China Institute of Water Resources and Hydropower Research

Peking Remote Sensing Wisdom Technology Co., Ltd.

Jing Qin

Tianjie Lei

Xiangyu Li

Geng Sun

Mingming Zhu

Lingyun Zhao

Jiabao Wang

Li Feng Zhang

Li Ni Zhang

Qian Wang

Weiwei Wang

Lu Wang

Huaidong Zhao

Yanhong Wang

Yazhen Zhang

Haoyu Yang

Xiaomin Guo

Ruihu Yao

Wenlong Niu

The present invention provides a prediction method and system of high slope deformation. First, historical deformation data of each period of each part of a high slope is obtained as sample data; the sample data is divided into training samples and test samples; then a parameter group of a Support Vector Machine (SVM) model is optimized by using the training samples and a particle Swarm Optimization (PSO) algorithm to determine an optimal parameter group of the SVM model, to obtain a trained SVM model; whether the trained SVM model satisfies a condition is verified by using the test samples, and when the SVM model does not satisfy the condition, an optimal parameter group of the SVM model is re-determined; and finally the deformation of each area of the high slope is predicted by using the SVM model that satisfies the condition.

Prediction method and system of high slope deformation

A dam slope deformation monitoring system and method are provided. The monitoring system monitors an entire dam in a reservoir area by using an unmanned aerial vehicle (UAV) photogrammetry system, and determines an encrypted monitoring area (steep slope) with the relatively large deformation and a relatively large digital elevation difference; determines, in the intensive monitoring area, a first level key monitoring area with the larger deformation by using a ground-based radar interferometry measurement system; determines, in the first level key monitoring area, a second level key monitoring area with the larger deformation by using a ground-based three-dimensional lidar measurement system; determines, in the second level key monitoring area, a key monitoring particle with a high deformation speed by using a global navigation satellite system (GNSS). The core chip stack is used to monitor and warn the collapse process in the area where the key monitoring particles are located.

Dam slope deformation monitoring system and method

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Beijing, China

Jing Qin