直升机声疲劳源的诊断技术研究

首次开展直升机声疲劳源的诊断工作,基于小波变换原理,建立了直升机声疲劳源的诊断方法与技术,它包含小波分解与重构阶数的确定、噪声信号分解、分解信号重构以及分离信号的1/3倍频程计算等方面内容.该方法具有低频信号分辨率高和易于重构等特征,特别适合直升机的主、尾桨噪声信号进行分离.通过对模拟的主、尾桨信号进行分离,并将分离后的信号与原始信号相比,发现误差不超过2.3%,因此,验证了该法的有效性.另外,应用该法还对小松鼠直升机所记录的噪声信号进行主、尾桨噪声分离,所得结果表明:建立的直升机声疲劳源的诊断技术,能够处理直升机非平稳噪声信号,可以完成直升机主、尾桨噪声的分离.

Diagnose of Noise Fatigue Sources of a Helicopter

According to the wavelet transformation theory, a diagnose method for helicopters is established, including the order number of the wavelet decomposition and reconstruction, the noise signal decomposition, the separate signal reconstruction and 1/3 times frequency calculation. Since this method is with the high distinguishability for the low frequency signal and easy to reconstruct, it is fit for the noise signal separation of helicopter. By this method, the simulating noise signals are separated, and the separated signals are compared with the original signals, then it is found that the error between the separated signal and the original signal is lower than 2.3 percent. Moreover, on the basis of this method, the noise signals of the main rotor and tail rotor recorded from an AS350 helicopter are separated. It is shown that this diagnose method can be used to treat the non stationary noise signals and separate the noise signals of the main rotor and tail rotor of the helicopter.