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相关概念视频

Wind Turbine Machine Models01:24

Wind Turbine Machine Models

102
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
102
Design Example: Calculating Safe Diameter for Wind-Exposed Disc01:17

Design Example: Calculating Safe Diameter for Wind-Exposed Disc

41
Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
41
Mechanical Efficiency of Real Machines01:14

Mechanical Efficiency of Real Machines

635
The mechanical efficiency of a machine is a fundamental concept that describes how effectively a machine can convert input work into output work. According to this concept, the efficiency of a machine is equal to the ratio of the output work to the input work. An ideal machine, meaning a machine that has no energy losses, has an efficiency of one. This implies that the input work and the output work are equal.
However, in reality, no machine can be truly ideal, and all of them experience some...
635
Turbine-Governor Control01:17

Turbine-Governor Control

161
Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...
161
Three-Winding Transformers01:19

Three-Winding Transformers

193
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
193
Energy Losses in Transformers01:21

Energy Losses in Transformers

828
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
828

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相关实验视频

Updated: Jun 5, 2025

Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

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基于深度学习的风力轮机预测性维护的RUL预测.

Syed Shazaib Shah1, Tan Daoliang1, Sah Chandan Kumar2

  • 1School of Energy and Power, Beihang University, Beijing, 100191, PR China.

Heliyon
|December 16, 2024
PubMed
概括
此摘要是机器生成的。

风力轮机的预测性维护 (PdM) 通过新的深度学习方法得到了改进. 这种方法准确地预测了剩余的使用寿命 (RUL),使远程操作能够及时维护.

关键词:
注意力机制注意力机制深度学习是一种深度学习.预测性维护是指预测性维护.剩余的使用寿命.风力轮机的风力轮机

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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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Last Updated: Jun 5, 2025

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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:

  • 工程 工程师 工程师 工程师
  • 计算机科学 计算机科学
  • 可再生能源可再生能源是可再生能源.

背景情况:

  • 风电场的运营和维护 (O&M) 成本是显著的.
  • 目前的预测性维护 (PdM) 方法与风电场的远程性质相斗争,限制了实际应用.
  • 准确的剩余使用寿命 (RUL) 预测对于有效的维护计划至关重要.

研究的目的:

  • 引入一种新的深度学习 (DL) 方法来准确预测风力轮机中的RUL.
  • 解决目前PdM方法在偏远风电场环境中的局限性.
  • 通过提供可靠的提前维护窗口来实现PdM的实际实施.

主要方法:

  • 开发了一种基于注意力的多参数深度学习方法,绕过了传统的特征工程.
  • 提出了两个模型:用于RUL预测的ForeNet-2d和ForeNet-3d.
  • 对七种风力轮机故障类型的预测RUL的模型进行了验证.

主要成果:

  • 实现了RUL的2周预报窗口.
  • 证明了高准确度,最精确的预测偏离实际RUL只有10分钟.
  • 最不准确的预测偏离了1.8天,大多数预测是在实际RUL的几个小时内进行的.

结论:

  • 拟议的DL方法大大提高了风电场PdM的可靠性和实用性.
  • 准确的RUL预测为维护提供了大量的时间框架,这对于远程风力轮机访问至关重要.
  • 这种方法通过自动化特征提取来最大限度地减少人为错误,为高效的风电场O&M铺平了道路.