柔性薄壁轴承的内外圈是椭圆,这使得它和普通滚动轴承的振动特性完全不同。这种轴承旋转过程中椭圆长短轴会对轴承造成周期性冲击,这种正常的周期性冲击和轴承元件损伤引起的故障周期性冲击混合在一起,掩盖了故障周期性冲击。分析了这...柔性薄壁轴承的内外圈是椭圆,这使得它和普通滚动轴承的振动特性完全不同。这种轴承旋转过程中椭圆长短轴会对轴承造成周期性冲击,这种正常的周期性冲击和轴承元件损伤引起的故障周期性冲击混合在一起,掩盖了故障周期性冲击。分析了这种正常周期性冲击的频率分布特点,根据奇异值和频率的内在关系,提出利用奇异值分解(Singular Value Decomposition,SVD)来消除这种正常周期性冲击,选择正常周期性冲击的频率成分对应的奇异值进行SVD重构,可以准确地分离出这种正常冲击,从而消除其对故障周期性冲击的干扰。进而采用连续Morlet小波变换对消除了正常周期性冲击的柔性薄壁轴承振动信号进行故障冲击特征提取,选择峭度最大的尺度为故障特征尺度,清晰地提取到了柔性薄壁轴承的故障冲击特征,故障特征提取效果优于没有消除正常冲击时的故障特征提取效果。展开更多
针对工业环境中随机冲击干扰下滚动轴承微弱故障特征提取难题,提出一种基于自适应短时维纳滤波(Adaptive Short Time Wiener Filtering,ASTWF)和改进正交匹配追踪(Orthogonal Matching Pursuit,OMP)的滚动轴承故障特征提取方法。该方法...针对工业环境中随机冲击干扰下滚动轴承微弱故障特征提取难题,提出一种基于自适应短时维纳滤波(Adaptive Short Time Wiener Filtering,ASTWF)和改进正交匹配追踪(Orthogonal Matching Pursuit,OMP)的滚动轴承故障特征提取方法。该方法首先采用包络峭度和随余比(Random Shocks and Margin Ratio,RMR)作为联合判据,界定窗长界限并自适应确定STWF最优窗长参数,进而将随机冲击干扰从测试信号中分离出来;然后,利用立方包络自相关谱估计信号中周期频率,构造周期原子库,降低匹配原子冗余度;最后,利用相似性理论优化匹配追踪迭代终止条件,并结合周期原子库,实现弱故障冲击特征快速、准确提取。根据仿真信号和通过变速箱下线检测所得工程数据,可验证所提出方法可有效识别随机冲击干扰下的滚动轴承微弱故障特征。对比最小熵形态反卷积(Minimum Entropy Morphological Deconvolution,MEMD)方法对于随机冲击干扰下滚动轴承微弱故障特征提取效果,发现所提出方法具有更好的故障特征提取能力;与经典OMP方法相比,所提出改进OMP方法信号重构速度提升66%。展开更多
Tungsten current price was transformed yearly to its constant price since 1900, which is roughly decomposed into four components as trend, cycle, impact and random. The core prices, consisting of the trend and the cyc...Tungsten current price was transformed yearly to its constant price since 1900, which is roughly decomposed into four components as trend, cycle, impact and random. The core prices, consisting of the trend and the cycle, present regularities that a long-run cycle is embedded within two major cycles, and major cycle is composed of low-price period and high-price period, along with the rapid rise into a tower, and along with deep down into next trough; three sharply upward shocks occur by the events in a tower. Fluctuations in prices trend to slow cycles and expand the bands. It can be expected that tungsten price will highly stand over 17 a, and is is a advice that reducing production and restricting export maybe maintain a high price level.展开更多
文摘柔性薄壁轴承的内外圈是椭圆,这使得它和普通滚动轴承的振动特性完全不同。这种轴承旋转过程中椭圆长短轴会对轴承造成周期性冲击,这种正常的周期性冲击和轴承元件损伤引起的故障周期性冲击混合在一起,掩盖了故障周期性冲击。分析了这种正常周期性冲击的频率分布特点,根据奇异值和频率的内在关系,提出利用奇异值分解(Singular Value Decomposition,SVD)来消除这种正常周期性冲击,选择正常周期性冲击的频率成分对应的奇异值进行SVD重构,可以准确地分离出这种正常冲击,从而消除其对故障周期性冲击的干扰。进而采用连续Morlet小波变换对消除了正常周期性冲击的柔性薄壁轴承振动信号进行故障冲击特征提取,选择峭度最大的尺度为故障特征尺度,清晰地提取到了柔性薄壁轴承的故障冲击特征,故障特征提取效果优于没有消除正常冲击时的故障特征提取效果。
文摘针对工业环境中随机冲击干扰下滚动轴承微弱故障特征提取难题,提出一种基于自适应短时维纳滤波(Adaptive Short Time Wiener Filtering,ASTWF)和改进正交匹配追踪(Orthogonal Matching Pursuit,OMP)的滚动轴承故障特征提取方法。该方法首先采用包络峭度和随余比(Random Shocks and Margin Ratio,RMR)作为联合判据,界定窗长界限并自适应确定STWF最优窗长参数,进而将随机冲击干扰从测试信号中分离出来;然后,利用立方包络自相关谱估计信号中周期频率,构造周期原子库,降低匹配原子冗余度;最后,利用相似性理论优化匹配追踪迭代终止条件,并结合周期原子库,实现弱故障冲击特征快速、准确提取。根据仿真信号和通过变速箱下线检测所得工程数据,可验证所提出方法可有效识别随机冲击干扰下的滚动轴承微弱故障特征。对比最小熵形态反卷积(Minimum Entropy Morphological Deconvolution,MEMD)方法对于随机冲击干扰下滚动轴承微弱故障特征提取效果,发现所提出方法具有更好的故障特征提取能力;与经典OMP方法相比,所提出改进OMP方法信号重构速度提升66%。
基金Project(2013ZK2001)supported by the Major Soft Science Program of Hunan Provice,ChinaProjects(1382ZD024,13BGL105)supported by the National Social Science Foundation of China
文摘Tungsten current price was transformed yearly to its constant price since 1900, which is roughly decomposed into four components as trend, cycle, impact and random. The core prices, consisting of the trend and the cycle, present regularities that a long-run cycle is embedded within two major cycles, and major cycle is composed of low-price period and high-price period, along with the rapid rise into a tower, and along with deep down into next trough; three sharply upward shocks occur by the events in a tower. Fluctuations in prices trend to slow cycles and expand the bands. It can be expected that tungsten price will highly stand over 17 a, and is is a advice that reducing production and restricting export maybe maintain a high price level.