Применение нейросетевых технологий для определения величины расхода сыпучего вещества
Copyright policy )Применение нейросетевых технологий для определения величины расхода сыпучего вещества
A method is proposed for estimation of dependence between primary measuring capacitor sensor output signal and density of grain flow based on neural network technologies. Description of the method and results of investigation are presented.
Рассматривается способ установления зависимости параметров выходного сигнала емкостного первичного измерительного преобразователя от плотности потока зерна с помощью нейросетевых технологий. Приведены методика и результаты экспериментов.
ИЗМЕРЕНИЕ РАСХОДА,FLOW MEASURING,ЗЕРНО,GRAIN,ПЕРВИЧНЫЙ ЕМКОСТНЫЙ ПРЕОБРАЗОВАТЕЛЬ,PRIMARY CAPACITOR SENSOR,НЕЙРОСЕТЕВЫЕ ТЕХНОЛОГИИ,NEURAL NETWORK TECHNOLOGIES
ИЗМЕРЕНИЕ РАСХОДА,FLOW MEASURING,ЗЕРНО,GRAIN,ПЕРВИЧНЫЙ ЕМКОСТНЫЙ ПРЕОБРАЗОВАТЕЛЬ,PRIMARY CAPACITOR SENSOR,НЕЙРОСЕТЕВЫЕ ТЕХНОЛОГИИ,NEURAL NETWORK TECHNOLOGIES
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