Abstract
This paper presents a soft-sensing technique of determining the mass flow rate of a liquid-liquid heat exchanger using temperature measurements and a distributed parameter model. The efficiency of a heat exchanger is intimately related to its mass flow rate and as a consequence mass flow rate measurements are essential for any fault detection or monitoring program of the heat exchanger. However the costly mass flow rate sensor measurements can be bypassed by this soft-sensing technique which primarily employs measurements from inexpensive temperature sensors. We first develop a distributed parameter model of the counter flow type heat exchanger using energy balance equations. Thereafter, a state-space model of the heat exchanger is formulated using orthogonal collocation method where temperature at the collocation points and the unknown mass flow rate are considered as the state variables. The mass flow rate is estimated by a Hybrid Extended Kalman Filter algorithm using the outlet temperature measurements. The sensitivity of the soft-sensing technique in presence of modeling errors and measurement noise is also studied using a suitable simulation example.
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