Coal Flow Detection of Belt Conveyor Based on the Two-Dimensional Laser

Miao, Di; Ling, Yang; Wei, Shina

doi:10.1109/access.2023.3301768

“…As a crucial part of the underground transportation system, the health status of belt conveyors directly affects the production efficiency of coal mines [1][2][3]. However, when the belt conveyors is subjected to long-term high-intensity work, it is inevitable that the faults such as joints falling off, roller faults, * Author to whom any correspondence should be addressed.…”

Section: Introductionmentioning

confidence: 99%

Audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional network in strong noise environments

Li,

Wang,

Liang

et al. 2024

Meas. Sci. Technol.

0

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Fault diagnosis of belt conveyors is crucial for coal mine production, but audio-based fault diagnosis in underground coal mines remains challenging due to the strong noise environment. To address this problem, a method for audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional networks in a strong noise environment is proposed. Firstly, the improved beluga whale optimization is designed by introducing the non-linear balance factor and non-linear probability and combining them with the proposed cyclical shock factor to optimize the variational modal decomposition parameters to achieve noise reduction and signal reconstruction. Secondly, an improved adaptive noise reduction convolutional network is developed using an adaptive threshold activation function and an improved loss function to enhance noise robustness and fault diagnosis accuracy. Finally, the proposed method's effectiveness is evaluated in low and strong noise environments, with experimental results demonstrating superior fault diagnosis performance. In low noise environments, the fault diagnosis accuracy is 98.61%, and in strong noise environments, it is 98.96%, outperforming existing fault diagnosis methods.

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Coal flow volume detection method for conveyor belt based on TOF vision

Hou,

Qiao,

Dong

et al. 2024

Measurement

2

0

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Audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional network in strong noise environment

Li,

Wang,

Liang

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Fault diagnosis of belt conveyors is crucial for coal mine production, but audio-based fault diagnosis in underground coal mines remains challenging due to the strong noise environment. To address this problem, a method for audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional networks in a strong noise environment is proposed. Firstly, the improved beluga whale optimization is designed by introducing the non-linear balance factor and non-linear probability and combining them with the proposed cyclical shock factor to optimize the variational modal decomposition parameters to achieve noise reduction and signal reconstruction. Secondly, an improved adaptive noise reduction convolutional network is developed using an adaptive threshold activation function and an improved loss function to enhance noise robustness and fault diagnosis accuracy. Finally, the proposed method's effectiveness is evaluated in low and strong noise environments, with experimental results demonstrating superior fault diagnosis performance. In low noise environments, the fault diagnosis accuracy is 98.61%, and in strong noise environments, it is 98.96%, outperforming existing fault diagnosis methods.

show abstract

Coal Flow Detection of Belt Conveyor Based on the Two-Dimensional Laser

Cited by 4 publications

References 16 publications

Audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional network in strong noise environments

Audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional network in strong noise environments

Coal flow volume detection method for conveyor belt based on TOF vision

Audio fault diagnosis of belt conveyors based on improved variational modal decomposition and improved adaptive noise reduction convolutional network in strong noise environment

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