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Ultrasonic guided waves have been widely used to monitor straight tubes because of their applicability to full-volume inspection at long distances. However, the use of ultrasonic guided waves is limited when inspecting tubes with bends. Bends in tubes distort the propagation of guided waves and cause a reflection. Reflection signals from the bends and any discontinuities in the bend overlap each other, thereby hindering the inspection of bends. A technique for inspecting for discontinuities in bends is obviously needed. In this study, the sensitivity of guided waves to discontinuities at different bend locations is investigated through a numerical simulation technique. A technique for comparing frequency responses is proposed to inspect for discontinuities in bends. The frequency responses of the reflection signals of full bends and bends with discontinuities are obtained from the modal assurance criteria for different guided wave modes and inspection signals of different center frequencies. If two frequency responses are similar, then no discontinuities exist in the bend region. The technique is validated by numerical simulations and experimental results. [ABSTRACT FROM AUTHOR]

Recently the use of ultrasonic guided wave for detecting has become attractive in nondestructive testing. The axial length of the pipe discontinuity is not linear with the guided wave signal amplitude. Thus, it is difficult to identify the degree of damage using the reflection coefficient. In order to explore the relationship between the guided wave signal and the discontinuity length, an ultrasonic processing and pattern recognition tool is studied. The characteristic information of the guided wave signal is extracted by wavelet packet decomposition technique. Several temporal characteristics on each scale are combined to a feature set. In order to reduce the computational complexity, the dimension of the feature set is reduced by the kernel sliced inverse regression (KSIR) algorithm. A pattern recognition model, the continuous hidden markov model (CHMM), is introduced to classify and identify different states of the pipe by pre-trained models. Comparing to the log-likelihood probability calculated by all classifiers, the maximum value corresponds to the right state. A guided wave test to a pipe with artificial corrosion on the outer surface was conducted to verify the correctness of the algorithm. Five discontinuity levels were identified correctly, achieving the objective of preliminary quantitative evaluation. The results show that the CHMM model is more robust and can accurately identify the axial discontinuities. [ABSTRACT FROM AUTHOR]