References
- X. Long et al., “A Review on Light-Emitting Diode Based Automotive Headlamps,” Renewable and Sustainable Energy Reviews, vol. 41, 2015, pp. 29–41.
- D. Busek and K. Dusek, “Overview of Various Failures of Luminaires Assembled with SMD LED Chips,” 2022 45th International Spring Seminar on Electronics Technology (ISSE), 2022, pp. 1–5.
- M. Esteki et al., “LED Systems Applications and LED Driver Topologies: A Review,” IEEE Access, vol. 11, 2023, pp. 38324–38358.
- R. Sananda, C. Tejaswi, and B. Rishaya, “Trends and Challenges in Automotive Headlamps,” Proc.SPIE, vol. 12638, 2023, p. 126380R.
- D.-B. Perng, H.-W. Liu, and C.-C. Chang, “Automated SMD LED Inspection using Machine Vision,” The International Journal of Advanced Manufacturing Technology, vol. 57, no. 9, 2011, pp. 1065–1077.
- K. Fumagalli, R. Faranda, and L. Farne, “Analysis of Possible LED Failure Mode,” 2014 Petroleum and Chemical Industry Conference Europe, 2014, pp. 1–8.
- H. Jiang et al., “LED Device Fault Diagnosis Base on Neural Network and SVM Model Analysis,” 2017 14th China International Forum on Solid State Lighting: International Forum on Wide Bandgap Semiconductors China (SSLChina: IFWS), 2017, pp. 45–47.
- A. Arora and V. Goel, ‘Real Time Fault Analysis and Acknowledgement System for LED String,” 2018 International Conference on Computing, Power and Communication Technologies (GUCON), 2018, pp. 457–461.
- H. K. Fu et al., “Accelerated Life Testing and Fault Analysis of High-Power LED,” IEEE Transactions on Electron Devices, vol. 65, no. 3, 2018, pp. 1036–1042.
- M. S. Ibrahim et al., “Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light-Emitting Diodes,” Laser & Photonics Reviews, vol. 14, no. 12, 2020, p. 2000254.
- Y. Shang et al., “A Novel Fault Diagnosis Strategy for LED Lamps via Light Output Time-Frequency Characteristics Analysis and Machine Learning,” Heliyon, vol. 9, no. 9, 2023.
- J. R. Martinez-Perez et al., “Advanced Detection of Failed LEDs in a Short Circuit for Automotive Lighting Applications,” Sensors, vol. 24, no. 9; doi: 10.3390/s24092802.
