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Online shearer-onboard personnel detection method for the intelligent fully mechanized mining face
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science ( IF 1.8 ) Pub Date : 2021-07-13 , DOI: 10.1177/09544062211030973
Dong Wei 1 , Zhongbin Wang 1, 2 , Lei Si 1 , Chao Tan 1 , Xuliang Lu 1
Affiliation  

As unmanned coal mining technology gradually replaces the traditional mechanized coal mining technology, shearer operation mode is changed from local control to remote control in intelligent fully mechanized mining face. In remote control mode, it is difficult to protect the personnel who straying into the shearer operator space without observation and reminder from the shearer operator. Hence, it is necessary to establish an intelligent personnel detection method to protect the safety of coal miners in intelligent unmanned mining face. The environment of low and non-uniform illumination in fully mechanized coal mining face has seriously restricted the application of personnel detection technology based on visible light imaging. Therefore, a personnel detection method based on infrared thermal imaging is proposed in this paper to solve the disadvantages of using visible light imaging in downhole applications. On this basis, a spatiotemporal guided filter is proposed to harmonize the relationship between edge-preserving and noise-removing. Then, an improved Lucas-Kanade method based on the adaptive-size window is utilized to achieve a more robust personnel detection. Moreover, the personnel detection in the shearer operating space is realized based on epipolar geometry and morphology processing. Finally, the laboratory experiment and industrial test are carried out to evaluate the proposed method, and the results indicate the feasibility and superiority of the proposed methods which show considerable application prospects.



中文翻译:

智能综采工作面采煤机在线人员检测方法

随着无人采煤技术逐渐取代传统的机械化采煤技术,采煤机作业方式从就地控制向智能综采工作面远程控制转变。在远程控制模式下,如果没有采煤机操作员的观察和提醒,很难保护误入采煤机操作员空间的人员。因此,有必要建立智能人员检测方法,以保障智能无人采工作面煤矿工人的安全。综采工作面照明度低且不均匀的环境严重制约了基于可见光成像的人员检测技术的应用。所以,针对可见光成像在井下应用中的不足,本文提出了一种基于红外热成像的人员检测方法。在此基础上,提出了一种时空引导滤波器来协调边缘保留和噪声去除之间的关系。然后,利用基于自适应大小窗口的改进 Lucas-Kanade 方法来实现更鲁棒的人员检测。此外,采煤机操作空间中的人员检测是基于对极几何和形态处理实现的。最后,通过实验室实验和工业试验对所提出的方法进行了评价,结果表明了所提出方法的可行性和优越性,具有可观的应用前景。在此基础上,提出了一种时空引导滤波器来协调边缘保留和噪声去除之间的关系。然后,利用基于自适应大小窗口的改进 Lucas-Kanade 方法来实现更鲁棒的人员检测。此外,采煤机操作空间中的人员检测是基于对极几何和形态处理实现的。最后,通过实验室实验和工业试验对所提出的方法进行了评价,结果表明了所提出方法的可行性和优越性,具有可观的应用前景。在此基础上,提出了一种时空引导滤波器来协调边缘保留和噪声去除之间的关系。然后,利用基于自适应大小窗口的改进 Lucas-Kanade 方法来实现更鲁棒的人员检测。此外,采煤机操作空间中的人员检测是基于对极几何和形态处理实现的。最后,通过实验室实验和工业试验对所提出的方法进行了评价,结果表明了所提出方法的可行性和优越性,具有可观的应用前景。利用基于自适应大小窗口的改进 Lucas-Kanade 方法来实现更稳健的人员检测。此外,采煤机操作空间中的人员检测是基于对极几何和形态处理实现的。最后,通过实验室实验和工业试验对所提出的方法进行了评价,结果表明了所提出方法的可行性和优越性,具有可观的应用前景。利用基于自适应大小窗口的改进 Lucas-Kanade 方法来实现更稳健的人员检测。此外,采煤机操作空间中的人员检测是基于对极几何和形态处理实现的。最后,通过实验室实验和工业试验对所提出的方法进行了评价,结果表明了所提出方法的可行性和优越性,具有可观的应用前景。

更新日期:2021-07-13
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