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dc.contributor.advisorKim, Jeonghee
dc.contributor.advisorGoulart, Ana
dc.creatorLopez, Cameryn Summer
dc.date.accessioned2023-02-07T16:19:08Z
dc.date.available2024-05-01T06:06:26Z
dc.date.created2022-05
dc.date.issued2022-04-11
dc.date.submittedMay 2022
dc.identifier.urihttps://hdl.handle.net/1969.1/197339
dc.description.abstractUncertainty of the precise location of underground pipelines poses a safety risk to excavator operators and nearby construction workers. Excavator collisions with pipeline carrying hazardous material can result in significant injuries or fatalities along with increased project time for repair. The current methods for warning operators of nearby pipelines only provide the approximate location. There is then a need for locating the pipeline in real-time and properly alerting excavation operators of the proximity of the machine to a pipeline. Several methods have been implemented for underground object detection: ground penetrating radar (GPR), electromagnetic signal generation, acoustic excitation, and magnetic anomaly detection (MAD). Among these methods, MAD has been found to be the most suitable for the case of a moving sensor and stationary ferromagnetic target. MAD exploits the magnetic anomaly created by large ferromagnetic material to locate underground structures. A magnetic anomaly is detected when the measured geomagnetic field deviates from its expected value at a particular point. Current magnetic anomaly inversion techniques are complex and time-consuming, and thus implementation at excavation jobsites is not practical. The work described in this paper utilizes two magnetometers to cancel the geomagnetic background and effectively estimate the proximity to a steel pipeline in real-time.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectmagnetic anomaly
dc.subjectmagnetometer
dc.subjectexcavation damage
dc.titlePipeline Collision Avoidance for Excavation Work Using Magnetic Anomaly Detection (MAD)
dc.typeThesis
thesis.degree.departmentMultidisciplinary Engineering
thesis.degree.disciplineEngineering Technology
thesis.degree.grantorTexas A&M University
thesis.degree.nameMaster of Science
thesis.degree.levelMasters
dc.contributor.committeeMemberHam, Youngjib
dc.type.materialtext
dc.date.updated2023-02-07T16:19:08Z
local.embargo.terms2024-05-01
local.etdauthor.orcid0000-0002-2090-5670


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