角振动校准装置研究

为提升对惯性器件的动态性能评价能力,通过对被校传感器施加标准正弦角振动激励,精确测量角振动过程,实现了对角振动传感器的校准。基于不同频段的特点,将校准频段划分为低频和高频2部分,并提出空气轴承与无刷直流力矩电机相结合的低频角振动台方案,以及轻质空心杯精密空气轴承与框式电磁驱动结构相结合的高频角振动台方案;分别采用精密角度编码器和衍射光栅激光干涉仪实现对低频和高频角振动的测量,成功研制出频率范围为0.25~550Hz、角加速度范围为0.1~1 760rad/s2以及角速度波形失真小于2%的角振动绝对法校准装置。与德国国家物理技术研究院的角振动校准装置相比,该装置能够显著提升承载能力,可广泛用于惯性器件动态性能的测试与评价。     

某3级风扇试验流场诊断及性能优化

压气机试验是检验压气机设计是否达标的重要过程,并可在原设计基础上进行优化来发掘设计的潜能。利用级间总压和壁面静压在某3级风扇第1阶段试验对级间流场进行了详细测量和级性能诊断,提出了静叶角度优化方案;通过第2阶段试验,得出了角度优化后使设计转速喘振裕度提高了7.5个百分点,达到了设计指标的结论。流场诊断技术在压气机试验中起到了关键作用。结果表明:壁面静压结合级间径向总压测量方法基本能够满足在压气机试验中性能优化的需要。     

国产高档数控系统在航空领域的应用与性能分析

基于目前国产数控系统在航空结构件加工中的实际运行情况以及在使用过程中暴露出的问题,详细统计并分析了国产数控系统在航空结构件加工中的应用现状和综合性能。结合"工业4.0"发展理念,探讨了面向航空领域国产数控系统对航空企业实现智能化制造的意义和未来发展。     

机场容量利用及流量分配优化策略

为了充分利用机场容量,减少航班延误,需要合理分配进离场流量。以机场容量作为约束,以进离场航班总延误成本最小作为目标,建立进离场流量分配优化模型。构建随延误时间呈超线性增长的延误成本计算公式,引入航班进离场延误成本权重系数作为不同进离场优先级的决策偏好信息。用动态规划法求解模型,并引入最优决策候选集合的概念,缩小计算过程中的搜索量,减少计算时间。算例结果分析表明,方法可以在机场容量约束下得出进离场流量分配的最优策略,使得航班总延误成本最小,并且快速计算可以满足实时决策支持的要求。     

面向未知区域深度测量的序列图像稠密点特征生成算法

对未知着降区平坦度测量是无人机在复杂地形下安全着陆的关键问题。首先,根据小孔成像原理推导出基于单目序列图像的未知区域深度计算方程;其次,针对稀疏匹配存在深度信息重构误差大而稠密匹配在平滑区域误匹配率高的问题,提出一种基于Delaunay三角剖分的稠密点特征生成算法;然后,分别对序列图像中的2帧图像提取亚像素级Harris角点和尺度不变特征变换(SIFT)特征点,并分别进行特征点匹配;再以2种特征点间的欧氏距离作为约束条件将2种特征点进行融合,生成准稠密特征点;最后,将准稠密特征点进行Delaunay三角剖分,并根据每个剖分三角形上3个顶点像素偏差的方差值制定稠密特征点的生成策略,并结合所提出的深度计算方程计算整个未知区域各点的深度信息。通过Vega Prime(VP)搭建仿真演示验证系统,实验结果表明在机载相机距地面400m处计算高度分别为90m和55m的物体深度信息时,其深度测量相对误差不超过0.89%,具有较高的精度。     

民用飞机静气动弹性载荷计算方法研究

以某大型客机为例,根据气动外形利用有限元软件PANTRAN建立高阶气动面元,利用ZONAIR静气动弹性方法,分析了其弹性载荷,包含气动力系数、过载、迎角,并与刚性载荷进行了对比。此方法合理可靠,可用于民用飞机的弹性载荷设计分析。     

无网格法耦合RNG k-ε湍流模型在亚、跨声速翼型黏性绕流中的数值模拟

基于移动最小二乘无网格方法,耦合RNG(Re-Normalisation Group)k-ε湍流模型求解雷诺平均Navier-Stokes方程。采用AUSM(Advection Upstream Splitting Method)+-up迎风格式求解数值通量,应用在高度各向异性点云结构中取得良好结果的点云重构技术结合移动最小二乘法拟合空间导数,并用三阶SSP(Strong Stability Preserving)型Runge-Kutta显式时间推进格式求解离散后的控制方程。在此基础之上,实现了对NACA0012、RAE2822翼型亚、跨声速黏性绕流的数值模拟,给出了翼型表面压力系数分布曲线、不同位置处的平均速度剖面、马赫数等值线等计算结果,并与实验值及相关文献数值模拟结果进行比较,结果吻合较好。表明所发展的结合点云重构技术的无网格方法耦合RNGk-ε湍流模型能够成功模拟翼型亚、跨声速黏性绕流,验证了所提算法的有效性,并拓展了无网格方法求解湍流流动的途径。     

一种基于冗余测量的自适应卡尔曼滤波算法

针对目前自适应滤波算法的不足,在测量系统量测噪声方差未知的情况下,设计了一种基于冗余测量的自适应卡尔曼滤波(RMAKF)算法。通过对系统冗余测量值的一阶、二阶差分序列进行有效的统计分析,可以准确估计系统量测噪声统计特性,进而在滤波过程中自适应调节噪声方差阵R,提高滤波精度。以全球定位系统/惯性导航系统(GPS/INS)松组合导航系统为对象进行了仿真实验,结果表明该算法在测量系统噪声特性未知或发生改变时,可对其进行准确估计,在采用低精度惯性器件情况下,滤波结果较其他主要自适应卡尔曼滤波算法有较明显的改进。     

Practical compensation for nonlinear dynamic thrust measurement system

The real dynamic thrust measurement system usually tends to be nonlinear due to the complex characteristics of the rig, pipes connection, etc. For a real dynamic measuring system,the nonlinearity must be eliminated by some adequate methods. In this paper, a nonlinear model of dynamic thrust measurement system is established by using radial basis function neural network(RBF-NN), where a novel multi-step force generator is designed to stimulate the nonlinearity of the system, and a practical compensation method for the measurement system using left inverse model is proposed. Left inverse model can be considered as a perfect dynamic compensation of the dynamic thrust measurement system, and in practice, it can be approximated by RBF-NN based on least mean square(LMS) algorithms. Different weights are set for producing the multi-step force, which is the ideal input signal of the nonlinear dynamic thrust measurement system. The validity of the compensation method depends on the engine’s performance and the tolerance error0.5%, which is commonly demanded in engineering. Results from simulations and experiments show that the practical compensation using left inverse model based on RBF-NN in dynamic thrust measuring system can yield high tracking accuracy than the conventional methods.     

Specific grinding energy and surface roughness of nanoparticle jet minimum quantity lubrication in grinding

Nanoparticles with the anti-wear and friction reducing features were applied as cooling lubricant in the grinding fluid. Dry grinding, flood grinding, minimal quantity of lubrication（MQL）, and nanoparticle jet MQL were used in the grinding experiments. The specific grinding energy of dry grinding, flood grinding and MQL were 84, 29.8, 45.5 J/mm³, respectively. The specific grinding energy significantly decreased to 32.7 J/mm³ in nanoparticle MQL. Compared with dry grinding, the surface roughness values of flood grinding, MQL, and nanoparticle jet MQL were significantly reduced with the surface topography profile values reduced by 11%, 2.5%, and 10%,respectively, and the ten point height of microcosmic unflatness values reduced by 1.5%, 0.5%,and 1.3%, respectively. These results verified the satisfactory lubrication effects of nanoparticle MQL. MoS₂, carbon nanotube（CNT）, and ZrO₂ nanoparticles were also added in the grinding fluid of nanoparticle jet MQL to analyze their grinding surface lubrication effects. The specific grinding energy of MoS₂ nanoparticle was only 32.7 J/mm³, which was 8.22% and 10.39% lower than those of the other two nanoparticles. Moreover, the surface roughness of workpiece was also smaller with MoS₂ nanoparticle, which indicated its remarkable lubrication effects. Furthermore,the role of MoS₂ particles in the grinding surface lubrication at different nanoparticle volume concentrations was analyzed. MoS₂ volume concentrations of 1%, 2%, and 3% were used.Experimental results revealed that the specific grinding energy and the workpiece surface roughness initially increased and then decreased as MoS₂ nanoparticle volume concentration increased.Satisfactory grinding surface lubrication effects were obtained with 2% MoS₂ nanoparticle volume concentration.