High frequency non-intrusive electric device detection and diagnosis

Roman Jonetzko, Matthias Detzler, K. Gollmer, Achim Guldner, Marcel Huber, R. Michels, Stefan Naumann
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引用次数: 5

Abstract

The number of electronic devices in households as well as in industrial workplaces is continuously growing because of progress in automation. Identifying unusual operating behavior, detecting device failures in advance, and recognizing energy saving potentials are key features to improve the reliability, safety, and profitability of those systems. Facing these tasks, todays research is focused inter alia on a non-intrusive load monitoring approach, where the electrical signal is measured at a central point with modern hardware and processed by pattern recognition algorithms. Thus, we developed a smart meter prototype with a high sampling frequency, which allows for continuous measurement of the current and voltage from three-phase power lines. Besides this, in this paper we describe the usage of current-only measurement data (simple and safe installation using current transformers) with which we were able to classify state changes of a mobile air-conditioner with the help of Fourier descriptors as well as with additional voltage measurement.
高频非侵入式电气设备检测与诊断
由于自动化的进步,家庭和工业工作场所的电子设备数量不断增长。识别异常操作行为,提前检测设备故障,识别节能潜力是提高这些系统可靠性、安全性和盈利能力的关键特征。面对这些任务,目前的研究主要集中在非侵入式负载监测方法上,其中电信号在现代硬件的中心点测量,并通过模式识别算法进行处理。因此,我们开发了一种具有高采样频率的智能电表原型,可以连续测量三相电力线的电流和电压。除此之外,在本文中,我们描述了仅电流测量数据的使用(使用电流互感器的简单和安全安装),我们能够在傅里叶描述符的帮助下对移动空调的状态变化进行分类,以及额外的电压测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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