A novel local temperature change detection approach in a 3D thermal field

Local thermal field monitoring is of great importance in industrial engineering practice. In view of the complex thermodynamics of a 3D thermal field, the local temperature change beneath the global thermal field is relatively challenging to detect using existing approaches. To fill this gap, we propose a thermal field monitoring method that decomposes the dynamic thermal field into global trend and local variability parts. Specifically, a universal kriging model that characterises the spatial correlation at each time epoch is developed to model the local variability using sensing data. To efficiently monitor the thermal field changes, a multivariate cumulative sum chart that uses the estimated parameters is designed. An actual case study of the thermal field of a granary is used to validate the performance of the proposed method.