Volume 49 Issue 8
Aug.  2023
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Article Navigation >  Journal of Mine Automation  > 2023  >  49(8): 88-93, 147
LI Xiaowei, WANG Jianye. Research on high sampling frequency mine electric spark image recognition and anti-interference methods[J]. Journal of Mine Automation，2023，49(8)：88-93, 147.  doi: 10.13272/j.issn.1671-251x.18145
Citation: LI Xiaowei, WANG Jianye. Research on high sampling frequency mine electric spark image recognition and anti-interference methods[J]. Journal of Mine Automation，2023，49(8)：88-93, 147.  doi: 10.13272/j.issn.1671-251x.18145
shu

Research on high sampling frequency mine electric spark image recognition and anti-interference methods

doi: 10.13272/j.issn.1671-251x.18145

  • School of Artificial Intelligence, China University of Mining and Technology-Beijing, Beijing 100083, China

  • Received Date: 2023-08-07
  • Rev Recd Date: 2023-08-16
    • Available Online: 2023-09-04
    Abstract
  • Leakage of electricity from cables and electrical equipment outside the explosion-proof enclosure, and mine sparks generated by high-power radio transmissions on metal supports and metal of electromechanical equipment due to induced electromotive discharges, can cause gas and coal dust explosions and mine fires. Therefore, it is necessary to detect mine electrical sparks as soon as possible. The main factor affecting the recognition of mine electric sparks is the mine light source. In order to reduce the interference of mine light sources on mine electric spark image recognition, a high sampling frequency mine electric spark image recognition and anti-interference method has been proposed. Based on the longest continuous emission time of the electric spark and the shortest continuous emission time of the flash light source, the sampling frequency of the camera is calculated to ensure that the electric spark image only appears in one frame of the image each time the electric spark appears. When the mine light source exists, the interference light source image appears on at least 2 consecutive frames of image. The method calculates the pixel grayscale sum of each image frame. If the difference between the pixel grayscale of the current frame image and the pixel grayscale sum of adjacent frames is greater than the set threshold, a mine electric spark alarm signal will be issued. The experimental results show that under the condition of no interference light source, this method can accurately recognize mine electric spark images with an accuracy rate of 100%. Under the interference of constant light sources such as fluorescent lamps and incandescent lamps, the recognition accuracy of electric sparks in mixed images of electric sparks and fluorescent lamps reaches 99.40%. The recognition accuracy of electric sparks in mixed images of electric sparks and incandescent lamps reaches 99.67%. Under the interference of a flashing light source, the accuracy of electric spark recognition in the mixed image of electric spark and flash lamp reaches 100%.

     

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