小波滤噪在布里渊光纤传感技术中的应用

Application of Wavelet Denoising Method in Brillouin Optical Sensing Technique

针对布里渊分布式传感技术在实际工程应用中的测试信号受外界环境干扰从而影响测试精度的问题,本文提出采用小波信号处理方法对布里渊分布式光纤传感技术的实测信号进行滤噪处理,并以基于布里渊光纤传感技术的实体智能拉索的应变测试数据进行了验证。实验结果表明,该信号处理方法可以有效的消除测试应变中的噪声,提高了索力测试精度,滤噪前后拉索总平均测试索力相对于控制索力的最大相对误差分别为8.8%和5.1%,适合对含噪布里渊传感测试信号进行的滤噪处理。

Since the measuring signal obtained from Brillouin distributed sensing system, which is disturbed by the external environment, degrades the measuring accuracy in field applications, a wavelet signal processing method is used to denoise the measured signal based on Brillouin distributed optical fiber sensing technology, and verified by the measured strain data of a smart cable based on the Brillouin sensing technology. The results of wavelet denoising method shows that this method can effectively denoise measured strain of the smart cable polluted by noise, and improve the measuring accuracy of cable force. The maximum relative errors between the control cable force and the whole average cable force before and after noise filtering are 8.8% and 5.1%, respectively, which hints that the wavelet denosing method is suitable for the measured signal obtained from the Brillouin optical sensing system.