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Optimal sensor network design for multi-scale, time-varying differential algebraic equation systems: Application to an entrained-flow gasifier refractory brick

Journal Article · · Computers and Chemical Engineering
 [1];  [2]
  1. West Virginia Univ., Morgantown, WV (United States). Dept. of Chemical and Biomedical Engineering; West Virginia Univ., Morgantown, WV (United States)
  2. West Virginia Univ., Morgantown, WV (United States). Dept. of Chemical and Biomedical Engineering
An algorithm for optimal sensor network design for multi-scale, time-varying differential algebraic equation systems with non-separable dynamics is presented. As the process is time-varying, an integral normalized posterior error covariance of a multi-scale filter is minimized to obtain the optimal sensor locations. For reducing the computational cost, an adaptive sampling rate approach is considered for the slowly-varying variables. The algorithm is applied to a smart refractory brick with embedded sensors as part of an entrained-flow gasifier. Thermistors and interdigital capacitors are considered as candidate measurement technologies for estimating temperature and slag penetration profile along the gasifier wall. Finally, when the optimal set of sensors obtained from the algorithm is used for estimating temperature and slag penetration profiles in a multi-scale Kalman filter framework, satisfactory estimates are obtained despite high measurement noise and model mismatch.
Research Organization:
West Virginia Univ., Morgantown, WV (United States)
Sponsoring Organization:
USDOE Office of Fossil Energy (FE)
Grant/Contract Number:
FE0012383
OSTI ID:
1849121
Journal Information:
Computers and Chemical Engineering, Journal Name: Computers and Chemical Engineering Journal Issue: C Vol. 141; ISSN 0098-1354
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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