信息技术在医院设备科应用的探索与实践

文中探讨了新一代信息技术在医院设备科中的应用实践以及医院信息化的建设与管理。全文分为6个部分,包括引言、医院信息化概述、医用耗材管理信息系统、医疗设备固定资产信息化管理、医疗数据管理平台以及结语,介绍了医院信息化的历史发展、现状与未来以及医院信息化建设的重要性,同时还探讨了医院信息化在设备科耗材管理和设备资产管理方面的应用。最后,分析了医院信息技术应用的风险与管理、医院设备科信息化应用的影响和管理策略。通过对新一代信息技术的深入研究,希望能为医院设备科信息技术的应用提供参考和借鉴。     

Neural network robust control of a 3-DOF hydraulic manipulator with asymptotic tracking

Multiaxial hydraulic manipulators are complicated systems with highly nonlinear dynamics and various modeling uncertainties, which hinders the development of high-performance controller. In this paper, a neural network feedforward with a robust integral of the sign of the error (RISE) feedback is proposed for high precise tracking control of hydraulic manipulator systems. The established nonlinear model takes three-axis dynamic coupling, hydraulic actuator dynamics, and nonlinear friction effects into consideration. A radial basis function neural network (RBFNN) is synthesized to approximate the uncertain system dynamics and external disturbance, which can greatly reduce the dependence on accurate system model. In addition, a continuous RISE feedback law is judiciously integrated to deal with the residual unknown dynamics. Since the major unknown dynamics can be estimated by the RBFNN and then compensated in the feedforward design, the high-gain feedback issue in RISE feedback control will be avoided. The proposed RISE-based neural network robust controller theoretically guarantees an excellent semi-global asymptotic stability. Comparative simulation is performed on a 3-DOF hydraulic manipulator, and the obtained results verify the effectiveness of the proposed controller.     

磁悬浮储能飞轮高速永磁电机设计及优化

高速磁悬浮储能飞轮是一种新型高比功率储能装置,其中高速大功率电机是能量转换与传输控制的核心。本文针对所研究的300kW磁悬浮飞轮储能系统的应用特性提出了一种轴式永磁同步电机方案,从电磁、结构和控制等方面进行综合分析与设计;在此基础上,为了适应高速稳定运行、高功率放电对高速电机提出的新要求,从转子的结构强度、电机损耗、运行区间的效率、转矩波动等方面出发对电机的设计参数进行优化分析。结果表明：优化后的电机结构强度高,能够满足储能飞轮在高转速、高功率连续充放电等工况下的使用要求,15000～30000r/min工作转速范围内电机效率达到90%以上。     

基于CNN和LSTM混合网络的电动汽车充电桩运行状态预测方法

随着电动汽车的大规模发展,公共充电桩运行数量和充电量逐年增长。然而,充电桩运行始终存在故障频发、运维难度大和维修成本高等问题,并且传统故障检测方法效率低下。因此提出了一种基于卷积神经网络(CNN)和长短期记忆(LSTM)网络的混合网络电动汽车充电桩运行状态预测方法,可以实现对电动汽车充电桩运行状况的综合评估。在特征数据输入阶段,对充电桩运行状态的关键指标进行分析,通过CNN提取运行状态影响因素的特征量,再利用LSTM判断和预测充电桩运行状态,从而实现对充电桩潜在故障的预警。试验结果表明,该方法预测准确率高、实用性强,能较准确地反映和预测充电桩的运作状态,可实际用于充电桩故障预测与运维检修。     

Roll angle of autocollimator measurement method based on hollow cube corner reflector

In this paper, a method of measuring roll angle with hollow cube corner reflector (HCCR) is proposed. Firstly, the space coordinate vector relationship between the mirror and the autocollimator is established by using the Euler rotation relationship, and the structure of the HCCR is designed. Secondly, through the actual measurement of the HCCR reflector''s angle sensitivity, the specific formula of roll angle measurement is obtained. The experimental results show that the method can be used to measure the roll angle, and the maximum root mean square (RMS) error is 15" in the range of 350", and the repeatability of the experiment is better than 2.7". On the basis of retaining the traditional autocollimator, the plane mirror is replaced with HCCR, which realizes the measurement of the roll angle of the autocollimator. This method does not change the internal structure of the autocollimator system, and there is no process error caused by special processing technology, so as to retain the autocollimator''s own long measurement distance, high measurement accuracy, high system stability, and large range of measurement performance, and it can also be used in industrial production.     

一种BDS/GPS/GLONASS融合精密单点定位方法

给出了一种基于 BDS/GPS/GLONASS 融合的精密单点定位方法,统一了三系统组合精密定位的时间系统和空间系统,建立了精密单点定位非差组合模型,并利用观测数据进行了精密单点定位解算。计算结果表明,相比单一系统而言,三系统组合有效缩短定位收敛时间以及提高在单系统卫星数较少或者卫星星座分布较差时的定位精度,无论是从连续性、可用性、可靠性、精度以及效率等各方面都更具优势。     

LD泵浦Pr∶YLF固体激光器

研究了LD泵浦Pr∶YLF固体激光器。激光器采用LD端面泵浦结构,通过建立激光器热效应模型,对激光晶体内部温度场进行了解析计算,模拟分析了不同掺杂浓度Pr∶YLF晶体的光吸收以及温度场分布,对激光器泵浦耦合系统和输出镜的透射率等参数进行了优化设计,实现了LD泵浦Pr∶YLF固体激光器的高功率、高效率输出。当LD泵浦功率为2W时,获得了最大输出功率为287mW,光光转换效率达16.1,光束质量因子为M2X=1.38,M2Y=1.35的640nm激光。     

Cleanable Air Filter Transferring Moisture and Effectively Capturing PM2.5

The lethal danger of particulate matter (PM) pollution on health leads to the development of challenging individual protection materials that should ideally exhibit a high PM_2.5 purification efficiency, low air resistance, an important moisture‐vapor transmission rate (MVTR), and an easy‐to‐clean property. Herein, a cleanable air filter able to rapidly transfer moisture and efficiently capture PM_2.5 is designed by electrospinning superhydrophilic polyacrylonitrile/silicon‐dioxide fibers as the adsorption–desorption vector for moisture‐vapor, and hydrophobic polyvinylidene fluoride fibers as the repellent components to avoid the formation of capillary water under high humidity. The desorption rate of water molecules increases from 10 to 18 mg min^?1, while the diameters of polyacrylonitrile fibers reduce from 1.02 to 0.14 µm. Significantly, by introducing the hydroxyl on the surface of polyacrylonitrile nanofibers, rapid adsorption–desorption of the water molecules is observed. Moreover, by constructing a hydrophobic to super‐hydrophilic gradient structure, the MVTR increases from 10 346 to 14 066 g m^?2 d^?1. Interestingly, the prepared fibrous membranes is easy to clean. More importantly, benefiting from enhanced slip effect, the resultant fibrous membranes presented a low air resistance of 86 Pa. A field test in Shanghai shows that the air filter maintains stable PM_2.5 purification efficiency of 99.99% at high MVTR during haze event.