Monitoring parameter selection method based on failure characteristic analysis

A technology of parameter selection and characteristic analysis, applied in the direction of electrical testing/monitoring, etc., can solve problems such as inapplicability to engineering practice, difficulty in acquiring system knowledge, and failure to consider the impact of testing resources.

Inactive Publication Date: 2012-09-12
NAT UNIV OF DEFENSE TECH
View PDF0 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The method based on the system model requires more detailed system knowledge, and it is difficult to obtain more detailed system knowledge in the equipment design stage
The calculation of RPN in the mechanism method only considers the occurrence probability and severity of the fault, but does not consider the propagation of the fault; when determining the monitoring parameters, there is no comprehensive analysis of th

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Monitoring parameter selection method based on failure characteristic analysis
  • Monitoring parameter selection method based on failure characteristic analysis
  • Monitoring parameter selection method based on failure characteristic analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] figure 1 It is a general flowchart of the present invention, and the steps are as follows:

[0037] Step 1, analyze the failure mode set F of the system to be analyzed aly .

[0038] Step 2, for F aly Execute extended FMMEA.

[0039] The third step is to determine the system monitoring parameter set according to the extended FMMEA results.

[0040] figure 2 yes figure 1 In step 1, determine the failure mode set F to be analyzed aly The flow chart, the steps are as follows:

[0041] 1.1 Analyze all possible failure mode sets F according to the system task profile and function all ;

[0042] 1.2 Select a fault f i , to determine whether it is a critical failure, if so, directly store it in F aly ; Otherwise, go to step 1.3;

[0043] 1.3 Judgment f i Is it a high failure rate failure? If so, directly store it in F aly ; Otherwise, go to step 1.4;

[0044] 1.4 Judgment f i Whether it is a fault with high propagation intensity, if so, directly store it in F ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention relates to a monitoring parameter selection method based on failure characteristic analysis. The method mainly includes the following steps: (1) determining a to-be-analyzed failure mode set according to system failure attributes (severity, failure rate, transmission intensity); (2) performing expanded failure modes, mechanisms and effects analysis (FMMEA) according to the to-be-analyzed failure mode set; and (3) determining a system monitoring parameter set according to the result of the extended FMMEA. System failure propagation characteristics and failure evolution characteristics are considered in the method based on the existing monitoring parameter determination method, thereby enabling finally obtained monitoring parameters to be more practicable in engineering.

Description

technical field [0001] The invention relates to a monitoring parameter selection method in the field of testability engineering oriented to prediction and health management, in particular to a monitoring parameter selection method considering fault propagation characteristics and fault evolution characteristics. Background technique [0002] Prognostics and Health Management (PHM) uses as few sensors as possible to collect various data information of the system, with the help of various intelligent reasoning algorithms (such as physical models, neural networks, data fusion, fuzzy logic, expert systems, etc.) Diagnose, predict failures, assess system health, and trigger optimal repair decisions taking into account various available resources and constraints. PHM is of great significance for improving system safety, reliability, maintainability and affordability, reducing life cycle costs, and realizing autonomous and predictive maintenance. Obviously, information perception ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G05B23/02
Inventor 邱静刘冠军吕克洪杨鹏杨述明陈希祥徐玉国张勇谭晓栋邓冠前王超王刚赵晨旭沈亲沐
Owner NAT UNIV OF DEFENSE TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap