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.     

Substitution of satellite-based land surface temperature defective data using GSP method

Land surface temperature (LST) as an important environmental variable provides valuable information for earth environmental system modelling. Currently, LST is obtained through satellite thermal sensors at various spatial and temporal resolutions. Although spatially continuous satellite-based LST measurements are intended to overcome the shortcomings of sparse ground-based LST measurements, LST images often contain anomalous values due to the existence of clouds or sensor malfunctioning. The problem becomes more serious where the users deal with high spatial resolution characterized by low temporal resolution. This study examines the capability of a newly developed graph signal processing (GSP) method using two-dimensional single-date thermal data. For this purpose, four Landsat/TIRS datasets are analyzed. The data of five elliptical regions on thermal images are eliminated and then reconstructed through the GSP method and using the LST values of the enclosing rectangles containing the ellipsoids. The results indicate that the temperature variation determined by the GSP method generally conforms to the original image LST values. According to a correlation test conducted on the original image LST and those obtained through the GSP method, the values vary from 58% to 95%, which is an above-the-average rate (RMSE from 0.69 to 2.27). The statistical analysis of the original image LST in both the elliptical regions and the enclosing rectangles containing the ellipsoids indicates that an increase in the variance of LST data causes an increased error in the calculation of temperature by the GSP method, and vice versa. The results of the analysis of variance (ANOVA) and Duncan test indicated that an increase in the number of the non-zero spectral bins would result in increased RMSE values for all the dates and the regions. Moreover, the model errors were significant at the 0.05 level across all the image date and five elliptical study regions. Based on the results, the use of this method is recommended for the reconstruction of LST missing values, where dissimilarity of atmospheric conditions limits the use of other methods that depend on the time series data of various dates and a great deal of data calculation.     

Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

高速低压差分信号（LVDS）器件应用设计方法研究

随着高速LVDS器件得到广泛应用，在高速信号使用LVDS传输时，信号传输线路问题、信号传输波形的最佳化成为非常重要的课题之一。由于印制电路板的布局布线直接影响信号传输质量，因此利用仿真对印制板分析成为设计上不可缺少的手段。有鉴于此，文章深入探讨了高速电路的设计，总结出设计技巧。     

VKM—5型立式捏合机研制与应用

介绍自行研制的VKM—5型立式捏合机的构造及工作原理,详述了该机采用液压传动和气动元件进行位置检测以及气、电、液安全联锁的特点,并说明与卧式捏合机对比试验情况。     

基于磁场映像的印制电路板故障诊断方法研究

简要分析了印制电路板的电磁场，提出了用电磁感应法测量磁场的电咱故障诊断新方法，并给出了测试系统组成方案。最后通过验证实验证明了该方法是确实可行的。     

胶州湾环境污染—卫星遥感信息分析

陆地卫星主题绘图仪(TM)图象和我国国土普查卫星全景相机照片解译分析与现场调查表明,胶州湾东岸工业废水污染相当严重,主要污染源集中在海泊河、李村河、娄山河以及沧口区沿海一线,污染水带宽达4～7km,在落潮流携带下扩散至湾口外海。由青岛碱厂排污形成的“白滩”污染区现有面积为0.53km~2。青岛市大气污染严重,源自市区的烟羽宽达14km,顺风飘逸远达30km,势必造成酸雨等灾害。     

激光外差干涉仪光电信号处理方法及特点

叙述和分析了外差激光干涉光电信号处理主其特点，指出了它们各自的应用范围，同时介绍了一处新型的光电信号处理方法，它不仅使外差干涉仪用于动态测量，而且可以同时实现高分辩率测量 。     

航天遥感仪器的反射镜轻量化的研究

反射镜轻量化是航天遥感仪器轻型化的重要技术途径之一。阐述了反射镜轻量化的意义,反射镜材料的选择,玻璃反射镜轻量化的结构型式和设计要求、设计方案和计算以及温度试验结果。     

Developing countries and remote sensing: how intergovernmental factors impede progress

Developing countries lag significantly behind more advanced nations in the local adoption and application of satellite remote sensing technology. Narrowing this gap through appropriate international cooperation is, however, often constrained by national interests and priorities. The paper presents an overview of several of these inter-governmental constraints using as its main basis the outcomes of recent regional and international conferences hosted by the United Nations. Future enhancement of international cooperation in remote sensing will occur best within settings where both developing and technologically advanced countries are sensitive and responsive to each other's concerns.