The Application of the Improved Genetic Algorithm in the Aeroengine Fault Diagnosis

Abstract

A improved genetic algorithm is proposed based on a new fitness function in allusion to the problem that the traditional genetic algorithm is not fully consider the knowledge of the problem itself.The improved genetic algorithm is used to analyze the fault feature , to extract the fault and remove redundant characteristic parameters for the fault classification and calculation.The diagnosis example shows that the method has faster convergence speed and can be effective for fault identification.

An early fault diagnosis method based on the optimization of a variational modal decomposition and convolutional neural network for aeronautical hydraulic pipe clamps

“…It is widely used in combinatorial optimization, machine learning, and other fields. Nevertheless, the high computation complexity in solving nonlinear [25,26], for this defect genetic algorithm, this paper on the crossover and mutation operators of the genetic algorithm to improve the genetic algorithm, according to the rules of neighbor selection of N/2 high fitness individuals, using the improved genetic algorithm to optimize variational modal decomposition of modal number k value and penalty factor α values. Its specific implementation flow chart is shown in the figure 1.…”