Improved particle swarm optimization diagnosis method and system for simulating nonlinear DC circuits

Abstract

The present invention relates to the technical field of fault diagnosis of analog circuits, and provides an improved particle swarm optimization diagnosis method and system for simulating non-linear direct current circuits, so as to solve the problem of unknown fault states and multiple fault states of analog circuits by current fault diagnosis methods based on pattern classification Insufficient diagnostic ability of the problem, the method includes: establish a fault diagnosis equation; calculate the fitness value of each particle; calculate the uniform inertia weight of all particles; calculate the change of fitness value; determine the final inertia weight of each particle in the current iteration value; update the velocity and position of each particle of the particle swarm; repeat the above steps until the method converges. Compared with the standard PSO algorithm, the technical solution proposed by the invention has higher fault diagnosis coverage and faster 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...

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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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