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Analog circuit fault feature extraction method based on cloud correlation coefficient matrix

A technology for simulating circuit faults and correlation coefficients, which is applied in the feature extraction of analog circuit faults, cloud correlation coefficient matrix to realize the feature extraction of analog circuits, can solve the problems of low similarity and tolerance of circuit components, and achieve low similarity and difference Large, high-resolution effects

Active Publication Date: 2018-11-16
GUILIN UNIV OF ELECTRONIC TECH
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to address the deficiencies of the prior art, and provide a method for extracting features of analog circuit faults based on the cloud correlation coefficient matrix, which solves the problem of circuit element tolerance, and the feature extracted by it has a large difference between various faults , the similarity between the same kind of faults is low, improving the fault diagnosis rate

Method used

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  • Analog circuit fault feature extraction method based on cloud correlation coefficient matrix
  • Analog circuit fault feature extraction method based on cloud correlation coefficient matrix
  • Analog circuit fault feature extraction method based on cloud correlation coefficient matrix

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Embodiment 1

[0054] Such as image 3 As shown, the tested analog circuit is selected as a Sallen_Key band-pass filter with a center frequency of 25kHz. In order to explain the technical solution of the present invention in more detail, single and double fault situations of the circuit are considered. The parameter values ​​of each component are their nominal values, and the allowable errors in the components are: the resistance tolerance range is ±5%X n , capacitance tolerance is ±10% x n , X n is the nominal value of the component, and the test stimulus is a single-cycle pulse signal with an amplitude of 5V and a pulse width of 10μs. Through the analysis of the sensitivity of the circuit, it can be known that the resistance R2, the resistance R3, the capacitance C1 and the capacitance C2 have the most significant influence on the output response of the circuit. Therefore, they are regarded as faulty component groups.

[0055] Single Fault Condition: When any component in a circuit is ...

Embodiment 2

[0066] Such as Figure 7 As shown, in order to verify the validity and universality of the scheme of the present invention, a relatively complex quadratic high-pass filter with four operational amplifiers in the circuit is used as the circuit under test. According to the sensitivity analysis, resistance R1, resistance R2, resistance R3, resistance R4 and capacitance C1, capacitance C2 have the most significant response to the circuit output, so they are taken as the fault element group. 100 Monte-Carlo analyzes are performed on each fault state of the circuit time-domain voltage signal, and 1000 sampling points are acquired each time within the first 400us of the test response. Other settings and diagnosis are the same as the circuit under test in Embodiment 1. Table 3 is the single fault mode, Table 4 is the double fault mode, NF is the normal state category, "—" indicates that the parameter does not exist, and k in Table 3 is kΩ.

[0067] Table 3 Single fault mode of quadr...

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Abstract

The present invention discloses an analog circuit fault feature extraction method based on a cloud correlation coefficient matrix. The method comprises the steps of: solving cloud numerical features of a fault mode, a membership matrix of a feature vector, an extreme value of the integrated membership matrix and a cloud correlation coefficient and a cloud association degree according to a cloud model, extracting a high-frequency sequence with a large degree of association corresponding to the fault extraction vector and a low-frequency sequence with a small degree of association, and randomlyselecting cloud correlation coefficients with large difference of the degrees of association as the fault feature vectors of the circuit so as to complete fault feature extraction of the tested analogcircuit. The analog circuit fault feature extraction method employs the cloud model capable of processing the circuit tolerance and the fuzziness at the boundary of the elements to improve the resolution ratio of the fault modes when fault diagnosis is performed, is good in diagnosis performance, can accurately locate the fault elements and improves the diagnosis performance and the efficiency ofthe circuit.

Description

technical field [0001] The invention relates to the field of fault diagnosis of analog circuits, in particular to the technical field of fault feature extraction of analog circuits, in particular to a method for feature extraction of analog circuits realized by a cloud correlation coefficient matrix. Background technique [0002] With the rapid development of integrated circuits (Integrated Circuit, referred to as IC), the complexity and density of circuits are constantly increasing. Now digital, analog and mixed signal circuits are integrated into ICs on the same substrate to form SoC (System -on-a-Chip, system-on-a-chip, referred to as SoC) and NoC (Network On Chip, network on chip, referred to as NoC). Digital circuits such as memories and controllers belong to digital IP (Intellectual Property, intellectual property, referred to as IP) cores, because they have complete test standards such as IEEE 1149.1 standards and IEEE 1500 standards, as well as their discrete output ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/316
CPCG01R31/316
Inventor 谈恩民王存存
Owner GUILIN UNIV OF ELECTRONIC TECH
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