The Analysis of Stochastic Signal from LHD Mining Machine

In this paper a novel procedure for LHD (Load-Haul-Dump) machine temperature signal analysis is proposed. In this procedure the signal segmentation and its decomposition into trend and residuals is made. Moreover in the next step the novel technique for further decomposition of residuals is proposed and stochastic analysis procedure is applied. The stochastic analysis is based on the ARMA (autoregressive moving average) models with Gaussian and strictly stable distribution. Different nature of extracted sub-signals offers specific opportunity to use them for condition monitoring as well as process monitoring purposes. Appropriate processing techniques give a chance to observe specific character in the acquired data. In this paper we present basic theory related to the applied methodology as well as practical example obtained by application of proposed techniques.

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