Method for predicting faults of power electronic circuit based on FRM-RVM (fuzzy rough membership-relevant vector machine)

Abstract

The invention discloses a method for predicting faults of a power electronic circuit based on an FRM-RVM (fuzzy rough membership-relevant vector machine), and the method comprises the following steps: monitoring voltage and current signals, and carrying out wavelet threshold denoising on the signals so as to form multidimensional circuit parameter vectors; carrying out dimensionality reduction on the multidimensional circuit parameter vectors so as to obtain multidimensional fault feature vectors; obtaining a fault feature vector sample set within a health tolerance range of the circuit; obtaining a fault feature vector of the circuit in the process of real-time operation at a periodic interval; computing the health degree of the fault feature vector to the fault feature vector sample set at each time point so as to form a health degree-time sequence of the circuit; giving out the threshold value of the health degree of the circuit; carrying out prediction on the health degree-time sequence of the circuit by using an RVM (Relevance Vector Machine) algorithm so as to obtain the health degree of the circuit in some future time, comparing the obtained health degree with the threshold value of the health degree, and determining the health situation of the circuit in some future time, thereby realizing the fault prediction of the circuit. By using the prediction method disclosed by the invention, the real-time state monitoring and health-status estimation on the power electronic circuit can be realized, thereby realizing the prediction on the future state of the circuit, and then predicting the time of fault occurrence in advance.

Description

technical field [0001] The invention relates to a power electronic circuit fault prediction method, in particular to a power electronic circuit fault prediction method based on FRM-RVM. Background technique [0002] With the increasing complexity of systems in the fields of aviation, aerospace, coal mines, and chemicals, based on considerations of reliability, safety, and economy of complex systems, failure prediction and health management (Prognostics and Health Management, PHM) technology with failure prediction technology as the core gain more and more attention. Modern electronic equipment has penetrated into various fields such as national defense and military, industry, transportation, IT, agriculture, communication, commerce, pharmaceutical manufacturing, and household appliances. The losses caused by electronic equipment failures have also greatly increased. Therefore, the power supply for electronic equipment The role of the system is more important. The power ele...

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Problems solved by technology

[0007] However, power electronic circuits contain different circuit components, and it is impossible to monitor each component at the same time. Due to the different lifespan and failure mechanism of different components, the performance degradation and interactive coupling of each component in the circuit, it is difficult to monitor the components composed of them. circuits or devices to make accurate predictions

At present, the fault prediction of power electronic circuits is mostly the prediction of key components in the circuit, and the selected fault characteristic parameters are mostly the parameters of components, but there are few studies on the fault prediction of the whole circuit

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