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Study on the Control Method of Temperature and Humidity Environment in Building Intelligent System Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Illumination Variation Similarity Based Fault Diagnosis for HV-LED Lamp Driven by Segmented Linear Driver

Authors : Fukang Sun, Shaofeng Zhu, Ye Wang

Published in: Advancements in Smart City and Intelligent Building

Publisher: Springer Singapore

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Abstract

In this paper, fault diagnosis methods based on illumination variation similarity analysis for High-voltage Light Emitting Diode (HV-LED) lamp driven by segmented linear driver are proposed. The proposed methods assess the illumination variation similarity between the diagnosed lamp and the different fault-type lamp to diagnose whether the diagnosed lamp occurs fault or not and confirm the fault type. Euclidean distance is applied for calculating illumination variation similarity. The proposed fault diagnosis methods contain four parts: illumination signal smoothing, similarity calculation, similarity assessment, and fault recognition. The illumination variation data of the fault-free and three different faulty lamps, which are based on one HV-LED lamp driven by four-segment linear driver, are investigated for method verification experiments. The experimental results and analysis are given to demonstrate the validity and effectiveness of the proposed fault diagnosis methods in test chamber environment.

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previous chapter Theoretical Study on Even Heating of Single Pipe Heating System
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Appendix
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Metadata
Title
Illumination Variation Similarity Based Fault Diagnosis for HV-LED Lamp Driven by Segmented Linear Driver
Authors
Fukang Sun
Shaofeng Zhu
Ye Wang
Copyright Year
2019
Publisher
Springer Singapore
Book
Advancements in Smart City and Intelligent Building

Print ISBN: 978-981-13-6732-8

Electronic ISBN: 978-981-13-6733-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-13-6733-5_51