• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2025, Vol. 61 ›› Issue (10): 250-262.doi: 10.3901/JME.2025.10.250

• 仪器科学与技术 • 上一篇    

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基于VMD-共振频带-能量熵的倒装焊芯片缺陷检测方法

李可1, 于成昊1, 明雪飞2, 顾杰斐1, 宿磊1, MICHAEL Pecht3   

  1. 1. 江南大学机械工程学院 无锡 214122;
    2. 中国电子科技集团有限公司第五十八研究所 无锡 214000;
    3. 马里兰大学CALCE中心 马里兰 20742 美国
  • 收稿日期:2024-05-24 修回日期:2024-11-05 发布日期:2025-07-12
  • 作者简介:李可,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为微电子可靠性、信号处理和故障诊断。E-mail:like_jiangnan@163.com;宿磊(通信作者),男,1986年出生,博士,副教授,硕士研究生导师。主要研究方向为微电子封装测试、无损检测、信号处理和故障诊断。E-mail:lei_su2015@jiangnan.edu.cn
  • 基金资助:
    国家自然科学基金(52375099,U23B2044)和国家重点研发计划(2023YFB4404203)资助项目。

Defect Inspection Method of Flip Chip Based on VMD-resonance Band-energy Entropy

LI Ke1, YU Chenghao1, MING Xuefei2, GU Jiefei1, SU Lei1, MICHAEL Pecht3   

  1. 1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122;
    2. Research Institute 58, China Electronics Technology Group Corporation, Wuxi 214000;
    3. Center for Advanced Life Cycle Engineering, University of Maryland, Maryland 20742 USA
  • Received:2024-05-24 Revised:2024-11-05 Published:2025-07-12

摘要: 针对单频超声激励获得的倒装焊芯片缺陷特征信息较少导致典型缺陷难以检测的问题,提出一种基于共振频带能量熵的倒装焊芯片缺陷检测方法。首先,通过倒装焊芯片理论模型求解芯片固有频率的解析值,分析芯片的结构特性。其次,提出一种改进变分模态分解(Variational mode decomposition,VMD)算法,利用Teager能量算子和多重极值分割融合算法对振动信号频谱进行划分从而确定模态数,根据频段边界和局部最大峰值点预估各个本征模函数(Intrinsic mode function,IMF)的惩罚因子和初始中心频率,并通过仿真信号分析,验证改进VMD算法提取信号共振频带的有效性。最后,利用改进VMD算法分析倒装焊芯片振动信号,并与经验模态分解等方法对比分析,结果表明改进VMD算法能够准确地获得共振频带及能量熵,并进一步验证了基于共振频带能量熵的方法对倒装焊芯片缺陷检测的有效性。

关键词: 改进变分模态分解, 共振频带, 能量熵, 倒装焊芯片, 缺陷检测

Abstract: The defect detection method for flip-chips based on the resonance band energy entropy is proposed to address the issue of limited defect feature information obtained from single-frequency ultrasonic excitation, which makes it challenging to detect typical defects. Firstly, the analytical values of the chip’s inherent frequencies are obtained by solving the theoretical model of flip-chip and analyzing the structural characteristics of the chip. Secondly, an improved variational mode decomposition(VMD) algorithm is proposed, which utilizes the Teager energy operator and multiple extreme value segmentation fusion algorithm to partition the vibration signal spectrum and determine the number of modes. The penalty factors and initial center frequencies of each intrinsic mode function(IMF) are estimated based on the frequency band boundaries and local maximum peak points. The effectiveness of the improved VMD algorithm in extracting the resonance band of the signal is validated through simulation signal analysis. Finally, the vibration signals of the flip-chip are analyzed using the improved VMD algorithm and compared with empirical mode decomposition and other methods. The results demonstrate that the improved VMD algorithm can accurately obtain the resonance band and energy entropy, further verifying the effectiveness of the resonance band energy entropy-based method for defect detection in flip-chip.

Key words: improved variational mode decomposition, resonance frequency band, energy entropy, flip chip, defect detection

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