时域信号分为无量纲和无量纲两类。尺寸参数包括最大值、峰值、平均值、方差

Time domain signals are divided into two categories: dimensionless and dimensionless. Dimensional parameters include maximum value, peak value, average value, variance, etc. These parameters vary greatly under different speeds and loads, which is not conducive to practical application. The dimensionless parameters include pulse index, kurtosis value, peak factor, margin index, etc. The dimensionless parameters of vibration signal in time domain are more sensitive. When the bearing runs smoothly, the dimensionless parameters are small and stable. Once the bearing fails, these indicators will be significant Variations can effectively characterize the running state of rolling bearings. Some indicators are usually applied at the same time for different parameter sensitivities, which has a good effect in bearing fault diagnosis and classification research.

Time domain signals are divided into two categories, no volume and no volume. Dimension parameters include maximum value, peak, average, variance, etc., which vary greatly at different speeds and loads and are not conducive to practical application. No volume parameters have pulse indicators, cliff values, peak factors, margin indicators, vibration signal timeless no volume spline parameters are more sensitive, when the bearing smooth operation no volume strap parameters are small and stable, once the bearing fault these indicators will have significant changes, can effectively characterize the rolling bearing operating state, for different parameters sensitivity is usually applied at the same time, in the bearing fault diagnosis and classification research has a good effect

Time domain signals can be divided into dimensionless and dimensionless. Size parameters include maximum value, peak value, average value, variance, etc. these parameters vary greatly under different speeds and loads, which is not conducive to practical application. The dimensionless parameters include impulse index, kurtosis value, peak factor, margin index, etc. the dimensionless parameters of vibration signal in time domain are relatively sensitive. When the bearing runs smoothly, the dimensionless parameters are small and stable. Once the bearing fails, these indexes will change significantly, which can effectively represent the running state of rolling bearing. According to the sensitivity of different parameters, some indexes are usually applied at the same time The research of bearing fault diagnosis and classification has a good effect<br>