Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance manag...Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance management such as multiple cards for one person, and swiping one's cards by others in China at present. Therefore, the research introduces a uniqueness detection system and method for in-pit coal-mine personnel integrated into the in-pit coal mine personnel positioning system, establishing a system mode based on face recognition + recognition of personnel positioning card + release by automatic detection. Aiming at the facts that the in-pit personnel are wearing helmets and faces are prone to be stained during the face recognition, the study proposes the ideas that pre-process face images using the 2D-wavelet-transformation-based Mallat algorithm and extracts three face features: miner light, eyes and mouths, using the generalized symmetry transformation-based algorithm. This research carried out test with 40 clean face images with no helmets and 40 lightly-stained face images, and then compared with results with the one using the face feature extraction method based on grey-scale transformation and edge detection. The results show that the method described in the paper can detect accurately face features in the above-mentioned two cases, and the accuracy to detect face features is 97.5% in the case of wearing helmets and lightly-stained faces.展开更多
随着煤矿开采的自动化、无人化进程不断推进,煤矿井下综采工作面自动化设备的数量逐渐增多,在此种情况下,为及时掌握综采工作面工作人员的位置信息,保障人员安全,本文对基于超宽带(Ultra-Wideband,UWB)技术的综采工作面人员定位系统进...随着煤矿开采的自动化、无人化进程不断推进,煤矿井下综采工作面自动化设备的数量逐渐增多,在此种情况下,为及时掌握综采工作面工作人员的位置信息,保障人员安全,本文对基于超宽带(Ultra-Wideband,UWB)技术的综采工作面人员定位系统进行设计。首先,结合煤矿井下综采工作面现场环境和实际需求,对系统总体结构进行设计。在算法方面,选用基于飞行时间(Time of Flight,TOF)的测距算法并采用双边双程测距的方式进行测距;为降低非视距误差和噪声对测距效果的影响,采用卡尔曼滤波算法对原始测距值进行处理;为避免测距过程中多个标识卡间的干扰,引入时间槽分配机制。硬件方面主要是完成基站和标识卡的相关硬件电路设计,主要包括电源电路、MCU最小系统电路、超宽带模块电路、通信电路等。在完成系统相关研究与设计的基础上,在模拟工作面环境下进行系统测试,测试结果表明,有效测量范围在25 m内时,系统测距误差小于0.2 m,测距值波动程度较低,测距稳定,满足系统设计要求。展开更多
基金financial supports from the National Natural Science Foundation of China (No. 51134024)the National High Technology Research and Development Program of China (No. 2012AA062203)are gratefully acknowledged
文摘Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance management such as multiple cards for one person, and swiping one's cards by others in China at present. Therefore, the research introduces a uniqueness detection system and method for in-pit coal-mine personnel integrated into the in-pit coal mine personnel positioning system, establishing a system mode based on face recognition + recognition of personnel positioning card + release by automatic detection. Aiming at the facts that the in-pit personnel are wearing helmets and faces are prone to be stained during the face recognition, the study proposes the ideas that pre-process face images using the 2D-wavelet-transformation-based Mallat algorithm and extracts three face features: miner light, eyes and mouths, using the generalized symmetry transformation-based algorithm. This research carried out test with 40 clean face images with no helmets and 40 lightly-stained face images, and then compared with results with the one using the face feature extraction method based on grey-scale transformation and edge detection. The results show that the method described in the paper can detect accurately face features in the above-mentioned two cases, and the accuracy to detect face features is 97.5% in the case of wearing helmets and lightly-stained faces.
文摘随着煤矿开采的自动化、无人化进程不断推进,煤矿井下综采工作面自动化设备的数量逐渐增多,在此种情况下,为及时掌握综采工作面工作人员的位置信息,保障人员安全,本文对基于超宽带(Ultra-Wideband,UWB)技术的综采工作面人员定位系统进行设计。首先,结合煤矿井下综采工作面现场环境和实际需求,对系统总体结构进行设计。在算法方面,选用基于飞行时间(Time of Flight,TOF)的测距算法并采用双边双程测距的方式进行测距;为降低非视距误差和噪声对测距效果的影响,采用卡尔曼滤波算法对原始测距值进行处理;为避免测距过程中多个标识卡间的干扰,引入时间槽分配机制。硬件方面主要是完成基站和标识卡的相关硬件电路设计,主要包括电源电路、MCU最小系统电路、超宽带模块电路、通信电路等。在完成系统相关研究与设计的基础上,在模拟工作面环境下进行系统测试,测试结果表明,有效测量范围在25 m内时,系统测距误差小于0.2 m,测距值波动程度较低,测距稳定,满足系统设计要求。
