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Fault Diagnosis of Mine Hoist Braking System Based on Wavelet Packet and Support Vector Machine

机译:基于小波包和支持向量机的矿井葫芦制动系统故障诊断

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This paper concerns mine hoist braking system fault diagnosis with the combination of wavelet packet and support vector machine. It is motivated by the scarce of fault samples in mine hoist such requiring very high security system. A novel approach is presented in order to diagnose blockage piston in cylinder, a typical fault of mine hoist braking system. This method mainly consists of three steps: (1) apply 3 levels wavelet package to construct and reconstruct signal of brake distance-time, extract fault feature vectors (2) set up training samples (3) establish a SVM fault classifier to complete fault diagnosis. Experimental results show that SVM method can effectively accomplish the blockage piston in cylinder fault diagnosis of braking system and has a high adaptability for fault diagnosis in the case of smaller number of samples.
机译:本文涉及矿井葫芦制动系统故障诊断与小波包和支持向量机的组合。这是通过矿井葫芦的故障样本稀缺的动机,这是如此需要非常高的安全系统。提出了一种新的方法,以便在圆柱体中诊断堵塞活塞,矿井葫芦制动系统的典型故障。这种方法主要由三个步骤组成:(1)应用3级小波包构造和重建制动距离的信号,提取故障特征向量(2)设置训练样本(3)建立SVM故障分类器以完成故障诊断。实验结果表明,SVM方法可以有效地完成制动系统的气缸故障诊断中的阻塞活塞,并且在较少数量的样品的情况下具有高适应性的故障诊断。

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