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相关概念视频

Transformers in Distribution System01:27

Transformers in Distribution System

475
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
475
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

491
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
491
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

708
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:
708
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

373
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
373
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

1.1K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.1K
Instrument Transformers01:23

Instrument Transformers

420
Instrument transformers, comprising voltage transformers (VTs) and current transformers (CTs), play crucial roles in power substations by providing isolated replicas of current or voltage for measurement and protection purposes. Voltage transformers reduce the primary voltage to levels suitable for relay operation and measurement, while current transformers scale down the primary current. The primary winding of a current transformer often consists of a single turn, achieved by threading the...
420

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相关实验视频

莫肯:基于多尺度变压器的Gating KAN专家网络用于时间序列预测.

Donghyun Kim1, Jimyung Kang2, Hoseong Hwang1

  • 1Department of Medical Artificial Intelligent, Eul-Ji University, Seongnam-si 13135, Republic of Korea.

Sensors (Basel, Switzerland)
|December 11, 2025
PubMed
概括

一个新的基于专家混合的科尔摩戈罗夫-阿诺德网络 (MoEKAN) 模型准确地预测负载自动切换器 (OLTC) 振动信号. 这种先进的诊断工具改善了电力变压器的状态监测和预测性维护.

关键词:
科尔摩戈罗夫阿诺尔德网络在OLTC上,OLTC是指OLTC.专家的混合-专家的混合.时间序列预测时间序列预测

相关实验视频

科学领域:

  • 电气工程 电气工程
  • 人工智能的人工智能
  • 信号处理 信号处理

背景情况:

  • 装载式水龙头变换器 (OLTC) 是电力变压器的重要组件.
  • 来自OLTC的振动信号提供了对设备健康状况和潜在故障的见解.
  • 准确预测这些信号对于预测性维护至关重要.

研究的目的:

  • 引入一种新的MoEKAN模型,用于OLTC振动信号的增强时间序列预测.
  • 提高OLTC状态监测的准确性和可靠性.

主要方法:

  • 开发了一个基于专家混合的科尔摩戈罗夫-阿诺德网络 (MoEKAN) 模型.
  • 集成的可逆实例规范化 (RevIN) 为数据分布适应性.
  • 采用基于变压器的门锁机制,用于动态专家集成.
  • 利用多级信号处理来捕获复杂的信号模式.

主要成果:

  • 摩肯模型在实际的OLTC运营数据上表现出优异的预测性能.
  • 实现了较低的预测错误:MSE为133.4579,MAE为7.2801和MAPE为4.4272. 这些都是低预测错误.
  • 在准确性方面表现优于所有基准比较模型.

结论:

  • 莫肯模型是OLTC振动信号预测的实用和有效工具.
  • 证实了该模型对OLTC可靠状态监测和预测性维护的潜力.
  • 突出了先进的人工智能模型在电力系统诊断中的重要性.