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Steering engine reliability simulation sampling method based on Markova chain Monte Carlo

A technology of Markov chain Monte Carlo and Markov chain, applied in special data processing applications, instruments, electrical digital data processing, etc.

Active Publication Date: 2011-04-27
陕西可维卓立科技有限公司
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Problems solved by technology

This method greatly improves the simulation efficiency and accuracy, and effectively solves the reliability simulation analysis problem of the mixed variable system where discrete variables and continuous variables coexist, so it has a wider application in the integrated design of reliability and performance

Method used

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  • Steering engine reliability simulation sampling method based on Markova chain Monte Carlo
  • Steering engine reliability simulation sampling method based on Markova chain Monte Carlo
  • Steering engine reliability simulation sampling method based on Markova chain Monte Carlo

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Embodiment Construction

[0075] A kind of steering gear reliability simulation sampling method based on Markov chain Monte Carlo of the present invention, this method is carried out according to following four stages successively; Its method flow chart is shown in figure 1 As shown, the specific implementation is described in detail as follows:

[0076] Phase 1: Markov Process Simulation

[0077] Markov process simulation mainly includes the following four steps:

[0078] ① Select the initial state X of the Markov chain 0 :

[0079] In the four-redundancy steering gear system, the initial state is the average value of each quantity in the table below.

[0080] Table 1 Random parameters of four-redundancy steering gear system reliability design

[0081] Moment of inertia of motor and pump

~N(1.6E-3, 2E-4)

Motor Armature Resistance

～N(0.5，0.06)

Motor armature inductance

~N(1E-2, 9E-4)

Motor damping coefficient

~N(3E-4, 2E-5)

Volumetric efficiency...

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Abstract

The invention discloses a steering engine reliability simulation sampling method based on Markova chain Monte Carlo, which comprises four stages: 1, Markova process simulation, namely selecting the initial state of a Markova chain, determining a random transition sampling probability density function, determining the next state of the Markova chain and constantly repeating to generate random sample points, of which the limit distribution is asymptotically optimal, of an importance sampling density function; 2, kernel density estimation, namely selecting a kernel density function, determining a window width parameter and a local bandwidth factor and generating a mixed importance sampling probability density function by using a self-adaptive width and kernel density estimation method according to Markova state points; 3, importance sampling, namely performing importance sampling according to the mixed importance sampling probability density function generated in the second stage; and 4,statistical calculation, performing failure probability estimation according to the important sample points generated in the third stage and calculating the failure probability of the system. The method effectively solves the problems of low simulation efficiency, low precision and mixed system.

Description

technical field [0001] The invention provides a steering gear reliability simulation sampling method based on Markov chain Monte Carlo, which belongs to an efficient and high-precision simulation method in the field of system reliability simulation analysis, and focuses on solving the problem of a hybrid system containing discrete variables , such as four redundant steering gear system, etc. Background technique [0002] The integrated design of system reliability and performance is a new technology to realize comprehensive analysis and design of reliability and performance by using methods such as fault and disturbance injection, system reliability simulation analysis and optimal design in the system design stage. The implementation of reliability and performance comprehensive analysis and design can achieve performance design at the design stage, while obtaining relevant reliability indicators, providing reliability analysis data for designers, and providing a way for earl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 王进玲曾声奎马纪明孙博冯强任羿郭健彬
Owner 陕西可维卓立科技有限公司
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