Dissertation > Excellent graduate degree dissertation topics show

Flatness Pattern Recognition and Control for the Cold Strip Mill Based on Artificial Intelligence

Author: ZuoZongPeng
Tutor: ZhangXiuLing
School: Yanshan University
Course: Control Theory and Control Engineering
Keywords: Flatness Pattern recognition Flatness control Effective matrix Adaptive neuro-fuzzy inference system
CLC: TP273
Type: Master's thesis
Year: 2010
Downloads: 97
Quote: 1
Read: Download Dissertation

Abstract


Along with the development of national economy and the improvement of living standards, the demand of board strips is increasing unceasingly, simultaneously the product quality’s request of board strips is also increasing. Flatness pattern recognition and control as relations product quality of board strips, is the key technology and has become the key research problem of steel industry. In recent years, the intelligence theory technology develops unceasingly, because intelligence method in modeling, optimization and control has powerful function, the intelligence research methods of flatness pattern recognition and control technology is an inevitable trend in the development of the modern flatness technology. The research subject of this article chooses the flatness pattern recognition and control for the cold strip mill based on artificial intelligence, which has the theory and the practical significance, studies the present theoretical knowledge of the intelligent recognition and control, carries on the comprehensive analysis to it, makes up for one’s deficiency by learning from others’ strong points, and carries on further research for the flatness control and pattern recognition using fuzzy neural network.Firstly, as the antijamming ability of the traditional least squares flatness pattern recognition method is poor, its precision is low, the result of the neural network flatness pattern recognition method has a long time network studying, being easy to fall into the local minimum and many other problems. This article fuses the merits of the fuzzy theories and neural network, fitting effectively three adaptive neuro fuzzy inference systems, and proposes a kind of flatness pattern recognition method based on adaptive neuro-fuzzy inference system. The result indicates that this method can overcome the above flaws very well, and can distinguish the common flatness flaw effectively, the recognition speed and the precision can be improved to some extent, and the recognition result is also very close to the actual value of flatness.Secondly, as flatness control system’s nonlinearity and the close coupling, as well as the traditional effective function method flatness static state effective matrix’s insufficient, getting through the massive production measured data’s computation and analysis, this article proposes the dynamic effective matrix method for flatness control and sets up flatness forecast model based on subtractive clustering ANFIS (Adaptive Neuro-Fuzzy Inference System). Through the flatness effective matrix forecast model based on subtractive clustering ANFIS, it obtains the effective matrix on line which changes unceasingly, realizes the effective control of flatness and gives dual attention to the flatness production timeliness and the complexity.Finally, this article carries on the simulation application on the 900HC rolling mill using the dynamic effective matrix method for flatness control, confirms fully the validity of the flatness forecast model and the dynamic effective matrix method for flatness control which proposed through the simulation experiment result.

Related Dissertations

  1. The Classification of High Dimsnsion Flew Field Based on Manifold Learning,V231.3
  2. Research on Text Classification Based on Biomimetic Pattern Recongnition,TP391.1
  3. Research on Identification System of Cashmere and Wool Fiber,TS101.921
  4. Intrusion detection based on the ultrasonic echo envelope in the military security patrols,E919
  5. Exploration and Analysis of Electronic Detection of Raw Silk’s Flatness,TS147
  6. Research on Key Technologies of Turning Expert System Based on SE300,TP182
  7. Improved Mathematical Model of Spatial Information Processing Based on Fuzzy Technology,O159
  8. The EMG Pattern Recognition System Based on Generalized Dynamic Fuzzy Neural Network,TP183
  9. Design and Implementation of System of Tables with Handwritten Content,TP391.41
  10. A Study on the Value Indictors System of Cultural Heritages in Henan,G122
  11. Action surface EMG nonlinear characteristic of,TH772
  12. Equal thickness interferometer for large-size digital measurement of flatness,TH744.3
  13. PMSM Vector Control System,TM341
  14. CUDA-based video fire detection system,TP391.41
  15. Dollar bill image detection of critical information and number identification,TP391.41
  16. Deck flatness simulation and evaluation method,U443.31
  17. SVM Based on SIFT and scene classification,TP391.41
  18. Seamless integration of automatic detection of ultrasonic vortex systems research and development,TH878.2
  19. Based on DCE-MRI of computer-aided diagnosis of benign and malignant breast lesions studied,TP391.7
  20. Based on LabVIEW typical communication signal modulation , parameter identification and simulation experiment,TP274
  21. Smartphone dimensional code recognition system design and implementation,TN929.53

CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Automatic control,automatic control system
© 2012 www.DissertationTopic.Net  Mobile