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TRACKING OPERATION REGIMES OF THE LHD MACHINES BASED ON HYDRAULIC SIGNAL ? SIGNAL SMOOTHING ISSUES
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M. Stachowiak;W. Koperska;B. Jachnik;P. Stefaniak
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1314-2704
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English
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20
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1.2
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The development of advanced analytics for data measured by SCADA systems is crucial from the viewpoint of process monitoring, management, and optimization. Many mining assets are characterized by cyclical operations performed with a fixed sequence of their course. An example is the Load Haul Dump (LHD) machine transporting material from the mining face to the dumping point, where the material is preloaded into a further means of transport - a conveyor belt. For wheel loader, the basic signal is pressure signal measured at a bucket?s hydraulic cylinder in which we can distinguish the particular sub-processes of haulage ? loading, driving with a full bucket, return to mining face. In the literature, there are known many methods of signal segmentation that are able to recognize these regimes automatically. Unfortunately, in the case of the raw hydraulic pressure signal, we are dealing with various artifacts and noises, which makes the segmentation task very difficult or even impossible. In this article, we present the review of signal smoothing methods and check their efficiency, especially in terms of retaining informative trends in the signals. All of the methods have been validated on real-life data from the LHD vehicles working in mining conditions. Each of the smoothing methods was tested for two samples, one shorter, containing a period of one hour and one longer - two hours. Comprehensive comparative analysis has been performed between presented methods - for a more accurate comparison, several statistics were determined based on the number and duration of designated cycles.
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conference
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20th International Multidisciplinary Scientific GeoConference SGEM 2020
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20th International Multidisciplinary Scientific GeoConference SGEM 2020, 18 - 24 August, 2020
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Proceedings Paper
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STEF92 Technology
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International Multidisciplinary Scientific GeoConference-SGEM
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SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts & Letters; Acad Fine Arts Zagreb Croatia; C
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383-394
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18 - 24 August, 2020
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website
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cdrom
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6907
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LHD; signal segmentation; signal smoothing; efficiency analysis; underground mining
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