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.     

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。     

基于模糊粗糙集的飞机远程故障诊断模型研究

粗糙集和模糊集结合在飞机故障诊断领域有巨大的发展潜力。针对当前飞机故障诊断中所存在的问题,借助C/S模式,将粗糙集和模糊集结合,提出一种新型的飞机远程故障诊断模型,并且开发出远程诊断系统框架。系统的可行性和有效性得到了飞机故障诊断实例的证实。该系统具有客户端响应快、系统效率高、诊断及时的特点,对于当前民用飞机远程故障诊断具有重要应用价值。     

工业远程监控系统实施新方案

近期远程监控系统在工业中逐步推广,针对工业系统的特点和工业网络的实际情况,在原有工业系统的基础上,增加现场设备区域的图像监控和数据传输功能,提出了一种工业远程监控系统实施方案。本文论述了该系统的结构、原理及实现方法,经具体实施证明,本文提出的方案已基本能够满足一个通用的基于公用网络的远程视频监控系统的要求,体现了较重要的理论价值和很强的工程实用价值。     

星载遥感器在模拟空间环境中辐射定标设备研制

文章简述了星载遥感器辐射定标设备的研制过程及其在模拟空间环境中的调试过程,试验证明了该设备设计的合理性。     

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.     

一种基于移步预测消除脉冲串扰的快速算法

以毫米波主被动复合探测器为工程应用背景,通过分析信号的特点,提出一种基于移步预测思想的快速算法来消除脉冲调制信号对被动通道信号的串扰。仿真分析和实验结果表明,该方法对改善信噪比效果明显,而且具有成本低、速度快和易于工程化实现的优点。     

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。     

神经网络在未来超分辨雷达中的应用

最新的技术发展已为研制超分辨雷达创造了条件。它能够突破普通雷达基于匹配滤波原理的分辨能力,而实现超分辨。超分辨雷达的巨大计算量通常来自求解非线性最小二乘问题时的多维搜索。本文针对这一问题,研究了雷达信号处理中的两个典型例子:(1)利用阵列处理检测个数已知而方向未知的雷达目标;(2)对波音727飞机进行超分辨距离多普勒成像。说明Hop-field神经网络通过集体运算能够求解各种困难的最优化问题,因而在未来的超分辨雷达中有广阔的应用前景。