Open AccessFuzzy Neural Network PID–based constant deceleration compensation device for the brakes of mining hoists
Author(s) -
Chenguang Ma,
Suzhi Tian,
Xinming Xiao,
Yuqiang Jiang
Publication year - 2020
Publication title -
advances in mechanical engineering/advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1177/1687814020937568
Subject(s) - constant (computer programming) , brake , compensation (psychology) , torque , pid controller , artificial neural network , control theory (sociology) , reliability (semiconductor) , automotive engineering , engineering , control engineering , computer science , control (management) , temperature control , artificial intelligence , psychology , power (physics) , physics , quantum mechanics , psychoanalysis , thermodynamics , programming language
In comparison with constant torque brakes, constant deceleration brakes are more advantageous for the safety of mining hoists, but complete set of such products manufactured by big companies are not what ordinary mining enterprises can afford. As an alternative solution, this article develops a constant deceleration compensation device, which adds the function of constant deceleration brake onto the original brakes. Control strategy based on Fuzzy Neural Network PID is investigated and simulated with the combination of AMEsim and Simulink. An actual device is built and tested in real industrial field. The application illustrates the feasibility of this constant deceleration compensation device, which can achieve constant decelerations within a very short time. This device will prevent dangerous decelerations from happening to hoists at a much lower cost, and greatly improve the safety and reliability of mining hoists.