Motor bearing fault diagnosis method based on artificial neural network
An artificial neural network and motor bearing technology, which is applied in the direction of mechanical bearing testing, mechanical component testing, machine/structural component testing, etc., can solve problems such as inability to accurately identify fault types, achieve strong anti-interference ability, and identify The effect of high accuracy and strong practicality
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[0026] The technical solution of the present invention is clearly and completely described below, obviously, the described embodiments are only some embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0027] The motor bearing fault diagnosis method based on artificial neural network of the present invention, comprises the following steps successively:
[0028] (1) Feature vector extraction: use the vibration sensor to collect the vibration signals of the inner ring, outer ring and rolling elements of the motor bearing in different states as feature data, form a feature vector, and use it as the input of the neural network;
[0029] Extract the four time-domain features of the inner ring, outer ring and rolling elements of the motor bearing, including mean value, va...
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