关键词: 液体推进剂火箭发动机;故障诊断;故障分析;演化策略;计算数学

Abstract: A clustering algorithm based on Evolution Strategies was proposed to make analysis on high dimensional data of liquid rocket engine propulsion system In order to prevent the solution population from premature convergence, the dynamic fitness adaptation technique and all sharing function were introduced An adaptive regulation scheme for evolution control parameters was specially presented for clustering analysis of high dimensional data A local clustering deadlock can also be overcome by the deadlock check and cluster recombination & collapse strategies This algorithm was used in the optimal clustering analysis for the 560 data samples of 14 sorts of common faults, each of 68 dimensions, which were simulated for a liquid rocket engine In addition, comparison with fuzzy Kohonen clustering networks (FKCN) has also been made,based on IRIS data The simulation results show that the evolution strategies based on clustering algorithm is superior to other non evolutionary clustering algorithms, particularly when the data is of high dimensions

Key words: Liquid propellant rocket engine;Fault diagnosis;Fault analysis;Evolution strategies;Computational mathematics