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Assessment of Damage Progression in Automotive Electronics Assemblies Subjected to Temperature and Vibration

[+] Author Affiliations
Pradeep Lall, Tony Thomas

Auburn University, Auburn, AL

Paper No. IPACK2018-8356, pp. V001T05A004; 12 pages
  • ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems
  • ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems
  • San Francisco, California, USA, August 27–30, 2018
  • Conference Sponsors: Electronic and Photonic Packaging Division
  • ISBN: 978-0-7918-5192-0
  • Copyright © 2018 by ASME


Electronics in automotive underhood environments is used for a number of safety critical functions. Reliable continued operation of electronic safety systems without catastrophic failure is important for safe operation of the vehicle. There is need for prognostication methods, which can be integrated, with on-board sensors for assessment of accrued damage and impending failure. In this paper, leadfree electronic assemblies consisting of daisy-chained parts have been subjected to high temperature vibration at 5g and 155°C. Spectrogram has been used to identify the emergence of new low frequency components with damage progression in electronic assemblies. Principal component analysis has been used to reduce the dimensionality of large data-sets and identify patterns without the loss of features that signify damage progression and impending failure. Variance of the principal components of the instantaneous frequency has been shown to exhibit an increasing trend during the initial damage progression, attaining a maximum value and decreasing prior to failure. The unique behavior of the instantaneous frequency over the period of vibration can be used as a health-monitoring feature for identifying the impending failures in automotive electronics. Further, damage progression has been studied using Empirical Mode Decomposition (EMD) technique in order to decompose the signals into Independent Mode Functions (IMF). The IMF’s were investigated based on their kurtosis values and a reconstructed strain signal was formulated with all IMF’s greater than a kurtosis value of three. PCA analysis on the reconstructed strain signal gave better patterns that can be used for prognostication of the life of the components.

Copyright © 2018 by ASME



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