2003 Fiscal Year Final Research Report Summary
Automatic Deterioration Monitoring System for Tunnel Wall Using Fusion Sensors on a Train
| Project/Area Number |
13650578
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
交通工学・国土計画
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| Research Institution | Ibaraki University |
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Principal Investigator |
AOSHIMA Shinichi IBARAKI Univ., College of Engineering, Associate Professor, 工学部, 助教授 (60280898)
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| Co-Investigator(Kenkyū-buntansha) |
SHIRAISHI Masatake IBARAKI Univ., College of Engineering, Professor, 工学部, 教授 (10091860)
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| Project Period (FY) |
2001 – 2003
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| Keywords | Railway / Tunnel / Concrete wall / Deterioration / Monitoring system / Sensor fusion / Crack / Evaluation function |
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| Research Abstract |
Recently, a concrete-wall falling accident at a railway tunnel often occurred. Currently, workers perform regular inspection. The inspection has problems for human error, working cost and time. So, the purpose of this research is development of automatic deterioration monitoring system for tunnel inner wall using fusion sensors on a train. We proposed a new automatic deterioration monitoring system. This system consists of fusion sensors set on a train to measure a state of a tunnel wall, a measurement control device to control efficiently the these sensors and record temporarily measured data, a data base for sensor information located on main stations, and a deterioration estimation system. The fusion sensors must measure a state of a tunnel wall at a high speed and non-contact. So, we selected a line sensor camera and laser distance sensor as fusion sensors. The data base storages the information for image and distance obtained from the fusion sensors and the deteriorate condition of the wall every day or every train. Then, the system estimates the degree of deterioration by comparing these data (image) obtained from trains, and suggests the maintenance time. In this research, we investigated a state estimation method of a crack or a difference in level by using data obtained from a line sensor camera or a laser distance sensor. Next, we investigated the relation between the train velocity and the cross-correlation coefficient of the interpolated crack Images, which is necessary for estimation of deterioration using sensors on high speed train. Then, we proposed the evaluation functions on a crack and a difference in level to diagnose tunnel wall deterioration. Some basic experiments showed validity of the proposed system and methods.
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