New data loggers detect water losses early
Sep 23 2019
Leaks in water pipe networks can result in significant water losses. Thanks to systematic monitoring of the network with Herman Sewerin’s SePem® data loggers, you can reliably identify existing leaks and catch new ones early on – much faster than with conventional methods.
In relation to the size of a measuring area, the volume of water initially escaping from a new leak is usually so low that it cannot be clearly distinguished from minimum night-time consumption when measuring the flow. In practice, many months often go by before the size of the damage is great enough to produce a flow volume that can clearly be identified as a leak. SEWERIN’s SePem® 100/150 can report the leak after just one night.
The SePem® 100 data loggers with integrated aerial are perfect for mobile use in the water pipe network. They are placed on fittings at measuring points in a specified section of network and record the level for a programmable period of time during the night – usually half an hour. The loggers are collected in the next day. The measurement data is transmitted to the SePem® 01 Master by radio. Noticeably high measurement values indicating a leak are immediately flagged up by an audible signal. This is a reliable way of detecting existing leaks. The data loggers are then successively inserted in other sections of the network until the whole network has been checked.
The SePem® 150 data loggers are designed for the stationary monitoring of water supply networks. They have an external aerial and are permanently fixed to fittings. The SePem® 150s record the minimum level every night for a programmable period of time, for example half an hour. The locations are periodically patrolled, for instance daily or weekly, when the noise loggers send their data telegrams to the SePem® 01 Master. Unlike the mobile application, there is no comparison of the absolute levels of two measuring points, but rather a relative change in the level at a measuring point means that a new leak can be very quickly identified.
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