A Fault Diagnosis Method for Current Sensor Gain of Permanent Magnet Linear Motor

Abstract

The invention discloses a method for diagnosing the gain fault of the current sensor of a permanent magnet linear motor. The diagnosis method first combines the switch trigger signal of the three-phase bridge inverter of the motor and the voltage of the DC bus to estimate the line voltage at the end of the motor, and then passes the line phase transform and park transform to obtain the dq axis voltage of the motor, and then use a discrete current observer to initially estimate the dq axis current of the motor, compare the estimated current with the measured current of the current sensor, and perform signal processing and analysis. The occurrence of the fault is judged by the fluctuation amplitude of the signal residual, the fault type is judged as a gain fault by the double frequency fluctuation of the signal residual, and finally the gain fault coefficient is constructed to judge the fault phase, so as to realize the location of the gain fault. The invention can diagnose the gain fault of the phase current sensor of the permanent magnet linear motor without adding a special sensor, and at the same time, the method of the invention is less affected by inaccurate motor parameters.

Description

technical field [0001] The invention relates to a fault diagnosis method for current sensor gain of a permanent magnet linear motor, which belongs to the field of motor fault diagnosis. Background technique [0002] In the closed-loop control system of the motor, the current information and speed information of the motor are usually required. During the operation of the motor, due to problems such as current impact and electromagnetic interference, it is easy to cause a gain failure of the current sensor and affect the operation. [0003] At this stage, the analysis of current sensor faults is mainly divided into two types: model-based diagnosis methods and signal-based diagnosis methods. The model-based diagnosis method is to construct an observer model to observe the actual current of the motor, compare it with the measured current, and diagnose the fault. This type of fault has a high dependence on the parameters of the motor model, and when the model is inaccurate, it ...

AI Technical Summary

Problems solved by technology

Existing diagnostic methods cannot meet the requirements of low dependence on the accuracy of model parameters and are applicable to motor drive systems with two-phase current sensors.

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