UPM Institutional Repository

Novitect; a novelty detection soft-computing algorithm for Structural Health Monitoring (SHM) system


Citation

Mustapha, Faizal and Abang Abdul Majid, Dayang Laila and Ng, Kooi Huat Novitect; a novelty detection soft-computing algorithm for Structural Health Monitoring (SHM) system. In: International Conference on Advances Science and Contemporary Engineering 2012 (ICASCE 2012), 21-26 Oct. 2012, Jakarta, Indonesia. (pp. 494-504).

Abstract

In view of the criticality of structural integrity, there are many approaches and structural health monitoring techniques developed to detect damage or crack in engineering structures. This paper aims to develop Novitect, a soft computing platform system for Structural Health Monitoring (SHM). Novitect is developed using MATLAB 2008-Graphical User Interface (GUIDE) module. This system allows users to calculate the novelty index and to display the novelty index plot by processing the generated ultrasonic guided waveform response data induced in a structure. Data of hollow cylinder-like structure is presented in this paper.Novitect is designed to use novelty detection method. Novelty detection method is a multivariate statistical technique used for damage identification based on the acquired waveform response via a smart PZT sensor. The validation of the developed soft computing platform was done by comparing the works done by Mustapha et.al [1] on the hollow cylinder like structure. The developed SHM software can be served as the in-service SHM maintenance tool.


Download File

[img] PDF
39694.pdf
Restricted to Repository staff only

Download (1MB)

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
Publisher: ScienceDirect
Keywords: Novelty index; Structural Health Monitoring (SHM); Ultrasonic guided wave; Smart PZT sensor; MATLAB-GUIDE.
Depositing User: Azian Edawati Zakaria
Date Deposited: 20 Nov 2015 08:31
Last Modified: 20 Nov 2015 08:31
URI: http://psasir.upm.edu.my/id/eprint/39694
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item