학술논문

Results Classification in an RGB LED Based Optical Fiber Sensor System using Python
Document Type
Conference
Source
2018 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2018 15th International Conference on. :33-36 Jul, 2018
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Field programmable gate arrays
Light emitting diodes
Classification algorithms
Clustering algorithms
Python
Optical fiber sensors
Optical fibers
RGB LED
optical fiber sensor
clustering
Language
Abstract
In this paper, the analysis of sensor results from a light emitting diode (LED) based optical fiber sensor (OFS) system is presented. A tri-color RGB (Red-Green-Blue) LED is used to provide three stimulus colors to stimulate a Surface Plasmon Resonance (SPR) sensor which is optically coupled to the system electronics. Analysis of the sensor results under different light conditions is used to identify a particular chemical under test. In the analysis approach undertaken, a combination of the CURE (Clustering Using REpresentatives) data clustering method (algorithm) and the k-nearest neighbor (kNN) algorithm is used for classifying the chemical under test. The system hardware is based on the field programmable gate array (FPGA) and the classification is undertaken on a personal computer (PC) using the Python open source programming language.