【摘要】 针对机器设备磨损产生的因素多,而且磨损量的多少与产生的因素具有高度非线性,磨损难以预测的问题,同时考虑到监测得到的数据为小样本事件也是磨损难以预测的原因,在齿轮箱实验数据的基础上,利用最小二乘支持向量机,给出预测步骤,提出一种以载荷、温度、振动信号特征、速度和时间为输入量,机器设备的磨损量为输出量的预测方法。用齿轮箱的实验数据验证了所提出的方法的有效性。更多还原

【Abstract】 The wear loss of the machine is affected by many factors and the relationship between wear loss and factors is a kind of typical nonlinear,so how to forecast the wear loss is very difficult.In the same time,small monitoring samples data is one of the reasons that the wear loss can’t be predicted accurately.In order to predict wear loss accurately,least-square-support-vector machine was chose to build up a new method to predict the wear loss of the gear box.Load,the features of vibration signal,temperature,velocity and time of the gear box were chose as inputs,the wear loss was chose as output.The detail steps of the method was shown and discussed.An experiment about a gear box was introduced to verify the method and the result shows the method is effective.更多还原