PMSM drive system inverter open-circuit fault online diagnosis method

A drive system, open-circuit fault technology, applied in the direction of instruments, measuring electrical variables, measuring devices, etc., can solve similar problems, reduce the possibility of misdiagnosis, do not affect the drive control, and increase the effect of hardware equipment

Active Publication Date: 2020-08-18
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

On the other hand, the data currently used for learning is usually directly obtained by signal s

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  • PMSM drive system inverter open-circuit fault online diagnosis method
  • PMSM drive system inverter open-circuit fault online diagnosis method
  • PMSM drive system inverter open-circuit fault online diagnosis method

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[0041] The present invention will now be further described in conjunction with the embodiments and drawings:

[0042] Such as figure 1 As shown, the PMSM drive system inverter open circuit fault diagnosis method in the present invention. The specific implementation is as follows:

[0043] Step 1: Use the state observer to estimate the PMSM three-phase current, obtain the three-phase current observation value, and make the difference between the current observation value and the actual value of the three-phase current in the system feedback to obtain the observation residual of the three-phase current.

[0044] The observer used to track the PMSM three-phase current is the Lomberg observer, and the expression is:

[0045]

[0046] among them, u(t)=(u d ,u q ) T , Y(t)=(i d ,i q ) T , K is the feedback coefficient matrix, A, B, C are the coefficient matrix in the PMSM state equation.

[0047] Such as figure 2 Shown is the change of the three-phase current residuals of the motor when th...

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Abstract

The invention relates to a PMSM drive system inverter open-circuit fault online diagnosis method, which can carry out online fault diagnosis and positioning on various inverter open-circuit faults. The method comprises the steps: introducing a Luenberger observer to track a PMSM three-phase current so as to obtain a three-phase current observation residual error as a fault diagnosis basis; designing a sampling strategy, and obtaining an original sample set for training; in offline training, introducing a principal component analysis method to preprocess an original sample set to obtain a datadimension reduction model, and then acquiring a classification model by training a support vector machine; finally, operating the dimension reduction model and the classification model in a driving system, and achieving the online diagnosis and positioning of faults. According to the method, hardware equipment is not added, and driving control is not affected; meanwhile, the method is not affectedby load and model parameter changes; through machine learning of actual working conditions, the method does not depend on a diagnosis basis set manually, and the possibility of misdiagnosis is reduced.

Description

technical field [0001] The invention belongs to the field of PMSM drive system fault diagnosis, and relates to an online diagnosis method for an open circuit fault of an inverter of a PMSM drive system, in particular to an online diagnosis method for an open circuit fault of an inverter of a PMSM drive system based on an observer and machine learning. Background technique [0002] In the field of modern industrial production and national defense industry, permanent magnet synchronous motors have been widely used due to their advantages of fast response, high power density and high efficiency. As its application becomes more and more extensive, higher requirements are put forward for the reliability of the permanent magnet synchronous motor drive system in practical applications. In the permanent magnet synchronous motor drive system, the inverter includes power electronic devices and its drive circuit. It is the link that combines digital control and power output most closel...

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Application Information

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IPC IPC(8): G01R31/54G01R31/56
Inventor 骆光照张泽良陶雪成陈寿洛
Owner NORTHWESTERN POLYTECHNICAL UNIV
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