齿轮是雷达传动系统的重要组成部分,其运行状态直接影响雷达精度和可靠性。因此,对雷达的齿轮运行状态进行监测诊断,保证其安全可靠地运行在最佳状态,具有重要意义。文中基于振动信号特征参数和误差逆传播神经网络算法,编制了齿轮运行状态智能诊断程序,实现了原理性实验中齿轮运行状态的准确识别,进一步将该方法应用于某雷达齿轮传动系统运行状态诊断监测中,取得很好结果,证明了该智能诊断技术应用在雷达机械运行状态监测的工程可行性。

As an important part of the servo drive system of radar, gear′s running state directly affects the accuracy and reliability of radar. Monitoring and diagnosing gear running status, to ensure the safe and reliable operation in the best state, is of great significance. Using the BP neural network, the intelligent monitoring and diagnosis procedures for the gear running status have been programmed based on characteristic parameters of vibration signal, with which, the operating status of the experimental gearbox has been accurately identified. Further on, the method was successful applied to a practical engineering, proving the engineering feasibility of the application of intelligent diagnosis technology in radar mechanical condition monitoring.

TN957