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.     

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.     

热处理作业系统中安全性评价的AHP方法

本给出了系统安全性评价的AHP方法，叙述了该方法的基本步骤，并以沈阳某集团公司热处理弹簧厂评价的实例说明了该方法的有效性。     

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。     

HML系统在商店偏好决策模型中的应用研究

对混合式机器学习系统（HML）进行了全面系统的介绍，并将其运用于服装消费商店偏好决策行为的研究中。采用上海统计局家庭调查网络，对300户家庭进行抽样分析后发现，服装消费商店偏好的主要影响因素是地区、季节、丈夫和妻子的学历、职业以及子女性别。在此基础上，将HML分析所得的结论与传统的研究方法和结果进行了系统比较：从方法上来看，因为属性变量包含间断变量和连续变量两种，因此传统统计分析要运用两种不同的检测方法对影响因素的相关性作出判断，结果需要经过统计学分析，才能得到结论；而HML分析结果比较直观和简单，便于理解。     

滚珠丝杠螺距误差补偿法提高数控机床定位精度的研究

在详细论述、对比了实现数控机床滚珠丝杠螺距误差补偿的硬件、软件方法的原理基础上,对滚珠丝杠螺距误差软件补偿法可有效提高数控机床的定位精度进行了试验验证。     

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。     

适用于含多个隐式极限状态方程的飞机结构系统安全分析新方法

工程复杂随机结构的概率安全分析中，最重要的两个步骤是建立所有失效模式的极限状态方程和计算所建立极限状态方程的失效概率。一般来说大型复杂工程结构的极限状态方程都是隐式的，且当材料参数、结构参数和外载荷等均为随机变量时，极限状态方程均为非线性的，为此文中提出了建立真实复杂结构多模式隐式极限方程的等效方法。该方法对于单个极限状态方程采用在均值点展开成线性项和高次项修正的方式，在概率等效的基础上，建立起原非线性隐式极限状态方程的概率等效线性显式极限状态方程。当结构系统所有极限状态方程都建立了其等效显式线性极限状态方程后，即可利用可得的可靠性分析方法来计算结构系统的等效失效概率。所提方法被用于真实飞机结构翼身连接接头的强度刚度多模式可靠性分析，与迭代响应面法计算结果的对比表明，所提方法具有较高的精度。并且所提方法可以与任何标准有限元程序相结合，而标准有限元程序是当今处理结构力学分析与设计的强有力的工具，文中方法提供了力学分析与概率安全分析相结合的合理连接，其应用前景将是十分广泛的。