Smart level sensor based on thermal resistance measurement with self calibration

L. Umar
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引用次数: 3

Abstract

A new detection method of level sensor based on the thermal resistance of gas and liquids using modeling of the current-voltage-curve is presented. The model directly examines the thermal resistance (Rth) of the sensor exposed to a specified medium whose value extracted simultaneously with the parameters of the sensor. In compared to the in air with 348K/W, the thermal resistance in water decreased around 82 %, and/or in silicon oil 67 %, in transmission oil 68 % and in petroleum 71 %. From these results, the sensor status between „empty“ (in air) and „full“ (in fluid) are clearly distinguishable. The change of overall thermal resistance due to the dirt was measured experimentally using a variety of fluids and the results were validated with the mathematical simulation. The changing of the thermal resistance is evaluated using the mathematical model based on heat transfer concept, enable to assess if soiling on the sensor surfaces so far increased, then the sensor must be changed or cleaned.
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基于热阻测量的智能液位传感器,具有自校准功能
提出了一种基于气体和液体热阻的液位传感器的检测方法,该方法采用电流-电压曲线建模。该模型直接检测传感器暴露在特定介质中的热阻(Rth),其值与传感器参数同时提取。与348K/W的空气中相比,在水中的热阻降低了82%左右,在硅油中降低了67%,在传动油中降低了68%,在石油中降低了71%。从这些结果中,传感器状态在“空”(空气中)和“满”(流体中)之间清晰地区分开来。用不同的流体实验测量了污垢对总热阻的影响,并通过数学模拟对结果进行了验证。利用基于传热概念的数学模型评估热阻的变化,从而评估传感器表面的污垢是否增加,则必须更换或清洗传感器。
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