• DocumentCode
    1948354
  • Title

    Time-frequency and auto-regressive techniques for prognostication of shock-impact reliability of implantable biological electronic systems

  • Author

    Lall, Pradeep ; Gupta, Prashant ; Kulkarni, Manish ; Panchagade, Dhananjay ; Suhling, Jeff ; Hofmeister, James

  • Author_Institution
    Dept. of Mech. Eng., Auburn Univ., Auburn, AL
  • fYear
    2008
  • fDate
    27-30 May 2008
  • Firstpage
    1196
  • Lastpage
    1207
  • Abstract
    A new approach based on auto-regressive and time- frequency analysis has been developed to monitor system- level damage in implantable biological electronic systems such as pacemakers and defibrillators. The approach focuses is on the pre-failure space and methodologies for quantification of failure in implantable biological electronics subjected to shock and vibration loads using the dynamic response. Presented methodologies are applicable at the system-level for identification of impending failures to trigger repair or replacement significantly prior to failure. Leading indicators of shock-damage have been developed to correlate with the damage initiation and progression in under variety of stresses in electronic systems. The approach is based on monitoring critical solder interconnects, and sensing the change in test-signal characteristics prior to failure, in addition to monitoring the transient strain characteristics optically using digital image correlation and strain gages. Previously, SPR based on wavelet packet energy decomposition and the Mahalanobis distance approach have been studied by the authors for quantification of shock damage in electronic assemblies [Lall 2006a.b]. In this paper, Auto-regressive (AR), wavelet packet energy decomposition, and time-frequency (TFA) techniques have been investigated for system identification, condition monitoring, and fault detection and diagnosis in implantable biological electronic systems. One of the main advantages of the AR technique is that it is primarily a signal based technique. Reduced reliance on system analysis helps avoid errors which otherwise may render the process of fault detection and diagnosis quite complex and dependent on the skills of the analyst. Results of the present study show that the AR and TFA based health monitoring techniques are feasible for fault detection and damage-assessment in electronic units. Explicit finite element models have been developed and various kinds of fail- ure modes have been simulated such as solder ball cracking, package falloff and solder ball failure.
  • Keywords
    defibrillators; impact (mechanical); pacemakers; prosthetics; regression analysis; reliability; Mahalanobis distance; autoregressive analysis; implantable biological electronic systems; shock damage; shock-damage; shock-impact reliability; time-frequency analysis; wavelet packet energy decomposition; Capacitive sensors; Condition monitoring; Electric shock; Fault detection; Fault diagnosis; Lead; Pacemakers; Stress; Time frequency analysis; Wavelet packets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Components and Technology Conference, 2008. ECTC 2008. 58th
  • Conference_Location
    Lake Buena Vista, FL
  • ISSN
    0569-5503
  • Print_ISBN
    978-1-4244-2230-2
  • Electronic_ISBN
    0569-5503
  • Type

    conf

  • DOI
    10.1109/ECTC.2008.4550127
  • Filename
    4550127