Simulation and Recognition of Concrete Lining Infiltration Degree via an Indoor Experiment
Joint Authors
Feng, Jun
Wang, Yujie
Liu, Xuezeng
Wang, Dongsheng
Zhao, Xinpeng
Bai, Yeping
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-11
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
It is difficult to form a method for recognizing the degree of infiltration of a tunnel lining.
To solve this problem, we propose a recognition method by using a deep convolutional neural network.
We carry out laboratory tests, prepare cement mortar specimens with different saturation levels, simulate different degrees of infiltration of tunnel concrete linings, and establish an infrared thermal image data set with different degrees of infiltration.
Then, based on a deep learning method, the data set is trained using the Faster R-CNN+ResNet101 network, and a recognition model is established.
The experiments show that the recognition model established by the deep learning method can be used to select cement mortar specimens with different degrees of infiltration by using an accurately minimized rectangular outer frame.
This model shows that the classification recognition model for tunnel concrete lining infiltration established by the indoor experimental method has high recognition accuracy.
American Psychological Association (APA)
Wang, Dongsheng& Feng, Jun& Zhao, Xinpeng& Bai, Yeping& Wang, Yujie& Liu, Xuezeng. 2020. Simulation and Recognition of Concrete Lining Infiltration Degree via an Indoor Experiment. Geofluids،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1166121
Modern Language Association (MLA)
Wang, Dongsheng…[et al.]. Simulation and Recognition of Concrete Lining Infiltration Degree via an Indoor Experiment. Geofluids No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1166121
American Medical Association (AMA)
Wang, Dongsheng& Feng, Jun& Zhao, Xinpeng& Bai, Yeping& Wang, Yujie& Liu, Xuezeng. Simulation and Recognition of Concrete Lining Infiltration Degree via an Indoor Experiment. Geofluids. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1166121
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1166121