Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning

In aerospace industry, gears are the most common parts of a mechanical transmission system. Gear pitting faults could cause the transmission system to crash and give rise to safety disaster. It is always a challenging problem to diagnose the gear pitting condition directly through the raw signal of vibration. In this paper, a novel method named augmented deep sparse autoencoder (ADSAE) is proposed. The method can be used to diagnose the gear pitting fault with relatively few raw vibration signal data. This method is mainly based on the theory of pitting fault diagnosis and creatively combines with both data augmentation ideology and the deep sparse autoencoder algorithm for the fault diagnosis of gear wear. The effectiveness of the proposed method is validated by experiments of six types of gear pitting conditions. The results show that the ADSAE method can effectively increase the network generalization ability and robustness with very high accuracy. This method can effectively diagnose different gear pitting conditions and show the obvious trend according to the severity of gear wear faults. The results obtained by the ADSAE method proposed in this paper are compared with those obtained by other common deep learning methods. This paper provides an important insight into the field of gear fault diagnosis based on deep learning and has a potential practical application value.     

Fully distributed time-varying formation tracking control for multiple quadrotor vehicles via finite-time convergent extended state observer

This paper investigates a time-varying anti-disturbance formation problem for a group of quadrotor aircrafts with time-varying uncertainties and a directed interaction topology. A novel Finite-Time Convergent Extended State Observer (FTCESO) based fully-distributed formation control scheme is proposed to enhance the disturbance rejection and the formation tracking performances for networked quadrotors. By adopting the hierarchical control strategy, the multi-quadrotor system is separated into two subsystems: the outer-loop cooperative subsystem and the inner-loop attitude subsystem. In the outer-loop subsystem, with the estimation of disturbing forces and uncertain dynamics from FTCESOs, an adaptive consensus theory based cooperative controller is exploited to ensure the multiple quadrotors form and maintain a time-varying pattern relying only on the positions of the neighboring aircrafts. In the inner-loop subsystem, the desired attitude generated by the cooperative control law is stably tracked under a FTCESO-based attitude controller in a finite time. Based on a detailed algorithm to specify the cooperative control protocol, the feasibility condition to achieve the time-varying anti-disturbance formation tracking is derived and the rigorous analysis of the whole closed-loop multi-quadrotor system is given. Some numerical examples are conducted to intuitively demonstrate the effectiveness and the improvements of the proposed control framework.     

A survey of safety separation management and collision avoidance approaches of civil UAS operating in integration national airspace system

Recent years have witnessed a booming of the industry of civil Unmanned Aircraft System (UAS). As an emerging industry, the UAS industry has been attracting great attention from governments of all countries and the aviation industry. UAS are highly digitalized, informationized, and intelligent; therefore, their integration into the national airspace system has become an important trend in the development of civil aviation. However, the complexity of UAS operation poses great challenges to the traditional aviation regulatory system and technical means. How to prevent collisions between UASs and between UAS and manned aircraft to achieve safe and efficient operation in the integrated operating airspace has become a common challenge for industry and academia around the world. In recent years, the international community has carried out a great amount of work and experiments in the air traffic management of UAS and some of the key technologies. This paper attempts to make a review of the UAS separation management and key technologies in collision avoidance in the integrated airspace, mainly focusing on the current situation of UAS Traffic Management (UTM), safety separation standards, detection system, collision risk prediction, collision avoidance, safety risk assessment, etc., as well as an analysis of the bottlenecks that the current researches encountered and their development trends, so as to provide some insights and references for further research in this regard. Finally, this paper makes a further summary of some of the research highlights and challenges.     

Fault mode probability factor based fault-tolerant control for dissimilar redundant actuation system

This paper presents a Fault Mode Probability Factor (FMPF) based Fault-Tolerant Control (FTC) strategy for multiple faults of Dissimilar Redundant Actuation System (DRAS) composed of Hydraulic Actuator (HA) and Electro-Hydrostatic Actuator (EHA). The long-term service and severe working conditions can result in multiple gradual faults which can ultimately degrade the system performance, resulting in the system model drift into the fault state characterized with parameter uncertainty. The paper proposes to address this problem by using the historical statistics of the multiple gradual faults and the proposed FMPF to amend the system model with parameter uncertainty. To balance the system model precision and computation time, a Moving Window (MW) method is used to determine the applied historical statistics. The FMPF based FTC strategy is developed for the amended system model where the system estimation and Linear Quadratic Regulator (LQR) are updated at the end of system sampling period. The simulations of DRAS system subjected to multiple faults have been performed and the results indicate the effectiveness of the proposed approach.     

多臂空间机器人的视觉伺服与协调控制

针对多臂空间机器人自主目标抓捕任务，首先建立多臂空间机器人的运动模型和其与目标的相对运动模型，采用Kane方法建立多臂空间机器人的动力学模型；其次，研究基于视觉伺服的机械臂在线轨迹规划算法，并引入零反作用机动，消除机械臂运动对平台姿态的扰动；再次，在不使用零反作用机动功能时，分别使用基于角动量前馈补偿的协调控制算法和逆动力学方法设计了协调控制器，在机械臂运动时保持平台姿态和相对目标的位置。最后，开发了基于Matlab的仿真软件MASS（多臂空间机器人仿真），仿真结果校验了上述方法的有效性。     

多臂协调操作自由飞行空间机器人的位置和内力混合控制

基于多臂自由飞行空间机器人多臂协调操使负载沿着期望的轨迹运动并且控制负载所受的内力为目的，在多臂自由飞行空间机器人系统协调操作的动力学方程基础上，推导了各个机械臂协调操作负载按期望轨迹运动时各个机械臂关节的驱动力矩的计算方法；给出了作用在负载的内力的定义，根据关节力矩计算方法和PID反馈控制原理，建立了多臂自由飞行空间机器人协调操作负载时的位置和内力的控制算法；讨论了所提出的控制算法的稳定性问题，得到了负载的位置误差和内力误差的约束条件。通过仿真实验证明该控制算法能够使负载的实际位姿和内力收敛到期望的轨迹和内力。     

杆的纵向振动分析

杆的纵向振动是连续系统的内容，一个连续系统具有分布质量，分丰弹性，分布阻尼，杆的纵向振动可用波动方程来描述，是用空间与时间坐标来描述的，运动方程是偏微方程。     

最坏风模型及对飞机突防航迹跟踪的影响

针对一类非线性动力学系统,本文推导出二次型性能指标下的微分对策解,由此得到一组含有非线性因素的最环风模型,这一模型特别适用于研究作空间机动飞行的飞机受外界环境扰动的灵敏性问题。最后考察了这一变化风场对飞机突防航迹非线性解耦跟踪的影响。     

基于混合灵敏度下H∞控制在三滑块质量矩导弹上的应用

由于质量矩导弹是一个具有非线性和模型不确定性的多变量系统，为了进一步提高控制系统的鲁棒性，对三滑块质量矩导弹进行了鲁棒控制系统的研究。以所建立的质量矩导弹数学模型为基础，通过对模型合理的简化，得到一个耦合的非线性动力学系统，考虑到质量矩导弹的鲁棒性要求和三个滑块的协调控制问题，在混合灵敏度控制的基础上，采用H∞控制理论对导弹进行姿态控制系统的研究，仿真结果验证了这种方法的有效性。     

Obscured Activity: AGN, Quasars, Starbursts and ULIGs Observed by the Infrared Space Observatory

Some of the most ‘active’ galaxies in the Universe are obscured by large quantities of dust and emit a substantial fraction of their bolometric luminosity in the infrared. Observations of these infrared luminous galaxies with the Infrared Space Observatory (ISO) have provided a relatively unabsorbed view to the sources fuelling this active emission. The improved sensitivity, spatial resolution and spectroscopic capability of ISO over its predecessor Infrared Astronomical Satellite (IRAS) of enabled significant advances in the understanding of the infrared properties of active galaxies. ISO surveyed a wide range of active galaxies which, in the context of this review, includes those powered by intense bursts of star formation as well as those containing a dominant active galactic nucleus (AGN). Mid-infrared imaging resolved for the first time the dust enshrouded nuclei in many nearby galaxies, while a new era in infrared spectroscopy was opened by probing a wealth of atomic, ionic and molecular lines as well as broad band features in the mid- and far-infrared. This was particularly useful, since it resulted in the understanding of the power production, excitation and fuelling mechanisms in the nuclei of active galaxies including the intriguing but so far elusive ultraluminous infrared galaxies. Detailed studies of various classes of AGN and quasars greatly improved our understanding of the unification scenario. Far-infrared imaging and photometry revealed the presence of a new very cold dust component in galaxies and furthered our knowledge of the far-infrared properties of faint starbursts, ULIGs and quasars. We summarise almost nine years of key results based on ISO data spanning the full range of luminosity and type of active galaxies.