Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Zimroz, Paweł; Trybała, Paweł; Wroblewski, Adam C.; Góralczyk, Mateusz; Szrek, Jarosław; Wójcik, Agnieszka; Zimroz, Radosław

doi:10.3390/en14133725

Cited by 52 publications

(31 citation statements)

References 46 publications

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“…This issue also applies to the mining industry of solid, liquid and gaseous minerals, which is expected to intensify production while minimizing negative impacts on the environment [4][5][6]. This determines the conduct of research and the search for new solutions-both in terms of improving the reliability of machines [7][8][9][10] and optimizing production processes [11][12][13][14][15][16][17] as well as improving work safety [18][19][20][21][22] and caring for the environment [23].…”

Section: Introductionmentioning

confidence: 99%

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Development of a Hydraulic System for the Automatic Expansion of Powered Roof Support

Szurgacz

Borska²,

Diederichs³

et al. 2022

Energies

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A mechanical support in a longwall complex requires proper supervision and control of operating parameters because it is responsible for the safety of machines and workers. Its main functions are to protect the excavation against the adverse effects of rock mass and to move it along with the operational progress of the shearer and the scraper conveyor. In the era of Industry 4.0 as well as green economy and sustainable development, the development of machines and devices included in the longwall complex is an important area of invention. When it comes to the mechanical support included in the longwall complex, the authors propose changes to the hydraulic control system. The main purpose of the work was to develop a system that can automatically expand the legs of the powered support. Tests were carried out under real conditions while equipping the support section with a prototypical hydraulic system and with a system monitoring the correct operation of the prototype. This article presents the development of a prototypical installation under real conditions for testing on a longwall. The innovative solution proposed by the authors consisted of introducing a prototypical double valve block into the hydraulic system of the housing, which enables the function of automatic section expansion. The authors proposed a solution aimed at shortening the work time of the powered-support-section operator. The research results made it possible to evaluate the usefulness of the proposed solution. This type of solution can be considered technical support in the process of coal mining in an underground mine. Analysis presented in this paper, along with results from research conducted and its conclusions, can be of practical help to enclosure users to improve reliability and achieve optimal performance.

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Section: Introductionmentioning

confidence: 99%

“…Energies 2022, 15, x FOR PEER REVIEW 2 of 15 well as improving work safety [18][19][20][21][22] and caring for the environment [23]. Sustainable development is also observed in hard-coal mining, which deals with the intensification of the mining process and an increase in efficiency.…”

Section: Introductionmentioning

confidence: 99%

Development of a Hydraulic System for the Automatic Expansion of Powered Roof Support

Szurgacz

Borska²,

Diederichs³

et al. 2022

Energies

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“…Applications of sound source localization include speaker location search in teleconference, event detection and tracking, and robot movement in an unknown environment [1,2]. Sound source localization solutions, implemented on edge computing devices may be a complementary localization solution for human rescue challenges in Underground Mine [3], applied as a monitoring or predictive maintenance solution [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Azimuth and Elevation for Multiple Acoustic Sources Using Tetrahedral Microphone Arrays and Convolutional Neural Networks

Sakavicius

Serackis

2021

Electronics

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A method for multiple acoustic source localization using a tetrahedral microphone array and a convolutional neural network (CNN) is presented. Our method presents a novel approach for the estimation of acoustic source direction of arrival (DoA), both azimuth and elevation, utilizing a non-coplanar microphone array. In our approach, we use the phase component of the short-time Fourier transform (STFT) of the microphone array’s signals as the input feature for the CNN and a DoA probability density map as the training target. Our findings imply that our method outperforms the currently available methods for multiple sound source DoA estimation in both accuracy and speed.

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“…As more research has been carried out on the ADR challenge, it is clear that new methods and hardware used to tackle it will pave the way to developing new applications requiring agile flight with capabilities for autonomous navigation and object detection. For instance, the primary task of gate detection in ADR could be exploited by applications such as parcel delivery or site inspections where a drone would be required to enter a house or a facility through a window that is detected automatically by the drone's perception system [15,16]; additionally, autonomous navigation and agile flight could be used in search and rescue applications where a drone has to fly over a disaster zone as quickly as possible, not only for the sake of finding survivors but also because battery life is limited [17,18].…”

Section: Introductionmentioning

confidence: 99%

Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera

Rojas-Perez

Martínez-Carranza

2021

Sensors

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Recent advances have shown for the first time that it is possible to beat a human with an autonomous drone in a drone race. However, this solution relies heavily on external sensors, specifically on the use of a motion capture system. Thus, a truly autonomous solution demands performing computationally intensive tasks such as gate detection, drone localisation, and state estimation. To this end, other solutions rely on specialised hardware such as graphics processing units (GPUs) whose onboard hardware versions are not as powerful as those available for desktop and server computers. An alternative is to combine specialised hardware with smart sensors capable of processing specific tasks on the chip, alleviating the need for the onboard processor to perform these computations. Motivated by this, we present the initial results of adapting a novel smart camera, known as the OpenCV AI Kit or OAK-D, as part of a solution for the ADR running entirely on board. This smart camera performs neural inference on the chip that does not use a GPU. It can also perform depth estimation with a stereo rig and run neural network models using images from a 4K colour camera as the input. Additionally, seeking to limit the payload to 200 g, we present a new 3D-printed design of the camera’s back case, reducing the original weight 40%, thus enabling the drone to carry it in tandem with a host onboard computer, the Intel Stick compute, where we run a controller based on gate detection. The latter is performed with a neural model running on an OAK-D at an operation frequency of 40 Hz, enabling the drone to fly at a speed of 2 m/s. We deem these initial results promising toward the development of a truly autonomous solution that will run intensive computational tasks fully on board.

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Application of UAV in Search and Rescue Actions in Underground Mine—A Specific Sound Detection in Noisy Acoustic Signal

Cited by 52 publications

References 46 publications

Development of a Hydraulic System for the Automatic Expansion of Powered Roof Support

Development of a Hydraulic System for the Automatic Expansion of Powered Roof Support

Estimation of Azimuth and Elevation for Multiple Acoustic Sources Using Tetrahedral Microphone Arrays and Convolutional Neural Networks

Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera

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