Enhancement of explosive energy distribution using UAVs and machine learning

Valencia, Jorge Andrés Alvarado; Battulwar, Rushikesh; Naghadehi, Masoud Zare; Sattarvand, Javad

doi:10.1201/9780429320774-79

Cited by 6 publications

(3 citation statements)

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“…The centerline of benches in an open-pit mine can be automatically extracted from the DEM, as shown in Winkelmaier et al [11]. Wind speed during simulation studies was 0 m/s, and hence, not considered, although speed and direction of the wind are parameters in Equation (6). The optimal flight plan would certainly change depending on wind conditions [39].…”

Section: Discussionmentioning

confidence: 99%

“…As a result, many companies have already been using drones for surveying, volumetric analyses, and visual inspection of inaccessible locations (e.g., Rio Tinto [1], BHP Billiton [2], Newmont [3], and Barrick [4]). Other applications, such as designed vs. actual survey of ramps and benches [5], detecting the height of safety berms, blast fragmentation analysis and determining the accuracy of drill 2 of 20 holes [6], and vegetation [7], and surface moisture [8] monitoring have been presented in the literature. Completing all of these tasks with aerial missions can result in significant benefits for mining operations in terms of time and resource utilization; however, available technologies for using drone images by application of artificial intelligence, computer vision, and machine learning algorithms have not yet been developed to their highest capacities.…”

Section: Introductionmentioning

confidence: 99%

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A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization

et al. 2020

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High-resolution terrain models of open-pit mine highwalls and benches are essential in developing new automated slope monitoring systems for operational optimization. This paper presents several contributions to the field of remote sensing in surface mines providing a practical framework for generating high-resolution images using low-trim Unmanned Aerial Vehicles (UAVs). First, a novel mobile application was developed for autonomous drone flights to follow mine terrain and capture high-resolution images of the mine surface. In this article, case study is presented showcasing the ability of developed software to import area terrain, plan the flight accordingly, and finally execute the area mapping mission autonomously. Next, to model the drone’s battery performance, empirical studies were conducted considering various flight scenarios. A multivariate linear regression model for drone power consumption was derived from experimental data. The model has also been validated using data from a test flight. Finally, a genetic algorithm for solving the problem of flight planning and optimization has been employed. The developed power consumption model was used as the fitness function in the genetic algorithm. The designed algorithm was then validated using simulation studies. It is shown that the offered path optimization can reduce the time and energy of high-resolution imagery missions by over 50%. The current work provides a practical framework for stability monitoring of open-pit highwalls while achieving required energy optimization and imagery performance.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization

et al. 2020

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“…Once regular UAS surveys become best practice for open-pit drilling, drill locations could be predefined in detailed orthophotos and subsurface drill orientations could be optimized by model-based interpretation of 3D data. In active mines, optical imagery is already implemented for explosive energy distribution optimization [68].…”

Section: Assessing the General Uas Survey Workflow With Focus On Imagmentioning

confidence: 99%

Integrated Geological and Geophysical Mapping of a Carbonatite-Hosting Outcrop in Siilinjärvi, Finland, Using Unmanned Aerial Systems

et al. 2020

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Mapping geological outcrops is a crucial part of mineral exploration, mine planning and ore extraction. With the advent of unmanned aerial systems (UASs) for rapid spatial and spectral mapping, opportunities arise in fields where traditional ground-based approaches are established and trusted, but fail to cover sufficient area or compromise personal safety. Multi-sensor UAS are a technology that change geoscientific research, but they are still not routinely used for geological mapping in exploration and mining due to lack of trust in their added value and missing expertise and guidance in the selection and combination of drones and sensors. To address these limitations and highlight the potential of using UAS in exploration settings, we present an UAS multi-sensor mapping approach based on the integration of drone-borne photography, multi- and hyperspectral imaging and magnetics. Data are processed with conventional methods as well as innovative machine learning algorithms and validated by geological field mapping, yielding a comprehensive and geologically interpretable product. As a case study, we chose the northern extension of the Siilinjärvi apatite mine in Finland, in a brownfield exploration setting with plenty of ground truth data available and a survey area that is partly covered by vegetation. We conducted rapid UAS surveys from which we created a multi-layered data set to investigate properties of the ore-bearing carbonatite-glimmerite body. Our resulting geologic map discriminates between the principal lithologic units and distinguishes ore-bearing from waste rocks. Structural orientations and lithological units are deduced based on high-resolution, hyperspectral image-enhanced point clouds. UAS-based magnetic data allow an insight into their subsurface geometry through modeling based on magnetic interpretation. We validate our results via ground survey including rock specimen sampling, geochemical and mineralogical analysis and spectroscopic point measurements. We are convinced that the presented non-invasive, data-driven mapping approach can complement traditional workflows in mineral exploration as a flexible tool. Mapping products based on UAS data increase efficiency and maximize safety of the resource extraction process, and reduce expenses and incidental wastes.

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Advanced Analytics for Rock Blasting and Explosives Engineering in Mining

Mariz

Soofastaei

2022

Advanced Analytics in Mining Engineering

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Enhancement of explosive energy distribution using UAVs and machine learning

Cited by 6 publications

References 0 publications

A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization

A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization

Integrated Geological and Geophysical Mapping of a Carbonatite-Hosting Outcrop in Siilinjärvi, Finland, Using Unmanned Aerial Systems

Advanced Analytics for Rock Blasting and Explosives Engineering in Mining

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