摘要
为使计算机安全、高效运行,降低计算机宕机风险,并选取最佳维修维护策略,文章探讨了计算机硬件故障检测与维修维护策略。文章构建包含应用层、操作系统层和硬件层的计算机硬件故障检测架构,应用层的故障检测模块通过向故障监控守候进程的事务分配发送故障检测请求,调用操作系统层的改进BP神经网络的故障检测方法完成计算机硬件故障检测,以故障检测结果为依据,构建标准故障库,设立与之相匹配的标准故障模型,基于模糊贴近度计算故障严重度、发生度和可检测度指标与标准指标的相似度,获取综合贴近度,依据最高综合贴近选取维修策略。实验结果表明:所提策略具有较好的故障检测能力且精准度高。
In order to make the computer run safely and efficiently,reduce the risk of computer downtime,and select the best maintenance strategy,the computer hardware fault detection and maintenance strategy are discussed.The computer hardware fault detection architecture constructed includes the application layer,operating system layer and hardware layer.The fault detection module of the application layer sends a fault detection request to the transaction allocation of the fault monitoring waiting process,calling the fault detection method of the improved BP neural network of the operating system layer to complete computer hardware fault detection,and then according to the fault detection results,the standard fault database is constructed and the matching standard fault model is set up to calculate the similarity between the fault severity,occurrence and detectability indexes and the standard indexes based on the fuzzy closeness,so as to obtain the comprehensive closeness and select the maintenance strategy according to the highest comprehensive closeness.The experimental results show that the proposed strategy has good fault detection ability and high accuracy.
作者
赵亚琴
蔡晓骝
ZHAO Yaqin;CAI Xiaoliu(Academy of Art and Design, Anhui Technical College Of Mechanical and Electrical Engineering,Wuhu 241000)
出处
《常州工学院学报》
2021年第6期41-46,共6页
Journal of Changzhou Institute of Technology
关键词
故障检测
维护策略
BP神经网络
免疫优化
故障模型
综合贴近度
fault detection
maintenance strategy
BP neural network
immune optimization
fault model
comprehensive closeness