Rolling bearing state monitoring method based on weighted similarity measure
A weighted similarity, rolling bearing technology, applied in the field of rolling bearing condition monitoring and bearing, can solve the problems of difficulty in timely and accurate detection of early faults of rolling bearings, poor noise resistance and robustness, and large errors, to simplify the dynamic analysis process. , good noise immunity and robustness, the effect of eliminating influence
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[0046] Examples such as figure 1 As shown, the rolling bearing condition monitoring method based on the weighted similarity measure is implemented in the following steps:
[0047] 1) Use the acceleration sensor to measure the vibration signal of the rolling bearing at fixed time intervals, and record the signal acquired for the ith time as x ik (k=1, 2, ..., N), N is the length of the sampling signal; the time interval is generally 10 minutes;
[0048] 2) According to the rising or falling relationship between adjacent sequence points, the sequence x ik Convert to sequence of binary symbols ,
[0049] ,
[0050] 3) Define m consecutive characters as a word, convert the binary symbol sequence into a set containing different word types by sliding the data points, calculate the frequency of occurrence of each word type, and finally get a length of 2 m The frequency sequence of words; generally set m=8;
[0051] 4) Taking the initial state as the normal reference state...
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