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邸新杰, 李午申, 白世武, 刘方明, 薛振奎. 金属磁记忆检测信号的二维谱熵特征[J]. 焊接学报, 2006, (11): 69-72.
引用本文: 邸新杰, 李午申, 白世武, 刘方明, 薛振奎. 金属磁记忆检测信号的二维谱熵特征[J]. 焊接学报, 2006, (11): 69-72.
DI Xin-jie, LI Wu-shen, BAI Shi-wu, LIU Fang-ming, XUE Zhen-kui. Two-dimension spectrum entropy feature for metal magnetic memory signal[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2006, (11): 69-72.
Citation: DI Xin-jie, LI Wu-shen, BAI Shi-wu, LIU Fang-ming, XUE Zhen-kui. Two-dimension spectrum entropy feature for metal magnetic memory signal[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2006, (11): 69-72.

金属磁记忆检测信号的二维谱熵特征

Two-dimension spectrum entropy feature for metal magnetic memory signal

  • 摘要: 金属磁记忆检测技术是能够对焊接裂纹进行早期诊断的最具有潜力的无损检测方法之一。以X70管线钢为主要研究对象,研究了其拉伸条件下金属磁记忆检测信号的二维特征谱熵分布规律,通过支持向量机模型,可以实现幅值谱熵和重心频率确定点的位置的分类,结合检测实例,得到了对焊缝中应力集中状态的诊断方法。结果表明,通过磁记忆信号二维特征谱熵的分布可以诊断出材料内部的应力集中状态,从而为利用金属磁记忆检测技术对裂纹萌生状态的诊断提供了依据。

     

    Abstract: Metal magnetic memory(MMM)is one of the most potential non-destructive testing methods which can diagnose welding crack in early stage.The distribution regularities of metal magnetic memory two-dimension spectrum entropy were investigated in tension test condition with the X70 pipeline steel. Using the feature of amplitude spectrum entropy and braycentre frequency, the support vector machine method can distinguish the different state of stress concentration.With the detection instance, the diagnostic method of stress concentration state in weld was gained.Research shows that the stress concentration state within the ferromagnetic material can be identified by the two-dimension spectrum entropy distribution of MMM signal.It is a base for utilizing MMM to detect the micro-cracks.

     

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