Aviation electromechanical actuator fault diagnosis method

Abstract

The invention relates to an aviation electromechanical actuator fault diagnosis method based on the symbolic dynamic information entropy theory and the improved Parks clustering algorithm. Symbolization processing of amplitude time series of bus current of an inverter side of an electromagnetic actuator can be carried out, and the calculated information entropy value and the calculated maximum amplitude of the bus current time series can be used as the two characteristic quantities of the electromechanical actuator fault diagnosis, and then a standard fault characteristic matrix based on training samples can be established, and then the fault types of the sample to be detected can be determined by calculating the distance between the sample to be detected and the fault characteristic matrix by adopting the improved Parks clustering algorithm. Compared to the conventional methods, the characteristic extraction and fault diagnosis method provided by the invention is advantageous in that the calculation is simple, and the required data size is small, and various electromechanical actuator faults can be effectively identified and diagnosed.

Description

technical field [0001] The invention belongs to a fault diagnosis method for an aviation electromechanical actuator, in particular to a fault diagnosis method for an aviation electromechanical actuator based on a symbolic dynamics information entropy theory and an improved parks clustering algorithm. Background technique [0002] Aero-mechanical actuator (Electro-mechanical actuator, EMA) is composed of brushless DC motor, ball screw and gear reducer. Compared with hydraulic actuators, electromechanical actuators have the characteristics of small size, light weight, and easy maintenance, so they are widely used in the aviation field. The research on fault diagnosis methods of electromechanical actuators is an important task to ensure the safe operation of aviation equipment. [0003] EMA faults include electrical faults and mechanical faults. Common electrical faults are mainly concentrated in the three parts of the motor winding, the motor drive system and the Hall positi...

AI Technical Summary

Problems solved by technology

[0008] In order to avoid the deficiencies of the prior art, the present invention proposes a fault diagnosis method for aviation electromechanical actuators based on the symbolic dynamics information entropy theory and the improved parks clustering algorithm, which solves the problem that the traditional fault diagnosis method can only detect one or two Actuator faults, and the fault feature extraction process is relatively complex and the amount of calculation is large

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