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Internal Leakage Detection of Hydraulic Cylinder Based on Wavelet Analysis and Backpropagation Neural Network

机译:基于小波分析的液压缸内漏电检测和背展交神经网络

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Hydraulic cylinders are used as actuators of the hydraulic system of cable pendulum bar in a space launch tower. Internal leakage is a common failure mode that severely affects space launch missions. Fast and accurate identification of hydraulic cylinder leakage can ensure the safety of hydraulic cylinders and the whole system. In this paper, wavelet analysis is used to extract fault features, and a backpropagation neural network is used to establish a classifier for intelligent identification of hydraulic cylinder leakage faults. Experimental results show that the proposed method has high accuracy, providing a basis for the realization of intelligent state monitoring of launch site hydraulic systems.
机译:液压缸用作空间发射塔的电缆摆栏液压系统的致动器。内部泄漏是一个常见的失败模式,严重影响太空发射任务。快速准确地识别液压缸泄漏可确保液压缸和整个系统的安全性。在本文中,小波分析用于提取故障特征,使用反向化神经网络来建立智能识别液压缸泄漏故障的分类器。实验结果表明,该方法具有高精度,为实现发射部位液压系统的智能状态监测提供了依据。

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