摘要
针对某履带式车辆发动机支撑压力传感器信号由于工况复杂、环境恶劣所导致的信噪比低、有效信号被埋没等问题,该文提出了一种基于自适应白噪声的完整集成经验模态分解与自相关函数(CEEMDAN-AF)和提升小波的联合去噪方法。该方法首先对信号进行CEEMDAN分解得到IMF分量,通过AF判别出IMF分量中噪声主导分量并对其进行提升小波去噪,最后进行数据重构得到去噪信号。通过实验仿真和实测压力传感器信号对比验证表明,该方法在信噪比和均方根误差方面具有优势,对实测压力传感器信号去噪效果明显。
In view of the problems of low signal-to-noise ratio caused by complex working conditions and poor environment,the effective signals are buried in a certain tracked vehicle engine support pressure sensor signal. Based on adaptive white noise,a complete integrated empirical mode decomposition and autocorrelation function and lifting wavelet threshold are proposed for joint de-noising. The method firstly decomposes the signal by CEEMDAN to obtain the IMF component. The noise dominant component is identified by AF and the noise is de-noised by lifting wavelet. Finally,the data is reconstructed. Through comparison and verification of experimental simulation and measured pressure sensor signals,the method has advantages in SNR and RMSE,and has obvious effect on DE noising of measured pressure sensor signals.
作者
顾中禹
靳鸿
崔建峰
GU Zhong-yu;JIN Hong;CUI Jian-feng(National Key Laboratory for Electronic Measurement Technology,Key Laboratory of Instrumentation Science and Dynamic Measurement,Ministry of Education,North University of China,Taiyuan 030051,China)
出处
《自动化与仪表》
2019年第5期5-9,共5页
Automation & Instrumentation
