Modelling of the hydraulic work roll bending control system of the plate rolling mill

Voronin, Stanislav S.; Gasiyarov, Vadim R.; Maklakova, E.A.

doi:10.1109/eiconrus.2017.7910739

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…The pole mill equipment is a multi-motor controlled transmission machine. And for the multi-motor control and harsh production environment, multi-coupled interference signals such as high frequency, RF (Radio Frequency), and spikes are generally encountered in its digital hardware system integration design [ 6 ]. Traditional machinery and equipment control units use industrial control machines or embedded control, represented by PLC (Programmable Logic Controller), ARM, and DSP.…”

Section: Introductionmentioning

confidence: 99%

Optimized design of battery pole control system based on dual-chip architecture

et al. 2022

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At present, the global demand for lithium batteries is still in a high growth state, and the traditional lithium battery pole mill control system is still dominated by ARM (Artificial Intelligence Enhanced Computing), DSP (Digital Signal Processing), and other single-chip control methods. There are problems such as poor anti-interference ability and insufficient real-time online analysis of production data. This paper adopts the dual-chip control system architecture based on "ARM+DSP", starting from the mechanical characteristics and operating signal features of the pole mill. The hardware system adopts a three-unit joint control hardware structure, which separates the control unit from the data processing unit and improves the operation of the system. The software system adopts fuzzy PID algorithm to realize deflection control and tension control, and verifies that the Fuzzy PID (Proportion Integration Differentiation) control algorithm can effectively improve the anti-interference ability of the deflection system and tension system. The results show that the data loss rate is low with the SPI communication between DSP and ARM. The tension error of the "ARM+DSP" control system does not exceed 5%, and the deviation of the correction band is within ±4mm. The dedicated dual-chip hardware architecture effectively improves the robustness and operation efficiency of the pole mill, solves the problem of low tension control accuracy, and provides a theoretical basis for the application of the dual-roll mill.

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Section: Introductionmentioning

confidence: 99%

Optimized design of battery pole control system based on dual-chip architecture

et al. 2022

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“…Therefore, in the continuous rolling process of battery pole double rolling equipment, with the increase of rolling working time and the change of internal conditions and external environment of the equipment, failure and "Sub-Health" state which is not conducive to the regular operation of the equipment will inevitably occur [4] [5]. Combined with the background of current industry 4.0 and conforming to the development trend of the intelligent manufacturing industry, it is urgent to improve the intellectual level of lithium battery pole double roller equipment, reduce equipment faults and subhealth status, and apply health diagnosis technology to lithium battery pole double roller equipment [6].…”

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confidence: 99%

Intelligent Health Diagnosis of Lithium Battery Pole Double Rolling Equipment Driven by Hybrid BP Neural Network and Expert System

Xiao

Deng

Fu-rong³

et al. 2022

IEEE Access

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At present, the fault diagnosis methods of lithium battery pole rolling mill mostly rely on manual experience and the self-test function of mature control devices such as frequency converters and lack the ability of intelligent fault diagnosis for the whole equipment and the ability to evaluate the health state of the equipment during operation. To improve the intellectual health diagnosis ability of lithium battery pole double rolling mill equipment, starting from the structure and technology of lithium battery pole double rolling equipment, this paper analyzes its common fault types. It summarizes the shortcomings and common fault types of existing equipment. Then, we introduce fuzzy reasoning into the fault diagnosis method based on Expert Systems and establish the FEFDM of lithium battery pole double rolling equipment. Finally, we introduce the concept of health degree, effectively connect BP neural network and health degree through the fuzzy set, and establish an equipment operation health state evaluation method based on an improved BP Neural Network, which realizes the evaluation ability of the health state of double roller equipment. In addition, we use Extended Kalman Filtering (EKF) to clean the "dirty data" and filter out the Gaussian white noise from the signal. The health diagnosis method proposed in this paper can meet the ability to accurately locate and diagnose the fault of lithium battery pole double roller equipment and evaluate the health state of equipment operation and maintain the equipment in advance.

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Modelling of the hydraulic work roll bending control system of the plate rolling mill

Cited by 2 publications

References 4 publications

Optimized design of battery pole control system based on dual-chip architecture

Optimized design of battery pole control system based on dual-chip architecture

Intelligent Health Diagnosis of Lithium Battery Pole Double Rolling Equipment Driven by Hybrid BP Neural Network and Expert System

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