数字温度传感器在多点温度测量系统中的应用

传统的温度测量系统,输出信号必须经过放大、A/D转换等处理之后才能送微控制器进行相应的处理,硬件电路设计复杂,成本较高。而由DALLAS公司生产的新型数字温度传感器DS18B20,能直接读出被测温度,并以串行数字信号传送给单片机进行处理。每片DS18B20都有唯一的ROM编码,使一根口线可接多片DS18B20。因而使用DS18B20构建多点温度测量系统可使测温系统结构更趋简单,成本更低、可靠性更高。本文介绍了DS18B20的特点、工作原理及由DS18B20构建的多点温度测量系统的硬软件设计。     

多激励下某直升机传动系统动载特性

针对由弧齿锥齿轮和行星轮系构成的直升机传动系统,构建了纯扭振动模型,采用集中参数法建立了齿侧间隙非线性动力学方程.通过有限元方法求得了时变啮合刚度,采用4-5阶变步长Runge-Kutta法对动力学方程进行了数值求解,借助动载系数、相图、Poincaré截面图、快速傅里叶变换频谱图等分析手段,研究了传动系统在时变啮合刚度、齿侧间隙、综合传动误差、外载荷等多种激励作用下系统的动载特性.结果表明啮合刚度对传动系统的影响最大,动载系数最大值为1.5;齿侧间隙对系统响应特性的影响是有限的;啮合误差在一定程度上抑制了齿轮系统的振动;外载荷波动对不同速级的影响不同,动载系数最大值发生在并车传动.     

非系统RS码的删／错译码算法

研究了非系统RS码的删/错译码算法。详细阐明了删/错译码原理,推导了各步的计算公式。该算法特别适用于干扰严重的组合信道中级连RS码的译码。     

捷联惯导系统圆锥补偿算法研究

为了提高高动态环境下捷联惯性导航系统的精度,消除圆锥效应带来的误差,对圆锥补偿算法的设计和圆锥补偿误差特性进行了研究.首先给出了旋转矢量方程和经典圆锥运动的角速度模型,进而推导出了经典圆锥运动的角增量公式、角增量叉乘公式,建立了圆锥补偿系数方程,给出了基于该方法的21种圆锥补偿算法.并对圆锥补偿误差特性进行了仿真研究,最后给出了计算机仿真结果.      

捷联惯导系统划船效应补偿算法研究

高速、高精度的划船效应补偿算法是提高捷联惯性导航系统(SINS)性能的重要环节.研究了划船效应补偿算法和划船效应补偿误差特性,推导了通用划船效应补偿系数方程和误差公式,给出了17种划船效应补偿算法,并对划船效应补偿误差特性进行了仿真研究.      

基于超声波的数控加工自动在机测厚装置设计

介绍了厚度检测在数控加工中的重要性,尤其是对于大型薄壁零件.针对在机厚度检测的难点,将在机检测技术与超声波测厚相结合,开展了在数控机床控制下的自动厚度测量装置的设计研究.经验证,本装置可以提高检测效率,减少加工时间,降低加工成本.     

双轴惯导轴系非正交误差全空间补偿技术研究

旋转调制技术实现了捷联惯导的高精度长航时导航,但轴系非正交误差的存在影响着导航姿态精度。传统轴系非正交误差补偿方法是针对旋转轴停留在固定位置完成的,提出一种全空间的轴系非正交误差补偿方法,不限定旋转轴的转停位置。试验结果证明该误差补偿方法较传统方法更优,对惯导姿态精度提升明显。     

Characterisation of residual ionospheric errors in bending angles using GNSS RO end-to-end simulations

Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique.     

一种双铰接结构柱塞杆头角度测量装置

发明了一种结构简单、操作方便的双铰接结构柱塞杆头角度测量装置,用于解决飞行器马达检修时柱塞杆头最大空间偏转角的检测问题,检测表明,测量准确、快捷,可满足飞行器马达检修的要求。     

Regional moment-independent sensitivity analysis with its applications in engineering

Traditional Global Sensitivity Analysis (GSA) focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output is beyond the traditional GSA techniques.To fully address this issue,in this work,two regional moment-independent importance measures,Regional Importance Measure based on Probability Density Function (RIMPDF) and Regional Importance Measure based on Cumula tive Distribution Function (RIMCDF),are introduced to find out the contributions of specific regions of an input to the whole output distribution.The two regional importance measures prove to be reasonable supplements of the traditional GSA techniques.The ideas of RIMPDF and RIMCDF are applied in two engineering examples to demonstrate that the regional moment-independent importance analysis can add more information concerning the contributions of model inputs.