基于可靠性数据的航材备件需求预测方法

航材备件的需求预测已成为装备综合保障领域研究的难点.主要对各部件寿命分布类型进行归纳与总结,建立多数零件服从寿命分布类型的需求预测模型,并对军机执行任务这一特殊情况建立了战损备件预测模型.以可靠性数据为研究基础,对正态分布、指数分布、威布尔分布等备件进行分类分析,根据实际情况逐步精确备件保障概率的取值.计算结果表明,方法能给出合理的备件保障概率和备件需求预测结果.     

基于遥测数据的无人机气动参数辨识方法研究

针对无人机在高空低速飞行时易受风场影响及在数据分析时遥测数据不完备的问题,进行了气动参数辨识方法研究,提出了基于空速管平面矢量三角形的风场估计方法及基于风场信息修正的气动角估计方法。以某型无人机为例,对遥测数据进行了充分分析与信息综合,运用逐步回归方法进行了纵向气动参数辨识,并进行了实验验证。结果表明,模型计算结果与实测数据吻合较好,说明所提方法有效。考虑到辨识模型的数学本质,该方法对其他固定翼无人机同样适用。     

Multi-state autonomous drilling for lunar exploration

Due to the lack of information of subsurface lunar regolith stratification which varies along depth, the drilling device may encounter lunar soil and lunar rock randomly in the drilling process. To meet the load safety requirements of unmanned sampling mission under limited orbital resources, the control strategy of autonomous drilling should adapt to the indeterminable lunar environments. Based on the analysis of two types of typical drilling media (i.e., lunar soil and lunar rock), this paper proposes a multi-state control strategy for autonomous lunar drilling. To represent the working circumstances in the lunar subsurface and reduce the complexity of the control algo-rithm, lunar drilling process was categorized into three drilling states:the interface detection, initi-ation of drilling parameters for recognition and drilling medium recognition. Support vector machine (SVM) and continuous wavelet transform were employed for the online recognition of dril-ling media and interface, respectively. Finite state machine was utilized to control the transition among different drilling states. To verify the effectiveness of the multi-state control strategy, drilling experiments were implemented with multi-layered drilling media constructed by lunar soil simulant and lunar rock simulant. The results reveal that the multi-state control method is capable of detect-ing drilling state variation and adjusting drilling parameters timely under vibration interferences. The multi-state control method provides a feasible reference for the control of extraterrestrial autonomous drilling.     

经济先发地区居民收入对幸福感影响的实证研究——基于非参数、半参数及分位数回归方法

选择经济先发居民为研究对象,通过构建半参数及分位数回归模型,系统研究绝对收入、相对收入、期望收入等变量对幸福感的影响,我们发现:绝对收入对幸福感有显著的正相关关系;相对收入对高学历者影响不显著,但对低学历者影响显著;绝对收入对幸福感越低者的影响越显著;相对收入对中低幸福感群体影响显著,每周工作时间对低幸福感群体影响显著且强度大,但对高幸福感群体的影响力在降低。     

一种基于非线性回归的载人航天器密封舱内在轨噪声分析方法

文章提出一种载人航天器密封舱内噪声非线性回归通用分析方法,可基于地面噪声试验测得的数量较多的数据样本和在轨噪声测试获取的少量数据样本,建立密封舱内位置–在轨噪声的数学模型。经验证该模型能够较为准确地拟合密封舱内在轨噪声水平,从而为开展载人航天器的降噪设计、优化噪声仿真模型和验证降噪措施效果提供数据支持。     

某型直升机维修保障能力生成模式研究

某型直升机是陆航部队近年来新装备的主力作战机型,目前正处于装备部队初期的故障高发阶段,而部队有限的装备维修保障能力直接制约了该型机战斗力的形成。本文结合前期对某型直升机的自身技术特点及其装备维修保障的研究,综合使用单位反映的各种问题,深入剖析了制约其维修保障能力形成的原因,以期为后续新装备快速形成装备维修保障能力提供借鉴。     

基于小波变换和支持向量机的开关电流电路故障诊断新方法

针对开关电流(Switched current,SI)电路的故障诊断和定位问题，为进一步提高故障诊断准 确率，提出了基于小波变换和粒子群优化(Particle swarm optimization，PSO)支持向量机 (Support vector machine，SVM)的开关电流电路故障诊断新方法。该方法首先对节点电流 信号进行蒙特卡罗分析，然后通过小波分解计算分形维数，再利用核主元分析（Kernel pri ncipal component analysis，KPCA）降低特征值维数，实现最优故障特征的提取。最后通 过PSO SVM完成对各种故障模式的分类。对六阶切比雪夫低通滤波器进行了仿真实验验证， 获取了较高的故障诊断准确率，与其他方法进行比较，实验结果显示了本文方法的优越性。     

Behavior and functional modeling methods of doubly salient electromagnetic generators for aircraft electrical power system applications

The Doubly Salient Electromagnetic Generator(DSEG) is a promising candidate in aircraft generator application due to the simplicity, robustness and reliability. However, the field windings and the armature windings are strongly coupled, which makes the inductance characteristics non-linear and too complex to model. The complex model with low precision also leads to difficulties in modeling and analysis of the entire aircraft Electrical Power System(EPS). A behavior level modeling method based on modified inductance Support Vector Machine(SVM) is proposed. The Finite Element Analysis(FEA) inductance data are modified based on the experiment results to improve the precision. A functional level modeling method based on input–output characteristics SVM is also proposed. The two modeling methods are applied to a 9 kW DSEG prototype. The steady state and transient process precision of the proposed methods are proved by comparing with the experiment results. Meanwhile, the modeling time consumption, the application time consumption and the calculation resource demand are compared. The DSEG behavior and functional modeling methods provide precious results with high efficiency, which accelerates theoretical analysis and expands the application foreground of the DSEG in the aircraft EPS.     

基于欠采样的零阶优化算法

非平衡学习吸引了许多研究者的关注。一般情况下,少数类是更值得关注的,并且其误分类代价要远高于多数类。由于非平衡数据分布的非均衡性,标准的分类算法将难以适用。为了解决非平衡数据分类问题,给出了基于欠采样的零阶优化算法。首先,为了降低数据非平衡分布的影响,针对不同非平衡比的数据集给出了不同的两种采样策略。然后,采用了一种引入间隔均值项的支持向量机(Support vector machine,SVM)优化模型进行分类,并使用带有方差减小的零阶随机梯度下降算法进行求解,提高了算法的精度。在非平衡数据上进行了对比实验,实验证明提出的方法有效提高了非平衡数据的分类效果。     

考虑刀具偏心的微铣削加工表面粗糙度预测模型研究

基于微铣削刀具轨迹建立了考虑刀具偏心、最小切削厚度的塑性材料微铣削底面粗糙度的预测模型,预测结果表明粗糙度表面形貌呈锯齿状,刀具偏心会影响表面粗糙度的形貌周期和高度,并进行微铣削加工实验,对粗糙度预测模型进行了验证。采用回归统计方法,建立了脆性材料微铣削加工表面粗糙度预测模型,对加工表面形貌进行观察,利用响应曲面法得到了各铣削用量对表面粗糙度的影响规律。