Linear analog circuit fault diagnosis method

Abstract

The invention discloses a linear analog circuit fault diagnosis method. The linear analog circuit fault diagnosis method comprises the steps of firstly simulating an analog circuit to obtain fault feature column vectors corresponding to fault source elements, dividing the corresponding fault source elements into an ambiguity set when the fault feature column vectors are identical within an error range, selecting a representative fault source element from each ambiguity set, respectively performing Q-time simulation on each representative fault source element to obtain Q fault feature column vectors, using each representative fault source element as a category, obtaining classification model data according to the corresponding fault feature column vectors, obtaining fault column vectors according to normally-operating output voltage phasor quantity vectors and fault output voltage phasor quantity vectors when the analog circuit breaks down, and classifying the fault column vectors according to the classification model data and corresponding classification methods to obtain fault diagnosis results. The linear analog circuit fault diagnosis method is simple and easy to operate and is based on multiple-time simulation, and the influence of tolerance on fault diagnosis can be effectively reduced.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of analog circuits, and more specifically relates to a method for fault diagnosis of linear analog circuits. Background technique [0002] In the current field of analog circuit fault diagnosis technology, there are two key and difficult problems to be solved. [0003] (1) Analog component parameter continuity problem [0004] The solution to this problem is to uniformly model the continuous variation of component parameters (from zero to infinity). However, it is obvious that the commonly used open-circuit and short-circuit fault models, as well as fixed-parameter fault types (such as parameter drift up and down by 50%) and fault segment models (such as parameter changes from ±5% to ±10%) are not up to the task. The system transfer function model can theoretically diagnose soft faults in the network, but because the system transfer function needs to be written for fault diagnosis, there...

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Problems solved by technology

However, it is obvious that the commonly used open-circuit and short-circuit fault models, as well as fixed-parameter fault types (such as parameters drifting up and down by 50%) and fault segment models (such as parameters changing from ±5% to ±10%) are not up to the task.

The system transfer function model can theoretically diagnose soft faults in the network, but because the system transfer function needs to be written for fault diagnosis, there are disadvantages such as complex circuits are difficult to write transfer functions, equations are not easy to solve, and component tolerances may cover fault signal

[0005] (2) The influence of tolerance on fault diagnosis

The tolerance problem will also cause the fault output to change around the standard fault output, which will affect the accuracy of fault diagnosis

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