Study on the orientation detection of surface cracks by electromagnetic acoustic emission. (April 2019)

• Record Type: Journal Article
• Authors: Cai, Zhichao
• Is Part Of: International journal of distributed sensor networks. Volume 15:Number 4(2019)
• Publication Date: 2019-04
• Subjects: Crack orientation -- electromagnetically induced acoustic emission -- Hilbert–Huang transform; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147719843860
• Languages: English
• ISSNs: 1550-1329

Abstract

Crack orientation plays a vital role in structural integrity analysis, which provides quantitative crack growth and structural failure information. Even though many structural health monitoring systems can detect crack location and length, only few methods are capable of detecting crack orientation. Recently, we have shown that an electromagnetically induced acoustic emission method can detect active defect with elastic waves. In this article, the ability of the electromagnetically induced acoustic emission method for finding the orientation of cracks is studied. Based on the free-electron theory and electroplastic flow concept, the mechanism of electromagnetically induced acoustic emission effect will be explored at the microscopic level. By studying the energy exchange between the free electrons and the metallic dislocations, the total energy and the trajectory of drift electrons radiated during the electromagnetic loading can be evaluated theoretically. The Hilbert–Huang transform method is applied for extracting properties of the experimental electromagnetically induced acoustic emission signals. The results showed that the correlation coefficients between the original signals and the intrinsic mode function components, as well as the instantaneous frequency of the intrinsic mode function, depended on the crack orientations. Hence, experimental results and analysis confirm that the crack orientation can be monitored by the crack-induced intrinsic mode function extracted from the electromagnetically induced acoustic emission signals.