Three-Dimensional Position Sensing System using Magnetic Sensor
| Project/Area Number |
06452232
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
電子デバイス・機器工学
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| Research Institution | Himeji Institute of Technology |
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Principal Investigator |
MAEDA Muneo Himeji Institute of Technology, Department of Electronics, Professor, 工学部, 教授 (90106493)
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| Co-Investigator(Kenkyū-buntansha) |
MAENAKA Kazusuke Himeji Institute of Technology, Department of Electronics, Associate Professor, 工学部, 助教授 (70173721)
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| Project Period (FY) |
1994 – 1995
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| Project Status |
Completed (Fiscal Year 1995)
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| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥5,200,000)
Fiscal Year 1995: ¥2,000,000 (Direct Cost: ¥2,000,000)
Fiscal Year 1994: ¥3,200,000 (Direct Cost: ¥3,200,000)
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| Keywords | Position sensing / Multi-dimensional sensor / Magnetic sensor / Neural network |
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| Research Abstract |
Two-and Three-dimensional position/movement detection system using a multi-dimensional magnetic sensor and a neural network was realized.
First, position and movement detection for parallel moving object and bending arms in a plane was achieved. As a magnetic source, permanent magnet was used for obtaining the static magnetic field and a coil was used for the alternating magnetic field. The two-dimensional semiconductor Hall cell was used for detection of the static magnetic field and the two-dimensional coil was used for the alternating magnetic field. As a signal processing part, an analog neural network was used. In the experiments, the detection error of less than 5% was achieved for area of around 100 mm square. Also, the optimization of the structure of the network was studied.
Next, based on the two-dimensional results, the system was expanded to three-dimensional. The neural network was optimized in order to directly treat the three analog signals. As a result, three-dimensional position detection was achieved with the error of less than 5%. The detection with signal processing takes several tens milliseconds and it can be used for real time processing.
In this research, we found that the analog neural network, especially three-inputs network, is practically useful for such applications, whereas the limitation of the application of neural networks is not clear until now. From the result that the performance of the detection is not depend on the shape and spatial resolution of the magnetic source and detector, this system opens the novel application of the movement control of the micro-machines, etc.
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Report
(3 results)
Research Products
(12 results)
