Retrieving 3D Large Gradient Deformation Induced to Mining Subsidence Based on Fusion of Boltzmann Prediction Model and Single-Track InSAR Earth Observation Technology

Jiang, Chuang; Wang, Lei; Yu, Xuexiang

doi:10.1109/access.2021.3089160

Cited by 12 publications

(10 citation statements)

References 20 publications

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“…Based on a substantial amount of measured data [21,[41][42][43][44][45], it was evident that during a complete subsidence process, a ground point typically undergoes three phases as depicted in Figure 1.…”

Section: Mining Subsidence Dynamic Process Analysismentioning

confidence: 99%

Application of a Variable Weight Time Function Combined Model in Surface Subsidence Prediction in Goaf Area: A Case Study in China

Chai,

Xu,

et al. 2024

Applied Sciences

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To attain precise forecasts of surface displacements and deformations in goaf areas (a void or cavity that remains underground after the extraction of mineral resources) following coal extraction, this study based on the limitations of individual time function models, conducted a thorough analysis of how the parameters of the model impact subsidence curves. Parameter estimation was conducted using the trust-region reflective algorithm (TRF), and the time function models were identified. Then we utilized a combined model approach and introduced the sliding window mechanism to assign variable weights to the model. Based on this, the combined model was used for prediction, followed by the application of this composite prediction to engineering scenarios for the dynamic forecasting of surface movements and deformations. The results indicated that, in comparison with DE, GA, PSO algorithms, the TRF exhibited superior stability and convergence. The parameter models obtained using this method demonstrated a higher level of predictive accuracy. Moreover, the predictive precision of the variable-weight time function combined model surpassed that of corresponding individual time function models. When employing six different variable-weight combination prediction models for point C22, the Weibull-MMF model demonstrated the most favorable fitting performance, featuring a root mean square error (RMSE) of 32.98 mm, a mean absolute error (MAE) of 25.66 mm, a mean absolute percentage error (MAPE) of 7.67%; the correlation coefficient R2 reached 0.99937. These metrics consistently outperformed their respective individual time function models. Additionally, in the validation process of the combined model at point C16, the residuals were notably smaller than those of individual models. This reaffirmed the accuracy and reliability of the proposed variable-weight combined model. Given that the variable-weight combination model was an evolution from individual time function models, its applicability extends to a broader range, offering valuable guidance for the dynamic prediction of surface movement and deformation in mining areas.

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Section: Mining Subsidence Dynamic Process Analysismentioning

confidence: 99%

Application of a Variable Weight Time Function Combined Model in Surface Subsidence Prediction in Goaf Area: A Case Study in China

Chai,

Xu,

et al. 2024

Applied Sciences

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“…When the surface deformation occurs, two or more interferometric measurements are made by the SAR system for various periods in the same area to obtain the surface deformation, and this technique is called the D-InSAR technology [36]. The problems of temporal decoherence, DEM error, orbital error, atmospheric delay, and deconvolution error faced by D-InSAR results limit its further application.…”

Section: A Differential Interferogramsmentioning

confidence: 99%

Monitoring and Assessment of SBAS-InSAR Deformation for Sustainable Development of Closed Mining Areas—a Case of Nanzhuang Mining Area

Li¹,

Tian²,

Wang³

et al. 2023

IEEE Access

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Closed mining areas are an important potential resource, and rational use of them are critical to implementing sustainable development strategies. To guide the more reasonable development and utilization of the closed mining areas, we proposed a method of surface deformation monitoring and subsidence risk assessment of the closed mining areas with SBAS-InSAR technology. Based on the analysis of deformation, a risk assessment model integrating subsidence hazard and subsidence vulnerability was proposed. Subsidence hazard include accumulate deformation and the subsidence rate of the last year. The tunnels and the land use types are used to assess the subsidence vulnerability. This method can achieve deformation monitoring and risk assessment of the closed mining areas, and the proposed method is validated by taking the Nanzhuang mining areas as an example. The results showed that the main subsidence areas in the closed mining areas are located in the tunnel in the southwest and the gangue pile area in the northeast of the mining areas, while the deformation in the vegetation-rich forested area is low. The area of low, medium and high subsidence risk zones is 65.5%, 27.8% and 6.7% respectively.

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“…For the noise points of type (2), only the distance slope filter could remove them (black circle). In engineering applications, owing to the complex environment in the mining area, it is difficult to avoid the emergence of noise points of type (2). Therefore, the distance slope filter greatly improved the applicability of the automatic extraction.…”

Section: A Advantages Of Distance Slope Filtermentioning

confidence: 99%

Automatic Deformation Extraction Method of Buildings in Mining Areas Based on TLS Point Clouds

Wang

Jiang

et al. 2022

IEEE Access

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Presently, the deformation extraction of buildings in mining areas using terrestrial laser scanner (TLS) point clouds is performed manually. Automatic deformation extraction holds great significance for building deformation monitoring in mining areas. Therefore, this study proposes an automatic extraction method for building deformation in mining areas using TLS point clouds. The corner points of doors and windows on the wall are considered as key points and the wall deformation in the mining area is extracted with minimal manual intervention. First, the input data were preprocessed, including 2D boundary point cloud acquisition and denoising (using a distance slope filter). Next, the key points were extracted via three steps: boundary line splitting, seed key point clustering, and key point judgment. Finally, the 3D coordinates of the key points and the relationship between the key points of the two phases were established to calculate the deformation value. The results confirmed negligible difference between the deformation value extracted using this method and the real value. Most of the errors were between −5 and 5 mm, and only a few exceeded ±5 mm; however, no error exceeded ±9 mm. The deformation value obtained using this method was almost identical to that obtained using the manual method, and the absolute error between them was below 8 mm. The performance verification of this method showed that the proposed distance slope filter removed the noise points more effectively compared to that of the traditional denoising filters, i.e., statistical and radius filters, establishing its suitability for the complex measurement environment of mining areas. During the automatic extraction of key point coordinates, the root mean square error (RMSE) values were below 2.0 mm; RMSE values during manual extraction were below 7.1 mm. The proposed method demonstrated greater stability than that of the manual extraction method.INDEX TERMS Deformation monitoring, mining damage assessment, point cloud, terrestrial laser scanner (TLS).

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Retrieving 3D Large Gradient Deformation Induced to Mining Subsidence Based on Fusion of Boltzmann Prediction Model and Single-Track InSAR Earth Observation Technology

Cited by 12 publications

References 20 publications

Application of a Variable Weight Time Function Combined Model in Surface Subsidence Prediction in Goaf Area: A Case Study in China

Application of a Variable Weight Time Function Combined Model in Surface Subsidence Prediction in Goaf Area: A Case Study in China

Monitoring and Assessment of SBAS-InSAR Deformation for Sustainable Development of Closed Mining Areas—a Case of Nanzhuang Mining Area

Automatic Deformation Extraction Method of Buildings in Mining Areas Based on TLS Point Clouds

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