ABSTRACT

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.

摘要

局部热场监测在工业工程实践中非常重要。鉴于3D热场的复杂热力学，使用现有方法检测全局热场以下的局部温度变化相对具有挑战性。为了填补这一空白，我们提出了一种热场监测方法，该方法将动态热场分解为全局趋势和局部变化部分。具体来说，开发了一个通用克立格模型，该模型描述了每个时期的空间相关性，以使用感测数据对局部变化进行建模。为了有效地监视热场变化，设计了使用估计参数的多元累积总和图。粮仓热场的实际案例研究用于验证所提出方法的性能。