Steam-Powered Sensing. Zhang, C., Syed, A., Cho, Y. H., & Heidemann, J. In Proceedings of the 9thACM SenSys Conference , pages 204–217, Seattle, Washington, USA, November, 2011. ACM. ![Steam-Powered Sensing [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex Sensornets promise to extend automated monitoring and control into industrial processes. In spite of great progress made in sensornet design, \emphinstallation 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 \emphgenerating electricity from heat, exploiting the high temperature of the very pipelines we monitor. We demonstrate that for temperature differences of 80 \textcelsius or more, we are able to sustain sensornet operation without grid electricity or batteries. Second, we show that \emphnon-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.
@InProceedings{Zhang11a,
author = "Chengjie Zhang and Affan Syed and Young H. Cho and John Heidemann",
title = "Steam-Powered Sensing",
booktitle = "Proceedings of the " # "9th" # " ACM {SenSys} Conference ",
year = 2011,
sortdate = "2011-11-01",
project = "ilense, cisoft",
jsubject = "sensornet_applications",
pages = "204--217",
address = "Seattle, Washington, USA",
month = nov,
publisher = "ACM",
location = "johnh: pafile",
keywords = "steamflood optimization, energy harvesting,
non-invasive detection",
xdoi = "xxx",
url = "http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.html",
pdfurl = "http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.pdf",
myorganization = "USC/Information Sciences Institute",
copyrightholder = "ACM",
copyrightterms = " Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org." ,
abstract = "Sensornets promise to extend automated monitoring and control into
industrial processes. In spite of great progress made in sensornet
design, \emph{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 \emph{generating electricity from heat},
exploiting the high temperature of the very pipelines we monitor. We
demonstrate that for temperature differences of 80~\textcelsius~or
more, we are able to sustain sensornet operation without grid
electricity or batteries. Second, we show that \emph{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.",
}
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{"_id":"wMRkAqJLWmfYeEPX8","bibbaseid":"zhang-syed-cho-heidemann-steampoweredsensing-2011","author_short":["Zhang, C.","Syed, A.","Cho, Y. H.","Heidemann, J."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Chengjie"],"propositions":[],"lastnames":["Zhang"],"suffixes":[]},{"firstnames":["Affan"],"propositions":[],"lastnames":["Syed"],"suffixes":[]},{"firstnames":["Young","H."],"propositions":[],"lastnames":["Cho"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]}],"title":"Steam-Powered Sensing","booktitle":"Proceedings of the 9thACM SenSys Conference ","year":"2011","sortdate":"2011-11-01","project":"ilense, cisoft","jsubject":"sensornet_applications","pages":"204–217","address":"Seattle, Washington, USA","month":"November","publisher":"ACM","location":"johnh: pafile","keywords":"steamflood optimization, energy harvesting, non-invasive detection","xdoi":"xxx","url":"http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.html","pdfurl":"http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.pdf","myorganization":"USC/Information Sciences Institute","copyrightholder":"ACM","copyrightterms":"Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org.","abstract":"Sensornets promise to extend automated monitoring and control into industrial processes. In spite of great progress made in sensornet design, \\emphinstallation 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 \\emphgenerating electricity from heat, exploiting the high temperature of the very pipelines we monitor. We demonstrate that for temperature differences of 80 \\textcelsius or more, we are able to sustain sensornet operation without grid electricity or batteries. Second, we show that \\emphnon-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.","bibtex":"@InProceedings{Zhang11a,\n\tauthor = \t\"Chengjie Zhang and Affan Syed and Young H. Cho and John Heidemann\",\n\ttitle = \t\"Steam-Powered Sensing\",\n\tbooktitle = \t\"Proceedings of the \" # \"9th\" # \" ACM {SenSys} Conference \",\n\tyear = \t\t2011,\n\tsortdate = \"2011-11-01\",\n\tproject = \"ilense, cisoft\",\n\tjsubject = \"sensornet_applications\",\n\tpages = \t\"204--217\",\n\taddress = \t\"Seattle, Washington, USA\",\n\tmonth = \tnov,\n\tpublisher = \t\"ACM\",\n\tlocation = \t\"johnh: pafile\",\n\tkeywords = \t\"steamflood optimization, energy harvesting,\n non-invasive detection\",\n\txdoi = \t\"xxx\",\n\turl =\t\t\"http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.html\",\n\tpdfurl =\t\"http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.pdf\",\n\tmyorganization =\t\"USC/Information Sciences Institute\",\n\tcopyrightholder = \"ACM\",\n\tcopyrightterms = \"\tPermission to make digital or hard \tcopies of portions of this work for personal or \tclassroom use is granted without fee provided that \tthe copies are not made or distributed for profit or \tcommercial advantage and that copies bear this \tnotice and the full citation on the first page in \tprint or the first screen in digital \tmedia. Copyrights for components of this work owned \tby others than ACM must be honored. Abstracting with \tcredit is permitted. \totherwise, to republish, to post on servers, or to \tredistribute to lists, requires prior specific \tpermission and/or a fee. Send written requests for \trepublication to ACM Publications, Copyright & \tPermissions at the address above or fax +1 (212) \t869-0481 or email permissions@acm.org.\" ,\n\tabstract = \"Sensornets promise to extend automated monitoring and control into\nindustrial processes. In spite of great progress made in sensornet\ndesign, \\emph{installation and operational costs} can impede their\nwidespread adoption---current practices of infrequent, manual\nobservation are often seen as sufficient and more cost effective than\nautomation, even for key business processes. In this paper we present\ntwo new approaches to reduce these costs, and we apply those\napproaches to rapidly detect blockages in steam pipelines of a\nproduction oilfield. First, we eliminate the high cost of bringing\npower to the field by \\emph{generating electricity from heat},\nexploiting the high temperature of the very pipelines we monitor. We\ndemonstrate that for temperature differences of 80~\\textcelsius~or\nmore, we are able to sustain sensornet operation without grid\nelectricity or batteries. Second, we show that \\emph{non-invasive\nsensing} can reduce the cost of sensing by avoiding sensors that\npierce the pipeline and have high installation cost with interruption\nto production. Our system instead uses surface temperature to infer\nfull or partial blockages in steam pipelines and full blockages in hot\nwater pipelines. Finally, we evaluate our ``steam-powered sensing''\nsystem to monitor potential blockages in steam pipeline chokes at a\nproduction oilfield. We also show the generality of our algorithm by\napplying it to detect water pipeline blockages in our lab. To our\nknowledge, this paper describes the first field-tested deployment of\nan industrial sensornet that employs non-solar energy harvesting.\",\n}\n\n","author_short":["Zhang, C.","Syed, A.","Cho, Y. H.","Heidemann, J."],"bibbaseid":"zhang-syed-cho-heidemann-steampoweredsensing-2011","role":"author","urls":{"Paper":"http://www.isi.edu/%7ejohnh/PAPERS/Zhang11a.html"},"keyword":["steamflood optimization","energy harvesting","non-invasive detection"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["steamflood optimization","energy harvesting","non-invasive detection"],"search_terms":["steam","powered","sensing","zhang","syed","cho","heidemann"],"title":"Steam-Powered Sensing","year":2011}