288
Views
2
CrossRef citations to date
0
Altmetric
Research Article

Large-gradient deformation monitoring and parameter inversion in a mining area using a method combining a dynamic prediction model and InSAR

, ORCID Icon, , &
Pages 838-847 | Received 12 Oct 2020, Accepted 09 Jun 2021, Published online: 20 Jun 2021
 

ABSTRACT

It is a challenge to map large-gradient deformation over mining areas via current InSAR (interferometric synthetic aperture radar) techniques. To this end, we present a new method that is combined with the DPM (dynamic prediction model). Our method can be divided into two parts. The core of the first part is a DPM-based simulation and removal for the large-gradient phase. The phase continuity can be restored to a great extent as the simulation has considered the delayed effect of underground mining. In this step, we can determine the DPM parameters following the rule of thumb. In the second, with LOS (line-of-sight) displacement observed from the first part, a multi-objective GA (genetic algorithm) was used to refine the DPM parameters and the subsequent deformation was predicted. Finally, we show an example of the proposed method in the case of a mine in Huaibei, China.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41971401]; Fundamental Research Funds for the Central Universities [2021YJSDC17].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 83.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.