Automated detection of light-emitting-diode chip surface blemishes on two background textures

Lin, Hong-Dar

doi:10.1117/1.2829150

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…Some researchers have tried to solve these problems encountered by the LED industry. Lin et al [234] proposed an automated detection method for surface blemishes that fall across two different background textures in an LED chip. Jeong et al [235] suggested a method that enables screening the potential field failure LEDs in mass production, in which the failure can occur by an external noise factor, by adding a "turn on current level screen" on an "operating current level screen".…”

Section: Developing a Unified Standard For Anomaly Detection And Qual...mentioning

confidence: 99%

A Review of Prognostic Techniques for High-Power White LEDs

Sun

Jiang

Yung

et al. 2017

IEEE Trans. Power Electron.

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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. Prognostics is an engineering technology that predicts the future reliability or determines the remaining useful lifetime (RUL) 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 (ROI) 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 photo-electro-thermal (PET) theory for LED systems are also discussed for clear understanding of the reliability and lifetime concepts for LEDs. Finally, the challenges

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Section: Developing a Unified Standard For Anomaly Detection And Qual...mentioning

confidence: 99%

A Review of Prognostic Techniques for High-Power White LEDs

Sun

Jiang

Yung

et al. 2017

IEEE Trans. Power Electron.

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show abstract

“…Mentioned analysis is needed as in the production process, as for example to create LED light sources for different purposes [8][9][10][11][12][13][14]. There are many different devices for LEDs monitoring and evaluation at the moment [15 -17].…”

Section: Introductionmentioning

confidence: 99%

Automated hardware-software system for LED's verification and certification

Chertov

Gorbunova

Peretyagin

et al. 2012

Twelfth International Conference on Solid State Lighting and Fourth International Conference on White LEDs and Solid State Ligh

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Scientific and technological progress of recent years in the production of the light emitting diodes (LEDs) has led to the expansion of areas of their application from the simplest systems to high precision lighting devices used in various fields of human activity. However, for all technology development at the present time it is very difficult to choose one or another brand of LEDs for realization of concrete devices designed for the implementation of high precision spatial and color measurements of various objects. In the world there are many measurement instruments for determining the various parameters of LEDs, but none of them are not capable to estimate comprehensively the LEDs spatial, spectral, and color parameters with the necessary accuracy and speed. This problem can be solved by using an automated hardware-software system for LED's verification and certification, developed by specialists of the OEDS chair of National Research University ITMO in Russia. The paper presents the theoretical aspects of the analysis of LED's spatial, spectral and color parameters by using mentioned of automated hardware-software system. The article also presents the results of spatial, spectral, and color parameters measurements of some LEDs brands.

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A global feature interaction network (GFINet) for image segmentation of GaN chips

Li,

Chen,

et al. 2024

Advanced Engineering Informatics

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Automated detection of light-emitting-diode chip surface blemishes on two background textures

Cited by 5 publications

References 22 publications

A Review of Prognostic Techniques for High-Power White LEDs

A Review of Prognostic Techniques for High-Power White LEDs

Automated hardware-software system for LED's verification and certification

A global feature interaction network (GFINet) for image segmentation of GaN chips

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