| Project/Area Number |
09555315
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
資源開発工学
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| Research Institution | Muroran Institute of Technology |
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Principal Investigator |
ITAKURA Ken-ichi Muroran Institute of Technology, Department of Computer Science and Systems Engineering, Associate Professor, 工学部, 助教授 (20168298)
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| Co-Investigator(Kenkyū-buntansha) |
SATO Kazuhiko Muroran Institute of Technology, Department of Computer Science and Systems Engineering, Professor, 工学部, 教授 (30002009)
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| Project Period (FY) |
1997 – 1999
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| Project Status |
Completed (Fiscal Year 1999)
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| Budget Amount *help |
¥13,000,000 (Direct Cost: ¥13,000,000)
Fiscal Year 1999: ¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1998: ¥2,400,000 (Direct Cost: ¥2,400,000)
Fiscal Year 1997: ¥8,400,000 (Direct Cost: ¥8,400,000)
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| Keywords | Drilling / Drilling Machine / AE / Acoustic Emission / Mechanical Data / Log / Logging / Visualization |
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| Research Abstract |
In underground construction, it is important to obtain rock structure information, including distribution of discontinuities, before excavation and support setting. Mechanical data (torque and thrust) and AE (acoustic emission) detected at the drill bit position can be useful for understanding underground structure along with stroke and revolution data monitored at the drilling machine site. Therefore, laboratory experiments were performed to develop hardware and software systems to visualize the rock mass interior.
The following results were obtained through experimentation :
1. Laboratory drilling experiments showed that AE variation, torque, and thrust detected at the bit position reflected rock type differences and located discontinuities.
2. Both signal transmission methods using optical transceiver and FM wave were able to transmit signals from the bit position to the drilling machine site through drilling rods.
3. Also, another data logging system using IC memory arranged behind the bit position was developed ; drilling experiments confirmed effectiveness of this system.
4. A data analysis system using neural network techniques was also developed for objective interpretation of logged data and display of logged strata and discontinuities.
The system developed in this project could successfully detect AE, torque, and thrust at the drill bit position in laboratory experiments. These data could more directly reflect information about rock drilling than conventional methods. In particular, it was found that this data logging method using IC memory should be a useful inclusion in any future drilling system if its manufactured electric circuit were small, waterproof, and shockproof.
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