Location

Snowbird, UT, USA

Start Date

1-1-1999 12:00 AM

Description

Ultrasonic testing for fatigue crack detection in metallic members are commonly performed using time domain analysis of Rayleigh waves. This approach will be successful only if the fatigue cracks produce strong interaction with the Rayleigh waves. The optimum frequency range of ultrasonic Rayleigh waves for scanning long structural members in the field is from 0.5 to 2.25 MHz because higher frequencies will not travel long distances. However, this frequency range may not always result in strong interaction with fatigue cracks. Hence, the data analysis procedure for characterizing such signals should provide enhanced sensitivity. Several authors have reported the advantages of using frequency domain analysis for detecting flaws [1–3]. This paper demonstrates the use of spectral analysis for detecting fatigue cracks in metallic members. The paper includes results from both direct-transmission and pulse-echo tests. Since Rayleigh waves are significantly affected by surface conditions, this study included crack detection in both painted and unpainted members.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

18B

Chapter

Chapter 6: Materials Characterization

Section

Cracks and Corrosion

Pages

1771-1777

DOI

10.1007/978-1-4615-4791-4_227

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

Fatigue Crack Detection in Metallic Members Using Spectral Analysis of Ultrasonic Rayleigh Waves

Snowbird, UT, USA

Ultrasonic testing for fatigue crack detection in metallic members are commonly performed using time domain analysis of Rayleigh waves. This approach will be successful only if the fatigue cracks produce strong interaction with the Rayleigh waves. The optimum frequency range of ultrasonic Rayleigh waves for scanning long structural members in the field is from 0.5 to 2.25 MHz because higher frequencies will not travel long distances. However, this frequency range may not always result in strong interaction with fatigue cracks. Hence, the data analysis procedure for characterizing such signals should provide enhanced sensitivity. Several authors have reported the advantages of using frequency domain analysis for detecting flaws [1–3]. This paper demonstrates the use of spectral analysis for detecting fatigue cracks in metallic members. The paper includes results from both direct-transmission and pulse-echo tests. Since Rayleigh waves are significantly affected by surface conditions, this study included crack detection in both painted and unpainted members.