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相关概念视频

Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

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In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
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Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

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Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
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Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

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When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
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Line Protection with Impedance Relays01:27

Line Protection with Impedance Relays

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Coordinating time-delay overcurrent relays in complex radial systems and directional overcurrent relays in multi-source transmission loops can be challenging. Impedance relays address these issues by responding to the voltage-to-current ratio, specifically measuring the apparent impedance of a line. These relays become more sensitive during faults as current increases and voltage decreases, thereby reducing the apparent impedance.
Under normal conditions, low load currents keep the measured...
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Load-frequency control01:28

Load-frequency control

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Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
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Non-Verbal Cues01:29

Non-Verbal Cues

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Non-verbal communication extends beyond gestures and facial expressions to include vocal elements known as paralanguage. Paralanguage consists of non-verbal vocal cues such as pitch, loudness, speech rate, pauses, and non-verbal vocalizations like laughter, sighs, and moans. These elements not only accompany speech but also provide critical emotional and contextual information.The Role of Paralanguage in CommunicationParalanguage adds depth to spoken language by conveying emotions and...
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相关实验视频

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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

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基于可调节的语网络的非侵入性负载识别.

Lingxia Lu1, Ju-Song Kang1, Fanju Meng1

  • 1College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
概括

这项研究引入了一个罗网络,用于非侵入性负载监控 (NILM),以识别未知的设备. 该方法允许实时重新训练,显著提高了智能电网中以前未见过的负载的准确性.

科学领域:

  • 电气工程 电气工程
  • 人工智能的人工智能
  • 智能电网技术 智能电网技术

背景情况:

  • 非侵入性负载监控 (NILM) 对智能电网和能源管理至关重要,它可以通过单点测量来识别负载.
  • 目前的NILM方法擅长识别预训练负载,但难以扩展性和识别未知的设备.
  • 未知负载识别的挑战限制了NILM系统的广泛采用和有效性.

研究的目的:

  • 开发一种新的NILM方法,能够识别未知的电荷.
  • 提高NILM系统的可扩展性和实时适应性.
  • 为了提高以前未遇到的设备的负载识别的准确性.

主要方法:

  • 提出了一个语网络架构,将一个固定的卷积神经网络 (CNN) 与两个可回调的回向传播 (BP) 网络相结合.
  • CNN从检测到的未知负载的电压-电流 (V-I) 轨迹中提取低维特征.
  • 对BP网络的在线再培训实时调整模型,增强其对准确识别的表示能力.

主要成果:

  • 拟议的罗网络在识别未知的负载方面取得了很高的准确性.
  • 在WHITED和PLAID数据集上的验证证明了该方法的有效性.
  • 实体环境测试证实了嵌入式Linux系统 (STM32MP1) 上的实用性和可扩展性.
关键词:
西安人的网络网络.在V-I轨道上.在嵌入式Linux系统中.非侵入性的负载监控.

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结论:

  • 基于罗网络的NILM方法为识别未知负载提供了一个可扩展的解决方案.
  • 在线再培训能力允许NILM系统的持续改进和适应.
  • 这种方法在现实世界的智能电网应用和能源管理中被证明是有效的.