基于遗传算法的柴油机瞬时转速特征优化方法OA

Studying fault diagnosis related to diesel engine combustion through online monitoring of instantaneous speed signals is one of the most practical and valuable technologies in diesel engine fault diagnosis in recent years.However,the complex structure of diesel engines leads to complex fluctuations and changes in instantaneous speed,making information identification difficult,especially in the extraction of instantaneous speed feature information for early faults in diesel engines.The weak signal of instantaneous speed in early faults of diesel engines is focused on,making it difficult to extract fault features.However,traditional fault feature optimization methods have problems such as low accuracy and low efficiency when processing instantaneous speed data of diesel engines.Six dimensionless feature parameters are extracted and optimized using a genetic algorithm,offering optimal parameters for diagnosing faults in diesel engine instantaneous speed signals.Through conducting fault simulation experiments,the effectiveness of this genetic algorithm in optimizing these specific fault features is confirmed.For power imbalance faults exceeding 15% amplitude,accurate diagnosis can be achieved using instantaneous speed signals.