| Title |
Pattern Classification of the Strength of Concrete by Feature Parameters and Evidence Accumulation of Ultrasonic Signal |
| Authors |
김세동(Kim, Se-Dong) ; 신동환(Sin, Dong-Hwan) ; 이영석(Lee, Yeong-Seok) ; 김성환(Kim, Seong-Hwan) |
| Keywords |
Pattern recognition method ; Artificial intelligence ; Evidence accumulation ; Concrete quality ; Ultrasonic nondestructive testing |
| Abstract |
This paper presents concrete pattern recognition method to identify the strength of concrete by evidence accumulation with multiple parameters based on artificial intelligence techniques. At first, zero-crossing(ZCR), mean frequency(MEANF), median frequency(MEDF) and autoregressive model coefficient(ARC) are extracted as feature parameters from ultrasonic signal of concrete. Pattern recognition is carried out through the evidence accumulation procedure using distance measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern recognition. |