A novel identification method of Volterra series in rotor-bearing system for fault diagnosis
A novel identification method of Volterra series in rotor-bearing system for fault diagnosis
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DOI：
10.1016/j.ymssp.2015.05.006
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发表时间：
2016
影响因子：
8.4
通讯作者：
Xin Xia;Jian-zhong Zhou;Jian Xiao;Han Xiao
中科院分区：
文献类型：
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作者：
Xin Xia;Jian-zhong Zhou;Jian Xiao;Han Xiao
沃尔泰拉级数被广泛应用于转子-轴承系统的故障诊断中，以防止危险事故的发生，提高经济效益。由于转子-轴承系统激励信号的周期性，沃尔泰拉级数的辨识涉及无穷解问题。但在现有的沃尔泰拉级数辨识方法中没有考虑这个问题。本文提出了一种用于沃尔泰拉序列辨识的关键核粒子群算法（KK-PSO）。该方法不直接辨识沃尔泰拉级数，而是先找出沃尔泰拉的关键核，从而简化了沃尔泰拉模型。然后，利用粒子群算法对最简单形式的沃尔泰拉级数进行辨识。其次，通过与最小二乘（LS）方法和传统PSO方法的比较，仿真验证了KK-PSO方法的可行性和有效性。最后，对转子轴承试验台进行了实验测试，得到了不同状态下的沃尔泰拉级数，并利用沃尔泰拉级数的核函数对不同的故障状态进行分类，建立了基于神经网络的故障诊断系统。分析结果表明，KK-PSO方法对沃尔泰拉系列转子-轴承系统的辨识具有良好的能力，所提出的方法可以进一步提高故障诊断的准确性。
Volterra series is widely employed in the fault diagnosis of rotor-bearing system to prevent dangerous accidents and improve economic efficiency. The identification of the Volterra series involves the infinite-solution problems which is caused by the periodic characteristic of the excitation signal of rotor-bearing system. But this problem has not been considered in the current identification methods of the Volterra series. In this paper, a key kernels-PSO (KK-PSO) method is proposed for Volterra series identification. Instead of identifying the Volterra series directly, the key kernels of Volterra are found out to simply the Volterra model firstly. Then, the Volterra series with the simplest formation is identified by the PSO method. Next, simulation verification is utilized to verify the feasibility and effectiveness of the KK-PSO method by comparison to the least square (LS) method and traditional PSO method. Finally, experimental tests have been done to get the Volterra series of a rotor-bearing test rig in different states, and a fault diagnosis system is built with a neural network to classify different fault conditions by the kernels of the Volterra series. The analysis results indicate that the KK-PSO method performs good capability on the identification of Volterra series of rotor-bearing system, and the proposed method can further improve the accuracy of fault diagnosis.