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相关概念视频

Energy and Power Signals01:17

Energy and Power Signals

272
In an electrical system with a resistor, voltage and current signals facilitate the measurement of power and energy across the resistor. For a continuous-time signal, the total energy over a time interval is defined as the integral of the square of the signal's magnitude over that interval. Mathematically, this is expressed as:
272
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

107
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
107
Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

78
Determining the subtransient fault current in a power system involves representing transformers by their leakage reactances, transmission lines by their equivalent series reactances, and synchronous machines as constant voltage sources behind their subtransient reactances. In this analysis, certain elements are excluded, such as winding resistances, series resistances, shunt admittances, delta-Y phase shifts, armature resistance, saturation, saliency, non-rotating impedance loads, and small...
78
Power in a Three-Phase Circuit01:15

Power in a Three-Phase Circuit

297
Three-phase systems have two configurations: the wye and delta. A star configuration can be three or four wires; in a delta configuration, the components are connected in a closed loop. Instantaneous power refers to the power value at a precise moment, and in a balanced three-phase system, it is constant. This is because the sum of the instantaneous powers in the three phases remains steady over time, despite individual fluctuations, due to the symmetry and phase relationship. The total...
297
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

180
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the...
180
Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

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Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...
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相关实验视频

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使用智能计量系统进行电力质量分析的异常检测.

Gabriele Patrizi1, Cristian Garzon Alfonso1, Leandro Calandroni1

  • 1Department of Information Engineering, University of Florence, Via di Santa Marta, 3, 50139 Florence, Italy.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
概括

本研究介绍了机器学习,用于快速检测电源质量异常,使用一个类支持向量机 (OCSVM),隔离森林 (IF) 和基于角度的异常检测 (ABOD). 这些方法有效地在线识别信号异常,改善系统可用性并降低维护成本.

关键词:
检测异常检测异常检测检测故障的检测故障检测.机器学习是机器学习.计量系统的计量系统电力质量 电力质量 电力质量

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科学领域:

  • 电气工程 电气工程
  • 计算机科学 计算机科学
  • 数据科学数据科学数据科学

背景情况:

  • 电力质量分析对于复杂的系统和大型工厂至关重要.
  • 在电压和电流信号中快速检测异常对于系统可用性和成本有效的维护至关重要.
  • 现有的方法可能缺乏在线检测所需的速度和效率.

研究的目的:

  • 实施和评估基于机器学习的异常检测算法,用于在线电源质量监测.
  • 评估一类支持向量机 (OCSVM),隔离森林 (IF) 和基于角度的异常值检测 (ABOD) 的有效性,以快速识别异常.
  • 为了证明将这些算法直接部署在传感器节点上的可行性,以实现低复杂性,高效的信号处理.

主要方法:

  • 使用的机器学习算法:一个类支持向量机 (OCSVM),隔离森林 (IF) 和基于角度的异常检测 (ABOD).
  • 应用算法用于电压和电流信号的在线聚类和异常检测.
  • 建立了用于方法评估的实验平台,使用一致的超参数和主要组件分析 (PCA) 来处理数据.

主要成果:

  • 提出的异常检测算法证明了快速有效地识别信号异常.
  • 模型实现了高性能指标,包括100%的回忆和高达92%的F1得分.
  • 计算的简单性允许在传感器节点上直接实现.

结论:

  • 机器学习算法,特别是OCSVM,IF和ABOD,是线上电源质量异常检测的有效工具.
  • 拟议的解决方案提供了一种低复杂度,高效的方法来提高系统可用性和减少维护.
  • 一旦初始算法检测到异常,可以使用进一步的分类算法进行深入调查.