摘要
针对生鲜食品在冷链配送过程中容易发生变质的问题,并考虑冷链过程的时序性特点,提出一种基于新型扩展模糊Petri网(EFPN)的故障诊断方法.该方法通过将模糊规则映射到扩展模糊Petri网,对故障诊断过程中的不确定性问题进行定量分析,从而得到引起故障的原因.利用库所带有的关键因素开始时间信息可排除未发生的因素,降低诊断推理过程的复杂程度.最后通过实例对该模型进行了验证和分析.
Aiming at the problems of perishable food in the cold chain process and its temporal characteristics, a fault diagnosing method was proposed based on a new kind of Extended Fuzzy Petri Net （EFPN）. This method can do quantitative analysis of uncertainties in the process of fault diagnosis and find out the causes of malfunction by mapping the fuzzy rule to Fuzzy Petri Net. The method can tell us when and what key problems will happen so as to exclude the events before they occur. It can reduce the complexity of the inference process. Finally, the model was verified and analyzed with examples.
出处
《天津科技大学学报》
CAS
北大核心
2015年第2期65-69,共5页
Journal of Tianjin University of Science & Technology
基金
国家自然科学基金资助项目(61070021
11301382)
