Method for predicting service life of key system of rail transit vehicles

A technology for rail transit vehicles and key systems, which is applied in the field of life prediction for key systems of rail transit vehicles. It can solve the problems of not taking into account the impact of maintenance on life, a large number of tests and data, etc., and achieve simple and universal calculation and life prediction Accurate, the effect of increasing accuracy

Inactive Publication Date: 2016-02-10
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

In the sense of probability and statistics, the life prediction results based on probability and statistics can better reflect the general law and overall characteristics of mechanical product life, but it requires a lot of experiments and data accumulation
Traditional life prediction methods based on probability and statistics only calculate the change of life over time without taking into account the impact of maintenance on life

Method used

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  • Method for predicting service life of key system of rail transit vehicles
  • Method for predicting service life of key system of rail transit vehicles
  • Method for predicting service life of key system of rail transit vehicles

Examples

Experimental program
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Embodiment 1

[0087] This paper selects the maintenance data of Line 2 of a subway company, assuming that the door system is repaired as new after the annual inspection or erection repair. Through the analysis of the maintenance data of Line 2 from 2011 to 2012, it can be seen that the failure of the main line and the number of maintenance of the vehicle are the main factors affecting the life of the vehicle in the first life cycle of the vehicle. , so the number of main line failures, the number of vehicle maintenance and the number of door failures caused by passengers are selected as the covariates of the door system, as shown in Table 1.

[0088] Table 1 Overhaul history of door system

[0089]

[0090] Standardize the original covariate data in Table 1 to obtain the correlation coefficient matrix

[0091] R = 1.0000 0.6822 0.1636 ...

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Abstract

The invention discloses a method for predicting the service life of a key system of rail transit vehicles. The method comprises the following steps of firstly, determining the key system of urban rail vehicles, and bringing in a proportional hazard model to carry out service life prediction on the key system; secondly, screening historical overhauling data of the key system to obtain concomitant variable factors, and processing concomitant variables by applying a principal component analysis method so as to obtain a concomitant variable matrix; thirdly, solving a parameter estimation value in the proportional hazard model by adopting a maximum likelihood estimation method and a Newton iteration method; finally, calculating the predicted service life of the key system of the rail transit vehicles by utilizing the obtained proportional hazard model. According to the method disclosed by the invention, the influence of the concomitant variable factors on the service life of the key system of the rail transit vehicles is considered, and the defect that the service life prediction is inaccurate as only system failure is considered in traditional service life prediction is overcome.

Description

technical field [0001] The invention belongs to the technical field of traffic safety engineering, in particular to a life prediction method for key systems of rail transit vehicles. Background technique [0002] Urban rail vehicle is a complex electromechanical system. Due to its complex operating conditions and harsh environment, it will gradually age during long-term operation, and its remaining life will gradually decrease, which will easily lead to serious accidents, resulting in huge property losses and casualties; and If maintenance and replacement are carried out blindly, it will bring huge waste. Therefore, it is of great significance to correctly predict the remaining life of urban rail vehicles to ensure the safe operation of equipment and improve economic benefits. [0003] At present, the methods of system life prediction include the life prediction method based on mechanics and the life prediction method based on probability statistics, such as the life predic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 任金宝邢宗义
Owner NANJING UNIV OF SCI & TECH
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