An improved joint method for onset picking of acoustic emission signals with noise

Abstract

The onset times of acoustic signals with spikes, heavy bodies and unclear takeoffs are difficult to be picked accurately by the automatic method at present. To deal with this problem, an improved joint method based on the discrete wavelet transform (DWT), modified energy ratio (MER) and Akaike information criterion (AIC) pickers, has been proposed in this study. First, the DWT is used to decompose the signal into various components. Then, the joint application of MER and AIC pickers is carried out to pick the initial onset times of all selected components, where the minimum AIC position ahead of MER onset time is regarded as the initial onset time. Last, the average for initial onset times of all selected components is calculated as the final onset time of this signal. This improved joint method is tested and validated by the acoustic signals with different signal to noise ratios (SNRs) and waveforms. The results show that the improved joint method is not affected by the variations of SNR, and the onset times picked by this method are always accurate in different SNRs. Moreover, the onset times of all acoustic signals with spikes, heavy bodies and unclear takeoffs can be accurately picked by the improved joint method. Compared to some other methods including MER, AIC, DWT-MER and DWT-AIC, the improved joint method has better SNR stabilities and waveform adaptabilities.

Keywords

Akaike information criterion (AIC) / modified energy ratio (MER) / discrete wavelet transform (DWT) / acoustic signals with noise

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