Abstract
Multisensor information fusion technology in welding process was studied, and Choquet fuzzy integral method was used in this paper to fuse the information obtained by arc, sound, and visual sensors in pulsed gas tungsten arc welding (GTAW) process. A novel method to obtain the fuzzy set function values in fuzzy integral was proposed to obtain the prediction results of single sensor, and a method by using supporting degrees of different sensors was proposed to obtain the fuzzy measure function values in fuzzy integral. Choquet fuzzy integral was used to fuse the information after the fuzzy set function and fuzzy measure values were obtained, and the multisensor information fusion model based on the method was proposed. Experiment was done to test the effectiveness of the method in the end.
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References
Cheng L (2008) Latest progress of research on fault diagnosis based on information fusion. Inf Technol J 7(5):825–829
Cai G, Du D, Tian Y, Hou R, Gao Z (2007) Defect detection of X-ray images of weld using optimized heuristic search based on image information fusion. Trans China Weld Inst 28(2):29–32+37
Carvalho EAN, Luciano BA, Freire RCS, Molina L, Freire EO. Fault-tolerant weld line detection for automatic inspection of storage tanks based on distance and visual information fusion. in 2009 I.E. Instrumentation and Measurement Technology Conference, I2MTC 2009, May 5, 2009 - May 7, 2009. 2009. Singapore, Singapore: IEEE Computer Society
Chang Y, Su H, Lin B, Yang X (2007) Spot welding quality fuzzy control system based on multisensor information fusion. Chin J Mech Eng EN 20(4):36–39
Chen B, Chen S (2010) Multi-sensor information fusion in pulsed GTAW based on fuzzy measure and fuzzy integral. Assem Autom 30(3):276–285
Chen B, Wang J, Chen S (2010) A study on application of multi-sensor information fusion in pulsed GTAW. Ind Robot 37(2):168–176
Chen B, Wang J, Chen S (2010) Prediction of pulsed GTAW penetration status based on BP neural network and D-S evidence theory information fusion. Int J Adv Manuf Technol 48(1–4):83–94
Pan C, Du S, Song Y, Li H (2007) Multiple information fusion and quality classification of aluminum alloy resistance spot welding. Chin J Mech Eng 43(8):181–185
Fan CJ, Lv FL, Chen SB (2009) Visual sensing and penetration control in aluminum alloy pulsed GTA welding. Int J Adv Manuf Technol 42(1–2):126–137
Grabisch M (1996) The representation of importance and interaction of features by fuzzy measures. Pattern Recogn Lett 17(6):567–575
Grabisch M (1996) The application of fuzzy integrals in multicriteria decision making. Eur J Oper Res 89(3):445–456
Sugeno M (1974) Theory of fuzzy integrals and its applications,[Doctoral Thesis], Tokyo,Tokyo Institute of Technology
Sugeno M (1977) Fuzzy measures and fuzzy integrals: a survey. Fuzzy automata and decision processes:89–102
Banon G (1981) Distinction between several subsets of fuzzy measures. Fuzzy Set Syst 5(3):291–305
Murofushi T, Sugeno M (1991) A theory of fuzzy measures: representations, the Choquet integral, and null sets. J Math Anal Appl 159(2):532–549
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43:59–69
Kohonen T (1990) The self-organizing map. Proc IEEE 78(9):1464–1480
Yang H, Chan L, King I (2002) Support vector machine regression for volatile stock market prediction. Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning:391–396
Ho C, Lee DT (2004) Travel-time prediction with support vector regression. IEEE Trans Intell Transp 5(4):276–281
Drucker H, Burges CJC, Kaufman L, Smola A, Vapnik V Support vector regression machines. Advances in Neural Information Processing Systems-9:155–161
Cho SB, Kim JH (1995) Multiple network fusion using fuzzy logic. IEEE Trans Neural Netw 6(2):497–501
Jousselme AL, Grenier D, Bosse E (2001) A new distance between two bodies of evidence. Inf Fusion 2(2):91–101
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Chen, B., Chen, S. & Feng, J. A study of multisensor information fusion in welding process by using fuzzy integral method. Int J Adv Manuf Technol 74, 413–422 (2014). https://doi.org/10.1007/s00170-014-6001-6
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DOI: https://doi.org/10.1007/s00170-014-6001-6