Full
Outline
Aiming at the problems of insufficient accuracy and weak environmental adaptability of traditional coal quantity detection devices due to the dynamic change of coal volume and the harsh working conditions such as high dust and high water mist in coal mines, a coal quantity detection method based on LiDAR and visual image fusion for extreme working conditions was proposed. Firstly, the joint calibration of LiDAR and visual camera was carried out, the mapping relationship was established and the coordinate system was unified. Then, the sampling data was obtained by a specific strategy, and the coal region was identified by Poisson reconstruction algorithm, spatial filtering strategy and structural similarity index. Finally, the depth image completion network was used to repair the depth map, and the coal amount was calculated based on the repair results. The results show that the maximum detection error of the fusion method of LiDAR and visual camera is only 2.90%, and the error decreases further with the increase of coal volume. Compared with mainstream depth completion algorithms such as ENet, the proposed algorithm achieves the best core accuracy index and meets the industrial real-time requirements. This method is basically consistent with the fluctuation of the detection curve of the contact electronic belt scale, which verifies its reliability. This method effectively overcomes the limitations of a single sensor, significantly improves the accuracy of coal quantity detection, and can operate stably in harsh environments. It provides a new technical solution for the accurate detection of coal quantity of belt conveyor and holds great significance for promoting the intelligent and efficient production of coal mines.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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