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Product multidimensional correlation-oriented degradation failure modeling method

A technology of degradation failure and modeling method, which is applied in special data processing applications, instruments, electrical digital data processing, etc.

Inactive Publication Date: 2015-12-02
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0006] The purpose of the present invention is in order to overcome the defect of existing reliability analysis method based on degradation, establishes the reliability analysis method of more flexible and more general multi-dimensional correlation degradation

Method used

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  • Product multidimensional correlation-oriented degradation failure modeling method
  • Product multidimensional correlation-oriented degradation failure modeling method
  • Product multidimensional correlation-oriented degradation failure modeling method

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Embodiment Construction

[0033] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following describes the present invention in further detail with reference to the accompanying drawings and taking a 3-dimensional correlation degradation process as an example. The specific embodiments described here are only used to explain the present invention, but not to limit the present invention.

[0034] Such as figure 1 As shown, the steps include:

[0035] Step 1: Collect and process the degradation data of each feature quantity.

[0036] The present invention takes the fatigue crack degradation data collected by the gear fatigue test as an example. All gear samples were tested at the same time point, and during the test, crack data was collected for all gear samples every 0.01 million revolutions, and the unit of crack size was inches.

[0037] In order to verify the degradation model based on D-VineCopula mentioned above, we selected the fatigue crack degrada...

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Abstract

The present invention discloses a product multidimensional correlation-oriented degradation failure modeling method. The method specifically comprises: determining reliability characteristic quantities of a product; collecting and processing degradation data of each characteristic quantity; establishing a degradation model of each characteristic quantity; estimating a parameter in the degradation model of each characteristic quantity; establishing a multidimensional correlation degradation model by using D-Vine Copula; and determining types and parameter values of all bivariate Copula functions. According to the method provided by the present invention, a multidimensional correlation variable joint density function and an edge density function thereof are connected by a plurality of bivariate Copula functions by using D-Vine Copula, so as to effectively process a multidimensional degradation process with complex correlation, and achieve better flexibility and generalization ability.

Description

Technical field [0001] The invention belongs to the technical field of reliability analysis of electromechanical products, and in particular is a reliability analysis method for products with multi-dimensional correlation degradation and failure. Background technique [0002] Reliability technology has become an important way to improve product efficiency and reduce product life cycle costs, and it is the focus of enterprise product competition. For some high-reliability and long-life key components in high-tech weaponry, nuclear power plants, aerospace and other fields, the reliability issues are particularly important. Due to the long failure time of high-tech complex products and it is difficult to obtain a large amount of failure time data, traditional reliability analysis methods based on failure time can no longer satisfy the product reliability analysis in this case. The reliability analysis method based on degradation was put forward under this background and received wi...

Claims

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Application Information

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IPC IPC(8): G06F17/50
Inventor 张志鹏刘宇游志毅姜涛
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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