Identification and evaluation for the dynamic signals caused by pressure fluctuation of aerostatic slider

2018 ◽  
Vol 70 (6) ◽  
pp. 927-934 ◽  
Author(s):  
Dongju Chen ◽  
Jihong Han ◽  
Xianxian Cui ◽  
Jinwei Fan

Purpose To identify the dynamic feature of the aerostatic slider caused by gas film, an evaluation system by a piezoelectric acceleration sensor is presented in time and frequency domain. Design/methodology/approach The dynamic pressure fluctuation is evaluated by the wavelet transform, cross correlation analysis and power spectral density (PSD). Wavelet transform is used to process the measured result of the aerostatic slider and the signal is decomposed into high-frequency and low-frequency signal. Correlation analysis method is used to evaluate the impact of the initial gas gap on the fluctuation in time domain. Findings According to the PSD analysis of the processed signal in the frequency domain, the natural frequency of the aerostatic slider is identified from the measured signal in frequency domain; this method provides a basis for the identification of guideway errors. Research limitations/implications The method can also be applied to the error identification of other components of the machine tool. Originality/value Wavelet transform is used to process the measured result of the aerostatic slider by acceleration sensor, and the signal is decomposed into high-frequency and low-frequency signal. Correlation analysis method is used to evaluate the impact of the initial gas gap on the fluctuation in time domain. According to the PSD analysis of the processed signal in the frequency domain, the natural frequency of the aerostatic slider is identified from the measured signal in frequency domain; this method provides a basis for the identification of slider errors.

2019 ◽  
Vol 11 (1) ◽  
pp. 01025-1-01025-5 ◽  
Author(s):  
N. A. Borodulya ◽  
◽  
R. O. Rezaev ◽  
S. G. Chistyakov ◽  
E. I. Smirnova ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Dongju Chen ◽  
Shuai Zhou ◽  
Lihua Dong ◽  
Jinwei Fan

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.


2021 ◽  
Vol 25 (1) ◽  
pp. 49-55
Author(s):  
Yiying Xiong

In view of the inaccuracy of the traditional correlation analysis method, this paper proposes a correlation analysis method between the multifractal characteristics of regional landforms and the development of geological disasters. Firstly, the multifractal characteristics of regional landforms are described by using the basic fractal characteristics of self-similarity or scale invariance. Then the corresponding relation table is established according to the width of the fractal spectrum and the number of landslides and hidden dangers, and the spatial relationship of geological disaster development is analyzed. Combined with the above-mentioned spatial relationship of geological disaster development and the multifractal characteristic data of regional landforms, the correlation coefficient between the two is calculated to complete the correlation analysis between the multifractal characteristics of regional geomorphology and the development of geological disasters. The experimental results show that compared with the traditional correlation analysis method, the correlation analysis results of the multifractal characteristics of regional geomorphology and the development of geological disasters are more accurate.


Sign in / Sign up

Export Citation Format

Share Document