An Active Vibration Control Method for Typical Piping System of Nuclear Power Plant

Zhang, Xiaomeng; Tao, Sui; Zhang, Haishuai; Zhang, Yanzhu; Liu, Lu; Zhang, Shuo

doi:10.1109/ddcls52934.2021.9455612

Cited by 1 publication

(3 citation statements)

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“…In this work, we propose to use, for example, functions such as Brownian motion, fractional Levy motion, fractional color noise, fractional Gaussian noise, anti-synchronization, and others, as acting to correct or control the behavior of the simulated process [6,17,[21][22][23][24]. In this case, the spectrum of changes in the nature of dynamic processes can vary from quasiperiodic to hyper chaotic processes.…”

Section: Research Methods Used For Analysis and Controlmentioning

confidence: 99%

“…where   T -thermodynamically spectrum of the dimensions of the Poincare's return time in an open space; q S -entropy of Tsallis; GMgeneralized memory; f d -fractal dimensions in the function of entropy of Tsallis;  -mean return time for Poincare;  -stability of Tsallis entropy; st T -stability of thermodynamics; q -exp -exponential of Tsallis. [6,8,18,19,[30][31][32].…”

Section: Research Methods Used For Analysis and Controlmentioning

confidence: 99%

“…The situation becomes much more complicated when several such devices operate in parallel on the same platform, foundation. In this case, it becomes an important task to identify the cause-and-effect relationships of the true sources of vibration [1][2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Deep Learning in Monitoring the Behavior of Complex Technical Systems

Israfil¹

2022

Adv. sci. technol. eng. syst. j.

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The article is devoted to the methods of monitoring and control of vibration processes occurring in the structure and units of complex and unique electromechanical equipment. The monitoring object is considered as a dynamic multidimensional information object, for the study of which analytical and numerical methods of modeling and simulation of multidimensional chaotic systems are used in the context of the scientific direction of physics of open systems. The structure of research of signals of vibration activity of equipment, description of mathematical models and algorithms based on them are presented. Demonstrative results of experiments carried out to analyze and evaluate the possibilities of controlling the behavior of a complex system using methods of influencing signals of various nature are presented. Using the methodology of Visual Thinking will improve the quality and efficiency of monitoring the vibrational activity of a complex technical object. Such a technique will make it possible to reasonably interpret the decision made to control the vibration process. The calculated parameters and the constructed visual images of the processed signals are proposed for use in the Input Layer of the Recurrent Neural Network of the Deep Learning algorithm.

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