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相关概念视频

Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

105
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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Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

68
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...
68
Reclosers and Fuses01:26

Reclosers and Fuses

77
Automatic circuit reclosers enhance the protection of distribution circuits by interrupting and auto-reclosing an AC circuit according to a preset sequence. They effectively manage temporary faults on overhead distribution lines, often caused by tree limbs or wildlife, by briefly disrupting service to improve overall reliability. However, contact with reclosers or energized broken conductors on the ground can pose serious hazards.
A comprehensive protection scheme for radial distribution...
77
Fault Types01:18

Fault Types

61
When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...
61
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

94
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...
94
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

139
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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相关实验视频

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基于云端协作深度学习的开关设备部分放电缺陷识别方法.

Zhijie Jia1, Songhai Fan2, Zhichuan Wang3

  • 1State Grid Sichuan Electric Power Research Institute, Chengdu, 610000, China. 17856626247@163.com.

Scientific reports
|March 31, 2025
PubMed
概括

本研究介绍了一种边缘计算和深度学习方法,用于切换器部分放电 (PD) 识别. 这种新的方法提高了实时监测和缺陷识别的准确性,提高了电气设备的安全性.

关键词:
深信网络是一个深信网络.边缘计算是一种边缘计算.局部线性嵌入局部线性嵌入部分核准部分核准开关设备 开关设备

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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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科学领域:

  • 电气工程 电气工程
  • 人工智能的人工智能
  • 电力系统 电力系统

背景情况:

  • 交换机的传统部分放电 (PD) 检测方法缺乏实时监测,快速评估和协作分析能力.
  • 现有的诊断模型由于训练时间长,识别效率低,协作分析薄弱而受到影响.
  • 需要先进的方法来克服在实际开关设备应用中传统PD检测的局限性.

研究的目的:

  • 提出一个共同的PD识别方法用于交换机,利用边缘计算和深度学习.
  • 开发一个边缘协作缺陷识别架构,用于增强开关设备监控.
  • 提高PD缺陷识别和切换设备实时分析的准确性和效率.

主要方法:

  • 构建了一个边缘协作缺陷识别架构,包括终端设备,集合,边缘计算和云计算侧面.
  • 使用UHF和宽带脉冲电流传感器提取PD信号,提取多维特征,并在边缘侧执行维度减小.
  • 在云端使用深度信念网络 (DBN) 进行PD缺陷识别,实时培训和模型部署到边缘进行推断.

主要成果:

  • 拟议的DBN方法在识别开关设备中的PD时达到88.03%的准确性.
  • 边缘计算架构将开关设备PD缺陷类型分类器的训练时间减少了44.28%.
  • 该方法可在多个开关装置单元中实时联合分析PD缺陷.

结论:

  • 提出的联合PD识别方法有效地解决了传统诊断模型的局限性.
  • 边缘计算和深度学习 (DBN) 的整合提高了交换机PD检测的效率和准确性.
  • 开发的架构能够实时监控,快速评估和协作分析开关设备中的PD缺陷.