Algorithms on Analysis of Fault Diagnosis of Electric Circuit

For fault diagnosis analysis on a series circuit that consists of a resistance inductance and capacitance needs an algorithm to achieve the goal. Resistance, inductance and capacitance in the series circuit fault diagnosis analysis algorithm is produced using the MULTISIM resistor, inductor and capacitor series circuit containing the simulation of thermal noise signal, and then using MATLAB construct a resistor, inductor and capacitor series circuit mathematical model to estimate the resistance, inductance and capacitance of the series circuit of electronic components parameters of resistance, inductance and capacitance value. Genetic algorithm is used to find the optimal solution of the objective function. The optimal solution is the parameter value of electronic components. The objective function is the sum of the squares of the difference between the simulation signal and the output signal of the mathematical model of the circuit. The error sum of squares made in this experiment is less than 1%. Fault refers to that the parameter values of electronic components are beyond the normal range. The k-nearest neighbor classification algorithm is used to classify the parameter values of electronic components into two states: within the normal range and outside the normal range. Therefore, circuit faults can be diagnosed.