摘要
为了快速准确地检测反映锅炉燃烧效率的重要指标炉渣碳质量分数,实时掌握锅炉燃烧工况,针对目前炉渣碳质量分数高精度检测法检测时间长而快速视觉检测法准确度低的问题,提出了一种基于机器视觉技术的锅炉炉渣碳质量分数检测方法。该方法通过采集炉渣图像,基于图像信息建立图像信息熵差与炉渣碳质量分数之间关系模型,再根据此关系模型,获得待测炉渣的碳质量分数。实验结果表明,与传统的灼烧失重法比较,检测时间少,所提方法的平均偏差小于2%,满足目前检测精度要求;与目前存在的视觉检测方法相比,提出的方法检测结果不受拍摄光照环境的影响,精度显著提高。该研究为进一步实现炉渣碳质量分数的实时在线检测打下了基础。
It is of great significance to detect slag carbon content rapidly and accurately for boiler combustion condition monitoring, boiler automated controlling, and reduction of energy consumption and emission. We present a new method for detecting carbon content of boiler slag based on machine vision technology, which is simple, fast and accurate. The slag images are acquired and then the carbon content of the slag is obtained according to the relationship model established here. Then the relation between slag image and slag carbon content is constructed via the information entropy difference of slag image and reference image. Experiment verifies that the average deviation of the proposed method is less than 2%, and the method spend shorter detection time than the traditional weight loss method, so the new method meets the detection requirements. Especially, the detection results are unaffected by the illumination environment, enabling real-time testing of the slag carbon content.
作者
邢超
张晓明
赵亚琳
王昭
高建民
XING Chao 1, ZHANG Xiaoming 2, ZHAO Yalin 1, WANG Zhao 1, GAO Jianmin 3(1. School of Mechanical Engineering, Xi＇an Jiaotong University, Xi＇an 710049, China;2. Shaanxi Special Equipment Inspection and Testing Institute, Xi＇an 710048, China;3. State Key Laboratory for Manufacturing Systems Engineering, Xi＇an Jiaotong University, Xi＇an 710049, Chin)
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2018年第8期49-53,123,共6页
Journal of Xi'an Jiaotong University
关键词
碳质量分数
炉渣图像
信息熵差
关系模型
光照环境
carbon content
slag image
information entropy difference
relationship model
illumination environment
