AE source localization and imaging on cylindrical shell structures based on six-AE-sensor monitoring network and VTR focusing imaging

ABSTRACT

This study is interested in how to utilise the virtual time reversal (VTR) technique to locate the continuous AE source in cylindrical shell structure. Thus, a six-AE-sensor monitoring network was designed to divide cylindrical surface into two symmetric semi-cylindrical monitoring areas whose four vertexes and two geometrical centres were defined as the measuring points. The AE source can be located in certain semi-cylindrical monitoring area whose centre measuring point first captured the emitted AE signal. Besides, the response signals at other four measuring points were used to localise the AE source. To realise the VTR focusing of the AE signals, the proposed method solved two key problems. One is to search the shortest helical path between two arbitrary points on a cylindrical surface, which can provide the shortest distance from AE source to sensor. The other is to extract the specific frequency coefficients of wavelet transform for the continuous AE signal, which can meet with the requirement for the instantaneous abrupt characteristic of the signals to be processed using VTR focusing technique. Finally, a continuous leak experiment was carried out on a gas-filled steel pipe. The corresponding localisation method can accurately estimate the location of the continuous leak source.

KEYWORDS:

• Continuous AE source
• virtual time reversal
• cylindrical shell structure
• non-destructive testing
• structural health monitoring

Author contributions

S.W., J.W. and J.H. conceived and designed the experiments. D.W. performed the experiments and analysed the data. H.W. and W.Z. contributed materials and analysis tools. S.W. and J.W. proposed the methodology and writing—review & editing.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (NSFC) under Grant [numbers 51565047, 51635010]; Inner Mongolia University of Science and Technology Innovation Fund under Grant [number 2017YQL04]; and Natural Science Foundation of Inner Mongolia under Grant [number 2017MS (LH) 0531].