@article{
 title = {Automatic model-based soft sensor generation for liquefied natural gas terminal pipeline},
 type = {article},
 year = {2014},
 volume = {53},
 id = {d1d59f83-c211-325d-8831-3940a0dc875f},
 created = {2019-02-13T12:19:07.700Z},
 file_attached = {false},
 profile_id = {e2d2f261-b93b-3381-802e-ec4f45d345ec},
 last_modified = {2019-02-13T12:19:07.700Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2014 American Chemical Society. A liquefied natural gas (LNG) receiving terminal is a facility to receive, store, and produce natural gas to demand. In the terminal, there are many pipelines that carry LNG, which is dangerous when it evaporates, but the number of sensors are not sufficient to monitor the property of fluids at all position of pipeline because of the cost of sensors. To solve the data insufficiency problem, a methodology for automatic model-based soft sensor generation is proposed in this paper. This methodology is composed of positional information extraction, automatic model formulation, and simulation with minimum errors. With the software based on this methodology, even the user who does not have a chemical or mathematical background can monitor the fluid property at whole terminal pipelines. For validation, the methodology is applied to an LNG terminal unloading pipeline, and it showed good accuracy and accessibility of various data types.},
 bibtype = {article},
 author = {Lee, S. and Jung, J. and Park, C. and Lee, U. and Han, C.},
 doi = {10.1021/ie502180w},
 journal = {Industrial and Engineering Chemistry Research},
 number = {39}
}

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A liquefied natural gas (LNG) receiving terminal is a facility to receive, store, and produce natural gas to demand. In the terminal, there are many pipelines that carry LNG, which is dangerous when it evaporates, but the number of sensors are not sufficient to monitor the property of fluids at all position of pipeline because of the cost of sensors. To solve the data insufficiency problem, a methodology for automatic model-based soft sensor generation is proposed in this paper. This methodology is composed of positional information extraction, automatic model formulation, and simulation with minimum errors. With the software based on this methodology, even the user who does not have a chemical or mathematical background can monitor the fluid property at whole terminal pipelines. For validation, the methodology is applied to an LNG terminal unloading pipeline, and it showed good accuracy and accessibility of various data types.","bibtype":"article","author":"Lee, S. and Jung, J. and Park, C. and Lee, U. and Han, C.","doi":"10.1021/ie502180w","journal":"Industrial and Engineering Chemistry Research","number":"39","bibtex":"@article{\n title = {Automatic model-based soft sensor generation for liquefied natural gas terminal pipeline},\n type = {article},\n year = {2014},\n volume = {53},\n id = {d1d59f83-c211-325d-8831-3940a0dc875f},\n created = {2019-02-13T12:19:07.700Z},\n file_attached = {false},\n profile_id = {e2d2f261-b93b-3381-802e-ec4f45d345ec},\n last_modified = {2019-02-13T12:19:07.700Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2014 American Chemical Society. A liquefied natural gas (LNG) receiving terminal is a facility to receive, store, and produce natural gas to demand. In the terminal, there are many pipelines that carry LNG, which is dangerous when it evaporates, but the number of sensors are not sufficient to monitor the property of fluids at all position of pipeline because of the cost of sensors. To solve the data insufficiency problem, a methodology for automatic model-based soft sensor generation is proposed in this paper. This methodology is composed of positional information extraction, automatic model formulation, and simulation with minimum errors. With the software based on this methodology, even the user who does not have a chemical or mathematical background can monitor the fluid property at whole terminal pipelines. For validation, the methodology is applied to an LNG terminal unloading pipeline, and it showed good accuracy and accessibility of various data types.},\n bibtype = {article},\n author = {Lee, S. and Jung, J. and Park, C. and Lee, U. and Han, C.},\n doi = {10.1021/ie502180w},\n journal = {Industrial and Engineering Chemistry Research},\n number = {39}\n}","author_short":["Lee, S.","Jung, J.","Park, C.","Lee, U.","Han, C."],"biburl":"https://bibbase.org/service/mendeley/e2d2f261-b93b-3381-802e-ec4f45d345ec","bibbaseid":"lee-jung-park-lee-han-automaticmodelbasedsoftsensorgenerationforliquefiednaturalgasterminalpipeline-2014","role":"author","urls":{},"metadata":{"authorlinks":{"lee, u":"https://bibbase.org/service/mendeley/e2d2f261-b93b-3381-802e-ec4f45d345ec","lee, u":"https://bibbase.org/show?bib=https://dblp.org/pid/172/3208.bib"}},"downloads":0},"search_terms":["automatic","model","based","soft","sensor","generation","liquefied","natural","gas","terminal","pipeline","lee","jung","park","lee","han"],"keywords":[],"authorIDs":["53Eu6D3PGMBxXrRti","5c9c263cdec2ee1000000059","5cf7553ccdc1abda0100005f","5de89d8a2c5eb2df01000115","5defa24b706001de01000116","5df1f31678da84de010000bc","5df737f28efe8dde01000116","5dfe154ef12c02df01000024","5e0257cd6ffa15df010000cf","5e0415b20fe3b7df01000096","5e103afd2a14dedf0100003a","5e1beb634c869ade010000a8","5e27fd854d75d8de010000ad","5e318f1800e4e5de010001a5","5e335147e0067bde01000194","5e337f387a676dee0100006b","5e348fe053b794de01000031","5e622936a84f4adf01000032","5e6482a9e89ef4df0100005e","5uJTfYkz8g7sk4JGG","6LPbpLbgj2WL9rTzb","9TSvYjjKKNJABZjyw","AFsKowzSGCYXtGgnA","F4ihjugSzaCtFvgvq","F7oWt4p9yWJajZxgS","KPt2RkeANfpK5kHe7","MKLATA3QnWw9tFT4P","P5P9YzrQ4afhAENuh","Pmkz8ZHvPuXR5xKgu","SQ3BdNc63bfqYCedJ","T3LhxYRHS6uSW3MGr","WCrkCJcD3nYDojs5Q","WYgE6NTaj89hF3c94","XSMne33P8tn6zKHwM","YFy9eDRKiXTNAZztq","YhgmPvj4dq6HFXkZc","eoT927awFCptDGteh","hKPL78kq22q3p3fNv","mYyiwbbdhikBnpXqZ","nxqNTEDeDzQdthSrH","pkLWRR8R3EpxYie5W","qMYFbvSwNNx7dzdta","rPjAGc5MiJuKRrR2w","usCJjqr7DyEHWYEmm","wbkAhTbGkjz2Hv7oT","y8HTa5oEmRuqgHAe9","yzH5vffy2NzMFdNWN"],"dataSources":["Mtx83Ei99HeufLMJ3","ya2CyA73rpZseyrZ8","5PETdajSpajMJ4M4L"]}