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Pipeline Flaw Detection Using Shear EMAT and Wavelet Analysis
Project Number

The goal of this project is to develop an Electromagnetic Acoustic Transducer (EMAT) sensor, capable of detecting physical flaws in the wall of a 30-inch natural gas pipeline. These physical flaws include: stress corrosion cracking (SCC), circumferential and axial flaws, and corrosion. In addition, work will be conducted to design, fabricate, test, and integrate the EMAT sensor with an autonomous robotic platform, providing a flexible in-line inspection tool for natural gas pipeline examination. 

ORNL PIG with EMAT sensors for inspecting a 30-inch diameter pipe
ORNL PIG with EMAT sensors for inspecting a 30-inch diameter pipe
ORNL Pig with EMAT sensors and resolver mounted inside a 30 inch pipe
ORNL Pig with EMAT sensors and resolver mounted inside a 30 inch pipe



Oak Ridge National Laboratory (ORNL) – project management and research product

Oak Ridge, Tennessee 37831


The integrity of gas pipelines need to be monitored frequently by pipeline operators to mitigate potential hazardous conditions. With more than 90% of the pipelines buried underground, locating potential flaws is a major challenge. In-line inspection technologies are necessary to locate the flaws without having to resort to excavation.

SCC is usually oriented along the axial length of the pipe and may remain undetected. If this occurs, the cracks may grow and/or coalesce and eventually lead to a leak or pipe rupture. Non-destructive inspection (NDI) systems such as EMAT are vital tools for the early location of SCC and other defects (i.e. corrosion, welding cracks, pits). It is important, however, that such tools be capable of accurately detecting SCC without false alarms and with some characterization of the size of the defects.

Stress corrosion cracks in pipes are influenced by both environment and stress. Initially, corrosion begins when water comes into contact with steel at points where the bond between the protective coating and steel has been broken. Without stress, the corrosion area will not transform into a crack. However, once the effects of cyclical loading, temperature, residual stress, and bending load act on the initial corrosion site, a crack or a colony of cracks can develop. Cracks in the pipelines can reduce the integrity of the pipe, and hence reduce its potential service life.

In a laboratory environment, SCC’s can be easily detected using liquid fluorescent magnetic particle inspection. However, this technique is not practical for in-line inspection of pipes. Magnetic flux leakage (MFL), which is a mainstay of the in-line pipe inspection industry, has difficulty detecting axially oriented cracks. Although there have been some developments in the area of liquid–filled wheel probes using ultrasonic shear waves, they do yet not offer reliable detection of cracks.

Oak Ridge National Laboratory (ORNL) is developing a shear horizontal (SH) wave electromagnetic acoustic transducer (EMAT) system for the inspection of pipelines. The SH–mode EMAT is used in a circumferentially oriented configuration, since the main objective of this system is to detect SCC’s that are axially oriented along the length of the pipes. This project is designed to develop the EMAT technique as an alternative tool to detect SCC’s.


The EMAT sensor under development will be capable of detecting numerous pipeline anomalies, including stress corrosion cracking, recently identified as a defect that could promote pipeline failure. Coupled with an autonomous robotic platform, the integrated sensor will have the ability to examine a large fraction of currently un-inspectable natural gas pipelines.

Accomplishments (most recent listed first)
  • Obtained a new 30"diameter (0.375" wall thickness) machined pipe with calibrated flaws. Half the flaws are rectangular in nature manufactured with a plunger EDM machine while the other half is parabolic machined with a circular saw. The depths of the flaws vary from 10% of the wall thickness to 75% of the wall thickness. The thickness of the flaws vary from 0.008" to 0.020". These samples were used to conduct measurements with the ORNL EMATs that will allow better calibration of the EMAT sensors.
  • Contracted a private company, Pfinde, Inc., from Connecticut to measure SCC cracks on the Battelle 1093 pipe, which was used to take measurements during the first sensor demonstration in FY2004. This will provide independent correlation of the results from the ORNL EMAT and the FAST (Flaw analysis and sizing technique) method used by Pfinde. This will also define the limitation of the ORNL EMAT in detecting SCC's.
  • ORNL participated in the Sensor Demonstration conducted at Battelle in January 2006. The ORNL EMAT was the only technology tested for the detection of stress corrosion cracking. The ORNL EMAT inspection tool acquired data as it was continuously pulled through a 26-inch diameter pipe with natural stress corrosion cracking, at the rate of about an inch per second. Three separate test lines were analyzed. ORNL took multiple scans to assess the consistency of the signal. Results were not displayed in real time; ORNL post processed the captured data to develop final results. The EMAT technology detected one false positive signal on each test line. The configuration of the SCC defects could have contributed to the false positive readings. Because the EMAT configuration scans a minimum of 9-inches of the pipe’s circumference, some of the false positives could have been the result of other cracks located in close proximity to the SCC defects under evaluation. Only one defect site provided no discernable signal; however magnetic particle analysis showed that these cracks were small and difficult to detect. Additionally, the identified location of one crack colony was off by a couple of inches. The most significant cracks in the test sample were detected by the ORNL Shear Horizontal EMAT technology.
  • The ORNL EMAT inspection tool performed very well during the Sensor Demonstration. One potential reason for the errors in detection could be related to the fact that the current ORNL set-up for detecting SCCs with the shear horizontal wave EMAT compares signals from ‘no-flaw’ regions with signals from ‘flaw’ regions to identify cracks. This approach requires training data from runs through known defect and no-defect regions. Unfortunately, a proper training set for a 26-inch pipe was not available. It is believed that the system performance would have only improved had a training set generated out of similar pipe geometry been used.
  • The ORNL EMAT inspection tool identified a false positive (flaws were there were none) on each scan line, and this could be the result of not having the algorithm needing further refinement. Lack of good natural SCC data has been one of the difficulties faced while developing this technology. Synthetic SCCs created using electrical discharge machining do not give a signature truly characteristic of a natural SCC.
Current Status

The fundamental development and fabrication of the EMAT sensor is complete. This project is concluded.

Project Start
Project End
DOE Contribution

$260,000 (FY05)

Performer Contribution


Contact Information

NETL – Daniel Driscoll ( or 304-285-4717)
ORNL – Venugopal Varma ( or 865-574-7156)

Additional Information

April, 2006: Pipeline Inspection Technologies Demonstration Report [PDF-7.29MB]

Pertinent Publications:
“Pathways for Enhanced Integrity, Reliability, and Deliverability”, Workshop Proceedings, September 2000, NETL, Office of Fossil Energy, U.S. Department of Energy.

“Roadmap Update for Natural Gas Infrastructure Reliability”, Workshop Proceedings, January 2002, NETL, Office of Fossil Energy, U.S. Department of Energy.

“Roadmap Update II, Natural Gas Infrastructure R&D delivery Reliability Program,” Workshop Proceedings, –National Energy Technology Laboratory, U.S. Department of Energy, Phoenix, Arizona, February 8, 2004.

“Pipeline Flaw Detection Using Shear EMAT and Wavelet Analysis”, Varma, V.K, Tucker, R., Kercel, S., Rose, J., Luo, W., and Zhao, X., GTI's Natural Gas Technologies II, February 8-11, 2004.

“Characterization of gas pipeline flaws using wavelet analysis”, Tucker, R.W., Kercel, S.W., and Varma, V.K, QCAV (Quality Control Using Artificial Intelligence), Gatlinburg, TN, May 2003.

“Pipeline flaw detection with wavelet packets and Gas”, Kercel, S.W, Tucker, R.W., and Varma, V.K, SPIE 2003.