Development of signal learning method by wavelet packet transform and application in identification of working appliances by their current waveform

2016 Fiscal Year Final Research Report

• Project/Area Number: 25330221
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Perceptual information processing
• Research Institution: Yuge National College of Maritime Technology
• Principal Investigator: KUZUME KOICHI 弓削商船高等専門学校, その他部局等, 教授 (80225151)
• Project Period (FY): 2013-04-01 – 2017-03-31
• 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

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.

Free Research Field

ディジタル信号処理