Data mining technology for mechanical engineering computer test system

•The processing is simple and suitable for the calculation of the dynamic balance test system with fewer sampling points.•Both the DFT method and the FFT method use the principle of Fourier transform spectrum analysis.•The classification results of fault data show that the improved Apriori algorithm...

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Bibliographic Details
Published in:Mechanical systems and signal processing Vol. 141; p. 106628
Main Authors: Li, Zhenjun, Yu, Xiaomo
Format: Journal Article
Language:English
Published: Berlin Elsevier Ltd 01.07.2020
Elsevier BV
Subjects:
Algorithms
Apriori algorithm
Background noise
Computer simulation
Data mining
Data mining technology
Filtration
Fourier transforms
Mechanical engineering
Noise reduction
Partial differential equations
Rotors
Signal de-drying
Signal processing
Spectrum analysis
Test system
Test systems
Data mining technology
Apriori algorithm
Signal de-drying
Test system
Mechanical engineering
ISSN:0888-3270, 1096-1216
Online Access:Get full text
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Summary:•The processing is simple and suitable for the calculation of the dynamic balance test system with fewer sampling points.•Both the DFT method and the FFT method use the principle of Fourier transform spectrum analysis.•The classification results of fault data show that the improved Apriori algorithm has been greatly improved, and the acquisition speed of fault rules has been improved. With the continuous development of information technology, data resources have become increasingly rich, but the knowledge contained in data resources has not been fully explored and utilized. In order to find an effective computer testing technology, the paper introduces the partial differential equation (PDE) into the denoising process of rotor vibration signal through data mining technology, and generalizes the unified model of PDE filtering. Several filtering methods are compared through simulation experiments. The effect is that the flexible rotor is balanced by different dynamic balancing methods, and satisfactory results are obtained. From the simulation results, it can be concluded that the integration method is not suitable to extract the unbalanced signal with strong noise background, but it provides a way to calculate the amplitude and phase of sinusoidal signal without noise; The processing is simple and suitable for the calculation of the dynamic balance test system with fewer sampling points; both the DFT method and the FFT method use the principle of Fourier transform spectrum analysis, but the FFT method calculates the speed much faster than the DFT method. Experiments on the classification of fault data prove that the improved Apriori algorithm is greatly improved compared with the original Apriori algorithm, and the speed of acquiring fault rules is improved.
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ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2020.106628