Assessment of lumen degradation and remaining life of LEDs using particle filter
Lall, P., Zhang, H., & Davis, L. (2013). Assessment of lumen degradation and remaining life of LEDs using particle filter. In ASME 2013 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems, 16-18 July 2013, Burlingame, CA, , p. V001T04A024. .
The development of light-emitting diode (LED) technology has resulted in widespread solid state lighting use in consumer and industrial applications. Previous researchers have shown that LEDs from the same manufacturer and operating under same use-condition may have significantly different degradation behavior. Applications of LEDs to safety critical and harsh environment applications necessitate the characterization of failure mechanisms and modes. This paper focuses on a prognostic health management (PHM) method based on the measurement of forward voltage and forward current of bare LED under harsh environment. In this paper experiments have been done on single LEDs subjected to combined temperature-humidity environment of 85°C, 85% relative humidity. Pulse width modulation (PWM) control method has been employed to drive the bare LED in order to reduce the heat effect caused by forward current and high frequency (300Hz). A data acquisition system has been used to measure the peak forward voltage and forward current. Test to failure (luminous flux drops to 70 percent) data has been measured to study the effects of high temperature and humid environment loadings on the bare LEDs. A solid state cooling method with a peltier cooler has been used to control the temperature of the LED in the integrating sphere when taking the measurement of luminous flux. The shift of forward voltage forward current curve and lumen degradation has been recorded to help build the failure model and predict the remaining useful life. Particle filter has been employed to assess the remaining useful life (RUL) of the bare LED. Model predictions of RUL have been correlated with experimental data. Results show that prediction of remaining useful life of LEDs, made by the particle filter model works with acceptable error-bounds. The presented method can be employed to predict the failure of LED caused by thermal and humid stresses.