An application of kalman filter and finite difference scheme to inverse heat conduction problems

Abstract

Problems of recovery temperature or heat flux on a surface of a conducting solid from temperature measurements made within the conducting solid are inverse heat conduction problems (IHCPs). In order to obtain an accurate recovery boundary temperature or heat flux, it is necessary to determine and to reduce the errors caused by the temperature measurements. A Kalman Filter is a good method in handling the random noise directly from the real-time measurement. Because Kalman Filter is a real-time filter, the inversion solver can combine Kalman Filter to inverse a real-time IHCP. In this paper, the first part will introduce an inverse solver to simulate the recovery boundary temperatures or heat fluxes. The second part of this paper will introduce a Kalman Filter estimator in handling the real-time measurement noise.

Keywords:

• Inverse heat conduction problems
• Kalman Filter
• real-time simulation