Optimal sensor placement for thermal error identification of NC machine tool based on LS-SVM and genetic algorithm

Guangxue Jingmi Gongcheng/Optics and Precision Engineering

Volumn 16, Issue 9, 2008, Pages 1682-1687

  Lin, Wei Qing ^a,b   Fu, Jian Zhong ^a   Xu, Ya Zhou ^a   Chen, Zi Chen ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b FUJIAN AGRICULTURE AND FORESTRY UNIVERSITY   (China)

Author keywords

Genetic algorithm; Least Square Support Vector Machine (LS SVM); NC machine tool; Temperature sensor

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; CURVE FITTING; DIESEL ENGINES; ERROR COMPENSATION; GENETIC ALGORITHMS; GENETIC ENGINEERING; GEODESY; IMAGE RETRIEVAL; LATHES; LEARNING SYSTEMS; MACHINE TOOLS; MACHINERY; MACHINING; NUMERICAL CONTROL SYSTEMS; REGRESSION ANALYSIS; RESEARCH AIRCRAFT; SENSOR NETWORKS; SENSORS; TEMPERATURE SENSORS; TOOLS; TWO PHASE FLOW; VECTORS;

AND GENETIC ALGORITHMS; AXIAL DIRECTIONS; CNC LATHES; ERROR IDENTIFICATIONS; LEAST SQUARE SUPPORT VECTOR MACHINE (LS-SVM); LEAST SQUARE SUPPORT VECTOR MACHINES; MEAN ABSOLUTE PERCENTAGE ERRORS; MEASUREMENT POINTS; MODE THEORIES; MODELING; NC MACHINE TOOL; NC MACHINE TOOLS; NOVEL METHODS; NUMERICAL CONTROL MACHINES; OPTIMAL SENSOR PLACEMENTS; RADIAL DIRECTIONS; REGRESSION MODELS; SVM MODELS;

SUPPORT VECTOR MACHINES;

EID: 54049118884     PISSN: 1004924X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (14)

1. RAMESH R, MANNAN M A. Error compensation in machine tools-A review. Part II. Thermal errors[J]. International Journal of Machine Tool and Manufacture, 2000, 40(9): 1257-1284.
2. DU ZH CH, YANG J G, DOU X L, et al.. Thermal error modeling of CNC turning center using radial basis function neural network[J]. Journal of Shanghai Jiaotong University, 2003, 37(1): 26-29. (in Chinese)
3. FU J ZH, CHEN Z CH. Research on modeling thermal dynamic errors of precision machine based on fuzzy logic and artifical neural network[J]. Journal of Zhejiang University (Engineering Science), 2004, 38(6): 742-746. (in Chinese)
4. LIN W Q, XU Y Z, FU J Z. Thermal error modeling and compensation of spindles based on LS-SVM[C]. International Technology and Innovation Conference, Hangzhou: IET Press, 2006: 1160-1166.
5. YANG J G, DENG W G, REN Y Q, et al.. Grouping optimization modeling by selection of temperature variables for the thermal error compensation on machine tools[J]. China Mechanical Engineering, 2004, 15(6): 478-480. (in Chinese)
6. LO C H, YUAN J X, NI J. Optimal temperature variable selection by grouping approach for thermal error modeling and compensation[J]. International Journal of Machine Tools and Manufacture, 1999, 39(9): 1383-1396.
7. GUO H Y, ZHANG L, ZHANG L L, et al.. Optimized sensor placement for urban flow measurement[J]. Smart Materials and Structures, 2004, 13: 528-534.
8. CYNTHIA S, ADITI C. Optimal sensor placement for damage characterization using genetic algorithms[C]. Structures, Structural Dynamics and Materials Conference, California, ASME Press, 2004: 678-684.
9. FU J ZH. Study on theory and application of thermal dynamical monitoring and control of precision machine[D]. Hangzhou: Zhejiang University, 1996. (in Chinese)
10. YANG J G. Error synthetic compensation technique and application for NC machine tools[D]. Shanghai: Shanghai Jiaotong University, 1998. (in Chinese)
11. YE D, LIU CH Y, CHE R SH, et al.. Dummy solid camera calibration technology using genetic algorithm[J]. Opt. Precision Eng., 2006, 14(3): 485-489. (in Chinese)
12. CHEN H, YE D, CHEN G, et al.. Digital image correlation search method based on genetic algorithm[J]. Opt. Precision Eng., 2007, 15(10): 1633-1637. (in Chinese)
13. VAPNIK V. Nature of Statistical Learning Theory [M]. New York: Springer Verlag, 1999.
14. SUYKENS J A K, Van GESTEL T, de BREBANTER J, et al.. Least Squares Support Vector Machines[M]. Singapore: World Scientific Pub. Co., 2002.