Life prediction for a vacuum fluorescent display based on two improved models using the three‐parameter Weibull right approximation method

Abstract

To obtain precise life information for vacuum fluorescent displays (VFDs), luminance degradation data for VFDs were collected from a group of normal life tests. Instead of exponential function, the three-parameter Weibull right approximation method (TPWRAM) was applied to describe the luminance degradation path of optoelectronic products, and two improved models were established. One of these models calculated the average life by fitting average luminance degradation data, and the other model obtained VFD life by combining the approximation method with luminance degradation test data from each individual sample. The results indicated that the test design under normal working stress was appropriate, and the selection of censored test data was simple. The two models improved by TPWRAM both revealed the luminance decaying law for VFD, and the pseudo failure time was accurately extrapolated. It was further confirmed by comparing relative error that using the second model gave a more accurate prediction of VFD life.The improved models in this study can provide technical references for researchers and manufacturers in aspects of life prediction methodology for its development. Due to the very long life of a VFD, the reduction in life test time and the improvement in test efficiency have become some of the important and urgent issues faced by business. As a result, accelerated life tests for VFD have been proposed. [3][4][5] Accelerated life tests of these products are conducted under abnormal operating conditions, so their rationality and their accuracy need to be verified by a normal life test. The large amounts of information contained in normal life tests not only reveal the characteristics of VFD luminance degradation, but can also give real-life information. What is more, these test results can be compared with those estimated from accelerated life tests to verify the rationality of the accelerated failure mechanism and the accuracy of life prediction models. As a complete normal stress test time is lengthy, it is necessary to establish a life prediction model that can calculate life using partially finished test data under normal working stress.Many researchers have predicted the life of optoelectronic products using a performance degradation method, and most of these investigators chose the exponential decay model. [6,7] Other researchers have used probability statistics methods to evaluate the life of the product. [8,9] Although these two methods have been widely used and studied, they have some deficiencies. The first method can only calculate the average life of the product, but can not obtain other life information, such as median life, reliability function and confidence interval. The reliability of the second method depends on the number of failure times, but test time and cost are a great challenge due to Abbreviations used: AIC, Akaike Information Criterion; DDDM, degradationdata-driven method; LSM, least square method; MLE, maximum likelihood estimation; TPWRAM, three-parameter Weibull right ap...

Extrapolated lifetime prediction of light-emitting diode lights based on equivalent average luminance and accelerated degradation tests

“…The average luminance degradation data ðt ij ; Lðt ij ÞÞ of test samples at each stress can be obtained from Eq. ( 1), so the three-parameter Weibull average luminance degradation function 25 can be expressed as E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 2 ; 1 1 7 ; 5 7 4…”

“…The average luminance degradation data (tij,Ltrue‾(tij)) of test samples at each stress can be obtained from Eq. (1), so the three-parameter Weibull average luminance degradation function 25 can be expressed as L¯(tij)=L¯i0exp(−(tij−t0iηi)mi),where L¯i0,mi,ηi,t0i are the initial average luminance of the product, shape parameter, scale parameter, and position parameter under the i′th stress, respectively.…”

Research on parameter estimation methods of fatigue life distribution model of automotive chassis parts

“…At present, the main methods of estimating parameters of Weibull distribution are statistical estimation method, 8,9 gray estimation method, 10,11 maximum likelihood method, 12–15 genetic algorithm, 16–20 and right approximation method. 21–27 These methods have different adaptability to different sample sizes, but basically all of them have high requirements on the initial value of iteration and need to go through complex calculations.…”

Two life prediction models for optoelectronic displays without conventional life tests

“…Optoelectronic displays refer to display devices that undergo multiple photoelectric conversions through electrical properties and include light‐emitting diodes (LED), organic LEDs (OLED), vacuum fluorescent display (VFD) . To obtain the variation rule of luminance performance with time during the failure process of these high‐reliability optoelectronic products and accurately collect their life information in a short time, it was important to conduct an accelerated degradation test (ADT) to analyze luminance attenuation performance and failure mechanisms.…”