Sachin Kumar, Nikhil M. Vichare, Eli Dolev, and Michael Pecht
Prognostic and Health Management Lab, Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, United States
A methodology for detecting the gradual health degradation of electronic products is presented by defining a health indicator to represent a product's health state in a time interval. A health indicator is defined as the weighted sum of a histogram bin's fractional contribution in a time interval that is based on the data collection rate, the likelihood of change in a product's performance, and a user's readiness to accept risk. The unified distance measure, Mahalanobis distance (MD), is used to create histograms where optimal bin-width is calculated using a kernel estimator. Summarization of a product's performance in a time interval for health and degradation estimation together with the behaviour of the MD values can reduce false alarms regarding the presence of fault and increase the capability of detecting intermittent and ''no fault found'' events. A case study performed on computers is presented. A healthy baseline for the computers was created and a threshold for both fault detection and degradation identification was defined. After fault injection into one of the computers, the increase in the MD values detected the initial change in performance parameters. After a short time period, the health indicator detected the degradation whereas the MD values returned to below threshold as the degradation in this case study was an after-effect of the damaging event.
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