Intelligent monitoring and prediction of deformation of uranium tailings dam based on SBAS-InSAR and BPNN

doi:10.16265/j.cnki.issn1003-3033.2024.04.1693

Abstract

Abstract:

To improve the efficiency of monitoring work in the retirement treatment of uranium tailings ponds, an intelligent monitoring and prediction model of deformation of uranium tailings ponds was proposed based on SBAS-InSAR technology and BPNN. Firstly, SBAS-InSAR technology was used to obtain the cumulative deformation and annual deformation rate of the uranium tailings pond over the past two years. The accuracy of InSAR monitoring values was verified using seven Global Navigation Satellite System (GNSS) monitoring stations on the first dam. Then, the cumulative settlement of four dam sections, including Leigongtang dam, nanpo cross dam, Battle dam and Songlin dam, was selected and analyzed in conjunction with rainfall. Finally, the cumulative settlement data of 100 settlement points of the uranium tailings dam were randomly extracted to predict the deformation of the uranium tailings dam. The results show that from December 2020 to December 2022, the deformation rate of uranium tailings dam is between -60.06-34.94 mm/a. The overall settlement of the uranium tailings dam is in a sinking state, with a maximum cumulative settlement of -46.67 mm. The average absolute error between the predicted values of BPNN and the actual monitoring values is 0.586 mm, and the mean square error is 0.624 mm.

Key words: small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR), back propagation neural network(BPNN), uranium tailings pond, intelligent deformation monitoring, sentinel-1A

CLC Number:

ZHOU Yi, PENG Guowen, HUANG Zhao, YANG Pengfei, LIU Dandan, CHEN Xiaoli. Intelligent monitoring and prediction of deformation of uranium tailings dam based on SBAS-InSAR and BPNN[J]. China Safety Science Journal, 2024, 34(4): 145-152.

Figures/Tables 9

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GNSS站点	H	P	R
a	-14.09	-15.12	1.03
b	-16.12	-16.59	0.47
c	-8.33	-7.41	-0.92
d	-8.56	-7.15	-1.41
e	-12.84	-14.44	1.6
f	-7.46	-10.01	2.55
g	-10.76	-12.63	1.87