Journal Published Online: 15 February 2021
Volume 44, Issue 3

Classification and Recognition Model of Water Saturation Level of Rock Based on Near-Infrared Spectroscopy

CODEN: GTJODJ

Abstract

In geotechnical engineering, the water saturation of rock cannot be obtained in real time and is lossless. To solve this problem, a continuous classification representation method of water saturation of rock is proposed herein, the classification and recognition theory of the water saturation level of rock is established, and near-infrared spectrum acquisition experiments of rock under different water saturation levels are carried out. Based on the near-infrared spectrum, the partial least square (PLS) method is used to establish the recognition model, and the model is applied to the real-time identification of the saturation level in the gravel water absorption process. The results are as follows: (1) In this paper, the method of hierarchical representation of water saturation of rock is proposed, which solves the limited extrapolation ability and extrapolation precision problems of the preparation accuracy of water saturation of the rock sample and the classification-learning algorithm and thus provides the completeness and feasibility for the identification of water saturation of rock. (2) The classification recognition theory and method based on near-infrared spectroscopy to set up the water saturation level of rock have better recognition precision and can realize the water saturation level of the rock in real time and nondestructively, and (3) when the PLS method is used to establish the recognition model, the appropriate threshold parameters are selected to eliminate the abnormal samples, and multiple spectral segments are used in the modeling, which can greatly improve the recognition accuracy of the model.

Author Information

Zhang, Fang
State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing, China School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing, China
Zhang, Xiulian
School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing, China State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing, China
Hu, Chen
School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing, China State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing, China
Li, Yingjun
School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing, China State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing, China
Wang, Zhenwei
Mine Safety Technology Branch of China Coal Research Institute, Beijing, China State Key Laboratory of Coal Mining and Clean Utilization (China Coal Research Institute), Beijing, China
Tao, Zhigang
School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing, China State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing, China
He, Manchao
School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing), Beijing, China State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing, China
Pages: 20
Price: $25.00
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Details
Stock #: GTJ20190413
ISSN: 0149-6115
DOI: 10.1520/GTJ20190413