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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
Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

132
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...
132
Multimachine Stability01:25

Multimachine Stability

150
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
150
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

98
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
98
Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

105
Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is...
105
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

204
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
204

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相关实验视频

Updated: Jun 14, 2025

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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基于反复二进制图和DSD-CNN的旋转机械的智能故障诊断方法

Yuxin Shi1, Hongwei Wang1, Wenlei Sun1

  • 1School of Mechanical Engineering, Xinjiang University, Urumqi 830046, China.

Entropy (Basel, Switzerland)
|August 29, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新方法,用于旋转机械故障诊断,使用复发二进制图 (RBP) 和轻量级深卷积神经网络 (DSD-CNN). 这种方法提高了准确性和效率,同时提高了对噪声的抵抗力,从而可靠地进行故障分类.

关键词:
错误诊断 错误诊断 错误诊断 是一个问题.信息是信息的.复杂性的二进制图表旋转机械机械的旋转机械

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科学领域:

  • 机械工程 机械工程
  • 信号处理 信号处理
  • 人工智能的人工智能

背景情况:

  • 传统的智能诊断算法难以利用时间序列故障信号相关性.
  • 旋转机械故障诊断在准确性和计算复杂性方面面临挑战.

研究的目的:

  • 为旋转机械提出一种新的故障诊断方法.
  • 解决传统算法的相关性特征和计算效率方面的局限性.

主要方法:

  • 一个重复二进制图 (RBP) 方法将故障振动信号转换为2D纹理图像.
  • 一个轻量级的深层可分离的扩展卷积神经网络 (DSD-CNN) 与注意模块被用于特征提取和诊断.

主要成果:

  • 拟议的模型在各种数据集上实现了卓越的诊断准确性和计算效率.
  • 与其他代表性故障诊断技术相比,该方法表现出优越的抗噪声性能.

结论:

  • RBP和DSD-CNN方法为旋转机械故障诊断提供了可靠和高效的解决方案.
  • 这种新的方法有效地提取特征信息,提高诊断性能.