Machine Learning based Laser Failure Mode Detection
Laser degradation analysis is a crucial process for the enhancement of laser reliability. Here, we propose a data-driven fault detection approach based on Long Short-Term Memory (LSTM) recurrent neural networks to detect the different laser degradation modes based on synthetic historical failure data. In comparison to typical threshold-based systems, attaining 24.41% classification accuracy, the LSTM-based model achieves 95.52% accuracy, and also outperforms classical machine learning (ML) models namely Random Forest (RF), K-Nearest Neighbours (KNN) and Logistic Regression (LR).
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningFault DetectionregressionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Machine Learning based Data Driven Diagnostic and Prognostic Approach for Laser Reliability Enhancement
In this paper, a data-driven diagnostic and prognostic approach based on machine learning is proposed to detect laser failure modes and to predict the remaining useful life (RUL) of a laser during its operation. We prese…
BIG-bench Machine LearningDiagnosticMultisensor fusion-based digital twin in additive manufacturing for in-situ quality monitoring and defect correction
Early detection and correction of defects are critical in additive manufacturing (AM) to avoid build failures. In this paper, we present a multisensor fusion-based digital twin for in-situ quality monitoring and defect c…
Fabry-Perot Lasers as Enablers for Parallel Reservoir Computing
We introduce the use of Fabry-Perot (FP) lasers as potential neuromorphic computing machines with parallel processing capabilities. With the use of optical injection between a master FP laser and a slave FP laser under f…
ClassificationGeneral ClassificationTowards Sustainable Precision: Machine Learning for Laser Micromachining Optimization
In the pursuit of sustainable manufacturing, ultra-short pulse laser micromachining stands out as a promising solution while also offering high-precision and qualitative laser processing. However, unlocking the full pote…
A Machine Learning-based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication
Semiconductor lasers, one of the key components for optical communication systems, have been rapidly evolving to meet the requirements of next generation optical networks with respect to high speed, low power consumption…
Anomaly DetectionDecision MakingPredictionPrognosis