Improved particle swarm optimization diagnosis method and system of analog non-linear direct current circuit

A technology for improving particle swarm and DC circuits, which can be used in analog circuit testing, electronic circuit testing, electrical digital data processing, etc., and can solve problems such as insufficient diagnostic capabilities in multiple fault states

Active Publication Date: 2015-11-25
SICHUAN AEROSPACE SYST ENG INST
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Problems solved by technology

[0005] The purpose of the present invention is to provide an improved particle swarm optimization diagnosis method and system for simulating nonlinear DC circuits, so as to solve the problem that the current fault diagnosis method based on pattern classification is insufficient in diagnosing the unknown fault state and multiple fault states of the analog circuit. question

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  • Improved particle swarm optimization diagnosis method and system of analog non-linear direct current circuit
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  • Improved particle swarm optimization diagnosis method and system of analog non-linear direct current circuit

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Embodiment 1

[0133] Embodiment 1 provides an improved particle swarm optimization diagnosis method for simulating nonlinear DC circuits, such as figure 1 As shown, the method includes step to step, and each step will be described in detail below.

[0134] Step S1: Carry out signal sampling on the CUT, and establish a fault diagnosis equation.

[0135] Specifically, step S1 performs voltage sampling on accessible test nodes of the circuit to be tested under the excitation of a DC voltage excitation source, establishes a fault diagnosis equation, and uses the fault diagnosis equation as a fitness function. The types of three different diagnostic equations can refer to the detailed description of the present invention in the summary of the invention. It should be noted that when the number of faulty components of the CUT is known, the DE2 diagnostic equation is used; if the number of faulty components is unknown, the DE3 diagnostic equation is used. In this embodiment, the DE1 diagnostic equ...

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Abstract

The invention, which relates to the technical field of the analog circuit fault diagnosis, provides an improved particle swarm optimization diagnosis method and system of an analog non-linear direct current circuit. With the method and system, a problem that the existing pattern-classification-based fault diagnosis method does not has the enough diagnosis capability for the unknown fault state and a multi-fault state of the analog circuit can be solved. The method comprises: establishing a fault diagnosis equation; calculating fitness values of all particles; calculating a unified inertia weight of all particles; calculating changes of the fitness values; determining a final value of the inertia weight of all particles at current iteration; updating speeds and positions of all particles in the particle swarm; and repeating all above-mentioned steps until method convergence is realized. Compared with the standard PSO algorithm, the method and system based on the technical scheme have the high fault diagnosis coverage rate and the fast fault diagnosis speed.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis of analog circuits, in particular to an improved particle swarm optimization diagnosis method and system for simulating nonlinear DC circuits. Background technique [0002] Analog circuit fault diagnosis refers to solving the physical position and parameters of fault components when the topological structure of the circuit network, the input excitation signal (the excitation signal can also be selected) and the response to the fault are known. In the analog circuit, faults can be divided into Soft faults and hard faults, in which soft faults are caused by the slow change of component parameters over time and exceed tolerances, and hard faults are caused by sudden large deviations of component parameters (such as open circuit and short circuit). [0003] Most of the existing soft fault diagnosis methods for analog circuits are based on pattern classification theory. Such diagnostic methods...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/316G06F19/12
Inventor 敖永才周保琢杨筱倩王诗利
Owner SICHUAN AEROSPACE SYST ENG INST
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