Abstract
Effective filtering of the infrasound signal generated by coal samples is the basis for realizing the prediction of the infrasound of coal sample damage. Based on the infrasonic signal test of the coal samples during the loading process, a simulation method was used to construct a mixed signal containing noise signals and infrasound signals. Three methods are used to filter the mixed signal, including wavelet filtering, EMD filtering, and EMD-wavelet joint filtering. The filtering effect was compared by correlation coefficient, signal-to-noise ratio, and frequency domain waveform graph. The comparison results showed that the EMD-wavelet joint filtering method had the highest correlation coefficient and signal-to-noise ratio after noise filtering, and the noise signal in the frequency domain waveform diagram was the most thorough. It provides a new method for filtering infrasound signals in the process of coal sample loading, which is greatly significant for improving the accuracy of infrasound prediction of coal sample damage.
Highlights
Infrasound mainly refers to sound waves with a frequency between 0.01 and 20 Hz
According to the test results, it could be seen that the infrasound signal of the coal sample showed abrupt characteristics during the loading process
The rationality of the denoising method was quantitatively evaluated by comparing the signal-to-noise ratio and correlation coefficient before and after processing
Summary
Infrasound mainly refers to sound waves with a frequency between 0.01 and 20 Hz. As a lowfrequency wave, it has the characteristics of low frequency and long wavelength. According to the experimental purpose and experimental plan, the infrasound test of the coal samples was carried out during the loading process. According to the test results, it could be seen that the infrasound signal of the coal sample showed abrupt characteristics during the loading process.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have