小波分析在声学法炉内空气动力场测量中的应用

Wavelet Analysis Application on Aerodynamic Field Measurement in Furnace by Acoustic Method

声学法测量是炉内动力场检测的先进方法,但是,由于炉内复杂的环境噪声及声波传播时的衰减,声波信号的可靠辨识以获得准确的传播时间成为该方法的关键之一。基于小波技术在包括信号处理等许多方面所具有的巨大优越性,研究了小波分析应用于声学法测量的方法。将静态场中的声波信号加上不同随机噪声并进行滤波分析,证明小波法的结果明显优于传统滤波方法。在此基础上,结合声学法测量中具体声波信号的特点,给出了小波及小波包分析在声波信号消噪处理中的应用方法及其在炉膛模型动力场声学法测量实验中的应用结果。

Acoustic method is an advanced technique for the aerodynamic field measurement in furnace. However, for the complicated background noise and the attenuation of acoustic signals in propagation, reliable identification of the signals received is a key to achieve the accurate flight time data. Wavelet analysis possesses a giant advantage in many fields including signal processing. This paper showed that by adding different random noise to the acoustic signals transmitting in a static field, and then comparing the filtering effects by different methods, the wavelet analysis proves to be more effective than the traditional method. The wavelet analysis was used to process the acoustic signals from the aerodynamic field measurement in a furnace model, with satisfactory measuring results presented. And as well, the principle of using wavelet and wavelet packet to analyze the acoustic signals in the measurement was introduced.