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Journal Articles

Extracting Quantitative Information on Pipe Wall Damage in Absence of Clear Signals From Defect

Amit Shelke, Umar Amjad, Milos Vasiljevic, Tribikram Kundu, Wolfgang Grill

Publisher: ASME

J. Pressure Vessel Technol. October 2012, 134(5): 051502.

https://doi.org/10.1115/1.4005877

Published Online: September 10, 2012

... inspection technique even today, especially when the transducers cannot come in direct contact with the pipe wall. The current technological challenges for pipe inspection by generating guided waves using noncontact transducers are to detect a small defect on the pipe wall and estimate its location and size...

View Article titled, Extracting Quantitative Information on Pipe Wall Damage in Absence of Clear Signals From Defect

Topics: Pipes, Signals, Wave packets, Waves, Damage, Transducers

Journal Articles

Pipe Wall Damage Detection in Buried Pipes Using Guided Waves

Rais Ahmad, Sourav Banerjee, Tribikram Kundu

Publisher: ASME

J. Pressure Vessel Technol. February 2009, 131(1): 011501.

https://doi.org/10.1115/1.3027460

Published Online: November 25, 2008

.... , and Kundu , T. , 2000 , “ A New Sensor for Pipe Inspection by Lamb Waves ,” Mater. Eval. 0025-5327 , 58 ( 8 ), pp. 991 – 994 . Guo , D. , and Kundu , T. , 2001 , “ A New Transducer Holder Mechanism for Pipe Inspection ,” J. Acoust. Soc. Am. 0001-4966 10.1121/1.1377289 , 110 ( 1...

View Article titled, Pipe Wall Damage Detection in Buried Pipes Using Guided Waves

Topics: Pipes, Wavelet transforms, Waves, Soil, Damage

Journal Articles

Defect Classification in Pipes by Neural Networks Using Multiple Guided Ultrasonic Wave Features Extracted After Wavelet Processing

Piervincenzo Rizzo, Ivan Bartoli, Alessandro Marzani, Francesco Lanza di Scalea

Publisher: ASME

J. Pressure Vessel Technol. August 2005, 127(3): 294–303.

https://doi.org/10.1115/1.1990213

Published Online: January 27, 2005

...Piervincenzo Rizzo; Ivan Bartoli; Alessandro Marzani; Francesco Lanza di Scalea This paper casts pipe inspection by ultrasonic guided waves in a feature extraction and automatic classification framework. The specific defect under investigation is a small notch cut in an ASTM-A53-F steel pipe...

View Article titled, Defect Classification in Pipes by Neural Networks Using Multiple Guided Ultrasonic Wave Features Extracted After Wavelet Processing

Topics: Artificial neural networks, Damage, Inspection, Pipes, Signals, Wavelets, Waves, Feature extraction, Reflection, Steel

Journal citation

NARROW

Extracting Quantitative Information on Pipe Wall Damage in Absence of Clear Signals From Defect

Pipe Wall Damage Detection in Buried Pipes Using Guided Waves

Defect Classification in Pipes by Neural Networks Using Multiple Guided Ultrasonic Wave Features Extracted After Wavelet Processing

ASME Journals

ASME Conference Proceedings

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Extracting Quantitative Information on Pipe Wall Damage in Absence of Clear Signals From Defect

Pipe Wall Damage Detection in Buried Pipes Using Guided Waves

Defect Classification in Pipes by Neural Networks Using Multiple Guided Ultrasonic Wave Features Extracted After Wavelet Processing

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

Opportunities

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