.png){kind=icon}
.png){kind=icon}
Return
Data mining technology for mechanical engineering computer test system
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ymssp.2020.106628.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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. (C) 2020 Elsevier Ltd. All rights reserved.
Keywords:
Mechanical engineering
Test system
Apriori algorithm
Signal de-drying
Data mining technology
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.9
Papers:
1.3W
Citations:
6.6W