电子商务环境下自助售货机故障自动诊断研究

Research on Automatic Fault Diagnosis of Self-service Vending Machine in E-commerce Environment

现今,网络执行远程维护诊断系统存在无法确定故障下的唯一索引,甚至诊断结果不精准的问题。针对该问题,提出了基于故障树的电子商务环境下自助售货机故障自动诊断研究。依据电子商务环境下自助售货机结构,设计知识规则匹配遵守原则,确定知识规则编码下唯一索引。构造故障树,定性、定量分析故障树,构建诊断专家系统知识库模型,设计自助售货机故障自动诊断流程将表明存在故障的自助售货机中的商品销售失败的故障数据传送到移动终端,由移动终端显示状态数据。通过实验验证结果可知,该技术饮料温度范围为15℃~20℃,与实际故障温度范围一致;投币故障反应与实际情况一致,具有精准诊断结果。

Nowadays, the network remote maintenance diagnosis system can not determine the unique index under the fault, and even the diagnosis result is not accurate.. Aiming at this problem, the research on automatic fault diagnosis of self-service vending machine is presented based on fault tree. According to the structure of self-service vending machine in e-commerce environment, the principle of knowledge rule matching is designed to determine the unique index under knowledge rule coding. The fault tree is constructed, the fault tree is analyzed qualitatively and quantitatively, the knowledge base model of diagnosis expert system is established, and the fault automatic diagnosis flow of self-service vending machine is designed. The experimental results show that the temperature range of the beverage is from 15 ℃ to 20 ℃, which is consistent with the actual fault temperature range, and the coin fault response is consistent with the actual situation.