粗糙条件熵算法在故障诊断中应用分析

给出了一种基于条件熵的算法,并应用于弹载电子设备故障诊断中。结果表明,诊断结果准确可靠,且弥补了差别矩阵算法和差别函数算法的不足。     

涡扇发动机故障诊断硬件在回路实时仿真平台

硬件在回路仿真是发动机故障诊断算法由理论转向实际工程应用的重要阶段,但目前航空发动机故障诊断算法的研究多数处于软件数字仿真阶段。构建民用涡扇发动机故障诊断算法硬件在回路实时仿真验证平台,开发考虑健康退化的民用涡扇发动机多维调度分段线性化模型,分析并模拟仿真民用涡扇发动机的四类典型常见故障。经过对相关诊断算法进行实验验证,表明该平台及使用的模型和方法都是行之有效的,具有一定的工程使用价值。     

基于融合诊断的某型飞机故障诊断应用研究

以某新型军用飞机的电传操纵系统为研究对象,分析了案例推理和故障树诊断的方法。在此基础上,提出了将两种方法进行融合的思想,开发了通用化的故障诊断软件,大大提高了故障诊断效率,对第三代飞机的故障诊断提供了一种有效的途径。     

Physical mechanism of the vertical electric field generation over active tectonic faults

The concept of the Global Electric Circuit (GEC) provides an explanation of the existence of a vertical atmospheric electric field and coupling between the ground and ionosphere. Presently, ionospheric physics pays more attention to electric fields and coupling processes in the polar and auroral regions, whereas in other areas the potential difference between the ground and ionosphere usually is not taken into account. Regional processes exist, however, that are able to significantly affect the GEC parameters and through modification of the ionospheric potential to create plasma density irregularities of different scales within the ionosphere. One such source of ionosphere modification is air ionization in the vicinity of active tectonic faults, which takes place due to increased radon emanation. This paper considers the process of local modification of the GEC and corresponding ionospheric variability due to tectonic activity.     

基于正交小波变换的动态系统的故障检测

利用正交小波变换在时-频域均有良好局部化的品质,提出了一种对动态系统故障诊断中非平稳信号进行分析与处理的方法.仿真结果表明,该方法不仅使测试结果更加精确,而且便于进行快速的故障诊断.     

一起波音737起落架指示系统故障分析

对一起波音737飞机起落架指示故障进行深入分析,并结合实际运行情况提出了相关的预防性措施。     

缔约过失责任问题探讨

缔约过失责任是在合同缔结过程中产生的一种责任形式，是合同法中一项独立的法律制度。缔约过失责任与违约责任有着本质的区别，是基于缔约方违反先合同义务产生的责任形式，其损害对象是对方的信赖利益，而不是合同利益。本文通过对缔约过失责任的论述，阐明其产生的理论基础、成立要件、责任形式以及立法现状和趋势，谨希望能有助于我国相关立法的发展与完善。     

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.     

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。