Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A fault diagnosis method for electronic products based on discretized multivalued extended d-matrix

An electronic product and fault diagnosis technology, which is applied to the generation of response errors, electrical digital data processing, instruments, etc., can solve the problem that important information cannot be fully utilized, and achieve the effect of improving application feasibility and isolation ability

Active Publication Date: 2021-01-15
BEIHANG UNIV
View PDF11 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that the current electronic product fault diagnosis simply uses 0 / 1 binary value to represent the test data, but the important information in the test data cannot be fully utilized, the present invention proposes a kind of electronic product fault diagnosis based on the discretized multi-valued extended D matrix. Diagnosis method, the present invention uses K-means clustering to discretize the data of a single test point, constructs a multi-valued D matrix, and realizes fault diagnosis by calculating the Manhattan distance between the test vector and the multi-valued D matrix

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
  • A fault diagnosis method for electronic products based on discretized multivalued extended d-matrix
  • A fault diagnosis method for electronic products based on discretized multivalued extended d-matrix
  • A fault diagnosis method for electronic products based on discretized multivalued extended d-matrix

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0022] The implementation process of the fault diagnosis method based on the discretization multi-valued extended D matrix provided by the present invention is as follows: figure 1 As shown, the following combination as figure 2 A certain power board shown is used as an object to illustrate the implementation steps of the fault diagnosis method of the present invention.

[0023] Such as figure 2 As shown, the power supply board in the embodiment of the present invention can output 7 kinds of voltages including 18V, 12V, 5V, 3.3V, 2.5V, 1.8V and 0.9V. The power supply board is provided with 28V voltage by an external power supply. The 28V voltage is converted to 18V voltage output through the LM7818 chip, and the 28V voltage is converted to 12V voltage output through the LM2596 at the same time. Converted to 5V to supply power for...

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 invention provides an electronic product fault diagnosis method based on a discretized multi-value extended D matrix, and belongs to the technical field of electronic product fault diagnosis and testing. Including: obtaining the sample data of the electronic product to be diagnosed in normal state and each fault state; clustering the sample data obtained at each test point, obtaining the number of clusters and cluster centers under each test point, and establishing discretization At the same time, construct a discretized test vector; calculate the Manhattan distance with each row in the discretized multi-valued D matrix, find the row of the D matrix with the shortest Manhattan distance to the test vector, and the state corresponding to the row is The state of the electronic product diagnosed according to the discretized test vector. The invention uses K-means clustering to discretize the data of a single test point, constructs a multi-valued D matrix, and realizes fault diagnosis by calculating the Manhattan distance between the test vector and the multi-valued D matrix, thereby improving the application feasibility of the method.

Description

technical field [0001] The invention relates to an electronic product fault diagnosis method based on a discretized multi-value extended D matrix, and belongs to the technical field of electronic product fault diagnosis and testing. Background technique [0002] With the development of electronic product integration and functional diversification, the transmission relationship of fault signals is becoming more and more complicated, which increases the difficulty of product fault diagnosis. At present, in the fault diagnosis test of electronic products, the correlation matrix between the fault and the test is used, also known as the D matrix, and the signal transmission relationship between the fault and the test is represented by 0 / 1 value, 0 means no fault, 1 means there is a fault , the fault diagnosis method based on D matrix has the characteristics of simple calculation and high operation efficiency, and has been widely used in aviation, aerospace, shipbuilding, weaponry...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/07G06K9/62
CPCG06F11/079G06F18/23213G06F18/214
Inventor 石君友邓怡郭绪浩何庆杰
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products