Abstract
Errors arise in the measurement of sound absorption coefficient using impedance tube due to various factors. Minimizing the errors require additional hardware or proper calibration of certain components. This paper proposes a new intelligent error correction mechanism using mathematical modelling and soft computing paradigms. A low cost impedance tube is designed, developed and its performance is compared with a commercially available standard tube. A particle swarm optimization and neural network based system is developed to reduce the random and systematic errors in the developed impedance tube. The proposed system is tested using various porous and non-porous functional textile materials and the results are validated. A significant reduction in error is obtained at all frequency ranges with PSO based prediction method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
