Neuro-mechanical methods of control and diagnostics of the technical state of aircraft engine TV3-117 in film regions
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Дата
2020
ORCID
DOI
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Вісник Херсонського національного технічного університету. - 2020. - № 1(72), ч. 1. - С. 141-154
Анотація
Обґрунтовано доцільність застосування нейронних мереж у задачі контролю і діагностики технічного стану авіаційного двигуна ТВ3-117. Визначено доцільність розробки нейронних мереж на базі на базі нейрорегулятора NN Predictive Controller. З'ясовано застосування градієнтного методу навчання нейронних мереж, а також розроблено метод навчання нейрорегулятора на основі нейромодулятора із застосуванням методу зворотного поширення помилки. Отримано розв’язок задачі контролю параметрів технічного стану авіаційного двигуна ТВ3-117, який підтверджує доцільність застосування нейронних мереж у задачі контролю і діагностики технічного стану авіаційного двигуна ТВ3-117.
The subject of the study in the article is the modes of operation of the aircraft engine TV3-117 and methods of their control and diagnostics. The purpose of the work is to develop methods of control and diagnostics of the technical condition of the aircraft engine TV3-117 on the basis of neural network technologies in real time. The following tasks are solved: substantiation of the preconditions of the use of neural networks in the task of control and diagnostics of the technical condition of the aircraft engine TV3-117, construction of the generalized neural network and the choice of the algorithm for its training, the solution of the task of controlling the parameters of the technical condition of the aircraft engine TV3-117 with the use of neural networks. The following methods are used: methods of probability theory and mathematical statistics, methods of neuroinformatics, methods of the theory of information systems and data processing. The following results were obtained: The feasibility of using neural networks in the task of controlling and diagnosing the technical condition of the aircraft engine TV3-117 was substantiated. The expediency of developing neural networks based on the NN Predictive Controller. The expediency of using the gradient method of teaching neural networks is substantiated, as well as the method of training a neuro-regulator based on a neuro-modulator with the use of the method of reverse error propagation. The expediency of using the gradient method of teaching neural networks is substantiated, as well as the method of training a neuro-regulator based on a neuromodulator with the use of the method of reverse error propagation. The solution of the task of controlling the parameters of the technical condition of the aircraft engine ТВ3-117, which confirms the expediency of using neural networks in the task of control and diagnostics of the technical condition of the aircraft engine TV3-117, is obtained. The application of neural network technologies is effective in solving a wide range of poorly formalized tasks, one of which is the task of controlling the technical condition of the aircraft engine TV3-117. The advantage of neural networks in their application in the tasks of control and diagnostics of the technical condition of the aircraft engine TV3-117 is the possibility of working with small training samples, the appointment of soft tolerances, using the experience of experts to assess the technical condition of the aircraft engine TV3-117, which is important in the condition’s information incompleteness.
Обоснована целесообразность применения нейронных сетей в задачах контроля и диагностики технического состояния авиационного двигателя ТВ3-117. Определена целесообразность разработки нейронных сетей на базе нейрорегулятора NN Predictive Controller. Выяснено применение градиентного метода обучения нейронным сетям, а также разработан метод обучения нейрорегулятору на основе нейромодулятора с применением метода обратного распространения ошибки. Получено решение задачи контроля параметров технического состояния авиационного двигателя ТВ3-117, подтверждающего целесообразность применения нейронных сетей в задаче контроля и диагностики технического состояния авиационного двигателя ТВ3-117.
The subject of the study in the article is the modes of operation of the aircraft engine TV3-117 and methods of their control and diagnostics. The purpose of the work is to develop methods of control and diagnostics of the technical condition of the aircraft engine TV3-117 on the basis of neural network technologies in real time. The following tasks are solved: substantiation of the preconditions of the use of neural networks in the task of control and diagnostics of the technical condition of the aircraft engine TV3-117, construction of the generalized neural network and the choice of the algorithm for its training, the solution of the task of controlling the parameters of the technical condition of the aircraft engine TV3-117 with the use of neural networks. The following methods are used: methods of probability theory and mathematical statistics, methods of neuroinformatics, methods of the theory of information systems and data processing. The following results were obtained: The feasibility of using neural networks in the task of controlling and diagnosing the technical condition of the aircraft engine TV3-117 was substantiated. The expediency of developing neural networks based on the NN Predictive Controller. The expediency of using the gradient method of teaching neural networks is substantiated, as well as the method of training a neuro-regulator based on a neuro-modulator with the use of the method of reverse error propagation. The expediency of using the gradient method of teaching neural networks is substantiated, as well as the method of training a neuro-regulator based on a neuromodulator with the use of the method of reverse error propagation. The solution of the task of controlling the parameters of the technical condition of the aircraft engine ТВ3-117, which confirms the expediency of using neural networks in the task of control and diagnostics of the technical condition of the aircraft engine TV3-117, is obtained. The application of neural network technologies is effective in solving a wide range of poorly formalized tasks, one of which is the task of controlling the technical condition of the aircraft engine TV3-117. The advantage of neural networks in their application in the tasks of control and diagnostics of the technical condition of the aircraft engine TV3-117 is the possibility of working with small training samples, the appointment of soft tolerances, using the experience of experts to assess the technical condition of the aircraft engine TV3-117, which is important in the condition’s information incompleteness.
Обоснована целесообразность применения нейронных сетей в задачах контроля и диагностики технического состояния авиационного двигателя ТВ3-117. Определена целесообразность разработки нейронных сетей на базе нейрорегулятора NN Predictive Controller. Выяснено применение градиентного метода обучения нейронным сетям, а также разработан метод обучения нейрорегулятору на основе нейромодулятора с применением метода обратного распространения ошибки. Получено решение задачи контроля параметров технического состояния авиационного двигателя ТВ3-117, подтверждающего целесообразность применения нейронных сетей в задаче контроля и диагностики технического состояния авиационного двигателя ТВ3-117.
Опис
Vladov, S. I. Neuro-mechanical methods of control and diagnostics of the technical state of aircraft engine TV3-117 in film regions / S. I. Vladov, K. H. Kotliarov, S. A. Hrybanova and ot. // Вісник Херсонського національного технічного університету. - 2020. - № 1(72), ч. 1. - С. 141-154. - DOI: https://doi.org/10.35546/kntu2078-4481.2020.1.1.17.
Ключові слова
Техніка. Технічні науки. Machinery. Engineering. Техника. Технические науки, Наукові публікації. Scientific publications. Научные публикации, Україна. Ukraine. Украина, авіаційний двигун ТВ3-117, aircraft engine TV3-117, авиационный двигатель ТВ3-117, нейронна мережа, neural network, нейронная сеть, технічний стан, technical condition, техническое состояние, контроль, control, діагностика, diagnosis, диагностика