Failure Mechanisms Associated With Lens Shape of High-Power LED Modules in Aging Test

Hsu, Yi‐Cheng; Lin, Yi Ru; Chen, Ming-Hung; Tsai, Chun-Chin; Kuang, Jao-Hwa; Huang, Sheng; Hu, Hung-Lieh; Su, Yeh-I; Cheng, Wood-Hi

doi:10.1109/ted.2007.911905

Cited by 70 publications

(8 citation statements)

References 10 publications

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“…Both the PoF and DD‐based PHM methods have been employed successfully in the prediction of failures in many devices and systems (e.g., machinery systems, LED lighting devices and systems, hybrid systems). [ 48,187 ] However, the PoF methods [ 188–191,203,204 ] require comprehensive knowledge of products in advance (e.g., materials and geometries, thermal, electrical, mechanical, etc. ), life‐cycle conditions, and other processes that lead to failures always increases the time and cost in actual applications.…”

Section: Fusion Prognostics Approach For Ledsmentioning

confidence: 99%

Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes

Ibrahim

Fan

Yung

et al. 2020

Laser & Photonics Reviews

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Light-emitting diodes (LEDs) are among the key innovations that have revolutionized the lighting industry, due to their versatility in applications, higher reliability, longer lifetime, and higher efficiency compared with other light sources. The demand for increased lifetime and higher reliability has attracted a significant number of research studies on the prognostics and lifetime estimation of LEDs, ranging from the traditional failure data analysis to the latest degradation modeling and machine learning based approaches over the past couple of years. However, there is a lack of reviews that systematically address the currently evolving machine learning algorithms and methods for fault detection, diagnostics, and lifetime prediction of LEDs. To address those deficiencies, a review on the diagnostic and prognostic methods and algorithms based on machine learning that helps to improve system performance, reliability, and lifetime assessment of LEDs is provided. The fundamental principles, pros and cons of methods including artificial neural networks, principal component analysis, hidden Markov models, support vector machines, and Bayesian networks are presented. Finally, discussion on the prospects of the machine learning implementation from LED packages, components to system level reliability analysis, potential challenges and opportunities, and the future digital twin technology for LEDs lifetime analysis is provided.

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Section: Fusion Prognostics Approach For Ledsmentioning

confidence: 99%

Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes

Ibrahim

Fan

Yung

et al. 2020

Laser & Photonics Reviews

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“…This has to do with the fact that optical components in LED packages have a central role in the optical performance of LED devices by controlling the emission of light from the device. In fact, any depreciation in lumen output may involve a chromaticity shift as well [161][162][163][164][165][166][167][168][169][170][171][172][173][174][175][176]. As already mentioned, an LED lamp is a complicated system, containing secondary lenses, reflective layers, and diffusers, all intended to achieve a desired light emission pattern.…”

Section: Degradation Of Optical Materialsmentioning

confidence: 99%

“…In addition, the operation condition is also considered to be a determining factor. For instance, stress variations induced by thermal shock can accelerate the formation of cracks in the epoxy lens [171,172]. Also, humidity and thermal exposure can result in deterioration of mechanical strength as well as fracture resistance, both having negative implications for crack resistance [173].…”

Section: Lens Crackingmentioning

confidence: 99%

“…Phosphor thermal quenching debonding at the soldered areas, mainly caused by the existing differences between the CTEs as well as temperature cycles during production and service is another commonly observed failure modes in LEDs. Severe delamination is also reported at the interface of lead frames and epoxy moulding compound (EMC) used to encapsulate the lead frame [65,171,172]. It is reported that curing of epoxy resins during production is associated with a significant shrinkage, which is a source of internal stress and mismatch in the package [164].…”

Section: Delamination and Debondingmentioning

confidence: 99%

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Degradation of optical materials in solid-state lighting systems

Mehr

Bahrami

Driel

et al. 2019

International Materials Reviews

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In this paper, degradation mechanisms of optical materials, used in the light emitting diode (LED)-based products, are reviewed. The LED lighting is one of the fastest technology shifts in human history. Lighting accounts for almost 20% of the global electrical energy use, inferring that replacement of traditional lighting sources with LEDs with higher efficiencies will have major positive implications for the global energy consumption. Organic optical materials are key components in LEDs in the sense that they control the functionality of the device and they have decisive effects on the durability and reliability of LEDs. This paper aims at describing the influences of chemical structure and service conditions on the degradation mechanisms of organic optical materials in LEDs which lead to the lumen depreciation, discolouration, and colour shift of the LED light output. The contributions of different degradation mechanisms of optical and package materials in LED-based products to the lumen depreciation and colour shift are methodically reviewed.

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“…High-brightness LEDs have demonstrated excellent ability for functioning in back and general lighting applications [2]. LEDs are usually considered DC devices, powered by a few volts of direct current.…”

Section: Introductionmentioning

confidence: 99%

Numerical Study of Thermal Behavior in Alternating Current Light-Emitting Diodes

Hwu¹,

Hsieh

2013

Advances in Mechanical Engineering

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The thermal characteristics of an alternating current light-emitting diode (AC LED) chip based on a three-dimensional unsteady numerical simulation are discussed. In this model, the difficulties due to the tiny scale and extra-low aspect ratio of the AC LED microchip geometry are resolved. A time lag between the maximum forward voltage and the highest mean junction temperature is observed. The influence of different input power frequencies on the thermal fields is also investigated for AC LEDs with 600 m × 600 m area. A numerical simulation of the junction temperature distributions shows that the AC LED has a better performance under a higher frequency than under a lower frequency.

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Failure Mechanisms Associated With Lens Shape of High-Power LED Modules in Aging Test

Cited by 70 publications

References 10 publications

Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes

Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes

Degradation of optical materials in solid-state lighting systems

Numerical Study of Thermal Behavior in Alternating Current Light-Emitting Diodes

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