Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Discrete Fourier Transform

Discrete Fourier Transform

The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...

¹³C NMR: ¹H–¹³C Decoupling

¹³C NMR: ¹H–¹³C Decoupling

The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...

Downsampling

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...

Energy Stored In A Coaxial Cable

Energy Stored In A Coaxial Cable

A coaxial cable consists of a central copper conductor used for transmitting signals, followed by an insulator shield, a metallic braided mesh that prevents signal interference, and a plastic layer that encases the entire assembly.
In the simplest form, a coaxial cable can be represented by two long hollow concentric cylinders in which the current flows in opposite directions. The magnetic field inside and outside the coaxial cable is determined by using Ampère's law. The magnetic field...

Harmonic Mean

Harmonic Mean

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...

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...

You might also read

Related Articles

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

Sort by

Same author

Fast Averaged Cyclic Periodogram method to compute spectral correlation and coherence.

ISA transactions·2022

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 19, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Data compression in wireless sensors network using MDCT and embedded harmonic coding.

Jaafar K Alsalaet¹, Abduladhem A Ali²

¹Department of Mechanical Engineering, College of Engineering, University of Basrah, Basrah, Iraq.

ISA Transactions

|December 27, 2014

Summary

This summary is machine-generated.

This study introduces a new data compression method for wireless sensor networks (WSNs) to improve vibration signal analysis for structural health monitoring and fault diagnosis. The technique enhances sampling rates and conserves node power.

Keywords:

Data compression Embedded coding MDCT Wireless sensors network

More Related Videos

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Apr 19, 2026

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Data Acquisition Protocol for Determining Embedded Sensitivity Functions

Published on: April 20, 2016

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Engineering
Signal Processing
Wireless Sensor Networks

Background:

Wireless sensor networks (WSNs) are crucial for vibration measurement in structural health monitoring and machinery diagnostics.
WSNs offer advantages like low cost and quick setup but suffer from limited bandwidth and low sampling rates.
Data compression is essential to overcome bandwidth limitations, enhance sampling, and conserve power in WSNs.

Purpose of the Study:

To propose an efficient data compression scheme for vibration signals in WSNs.
To address the challenge of limited bandwidth and power constraints in wireless nodes.
To improve the effectiveness of vibration analysis for structural and machinery monitoring.

Main Methods:

A novel data compression scheme combining Modified Discrete Cosine Transform (MDCT) and Embedded Harmonic Components Coding (EHCC).
EHCC is utilized to exploit harmonic redundancy inherent in vibration signals.
The scheme is optimized for resource-constrained hardware typical of wireless nodes.

Main Results:

The proposed scheme achieves improved compression ratios by leveraging harmonic redundancy.
Experimental tests demonstrate the speed and effectiveness of the compression method.
The technique enhances the feasibility of high-frequency vibration sampling in WSNs.

Conclusions:

The MDCT followed by EHCC offers a fast and effective solution for compressing vibration signals in WSNs.
This approach significantly improves compression ratios, making WSNs more viable for detailed structural and machinery monitoring.
The developed scheme successfully balances compression efficiency with the hardware limitations of wireless nodes.