BOXMAP - NON-INVASIVE DETECTION OF CRACKS IN STEEL BOX GIRDERS

This paper presents BOXMAP technology, which has been developed by Physical Acoustics Limited and Cardiff University over the past 5 years, as a proven method for locating cracks in steel bridges. The methodology for monitoring structures is described in detail, highlighting strategic and practical considerations for the client and the engineer. These include access requirements, structural investigation and the filtering of any extraneous "noise" from crack data. One of the main benefits comes from data collected from continuous or intermittent monitoring, which can be used as structural fingerprints. These fingerprints can then be compared at regular intervals and the change in condition and/or rate of crack growth determined. This provides qualitative and quantitative information, from which repairs can be ranked and a priority-based maintenance strategy developed. The overall benefit is reduced whole life costs. Several monitoring strategies have been developed for investigations on different structural scales: (1) "Global" monitoring - Identifying the presence of active defects in steel box girders and I-beams with a minimum number of sensors over long distances; (2) "Semi-Global" monitoring - Accurate location and identification of individual cracks, a 100% volumetric test technique; and (3) "Local" area monitoring - Precise location, identification and measurement of known cracks. Details about the strategy, capabilities and limitations of each of the levels of monitoring are presented, along with examples from laboratory tests and bridge trials with particular emphasis on source location and characterisation. For the covering abstract see ITRD E106406.

Language

  • English

Media Info

  • Features: References;
  • Pagination: p. 80-7

Subject/Index Terms

Filing Info

  • Accession Number: 00801541
  • Record Type: Publication
  • Source Agency: Transport Research Laboratory
  • ISBN: 0-7277-2854-7
  • Files: ITRD
  • Created Date: Nov 8 2000 12:00AM