马钢300 t 铁水预处理倾翻车液压系统优化

介绍了马钢四钢轧300t铁水预处理铁水车倾翻复位过程中经常出现液压缸卡阻故障,此故障不仅制约生产的正常运行,还易造成铁水罐外溢铁水的事故,通过对倾翻油缸缸口块进行重新优化,很好的解决了这一难题。     

Ausgleich der Volatilität der Erneuerbaren Energien mittels Wärmespeichern auf Salzbasis

To compensate for the volatility of renewable energies, solutions beyond fossil reserve power plants are needed. One approach is salt-based heat storage with phase change materials (PCM). In order to achieve economic efficiency, ambitious targets are required. A sensible and latent heat storage system for the temperature range around 400 °C based on salts and thermal oils with high development potential is presented.     

Bearing failure detection using matching pursuit

In this paper, a new approach to the detection of localized defects of rolling element bearings is proposed. It employs matching pursuit with time–frequency atoms to analyze bearing vibration and extract vibration signatures. In particular, this approach utilizes not only the temporal and spectral but also the scale characteristics of the vibration generated due to the presence of a defect for the detection. This leads to a high signal-to-noise ratio and facilitates considerably the detection at the early stage of failure development. Experimental results show that the proposed approach is sensitive and reliable and works better than continuous wavelet transform and envelope detection.     

基于PC机和80C196单片机的温度微机控制系统

文章介绍了由PC机和80C196单片机构成的热处理温度微机控制系统,并就集中温度数据采集方法、PC机和单片机的数据通信格式、单片机软硬件设计、双向晶闸管的触发电路等相关技术进行了分析,给出了串行通信中断接收及数据处理程序设计流程图.     

基于改进的K-means聚类图像分割算法

介绍一种采用K—L变换、二维向量小波和改进的K—means结合的图像分割算法。阐述和分析了二维向量小波变换和Laws纹理能量测度，得出图像每个像素点可用9个纹理特性来描述的结论。运用K—means算法的思想对其进行改进，最后得出分割后的图像。试验结果证明，运用以上处理方法可显著提高分割速度和精度。     

基于虚拟仪器的溢流阀动态特性测试技术

在分析溢流阀动态特性测试原理的基础上，设计了溢流阀动态特性测试虚拟仪器系统。此系统应用小波降噪的方法提高测试信号的质量，然后提取信号特征点，得到溢流阀动态特性的各项参数。     

小波分析在液压缸泄漏检测中的应用

本文介绍了一种基于小波分析的液压缸泄漏故障检测方法，通过检测液压缸工作腔压力信号小波变换在适当尺度上的极大值点，提取出压力信号的突变特征，从而为液压缸泄漏检测提供了定量的依据。     

小波变换在管道弱超声回波奇异性检测中的应用

研究了小波变换在细尺度下检测信号奇异性的原理。通过对样管中标准缺陷的超声回波分析试验,证明6层db5小波变换可以有效地分离出湮没在噪声中的微弱缺陷信号,并可以有效地分离出信号的孤立奇异点,准确定位缺陷出现时刻。     

基于小波包和支持向量机的滚动轴承故障模式识别

为了解决对故障轴承的特征提取和故障特征准确分类问题,提出了应用小波包变换和支持向量机相结合进行滚动轴承故障诊断的方法.小波包变换具有良好的时-频局部化特征,非常适于对瞬态或时变信号进行特征提取.而支持向量机可完成模式识别和非线性回归.利用上述原理根据轴承振动信号的频域变化特征,采用小波包变换对其提取频域能量特征向量,然后利用建立的支持向量机多故障分类器完成滚动轴承故障模式的识别.试验结果表明,支持向量机可以有效、准确地识别轴承的故障模式,为轴承故障诊断向智能化发展提供了新的途径.     

Surface wavelength content based clustering using neural networks for manufacturing process mapping

Manufacturing processes produce a unique texture on the surface that serves as a fingerprint of the process. It is possible to provide feedback to the process by studying the surfaces carefully. Analytical techniques such as Fourier analysis and digital filters are commonly used to characterize surface profiles. Parameters extracted from filtered profiles are monitored to detect variations in the process. This requires the development of an inference engine to map metrology parameters to manufacturing process parameters. This paper presents an artificial neural network (ANN) based inference engine for providing process feedback with surface finish input. Parameters such as R_a and W_a as well as advanced wavelet based features are extracted from surface finish data collected from a crankshaft manufacturing line and fed as input to the neural network. This input is then clustered using a competitive neural network trained in unsupervised mode. The resulting clusters are analyzed and discussed. The network is then tested with new data to evaluate the quality of the clusters previously generated and to demonstrate the applicability of this technique for detecting process variations.