Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

480
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
480
Time and frequency -Domain Interpretation of Phase-lag Control01:21

Time and frequency -Domain Interpretation of Phase-lag Control

424
Phase-lag controllers are widely used in control systems to improve stability and reduce steady-state errors. A dimmer switch controlling the brightness of a light bulb serves as a practical example of phase-lag control, gradually adjusting the bulb's brightness. Mathematically, phase-lag control or low-pass filtering is represented when the factor 'a' is less than 1.
Phase-lag controllers do not place a pole at zero, but instead influence the steady-state error by amplifying any...
424
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

757
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...
757
Load-frequency control01:28

Load-frequency control

682
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
682
Phase-lead and Phase-lag Controllers01:22

Phase-lead and Phase-lag Controllers

585
Understanding the working function of different types of controllers can be illustrated with practical analogies, such as adjusting a stereo's volume equalizer. Cranking up the bass involves a phase-lead controller, which functions as a high-pass filter, while increasing the treble uses a phase-lag controller, which acts as a low-pass filter. PD controllers, similar to high-pass filters, enhance the system's response to high-frequency components. PI controllers, akin to low-pass...
585
Frequency-Domain Interpretation of PD Control01:24

Frequency-Domain Interpretation of PD Control

394
Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...
394

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Ecological Porous Concrete: A Review of Multi-Scale Pore Structure Engineering for Coupled Mechanical and Ecological Performance.

Materials (Basel, Switzerland)·2026
Same author

Spatial transcriptomics reveals coordinated ventricular patterning and maturation in the developing human heart.

Nature communications·2026
Same author

Corrigendum to "Development and Validation of a Risk Prediction Model for Postoperative Pulmonary Infection in Renal Transplant Patients" Transplantation Proceedings, 58(2026), 511-519.

Transplantation proceedings·2026
Same author

Bacterial domain fusion drives biomineralization innovation in <i>Colepidae</i> ciliates.

mBio·2026
Same author

CardioNVT: an AI platform for immunostaining-free, high-throughput cardiomyocyte ploidy assessment in situ.

Science bulletin·2026
Same author

Proteomic stratification reveals immune metabolic heterogeneity in lung adenocarcinoma.

Discover oncology·2026

Related Experiment Video

Updated: Feb 15, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.7K

Measurement and control from frequency to phase based on virtual signal reconstruction.

Zhiqi Li1, Wei Zhou1, Jingbiao Chen2

  • 1School of Electro-Mechanical Engineering, Xidian University, Xi'an 710071, China.

The Review of Scientific Instruments
|February 3, 2018
PubMed
Summary

This study introduces a novel virtual reconstruction method for precise phase comparison between signals of different frequencies. The technique achieves an exceptional comparison precision of 10-17/day without frequency transformation.

More Related Videos

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

2.3K
The Frequency Domain Thermoreflectance Technique for Thermal Property Measurements
09:10

The Frequency Domain Thermoreflectance Technique for Thermal Property Measurements

Published on: December 5, 2025

833

Related Experiment Videos

Last Updated: Feb 15, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.7K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

2.3K
The Frequency Domain Thermoreflectance Technique for Thermal Property Measurements
09:10

The Frequency Domain Thermoreflectance Technique for Thermal Property Measurements

Published on: December 5, 2025

833

Area of Science:

  • Metrology
  • Signal Processing
  • Virtual Reconstruction

Background:

  • Accurate phase comparison is crucial for high-precision frequency measurements.
  • Existing methods often require frequency transformation, introducing potential errors.
  • Directly processing phase differences between signals of different nominal frequencies presents a significant challenge.

Purpose of the Study:

  • To propose a virtual reconstruction method for direct phase information capture between different nominal frequency signals.
  • To achieve high-precision phase comparison without frequency transformation.
  • To validate the method's performance and precision.

Main Methods:

  • Constructing a virtual standard frequency signal matching the measured signal's nominal frequency.
  • Implementing synchronous comparison gates covering multiple signal periods.
  • Determining phase variations within each gate for continuous phase measurement.

Main Results:

  • Successful direct processing of phase differences between signals with different nominal frequencies.
  • Achieved a comparison precision of 10-17/day.
  • Demonstrated the method's effectiveness across a wide range.

Conclusions:

  • The proposed virtual reconstruction method offers a direct and precise approach to phase comparison.
  • This technique eliminates the need for frequency transformation, enhancing measurement accuracy.
  • The demonstrated precision of 10-17/day validates its utility in advanced metrology applications.