TY - GEN
T1 - Miniature MEMS-based data recorder for prognostics and health management (PHM)
AU - Engelman, Matt
AU - Judkins, Justin
AU - Vohnout, Sonia
AU - Enikov, Eniko
PY - 2010
Y1 - 2010
N2 - Novel prognostic sensors and reasoner algorithms are the core technology for detecting defects caused by accumulation of fatigue damage in electrical and mechanical systems over time. However, serious technical challenges to implementing a general health management strategy for helicopters and military aircraft still exist. For example, severe heat and vibration make it difficult to distinguish fault signatures from environmental noise. Moreover, bearing loads are very dynamic, making it difficult to distinguish subtle wear-out signatures from normal acoustic patterns. Detection can be improved by increasing the number of sensor locations, but this option is unattractive from the standpoint of added cost, weight, and data overhead of such a system. Our approach is to integrate MEMS sensors with a standard commercial microcontroller and measurement electronics. In this way, prognostic sensors can be positioned closer to the stressed components and provide higher fidelity data with lower cost. We present an innovative design for a prognostics and health management (PHM) data recorder that will facilitate sense-and-response logistics, and provide a small and inexpensive package. This low-cost, low-power, and lightweight solution is based largely on COTS components; it is implemented using a standard low-power lightweight microcontroller core and COTS MEMS sensors to record and process local temperature and vibration data, and status reporting is implemented using a short range wireless transceiver.
AB - Novel prognostic sensors and reasoner algorithms are the core technology for detecting defects caused by accumulation of fatigue damage in electrical and mechanical systems over time. However, serious technical challenges to implementing a general health management strategy for helicopters and military aircraft still exist. For example, severe heat and vibration make it difficult to distinguish fault signatures from environmental noise. Moreover, bearing loads are very dynamic, making it difficult to distinguish subtle wear-out signatures from normal acoustic patterns. Detection can be improved by increasing the number of sensor locations, but this option is unattractive from the standpoint of added cost, weight, and data overhead of such a system. Our approach is to integrate MEMS sensors with a standard commercial microcontroller and measurement electronics. In this way, prognostic sensors can be positioned closer to the stressed components and provide higher fidelity data with lower cost. We present an innovative design for a prognostics and health management (PHM) data recorder that will facilitate sense-and-response logistics, and provide a small and inexpensive package. This low-cost, low-power, and lightweight solution is based largely on COTS components; it is implemented using a standard low-power lightweight microcontroller core and COTS MEMS sensors to record and process local temperature and vibration data, and status reporting is implemented using a short range wireless transceiver.
KW - CBM
KW - CMOS
KW - Condition-based maintenance
KW - MEMS
KW - PHM
KW - Prognostics
KW - Sensors
UR - http://www.scopus.com/inward/record.url?scp=78649619586&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649619586&partnerID=8YFLogxK
U2 - 10.1109/AUTEST.2010.5613608
DO - 10.1109/AUTEST.2010.5613608
M3 - Conference contribution
AN - SCOPUS:78649619586
SN - 9781424479597
T3 - AUTOTESTCON (Proceedings)
SP - 343
EP - 350
BT - AUTOTESTCON 2010
T2 - 45 Years of Support Innovation - Moving Forward at the Speed of Light, AUTOTESTCON 2010
Y2 - 13 September 2010 through 16 September 2010
ER -