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Application of GPR in urban utility detection ranging and characterization

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dc.contributor.author Hebsur, AV
dc.contributor.author Muniappan, N
dc.contributor.author Rao, EP
dc.contributor.author Venkatachalam, G
dc.date.accessioned 2013-11-11T18:18:50Z
dc.date.available 2013-11-11T18:18:50Z
dc.date.issued 2013-11-11
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/8978
dc.description.abstract Keeping track of underground utilities through maps or real physical signs is essential for their maintenance and quick repairs, whenever required, without causing much obstruction to day to day life. It is not uncommon that maps are misplaced or real physical signs are destroyed. In such situations, digging and excavation becomes unavoidable during repair works. Ground penetrating radar (GPR) is one of the non invasive methods which now are being applied for detection, ranging and characterization of subsurface buried objects. GPR employs radar pulses, sends them into ground, then get back scattered energy from dielectric discontinuities in the subsurface. Frequency of antennae determine their capacity to detect and resolve the buried objects (depth of penetration is worth a mention). Hence, 400MHz and 200MHz frequency antennae are generally used for utility mapping at shallow depths up to 4 to 5 meters. GPR response to buried objects is very much dependent upon buried object locations, their constituents, their surroundings and antennae properties. It is very crucial to have a database of GPR responses corresponding to various influencing factors over their ranges of variability either by experimental or simulation studies. In the present work, an attempt has been made to generate data so as to know the dependence of GPR responses on changes in the influencing factors. Simulations have been carried out by using exclusive GPR simulation software called GPRMax. Several typical ground scenarios have been simulated and effects of various object, medium and antennae parameters on response of GPR have been studied and relationships have been established between them using response surface method (RSM). Finally, real GPR data has been compared with simulated data and interpreted. en_US
dc.language.iso en en_US
dc.subject Urban utilities en_US
dc.subject Buried objects en_US
dc.subject GPR, Simulation en_US
dc.subject Response Surface Method en_US
dc.title Application of GPR in urban utility detection ranging and characterization en_US
dc.type Conference-Full-text en_US
dc.identifier.year 2012 en_US
dc.identifier.conference ICSBE-2012: International Conference on Sustainable Built Environment en_US
dc.identifier.place Kandy, Sri Lanka en_US
dc.identifier.email almelu@iitb.ac.in en_US
dc.identifier.email muniappan@iitb.ac.in en_US
dc.identifier.email ceepria@iitb.ac.in en_US
dc.identifier.email gvee@iitb.ac.in en_US


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