Proof-of-principle of Distributed Acoustic Sensing (DAS) for detection of sewer defects, extraneous water intrusion and sewage exfiltration.

Abstract

Extraneous water intrusion and sewage exfiltration due to sewer defects are difficult to detect. This study presents a potentially effective sewer defect diagnosis method, namely, the distributed acoustic sensing (DAS) framework. Firstly, a proof-of-principle study was performed using a 5-m sewer model for DAS signal analysis. Controlled intrusions were applied with defined flow rate and fall height, under defined static and dynamic background flows. Under laboratory conditions, pouring-induced intrusion events generated localized transient strain impacts with clear time- and frequency-domain fingerprints, enabling DAS to localize the impact region and distinguish between inflow-side and manhole-side responses. For exfiltration, time-domain responses of the DAS signals were too weak, but upon amplification of the power spectral density (PSD) between 20 and 30 Hz, leakages were detected by consistent and localized amplified signals under experimental scenarios. Secondly, a field test was conducted on an 800-m sanitary sewer in operation. Despite urban noise interference, statistical screening of amplified PSD signals between 20 and 30 Hz identified recurrent mid-level events to be associated with two candidate defective segments, which were later confirmed. These results provide an initial proof-of-principle field demonstration, but the field evidence remains limited and further validation is still required before broader engineering applicability.