首页|Report Summarizes Machine Learning Study Findings from National Taipei Universit y of Technology (Wavelength-Dependent Bragg Grating Sensors Cascade an Interfero meter Sensor to Enhance Sensing Capacity and Diversification through the Deep Be lief ...)
Report Summarizes Machine Learning Study Findings from National Taipei Universit y of Technology (Wavelength-Dependent Bragg Grating Sensors Cascade an Interfero meter Sensor to Enhance Sensing Capacity and Diversification through the Deep Be lief ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Taipei, Taiwan, by NewsRx c orrespondents, research stated, “Fiber-optic sensors, such as fiber Bragg gratin g (FBG) sensors and fiber-optic interferometers, have excellent sensing capabili ties for industrial, chemical, and biomedical engineering applications.” Financial supporters for this research include National Science And Technology C ouncil, Taiwan. Our news reporters obtained a quote from the research from National Taipei Unive rsity of Technology: “This paper used machine learning to enhance the number of fiber-optic sensing placement points and promote the cost-effectiveness and dive rsity of fiber-optic sensing applications. In this paper, the framework adopted is the FBG cascading an interferometer, and a deep belief network (DBN) is used to demodulate the wavelength of the sampled complex spectrum. As the capacity of the fiber-optic sensor arrangement is optimized, the peak spectra from FBGs und ergoing strain or temperature changes may overlap. In addition, overlapping FBG spectra with interferometer spectra results in periodic modulation of the spectr al intensity, making the spectral intensity variation more complex as a function of different strains or temperature levels. Therefore, it may not be possible t o analyze the sensed results of FBGs with the naked eye, and it would be ideal t o use machine learning to demodulate the sensed results of FBGs and the interfer ometer.”
National Taipei University of TechnologyTaipeiTaiwanAsiaCyborgsEmerging TechnologiesMachine Learning
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