Qiao Huang

Dynamic Model and Estimator Development for a Smart Refractory Brick with Embedded Wireless Sensors for Gasifier Applications

This project aims at the development of a novel ‘smart’ refractory brick where various types of sensors are embedded in it. Although the ‘smart’ brick technology is promising, several issues needed to be addressed before it can be commercialized. First, a significant temperature drop is expected along the sensor length. Therefore, the traditional correlation-based approaches used for converting the raw measurements from a sensor to the variable of interest cannot be used. Second, thermal and electrical properties of the refractory do change in course of gasifier operation as the flowing molten slag penetrates into the refractory lining. The response of the embedded sensors can change due to changes in the temperature, and/or extent of slag penetration. Therefore, it becomes difficult to estimate the variables of interest by using the raw measurements. Third, if a model-based approach is used to estimate the temperature and extent of slag penetration, then model inaccuracy and measurement noise must be accounted for. Fourth, it is desired that the measurements collected from the embedded sensors are sent by using a wireless transmitter. Measurements from wireless sensor networks can be out-of-sequence leading to poor estimation. In order to address above issues, first-principles, dynamic model of the ‘smart’ brick has been developed. Sensor models are developed with consideration of installation direction. These models are further used in Kalman filter-based estimation framework to estimate the temperature and extent of slag penetration. Out-of-sequence measurement problem is also addressed. Finally, the optimal sensor placement for this ‘smart’ brick system is obtained by maximizing the state estimation accuracy. 

• Huang Q, Bhattacharyya D, “Optimal Sensor Network Design for Multi-Scale, Time-Varying Differential Algebraic Equation Systems: Application to an Entrained-Flow Gasifier Refractory Brick”, Computers & Chemical Engineering, 141, 106985,  2020 

• Huang Q, Paul P, Bhattacharyya D, Pillai R, Sabolsky K, Sabolsky E,  “Estimations of Gasifier Wall Temperature and Extent of Slag Penetration Using a Refractory Brick with Embedded Sensors”, Industrial and Engineering Chemistry Research, 56, 9858-9867, 2017 

• Huang Q, Paul P, Bhattacharyya D, Pillai R, Sabolsky K, Sabolsky E,  “Model-Based Estimation in Gasifiers Using a Smart Refractory Brick with Embedded Sensors”, Proceedings of  11th International Workshop on Structural Health Monitoring, Stanford University, CA, September 12-14, 2017 

• Huang Q, Sabolsky E, Pillai R, Sabolsky K, Bhattacharyya D,  “Health-Monitoring of Multiscale Systems Using an Optimal Multi-Rate Wireless Sensor Network”, Paper 646d, AIChE Annual Meeting, Minneapolis, MN, October 29-November 3, 2017

• Huang Q, Paul P, Bhattacharyya D, Pillai R, Sabolsky K, Sabolsky E,  “Model-Based Estimation in Gasifiers Using a Smart Refractory Brick with Embedded Sensors”, 11th International Workshop on Structural Health Monitoring, Stanford University, CA, September 12-14, 2017 

• Huang Q, Bhattacharyya D, Sabolsky E, “Estimation of Gasifier Wall Profile Using Measurements from a Wireless Sensor Network”, Paper 247i, AIChE Annual Meeting, San Francisco, CA, November 13-18, 2016

• Huang Q, Bhattacharyya D, Sabolsky, E, “Dynamic Model of a Smart Refractory Brick for Gasifier Applications”, Paper 126c, AIChE Annual Meeting, Atlanta, GA, November 16-21, 2014