Fiber optic sensing process control system based on data mining algorithm - Gao, Wei (Oficyna Wydawnicza Politechniki Wrocławskiej, 2025)
To measure the state of ethanol differentiation process, a fiber option sensing based process state monitoring system is designed. It includes a laser, demo module, PC processing module, fiber option sensing network, and state feedback control unit. A data mining algorithm for multi-parameter demo is proposed to accurately achieve temperature and strain field classification and combine accuracy to the different weights of temperature and strain on different positions, improving the correlation between wavelengths offset and state parameters. The experiment compared four common abnormal situations, The experiment adopts the method of collecting the temperature field inside the tank and the stress field outside the tank, with strain testing of 100–5000 με and temperature testing range of 0–120 °C. The results showed that the average temperature sensitivity after calibration was 0.0102 nm / °C, and the linearity was 0.9959. The average strain sensitivity is 0.499 pm/με, and the linearity is 0.9982. Feedback control has the ability to adjust state fluctuations online, and the feedback time varies for different types of anomalies. The temperature and strain wavelength deviations after correction for all four cases are less than ±1 °C and ±50 με.
Optica Applicata, Vol. 55, 2025, nr 1, s. 49-62
Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory
http://opticaapplicata.pwr.edu.pl/
Keywords: optyka; data mining; FBG network; industrial process equipment; fiber optic sensing; optimum control