Method of continuous programmed diagnostics of equipment

Authors: Zatonskiy A. V.

It is important to diagnose mining and processing equipment to optimize effectiveness and image of businesses and industries. Existing software tools of vibration diagnostics feature some disadvantages, including computational complexity and multiplicity of settings. Moreover, troubleshooting of equipment conventionally uses only special diagnostic information, while the data on the process-dependent parameters are also applicable. This article proposes a simple and efficient method of programmed determination of state changes in equipment. The method is tested using specially generated sequences of noisy signals reflective of transient processes in standard process equipment. The trends of the signals were processed using different nature filters. The filtered sequence of the signals over an assigned period of time was converted to a histogram of value ranges of the signals. The difference of the histograms was calculated as the rate of difference between the vectors formed by the values of pockets in the histograms. Special condition of equipment is identified by the sum of differences of the histograms within a sliding window. It is shown that with the appropriate filtration algorithm and rate of difference of histograms at the moment of special condition, the value of the diagnostic signal increases by a few times as compared with the normal condition of equipment. This computationally simple algorithm allows using data of any nature for continuous diagnostics of equipment.

Keywords: mining equipment, diagnostics, identification, special conditions, algorithm, software.
For citation:

Zatonskiy A. V. Method of continuous programmed diagnostics of equipment. MIAB. Mining Inf. Anal. Bull. 2020;(4):146-154. [In Russ]. DOI: 10.25018/0236-1493-20204-0-146-154.

Issue number: 4
Year: 2020
Page number: 146-154
ISBN: 0236-1493
UDK: 622.6+004.92
DOI: 10.25018/0236-1493-2020-4-0-146-154
Article receipt date: 19.02.2020
Date of review receipt: 16.03.2020
Date of the editorial board′s decision on the article′s publishing: 20.03.2020
About authors:

A.V. Zatonskiy, Dr. Sci. (Eng.), Professor, Perm National Research Polytechnic University, Berezniki branch, 618404, Berezniki, Russia, e-mail:

For contacts:

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