scholarly journals Determination of Spectral Characteristics in a Vibration Sensor Microcircuit

2020 ◽  
Vol 9 (3) ◽  
pp. 2044-2050
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Integrated Circuit ◽  
Spectral Characteristics ◽  
Digital Signal ◽  
Vibration Signal ◽  
Vibration Sensor ◽  
Signal Processing Algorithms

This article discusses aspects of the implementation of digital signal processing algorithms in devices with multifunctional diagnostics of bearing assemblies in integrated-circuit form. The possibility of applying the effective implementation of spectral analysis algorithms on a defined basis is considered. The structural flow chart of the filter which performs Goertzel transformation and schemes for implementation of the fast Fourier transform unit is shown. To solve these problems in Matlab environment were developed mathematical models of Goertzel filter of fast Fourier transform unit was simulated operation of these units for specifying of parameters and evaluation of achieved characteristics. After the evaluation of simulation results, 2 types of spectral analysis units were developed: Goertzel transformation units for accurate calculations and fast Fourier transform units for analysis during the whole operating band. The created units of spectral analysis make it possible to efficiently solve the problems of bearing diagnostics, obtain information on the video spectrum of the vibration signal in the full frequency band and at the same time to determine the exact value or vibration levels at the characteristic frequencies.

The Implementation of Fast Fourier Transform and Coherence Function to Detect the Millimetric Hole on Strip Iron Plate

2020 ◽  
Vol 840 ◽  
pp. 430-437
Author(s):  
Ardi Wiranata ◽  
Ekrar Winata
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Trigger Point ◽  
Coherence Function ◽  
Digital Signal ◽  
Vibration Signal ◽  
Computational Time ◽  
Iron Plate ◽  
The Difference ◽  
Magnitude Squared Coherence

In this study, Fast Fourier Transform (FFT) was used in order to detect bore hole in a structure. FFT is a common method in digital signal processing (DSP) to characterize the frequency emitted by some structure. This method is widely used because of its simplicity. Computational time needed for FFT is relatively lower than another method. The use of FFT to analyze defect in structure is not commonly used since FFT has some weakness for example spatial frequency cannot be extracted to point out the defect location. In this paper, defect was designated as a hole in a strip iron plate with 20 mm in diameter. The strip iron plate was 1 meter long, 38 mm wide and 3 mm thick. This strip iron plate was clamped at one of its ends while the other side is left free. In order to produce vibration signal, impact hammer Bruel Kjaer Type 8202 was used with plastic tip to limit the vibration frequency in to the range of 0 - 1000 Hz. The trigger point was 30 mm from its free end. Three accelerometers were placed series in one line with the trigger point with 300 mm distance of each accelerometer. The position of the hole was varied in three different position. The first position was between trigger point and first accelerometer, between first and second accelerometer and between the second and third accelerometer. The raw signal obtained from the accelerometer was processed by using FFT to understand the mode shape changes in the strip iron plate due to the bore hole. Furthermore, the FFT result was analyzed as function of receiver position to determine the position of hole. The result shows that the frequency characters were different in each case and further analysis by using magnitude-squared coherence function need to be used in order to quantitatively find the difference between FFT result.

Comparison of fast Fourier transform and autoregressive spectral analysis for the study of heart rate variability in diabetic patients

2005 ◽  
Vol 104 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Denis Chemla ◽  
Jacques Young ◽  
Fabio Badilini ◽  
Pierre Maison-Blanche ◽  
Hélène Affres ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Diabetic Patients

scholarly journals Fourier Transform Infrared Spectral Analysis of Polyisoprene of a Different Microstructure

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Dongmei Chen ◽  
Huafeng Shao ◽  
Wei Yao ◽  
Baochen Huang
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Spectral Analysis ◽  
Fourier Transform ◽  
Magnetic Resonance ◽  
Detailed Analysis ◽  
Fourier Transform Infrared ◽  
Ftir Spectra ◽  
H Nmr ◽  
Infrared Spectral

Some polyisoprene samples of different microstructure contents were studied by Fourier transform infrared (FTIR) and1H Nuclear magnetic resonance (1H NMR). On the basis of detailed analysis of FTIR spectra of polyisoprene, the shift of absorption peaks caused by microstructure content’s variation was discussed. The contents of the polyisoprene samples’ microstructure which was determined by the1H NMR was used as the standard. Through the choice, calculation, and comparison with the corresponding absorption peaks of FTIR, a method based on the results of the analysis has been developed for the determination of the microstructure contents of polyisoprene by FTIR.

scholarly journals Cloud Determination of All-Sky Images under Low-Visibility Conditions

2009 ◽  
Vol 26 (10) ◽  
pp. 2172-2181 ◽  
Author(s):  
Juan Huo ◽  
Daren Lu
Keyword(s):  
Numerical Simulation ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Aerosol Optical Depth ◽  
Image Features ◽  
Threshold Method ◽  
Integrated Method ◽  
Low Visibility ◽  
Key Factor

Abstract The threshold method is commonly used to determine cloud in a sky image. This paper evaluates the method by numerical simulation and shows that the aerosol optical depth (AOD) is a key factor that influences the accuracy. Particularly when the visibility is low, a single threshold method is inappropriate. To improve the accuracy of cloud determination from low-visibility sky images, an integrated cloud-determination algorithm is presented that is based on the fast Fourier transform, symmetrical image features, and threshold methods. The preliminary comparison tests show that the new integrated method improves the ability to determine cloud under lower-visibility conditions.

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