scholarly journals Continuous Monitoring and Improvement of the Blasting Process in Open Pit Mines Using Unmanned Aerial Vehicle Techniques

2020 ◽  
Vol 12 (17) ◽  
pp. 2801
Author(s):  
Thomas Bamford ◽  
Filip Medinac ◽  
Kamran Esmaeili

The current techniques used for monitoring the blasting process in open pit mines are manual, intermittent and inefficient and can expose technical manpower to hazardous conditions. This study presents the application of unmanned aerial vehicle (UAV) systems for monitoring and improving the blasting process in open pit mines. Field experiments were conducted in different open pit mines to assess rock fragmentation, blast-induced damage on final pit walls, blast dynamics and the accuracy of blastholes including production and pre-split holes. The UAV-based monitoring was done in three different stages, including pre-blasting, blasting and post-blasting. In the pre-blasting stage, pit walls were mapped to collect structural data to predict in situ block size distribution and to develop as-built pit wall digital elevation models (DEM) to assess blast-induced damage. This was followed by mapping the production blasthole patterns implemented in the mine to investigate drillhole alignment. To monitor the blasting process, a high-speed camera was mounted on the UAV to investigate blast initiation, sequencing, misfired holes and stemming ejection. In the post-blast stage, the blasted rock pile (muck pile) was monitored to estimate fragmentation and assess muck pile configuration, heave and throw. The collected aerial data provide detailed information and high spatial and temporal resolution on the quality of the blasting process and significant opportunities for process improvement. The current challenges with regards to the application of UAVs for blasting process monitoring are discussed, and recommendations for obtaining the most value out of an UAV application are provided.

2019 ◽  
Vol 29 (2) ◽  
pp. 771-790 ◽  
Author(s):  
Xuan-Nam Bui ◽  
Yosoon Choi ◽  
Victor Atrushkevich ◽  
Hoang Nguyen ◽  
Quang-Hieu Tran ◽  
...  

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Nguyen QUOC LONG ◽  
Ropesh GOYAL ◽  
Bui KHAC LUYEN ◽  
Le VAN CANH ◽  
Cao XUAN CUONG ◽  
...  

Lightweight Unmanned Aerial Vehicle (UAV) for 3D topographic mapping in mining industry has been raised significantly in recent years. Especially, in complex terrains such as in open-pit mines in which the elevation is rapidly undulating, UAV-based mapping has proven its economical efficiency and higher safety compared to the conventional methods. However, one of the most important factors in UAV mapping of complex terrain is the flight altitude, which needs to be considered seriously because of the safety and accuracy of generated DEMs. This paper aims to evaluate the influence of the flight height on the accuracy of DEMs generated in open-pit mines. To this end, the study area is selected in a quarry with a complex terrain, which is located in northern Vietnam. The investigation was conducted with five flight heights of 50 m, 100 m, 150 m, 200 m, and 250 m. To assess the accuracy of resulting DEMs, ten ground control points (GCPs), and 385 checkpoints measured by both GNSS/RTK and total station methods were used. The accuracy of DEM was assessed by root-mean-square error (RMSE) in X, Y, Z, XY, and XYZ components. The results show that DEM models generated at the flight heights of less than 150 m have high accuracy. RMSEs of the 10 GCPs increase from 1.8 cm to 6.2 cm for the vertical (Z), and from 2.6 cm to 6.3 cm for the horizontal (XY), whereas RMSE of 385 checkpoints increase gradually from 0.05 m to 0.15 m for the vertical (Z) when the flight height increases from 50 m to 250 m.


2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Le VAN CANH ◽  
Cao XUAN CUONG ◽  
Nguyen QUOC LONG ◽  
Le THI THU HA ◽  
Tran TRUNG ANH ◽  
...  

Open-pit coal mines’ terrain is often complex and quickly and frequently changes. Therefore, topographic surveys of open-pit mines are undertaken on a daily basis. While these tasks are very time-consuming and costly with traditional methods such as total station and GNSS, the unmanned aerial vehicle (UAV) based method can be more efficient. This method is a combination of the “Structure from motion” (SfM) photogrammetry technique and UAV photogrammetry which has been widely used in topographic surveying. With an increasing popularity of RTK-enabled drones, it is becoming even more powerful method. While the important role of ground control points (GCP) in the accuracy of digital surface model (DSM) generated from images acquired by “traditional” UAVs (not RTK-enabled drones) has been proved in many previous studies, it is not clear in the case of RTK-enabled drones, especially for complex terrain in open-pit coal mines. In this study, we experimentally investigated the influence of GCP regarding its numbers and distribution on the accuracy of DSM generation from images acquired by RTK-enabled drones in open-pit coal mines. In addition, the Post Processing Kinematic (PPK) mode was executed over a test field with the same flight altitude. DSM generation was performed with several block control configurations: PPK only, PPK with one GCP, and PPK with two GCPs. Several positions of GCPs were also examined to test the optimal locations for placing GCPs to achieve accurate DSMs. The results show that the horizontal and vertical accuracy given by PPK only were 9.3 and 84.4 cm, respectively. However, when adding at least one GCP, the accuracy was significantly improved in both horizontal and vertical components, with RMSE for XY and Z ranging between 3.8 and 9.8 cm (with one GCP) and between 3.0 and 5.7 cm (with two GCPs), respectively. Also, the GCPs placed in the deep areas of the open-pit mine could ensure the cm-level accuracy.


2021 ◽  
Vol 13 (18) ◽  
pp. 3652
Author(s):  
Duo Xu ◽  
Yixin Zhao ◽  
Yaodong Jiang ◽  
Cun Zhang ◽  
Bo Sun ◽  
...  

Information on the ground fissures induced by coal mining is important to the safety of coal mine production and the management of environment in the mining area. In order to identify these fissures timely and accurately, a new method was proposed in the present paper, which is based on an unmanned aerial vehicle (UAV) equipped with a visible light camera and an infrared camera. According to such equipment, edge detection technology was used to detect mining-induced ground fissures. Field experiments show high efficiency of the UAV in monitoring the mining-induced ground fissures. Furthermore, a reasonable time period between 3:00 a.m. and 5:00 a.m. under the studied conditions helps UAV infrared remote sensing identify fissures preferably. The Roberts operator, Sobel operator, Prewitt operator, Canny operator and Laplacian operator were tested to detect the fissures in the visible image, infrared image and fused image. An improved edge detection method was proposed which based on the Laplacian of Gaussian, Canny and mathematical morphology operators. The peak signal-to-noise rate, effective edge rate, Pratt’s figure of merit and F-measure indicated that the proposed method was superior to the other methods. In addition, the fissures in infrared images at different times can be accurately detected by the proposed method except at 7:00 a.m., 1:00 p.m. and 3:00 p.m.


Author(s):  
Amirhossein Fereidountabar ◽  
Gian Carlo Cardarilli ◽  
Luca Di Nunzio ◽  
Rocco Fazzolari

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