Abstract
A system based on acoustic resonance and combined with pattern recognition was attempted to discriminate cracks in eggshell. Support vector data description (SVDD) was employed to solve the classification problem due to the imbalanced number of training samples. The frequency band was between 1,000 and 8,000 Hz. Recursive least squares adaptive filter was used to process the response signal. Signal-to-noise ratio of acoustic impulse response was remarkably enhanced. Five characteristics descriptors were extracted from response frequency signals, and some parameters were optimized in building model. Experiment results showed that in the same condition SVDD got better performance than conventional classification methods. The performance of SVDD model was achieved with crack detection level of 90% and a false rejection level of 10% in the prediction set. Based on the results, it can be concluded that the acoustic resonance system combined with SVDD has significant potential in the detection of cracked eggs.
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References
Lin J, Puri VM, Anantheswaran RC (1995) Trans ASAE 38(6):1769–1776
Cho HK, Choi WK, Paek JK (2000) Trans ASAE 43(6):1921–1926
De Ketelaere B, Coucke P, De Baerdemaeker J (2000) J Agr Eng Res 76:157–163
Coucke P, De Ketelaere B, De Baerdemaeker J (2003) J Sound Vib 266:711–721
Wang J, Jiang RS (2005) Eur Food Res Technol 221:214–220
Jindal VK, Sritham E (2003) ASAE Annual International Meeting, USA
Tax DMJ, Duin RPW (1999) Pattern Recognit Lett 20:1191–1199
Pan Y, Chen J, Guo L (2009) Mech Syst Signal Process 23:669–681
Lee SW, Park JY, Lee SW (2006) Patten Recognit 39:1809–1812
Podsiadlo P, Stachowiak GW (2006) Tribol Int 39:1624–1633
Sanchez-Hernandeza C, Boyd DS, Foody GM (2007) Ecol Inf 2:83–88
Liu YH, Lin SH, Hsueh YL, Lee MJ (2009) Expert Syst Appl 36:1978–1998
Cho HW (2009) Expert Syst Appl 36:434–441
Tax DMJ, Duin RPW (2001) J Mach Learn Res 2:155–173
Tax DMJ, Duin RPW (2004) Mach Learn 54:45–66
Guo SM, Chen LC, Tsai JHS (2009) Pattern Recognit 42:77–83
De Ketelaere B, Maertens K, De Baerdemaeker J (2004) Math Comput Simul 65:59–67
Adall T, Ardalan SH (1999) Comput Elect Eng 25:1–16
Madsen AH (2000) Signal Process 80:1489–1500
Chase JG, Begoc V, Barroso LR (2005) Comput Struct 83:639–647
Wang X, Feng GZ (2009) Signal Process 89:181–186
Djigan VI (2006) Signal Process 86:776–791
Bu HG, Wang J, Huang XB (2009) Eng Appl Artif Intell 22:224–235
Tao Q, Wu GW, Wang J (2005) Pattern Recognit 38:1071–1077
Xie JS, Qiu ZD (2007) Pattern Recognit 40:557–562
Devos O, Ruckebusch C, Durand A, Duponchel L, Huvenne JP (2009) Chemom Intell Lab Syst 96:27–33
Liu X, Lu WC, Jin SL, Li YW, Chen NY (2006) Chemom Intell Lab Syst 82:8–14
Chen QS, Zhao JW, Fang CH, Wang DM (2007) Spectrochim Acta Pt A Mol Biomol Spectrosc 66:568–574
Huang WL, Jiao LC (2008) Prog Nat Sci 18:455–461
Foody GM, Mathur A, Sanchez-Hernandez C, Boyd DS (2006) Remote Sens Environ 104:1–14
Acknowledgments
This work is a part of the National Key Technology R&D Program of China (Grant No. 2006BAD11A12). We are grateful to the Web site http://www-ict.ewi.tudelft.nl/~davidt/dd_tools.html, where we downloaded SVDD Matlab codes free of charge.
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Lin, H., Zhao, Jw., Chen, Qs. et al. Eggshell crack detection based on acoustic response and support vector data description algorithm. Eur Food Res Technol 230, 95–100 (2009). https://doi.org/10.1007/s00217-009-1145-6
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DOI: https://doi.org/10.1007/s00217-009-1145-6