steam-powered sensing
Sensornets promise to extend automated monitoring and control into industrial processes. In spite of great progress made in sensornet design, installation and operational costs can impede their widespread adoption---current practices of infrequent, manual observation are often seen as sufficient and more cost effective than automation, even for key business processes. In this paper we present two new approaches to reduce these costs, and we apply those approaches to rapidly detect blockages in steam pipelines of a production oilfield. First, we eliminate the high cost of bringing power to the field by generating electricity from heat , exploiting the high temperature of the very pipelines we monitor. We demonstrate that for temperature differences of 80 C or more, we are able to sustain sensornet operation without grid electricity or batteries. Second, we show that non-invasive sensing can reduce the cost of sensing by avoiding sensors that pierce the pipeline and have high installation cost with interruption to production. Our system instead uses surface temperature to infer full or partial blockages in steam pipelines and full blockages in hot water pipelines. Finally, we evaluate our "steam-powered sensing" system to monitor potential blockages in steam pipeline chokes at a production oilfield. We also show the generality of our algorithm by applying it to detect water pipeline blockages in our lab. To our knowledge, this paper describes the first field-tested deployment of an industrial sensornet that employs non-solar energy harvesting.
non-invasive sensing blockage detection thermal energy harvesting industrial wireless sensor networks