Data Collection for Loggers

The collection of data from acoustic loggers is done in coordination with the water services agency in the city of Montreal. The agency has placed a series of loggers covering downtown Montreal or the area known as Ville-Marie. The loggers are provided and installed by a company named Guttermann. The state of the loggers and the network can be viewed via an online system named Zonescan. Permitted by the agency, this research collects a substantial number of acoustic signals that cover multiple aspects of the acoustic leak detection spectrum. Additionally, the agency has checked to assess and verify the quality of their currently installed system.

IV.2.1 Zonescan System

The zonescan interface is an online system that connects all the installed acoustic loggers. Through transmitters and online servers, the data is collected and assessed to determine the existence of leaks, the status of the network and the status of the loggers and other devices forming the surveillance network. Figure IV-7 presents one of the interfaces of the zone scan system. This interface represents the status of the loggers regarding power and battery life. Similarly, through another interface, it is possible to detect leaks and collect sound files of the relative leaks. Additionally, through the regular checkups, it is possible to identify new sounds that create interference within the network, such as leak sounds and pump sounds. Another

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interface is the leak detection interface, which presents correlated between multiple sensors to identify the existence and locations of leaks.

Figure IV-7: Zonescan Maintenance Interface

Figure IV-8 shows this interface by showing a detected leak in the vicinity of the Fine Art Museum of Montreal. To detect the leak, the figure shows that two loggers are used and their codes are presented as 507-241 and 507-244. The figure also shows the overall length of the pipeline between the two sensors as well as the predicted distance from each sensor towards the leak. Another presented measure is the distance from the center point between the two sensors towards the leak. The software indicates 100% certainty of the existence of this leak, but this remains to be further investigated as errors may arise from this system and that is one of the main reasons for the conduction of this research. The aim is to increase the reliability of this system through increasing its detection accuracy by eliminating false alarms and increasing its pinpointing accuracy as well.

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Figure IV-8: Zonescan Leak Pinpointing Interface

To pinpoint a leak, the system uses the sound signals collected from the loggers on both ends of the suspected leak. Figure IV-9 shows that the system then moves towards performing a cross- correlation between the two signals for pinpointing purposes. As the figure shows, the software shows that the leak is closer to sensor 507-241 than to its counterpart sensor 507-244. Additionally, the software predicts that the distance from sensor 507-241 towards the leak location is 28.7 meters, whereas the distance from the second sensor, i.e. sensor 507-244, is estimated to be 56.5 meters. The software also indicates that the quality of their assessment is 100% and therefore the leak is highly likely to exist. Multiple situations may have occurred where pump sounds and other factors within the network create leak like conditions, but no leaks are to be found.

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Figure IV-9: Zonescan Leak Cross Correlation Report

IV.2.2 Data Collection

The zonescan interface regularly listens to the underground network to detect sound anomalies within the network. The loggers start listening after 2 AM in the morning to minimize outside interference and noise. After listening for multiple hours, the loggers establish a sense of the ideal state and accordingly identify irregularities. In multiple cases, pump sounds are often assessed as leaks. The initial step is to collect sound files for various states. Therefore, the data is collected over the span of 30 days and various categories of sound files are collected, including leaks, no leaks, possible leaks, pump sounds and valve leaks. The possible leak option is created by the providing company. However, this research aims to eliminate the possible leak response

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as it offers little to no information and adds confusion to the process. Additionally, pump sounds are distinguishable from leak sounds on the micro level because of the variation of the frequency distribution between the two classes of detection.

Over the course of 30 days, various types of sound signals were collected and analyzed, totaling 5167 sound files for different states of the leak detection system. Each sound file represents 16 seconds of recording and is comprised of 16384 data points forming the acoustic signal. Table IV-1 concludes the collection works over the course of 30 days, starting on April 1st_{, 2017 and} ending on April the 30th _{of the same year. The collected files have 722 leak state sound files, 957} no-leak state sound files and 3488 sound files for possible leaks. The collected data is analyzed as in section IV.1.1 of the methodology and the data is collected and organized in an excel sheet for analysis.

Table IV-1: Summary of Collected Acoustic Data Class Leak No Leak Possible Leak Total

Collected Signals 722 957 3488 5167