Smart city intelligent rail vehicle fault gene prediction method and system

A vehicle fault and gene prediction technology, which is applied in prediction, instrument, character and pattern recognition, etc., can solve the problem that the fault detection method cannot be adjusted, and achieve the effect of improving accuracy

Pending Publication Date: 2021-04-30
CENT SOUTH UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Benefits of technology

This patented describes methods that use advanced testing techniques such as molecular biology or machine vision technologies to accurately diagnose failures in railway cars without relying solely upon previous knowledge about them. These advancements make it easier for companies to maintain their fleet's assets by identifying any future issues before they become too late.

Problems solved by technology

Technological Problem: Current systems are limited by their ability to detect failures accurately due to factors like road conditions or equipment failure modes such as overload or insufficient power supply. Additionally, current approaches require manual intervention from human operators who may take longer than necessary time before identifying any issues with an aircraft system.

Method used

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  • Smart city intelligent rail vehicle fault gene prediction method and system
  • Smart city intelligent rail vehicle fault gene prediction method and system
  • Smart city intelligent rail vehicle fault gene prediction method and system

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Embodiment Construction

[0050] Such as figure 1 , the specific implementation process of the embodiment of the present invention is as follows:

[0051] Step 1: Acquisition of historical failure data of new smart rail train components

[0052] The invention uses high-frequency and low-frequency sensors and electric sensors to collect historical vibration information data of various types of urban smart rail vehicle components, and technology changes greatly reduce the cost of popularization and application of sensors. In addition, the wireless sensor network (WSN) plays an important role. Using this method, the vibration signals of multiple trains can be uploaded and integrated to the data integration platform in time. The information collection modules involved in step 1 include the vibration amplitude collection module of vehicle components, A vibration frequency acquisition module and a vibration period acquisition module. The collected information includes vibration amplitude A, frequency f, pe...

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Abstract

The invention discloses a smart city intelligent rail vehicle fault gene prediction method and system, and the method comprises the steps: collecting the vibration data Xh (0) = [e1, e2, e3,..., en] belongs to R of a train part, and enabling e1, e2,..., en to represent the vibration information of each sampling point on a train; encoding the vibration data into a DNA sequence, extracting features of the DNA sequence, and permuting and combining the features to form a predictable DNA sequence, namely a candidate vehicle part fault gene; and training an ESNs deep echo state network by using the candidate vehicle part fault gene to obtain a prediction model. The method and system can accurately predict the vehicle fault.

Description

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Claims

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Application Information

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Owner CENT SOUTH UNIV
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