Fuzzy Neural Network PID–based constant deceleration compensation device for the brakes of mining hoists

Abstract

<jats:p> 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. </jats:p>

Thermal-mechanical coupling analysis and optimization of mine hoist brake disc

“…At the same time, the brake shoes are pushed by disc springs to compress the brake disc and friction torque is generated. 17,18 The friction between brake shoe and brake disc converts kinetic energy into heating energy. The frictional heat generated during braking is difficult to be emitted in a short period of time.…”

“…At the same time, the brake shoes are pushed by disc springs to compress the brake disc and friction torque is generated. 17,18…”

Reliability evaluation of electromechanical braking system of mine hoist based on fault tree analysis and Bayesian network

“…In order to improve the reliability of the brake system, many scholars have carried out research on the hydraulic brake system. Ma [26] and others designed a constant deceleration compensation device in order to make the brake capable of constant deceleration, so that the brake has a constant deceleration function and greatly improves the safety and reliability of the mine hoist; Popescu [27] and others established a numerical calculation model for the temperature of the moving disk of the mine hoist under emergency braking to ensure the safe operation of the hoist under emergency braking, and determined that the temperature did not exceed the limit value during emergency braking; Li [28] and others adopted the fault diagnosis method of mine hoist braking system based on mechanical learning to realize high-precision fault diagnosis of mine hoist braking system and further improve the reliability of braking system; Xu [29] and others designed a disc brake with real-time monitoring of brake positive pressure and certain brake fault diagnosis function to solve the fault problem of the hydraulic disc brake of the mine hoist, which is used to diagnose the fault of the disc brake in real time and avoid further expansion of the fault accident. However, the research on the reliability of the braking system mainly focuses on the hydraulic braking system, and the research on the reliability of the electro-mechanical braking system is less.…”

A Novel PID Control Strategy Based on Improved GA-BP Neural Network for Phase-Shifted Full-Bridge Current-Doubler Synchronous Rectifying Converter

“…Fuzzy control has strong fault tolerance, but fuzzy processing will reduce the control accuracy and dynamic quality of the system [11]. In literature [12,13], neural network PID has the ability of online estimation and self-learning and can be approximated by any nonlinearity. Moreover, the regulation process does not depend on the system model, which is suitable for the control of rectifying converter.…”