Abstract
In this paper, we proposed a system to integrate optical and electronic instrumentation devices to predict a mode-locking fiber laser response, using a remote data acquisition with processing through an artificial neural network (ANN). The system is made up of an optical spectrum analyzer (OSA), oscilloscope (OSC), polarimeter (PAX), and the data acquisition automation through transmission control protocol/internet protocol (TCP/IP). A graphic user interface (GUI) was developed for automated data acquisition with the purpose to study the operational characteristics and stability at the passively mode-locked fiber laser (figure-eight laser, F8L) output. Moreover, the evolution of the polarization state and the behavior of the pulses are analyzed when polarization is changed by proper control plate adjustments. The data is processed using deep learning techniques, which provide the characteristics of the pulse at the output. Therefore, the parameter classification-identification is in accordance with the input polarization tilt used for the laser optimization.
Highlights
Over the years, automation and data acquisition systems have received special interest due to their potential to solve tasks efficiently in many areas such as medicine [1], manufacture industries [2], video processing [3], agriculture [4], imaging [5], meteorological systems [6], remote laboratory [7], and others
The increase in the angle for data acquisition consist in varying the retarder plate PC1; for proper configuration of PC1, we generate harmonics mode-locking pulses [42] with repetition frequencies of 940.1 kHz up to 1.8 MHz
The sampling allowed observing the evolution of the polarization, simultaneously detecting the components of the temporal and spectral waveform and, at the same time, saving the information in the remote storage unit for later processing for the classification and identification of the parameters, as well as the optimization of the laser using the Artificial Neural Networks (ANN)
Summary
Automation and data acquisition systems have received special interest due to their potential to solve tasks efficiently in many areas such as medicine [1], manufacture industries [2], video processing [3], agriculture [4], imaging [5], meteorological systems [6], remote laboratory [7], and others. The development of software application in the monitoring and controlling can help reducing time and obtaining samples with good accuracy; here, the use of a graphical user interface (GUI) is a reliable alternative in remote systems [8,9,10]. Software like LabVIEW is commonly used for creating virtual environments; in addition, this software allows on-line data acquisition or off-line mass data storage through a USB-interface and its subsequent visualization in workstations [15], or in some cases it allows observation and analysis of the experimental processes [16]
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