Kam-Chuen Yung

Lifetime Estimation of High-Power White LED Using Degradation-Data-Driven Method

High-power white light-emitting diodes (HPWLEDs) have attracted much attention in the lighting market. However, as one of the highly reliable electronic products which may be not likely to fail under the traditional life test or even accelerated life test, HPWLEDs lifetime is difficult to estimate by using traditional reliability assessment techniques. In this paper, the degradation-data-driven method (DDDM), which is based on the general degradation path model, was used to predict the reliability of HPWLED through analyzing the lumen maintenance data collected from the IES LM-80-08 lumen maintenance test standard. The final predicted results showed that much more reliability information (e.g., mean time to failure, confidence interval, reliability function, and so on) and more accurate prediction results could be obtained by DDDM including the approximation method, the analytical method, and the two-stage method compared to the IES TM-21-11 lumen lifetime estimation method. Among all these three methods, the two-stage method produced the highest prediction accuracy.

Predicting long-term lumen maintenance life of LED light sources using a particle filter-based prognostic approach

Destructive life test is time-consuming and expensive to estimate the LEDs life.TM-21 standard with least-squares regression has weakness in predicting LEDs life.A dynamic recursive method of PF is developed to model the lumen degradation data.An SMC method is proposed to predict RUL distribution with a confidence interval.PF has higher accuracy than TM-21 standard in the LEDs long-term life prediction. Lumen degradation is a common failure mode in LED light sources. Lumen maintenance life, defined as the time when the maintained percentages of the initial light output fall below a failure threshold, is a key characteristic for assessing the reliability of LED light sources. Owing to the long lifetime and high reliability of LED lights sources, it is challenging to estimate the lumen maintenance life for LED light sources using traditional life testing that records failure data. This paper describes a particle filter-based (PF-based) prognostic approach based on both Sequential Monte Carlo (SMC) and Bayesian techniques to predict the lumen maintenance life of LED light sources. The lumen maintenance degradation data collected from an accelerated degradation test was used to demonstrate the prediction algorithm and methodology of the proposed PF approach. Its feasibility and prediction accuracy were then validated and compared with the TM-21 standard method that was created by the Illuminating Engineering Society of North America (IESNA). Finally, a robustness study was also conducted to analyze the initialization of parameters impacting the prediction accuracy and the uncertainties of the proposed PF method. The results show that, compared to the TM-21 method, the PF approach achieves better prediction performance, with an error of less than 5% in predicting the long-term lumen maintenance life of LED light sources.

Prognostics of lumen maintenance for High power white light emitting diodes using a nonlinear filter-based approach

High power white light emitting diodes (HPWLEDs), with advantages in terms of luminous efficacy, energy saving, and reliability, have become a popular alternative to conventional luminaires as white light sources. Like other new electronic products, HPWLEDs must also undergo qualification testing before being released to the market. However, most traditional qualification tests, which require all devices under testing to fail, are time-consuming and expensive. Nowadays, as recommended by the Illuminating Engineering Society (IES, IES-TM-21-11), many LED manufacturers use a projecting approach based on short-term collected light output data to predict the future lumen maintenance (or lumen lifetime) of LEDs. However, this projecting approach, which depends on the least-square regression method, generates large prediction errors and uncertainties in real applications. To improve the prediction accuracy, we present in this paper a nonlinear filter-based prognostic approach (the recursive Unscented Kalman Filter) to predict the lumen maintenance of HPWLEDs based on the short-term observed data. The prognostic performance of the proposed approach and the IES-TM-21-11 projecting approach are compared and evaluated with both accuracy- and precision-based metrics.

A Review of Prognostic Techniques for High-Power White LEDs

High-power white light-emitting diodes (LEDs) have attracted much attention due to their versatility in a variety of applications and growing demand in markets such as general lighting, automotive lamps, communications devices, and medical devices. In particular, the need for high reliability and long lifetime poses new challenges for the research and development, production, and application of LED lighting. Accurate and effective prediction of the lifetime or reliability of LED lighting has emerged as one of the key issues in the solid-state lighting field. Prognostic is an engineering technology that predicts the future reliability or determines the remaining useful lifetime of a product by assessing the extent of deviation or degradation of a product from its expected normal operating conditions. Prognostics bring benefits to both LED developers and users, such as optimizing system design, shortening qualification test times, enabling condition-based maintenance for LED-based systems, and providing information for return-on-investment analysis. This paper provides an overview of the prognostic methods and models that have been applied to both LED devices and LED systems, especially for use in long-term operational conditions. These methods include statistical regression, static Bayesian network, Kalman filtering, particle filtering, artificial neural network, and physics-based methods. The general concepts and main features of these methods, the advantages and disadvantages of applying these methods, as well as LED application case studies, are discussed. The fundamental issues of prognostics and photoelectrothermal theory for LED systems are also discussed for clear understanding of the reliability and lifetime concepts for LEDs. Finally, the challenges and opportunities in developing effective prognostic techniques are addressed.

Optimal Design of Life Testing for High-Brightness White LEDs Using the Six Sigma DMAIC Approach

Life testing is an essential reliability assessment procedure to qualify a new product or technology before being released to the market. High-brightness white light-emitting diodes (HBWLEDs) with high efficiency, environmental benefits, and high reliability have attracted increasing interest in the field of lighting systems. However, owing to the long lifetime of LEDs, traditional life testing methods for LEDs, which record only failure time, are time consuming and expensive. Therefore, designing an optimal life testing process for HBWLEDs is desirable for accelerating LED technology innovation and development. This paper applies the Six Sigma define-measure-analyze-improve-control (DMAIC) approach to analyze the restrictions in the traditional life testing for HBWLEDs and optimize the life testing procedure. The goal is to shorten the testing time, reduce the testing operation cost, and maintain accurate reliability estimation. In this work, a general reliability estimation method with degradation data is developed by integrating a recursive unscented Kalman filter approach to estimate HBWLED reliability. The results show that, with the help of a recursive UKF, the accuracy of reliability estimation can be improved compared with the ordinary nonlinear least squares approach. Furthermore, the operation time and cost of LED life testing can be reduced by 57.75% and 71.51%, respectively, compared with traditional life testing.

Degradation mechanism beyond device self-heating in high power light-emitting diodes

A unique degradation property of high power InGaN/GaN multiple quantum well (MQW) white light-emitting diodes (LEDs) was identified. The LEDs were stressed under different forward-currents. The various ageing characteristics were analyzed for both the electrical response and electro-luminescence (EL) spectra. The Raman spectroscopy allowed noninvasive probing of LED junction temperature profiles which correlated well with the EL characteristics, showing a junction temperature drop during degradation at certain current levels. In addition to the common observations: (1) a broadening of the light intensity-current (L-I) characteristic in the nonlinear regime, and (2) a shift of the current-voltage (I-V) dependence to higher current levels, the EL spectra showed different temperature responses of the two blue emission peaks, 440 and 463 nm. The former was temperature sensitive and thus related to shallow defect levels, while the latter was thermally stable and deeper defect states were involved in the degrad...

Anomaly detection for chromaticity shift of high power white LED with mahalanobis distance approach

High power white LED (HPWLED) with the benefits of high efficiency, small size, lower power consumption and high reliability has been commercially used as a substitute of the traditional white light sources in the application of general lighting systems, monitor backlighting and so on. Nowadays, in the LEDs reliability field, many previous researches paid attentions only on the lumen depreciation failure in LED products, ignoring another common failure mode called chromaticity shift. In this paper, we used a data-driven method based on a multivariate distance measure, Mahalanobis distance (MD), to detect the chromaticity shift anomaly of HPWLED after aging test. The result shows that by dealing MD distributions with Weibull statistical model, a chromaticity anomaly alarm indicator can be established to detect anomaly of chromaticity shift before HPWLED failed.

Near-threshold ultraviolet-laser ablation of Kapton film investigated by x-ray photoelectron spectroscopy

Near-threshold ultraviolet-laser (355 nm) ablation of 125-μm thick Kapton films was investigated in detail using x-ray photoelectron spectroscopy. Different from the irradiation at higher fluences, the contents of the oxygen, amide group, and C-O group on the ablated surface increased with an increase in the pulse number, whereas the carbon contents decreased, although the contents of the nitrogen and the carbonyl group (C=O) decreased slightly. This implied that there was no carbon-rich residue on the ablated surface. Near the ablation threshold, only photolysis of the C-N bond in the imide rings and the diaryl ether group (C-O) took place due to a low surface temperature rise, and the amide structure and many unstable free radical groups were created. Sequentially, the oxidation reaction occurred to stabilize the free radical groups. The decomposition and oxidation mechanism could explain the intriguing changes of the chemical composition and characteristics of the ablated surface. In addition, the content of the C-O group depended on the opposite factors: the thermally induced decomposition of the ether groups and the pyrolysis of the C a r y l -C bond. Upon further irradiation, the cumulative heating may induce the breakage of the C a r y l -C bond and enhance the oxidation reaction, resulting in an increase of the content of the C-O group.

Envelope probability and EFAST-based sensitivity analysis method for electronic prognostic uncertainty quantification

Abstract The primary phase of electronic prognostic uncertainty quantification included the identification and quantification of uncertainty sources through utilizing sensitivity analysis method. An improved EFAST-based sensitivity analysis method that considered the possibility of parameter fluctuation was used to identify the key factors (KFS) of uncertainty sources. Also, an envelope probability method was adopted to further quantify the key factors of parameter distribution. Finally, a board-level electronic product was chosen as the study case of this paper. Comparing the result of uncertainty quantification, sensitivity analysis was used to drive the result of the single-dimensional method. It was obvious that the sensitivity analysis method used in this paper has optimized the input parameters of the model and improved the accuracy of electronic prognostic uncertainty quantification.

Time-variant reliability analysis of ship grillage structure

Material characteristics, environmental conditions and loading characteristics under the time domain features shall be taken into consideration so as to effectively evaluate the reliability of ship grillage structure. Moreover, the method of time-variant reliability serves as an effective approach to solve the problem. In the paper, based on the loading environmental features of ships during the enlistment, research has been conducted on the changing of material geometrical and mechanical characteristics with time under the corrosive action. Furthermore, on the basis of time-variant theory, the timevariant model of section modulus as well as bending strength concerning the ship grillage structure has been established, thus generating a time-variant reliability analysis method integrated with out-crossing rate and First Order Second Moment(FOSM) method. Besides, the paper analyzes the time consecutiveness of ship grillage structure reliability based on the time-variant reliability cases of certain ship grillage structure under the corrosion environment while the failure probability of the ship during the enlistment has been accurately predicted.