摘要
为了提高二氧化碳宫颈糜烂激光治疗仪的故障分析诊断能力,提出基于故障谱特征提取的二氧化碳宫颈糜烂激光治疗仪故障自动检测方法。构建二氧化碳宫颈糜烂激光治疗仪的故障工况下的电流内环动态特征检测模型,采用大数据挖掘技术,实现对治疗仪器设备的故障工况特征融合分析,在模糊度融合模型下,构建二氧化碳宫颈糜烂激光治疗仪故障自适应状态监测模型,结合二氧化碳宫颈糜烂激光治疗仪故障工况下的信息融合和特征聚类结果,采用故障谱特征提取方法,实现激光治疗仪故障自动检测和系统优化设计,提高激光治疗仪稳态工作能力。仿真结果表明,设计的激光治疗仪故障自动检测系统稳定性较好,故障检测的精度较高。
In order to improve the fault analysis and diagnosis ability of carbon dioxide laser therapeutic instrument for cervical erosion,an automatic fault detection method of carbon dioxide laser therapeutic instrument for cervical erosion based on fault spectrum feature extraction was proposed.The dynamic characteristic detection model of current inner loop under the fault condition of carbon dioxide cervical erosion laser therapeutic instrument is constructed.The big data mining technology is used to realize the fusion analysis of fault condition characteristics of therapeutic instruments and equipment.Under the fuzzy fusion model,the adaptive state monitoring model of carbon dioxide cervical erosion laser therapeutic instrument is constructed.Combined with the information fusion and feature clustering results under the fault condition of carbon dioxide cervical erosion laser therapeutic instrument,the fault spectrum feature extraction method is adopted to realize the automatic fault detection and system optimization design of laser therapeutic instrument,and improve the steady-state working ability of laser therapeutic instrument.The simulation results show that the designed automatic fault detection system of laser therapeutic apparatus has good stability and high fault detection accuracy.
作者
陈英
刘芳
CHEN Ying;LIU Fang(Edong Medical Group City Center Hospital,Huangshi Hubei 435000,China)
出处
《自动化与仪器仪表》
2021年第4期124-126,131,共4页
Automation & Instrumentation
基金
湖北省卫健委联合基金(No.WJ2019H206)。
关键词
二氧化碳
宫颈糜烂
激光治疗仪
自动检测
carbon dioxide
cervical erosion
laser therapeutic apparatus
malfunction
automatic detection
