Near-wall topological patterns and flow structures over a simplified Danaus plexippus model

Studies on the high-lift mechanisms of butterfly gliding flights shed light on the design of the micro air vehicles. The flow field around a simplified Danaus plexippus model is investigated using the hydrogen bubble visualization and the Particle Image Velocimetry (PIV) techniques. There are three near-wall topological patterns with different Angles of Attack (AoAs): the separation bubble, the Leading-Edge Vortex (LEV) and the high AoAs flow. For the separation bubble pattern, two saddles and two foci form in the middle of the model. The features of the LEV pattern are the leading-edge separation lines. The topological characteristics of the separation lines are changed by the interaction between the LEV and the Wing-Tip Vortex (WTV). For the high AoAs flow pattern, four unstable foci are found at the forewing and the hindwing respectively. The angle between the trajectory of the WTV and the model increases with increasing AoA even though the slope of the WTV angle versus AoA curve declines at the moderate AoAs.     

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating machinery is vital in manufacturing system, which can prevent catastrophic failure and reduce financial losses. Recently, Deep Learning (DL)-based fault diagnosis method becomes a hot topic. Convolutional Neural Network (CNN) is an effective DL method to extract the features of raw data automatically. This paper develops a fault diagnosis method using CNN for InfRared Thermal (IRT) image. First, IRT technique is utilized to capture the IRT images of rotating machinery. Second, the CNN is applied to extract fault features from the IRT images. In the end, the obtained features are fed into the Softmax Regression (SR) classifier for fault pattern identification. The effectiveness of the proposed method is validated using two different experimental data. Results show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.     

改革开放以来我国社会管理思想的发展脉络及评述

改革开放以来,市场经济使国家和社会的关系发生了深刻变化,中国共产党在治国理政的过程中,不断探索和调整适合我国国情和发展需要的社会管理理念、方式和决策机制。从十一届三中全会至今,历次党代会上中国共产党都对社会管理都有新的认识、新的提法和新的部署,反映了党在不断探索和调试的过程中,在理论和实践的互动中社会管理思想的逐步形成。     

作动器故障下的无人机容错控制方法

在执行任务过程中,无人机的传感器、作动器等均可能出现故障。文章针对常规布局无人机的作动器故障,提出了 1种反步法和控制分配相结合的容错控制方法。首先,建立无人机数学模型,并对作动器故障进行分类和建模;然后,根据模型设计反步最优控制器和基于控制分配的容错控制器;最后,通过仿真验证表明,所设计的容错控制方法能够实现作动器故障下的姿态快速稳定控制,且稳定性好,基本无侧滑角,各操纵面均在约束范围内,达到容错控制要求。     

发动机故障诊断的变记忆约束滤波算法

为提高故障诊断可靠性,给出了3种利用多次测量信息减少测量误差影响的方法,即变记忆约束滤波算法、分段算术平均预平滑算法以及指数顶平滑算法。其中,变记忆约束滤波算法能够有效地避免由于故障方程多重共线性所引起的病态解。证明了多故障诊断问题中滤波算法与分段算术平均算法的等价性,证明了在衰减滤波的条件下（第一变记忆因子小于1）,随测量点数的增加,变记忆滤波算法的第一变记忆因子与指数平滑的平滑系数之和趋近于1。利用计算机仿真方法对于所得结论进行了检验。     

基于故障字典的旋转整流器故障检测方法

以交流电为主要电源的飞机普遍采用无刷交流发电机作为发电装置,但由于半导体器件抗干扰、抗过载能力差,旋转整流器成为故障发生率较高的部件,文中介绍了利用快速傅里叶变换（FFT）通过对励磁电流的分析来检测可能出现的故障,并利用故障字典快速地判断出故障原因。     

Plane wave spectrum and boresight error of radome-enclosed antennas

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角速率平台伺服机构的智能控制与容错研究

介绍了角速率平台伺服机构智能控制研制进展。用单片机控制,对角速率反馈通道实现了2次故障判别、1次系统重构。用Fuzzy控制建立了相应隶属函数,确定了故障判别阈值。实验表明系统工作稳定,故障的Fuzzy差别合理,故障通道切换平稳,重构后系统工作仍正常。     

智能诊断的定量推理机制和最优推理环境

描述和分析了一种新的基于智能信息处理的故障检诊方法,可以处理复杂动态系统故障检诊面临的复杂故障组合模式和时间特性。从推理机制的量化和推理环境的优选两方面完善了该理论,使其诊断能力、实时性和适用范围都得到提高。推理机制的量化是通过引入概率信息实现的。考虑到诊断过程中可能出现新的故障。又进一步引入了候选项集合扩张机制描述该现象,并提供了相关的概率计算公式。推理机制定量化使得诊断结果可以精确度量,检诊过程也可精确控制。推理环境优选则是通过引入熵信息实现的,由此提高了诊断效率。