噪声与振动控制2019，Vol.39Issue(4)：7-11,5.DOI:10.3969/j.issn.1006-1355.2019.04.002
汽车驾驶性评价中小波去噪分解层数的确定
Determination of the Number of Wavelet Denoising Decomposition Layers in Vehicle Driving Evaluation
摘要
Abstract
In the process of vehicle driving evaluation test, a lot of noise signals are usually mixed in the collected signals. And the wavelet transform is usually used for denoising. However, if the number of the wavelet denoising decomposition layers is not properly selected, it will reduce the denoising effect and lower the accuracy of the driving evaluation. For this reason, a multi-index fusion method based on root mean square error, signal-to-noise ratio and data smoothness, collected and combined by information entropy method, is proposed to select the optimal number of layers for wavelet decomposition, so as to obtain the best denoising effect. This method is performed for the acceleration data denoising of the car’s vibration signals collected under a certain shifting condition. The results show that the wavelet denoising method based on this multi-index fusion can well filter the noise in the initial signal and retain the useful components such as various shocks and vibrations during driving so as to ensure the accuracy of the indicators extracted during the subsequent driving evaluation.关键词
声学/汽车驾驶性评价/小波去噪/信息熵法/多指标融合/分解层数Key words
acoustics/ vehicle driving evaluation/ wavelet denoising/ information entropy method/ multiple indicator fusion/ decomposition layer分类
交通工程引用本文复制引用
刘海江,张欣,李敏..汽车驾驶性评价中小波去噪分解层数的确定[J].噪声与振动控制,2019,39(4):7-11,5.基金项目
国家自然科学基金资助项目(U1764259) （U1764259）
