A robust condition monitoring methodology for grinding wheel wear identification using Hilbert Huang transform

Grinding is a finishing operation performed to obtain the desired finish on the component. Wheel wear is one of the primary constraints in achieving the desired productivity in grinding. A new methodology is proposed for accurate and timely identification of wheel wear in cylindrical grinding using Hilbert Huang transform and support vector machine. During the grinding of EN31 carbon steel, the condition of the wheel and its wear was monitored with an accelerometer and power cell. Both vibration and power signals captured were used to identify the condition of the wheel and its wear. An exhaustive feature set is generated in the frequency and the time-frequency domain. Hilbert Huang transform, an adaptive time-frequency analysis technique, was used to extract the features of tool wear in the time-frequency domain. The first three IMF constituents were further chosen for feature extraction of statistical parameters based on their mean energy. Random forests algorithm was used to identify the relevant features. The methodology was validated with several grinding experiments and, is found to give an accuracy of 100% with both low and high cutting depths. The results indicated the robust and reliable wheel wear detection in cylindrical grinding with the use of relatively cheap sensors like accelerometers. The proposed method can be widely used in many applications in the industry where grinding is predominantly used as the finishing operation.     

α-β坐标系下瞬时无功功率的笼型异步电机转子故障诊断

根据α-β两相静止坐标下的瞬时无功功率理论,推导出笼型异步电动机定子瞬时无功功率在正常状态、转子断条故障、转子偏心故障、以及两者的复合故障状态下的表达式,并提取出不易被基频淹没、易于辨识的故障特征频率,以此达到诊断电机的目的。同时,转子复合状态下的故障特征频率得到有效分离。最后,利用双Hilbert变换,滤除瞬时无功功率频谱中的直流成分,更好地突出故障特征分量。实验采集定子三相电压电流,经过坐标变换,运用两相静止坐标系瞬时无功功率理论得到瞬时无功功率,进行频谱分析,验证了此法对电机转子各种故障诊断的准确性。     

Cognitive information delivery in geo‐location database based cognitive radio networks

For the problem of spectrum scarcity and wastage, cognitive radio (CR) technology provides a solution to utilizing the vacant spectrum more efficiently. As one of the most promising techniques to obtain the cognitive information in TV white spaces, geo‐location database approach has attracted a lot of recent attentions, with its goal of enhancing the efficiency of spectrum usage and avoiding the interference to TV receivers. However, existing works mainly focus on the construction and applications of geo‐location database, and seldom consider how to deliver the cognitive information from the database to TV band devices. In this paper, we investigate the tradeoff between increasing the accuracy of cognitive information delivery and reducing the overhead. We design two mesh fusion algorithms to reduce the redundancy of cognitive information and improve the efficiency of cognitive information delivery. Finally, we verify our analysis and evaluate the efficiency of the proposed mesh fusion algorithms through numerical studies. Copyright © 2016 John Wiley & Sons, Ltd.     

基于切削声信号与优化SVM的刀具磨损状态监测

提出了一种利用切削声实现刀具磨损状态多特征监测的方法。根据经验模态分解与Hilbert变换理论,提取切削声信号的内禀模态能量与不同频段的Hilbert谱能量作为监测信号的备选特征。采用支持向量机作为分类器,针对备选特征的有效筛选问题,利用多种群遗传算法对分类器的输入特征进行了优化,剔除备选特征中的干扰特征,利用多种群遗传算法对分类器的模型参数进行了优化。利用优化后的分类器对测试样本进行分类,并与优化前的分类结果进行了对比。结果表明,优化后分类器的分类性能得到了明显提升,该方法可以对刀具磨损状态进行有效识别。     

基于形态分量分析的希尔伯特变换在滚动轴承故障诊断中的应用

形态分量分析是一种基于信号形态多样性和信号稀疏表示的信号处理方法。滚动轴承故障信号具有振幅呈指数衰减与环境噪声大的特点。通过构建一个对冲击信号敏感的字典,利用形态分量分析对轴承故障信号的时域形态特征进行最优化稀疏表示,得到滚动轴承冲击信号。并对形态分量分析后的冲击信号进行希尔伯特变换,得到明确的故障特征频率及其倍频。仿真分析与实验结果表明：该方法具有良好的降噪功能,能够准确地提取滚动轴承故障信号中的早期冲击特征。     

基于排列熵的电磁声发射信号到达时间识别

排列熵算法简单高效,能够反映出信号的微小变化,是一种有效的信号突变检测工具。通过引入信号包络排列熵分析方法,对声发射信号到达时间识别问题进行求解。排列熵对信号幅值的大小不敏感,但对信号幅值的变化敏感,通过记录信号包络排列熵的变化,根据包络排列熵第一个极小值时刻来识别信号到达时间。根据裂纹电磁声发射实测信号识别结果可知,包络排列熵方法对声发射信号到达时间具有较高的识别精度。     

医院环境空间心理需求与管理创新

从医院环境空间、心理需求和管理创新三个方面出发,分析了空间环境对病人生理、心理和行为的影响,指出医院公共空间的设置应契合使用者对医院总体空间的使用需求,从而提高医疗建筑的质量,实现以人为本的理念。     

变量核参数型Marcinkiewicz积分在Companato空间上的相关不等式

利用核函数Ω的性质,证明了带可变核的参数型Marcinkiewicz积分算子μρΩ,0与μρΩ∞,＂在Companato空间εα,p上的一个不等式关系.     

二维一阶非线性方程的反周期解

在H ilbert空间中考虑二维非线性方程,探讨在何种条件下其具有反周期解.证明在一定条件下,方程具有反周期解.     

Isolated nonnegative solutions of infinite-dimensional algebraic Riccati equations

For an infinite-dimensional continuous (or discrete)-time linear system, based on the study of the representation of nonnegative solutions of the algebraic Riccati equation (ARE), we get some sufficient and necessary conditions for a nonnegative solution of (ARE) to be isolated in the set of all nonnegative solution of (ARE) with respect to the norm topology, the strong operator topology and weak operator topology, respectively.