Diagnose Fault Of Analog Circuits Based On Genetic Algorithms

At present, fault diagnosis of analog circuits has gotten many great achievements. A lot of theoriesand methodologies have been developed through the consistent development. Combined with varies ofnew technologies and methods, fault diagnosis of analog circuits has become a cross-discipline.However, the fault diagnosis of analog circuits still has many limitations in practice due to thecomplexities and varieties in faults.Fault diagnosis of analog circuits based on genetic algorithm and SLPS has been researched in thispaper. To capture sample data is the basic for fault diagnosis of analog circuits. In this paper, theauto-capture technology of fault sample based on SLPS has been turned into reality, which increasinglyimproves the acquisition speed of the fault samples. There are two aspects of the application oftechnology. First, the test sample acquisition. The other, when genetic algorithm is used in faultdiagnosis of analog circuits, the acquisition of real-time search samples which are compared with testsamples is needed in the fitness function. Finally, examples are given in the paper. The method isconfirmed the practicality of hard fault diagnosis under the conditions without tolerance.In order to improve the speed of fault diagnosis, the application in soft fault diagnosis of analogcircuits based on sensitivity analysis combined with the genetic algorithm is presented in this paper.We have discussed the sensitivity analysis of analog circuits. Estimate the offset of the componentparameters to diagnose the fault of the analog circuits. We convert the diagnosis equation, which isconstituted by the incremental test node voltage and the component parameters variation, into thelinear programming problem about finding the smallest independent variable based on the hardconstraints of the fault diagnosis equation. And the linear programming problem with constraints isconverted to the extreme solution without constraints by the penalty function. The genetic algorithm isused to solve the optimal solution. Then, the influence of the control parameters of genetic algorithmis discussed with examples. A new Self-adaptive Genetic Algorithms was proposed and theexperiments show that the method has a good efficiency on the soft fault diagnosis of tolerance analogcircuits and has a higher speed.