智慧煤矿数据驱动检测技术研究

Research on data-driven detection technology of smart coal mine

  • 摘要: 数据驱动检测技术是智慧煤矿发展的有效组成部分,其在无需知道智慧煤矿大数据系统精确解析模型的情况下完成对未来对象系统行为的预测。针对智慧煤矿的生产运行智能化、安全生产本质化、运营模式科学化等难题,分析了数据驱动检测技术在煤矿设备故障诊断、胶带运输异物检测、煤矸检测辨识等3个方面的应用现状。展望了数据驱动检测技术在这3个方面的发展趋势:① 模糊数学与人工神经网络应更加有效融入煤矿设备故障诊断中;② 视频防抖、图像分割及目标检测技术应更加有效融入胶带运输异物检测中;③ 分拣机器人、计算机视觉及图像识别技术应更加有效融入煤矸检测辨识中,提高算法普适性将是煤矸图像识别发展的方向之一。

     

    Abstract: Data-driven detection technology is an effective part of development of smart coal mine. It can predict behavior of future object system without knowing accurate analytical model of smart coal mine big data system. For the difficult problems of intelligent production operation, inherent safety production,scientific operation mode of smart coal mine, application status of data-driven detection technology in fault diagnosis of coal mine equipment, detection of foreign object in belt transportation and detection and identification of coal-gangue was analyzed.The development trend of data-driven detection technology in these three aspects was prospected: ① Fuzzy mathematics and artificial neural network should be integrated into fault diagnosis of coal mine equipment more effectively; ② Video anti-shake, image segmentation and target detection technologies should be more effectively integrated into detection of foreign object in belt transportation; ③ Sorting robot, computer vision and image recognition technologies should be more effectively integrated into detection and identification of coal-gangue, and improving universality of the algorithm would be one of the development directions of coal-gangue image recognition.

     

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