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相关概念视频

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

59
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,...
59
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

153
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
153
Second Order systems II01:18

Second Order systems II

73
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
73
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

80
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....
80
Typical Model Studies01:30

Typical Model Studies

200
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
200
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

76
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
76

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相关实验视频

Updated: May 20, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

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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和动态系统的故障重建方法使用自适应估计和优化.

Zhi-Wei Gao1, Qiang Huang1, Yuanhong Liu1

  • 1Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing, China.

ISA transactions
|March 25, 2025
PubMed
概括

本研究引入了一种使用自适应估计的复杂工业系统实时故障检测和诊断的新方法. 该技术有效地重建故障和和的输入信号,提高系统的安全性和可靠性.

科学领域:

  • 控制系统工程 控制系统工程
  • 故障诊断和故障耐受性控制
  • 系统识别和自适应控制

背景情况:

  • 现代工业系统面临着日益复杂的复杂性,要求更高的安全性和可靠性.
  • 早期故障检测和严重程度评估对于防止性能下降至关重要.

研究的目的:

  • 为和动态系统开发实时监控和故障重建技术.
  • 为应对系统异常和性能下降所带来的挑战.

主要方法:

  • 利用实时输入和输出数据进行监控和故障重建.
  • 采用自适应估计和优化技术,包括未知输入解.
  • 分隔和信号,重建超和输入和添加式故障.

主要成果:

  • 成功重建了添加式故障和超和输入信号.
  • 证明了重建和输入信号的能力,即使无法测量.
  • 验证了离线设计和实时实现,以获得卓越的性能.

结论:

  • 拟议的自适应估计方法有效地提高了和动态系统中的故障诊断.
  • 该方法为复杂的工业应用提供了安全性和可靠性的显著改进.
关键词:
飞机系统 飞机系统 飞机系统断层重建 断层重建实时数据实时数据.实时监控实时监控机器人系统 机器人系统和动态系统是和的动态系统.未知不确定性未知不确定性

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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  • 在飞机和机器人系统上被证明适用.