中国机械工程 ›› 2013, Vol. 24 ›› Issue (23): 3176-3180.

• 智能制造 • 上一篇    下一篇

旋转机械参数图形多尺度多结构元边缘检测

张颖1;刘占生2;苏宪章3   

  1. 1.东北石油大学,大庆,163318
    2.哈尔滨工业大学,哈尔滨,150001
    3.中海油安全技术服务有限公司,天津,300456
  • 出版日期:2013-12-10 发布日期:2013-12-06
  • 基金资助:
    国家自然科学基金资助项目(50875056)

Multi-scale and Multi-structure Element Edge Detection of Parameter Images for Rotating Machinery

Zhang Ying1;Liu Zhansheng2;Su Xianzhang3   

  1. 1.Northeast Petroleum University,Daqing,Heilongjiang,163318
    2.Harbin Institute of Technology,Harbin,150001
    3.CNOOC Security Technology Services Co,. Ltd.,Tianjin,300456
  • Online:2013-12-10 Published:2013-12-06
  • Supported by:
    National Natural Science Foundation of China(No. 50875056)

摘要:

以旋转机械振动信号参数图形为研究对象,在600 MW模化汽轮机转子试验台上完成了转子正常、转子不对中和轴承松动故障的实验研究,得到了相应的振动参数三维图形。对不同故障的振动参数三维图形进行了二维灰度转化及图形预处理;依据多尺度滤波增强处理方法滤除了参数图形的噪声,增强了有用信息;利用多结构元边缘检测算子对参数图形进行了边缘检测。结果表明:多尺度多结构元边缘检测方法抗噪能力强,能够在滤除旋转机械振动信号参数图形中噪声的同时,有效地提取图形的边缘特征,适用于环境噪声较为复杂的旋转机械状态监测。

关键词: 旋转机械, 参数图形, 多尺度, 多结构元, 数学形态学, 边缘检测

Abstract:

The vibration signal parameter images for rotating machinery were studied as the object. The 3D vibration parameter images were obtained from rotor's normal state, misalignment and bearing pedestal looseness which were examined on the modeling of 600MW turbine rotor experimental bench. These 3D images of different faults were pretreated and transformed to 2D gray-scale images. According to the multi-scale filtering enhancement processing method, the noise was filtered out and the available information was enhanced of the parameter images. The edges of the parameter images were detected using the multi-structure edge detection operator. The results show that the multi-scale and multi-structure element edge detection method has strong anti-noise ability, this method can filter out the noises and obtain the edge features of vibration signal parameter images for rotating machinery effectively. This method is suitable for the condition monitoring whose environmental noise is comparatively complicated for rotating machinery.

Key words: rotating machinery, parameter image, multi-scale, multi-structure element, mathematical morphology, edge detection

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