网络的液压钻机故障诊断方法在小样本情况下,诊断准确率高,实用性强。
A fault diagnosis method of hydraulic drilling rig based on particle swarm optimization radial basis neural network is proposed. The method uses the virtual instrument and LabVIEW software to collect the characteristic signals of the hydraulic drilling rig, and uses the particle swarm optimization algorithm to optimize the center value, width and weight of the radial basis of the radial basis neural network, and realizes the fault diagnosis of the hydraulic rig. The results show that the method of fault diagnosis of hydraulic drilling rig based on particle swarm optimization radial basis function neural network has high diagnostic accuracy and good practicability in the case of small sample.