A statistical approach for evaluating crack defects in structures under dynamic responses

ABSTRACT

This article presents a new approach to processing data in identifying and evaluating defects of structures with deformation measurement signals. By using sensitive characteristics observed in the old statistical parameters such as mean values, variances, and standard deviations, we propose three new parameters including kurtosis, skewness of signals, and statistical density function. In addition, we apply cumulative function in statistical and data analysis. High reliability and accuracy of the present approach has been verified through 38 bridges with over 300 span structures in Ho Chi Minh City (HCMC). Furthermore, we have conducted experiments with a small-scale model at the Laboratory of Applied Mechanics (LAM) to compare computational results with ones derived from practical data. Obtained results show promising applicability of sensitive parameters extracted from statistical features in identifying and evaluating defects in structures.

KEYWORDS:

• Deformation signals
• beams
• mean values
• variances
• standard deviations
• sharpness
• gradient
• kurtosis
• skewness

Acknowledgements

Dear Professor Rachel Edwards,

Editor in Chief, Nondestructive Testing and Evaluation,

Thank you very much for reviewing our manuscript. The reviewers’ comments are very encouraging and highlight for the importance of this research.

The authors would like to thank reviewers for their comments on our paper. We have provided point-to-point responses to the reviewers’ comments in the revised version. All changes in the revised paper are highlighted with blue text.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notations of revisions

The reviewers’ comments are in normal text and authors’ responses are in italics.

Additional information

Funding

This research is funded by Ho Chi Minh City University of Technology, VNUHCM, under grant number BK-SDH-2019- 1880703.