Accident prevention through equipment-mounted buried utility detection.
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2005/08/31
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By Bernold LE
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Description:The demand for new buried utilities is growing with new construction, re-construction, and the growth of the subsurface infrastructure worldwide. As a result, contractors are busy digging and drilling into the ground in order to bury new pipes. Because the machinery for placing the new utilities underground, such as backhoe excavators, trenchers, augers, drills, and plows, cannot sense when they are getting close to already buried objects, utilities are easily damaged, possibly leading to electrocutions or gas explosions. Despite great efforts in locating existing utilities before a contractor is allowed to dig, accidents of all kinds occur in great numbers. This paper will discuss a multi-sensor approach to detecting and locating various kinds of utilities using a combination of electromagnetic induction (EMI) and ground penetrating radar (GPR). While the EMI detects metallic material, the GPR is capable of finding concrete ducts and pipes made of non-ferrous material. The two sensory systems have been integrated into a mobile unit and a system that mounts directly onto a digging machine. This paper will describe the integrated system, describe the sensors, and show how the system was used to successfully support an excavating contractor working on a chilled water distribution system on a university campus. [Description provided by NIOSH]
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ISBN:1886431094
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Pages in Document:1-11
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NIOSHTIC Number:nn:20029398
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Citation:Trends and current best practices in construction safety and health. Hinze J, ed. Gainesville, FL: IeJC, 2005 Aug; :1-11
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Federal Fiscal Year:2005
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Performing Organization:North Carolina State University, Raleigh, North Carolina
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Peer Reviewed:False
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Start Date:20010930
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Source Full Name:Trends and current best practices in construction safety and health
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End Date:20050531
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Main Document Checksum:urn:sha-512:7dc847c09aedf140bc731323e8446b4703641ae07d6ad9e7b7238120dab30b8f7dcaa9b938d34d035f87873a0fe7fec262d5d13dcaf290925445e82b6de3b57d
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