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相关概念视频

State Space Representation01:27

State Space Representation

162
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
162
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

62
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
62
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

364
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
364
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

85
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
85

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相关实验视频

Updated: Jun 4, 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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结构在线损坏识别和动态可靠性预测方法基于无气味卡尔曼波器.

Yan Zhang1, Yongbo Zhang1,2, Jinhui Yu1

  • 1School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.

Sensors (Basel, Switzerland)
|December 17, 2024
PubMed
概括

这项研究引入了一种新的结构健康监测方法,使用无臭卡尔曼波器 (UKF) 实时识别损坏并预测系统可靠性.

关键词:
没有香味的卡尔曼过器动态可靠性预测预测.性能退化过程中的性能退化过程.结构损坏的识别和识别

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科学领域:

  • 结构工程 结构工程
  • 可靠性工程可靠性工程
  • 信号处理 信号处理

背景情况:

  • 传感器技术的进步使得结构性在线监控成为可能.
  • 在实时损坏诊断和动态可靠性预测方面仍然存在挑战.

研究的目的:

  • 开发一种在线结构损坏识别方法.
  • 为结构实现准确的实时动态可靠性预测.

主要方法:

  • 使用无气味卡尔曼波器 (UKF) 来识别结构损坏.
  • 使用预期最大化 (EM) 算法进行性能模型参数估计.
  • 实现了动态可靠性预测的条件概率.

主要成果:

  • 拟议的方法准确地识别了在运行过程中结构损坏的状态.
  • 实现精确,实时和动态可靠性预测.
  • 在具有随机效应的维纳降解过程中证明有效性.

结论:

  • 基于UKF的方法增强了结构性健康管理.
  • 为评估结构完整性和预测未来性能提供可靠的工具.