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WKNN-LSSVM-based analog circuit fault diagnosis method

A technology for simulating circuit faults and diagnostic methods, applied in CAD circuit design, measuring electricity, measuring electrical variables, etc.

Inactive Publication Date: 2016-05-11
BOHAI UNIV
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  • Claims
  • Application Information

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Problems solved by technology

[0007] In summary, the existing analog circuit fault diagnosis methods still need to be improved

Method used

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  • WKNN-LSSVM-based analog circuit fault diagnosis method
  • WKNN-LSSVM-based analog circuit fault diagnosis method
  • WKNN-LSSVM-based analog circuit fault diagnosis method

Examples

Experimental program
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Embodiment Construction

[0042] Such as figure 1 As shown, the analog circuit fault diagnosis method based on WKNN-LSSVM is specifically:

[0043] The first step is to use the circuit simulation software Multisim12.0 to construct the analog circuit to be diagnosed, and test the performance index of the circuit online, that is, the normal and fault characteristics of the circuit, including the waveform of the circuit under normal and fault states, and the voltage value of some nodes of the circuit normal and fault data.

[0044] In this embodiment, the bandpass filter circuit is selected as the experimental object, see figure 2 , the band-pass filter circuit constructed in this example is composed of a low-pass filter circuit and a high-pass filter circuit in series. Except for formula conversion according to the characteristics of the filter circuit, the values ​​of other components are initially randomly selected. Secondly, this example is based on the fault diagnosis of the analog circuit based ...

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Abstract

The invention relates to a WKNN-LSSVM-based analog circuit fault diagnosis method which is fast in running speed and high in diagnosis precision. The method is characterized by including the steps of: utilizing circuit simulation software to build an analog circuit to be diagnosed, selecting normal and fault data of part of node voltage values of the circuit as test data, obtaining mathematical model of an improved LSSVM classifier, solving a Lagranigian multiplier alpha<*> and a weight vector omega <*>of the improved LSSVM classifier, using the weight vector omega <*> as a feature weight in an improved KNN distance formula, finding k training samples x of a known type which are the closest to a test sample x<t> of an unknown type, and then making a judgment of a normal type or fault type on the test sample x<t> according to a classification function. The adaptation to the complexity and diversity of the analog circuit and the nonlinearity and fault tolerance of fault data can be improved, and the reliability of a diagnosis result is guaranteed.

Description

technical field [0001] The invention relates to an analog circuit fault diagnosis method, in particular to an analog circuit fault diagnosis method based on WKNN-LSSVM. Background technique [0002] With the rapid development of electronic technology, the wide applicability, complexity and density of analog circuits are increasing, and the reliability requirements for their operation are also increasing. In military, aerospace and other fields, it is particularly important to evaluate whether analog circuits can achieve real-time performance. However, due to the diversity of fault phenomena, the tolerance of its own component parameters and the extensive nonlinearity of analog circuits, the development of existing evaluation technologies is slow. At present, the development of intelligent technologies such as neural networks, fuzzy logic, and genetic algorithms has provided an effective space for fault diagnosis of analog circuits. Among them, neural networks and support ve...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/3163G06F17/50
CPCG01R31/3163G06F30/36G06F30/367
Inventor 张志强张爱华霍星陈晨
Owner BOHAI UNIV
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