Empirical modeling of acoustic signal attenuation in municipal sewer pipes for condition monitoring applications
An important challenge for a smart city is to prevent occurrence of sewer system overflows (SSOs) that can degrade the environment and pose a public health hazard. To prevent SSOs, timely detection and cleaning of clogged sewer pipes is essential. Present industry standard to detect sewer blockage is based on passing a close circuit television (CCTV) mounted crawler through the pipes. An operator observes the video and annotates it based on the condition of a pipe. This system is complex, expensive and man-hour intensive. There is a need to develop an acoustic based method that can replace the traditional CCTV based system. Clogged pipes cause severe attenuation on acoustic signals which can be used as a measure of existence and extent of blockage. This study reports an empirical based approach to determine acoustic signal attenuation in sewer pipes. Extensive field measurements were made in Charlotte, North Carolina to collect in-pipe signal propagation data from installed sewers to support this work. The findings were used to justify further research and development by a technology startup company that successfully produced an acoustic based sewer line blockage detection system. © 2018 IEEE.
IEEE Green Technologies Conference
Khan, M. S. (2018). Empirical modeling of acoustic signal attenuation in municipal sewer pipes for condition monitoring applications. Proceedings from 2018 IEEE Green Technologies Conference (GreenTech): 137-143. doi: 10.1109/GreenTech.2018.00033.