The sizing of small surface-breaking fatigue cracks using ultrasonic arrays. (October 2018)

• Record Type: Journal Article
• Authors: Peng, Chaoyong; Bai, Long; Zhang, Jie; Drinkwater, Bruce W.
• Is Part Of: NDT & E international. Volume 99(2018)
• Page Start: 64
• Page End: 71
• Publication Date: 2018-10
• Subjects: Ultrasonic arrays -- Defect sizing -- Defect characterisation -- Fatigue crack -- Total focusing method -- Scattering coefficient matrix; Nondestructive testing -- Periodicals; Contrôle non destructif -- Périodiques; Electronic journals; 620.1127
• DOI: 10.1016/j.ndteint.2018.06.005
• Languages: English
• ISSNs: 0963-8695

Abstract

Abstract: Using ultrasonic arrays to detect and characterise surface breaking cracks is important in the non-destructive evaluation (NDE) field. It can provide early warning of failure and useful information for component integrity assessment. Typically, cracks are approximated by machined slots and used to examine and assess defect detection and characterisation methods. In this paper, real surface breaking cracks are fabricated in 3-point bending specimens following ASTM standard E1820 and used to examine the performance of two array defect characterisation methods: image-based and scattering matrix sizing. In both cases, an array is used to record the full matrix capture (FMC). In image-based sizing, the total focusing method (TFM) is used to form an image from which the defect size is measured directly. This approach is shown to work well for cracks greater than two wavelengths in size. The FMC is also used to extract the defect scattering matrix which is then compared to a pre-computed smooth-crack scattering matrix database. The best match between experiment and this database is found by cross-correlation and used to characterise the defect. This approach is shown to work well for defects in the range of 0.78–1.84 wavelengths. Within these ranges of applicability, both methods show excellent agreement between the known crack length and that measured ultrasonically, with errors less than 19% in all cases.