ALGORITHMS TO PROCESS DATA OF PRESSURE IN HYDROCYLINDERS OF BOTTOMHOLE SUPPORTS

Algorithms to analyze data produced by pressure sensors mounted on hydraulic cylinders of mine linings, which are exploited in lavas of the Starobin potash deposit, are presented. To build algorithms, data mining process has been represented by three general stages. First of them consists of data preprocessing. Based on data specifics, algorithms of removing outliers as well as determining characteristics independent of tunneling machine location and state of bottomhole supports were included in it. The second stage contains algorithms of finding in the preprocessed data of cycles, which were created by descent of mining supports, and phases of cycles that depend on location of the tunneling machine relative to those supports. Algorithms of the third stage were built to compute data characteristics connected with the found cycles and their phases. Besides, modifications of correlation algorithms for aggregated data were developed in order to investigate relationship between the characteristics, including their coupling with behavior of rock pressure. The algorithms are designed for use in automated monitoring systems of rock pressure in lavas of potash mines, including mines of the Joint Stock Company “Belaruskali”. The developed algorithms were programmed. Program realizations were seriously tested on big data supplied by pressure sensors mounted on hydraulic cylinders of bottomhole supports of the Starobin potash deposit. As an example of application of the developed algorithms, it is shown that acceleration of mining process increases the likelihood of rock blows to the supports.

data mining, mining supports, extraction of the potassium salt, Starobin deposit, monitoring, lava penetration rate, blows to the mining supports

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