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Related Concept Videos

Discrete Fourier Transform01:15

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...
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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...
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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the C=O, C=N, and C=C occur between 1600–1850 cm−1.
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Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine
08:27

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Published on: January 5, 2024

Frequency identification of vibration signals using video camera image data.

Yih-Nen Jeng1, Chia-Hung Wu

  • 1Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 70701, Taiwan. ynjeng@mail.ncku.edu.tw

Sensors (Basel, Switzerland)
|December 4, 2012
PubMed
Summary

Image data acquisition systems using cameras can capture vibration signals but may produce non-physical modes due to insufficient frame rates. A simple model predicts and excludes these false modes for accurate low-frequency vibration analysis.

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Area of Science:

  • Mechanical Engineering
  • Signal Processing
  • Optical Measurement

Background:

  • Image data acquisition systems offer non-contact vibration measurement capabilities.
  • High-speed cameras and webcams can be used for capturing vibration signals.
  • Insufficient frame rates can introduce non-physical vibration modes.

Purpose of the Study:

  • To investigate the potential of image data acquisition systems for precise vibration signal capture.
  • To identify and mitigate non-physical vibration modes induced by insufficient frame rates.
  • To demonstrate the performance of enhanced image acquisition systems for low-frequency vibration analysis.

Main Methods:

  • Utilizing a high-speed camera or webcam connected to a personal computer (PC) for image data acquisition.
  • Enhancing gray-level resolution by summing pixel data and attaching a marked paper sheet.
  • Employing a simple model to predict and exclude non-physical vibration modes.
  • Conducting experiments with LED light sources and vibration exciters.

Main Results:

  • Non-physical modes were induced by insufficient frame rates, with critical frequencies identified at 60 Hz for a CMOS camera and 7.8 Hz for a webcam.
  • Image signal enhancement techniques improved gray-level resolution.
  • Factors were found to partially suppress non-physical modes but not eliminate them entirely.
  • Experimental data confirmed the accurate capture of dominant vibration modes below critical frequencies.

Conclusions:

  • Non-contact image data acquisition systems are promising for collecting low-frequency vibration signals.
  • Careful consideration of camera frame rates is crucial to avoid non-physical modes.
  • Proposed enhancement techniques and predictive models improve the reliability of vibration analysis using image systems.