Mechanical Automatic Monitoring System Based on Nonlinear Correlation Dimension Feature Extraction
CHANG Yongzhi
QIU Yaze
ZHENG Zhen
TU Haojie
Abstract：The fault feature extraction of the vibration signal of natural gas compressor in fault state is the core technol‐ogy in design of mechanical automation detection system .A mechanical automatic monitoring system is proposed based on nonlinear correlation dimension feature extraction ,the principle of fault diagnosis is analyzed ,and the time series analysis of fault vibration signals is obtained .Phase space reconstruction method of fault vibration signal is designed ,and key technolo‐gy of computing of optimal time delay and embedding dimension parameters for phase space reconstruction is improved .The correlation dimension fault feature is extracted ,and the automatic monitoring system is obtained based on Simulink platform . Experimental results show that the system can make the standard deviation of correlation dimension extraction decreased sig‐nificantly ,and the clustering ability is enhanced ,the system can effectively detect all kinds of faults ,monitoring of mechani‐cal equipment is obtained .It has better engineering practice value in the field of automatic fault diagnosis and instrument de‐sig n .
Keywords：nonlinearcorrelation dimensionfeature extractionautomation equipment
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2311-2315 )