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Motor train unit axle residual life estimation method based on ResNet and GRU

A technology for EMUs and axles, applied in special data processing applications, geometric CAD, computer-aided design, etc., can solve problems such as high maintenance costs and failure rates, and inability to accurately predict the insufficient maintenance of bogie axles, etc., to achieve in-depth improvement The effect of feature extraction ability

Inactive Publication Date: 2020-12-11
CRRC CHANGCHUN RAILWAY VEHICLES CO LTD
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AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem that the remaining life of the bogie axle cannot be accurately estimated at the present stage, resulting in insufficient maintenance or excessive maintenance cost and high failure rate, the present invention proposes a method of preprocessing the axle vibration data through ResNet, and using the GRU to control the axle vibration. Extract features from the data, simulate the performance degradation trend of the axle, and realize the life prediction of the axle

Method used

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  • Motor train unit axle residual life estimation method based on ResNet and GRU
  • Motor train unit axle residual life estimation method based on ResNet and GRU
  • Motor train unit axle residual life estimation method based on ResNet and GRU

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Embodiment Construction

[0039] refer to figure 1 , a method for estimating the remaining life of an EMU axle based on ResNet and GRU is implemented as follows.

[0040] Perform FFT transformation on the bogie axle vibration signals collected under different working conditions, and obtain the amplitude signal data in the frequency domain as the training set;

[0041] The amplitude signal in the frequency domain is normalized by the BN algorithm and used as feature input, and the life degradation ratio of the axle is used as the output of the model for training. The formula is as follows:

[0042]

[0043] where x t ∈ R N Represents the N-dimensional feature input of the axle at time t; y t ∈[0,1] represents the life degradation rate of the axle at time t; V TRN Represents the vibration signal data of the axle under a certain working condition in the training set; R is the amplitude feature matrix in the frequency domain; T is the design life running time of the axle;

[0044] The VGG16 network...

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Abstract

The invention relates to a motor train unit axle residual life prediction method based on ResNet and GRU, and discloses a motor train unit axle residual life prediction method based on ResNet and GRU,and the method comprises the steps: preprocessing vibration data of a collected bogie axle of a high-speed motor train unit by ResNet, extracting features of the axle vibration data by GRU, simulating an axle performance degradation trend, and achieving life prediction of an axle. The change rule of the axle life trend is explored by utilizing the characteristic that a memory unit of a GRU network has long-term and short-term memory on time series data, and an axle life prediction model is established, so that the phenomenon of insufficient or excessive maintenance in planned and preventive maintenance due to incapability of accurately estimating the residual life of the bogie axle in the past is avoided, and the maintenance efficiency is improved. Maintenance cost and the failure rate are reduced.

Description

technical field [0001] The invention belongs to a method for estimating the life of parts and components of rail vehicles, in particular to a method for estimating the remaining life of an EMU axle based on ResNet and GRU. Background technique [0002] High-speed EMUs are an important part of high-speed railways, and the stable and reliable operation of their systems and components is the key to ensuring railway transportation. The bogie system is the core component of the EMU, and the health status of its sub-components seriously affects the driving safety of the EMU. Since the remaining life of each component of the bogie cannot be accurately estimated, the planning and preventive measures adopted by the EMU at this stage Insufficient or excessive maintenance exists in maintenance, resulting in problems such as high maintenance cost and failure rate. Contents of the invention [0003] In order to solve the problem that the remaining life of the bogie axle cannot be accu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/15G06F30/17G06F30/27G06F119/04
CPCG06F30/17G06F30/15G06F30/27G06F2119/04Y02T90/00
Inventor 邵俊捷张瑛王中尧逯骁
Owner CRRC CHANGCHUN RAILWAY VEHICLES CO LTD
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