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Discrete Fourier Transform

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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...

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Updated: Apr 27, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

Frequency feature based quantification of defect depth and thickness.

Shulin Tian¹, Kai Chen¹, Libing Bai¹

¹School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.

The Review of Scientific Instruments

|July 3, 2014

Summary

This summary is machine-generated.

This study introduces a new pulsed eddy current method using a frequency-to-zero feature for quantifying subsurface defects and metal loss in metallic materials, enhancing inspection accuracy.

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Area of Science:

Materials Science
Non-Destructive Testing
Electromagnetism

Background:

Pulsed eddy current (PEC) methods are crucial for non-destructive evaluation.
Accurate quantification of subsurface defects and metal loss remains a challenge.
Existing PEC techniques can be limited in sensitivity and resolution.

Purpose of the Study:

To develop an advanced frequency feature-based pulsed eddy current method.
To propose a novel 'frequency to zero' feature for improved defect quantification.
To enhance the accuracy of metal loss and subsurface defect detection.

Main Methods:

Development of a pulsed eddy current (PEC) testing approach.
Introduction and application of a 'frequency to zero' feature.
Utilizing curve fitting to generate additional frequency components.
Experimental validation on metallic specimens.

Main Results:

Successful development of the frequency feature-based PEC method.
Demonstrated effectiveness of the 'frequency to zero' feature for quantification.
Improved accuracy in detecting subsurface defects and metal loss.
Validation of the method through experimental testing.

Conclusions:

The proposed frequency feature-based PEC method offers enhanced accuracy for defect quantification.
The 'frequency to zero' feature is a promising tool for subsurface inspection.
Further research can explore broader applications and optimizations.