贯流泵站运行产生的噪声由机械振动和水流湍流引起,频段广、动态性强,对周边环境影响显著.为研究其噪声特性并优化降噪方法,现场采集泵站不同工况下的噪声数据,并利用主成分分析(Principal Component Analysis,PCA)提取主要频段特征.针对提取的噪声特性,设计最小均方(Least Mean Square,LMS)和递推最小二乘法(Recursive Least Square,RLS)自适应滤波算法,分别用于低频机械振动噪声和高频水流噪声的抑制.最后,通过实验证实自适应滤波技术在复杂噪声环境中具有较好的应用价值.
Field Noise Test and Noise Reduction Treatment Method of Tubular Pumping Station
The noise generated by the operation of tubular pump station is caused by mechanical vibration and water turbulence,which has a wide frequency band and strong dynamics and has a significant impact on the surrounding environment.In order to study its noise characteristics and optimize noise reduction methods,the noise data of pumping stations under different working conditions were collected on site,and the main frequency band characteristics were extracted by Principal Component Analysis(PCA).According to the extracted noise characteristics,Least Mean Square(LMS)and Recursive Least Square(RLS)adaptive filtering algorithms are designed to suppress low-frequency mechanical vibration noise and high-frequency water flow noise respectively.Finally,the experiment proves that adaptive filtering technology has good application value in complex noise environment.
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