scholarly journals Spindle vibration signal extraction method based on improved all phase Fast Fourier Transform

2020 ◽  
Vol 789 ◽  
pp. 012066
Author(s):  
Z Wang ◽  
SY Du ◽  
LC Roşca
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Extraction Method ◽  
Vibration Signal ◽  
Signal Extraction ◽  
Spindle Vibration

scholarly journals Reviews of bearing vibration measurement using fast Fourier transform and enhanced fast Fourier transform algorithms

2019 ◽  
Vol 11 (1) ◽  
pp. 168781401881675 ◽  
Author(s):  
Hsiung-Cheng Lin ◽  
Yu-Chen Ye
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Vibration Signal ◽  
Rolling Element Bearing ◽  
Vibration Measurement ◽  
Time Frequency ◽  
Diagnosis And Prognosis ◽  
Vibration Signal Analysis ◽  
Critical Components ◽  
Comparative Results

The rolling element bearing is one of the most critical components in a machine. Vibration signals resulting from these bearings imply important bearing defect information related to the machinery faults. Any defect in a bearing may cause a certain vibration with specific frequencies and amplitudes depending on the nature of the defect. Therefore, the vibration analysis plays a key role for fault detection, diagnosis, and prognosis to reach the reliability of the machines. Although fast Fourier transform for time–frequency analysis is still widely used in industry, it cannot extract enough frequencies without enough samples. If the real frequency does not match fast Fourier transform frequency grid exactly, the spectrum is spreading mostly among neighboring frequency bins. To resolve this drawback, the recent proposed enhanced fast Fourier transform algorithm was reported to improve this situation. This article reviews and compares both fast Fourier transform and enhanced fast Fourier transform for vibration signal analysis in both simulation and practical work. The comparative results verify that the enhanced fast Fourier transform can provide a better solution than traditional fast Fourier transform.

The Wavelet De-Noising of Vibration Signals for Aircraft Rolling Bearings

2014 ◽  
Vol 912-914 ◽  
pp. 873-877 ◽  
Author(s):  
Feng Kui Cui ◽  
Fei Fei Lv ◽  
Xiao Qiang Wang ◽  
Dong Ying Zhang
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Noise Reduction ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Rolling Bearings ◽  
Vibration Signals ◽  
Noise Interference ◽  
Low Snr ◽  
Contrast Analysis

Aiming at air rolling bearing vibration signals low SNR and nonstationary characteristics, taking wavelet theory and principles of the wavelet noise reduction for air vibration signals of rolling bearings to conduct wavelet noise reduction processing.By means of the simulation signal wavelet noise reduction processing and fast Fourier transform, the contrast analysis of the vibration signals after wavelet noise reduction and FFT transform and the original signal directly to the result of the fast Fourier transform, and thus prove the validity of the vibration signal wavelet noise reduction. Through the actual vibration signals of bearing conductnoise reduction processing, the result is a further indication of the superiority of wavelet noise reduction in eliminate noise interference.

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.

Vibration signature analysis of distributed defects in ball bearing using wavelet decomposition technique

2017 ◽  
Vol 48 (1-2) ◽  
pp. 7-18 ◽  
Author(s):  
SS Kulkarni ◽  
AK Bewoor ◽  
RB Ingle
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Wavelet Decomposition ◽  
Ball Bearing ◽  
Vibration Signal ◽  
Extended Defects ◽  
Decomposition Technique ◽  
Outer Race ◽  
Time Frequency ◽  
Extended Type

The analysis of vibration signals acquired from a ball bearing with an extended type of distributed defects is carried out using wavelet decomposition technique. The influence of artificially generated defect and its location on outer and inner race of the ball bearing is observed using vibration data acquired from bearing housing. The comparison of diagnostic information from fast Fourier transform and time frequency decomposition method is made for inner and outer race of ball bearing with single as well as multiple extended defects. To decompose vibration signal acquired from bearing, db04 wavelet technique was implemented. It is observed that impulses appear with a time period corresponding to characteristic defect frequencies. The results observed from wavelet decomposition technique and fast Fourier transform reveal that the characteristic defect frequency is quite consistent even with change in location of defect. The extended type of distributed defects in the ball bearings can also be effectively diagnosed with the help of wavelet decomposition technique and fast Fourier transform.

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.

scholarly journals Separation of the Structure Signal by the Maximal Overlap Discrete Wavelet Transform and Fast Fourier Transform

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Thanh Q. Nguyen
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Fast Fourier Transform ◽  
Discrete Wavelet Transform ◽  
Power Spectra ◽  
Vibration Signal ◽  
Discrete Wavelet ◽  
Single Spectrum ◽  
Power Spectral ◽  
Vibration Process

Power spectral density (PSD) is used for evaluating a structure’s vibration process. Moreover, PSD not only shows a discrete form of vibration but also presents various components in a vibration structure. The superposition of multiple vibration patterns on the same spectrum poses difficulty in analyzing the spectral information in the way needed to find the structure’s discrete vibration. This paper proposes a method for separating the synthetic vibration signal into a structure’s discrete vibration and other extraneous vibrations using the maximal overlap discrete wavelet transform (MODWT) method combined with the method of fast Fourier transform (FFT). With the combination of these two algorithms, MODWT and FFT, the signals of the synthesized vibration have been separated into component signals with different frequency ranges. This means that PSD will be formed, which is based on the combination of the single power spectra of the component signals. Thus, the single spectrum of each of these constructed components can be used to evaluate the types of discrete vibrations coexisting in a structure’s vibration process. The survey results in this paper show the sensitivity and suitability of select types of discrete vibrations to be separated out during the assessment of the structural change, so as to achieve the best possible plan for eliminating the unwanted and unexpected noise and vibration components.

Application of Mathematical Morphology Filter in Non-Stationary Signal of the Spindle Dynamic Balance Regulator Online Adjustment Process

2013 ◽  
Vol 443 ◽  
pp. 150-154
Author(s):  
Zheng Bang Hu ◽  
Dong Sheng Zhang ◽  
Mu Xun Xu ◽  
Tao Tao
Keyword(s):  
Fourier Transform ◽  
Mathematical Morphology ◽  
Dynamic Balance ◽  
Vibration Signal ◽  
Adjustment Process ◽  
Short Time Fourier Transform ◽  
Spindle Vibration ◽  
Non Stationary Signal ◽  
Short Time ◽  
Morphology Filter

The signal which is generated by the dynamic balance regulator for unbalanced spindle in the process of adjustment, having strong nonstationarity. The traditional signal processing methods could not deal with these signals, but also could not express the processing of signal changes. Aiming at the problem, a method combining mathematical morphology filter and the short-time Fourier transform is applied in the non-stationary signal processing in this paper. Using mathematical morphology filter could reduce the noise of spindle vibration signal, and improve the SNR. The amplitude of spindle vibration signal could be got by means of short-time Fourier transform method. Utilized the method proposed in this paper, non-stationary signal of the spindle dynamic balance regulator online adjustment process has been analysed, the results of the experiment show the feasibility of the method.

The Processing Way of Pipeline Vibration Signal Based on Wavelet Transform

2011 ◽  
Vol 317-319 ◽  
pp. 1525-1528
Author(s):  
Ji Chen Shen ◽  
Shi Rong Zhao ◽  
Jing Min Chen
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Fast Fourier Transform ◽  
Frequency Spectrum ◽  
Frequency Band ◽  
Spectrum Analysis ◽  
Vibration Signal ◽  
Scale Analysis ◽  
Frequency Spectrum Analysis ◽  
Pipeline Vibration

The vibration phenomenon of pipeline for conveying liquid and gas is very common. Based on the feature of pipeline vibration and multi-resolution of wavelet, this paper has mainly simulated the vibration signal of pipeline and made muti-scale analysis of the signal. At the same time, this paper points out that the selected frequency band which causes the vibration can be found out, by using frequency spectrum analysis of pipeline vibration signal, combined with Fast Fourier Transform (FFT).So this paper shows that the processing way of pipeline vibration signal based on wavelet transform is available.

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