An approach for crack detection in sewer pipes using acoustic signals
This study investigates use of acoustic signals to detect cracks in polyvinyl chloride (PVC) sewer pipes. Cracked sewer pipes can result in release of untreated human and industrial waste, toxic materials and debris affecting human health and the environment. The released toxic effluents can pollute water reservoirs and damage public and private property. Polyvinyl Chloride (PVC) pipes have been extensively used in sewer systems for the past several decades. These pipes fail due to improper installation and engineering, incorrect operation, internal and external contamination, manufacturing defects and abuse by the users. Existing industry standard for crack detection in sewer pipes is based on a Closed-circuit television (CCTV) mounted crawler that passes through the sewer pipes and relays the video to an operator who visually observes and records the presence of cracks. This method requires a special vehicle, an electric generator, a reel-mounted data link cable and a customized software with a dedicated control system. There is a need for developing a system that can be easily deployable, economical and consistent in detecting cracks in pipes. The aim of this project is to analyze and relate attenuation in the acoustic signal to the condition of a pipe sample. Extensive empirical testing has been conducted on 0.1 m diameter PVC pipes with and without cracks. The preliminary results show that acoustic frequencies between 800 Hz-1.2 kHz are severely attenuated due to signal loss from cracks. Further testing in the laboratory and field is in progress to classify the location and extent of cracks in pipes. The findings from the study can be used to develop an acoustic based pipeline crack detection application. © 2017 IEEE.
GHTC 2017 - IEEE Global Humanitarian Technology Conference, Proceedings
Khan, M. S. (2017). An approach for crack detection in sewer pipes using acoustic signals. 2017 IEEE Global Humanitarian Technology Conference (GHTC) Proceedings: 1-6. doi: 10.1109/GHTC.2017.8239242.