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。
The vibration signal parameter images for rotating machinery were studied as the ob- ject. 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 experimen- tal bench. These 3D images of different faults were pretreated and transformed to 2D gray--scale ima- ges. 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 environ- mental noise is comparatively complicated for rotatinu machinery.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2013年第23期3176-3180,共5页
China Mechanical Engineering
基金
国家自然科学基金资助项目(50875056)
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
rotating machinery
parameter image
multi-- scale
multi-- structure element
math-ematical morphology~ edge detection