scholarly journals A Wiener process–based remaining life prediction method for light-emitting diode driving power in rail vehicle carriage

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983221 ◽  
Author(s):  
Zhi Gao ◽  
Xiaojing Yin ◽  
Bangcheng Zhang ◽  
Minmin Chen ◽  
Bo Li
Keyword(s):  
Wiener Process ◽  
Life Prediction ◽  
Light Emitting Diode ◽  
Prediction Method ◽  
Remaining Life ◽  
Output Current ◽  
Degradation Model ◽  
Light Emitting ◽  
Accelerated Degradation ◽  
Rail Vehicle

Remaining life prediction is an effective way to optimize maintenance strategy and improve service life for light-emitting diode driving power in rail vehicle carriage. In this article, a Wiener process–based remaining life prediction method is proposed with the analysis of performance degradation data of light-emitting diode driving power in rail vehicle carriage. First, the temperature and humidity stress accelerated degradation tests are put forward in order to measure the output current of light-emitting diode driving power. Based on the output current, the accelerated degradation model is established. The drift and diffusion coefficients of the Wiener process are then obtained without prior information. Finally, the reliability of light-emitting diode driving power in rail vehicle carriage is assessed and the remaining lifetime is predicted after updating the degradation model parameters with Bayesian inference. The results show that the proposed method can improve the precision of assessment and reduce the uncertainty of prediction significantly. It also provides a potential solution for life prediction of other similar products.

Remaining useful life prediction method for machine tools based on meta-action theory

2021 ◽  
pp. 1748006X2110025
Author(s):  
Zongyi Mu ◽  
Yan Ran ◽  
Genbao Zhang ◽  
Hongwei Wang ◽  
Xin Yang
Keyword(s):  
Machine Tools ◽  
Life Prediction ◽  
Action Theory ◽  
Prediction Method ◽  
Operational Reliability ◽  
Remaining Useful Life ◽  
Practical Application ◽  
Dynamic Prediction ◽  
Degradation Model ◽  
Useful Life

Remaining useful life (RUL) is a crucial indictor to measure the performance degradation of machine tools. It directly affects the accuracy of maintenance decision-making, thus affecting operational reliability of machine tools. Currently, most RUL prediction methods are for the parts. However, due to the interaction among the parts, even RUL of all the parts cannot reflect the real RUL of the whole machine. Therefore, an RUL prediction method for the whole machine is needed. To predict RUL of the whole machine, this paper proposes an RUL prediction method with dynamic prediction objects based on meta-action theory. Firstly, machine tools are decomposed into the meta-action unit chains (MUCs) to obtain suitable prediction objects. Secondly, the machining precision unqualified rate (MPUR) control chart is used to conduct an out of control early warning for machine tools’ performance. At last, the Markov model is introduced to determine the prediction objects in next prediction and the Wiener degradation model is established to predict RUL of machine tools. According to the practical application, feasibility and effectiveness of the method is proved.

Accelerated Degradation of High Power Light-Emitting Diode Resulted from Inhomogeneous Current Distribution

2011 ◽  
Vol 50 ◽  
pp. 034301
Author(s):  
Shih Chun Yang ◽  
Pang Lin ◽  
Han Kuei Fu ◽  
An Tse Lee ◽  
Tzung Te Chen ◽  
...  
Keyword(s):  
Current Distribution ◽  
High Power ◽  
Light Emitting Diode ◽  
Light Emitting ◽  
Accelerated Degradation

scholarly journals Coating Life Prediction for Combustion Turbine Blades

1998 ◽  
Author(s):  
Kwai S. Chan ◽  
N. Sastry Cheruvu ◽  
Gerald R. Leverant
Keyword(s):  
Experimental Data ◽  
Turbine Blade ◽  
Cycle Time ◽  
Life Prediction ◽  
Aluminide Coating ◽  
Turbine Blades ◽  
Prediction Method ◽  
Remaining Life ◽  
Degradation Mechanisms ◽  
Useful Life

A life prediction method for combustion turbine blade coatings has been developed by modeling coating degradation mechanisms including oxidation, spallation, and aluminum loss due to inward diffusion. Using this model, the influence of cycle time on coating life is predicted for GTD-111 coated with an MCrAlY, PtAl, or aluminide coating. The results are used to construct a coating life diagram that depicts failure and safe regions for the coating in a log-log plot of number of startup cycles versus cycle time. The regime where failure by oxidation, spallation, and inward diffusion dominates is identified and delineated from that dominated by oxidation and inward diffusion only. A procedure for predicting the remaining life of a coating is developed. The utility of the coating life diagram for predicting the failure and useful life of MCrAlY, aluminide, or PtAl coatings on the GTD-111 substrate is illustrated and compared against experimental data.

LED life prediction based on lumen depreciation and colour shift

2016 ◽  
Vol 49 (1) ◽  
pp. 84-99 ◽  
Author(s):  
AN Padmasali ◽  
SG Kini
Keyword(s):  
Life Prediction ◽  
Energy Savings ◽  
Light Emitting Diode ◽  
Light Output ◽  
Light Sources ◽  
Colour Stability ◽  
Light Emitting ◽  
Colour Temperature ◽  
Life Estimation ◽  
Chromaticity Coordinates

Light emitting diodes, with advantages in energy savings, luminous efficacy and greater reliability, are becoming preferred over conventional white light sources. Currently, only light output depreciation is considered for life estimation of light emitting diode luminaires but it is recommended to include colour shift variations for applications demanding colour stability. In this paper, an extended Kalman filter is employed to determine L70 life and colour temperature degradation over life of a light emitting diode luminaire. The colour shift in terms of Duv is determined by statistical polynomial cure fitting. The variation in chromaticity coordinates over life is determined and life based on colour shift is determined by acceptable Duv limits. The results are compared to life determined by the IES-TM-21 method and the correlated colour temperature limits taken from the luminaire data sheet.

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