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This paper utilizes acoustic parameters such as FS,NC, N, P, INC, FL, FH, W for acoustic signals S of different running conditions of a ballmill to deriveout the acoustic signatures and hence control signals, which is to be used for designing the control systems of the mill. The parameters FS, NC, N, P, INC, FL, FH and W are represented by sample rate in Hz, number of cepstral coefficients, length of frame in samples, number of filters in filter bank, frame increment, low end of the lowest filter, high end of highest filter and the window over which the analysis is to be performed respectively. The work establishes an appropriate theoretical background that helps to predict dynamic breakage characteristics with respect to particle size distribution of materials, adequately supported by experimental data. The signatures of different running conditions of grinding mill have been extracted from the captured signal in time frame these have been used as feedback signal to monitor the grinding operation. Condenser based microphones have been used for capturing acoustic signals in time domain directly in computers and stored for further analysis. Matlab R2010b has been used for different analysis of the experiment. On analyzing the signatures, it has been observed whether the fines are produced progressively to attain the desired size range or the mill producing undesired products. Thus, the approach has been used in this paper has the ability to arrive in the stage of optimum grinding by tuning parameters of the mill in real time, and also it can prevent the mill to enter into an erroneous state. Moreover, on study it has found that the present scheme can be used more accurately in comparison to the earlier work of the author. This paper presents an implementation scheme to use acoustic signal as the control signal to regulate the operation of a grinding mill.

Design of Intelligent Control System Using Acoustic Parameters for Grinding Mill Operation