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.     

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。     

模拟磁带重放信号数字化过程中的频偏校正技术及应用

模拟磁带重放信号中存在的频率偏移会对信号的处理分析产生不利影响。利用模拟磁记录器的多个磁道同时记录的能力,将实际信号和特定的参考信号同时进行记录,磁带信号重放和数字化过程中,利用这个参考信号来控制A/D采集时钟的速度,从而可在很大程度上减少磁带重放系统带来的频率偏移。实验结果表明,该技术方法能有效地解决模拟磁带重放信号中存在的频偏问题。     

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。     

双舌型挡板VGT蜗壳速度场的试验研究

使用IFA30 0热膜风速仪 ,通过选择合适的低通滤波器、合适的采样频率和采样时间 ,用X形探针测量了其无叶喷嘴出口速度的分布以及蜗壳流道的速度场。结果表明 :在两挡板全关时 ,喷嘴出口速度分布较均匀 ;随两挡板开度变化 ,喷嘴出口速度分布变化较大 ;而且沿蜗壳周向其径向速度分布较均匀 ,切向速度分布变化较大 ;沿蜗壳轴向 ,两者变化均较大。当两挡板开度变化时 ,蜗壳流道截面上通流速度的分布不同于自由涡流规律 ,二次流速度分量分布形态类似。     

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。     

基于信号采样的干扰信号产生技术

目前电子对抗系统广泛使用的数字储频技术主要是通过采样、存储和复制产生干扰信号.阐述了基于采样技术的信号重构及其基本原理,重点介绍分析了在此基础上利用信号处理技术,合成产生干扰信号的原理和方法.     

一种新的共轭增强MUSIC测向算法

提出一种新的测向算法。利用阵列输出的非零时延互相关函数及其共轭形成伪阵列输出,从而得到伪协方差矩阵,对其进行特征分解,利用信号子空间与噪声子空间的正交性,搜索得到的空间谱函数的极大值点对应的角度就是波达方向。仿真实验表明,新算法可对多于阵元数的信号进行测向,其测角精度和分辨力优于MUISC和MUSIC-like算法。