Denoising methods of acceleration signal of intelligent compaction for asphalt pavement
To address the noise interference in the vibration acceleration signals of intelligent compac-tion for asphalt pavements,wavelet transform and complete ensemble empirical mode decomposition with adaptive noise were used to denoise the acceleration signals.The denoising effects of the two methods were compared based on the modal aliasing degree of each signal component,the time-frequency representation of the signals,the signal-to-noise ratio,and the variation of intelligent compaction measurement values,and then relationship models between the intelligent compaction measurement values and the compaction degree were established before and after denoising.The research indicates that both denoising methods can suppress high-frequency noise and spurious effects in the signals.However,complete ensemble empirical mode decomposition with adaptive noise is more effective in reducing modal aliasing,and can achieve a higher signal-to-noise ratio and better denoising effect,while also alleviating the overlap of intelligent compaction measurement values that varies with the number of compaction cycles,thereby enhancing their correlation with the compaction degree.Comparing two denoised intelligent compaction measurement values including of compaction control value(CCV)and vibratory compaction value(VCV),CCV more accurately reflects changes in compaction degree under different vibration cycle counts and temperatures,making it more suitable for monitoring the quality of intelligent compaction in asphalt pavements.
万方数据
维普
