1988 Fiscal Year Final Research Report Summary
Automatic Measuring Process by Multi-level-sensing System using Optical Fibers and Artificial Intelligence
| Project/Area Number |
62550087
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
機械工作
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| Research Institution | Chiba University |
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Principal Investigator |
SAITO Yoshio Chiba University, Associate Professor, 工学部, 助教授 (00108218)
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| Project Period (FY) |
1987 – 1988
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| Keywords | Optical Fibers / Multi-level-sensing System / Inspection / Automatic Measuring Process / 人工知能 |
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| Research Abstract |
The aim of this project is to develop the automatic measuring process by multi-level-sensing system using optical fibers and artificial intelligence. The performance of the sensor with several couple of optical fibers were inves-tigated in relation to the measuring accuracy and the position of fiber. The accuracy of this measuring system was simulated considering the location of fibers and the multi-level-sensing system were carried out to alter the measur-ing accuracy in order to shorten the measuring time. As a result the following conclusions can be drawn.
1. Analyzing a fundamental characteristics of optical fiber sensor, the measur-ing system with several couple of fibers is superior to that with single couple. Comparing the results, the accuracy maninly depends on the location error of attached fibers and the reflection factor of object to be measureed.
2. Examining the performance of the multi-level sensing system using the coordi-nate measuring machine, the sensor propose here has enough sensitivity and is available to rough measuring process.
3. To develop the practical application technique the automatic process planning was carried out with coordinate measuring machine which is controlled by CNC. From the results, it needs to discuss that how to separate the distance and sur-face quality in measured data.
4. The sufficient agreement between the simulation and the practical process was obtained by calculating the several properties from the data. It is important to apply an aritificial intelligence to the decision process for measuring path.
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