A Hybrid CNN-LSTM Approach for Laser Remaining Useful Life Prediction

Abstract

A hybrid prognostic model based on convolutional neural networks (CNN) and long short-term memory (LSTM) is proposed to predict the laser remaining useful life (RUL). The experimental results show that it outperforms the conventional methods.

Optoelectronics and Communications Conference 2021

References in corpus (1)

• Machine Learning based Laser Failure Mode Detection

Cited by in corpus (2)

• A Machine Learning-based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication
• Degradation Prediction of Semiconductor Lasers using Conditional Variational Autoencoder