轨/姿控发动机试验数据快速自动处理技术

轨/姿控发动机试验数据需即时提供,大量数据的快速自动处理技术未见报道。在简述了高空模拟试验特点、Pacific6000原理及数据文件结构后,分析了当前计算方法优缺点;在此基础上,将网络脚本语言的设计思想引入试验数据处理过程,提出了实现数据快速处理的数据流式算法,进而形成自动处理技术;基于此算法开发了工程应用软件,在实际试验中应用,取得了良好效果。该技术对类似计算和海量数据的快速处理具重要工程参考意义。     

单相流体回路辐射器性能优化方法

文章以“神舟”飞船辐射器为例,对管肋式单相流体回路辐射器的肋宽进行了优化分析。采用理论分析与数值求解相结合的方法,分析了管肋式辐射器常用性能评价方法--能质比及微元能质比（单位质量散热能力）随肋片宽度的变化规律;而后以提高辐射器能质比为优化目的,对辐射器肋宽进行了优化,得出了辐射器的最佳能质比对应的肋宽表达式;最后给出了“神舟”飞船辐射器优化前后的参数对比。文章对管肋式辐射器的优化设计具有很好的参考价值。     

压缩映射原理在平台惯导系统加速度计标定中的应用

传统的平台惯导系统加速度计所采用的自标定方法受到加速度计零偏预装值的影响存在着一定的误差,而且加速度计标定参数准确性的验证方法也较为烦琐,不利于操作。基于压缩映射原理,针对平台惯导系统加速度计提出了一种迭代式标定方法,消除了传统加速度计自标定方法中的误差,同时提出了一种简单、有效地验证加速度计标定参数准确性的方法,并对这种迭代式加速度计标定方法的收敛性进行了证明以及试验验证。     

半球谐振子薄壁厚度不均匀性对陀螺精度的影响

针对半球谐振陀螺仪的工艺制造偏差,研究半球谐振子薄壁厚度不均匀对陀螺精度的影响,建立误差模型,分析误差机理．首先对谐振子进行应变分析,然后分析薄壳微元的受力情况,根据力和力矩平衡方程建立半球谐振子动力学方程,得出由于厚度不均匀造成的半球谐振陀螺仪角速率误差．研究结果表明其傅立叶展开式的1～3次谐波项对角速率误差无影响,而4次谐波有影响．为提高陀螺精度,对陀螺厚度不均匀加以平衡．     

刚性车轮月面牵引通过性的模型试验

以重塑模拟月壤为介质,利用深空探测车车轮牵引特性实验台,研究了月面巡视探测器的刚性轮齿车轮与模拟月壤的交互作用,分析了车轮转速、轮上载荷等试验因素对车轮牵引通过性的影响.研究结果表明,当车轮转速较低时,挂钩牵引力随滑转率的增加而不断提高;当车轮转速较高时,存在着临界滑转率点.轮上载荷的增加有利于提高车轮的挂钩牵引力,但对挂钩牵引力系数的影响较小.     

Introduction to the Payloads and the Initial Observation Results of Chang＇E-1

Chang'E-1,the orbiter circling the moon 200km above the moon surface,is the first Chinese Lunar exploration satellite.The satellite was successfully launched on 24th October 2007.There are 8 kinds of scientific payloads onboard,including the stereo camera,the laser altimeter,the Sagnac-based interferometer image spectrometer,the Gamma ray spectrometer,the X-ray spectrom-eter,the microwave radiometer,the high energy particle detector,the solar wind plasma detector and a supporting payload data management system.Chang'E-1 opened her eyes to look at the moon and took the first batch of lunar pictures after her stereo camera was switched on in 20th November 2007.Henceforth all the instruments are successfully switched on one by one.After a period of parameter adjustment and initial check out,all scientific instruments are now in their normal operating phase.In this paper,the payloads and the initial observation results are introduced.     

基于CMPSO算法的永磁同步电机转动惯量识别研究

永磁同步电机(PMSM)是一种具有很强非线性的动态系统,在工业驱动应用中发挥着重要作用。实时辨识转动惯量对于高精度PMSM系统控制和稳定性状态监测具有重要意义,但传统转动惯量识别方法精度较低。在传统离散模型参考自适应理论基础之上,用柯西变异粒子群优化(CMPSO)算法代替待辨识参数自适律设计环节,以实现PMSM转动惯量识别。该转动惯量辨识方法充分利用了CMPSO算法的快速高效收敛性,仿真结果和试验结果表明了可行性、正确性和准确性。     

基于双变量预测控制的表贴式永磁同步电机直接转矩控制系统

基于电压矢量幅值和相角为变量的表贴式永磁同步电机(SPMSM)定子磁链幅值和转矩表达式,给出了9个不同幅值和相角的备选电压矢量,采用预测控制计算得出施加不同电压矢量下一时刻的定子磁链幅值和转矩值,建立了基于磁链和转矩误差的目标函数,并选择使目标函数最小的电压矢量为作为下一时刻施加的最优电压矢量。仿真结果表明:在双变量预测控制下,SPMSM直接转矩控制系统运行良好,定子磁链轨迹为理想圆,磁链和转矩均符合控制要求,转速跟踪良好,定子电流波形正弦。进一步对比分析表明:与开关表和固定电压矢量选择策略相比,双变量预测控制能显著减小转矩和磁链脉动。与开关表相比,转矩脉动均方根误差降低了62.92%,磁链脉动均方根误差降低了45.05%,评价函数均值降低了60.30%;与固定电压矢量选择策略相比,转矩脉动均方根误差降低了22.40%,磁链脉动均方根误差降低了3.85%,评价函数均值降低了15.93%。     

Fault diagnosis based on measurement reconstruction of HPT exit pressure for turbofan engine

Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.