Research on sensing information fusion based on fuzzy theory

2nd International Symposium on Application of Materials Science and Energy Materials

材料科学;能源学

Yang, Jing^1 ; Li, Yingna^1 ; Wu, Zhuoheng^2 ; Zhao, Zhengang^1 ; Li, Chuan^1

Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China^1

Guangdong Polytechnic College, Guangdong, China^2

关键词: Data fusion algorithm;    Data fusion methods;    Erroneous datum;    Fuzzy proximity;    ITS applications;    Noise estimation;    Sensing information;    Sensor monitoring;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/490/6/062076/pdf
DOI  :  10.1088/1757-899X/490/6/062076

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Aiming at the difficulty of noise estimation and outlier estimation in data fusion, a fuzzy theory data fusion algorithm based on confidence distance is proposed and its application in sensor monitoring is studied. Firstly, according to the characteristics of sensor monitoring values, the characteristics of traditional fuzzy theory data fusion methods are analyzed. Secondly, the confidence distance is used to describe the fuzzy proximity between the data, and the erroneous data is eliminated. Finally, the data is merged by proximity to get the result of the fusion. Experiments show that the difference of the fusion value based on the confidence distance is small, and the fusion result is close to the actual state of the measured object.