1. 河南科技大学机电工程学院
2. 洛阳普莱柯生物工程股份有限公司
纸质出版:2014
移动端阅览
[1]崔建鹏,徐彦伟,颉潭成,南翔,王俊澎,刘守川.基于多信息融合的疫苗培养基检测研究[J].传感器与微系统,2014,33(05):18-20+23.
CUI Jian-peng, XU Yan-wei, XIE Tan-cheng, et al. Research on detection of vaccines medium based on multi-information fusion[J]. 2014, 33(5): 18-20+23.
[1]崔建鹏,徐彦伟,颉潭成,南翔,王俊澎,刘守川.基于多信息融合的疫苗培养基检测研究[J].传感器与微系统,2014,33(05):18-20+23. DOI: 10.13873/j.1000-97872014.05.027.
CUI Jian-peng, XU Yan-wei, XIE Tan-cheng, et al. Research on detection of vaccines medium based on multi-information fusion[J]. 2014, 33(5): 18-20+23. DOI: 10.13873/j.1000-97872014.05.027.
针对疫苗培养基检测准确率较低的问题
首次提出利用机器视觉、红外温度和光照度的多传感器信息融合技术检测疫苗培养基。通过BP神经网络将3种传感器采集到的信息在特征层进行融合
在模型的建立过程中
对各个信息的主成分因子数进行了优化。从实验结果看
模型对预测集检测的识别率为97%
实验结果表明:通过多信息融合方法检测疫苗培养基是可行的
检测结果的准确性和稳定性相对于单个模型有明显提高。
Aiming at problem of low detection accuracy of vaccine medium
first propose using machine vision
multi-sensor information fusion technology of infrared temperature and illumination to detect vaccine medium. Through BP neural network
information collected by three kinds of sensors is fused in feature level
in process of model building
numbers of principal components factor of each message are optimized. From experimental results
detection recognition rate of model on prediction set is 97 %
test results show that detecting vaccine medium through multi-information fusion method is feasible
accuracy and stability of test results are improved significantly relative to individual model.
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