scholarly journals NEW APPROACHES IN MULTI-SHAFT GEAR DRIVES VIBRATION DIAGNOSTICS

2020 ◽  
Vol 6 (1) ◽  
pp. 14-24
Author(s):  
Dmitry V. Omes ◽  
Alexandr V. Dragan
Keyword(s):  
Signal Analysis ◽  
Vibration Analysis ◽  
Vibration Signal ◽  
Vibration Sensor ◽  
Vibration Diagnostics ◽  
Gear Drive ◽  
Vibration Signal Analysis ◽  
Low Sensitivity ◽  
Gear Drives ◽  
Modulation Coefficient

Presented studies are aimed at developing of new and improving of existing methods of vibration signal analysis to detect local gears damages during their operating.The new method of calculating the modulation coefficient showed low sensitivity to the place of mounting of the vibration sensor and makes it possible to use in the absence of information about the vibration activity of the gear drive in the previous workable condition.A technique for designing and using unique wavelets was developed. The technique reflects the specifics of real processes in the interaction of meshing teeth and adapted for gears vibration analysis. Using of unique wavelets can noticeably increase the wavelet coefficients sensitivity to changes in gears condition.

scholarly journals DETECTING CLASSIFIER-COAL MILL DAMAGE USING A SIGNAL VIBRATION ANALYSIS

SINERGI ◽  
2019 ◽  
Vol 23 (3) ◽  
pp. 175
Author(s):  
Dedik Romahadi ◽  
Alief Avicenna Luthfie ◽  
L. B. Desti Dorion
Keyword(s):  
Signal Analysis ◽  
Vibration Analysis ◽  
Vibration Signal ◽  
Cement Industry ◽  
Cement Production ◽  
Sophisticated Method ◽  
Unbalanced Rotor ◽  
Long Time ◽  
Vibration Signal Analysis ◽  
Engine Condition

A classifier plays a crucial role in the cement industry. It is in charge of separating coal that has been smoothened out and is ready to be burned although the coal is still rough after going through the grinding process. It takes a long time to burn coal that is not perfectly processed with a classifier. Therefore, it will reduce the amount of cement production, and the factories will release more energy. The closed arrangement and the number of components in the unit classifier requires a sophisticated method to detect damage that occurs early. Vibration analysis is a method that has been effectively employed in detecting the initial damage that occurs to the engine, especially the classifier. This study was aimed at detecting the location of the damage occurring in the classifier by using a vibration signal analysis and by measuring the magnitude of vibration and presenting it to the frequency domain (spectrum) form using Fast Fourier Transform. Engine condition assessment referred to ISO 10816-3 standard in velocity and displacement modes. Based on data spectrum analysis, the dominant damage laid in the unbalanced rotor. Spectrum characteristics of the damage appeared to be in the spectrum line worth 438.01 μm at a 3.5-Hz frequency (1X) radially. This analysis proved to be supported by the decrease in vibration value to 18.65 μm after balancing the Classifier rotor.

scholarly journals Research on transformer condition evaluation technology based on vibration signal analysis

2021 ◽  
Vol 645 ◽  
pp. 012036
Author(s):  
Ma Hao ◽  
Yao Chuang ◽  
Duan Minghui ◽  
Wei Jufang ◽  
Zhang Xin ◽  
...  
Keyword(s):  
Signal Analysis ◽  
Vibration Signal ◽  
Condition Evaluation ◽  
Vibration Signal Analysis

Local Geometric Projection-Based Noise Reduction for Vibration Signal Analysis in Rolling Bearings

2008 ◽  
Author(s):  
Ruqiang Yan ◽  
Robert X. Gao ◽  
Kang B. Lee ◽  
Steven E. Fick
Keyword(s):  
Time Series ◽  
Phase Space ◽  
Noise Reduction ◽  
Signal Analysis ◽  
Signal To Noise Ratio ◽  
Multifractal Spectrum ◽  
Vibration Signal ◽  
Rolling Bearings ◽  
One Dimensional ◽  
Vibration Signal Analysis

This paper presents a noise reduction technique for vibration signal analysis in rolling bearings, based on local geometric projection (LGP). LGP is a non-linear filtering technique that reconstructs one dimensional time series in a high-dimensional phase space using time-delayed coordinates, based on the Takens embedding theorem. From the neighborhood of each point in the phase space, where a neighbor is defined as a local subspace of the whole phase space, the best subspace to which the point will be orthogonally projected is identified. Since the signal subspace is formed by the most significant eigen-directions of the neighborhood, while the less significant ones define the noise subspace, the noise can be reduced by converting the points onto the subspace spanned by those significant eigen-directions back to a new, one-dimensional time series. Improvement on signal-to-noise ratio enabled by LGP is first evaluated using a chaotic system and an analytically formulated synthetic signal. Then analysis of bearing vibration signals is carried out as a case study. The LGP-based technique is shown to be effective in reducing noise and enhancing extraction of weak, defect-related features, as manifested by the multifractal spectrum from the signal.

scholarly journals Vibration analysis based on the spectrum kurtosis for adjustment and monitoring of ball bearing radial clearance

2018 ◽  
Vol 211 ◽  
pp. 06006 ◽  
Author(s):  
Anthimos Georgiadis ◽  
Xiaoyun Gong ◽  
Nicolas Meier
Keyword(s):  
Signal Analysis ◽  
Vibration Signal ◽  
Radial Clearance ◽  
Spectral Kurtosis ◽  
Vibration Data ◽  
Bearing Clearance ◽  
Bearing Condition Monitoring ◽  
Bearing Vibration ◽  
Vibration Signal Analysis

Vibration signal analysis is a common tool to detect bearing condition. Effective methods of vibration signal analysis should extract useful information for bearing condition monitoring and fault diagnosis. Spectral kurtosis (SK) represents one valuable tool for these purposes. The aim of this paper is to study the relationship between bearing clearance and bearing vibration frequencies based on SK method. It also reveals the effect of the bearing clearance on the bearing vibration characteristic frequencies This enables adjustment of bearing clearance in situ, which could significantly affect the performance of the bearings. Furthermore, the application of the proposed method using SK on the measured data offers useful information for predicting bearing clearance change. Bearing vibration data recorded at various clearance settings on a floating and a fixed bearing mounted on a shaft are the basis of this study

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