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Construction method of igbt residual service life prediction model for converter device

A technology of life prediction model and variable flow device, which is applied in the direction of neural learning method, biological neural network model, neural architecture, etc., can solve the problems of poor generalization and doubts in the generalization ability of the model, and achieve strong generalization , Avoid major operational accidents, improve the effect of accuracy

Active Publication Date: 2022-04-26
CRRC YONGJI ELECTRIC CO LTD
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AI Technical Summary

Problems solved by technology

There are many human factors in the establishment of the existing prediction method model, and the generalization ability of the corresponding model is questionable. It can only be successfully fitted for a specific type of IGBT under specific use conditions, and the generalization is not strong.

Method used

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  • Construction method of igbt residual service life prediction model for converter device
  • Construction method of igbt residual service life prediction model for converter device
  • Construction method of igbt residual service life prediction model for converter device

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Experimental program
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Embodiment Construction

[0030] The construction method of the remaining service life prediction model of the IGBT of the converter device is realized by the following steps:

[0031] Step 1. Collect IGBT accelerated aging data

[0032] On the high and low temperature standard test bench, change the IGBT within the test temperature range, from the minimum temperature to the maximum temperature as a cycle (according to the test standard: minimum temperature T min= -40℃; maximum temperature T max =125℃), the period of each cycle is the same (the period of each cycle is 4 hours); after each cycle, a set of characteristic parameter data sets are collected: emitter-collector saturation voltage drop V ce(sat) , gate-emitter threshold voltage V GE（th） , collector current I CE（on） , diode conduction voltage drop V f , gate saturation current IG（sat） and thermal impedance Z th ; Multiple cycles until all the characteristic parameters in the characteristic parameter data set reach the degradation judgment ...

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Abstract

The invention relates to a method for constructing a forecasting model for the remaining service life of an IGBT of a converter device, in particular to a method for constructing a forecasting model for the remaining service life of an IGBT for a rail transit converter device based on a long-short-term memory network. Solve the difficult problem of using LSTM to construct the remaining service life prediction model of the IGBT of the converter device. The method is realized by the following steps: Step 1, collecting IGBT accelerated aging data; Step 2, data normalization processing; Step 3, constructing and training a long-short-term memory network; Step 4, verifying the prediction model. The present invention obtains a prediction model for the remaining service life of the IGBT of the converter device that achieves the required prediction error index by determining the characteristic parameters, constructing the LSTM deep network architecture, and specifying the network training parameters. The prediction model constructed by this method is based on the long-short-term memory network and is applied to the remaining service life prediction of the IGBT of the converter device, especially the traction converter of rail transit.

Description

technical field [0001] The invention relates to a method for constructing a forecasting model for the remaining service life of an IGBT of a converter device, in particular to a method for constructing a forecasting model for the remaining service life of an IGBT for a rail transit converter device based on a long-short-term memory network. Background technique [0002] Rail transit converters consist of many electrical components, but the core of rectifiers and inverters is power electronic devices, mainly insulated gate bipolar transistors (IGBTs). Since the IGBT came out in 1985, it has become the mainstream switching device for semiconductor converters. The reliability of the traction converter directly affects the reliable operation of rolling stock, and the failure of IGBT is an important factor affecting the reliability of the main converter. According to foreign statistics, in the faults of industrial converters, the IGBT fault rate accounts for more than 30%, and t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G06N3/04G06N3/08G06F119/02
CPCG06F30/27G06N3/08G06F2119/02G06N3/045
Inventor 王昭李骁猛刘谆侯涛吴晓威
Owner CRRC YONGJI ELECTRIC CO LTD
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