Analysis of multifractality of multivariable coupling relationship of complex electromechanical system in process industry

Abstract

Analysis of the multivariable coupling relationship, detection of the features of the coupling, and quantification of different degrees of each variable for the coupling are important foundations for information modeling, key point identification, and fault tracing of complex electromechanical systems. It is significant to understand the reasons associated with system conditions exchange, and improve the abilities of accident prevention and safety control of the system. In order to study the multifractal properties of the multivariable coupling relationship of the production system in the process industry, coupling detrended fluctuation analysis (CDFA) was applied. The strength and sources of the multifractality were estimated by shuffling and phase randomization with confidence bands. Different degrees of each variable were qualitatively and quantitatively quantified by the Chi square test. Empirical results showed that the CDFA was suitable for analyzing the multivariable coupling relationship of complex electromechanical system, and the coupling exhibited an obvious multifractal feature. Long-range correlation and fat-tailed probability density function of variables are sources for the multifractality of the multivariable coupling relationship of production system in process industry. Some invariant values, such as the multifractality power and ranks of different degree of single variable for the coupling, were detected for a specific operation condition, which were meaningful for conditions identification and information quality control of complex electromechanical system in process industry.