Extended Kalman Filter models and resistance spectroscopy for prognostication and health monitoring of leadfree electronics under vibration

A technique has been developed for monitoring the structural damage accrued in BGA interconnects during operation in vibration environments. The technique uses resistance spectroscopy based state space vectors, rate of change of the state variable, and acceleration of the state variable in conjunction with Extended Kalman Filter and is intended for the pre-failure time-history of the component. Condition monitoring using the presented technique can provide knowledge of impending failure in high reliability applications where the risks associated with loss-of-functionality are too high to bear. The methodology has been demonstrated on SAC305 leadfree area-array electronic assemblies subjected to vibration. Future state of the system has been estimated based on a second order Extended Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying interconnect damage using plastic strain. Performance of the prognostication health management algorithm during the vibration test has been quantified using performance evaluation metrics. Model predictions have been correlated with experimental data. The presented approach is applicable to functional systems where corner interconnects in area-array packages may be often redundant. Prognostic metrics including α-λ metric, beta, and relative accuracy have been used to assess the performance of the damage proxies. The presented approach enables the estimation of residual life based on level of risk averseness.