疲劳裂纹起始扩展门槛值的研究

 1.疲劳裂纹起始扩展门槛值(△K_(th))的概念 人们通常提到的疲劳裂纹扩展门槛值△K_(th)是在裂纹扩展过程中不断下降△K,使裂纹扩展不断减慢,直至停止扩展时所对应的△K值。它由降K程序测定,试验方法见文献。达到△K_(th)时裂纹前缘塑性区很小,在厚度和应力比一定的条件下,△K_(th)是材料常数。然而,在构件承受变幅交变载荷作用时,某级载荷使裂纹尖端产生应力强度因子K_(fmax),对应     

基于运动状态的航迹起始算法研究

 针对传统的基于逻辑的航迹起始方法在量测扩展过程中存在的弊端,提出了基于目标运动状态的航迹起始算法,并给出了更为精确的起始波门构造方法。利用目标的位置信息形成候选目标航迹,在候选目标航迹扩展过程中,采用提出的修正Hough变换提取目标状态信息,并根据目标〖JP2〗的状态信息对候选航迹进行检验。仿真结果表明,该算法比其他基于逻辑的方法有更低的虚警概率,并且对存储空间要求低,适于工程应用。     

浅析水平扭转M型下滑天线对入口高度及下滑角的影响

对于M型下滑天线,对天线作微调能改变近场DDM分布,从而对入口高度产生影响。本文阐述了扭动天线及调整辐射场形的原理。通过扭动上、下天线,定量分析入口高度和下滑角的改变量与扭动距离的依赖关系,并对飞行校验中的实例进行比较。对比扭动对近场(入口高度)和远场(下滑角)的影响。理论计算得出:上天线向跑道方向扭动一定角度,可以明显提高入口高度,向跑道外侧扭动后,入口高度减小;扭动下天线情况则相反,且两者基本都不影响下滑角。因此表明,扭动天线是一种有效改变近场的方法。     

基于先验门限优化准则的探测阈值自适应选择

针对 2维测量和 4 -sigma确认门 ,把先验检测门限优化准则和修正 Riccati方程的解析近似表示相结合 ,得到了在瑞利起伏环境下使跟踪性能优化的信号探测阈值解析表示式 ,从而使在线求解自适应信号探测阈值能比较容易地实现。通过研究和仿真发现 :在滤波稳定阶段 ,本文给出的自适应信号检测门限方法的跟踪性能优于固定虚警率方法的跟踪性能 ;基于先验检测门限优化准则实现检测 -跟踪的联合优化要求信噪比要大于一定的门限 ,在瑞利起伏环境下 ,对 2维测量和 4 -sigma确认门 ,该门限为 1 .57     

自适应阈值突发模式光接收机的性能分析

在考虑判决阈值的衰落时间和噪声特性对光接收机性能的影响后,提出了一种分析突发模式光接收机误码性能的综合模型,并分析了与传统的交流耦合光接收机相比较时,突发模式光接收机的灵敏度损失.     

断裂韧性K1C和断裂门槛值 Δ Kth可靠性测定方法

采用定量方程随机化方法,建立了断裂p-J_R-Δa曲线方程,断裂p-J_R-Δa曲线与钝化线的交点即为试验测定具有可靠度p的J积分临界值(J_1C)_p值,根据断裂力学测试原理,由试验测定(J_1C)_p值可转化出断裂韧性(K_1C)_p值;还建立了断裂门槛ΔK_th值的可靠性测定方法,并对试验数据进行了统计分析处理,得到了一些具有重要应用价值的结果和数据.研究发现:断裂门槛值ΔK_th服从正态分布.     

纳秒激光脉冲宽度对2024铝合金损伤特性的影响

飞机激光除漆对2024铝合金蒙皮可能造成潜在的损伤,需探究激光参数变化对基体材料表面的作用规律,其中脉冲宽度对激光-材料作用与材料损伤特性具有重要影响。本文采用COMSOL Multiphysics软件模拟分析了不同脉冲宽度时激光作用铝合金表面的温升特性,并借鉴ISO 11254 1-on-1激光损伤阈值测试方法研究了脉冲宽度对铝合金损伤阈值的影响,进一步分析了不同脉冲宽度下的烧蚀凹坑微观形貌、直径与深度变化规律。结果表明：铝合金表面峰值温度随脉冲宽度增加而降低;脉冲宽度从150 ns增加到240和330 ns时,铝合金损伤阈值从9.96 J/cm²分别增加到11.24和12.66 J/cm²,当激光能量密度达到损伤阈值时,3μm厚氧化膜被完全损伤,破坏了铝合金表面完整性;烧蚀凹坑直径和深度随脉冲宽度增加而增加,深度受影响程度更大。该研究可为激光与材料作用的脉冲宽度选择提供一定的参考。     

一种基于聚类分析的边带跟踪判决门限的确定

通过对窄带测角系统跟踪双噪声调频干扰信号合成边带时测角数据的分析,建立了一种边带跟踪情况下干涉仪鉴相器测角数据分布的数学模型.在用绝对误差和最小聚类算法提取角信息的基础上,推导出了一种基于聚类分析的绝对误差和门限的计算方法.理论分析和计算机仿真均证实了其用于边带跟踪判决门限的合理性与可行性.     

Lock threshold deterioration induced by antenna vibration and signal coupling effects in hypersonic vehicle carrier tracking system of Ka band

The envelope of a hypersonic vehicle is affected by severe fluctuating pressure, which causes the airborne antenna to vibrate slightly. This vibration mixes with the transmitted signals and thus introduces additional multiplicative phase noise. Antenna vibration and signal coupling effects as well as their influence on the lock threshold of the hypersonic vehicle carrier tracking system of the Ka band are investigated in this study. A vibration model is initially established to obtain phase noise in consideration of the inherent relationship between vibration displacement and electromagnetic wavelength. An analytical model of the Phase-Locked Loop(PLL), which is widely used in carrier tracking systems, is established. The coupling effects on carrier tracking performance are investigated and quantitatively analyzed by imposing the multiplicative phase noise on the PLL model. Simulation results show that the phase noise presents a Gaussian distribution and is similar to vibration displacement variation. A large standard deviation in vibration displacement exerts a significant effect on the lock threshold. A critical standard deviation is observed in the PLL of Binary Phase Shift Keying(BPSK) and Quadrature Phase Shift Keying(QPSK) signals. The effect on QPSK signals is more severe than that on BPSK signals. The maximum tolerable standard deviations normalized by the wavelength of the carrier are 0.04 and 0.02 for BPSK and QPSK signals,respectively. With these critical standard deviations, lock thresholds are increased from à12 andà4 d B to 3 and à2 d B, respectively.     

A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data

The current paper introduces a new multilayer perceptron (MLP) and support vector machine (SVM) based approach to improve daily rainfall estimation from the Meteosat Second Generation (MSG) data. In this study, the precipitation is first detected and classified into convective and stratiform rain by two MLP models, and then four multi-class SVM algorithms were used for daily rainfall estimation. Relevant spectral and textural input features of the developed algorithms were derived from the spectral MSG SEVIRI radiometer channels. The models were trained using radar rainfall data set colected over north Algeria. Validation of the proposed daily rainfall estimation technique was performed by rain gauge network data set recorded over north Algeria. Thus, several statistical scores were calculated, such as correlation coefficient (r), root mean square error (RMSE), mean error (Bias), and mean absolute error (MAE). The findings given by: (r = 0.97, bias = 0.31 mm, RMSE = 2.20 mm and MAE = 1.07 mm), showed a quite satisfactory relationship between the estimation and the respective observed daily precipitation. Moreover, the comparison of the results with those of two advanced techniques based on random forests (RF) and weighted ‘k’ nearest neighbor (WkNN) showed higher accuracy obtained by the proposed model.