Research on appliance event detection method based on intelligent perception technology

Ziyuan YANG; Xiaobin XU; Xin LI; Yimeng ZHAO

doi:10.11959/j.issn.2096-3750.2019.00138

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Research on appliance event detection method based on intelligent perception technology

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- Research on appliance event detection method based on intelligent perception technology
- Chinese Journal on Internet of Things Vol. 3, Issue 4, Pages: 109-115(2019)
- 作者机构：
  
  1. 内蒙古电力（集团）有限责任公司包头供电局，内蒙古包头 014030
  2. 内蒙古电力（集团）有限责任公司，内蒙古呼和浩特 010010
  3. 上海极熵数据科技有限公司，上海 201199
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2019.00138
  CLC： TP399
- Published：30 December 2019，
  
  Published Online：2019-09，
- 稿件说明：
移动端阅览
ZIYUAN YANG, XIAOBIN XU, XIN LI, et al. Research on appliance event detection method based on intelligent perception technology. [J]. Chinese journal on internet of things, 2019, 3(4): 109-115.
DOI：

ZIYUAN YANG, XIAOBIN XU, XIN LI, et al. Research on appliance event detection method based on intelligent perception technology. [J]. Chinese journal on internet of things, 2019, 3(4): 109-115. DOI： 10.11959/j.issn.2096-3750.2019.00138.

摘要

物联网和智能化技术的高速发展为用电负荷智能感知技术提供了系统支撑，也为用电行为识别提供了数据基础。为了实现对设备启停事件的精准识别，提出了利用高频率、高精度电能数据结合动态时间规整（DTW）算法的技术方案，并搭建了基于自主研发硬件的实验测试平台。实验结果表明，该用电事件识别算法具有较高的识别精确率和召回率，可以被应用于更多场景中，以实现用电负荷的全面感知。

Abstract

The rapid development of Internet of things and intelligent technologies provides the system support for intelligent load perception technology of power usage

as well as provides analytical data for power user behavior.In order to realize the accurate identification of equipment start or stop events

a technical proposal which combined the high frequency and high precision power data with the dynamic time consolidation (DTW) algorithm was proposed

and an experimental testing platform based on the independent hardware was built.The experimental results show that the power incident identification algorithm has a high identification accuracy and recall rate

which can be applied in more scenarios to realize the full perception of power load.

关键词

物联网智能感知非侵入式测量动态时间规整

Keywords

Internet of thingsintelligent perceptionnon-intrusive load monitoring (NILM)dynamic time warping (DTW)

references

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YANG T, ZHAI F, ZHAO Y J ,et al. Ubiquitous power Internet of things interpretation and research prospects[J]. Automation of Electric Power Systems, 2019,43(13): 9-20.

程祥, 李林芝, 吴浩 ,等. 非侵入式负荷监测与分解研究综述[J]. 电网技术, 2016,41(10): 3108-3117.

CHENG X, LI L Z, WU H ,et al. Review of research on non-invasive load monitoring and decomposition[J]. Power System Technology, 2016,41(10): 3108-3117.

TSAI M, LIN Y . Modern development of an adaptive non-intrusive appliance load monitoring system in electricity energy conservation[J]. Applied Energy, 2012,96: 55-73.

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KELLY J, KNOTTENBELT W . Neural NILM:deep neural networks applied to energy disaggregation[C]// Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. ACM, 2015: 55-64.

SAKOE H, CHIBA S . Dynamic programming algorithm optimization for spoken word recognition[J]. IEEE Transaction Acoust Speech Signal Process, 1978,26(1): 43-49.

BERNDT D J, CLIFFOD J . Using dynamic time warping to nd patterns in time series[C]// KDD Workshop, 1994, 10(16): 359-370.

SALVADOR S, CHAN P . FastDTW:toward accurate dynamic time warping in linear time and space[C]// KDD Workshop. 2004: 70-80.

ZHAO J, ITTI L . ShapeDTW:shape dynamic time warping[J]. Pattern Recognition, 2018,74: 171-184.

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