Scholarly record
OVERSIZED ORE PIECES DETECTION METHOD BASED ON COMPUTER VISION AND SOUND PROCESSING FOR VALIDATION OF VIBRATIONAL SIGNALS IN DIAGNOSTICS OF MINING SCREEN
Abstract
The main purpose in mineral processing plant is to obtain the highest possible value from a processed raw material. In majority of concentrators in the world mining the first step of the processing technology is sieving of ore that is performed using vibrating screens. Usually, in the whole technological system there are only several such machines. That is why their continuous operation is critical and they are often concerned as a bottleneck of the whole system. Although the vibrating screens are expected to keep the highest reliability indicators, their maintenance is still very often carried out using a planned and preventive strategy. Usually the diagnostics of such systems is based on vibro-acoustic methods. But the collected vibrational signals may be significantly disrupted be large pieces of ore hitting the screen. That?s why the development of diagnostic techniques, especially for rotational elements, should take into account validation methods associated with the identification of processed material impact on the screen and its elimination from the structure of the vibrational signal. Paper presents a method for detecting large rocks with the help of computer vision and audio signal processing. Usage of two sources of data makes possible cross validation of the results obtained by particular methods, which increases the robustness of the algorithm. The main purpose of the algorithm is to filter the vibrational signals from the screen for further analysis.
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