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相关概念视频

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
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
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...
106
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

36
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
36
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

516
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
516
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
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

128
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
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相关实验视频

Updated: Jun 23, 2025

Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions
11:22

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基于非同质马尔科夫过程的复杂系统的可靠性评估方法.

Xiaolei Pan1,2, Hongxiao Chen1,2, Ao Shen1,2

  • 1College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China.

Sensors (Basel, Switzerland)
|June 19, 2024
PubMed
概括
此摘要是机器生成的。

使用非均马尔科夫过程的新方法克服了复杂系统可靠性评估的维度诅咒. 它将系统分解为子系统,使复杂结构如反应堆保护系统 (RPS) 的准确分析成为可能.

关键词:
复杂的系统复杂的系统.这是维度的诅咒.不同质的马尔科夫过程.可靠性评估的可靠性评估

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科学领域:

  • 可靠性工程可靠性工程
  • 系统动力学系统动力学
  • 随机过程 随机过程

背景情况:

  • 马尔科夫方法是评估系统可靠性的标准,捕捉了可修复性和退化等动态行为.
  • "维度的诅咒"挑战了基于马尔科夫的复杂系统的可靠性评估,因为状态空间爆炸.
  • 现有的方法在复杂系统可靠性分析中与状态空间的指数增长作斗争.

研究的目的:

  • 为使用非均马尔科夫过程的复杂系统提出一种新的可靠性评估方法.
  • 在处理高维状态空间时解决传统马尔科夫方法的局限性.
  • 为评估复杂系统的可靠性提供准确有效的方法.

主要方法:

  • 复杂系统的分解为多层次子系统,基于系统功能的可管理状态空间.
  • 为每个子系统和整个系统开发均或非均的马尔科夫模型.
  • 一个算法将子系统不可用度曲线转换为2x2动态状态过渡概率矩阵 (STPMs),用于上级模型输入.

主要成果:

  • 拟议的方法通过将子系统可靠性数据集成到更高层次的分析中,成功地建模了复杂的系统.
  • 一个关于反应堆保护系统 (RPS) 的案例研究证明了该方法的有效性和准确性.
  • 与现有方法的比较证实了新方法在可靠性评估中的优越性.

结论:

  • 提出的基于非均马尔科夫过程的方法有效地克服了复杂系统可靠性的维度诅咒.
  • 子系统分解和STPM转换算法为分析复杂系统提供了强大的框架.
  • 该方法为复杂工程应用中的可靠性评估提供了经过验证和准确的解决方案.