By Topic

Designed strength identification of concrete by ultrasonic signal processing based on artificial intelligence techniques

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Se-Dong Kim ; Dept. of Electr. Eng., Doowon Tech. Coll., Kyonggi-do, South Korea ; Dong-Hwan Shin ; Lea-Mook Lim ; Jin Lee
more authors

This paper presents a pattern recognition method to identify the designed strength of concrete by evidence accumulation based on artificial intelligence techniques with multiple feature parameters. Concrete specimens in this experiment, which were designed to have the strengths of 180, 210, 240, 300, and 400 kg/cm/sup 2/, respectively, have been considered. Variance, zero-crossing, mean frequency, autoregressive (AR) model coefficients, and linear cepstrum coefficients are extracted as feature parameters from ultrasonic signals of concretes. Pattern recognition is carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is introduced to transform the distance for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern identification.

Published in:

Ultrasonics, Ferroelectrics, and Frequency Control, IEEE Transactions on  (Volume:52 ,  Issue: 7 )