Shearer drum load identification method based on audio recognition

In order to solve the problems of the existing shearer drum load identification methods, such as difficult implementation of related algorithms, complex engineering implementation mode and high application difficulty, through analyzing the characteristics of the audio signal during shearer operation, a shearer drum load identification method based on audio recognition is proposed. In order to ensure that the audio signal in each analysis period has the same load condition under the same operation standard, the cutting current and the traction speed are introduced into the dynamic energy calculation as variables, and the dynamic energy normalization algorithm (DENA) is adopted to normalize the original audio signal of the shearer. The normalized signal is compared and analyzed with the signal in the standard operation condition library, and the difference between the two is judged by the maximum dissimilarity coefficient, so as to determine the characteristics of the drum load and realize the identification and judgment of the drum load. The test results show that DENA can effectively suppress the noise energy in the audio signal and improve the resolution of the key characteristic values in the audio signal. The boundary of the characteristic parameters of the audio signal is obvious when the shearer cuts coal and rock, and there is no cross aliasing phenomenon. Under ideal conditions, that is, when the maximum dissimilarity coefficient is less than 0.189, the total coal-rock interface recognition rate can reach 78.6%.