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将模式识别技术引入到工程机械液压系统的状态监测,以提高监测的可靠性。首先介绍了三种主要的模式识别方法,在此基础上以阀控液压缸系统为例阐述了如何利用神经网络模式识别技术对液压泵异常状态进行监测。结果表明,本文提出的方法可以快速、准确地监测出液压泵的异常状态。
The pattern recognition technology is introduced into the condition monitoring of hydraulic system of construction machinery to improve the reliability of monitoring. Firstly, three main methods of pattern recognition are introduced. Based on this, the valve-controlled hydraulic cylinder system is taken as an example to illustrate how to monitor abnormal state of hydraulic pump by using neural network pattern recognition technology. The results show that the proposed method can quickly and accurately monitor the abnormal state of the hydraulic pump.