Naphtha cracking furnace fault diagnosis based on adaptive quantum ant colony algorithm

Huagong Xuebao/CIESC Journal

Volumn 60, Issue 2, 2009, Pages 401-408

  Wang, Ling ^a,b   Wang, Xiuting ^a   Yu, Jinshou ^b  

^a SHANGHAI UNIVERSITY   (China)

^b EAST CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Cracking furnace; Fault diagnosis; Feature selection; Quantum ant colony algorithm

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTER SIMULATION; ELECTRIC FAULT LOCATION; FEATURE EXTRACTION; FURNACES; GLOBAL OPTIMIZATION; NAPHTHAS; SUPPORT VECTOR MACHINES;

ANT-COLONY OPTIMIZATIONS; CRACKING FURNACE; FAULT DATUM; FAULT DIAGNOSIS; FAULT FEATURES; FEATURE SELECTION; HIGH-DIMENSIONAL DATUM; NUMERICAL SIMULATION EXPERIMENTS; OPTIMIZATION ABILITIES; PRODUCTION PROCESS; QUANTUM ANT COLONY ALGORITHM; QUANTUM BITS; SENSOR FAULTS; SMALL SAMPLES; SYSTEM NOISE;

ADAPTIVE ALGORITHMS;

EID: 61349128526     PISSN: 04381157     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. Ma Longbo, Zhang Hongjian, Zhou Hongliang, He Qing. Flow regime identification of oil-water two-phase flow based on HHT and SVM. Journal of Chemical Industry and Engineering (China), 2007, 58(3): 617-622
2. Liu Yi, Wang Haiqing, Li Ping. Local least squares support vector regression with application to online modeling for batch processes. Journal of Chemical Industry and Engineering (China), 2007, 58(11): 2846-2851
3. Samanta B. Gear fault detection using artificial neural networks and support vector machines with genetic algorithms. Mechanical Systems and Signal Processing, 2004, 18(3): 625-644
4. Chiang L H, Kotanchek M E, Kordon A K. Fault diagnosis based on Fisher discriminant analysis and support vector machine. Computer and Chemical Engineering, 2004, 28(8): 1389-1401
5. Wang S W, Xiao F. Detection and diagnosis of AHU sensor faults using principal component analysis method. Energy Conversion and Management, 2004, 45(17): 2667-2686
6. Lee J M, Yoo C K, Lee I B. Fault detection of batch processes using multiway kernel principal component analysis. Computers and Chemical Engineering, 2004, 28(9): 1837-1847
7. Chiang L H, Pell R J. Genetic algorithms combined with discriminant analysis for key variable identification. Journal of Process Control, 2004, 14(2): 143-155
8. Colorni A, Dorigo M, Maniezzo V. Distributed optimization by ant colonies//Proceedings of ECAL91-European Conf. on Artificial Life. Paris: Elsevier, 1991: 134-142
9. Dorigo M, Blum C. Ant colony optimization theory: a survey. Theoretical Computer Science, 2005, 344(2/3): 243-278
10. Marco D, Mauro B, Thomas S. Ant colony optimization. Computational Intelligence Magazine, IEEE, 2006, 1(4): 28-39
11. Han K H. Genetic quantum algorithm and its application to combinatorial optimization problem//IEEE Proc. of the 2000 Congress on Evolutionary Computation. San Diego: IEEE Press, 2000: 1354-1360
12. Han K H, Kim J H. Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Transactions on Evolutionary Computation, 2002, 6(6): 580-593
13. Wang Y, Feng X Y, Huang Y X, Pu D B, Zhou W G, Liang Y C, Zhou C G. A novel quantum swarm evolutionary algorithm and its applications. Neurocomputing, 2007, 70(4/5/6): 633-640
14. Han K H, Kim J H. On setting the parameters of quantum-inspired evolutionary algorithm for practical application//Proc. 2003 Congress on Evolutionary Computation. Piscataway NJ: IEEE Press, 2003: 178-184
15. Kennedy J, Eberhart R C. A discrete binary version of the particle swarm optimization algorithm//Proc. of the 1997 Conf. on Systems, Man, and Cybernetics. Piscataway: IEEE Press, 1997: 4104-4108
16. Zhuang Xiaofeng. Modeling and fault diagnosis for cracking furnaces[D]. Shanghai: East China University of Science and Technology, 2004
17. Christian B, Marco D. The hyper-cube framework for ant colony optimization. IEEE Transactions on System, Man, and Cybernetics-part B: Cybernetics, 2004, 34(2): 1161-172