Paper
10 June 2005 UXO location and identification using borehole magnetometery
Qing Zhang, Waleed Al-Nuaimy, Yi Huang, Jon Gascoyne
Author Affiliations +
Abstract
It is estimated that 10% of war-time bombs did not explode and can be found at the ground surface or buried at a depth of up to 8 meters depending on the formation of the soil. These unexploded bombs or ordnance (UXO) pose a real danger to construction workers and properties. Ground surface based methods become ineffective for objects sinking into deep places due to rapidly diminishing anomalous field and interfering metal debris distributed over ground surface. To overcome the difficulties, a unique inversion algorithm is proposed in this work with advantages of fast convergence and maximization of information extracted from individual hole measurement. It is more reliable than traditional methods by examining the possibilities within a number of estimations. The information from individual hole measurement is fully interpreted hence suggestion can be made for the positioning of next drilling in order to minimize the number of holes required for clearance. Based upon the recovered information, a comparison method is proposed for the identification and discrimination of UXO items from other objects that may be found in the environment, such as steel pipes and steel barrels. It is not sensitive to the interference in the data once the dipole moment is recovered. The results from a test site demonstrates its supreme capability to deal with real-world inversion problems having small number of available data points.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qing Zhang, Waleed Al-Nuaimy, Yi Huang, and Jon Gascoyne "UXO location and identification using borehole magnetometery", Proc. SPIE 5794, Detection and Remediation Technologies for Mines and Minelike Targets X, (10 June 2005); https://doi.org/10.1117/12.603445
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Cited by 1 scholarly publication.
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KEYWORDS
Magnetism

Data modeling

Modeling

Explosives

Metals

Tolerancing

Unexploded object detection

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