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.     

Multi-faults diagnosis of rolling bearings via adaptive customization of flexible analytical wavelet bases

Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features, as well as its easy burying in the complex, non-stationary structural vibrations and strong background noises. In this paper, a method based on the flexible analytical wavelet transform (FAWT) possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings. During the route of the proposed method, the proper FAWT bases are constructed via genetic optimization algorithm (GA) based on maximizing the spectral correlated kurtosis (SCK) which is firstly presented and proved to be efficient and effective in indicating interested fault mode. Via using the customized FAWT bases for each interested fault mode, the original vibration measurements are decomposed into fine frequency subbands, and the sensitive subband which enhances the signal-to-noise ratio (SNR) is selected to exhibit the fault signature on its envelope spectrum. The proposed method is tested via simulated signals, and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace, inner-race and roller defects. The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.     

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.     

PDM技术及其在直升机研制中的作用

本文首先分析了当前直升机在运用CAD/CAE/CAM技术进行研制中存在的一些问题,接着提供了解决的方法,介绍了PDM的概念、构成、主要功能。最后简述了PDM技术在直升机研制中的作用,以及企业在实施PDM当中应注意的一些问题。     

关于CCSDS体制数据安全保护实施位置的探讨

主要阐述CCSDS（空间数据系统咨询委员会）标准的信息安全问题，重点是航天器安全，从分析空间数据面临的安全威胁出发，讨论了CCSDS不同安全实施位置的特点；并在此基础上，通过对CCSDS业务及数据结构的影响对比，总结出不同安全实施方法的优缺点，该结合对于采用CCSDS标准的空间数据系统如何解决信息安全问题，具有一定的参考价值。     

基于关联分析的机载电子设备SRU级故障诊断方法

针对机载设备二类检测设备将故障隔离到SRU的要求,对LRU的内部结构进行了分析,提出了点、底项、组底项的概念,用关联值表示点与点之间、点与SRU之间及组底项之间的关联关系;针对多SRU结构UUT,提出逐级排除法故障诊断方法.     

一种用于人体早期病变诊断的仪器

根据探针在人体穴位电流量的变化情况 ,具体分析了该仪器电路设计的工作原理、电路结构及具体的使用方法。     

原子时自动测量及数据采集系统

介绍了普通的时间实验室的时频测量,实现自动测量和数据收集的基本系统方案,并以上海天文台原子时实验室为例介绍了实际可行的自动测量和数据收集系统,这个系统高性能、低价格,可应用于国内几乎所有的时间实验室。     

现场动平衡技术在生产中的应用

利用美国恩泰克公司提供的DP1500数据采集仪及现场动平衡软件,以实例说明了现场动平衡技术在锅炉引风机、排粉风机、电动机、机泵等转动设备不平衡故障排除中的应用,介绍了不平衡故障的识别方法,揭示出该技术在生产中的实用性、先进性和经济性.     

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。