Magnetoquasistatic sensors for rapid imaging of steel pipeline properties

Denenberg, Scott A.

Permalink

https://hdl.handle.net/2142/50452 Copy

Description

Title

Magnetoquasistatic sensors for rapid imaging of steel pipeline properties

Author(s)

Denenberg, Scott A.

Issue Date

2014-09-16

Director of Research (if dissertation) or Advisor (if thesis)

Cangellaris, Andreas C.

Doctoral Committee Chair(s)

Cangellaris, Andreas C.

Committee Member(s)

• Bernhard, Jennifer T.
• Jin, Jianming
• Kamalabadi, Farzad

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Corrosion Under Insulation (CUI)
• Magnetoresistive Sensors
• Meandering Winding Magnetometer (MWM)
• Meandering Winding Magnetometer (MWM)-Array
• Magnetoresistive Meandering Winding Magnetometer (MR-MWM)-Array
• Magnetoquasistatic Sensors

Abstract

The purpose of this research effort is to advance the capabilities of existing model-based spatially periodic magnetoquasistatic-field sensors in order to provide a solution for imaging the metallic properties of pipelines. The target problem addressed is rapidly imaging pipeline steel thickness through thick insulation and weatherjacketing materials in order to detect areas of corrosion. The following bullet points outline the advancements in sensor design, sensor electronics and electromagnetic models necessary to develop a corrosion under insulation (CUI) inspection tool. 1. Development of sensor and sensor electronics with sufficient sensitivity for steel thickness imaging. A fundamental problem with rapidly imaging steel thickness through thick coatings is achieving a sufficient signal to noise ratio (SNR). SNR is a function of sensor design and sensor electronics. Many possible sensing approaches are evaluated theoretically, leading to the development of magnetoresistive sense elements in a quasi-periodic drive structure. 2. Development and validation of cylindrical geometry models for inductive sensors. The existing models for inductive spatially periodic magnetoquasistatic-field sensors assume a planar layered medium geometry. Work has been done to extend this to a circularly symmetric planar layered medium, but the problem of a cylindrically layered medium, as seen in pipelines, has not been approached. Validation will show the needed improvement in agreement between the models and measurements taken with magnetoresistive sensors wrapped around cylindrical specimens. Models are developed and implemented for low-frequency applications, such as the detection of steel thickness, for sensors with the main drive legs aligned circumferentially around the pipe as well as for sensors with the main drive legs aligned axially. 3. Modeling of sensor interaction with local material deviations. The models developed for magnetoquasistatic-field sensors assume a uniformly layered medium. This assumption breaks down in the presence of local defects such as corrosion pitting and weatherjacket overlaps. A model is developed to better understand the footprint of the sensor as the magnetic fields diffuse through material layers. This model provides insight leading to a more effective design of magnetoquasistatic-field sensors with reduced unmodeled effects and increased scanning resolution. 4. Model-based correction for flawed regions to improve flaw sizing. For flaws smaller than the sensor footprint and for flaws with sharp edges, there is a deviation from the uniform-layered medium model. The same footprint model used to design a sensor with enhanced resolution can be further used to provide a more accurate assessment of flaw depth. This dissertation details the research completed in the process of designing a CUI inspection tool. The methodology used has proved successful in meeting the target requirements.

Graduation Semester

2014-08

Sponsor(s)/Grant Number(s)

This research effort was sponsored by JENTEK Sensors, Inc.

Permalink

http://hdl.handle.net/2142/50452

Copyright and License Information

Copyright 2014 Scott Denenberg

Owning Collections