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.     

变势能阱双稳态气动弹性能量收集的性能增强研究

提出一种新型的磁耦合变势能阱双稳态压电颤振能量收集器，设计了外部磁场作用下颤振能量收集系统的双稳态构型，并利用弹性支撑的外部磁铁的运动实现了变势能阱技术，解释了变势能阱双稳态对颤振能量收集系统的性能增强机理。建立了磁力-压电-气动弹性耦合的颤振能量收集系统的动力学分析模型，根据非线性磁偶极模型以及平衡点稳定性理论，讨论了系统出现双稳态构型的参数条件。对磁耦合双稳态颤振能量收集系统的动态特性进行了数值仿真研究，结果显示，双稳态构型能够使无磁力颤振能量收集系统的超临界颤振行为转变为亚临界颤振，发生极限环振动的风速能够降低50%以上，拓宽了能量收集器的有效工作风速范围，并分析了磁铁间距、磁偶极矩对能量收集性能的影响规律。采用弹性支撑的外部磁铁的运动来自适应调节内外部磁铁之间的距离，达到变势能阱的目的，有效地降低了双稳态的势能阱深度，使系统更容易发生双稳态势能阱间的跃迁运动，从而在双稳态的设计基础上，实现了能量收集工作风速范围和输出电功率的同步提升，为低风速下的能量收集提供了一种有效的设计途径。     

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.     

FDI飞机舵面损伤故障全局检测的非线性数学模型

阐述了飞机在单舵面损伤故障下 ,建立故障状态下的数学模型 ,以及同样输入条件下飞机正常运动时的数学模型 ,得到飞机在相同飞行条件下损伤时的气动系数和无损伤正常时的气动系数 ,最终得到气动系数的残差。这将为以后飞机过载残差和角加速度残差奠定基础。论文中结合一定的算例给予证实推论的正确性。     

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。     

一类非线性边值问题的激波解

研究了一类非线性奇摄动方程。首先得到了外层解，利用特异极限阶定了激波层的几种可能位置，对激波层的几种不同位置利用伸长变量构造出内层解。最后利用匹配原则求出了原方程在整个区间上的渐进解。     

质量矩导弹的神经网络及自适应非线性控制

本文对质量矩控制导弹的动力学方程简化和控制系统的设计进行了研究。详细阐述了所提出的控制方法，介绍了径向基单隐层神经网络进行误差补偿的算法原理，用Lyapunov理论证明了所采用方法的稳定性。在给出了质量矩导弹的六自由度动力学方程和简化后的方程后，用所提出的方法设计控制系统。通过仿真分析，得出了本文所提出的方法具有较好的误差补偿能力的结论。     

Phase coherence of MHD waves in the solar wind

Large amplitude MHD waves are commonly found in the solar wind. Nonlinear interactions between the MHD waves are likely to produce finite correlation among the wave phases. For discussions of various transport processes of energetic particles, it is fundamentally important to determine whether the wave phases are randomly distributed (as assumed in quasi-linear theories) or they have a finite coherence. Using a method based on a surrogate data technique and a fractal analysis, we analyzed Geotail magnetic field data (provided by S. Kokubun and T. Nagai through DARTS at the Institute of Space and Astronautical Science) to evaluate the phase coherence among the MHD waves in the earth's foreshock region. The correlation of wave phases does exist, indicating that the nonlinear interactions between the waves is in progress. This revised version was published online in August 2006 with corrections to the Cover Date.     

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。     

逆合成孔径雷达信号处理方法研究进展

在简要评述国内外现有的逆合成孔径雷达（ISAR）信号处理的运动补偿和成象方法之后，介绍了南京航空航天大学ISAR课题组近年来在ISAR信号处理方法研究中取得的主要进展，包括基于多散射点定位观点的雷达成象观测模型，基于最大似然原理的同时运动补偿和成象方法，基于最大似然原理的多目标成象方法和基于时频分析的多目标成象方法，以及超分辩成象方法，文末指出了在ISAR信号处理方面有待进一步研究的问题。