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飞机发动机是一种复杂的旋转机械,故障种类多而且难以辨别。为了保证飞行安全,对飞机发动机的故障进行正确、快速地检测,文中应用仿生小波变换对某型涡轮风扇发动机在飞行中空中停车的振动信号作了分析。实验结果表明,对在频谱图上难以找到其相应的明显频率成分的准周期故障信号,利用仿生小波变换(BWT)的自适应调节功能,使得故障信号的细节成分更加地突出,对比该频率和故障情况下计算出的特征频率,可以找出故障的原因。
Aircraft engine is a complex rotating machinery, the type of fault and more difficult to distinguish. In order to ensure the safety of the flight, the failure of the aircraft engine is detected correctly and quickly. The paper analyzes the vibration signal of a certain type of turbofan engine parked in the air during flight by using the bionic wavelet transform. The experimental results show that the details of the fault signal are more prominent by using the adaptive adjustment function of BWT to the quasi-periodic fault signal which is hard to find its corresponding obvious frequency component on the spectrum chart. Compared with the frequency and The characteristic frequency calculated under the fault condition can find the cause of the fault.