| Project/Area Number |
25330221
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Yuge National College of Maritime Technology |
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Principal Investigator |
KUZUME KOICHI 弓削商船高等専門学校, その他部局等, 教授 (80225151)
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| Co-Investigator(Kenkyū-buntansha) |
田房 友典 弓削商船高等専門学校, その他部局等, 教授 (20321507)
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | ウェーブレットパケット変換 / 学習 / リフティング / 稼働電気機器 / エネルギーマネージメントシステム / 消費電流波形 / 識別 / 統計量 / 信号学習法 / 分電盤 / EMS / 機械学習 / 消費電力波形 / 分電盤電流 / 評価指標 / Ｅｎｅｒｇｙ Ｍａｎａｇｅｍｅｎｔ Ｓｙｓｔｅｍ |
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| Outline of Final Research Achievements |
To realize the low carbon emission society, the importance of the renewable electric generator and power conservation is recognized. The EMS (Energy Management System) which enables to actively manage both the power demand and consumption is focused. It is required to disaggregation of individual electric appliances and to estimate the amount of power consumption. In this research, we are developing a new algorithm to estimate the working appliances by using their power current data. Firstly, we derived the theory of dyadic lifting wavelet for learning the target signal and investigated statistical property of the learning parameters. Next we applied our theory to ECG signal processing and power current data. In addition to above research, we developed the prototype of the electric power saving system by sensor network.
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