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

Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

812
Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
812
Harmonic Mean01:09

Harmonic Mean

3.5K
The arithmetic mean is usually skewed towards the larger values in the data set. Therefore, to avoid this inherent bias towards smaller values, the harmonic mean is used.
Take the example of the speed of a car, which is the measure of the rate of distance traveled. If the vehicle traverses the same distance back-and-forth, its average speed equals the total distance traveled divided by the total time taken. However, if the car moves with varying speeds, then the arithmetic mean is more skewed...
3.5K
Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

595
Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...
595
Sinusoidal Sources01:18

Sinusoidal Sources

980
Direct current (DC) refers to an electric current that flows in a single direction, maintaining a constant polarity. This is in contrast to alternating current (AC), which periodically changes its direction and magnitude. AC forms the backbone of modern electricity transmission and distribution systems due to its efficient long-distance transmission capabilities.
In homes, the power supplies use sinusoidal sources to provide electricity. These sources generate a voltage that varies sinusoidally...
980
Superposition Theorem for AC Circuits01:13

Superposition Theorem for AC Circuits

1.6K
Consider encountering a circuit in a steady state where all its inputs are sinusoidal, yet they do not all possess the same frequency. Such a circuit is not classified as an alternating current (AC) circuit, and consequently, its currents and voltages will not exhibit sinusoidal behavior. However, this circuit can be analyzed using the principle of superposition.
The principle of superposition stipulates that the output of a linear circuit with several concurrent inputs is equivalent to the...
1.6K
Parallel RLC Circuits01:14

Parallel RLC Circuits

1.5K
Street lamps equipped with RLC surge protectors are an excellent example of applying circuit analysis in practical scenarios. These surge protectors safeguard the lamp's components against sudden voltage spikes.
A simplified parallel RLC circuit model with a DC input source generating a step response is employed in this context. When the switch is turned on, Kirchhoff's current law is applied, leading to a second-order differential equation.
1.5K

You might also read

Related Articles

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

Sort by
Same author

Enhancement of Operational Safety in Marine Cargo Cranes on a Container Ship Through the Application of Authenticated Wi-Fi Based Wireless Data Transmission from Multiple Sensors.

Sensors (Basel, Switzerland)·2024
Same author

Case-Study-Based Overview of Methods and Technical Solutions of Analog and Digital Transmission in Measurement and Control Ship Systems.

Sensors (Basel, Switzerland)·2022
Same author

Towards Safety Improvement of Measurement and Control Signals Transmission in Marine Environment.

Sensors (Basel, Switzerland)·2020
Same author

Accuracy Analysis of Measuring X-Y-Z Coordinates with Regard to the Investigation of the Tombolo Effect.

Sensors (Basel, Switzerland)·2020
Same author

New Approach to Analysis of Selected Measurement and Monitoring Systems Solutions in Ship Technology.

Sensors (Basel, Switzerland)·2019

Related Experiment Video

Updated: Dec 21, 2025

Investigating the Potential of Singly Curved Thin Piezoelectric Transducers for Energy Harvesting and Structural Health Monitoring
07:02

Investigating the Potential of Singly Curved Thin Piezoelectric Transducers for Energy Harvesting and Structural Health Monitoring

Published on: November 14, 2025

506

Compressive Sensing Approach to Harmonics Detection in the Ship Electrical Network.

Beata Palczynska1, Romuald Masnicki2, Janusz Mindykowski2

  • 1Faculty of Electrical and Control Engineering, Gdansk University of Technology, 11/12 Gabriela Narutowicza Street, 80-233 Gdansk, Poland.

Sensors (Basel, Switzerland)
|May 15, 2020
PubMed
Summary

This study explores compressive sensing (CS) for detecting harmonics in ship electrical networks. It presents a fast reconstruction algorithm using the discrete Radon transform (DRT) and K-rank-order filters for efficient harmonic analysis.

Keywords:
compressive sensingdiscrete Radon transformharmonicssignal reconstructionsparse signal domain

More Related Videos

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
05:11

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition

Published on: June 27, 2025

513
Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

6.4K

Related Experiment Videos

Last Updated: Dec 21, 2025

Investigating the Potential of Singly Curved Thin Piezoelectric Transducers for Energy Harvesting and Structural Health Monitoring
07:02

Investigating the Potential of Singly Curved Thin Piezoelectric Transducers for Energy Harvesting and Structural Health Monitoring

Published on: November 14, 2025

506
High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition
05:11

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition

Published on: June 27, 2025

513
Data Acquisition Protocol for Determining Embedded Sensitivity Functions
07:46

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

6.4K

Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Data Science

Background:

  • Ship electrical networks are susceptible to harmonic distortions.
  • Harmonic detection is crucial for system stability and performance.
  • Existing methods may be computationally intensive or require extensive data.

Purpose of the Study:

  • To investigate the application of compressive sensing (CS) for detecting harmonics in frequency-sparse signals.
  • To develop and evaluate a fast reconstruction algorithm for harmonic analysis in ship electrical networks.
  • To explore the use of discrete Radon transform (DRT) and K-rank-order filters within a CS framework.

Main Methods:

  • Modeling ship electrical network signals as sparse representations in the discrete Fourier transform (DFT) domain.
  • Utilizing compressive sensing (CS) principles for signal reconstruction from under-sampled measurements.
  • Implementing a fast reconstruction algorithm based on the inverse discrete Radon transform (DRT).
  • Applying K-rank-order filters in the sparse domain to enhance convergence and acquire sub-Nyquist data.
  • Employing Bernoulli matrices for measurements, diverging from typical Gaussian approaches.

Main Results:

  • Preliminary numerical simulations confirm the effectiveness of the proposed CS-based algorithm for harmonic detection.
  • The algorithm demonstrates limitations that require further investigation.
  • The approach leverages fast Fourier transform (FFT) and inverse FFT (IFFT) for efficient analysis.
  • The data processing algorithm is characterized by low memory usage and processing load.

Conclusions:

  • The proposed compressive sensing technique offers a promising and efficient method for detecting harmonics in ship electrical networks.
  • The integration of DRT and K-rank-order filters provides a novel approach to under-sampled signal reconstruction.
  • The algorithm's speed and simplicity present significant advantages for practical implementation.