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.     

Development and performance evaluation of tropospheric scintillation model on Ku-band satellite link over Akure,Nigeria

Existing amplitude scintillation prediction models often perform less satisfactorily when deployed outside the regions where they were formulated. This necessitates the need to evaluate the performance of scintillation models developed in one region using data data from other regions while documenting their relative errors. Due to its variation with elevation angle, frequency, other link parameters and meteorological factors, we employed three years (January 2016 to December 2018) of concurrently measured satellite radio beacons and tropospheric weather parameters to develop a location-based amplitude scintillation prediction model over the Earth-space path of Akure (7.17^oN, 5.18^oE), South-western Nigeria. The satellite beacon measurement used Tektronix Y400 NetTek Analyzer at 1 s integration time while meteorological parameters, namely; temperature, pressure and relative humidity were measured using Davis Vantage Vue weather station at 1 min integration time. Comparative study of the model’s performance with nine (9) existing scintillation prediction models indicates that the best and worst performing models, in terms of root mean square error (RMSE), are the Statistical Temperature and Refractivity (STN) and direct physical and statistical prediction (DPSP) models with values 11.48 and 51.03 respectively. Also, worst month analysis indicates that April, with respective enhancement and fade values of 0.88 and 0.90 dB for 0.01% exceedance, is the overall worst calendar month for amplitude scintillation.     

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。     

CBERS-1卫星IRMSS数据在城市绿地系统规划的应用

文章以CBERS -1卫星长沙幅IRMSS数据作为基础资料 ,利用PCI遥感图像处理软件对数据进行了预处理和应用实验。实验证明CBERS -1卫星的IRMSS数据图像信息丰富 ,可解译程度较高 ,能满足大中城市中等比例尺城市绿地系统规划遥感调查的要求     

电液位置伺服系统的动态试验研究

本文研究了快速响应的电液位置伺服系统动态试验,着重讨论了在实践中如何选择伪随机二位式最大长度序列(PRBS)参数的问陋,并提出快速响应系统PRBS参数选择的原则,使系统辨识精度提高约15％。     

改进的次时间最优控制

本文在[1][2]基础上进一步探讨了次时间最优控制的改进问题,深入地阐明了次时间最优控制的某些特性后,提出了一个新的改进的设计方法。按照这种方法设计控制系统,不但实用而且可以大幅度提高次时间最优控制的最优性。并用实例比较了各种方法,证明了本文提出的方法的优越性。本文提出的方法应用于工程设计,对于提高系统的最优性是非常有效的。     

构建我国"绿色"税收体系的设想

通过阐述“绿色”税收体系的理论基础是外部性理论，分析了我国工业化进程中的环境现状，环境污染造成的危害，同时借鉴西方国家开征“绿色”税制的成功经验，提出了费改税、完善税种、开征新税、完善相关政策等构建我国“绿色”税收体系的初步设想。     

Digital Aircraft Sheet Metal Part Manufacturing System and Its Key Technology

The architecture of digital sheet metal manufacturing system is proposed based on the classification of sheet metal manufacturing information.The essence of digital manufacturing is the definition,management and transfer of information,and the key technologies are brought forward and described.It is pointed out that knowledge-based manufacturing elements design is necessary to make digital technology efficient.The management of all kinds of sheet metal manufacturing element information is to build single source of manufacturing data.Multi-state model-based digital transfer and coordination method is designed to provide a foundation for digital manufacturing of aircraft sheet metal part.The application of digital sheet metal manufacturing is exemplified with an aircraft sheet metal part.The application result is compared to that of the traditional analog transfer technology.It is shown that the developed technology can improve part quality,shorten manufacturing time and lower manufacturing cost.     

基于因子模糊化BP神经网络的磨损颗粒识别

在引入了一套磨粒形态学描述子来提取磨损颗粒的显微形态特征的基础上 ,采用人工神经网络技术 ,编制了用于磨损颗粒自动识别的 BP网络计算机模拟程序。在网络训练的过程中应用了本文引入的因子模糊化训练方法 ,使训练速度大大加快 ,以异或问题为例 ,速度可提高 5～ 1 0倍。应用此网络对磨粒测试库进行识别实验 ,识别正确率在 90 %以上 ,并且识别速度很快 ,大大优于传统的磨粒识别方法。     

某型无人直升机遥控系统BIT技术研究与实现

机内测试 (Built- In Test,简称 BIT)是一种能显著改善系统或设备测试性和诊断能力的重要技术手段。文中研究如何在遥控系统中运用 BIT技术来提高其测试性 ,并提出了一种分层测试方案 ,研究成果已应用于某型无人驾驶直升机 ,满足了遥控系统的测试性要求