论文部分内容阅读
设想某工程机械有6种不同部位、不同程度的故障状态,每种状态采用时域与频域的9个特征参数作样本指标。令X_(ik)=(X_(i1),X_(i2)……X_(i9))分别表示峰峰值、峰值、方差、均方幅值、峰值指标、基频幅值、二次谐波幅值、概率密度分布宽度和概率密度最大幅值。于是,就有表1的结果。其中概率密度分布宽度表示正态分布曲线的胖瘦,概率密度最大幅值表示正态分布曲线的高度,即信号能量的集中程度。
Imagine a construction machinery has 6 different parts, different levels of fault status, each state using the 9 parameters in time and frequency domain samples as a sample indicator. Let X_ (ik) = (X_ (i1), X_ (i2) ... X_ (i9)) denote peak-peak, peak, variance, mean square amplitude, peak index, fundamental frequency amplitude, second harmonic amplitude Value, probability density distribution width and probability density maximum amplitude. Thus, there is the result of Table 1. The width of the probability density distribution represents the fat and thin of the normal distribution curve, and the maximum amplitude of the probability density represents the height of the normal distribution curve, that is, the concentration of the signal energy.