典型快速谱峭图算法的研究及应用
发布时间：2019-01-17 10:41
【摘要】：针对工程实际中状态监测下的具体机械部件在特定运行环境中发生故障的原因及类型具有典型性,在分析快速谱峭图算法的基础上,提出了典型快速谱峭图算法。该算法借鉴快速谱峭图算法分层和选取中心频率的思想,以典型故障的三倍特征频率为带宽,快速定位谱峭度最大的频率区间,并将该算法应用于共振解调技术滤波器参数的确定。为了验证该算法的有效性,在滚动轴承故障诊断试验台上进行了振动测试,采用基于典型快速谱峭图算法的共振解调技术进行故障诊断和类型识别。结果表明,基于典型快速谱峭图算法的共振解调技术能够较好的诊断典型故障,具有一定的工程应用价值。
[Abstract]:In view of the typical causes and types of failure of mechanical components in a specific operating environment under state monitoring in engineering practice, a typical fast spectral kurtosis algorithm is proposed on the basis of analyzing the fast spectral kurtosis algorithm. The algorithm uses the idea of fast spectral kurtosis algorithm to layer and select center frequency, takes the characteristic frequency of three times of typical fault as the bandwidth, and quickly locates the frequency range with the largest spectral kurtosis. The algorithm is applied to the determination of filter parameters of resonance demodulation technique. In order to verify the validity of the algorithm, vibration test was carried out on the rolling bearing fault diagnosis test-bed, and the resonance demodulation technique based on the typical fast spectral kurtosis algorithm was used for fault diagnosis and type recognition. The results show that the resonance demodulation technique based on the typical fast spectral kurtosis algorithm can diagnose the typical faults well and has certain engineering application value.
【作者单位】： 石家庄铁道大学信息科学与技术学院;石家庄铁道大学机械工程学院;
【基金】：国家自然基金项目(11372197;11227201) 河北省自然基金项目(E2014210078)
【分类号】：TH17
本文编号：2409977
[Abstract]:In view of the typical causes and types of failure of mechanical components in a specific operating environment under state monitoring in engineering practice, a typical fast spectral kurtosis algorithm is proposed on the basis of analyzing the fast spectral kurtosis algorithm. The algorithm uses the idea of fast spectral kurtosis algorithm to layer and select center frequency, takes the characteristic frequency of three times of typical fault as the bandwidth, and quickly locates the frequency range with the largest spectral kurtosis. The algorithm is applied to the determination of filter parameters of resonance demodulation technique. In order to verify the validity of the algorithm, vibration test was carried out on the rolling bearing fault diagnosis test-bed, and the resonance demodulation technique based on the typical fast spectral kurtosis algorithm was used for fault diagnosis and type recognition. The results show that the resonance demodulation technique based on the typical fast spectral kurtosis algorithm can diagnose the typical faults well and has certain engineering application value.
【作者单位】： 石家庄铁道大学信息科学与技术学院;石家庄铁道大学机械工程学院;
【基金】：国家自然基金项目(11372197;11227201) 河北省自然基金项目(E2014210078)
【分类号】：TH17
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