Spectral decomposition using time-frequency continuous wavelet transforms for fault detection in the Bakken Formation

This paper presents the analysis and comparisons of the short time Fourier transform (STFT) and the continuous wavelet transform techniques (CWT) to the four sounds analysis (S1, S2, S3 and S4). It is found that the spectrogram short-time Fourier transform (STFT), cannot perfectly detect the internals components of these sounds that the continuous wavelet transform. However, the short time Fourier transform can provide correctly the extent of time and frequency of these four sounds. Thus, the STFT and the CWT techniques provide more features and characteristics of the sounds that will hemp physicians to obtain qualitative and quantitative measurements of the time-frequency characteristics.

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Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms

Computers in Industry ◽

10.1016/j.compind.2020.103378 ◽

2021 ◽

Vol 125 ◽

pp. 103378

Author(s):

Masoud Jalayer ◽

Carlotta Orsenigo ◽

Carlo Vercellis

Keyword(s):

Fault Detection ◽

Wavelet Transforms ◽

Rotating Machinery ◽

Fault Detection And Diagnosis ◽

Continuous Wavelet ◽

Continuous Wavelet Transforms ◽

Model Based ◽

Detection And Diagnosis ◽

Convolutional Lstm

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Applications and Comparison of Continuous Wavelet Transforms on Analysis of A-wave Impulse Noise

Archives of Acoustics ◽

10.1515/aoa-2015-0050 ◽

2015 ◽

Vol 40 (4) ◽

pp. 503-512 ◽

Cited By ~ 2

Author(s):

Jun Qin ◽

Pengfei Sun

Keyword(s):

Hearing Loss ◽

Wavelet Transform ◽

Wavelet Transforms ◽

Impulse Noise ◽

Continuous Wavelet ◽

Continuous Wavelet Transforms ◽

Time Frequency ◽

Mexican Hat ◽

Meyer Wavelets ◽

Hazard Level

Abstract Noise induced hearing loss (NIHL) is a serious occupational related health problem worldwide. The A-wave impulse noise could cause severe hearing loss, and characteristics of such kind of impulse noise in the joint time-frequency (T-F) domain are critical for evaluation of auditory hazard level. This study focuses on the analysis of A-wave impulse noise in the T-F domain using continual wavelet transforms. Three different wavelets, referring to Morlet, Mexican hat, and Meyer wavelets, were investigated and compared based on theoretical analysis and applications to experimental generated A-wave impulse noise signals. The underlying theory of continuous wavelet transform was given and the temporal and spectral resolutions were theoretically analyzed. The main results showed that the Mexican hat wavelet demonstrated significant advantages over the Morlet and Meyer wavelets for the characterization and analysis of the A-wave impulse noise. The results of this study provide useful information for applying wavelet transform on signal processing of the A-wave impulse noise.

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