ResearchBib Share Your Research, Maximize Your Social Impacts
Sign for Notice Everyday Sign up >> Login

Source of Uncertainty in Water Supply Pipeline Leak Detection Using District Meter Area Data

Journal: International Journal of Scientific Engineering and Research (IJSER) (Vol.2, No. 3)

Publication Date:

Authors : ;

Page : 10-17

Keywords : Water Supply Data Bases; SCADA; AMR; AMI; DMA; Multi-Parameter Sensors Sources of Uncertainty; Uncertainty Quantification; Uncertainty Calibration; Uncertainty Reduction;

Source : Downloadexternal Find it from : Google Scholarexternal


The use of multi parameter sensors for the day to day operational and management activities become an essential component of leading water utility companies in the effort to modernize their water distribution pipeline networks systems. With the widespread deployment of multi-parameter sensors to monitor water distribution pipeline networks operational activities, allows vast amount of data to be collected, analysed, and acted upon in the shortest periods of time. These multi-parameter sensors not only respond to the change of operational pattern to produce data, they also embed with computing and communication capabilities. These systems are able to store, process locally and transfer data they produce to the water utility companies? main database. During these processes there are strong possibilities that data tends to become uncertain. These uncertainties can be originated from different components of multi-parameter sensors used in DMA, such as SCADA, AMR, AMI, data collection error, measurement precision limitation, data sampling error, outdated source, data acquisition and transmission error?etc. Multi-parameter sensors used inside DMA like any other devices are subject to wear and tear, or mal functioned or system failure that leads to inaccuracy with time. Therefore the primary goal of this paper is to transfer knowledge among water utility professionals, by highlighting the potential sources and types of uncertainty DMA data used for water distribution system (WDS) pipeline leak detection, and address them using an appropriate uncertainty analysis tools to determine a more accurate and reliable result by increasing DMA data quality.

Last modified: 2021-07-08 15:10:37