Multi-frequency ultrasonic underground cavity scanning detection technology in borehole

Wang, Jinchao; Wang, Chuanying; Han, Zhengsheng

doi:10.1016/j.measurement.2020.107889

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…In this paper, the model HC-SR04 ultrasonic module [5] is selected to achieve obstacle avoidance function. The ultrasonic transmitting circuit is shown in Figure 3 by outputting square waves at P51 and P52 with both frequencies of 40 kHz and opposite phases.…”

Section: Ultrasonic Modulementioning

confidence: 99%

Research on surface garbage collection device based on YOLOv7

Yuan,

Chen,

et al. 2024

Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023)

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Section: Ultrasonic Modulementioning

confidence: 99%

Research on surface garbage collection device based on YOLOv7

Yuan,

Chen,

et al. 2024

Third International Conference on High Performance Computing and Communication Engineering (HPCCE 2023)

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“…Therefore, the greater the density of coal, the faster the ultrasonic velocity. The two factors have an approximately proportional relationship [19].…”

Section: Ultrasonic Velocitymentioning

confidence: 99%

“…Scholars like Shumskii et al [7][8][9] pioneered the application of ultrasonic technology to coal structure research, and obtained fruitful results on the ultrasonic features of disturbed coal, attenuation of acoustic wave in coal, and the ultrasonic estimation of coal structure and fissures. Ultrasonic testing has also been introduced to non-destructive testing [10][11][12][13][14][15], and achieved success in detecting internal damage of concrete and inspecting human organs [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Identification of Coal Structure for the Control of Heat-Induced Gas Outburst and Energy-Efficient Mining

Li¹,

Yao²,

Wen³

et al. 2020

IJHT

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Coal structure could be roughly divided into four types. Among them, the two kinds of tectonic coal face a high risk of heat-induced gas outburst, which arises from the unfavorable temperature conditions in the coal structure. However, there is not yet an efficient way to identify the type of coal structure. The adjacent types of coal structures are often misjudged. The lack of an efficient identification method hinders the prevention of heat-induced gas outburst, making it difficult to realize energy-efficient and safe mining. To solve the problem, this paper first theoretically analyzes the ultrasonic properties of different types of coals, and applies backpropagation neural network (BPNN) to build up an intelligent identification model for the type of coal structure. Specifically, the characteristic parameters of ultrasonic signal were taken as the basis for judging the type of coal structure, the identification algorithm of BPNN was adopted to accurately identify the structure type of coal, and then the heat-induced gas outburst risk of the coal was evaluated preliminarily. Experimental results show that the proposed model could accurately identify the type of coal structure, and even differentiate between adjacent types of coals. The research results provide a reference for effective prevention of heat-induced gas outburst, and realization of energy-efficient and safe mining.

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“…Measuring piles after the end of casting is comparatively difficult. Therefore, in order to improve the reliability and safety of piles, and ensure engineering quality, it is necessary to perform timely and accurate measurements on the drilled shafts before casting, and obtain their three-dimensional contour information [3,4].…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Profiling of Drilled Shafts Based on Four-Point Ultrasonic Measurement

Wang,

Han

et al. 2023

J. Phys.: Conf. Ser.

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Drilled piles are one of the most important foundation systems, and the shapes of the shafts prior to casting have a significant impact on their quality. In order to better obtain geometrical information on the shafts, this study proposes a profiling approach based on four-point ultrasonic measurement. First, data from horizontal sections are fitted using least squares to obtain sectional contour curves. Vertical contours are generated by iterative fitting to ensure the smoothness of the curves. Data-processing software is then used to merge the horizontal sectional curves and the vertical curves into a three-dimensional image that approximates the actual contours of the shaft.

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Multi-frequency ultrasonic underground cavity scanning detection technology in borehole

Cited by 9 publications

References 5 publications

Research on surface garbage collection device based on YOLOv7

Research on surface garbage collection device based on YOLOv7

Intelligent Identification of Coal Structure for the Control of Heat-Induced Gas Outburst and Energy-Efficient Mining

Three-Dimensional Profiling of Drilled Shafts Based on Four-Point Ultrasonic Measurement

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