摘要
针对实测水泵振动信号夹杂噪声等现象,利用多尺度数学形态谱及形态谱熵理论,对不同转速下的水泵振动实测信号进行分析,提取相应的特征形状和特征量,进行振动故障识别,并验证了该方法的可行性与准确性。研究表明,随着转速的逐步增加,存在着不对中和不平衡故障的水泵机组,其振动特性可以划分为正常运行、周期性碰摩运行及混沌运行3类;当水泵振动类型相同时,随着转速的变化,相应的数学形态谱及形态谱熵分析结果几乎不变;采用数学形态谱及形态谱熵理论能够对夹杂大量噪声的故障测试信号进行分析处理,且故障信号识别成功率较高,其中形态谱识别成功率高于形态谱熵,能较好地达到故障识别的目的,也充分证明了该方法的抗干扰性。
In view of observed pumps vibration signals with noises, the multi - scale mathematical morphology spectrum and spectrum entropy are used to analyze the signals with different revolving speeds. The features of signals are extracted to recognize the vibration types, and then the feasibility and accuracy of the method are proved. The results show that with the gradually - increased speed, vibration features of the pump units with misalignment and coupling unbalance fault can be divided into three types, namely normal operation, periodic rubbing and chaotic operation. When the vibration type is same, the analysis results based on morphological spectrum and spectrum entropy are almost the same for any revolving speeds change. The observed signals with plenty of noise can be analyzed and handled effectively by the two methods, however the recognition success rate of morphological spectrum is higher, which contributes to vibration recognition.
出处
《人民长江》
北大核心
2014年第14期93-96,共4页
Yangtze River
基金
江西省科技厅2013年度科技项目(20132BDH80022)
关键词
水泵振动识别
故障诊断
数学形态谱
形态谱熵
pump vibration recognition
fault diagnosis
mathematical morphology spectrum
morphology spectrum entropy
