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.     

CFG桩复合地基应力比数值分析

本文采用有限元ANSYS程序对CFG桩复合地基的单桩桩体荷载传递规律、应力比及影响因素进行了分析,得出了减小应力比的方法和措施,对工程可起借鉴的作用。     

Digital Aircraft Sheet Metal Part Manufacturing System and Its Key Technology

The architecture of digital sheet metal manufacturing system is proposed based on the classification of sheet metal manufacturing information.The essence of digital manufacturing is the definition,management and transfer of information,and the key technologies are brought forward and described.It is pointed out that knowledge-based manufacturing elements design is necessary to make digital technology efficient.The management of all kinds of sheet metal manufacturing element information is to build single source of manufacturing data.Multi-state model-based digital transfer and coordination method is designed to provide a foundation for digital manufacturing of aircraft sheet metal part.The application of digital sheet metal manufacturing is exemplified with an aircraft sheet metal part.The application result is compared to that of the traditional analog transfer technology.It is shown that the developed technology can improve part quality,shorten manufacturing time and lower manufacturing cost.     

深空探测器推进系统

以技术较成效的月球探测器、火星探测器推进系统为重点，介绍了国外深空探测活动的情况。简述了深空探测对推进系统的需求、我国航天器液体推进技术的现状。认为我国的推进技术经一些适应性发展，即可满足深空探测的需求，并且设想了我国近期较为可行的深空探测器推进系统方案。     

Expectations for Infrared Spectroscopy of 9P/Tempel 1 from Deep Impact

The science payload on the Deep Impact mission includes a 1.05–4.8 μm infrared spectrometer with a spectral resolution ranging from R∼200–900. The Deep Impact IR spectrometer was designed to optimize, within engineering and cost constraints, observations of the dust, gas, and nucleus of 9P/Tempel 1. The wavelength range includes absorption and emission features from ices, silicates, organics, and many gases that are known to be, or anticipated to be, present on comets. The expected data will provide measurements at previously unseen spatial resolution before, during, and after our cratering experiment at the comet 9P/Tempel 1. This article explores the unique aspects of the Deep Impact IR spectrometer experiment, presents a range of expectations for spectral data of 9P/Tempel 1, and summarizes the specific science objectives at each phase of the mission.     

经营者股票期权激励制度的经济学分析

经营者股票期权激励制度是一种对经营者实施有效激励的制度创新，它蕴涵着深刻的经济学理论。以往的经济学者从不同的角度对其进行了解说，但这些理论解说缺乏内在统一性，因而对该制度的经济学理论进行系统地分析成为文章的宗旨。     

钢筋砼条基及独立柱基有效高度的实用计算公式

为了便于广大工程实践人员对基础有效高度的确定，根据规范GB50010－2002及GB50007－2002推导求解出基础有效高度的实用计算公式及计算表格。     

几种生长模型参数的最小二乘估计方法及应用

提出一种Logistic模型、Gompertz模型、Mitscherlich模型和Bertallanffy模型的分布参数估计方法，这种方法以加权最小二乘法为基础，推导求解分布参数的方程组。利用这类曲线模型中参数形式的特点，使同时求解三个参数的问题简化为同时求解两个参数的问题，并给出求解参数耦合方程组的二重二分迭代法。预测地基沉降的计算实例表明，这种方法对于迭代初值的选取要求较低、求解速度快、精度高，而且通过选取权因子可以对已有数据实现“重近轻远”的处理。     

Coactive design of explainable agent-based task planning and deep reinforcement learning for human-UAVs teamwork

Unmanned Aerial Vehicles (UAVs) are useful in dangerous and dynamic tasks such as search-and-rescue, forest surveillance, and anti-terrorist operations. These tasks can be solved better through the collaboration of multiple UAVs under human supervision. However, it is still difficult for human to monitor, understand, predict and control the behaviors of the UAVs due to the task complexity as well as the black-box machine learning and planning algorithms being used. In this paper, the coactive design method is adopted to analyze the cognitive capabilities required for the tasks and design the interdependencies among the heterogeneous teammates of UAVs or human for coherent collaboration. Then, an agent-based task planner is proposed to automatically decompose a complex task into a sequence of explainable subtasks under constrains of resources, execution time, social rules and costs. Besides, a deep reinforcement learning approach is designed for the UAVs to learn optimal policies of a flocking behavior and a path planner that are easy for the human operator to understand and control. Finally, a mixed-initiative action selection mechanism is used to evaluate the learned policies as well as the human’s decisions. Experimental results demonstrate the effectiveness of the proposed methods.     

基于高光谱和LiDAR的黄河口湿地植被分类方法

利用无人机（Unmanned Aerial Vehicle, UAV）高光谱影像（Hyper-spectral Imaging, HSI）和激光雷达（Light Detection and Ranging, LiDAR）数据开展黄河口湿地植被分类方法研究。由于高空间分辨率HSI光谱变异性强,以及LiDAR点云密度不均匀,分类结果呈现出“椒盐”现象。为了解决这些问题,本文提出了一种结合空谱特征融合和通道注意力机制的双分支卷积神经网络（SSF-C-DBCNN）。光谱注意力机制通过为每个波段分配不同的权重来减少光谱变异性的影响。空间注意力机制侧重于学习和强调特征表达能力强的密集点云区域空间信息,从而减轻LiDAR点云密度不均匀对结果的影响。最后,在双分支融合特征后引入通道注意力机制来提取更深层次的特征。利用UAV采集的HSI和LiDAR数据进行实验验证,结果表明,本文提出方法的性能优于随机森林和五种深度学习方法,分类结果更为贴合实际土地覆盖,有效地抑制了“椒盐”现象。