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基于CCD的焦炉测温技术研究

Coking Furnace Temperature Measurement Technology Research Based on CCD

【作者】 李俊

【导师】 吴从中; 茅文深;

【作者基本信息】 合肥工业大学 , 电子与通信工程(专业学位), 2015, 硕士

【摘要】 准确检测焦炉温度对保证炼焦产品的质量以及焦炉生产的节能降耗意义重大。彩色CCD图像传感器能同时实现3通道辐射能量的接收,简化了实现比色测温的硬件系统,应用于测温系统能及时反映整个温度场的情况,相比于现有的焦炉测温方法具有测温准确、价格适中、自动测量等优点。本文分析了彩色CCD图像传感器应用于焦炉测温的可行性以及相关原理,针对基于CCD的焦炉测温中目标识别以及传统测温模型不够准确的问题提出了改进方案,构建了高温黑体的温度场,实验结果验证了改进方法的有效性与准确性。主要改进内容和方案如下:在目标识别方面,本文提出了一种基于Susan边缘信息的阈值分割算法。在基于颜色信息的高温辐射目标识别算法中用该方法替代原来的迭代阂值法,对高温黑体的识别结果表明该方法效果更好。在测温模型建立方面,本文在一种不依赖三基色代表波长的测温模型的基础上做了基色相减的改进,减弱环境光的干扰,提高了测温精度,在两种温度标定方法下的测温结果说明了改进后的测温模型精度高出很多。

【Abstract】 The accurate detection of coking furnace temperature is important for either the quality of productions or the energy conservation. The CCD image sensor is particularly suitable for temperature detection since it can detect the quantity of radiant energy in three channels simultaneously. Compared with ordinary technology, the CCD image sensor has many advantages, such as the high accuracy, the low cost and the automation. In this dissertation, we first introduce the principle of the CCD image sensor and analyze the feasibility of applications in the coking furnace temperature detection. Considering the deficiencies in the target detection in coking furnace and the traditional temperature detect model, we propose our modifications. At last we construct temperature field of blackbody and the experimental results verify the validity and accuracy of the improved methods.The main modifications are as follows:In the object detection aspect, we propose a threshold segmentation algorithm based on the Susan edge operator.In high-temperature radiation target recognition algorithm based on color information,we use the method instead of original iteration threshold method, the identification results of high temperature blackbody show that this method works better.In the temperature model establishing aspect,we improve the temperature model not relying on the three primary colors represents wavelength by color subtraction, ambient light interference reduced and the accuracy of temperature measurement improved. Temperature results in the two both data calibration methods illustrate the accuracy of the improved temperature model is much higher.

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