Acoustic and vibration methods for condition assessment of sewer networks – Smart Sewers (2024-2026)

The overall goal of this project is to investigate the potential of using vibration and acoustic measurements for condition assessment of sewer networks and, ultimately, to develop a method that continuously assesses the condition of the pipes using real-time measurements and machine learning algorithms.

Condition assessment of water and sewer pipe networks is time-consuming and costly, partly because they are underground. At the same time, parts of these networks are ageing and have structural problems such as leaks, sags, and corrosion. This in turn leads to operational problems. A significant issue is that sewer pipes have cracks, joint misalignments and other structural problems, allowing groundwater, precipitation, and drinking water from leaky water pipes to seep into the sewer pipes. This infiltration and inflow correspond to the same amount as the wastewater produced in households and other operations. That is, twice as much water that is transported, pumped, and treated in Sweden, due to substandard pipes in the sewer network. This leads to increased electricity and chemical use for transportation and treatment. Furthermore, these inflows of additional water cause overflows of untreated sewage into lakes and rivers. Poor condition of the network can also lead to sediment deposits and sewage blockages, which in turn can cause basement flooding.

Today's most accepted technique for condition assessment of sewers is a Closed Circuit video camera (CCTV) that is manually lowered into the network and films the pipes while an operator simultaneously observes and assesses pipe defects. This is time-consuming, costly, and subjective. A goal for a medium-sized municipality might be to return and film the pipes every ten years. In smaller municipalities with limited resources, the status of the pipes has never been systematically examined since they were laid down several decades ago. Therefore, there is a need to investigate and develop other methods for faster and cheaper condition assessment. One such method could be to perform vibration measurements and acoustic analysis of the network. An advantage of such a method is that it does not require entry into the network and faster condition assessment. In this way, it would be easier for water and sewer organizations to work with proactive maintenance. Acoustic methods have been previously used to find leaks in drinking water networks and gas pipelines. Acoustic methods have also been developed to investigate and assess the status of, for example, dam and bridge structures. However, there are currently no acoustic or vibration methods for assessing the condition assessment of sewer networks.

In this project, a method will be developed to collect and analyse vibration and acoustic data primarily from gravity sewers. This work includes selecting suitable sensors and frequency ranges and performing modelling of collected data. Furthermore, the chosen method will be tested on a pipe network set up in a lab to identify typical patterns that the signals give for various types of structural pipe defects. Based on the results from the lab, the method will also be tested in the field. There, we will make acoustic measurements on pipes that have also been flushed and filmed. The results from the acoustic measurements will be compared with the results from the CCTV inspections.

This project will be conducted in collaboration between Luleå University of Technology and the Water and Sewer departments of Boden municipality, as well as the water companies MittSverige Vatten & Avfall, Tekniska verken in Linköping, and Lumire. Luleå University of Technology is represented by researchers from Urban Water Engineering and Acoustic Engineering. A doctoral student will be employed and attached to the project. The doctoral student will also collaborate with the PostDoc financed by the project VA-NET, also led by Urban Water Engineering at Luleå University of Technology.

The project is funded by the Swedish research council Formas and the time period of the project is 2024 to 2026.