Autonomous distributed temperature sensing for long-term heated applications in remote areas
|Authors:||Kurth, A. M.|
|Resource type:||Composite Resource|
|Storage:||The size of this resource is 623.6 KB|
|Created:||Apr 01, 2018 at 5:06 p.m.|
|Last updated:||Apr 09, 2018 at 6:58 p.m. by CTEMPs OSU-UNR|
|Citation:||See how to cite this resource|
Distributed temperature sensing (DTS) is a fiber-optical method enabling simultaneous temperature measurements over long distances. Electrical resistance heating of the metallic components of the fiber-optic cable provides information on the thermal characteristics of the cable's environment, providing valuable insight into processes occurring in the surrounding medium, such as groundwater–surface water interactions, dam stability or soil moisture. Until now, heated applications required direct handling of the DTS instrument by a researcher, rendering long-term investigations in remote areas impractical due to the often difficult and time-consuming access to the field site. Remote control and automation of the DTS instrument and heating processes, however, resolve the issue with difficult access. The data can also be remotely accessed and stored on a central database. The power supply can be grid independent, although significant infrastructure investment is required here due to high power consumption during heated applications. Solar energy must be sufficient even in worst case scenarios, e.g. during long periods of intense cloud cover, to prevent system failure due to energy shortage. In combination with storage batteries and a low heating frequency, e.g. once per day or once per week (depending on the season and the solar radiation on site), issues of high power consumption may be resolved. Safety regulations dictate adequate shielding and ground-fault protection, to safeguard animals and humans from electricity and laser sources. In this paper the autonomous DTS system is presented to allow research with heated applications of DTS in remote areas for long-term investigations of temperature distributions in the environment.
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