Measurement parameters selection method for gas path fault diagnosis of two-shaft split flow turbofan engine

Aiming at measurement parameters optimal selection for gas path fault diagnosis in ground test bed, a four-step optimal method was presented. The four-step optimal method includes measurement parameters sensitivity analysis, component performance parameters correlation analysis, influence coefficient matrix condition number analysis and genetic algorithm validation. According to the first step, total air mass flow was picked out. In the second step, total temperature at fan exit and total temperature at compressor exit were picked out. In the third step, twelve measurement parameters combinations beneficial to fault diagnosis were picked out. In the final step, the best measurement parameters combination was obtained. Based on the genetic algorithm, the simulated diagnostic results show that, with these twelve measurement parameters combinations, all the fitness values for each single fault diagnosis are more than 0.85, which approximate the optimal fitness value 1. As to the most promising measurement parameter combination, all the fitness values are greater than 0.9 by genetic algorithm validation, which demonstrate the validity of this four-step optimal method.