Decision-Support System for the Rehabilitation of Deteriorating Sewers
| Autor: | Christos Emmanouilidis, Kostas Gratsias, D. Bairaktaris, S. Frondistou-Yannas, Vasilis Delis, N. Rerras, V. Kallidromitis |
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| Rok vydání: | 2007 |
| Předmět: |
Decision support system
Engineering Geographic information system Rehabilitation Artificial neural network business.industry medicine.medical_treatment Building and Construction computer.software_genre Automation Expert system medicine Information system Data mining Sanitary sewer Safety Risk Reliability and Quality business computer Civil and Structural Engineering |
| Zdroj: | Journal of Performance of Constructed Facilities. 21:240-248 |
| ISSN: | 1943-5509 0887-3828 |
| DOI: | 10.1061/(asce)0887-3828(2007)21:3(240) |
| Popis: | This paper describes an automated and integrated detection, structural assessment, and rehabilitation method selection system for sewers based on the processing of video footage obtained by closed circuit television surveys. The system is based on a neural network classifier (NNC) trained to identify longitudinal cracks in sewers. Results obtained from experimentation with the NNC indicate that crack detection based on single-frame processing is not sufficient, and frame sequence processing substantially improves crack recognition rates. Based on the location of the cracks, local and global structural damage is assessed and a rehabilitation method is selected. Based on the significance of damaged sewers, the rehabilitation projects are being prioritized. An expert system coordinates the various modules in the system and connects them to a geographic information system. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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