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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö > Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö B

Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö B

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ³¿»õ ÀνÄÀ» À§ÇÑ ÃÖÀûÀÇ ¼¾¼­ °áÁ¤ ¹æ¹ý
¿µ¹®Á¦¸ñ(English Title) A Method of Optimal Sensor Decision for Odor Recognition
ÀúÀÚ(Author) ³ë¿ë¿Ï   ±èµ¿±Ô   ±ÇÇü¿À   È«±¤¼®   Yong-Wan Roh   Dong-Ku Kim   Hyeong-Oh Kwon   Kwang-Seok Hong  
¿ø¹®¼ö·Ïó(Citation) VOL 17-B NO. 01 PP. 0009 ~ 0014 (2010. 02)
Çѱ۳»¿ë
(Korean Abstract)
º» ³í¹®¿¡¼­´Â ´ÙÁß ¼¾¼­¸¦ ¼±ÅÃÇÏ´Â ³¿»õ ÀÎ½Ä ½Ã½ºÅÛ¿¡¼­ ÃÖÀûÀÇ ¼¾¼­ Á¶ÇÕÀ» ¼±ÅÃÇϱâ À§ÇÏ¿© Åë°èÀû ºÐ¼® ±â¹ÝÀÇ ¼¾¼­ »çÀÌÀÇ »ó°ü°è¼ö¸¦ ÀÌ¿ëÇÏ´Â ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ¼¾¼­ °áÁ¤ ¹æ¹ýÀº ±Ý¼Ó »êÈ­¹° ¹ÝµµÃ¼(Metal Oxide Semiconductor : MOS) ¼¾¼­ ¾î·¹À̸¦ »ç¿ëÇÏ¿© ³¿»õ µ¥ÀÌÅ͸¦ ȹµæÇÑ ÈÄ È¹µæÇÑ ³¿»õÀÇ »ó°üµµ¸¦ ±â¹ÝÀ¸·Î ÀûÇÕÇÑ ¼¾¼­¸¦ °áÁ¤ÇÑ´Ù. ¿ì¼± ÃøÁ¤ ´ë»óÀÌ À¯»çÇÑ MOS °¡½º¼¾¼­ Áß ÀÀ´äÀÇ Å©±â°¡ ÀÛ°í º¯È­°¡ ³·Àº ¼¾¼­¸¦ Á¦¿ÜÇÏ¿© ÃÑ 16°³ÀÇ ¼¾¼­¸¦ ¼±º°ÇÑ´Ù. ÀԷµǴ ³¿»õ·ÎºÎÅÍ 16°³ÀÇ ¼¾¼­¸¦ »ç¿ëÇÏ¿© ³¿»õ DB¸¦ ±¸ÃàÇÏ°í °¢ ¼¾¼­º° »ó°ü°è¼ö¸¦ °è»êÇÑ ÈÄ »ó°üµµ°¡ ³·Àº ¼¾¼­¸¦ ¼±ÅÃÇÑ´Ù. ¼±ÅÃµÈ ¼¾¼­´Â À¯»çÇÑ ÀÀ´ä Ư¼ºÀ» °®´Â ¼¾¼­¸¦ Á¦°ÅÇÑ °ÍÀ̸ç Á¦¾ÈÇÑ ¹æ¹ýÀ¸·Î ÃÖÀûÀÇ ¼¾¼­¸¦ °áÁ¤ ÇÒ ¼ö ÀÖ´Ù. Á¦¾ÈµÈ ¼¾¼­ °áÁ¤ ¹æ¹ýÀÇ ¼º´É Æò°¡¸¦ À§ÇØ ²É ³¿»õ ÀÎ½Ä ½Ã½ºÅÛ¿¡ Àû¿ëÇÏ¿´´Ù. »ó°ü°è¼ö¸¦ ÀÌ¿ëÇÑ ²É ³¿»õ ÀÎ½Ä ½Ã½ºÅÛ¿¡ Á¦¾ÈÇÑ ¹æ¹ýÀ» Àû¿ëÇÑ °á°ú·Î 16°³ÀÇ ¼¾¼­¸¦ »ç¿ëÇÒ °æ¿ì 95.67%ÀÇ ÀνķüÀ» º¸ÀÌ´Â ¹Ý¸é Á¦¾ÈÇÑ ¼¾¼­ °áÁ¤ ¹æ¹ýÀ» Àû¿ëÇÑ ²É ³¿»õ ÀÎ½Ä ½Ã½ºÅÛÀº 6°³¸¦ »ç¿ëÇÑ °æ¿ì 94.67%, 8°³ÀÇ ¼¾¼­¸¦ »ç¿ëÇÑ °æ¿ì 96%ÀÇ ÀνķüÀ» µµÃâÇÏ´Â °ÍÀ» È®ÀÎÇÏ¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
In this paper, we propose method of correlation coefficients between sensors by statistical analysis that selects optimal sensors in odor recognition system of selective multi-sensors. The proposed sensor decision method obtains odor data from Metal Oxide Semiconductor(MOS) sensor array and then, we decide optimal sensors based on correlation of obtained odors. First of all, we select total number of 16 sensors eliminated sensor of low response and low reaction rate response among similar sensors. We make up DB using 16 sensors from input odor and we select sensor of low correlation after calculated correlation coefficient of each sensor. Selected sensors eliminate similar sensors' response therefore proposed method are able to decide optimal sensors. We applied to floral scent recognition for performance evaluation of proposed sensors decision method. As a result, application of proposed method with floral scent recognition using correlation coefficient obtained recognition rate of 95.67% case of using 16 sensors while applied floral scent recognition system of proposed sensor decision method confirmed recognition rate of 94.67% using six sensors and 96% using only 8 sensors.
Å°¿öµå(Keyword) ¼¾¼­ °áÁ¤ ¹æ¹ý   »ó°ü°è¼ö   ²É³¿»õ ÀνĠ  Sensors decision method   Correlation Coefficient   Floral scent Recognition  
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