摘要
为降低泌尿外科护理冲洗设备故障率,提出基于神经网络的泌尿外科护理冲洗设备故障检测系统设计方法。在设备的接入段采用无线传感器进行故障参数采样,采用接入层、汇聚层、核心层的三层体系结构构建故障检测系统的总体结构模型,分析泌尿外科护理冲洗设备的串联型电弧故障参数,采用存储、显示、管理分布式部署的方法实现对设备的故障特征分析,建立故障检测系统的数据采集模块、总线传输模块、信息处理模块和人机交互模块等,通过接口编译控制设计的方法实现对泌尿外科护理冲洗设备的故障稳态特征检测和反馈调节,采用神经网络分类模型实现对故障类别参数分类辨识,通过工作模态分类解析方法实现设备故障检测。测试结果表明,采用该方法进行故障检测的准确性较高,系统的稳定性较好。
In order to reduce the failure rate of nursing irrigation equipment in urology, a design method of fault detection system for nursing irrigation equipment in urology based on neural network is proposed. In the access section of the equipment, the wireless sensor is used to sample the fault parameters, and the three-layer architecture of access layer, convergence layer and core layer is used to construct the overall structure model of the fault detection system. The series arc fault parameters of urological nursing and flushing equipment are analyzed, and the distributed deployment method of storage, display and management is adopted to realize the fault feature analysis of the equipment. The data acquisition module, bus transmission module, information processing module and man-machine interaction module of the fault detection system are established. The steady-state characteristic detection and feedback adjustment of urology nursing irrigation equipment are realized by interface compilation and control design, the classification and identification of fault category parameters are realized by neural network classification model, and the equipment fault detection is realized by working mode classification and analysis method. The test results show that the accuracy of fault detection by this method is high, and the stability of the system is good.
作者
魏秀莲
WEI Xiulian(Linquan county people’s hospital,Fuyang,Anhui 236400,China)
出处
《自动化与仪器仪表》
2023年第2期222-225,共4页
Automation & Instrumentation
基金
阜阳市第六批产业创新团队项目《2019蚌埠医学院自然科学重点项目》(BYKT2019228ZD)。
关键词
神经网络
泌尿外科
护理冲洗设备
故障检测系统
故障类别参数识别
neural network
urology
nursing washing equipment
fault detection system
fault category parameter identification
