NEURO-MECHANICAL METHODS OF CONTROL AND DIAGNOSTICS OF THE TECHNICAL STATE OF AIRCRAFT ENGINE TV3-117 IN FILM REGIONS

 Предметом дослідження в статті є режими роботи авіаційного двигуна ТВ3-117 та методи їх контролю і діагностики. Мета роботи – розробка методів контролю і діагностики технічного стану авіаційного двигуна ТВ3-117 на основі нейромережевих технологій у режимі реального часу. В статті вирішуються наступні завдання: обґрунтування передумов застосування нейронних мереж у задачі контролю і діагностики технічного стану авіаційного двигуна ТВ3-117, побудова узагальненої нейронної мережі та вибір алгоритму її навчання, розв’язок задачі контролю параметрів технічного стану авіаційного двигуна ТВ3-117 із застосуванням нейронних мереж. Використовуються такі методи: методи теорії ймовірностей і математичної статистики, методи нейроінформатики, методи теорії інформаційних систем та обробки даних. Отримано наступні результати: Обґрунтовано доцільність застосування нейронних мереж у задачі контролю і діагностики технічного стану авіаційного двигуна ТВ3-117. Обґрунтовано доцільність розробки нейронних мереж на базі на базі нейрорегулятора NN Predictive Controller. Обґрунтовано доцільність 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. Висновки: Застосування нейромережевих технологій э ефективним при розв’язку широкого кола погано формалізованих задач, однією з яких є задача контролю технічного стану авіаційного двигуна ТВ3-117. Перевагою нейронних мереж при їх застосуванні у задачах контролю і діагностики технічного стану авіаційного двигуна ТВ3-117 є можливість роботи з малими навчальними вибірками, призначенням м’яких допусків, використанням досвіду експертів для оцінки технічного стану авіаційного двигуна ТВ3-117, що є важливим в умовах неповноти інформації.Ключові слова: авіаційний двигун, нейронна мережа, технічний стан, контроль і діагностикаThe 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 neuro-modulator 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. Conclusions: 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.Keywords: engine, neural network, technical condition, control and diagnosi

Stratigraphy of Late Cenozoic sediments of the western Chukchi Sea: New results from shallow drilling and seismic-reflection profiling

The Quaternary history of Beringia and of the Arctic–Pacific marine connection via the Bering Strait is poorly understood because of the fragmentary stratigraphic record from this region. We report new borehole and seismic-reflection data collected in 2006 in the southwestern Chukchi Sea. Sediment samples were analyzed for magnetic properties, grain size, heavy minerals, and biostratigraphic proxies (spores and pollen, foraminifers, ostracodes, diatoms, and aquatic palynomorphs). Two shallow boreholes drilled between the Chukotka Peninsula and the Wrangel Island recovered sediments of two principal stratigraphic units with a distinct unconformity between them. Based on predominantly reverse paleomagnetic polarity of the lower unit and pollen spectra indicative of forested coasts and climate warmer than present, the age of this unit is estimated as Pliocene to early Pleistocene (broadly between ca. 5 and 2 Ma). Attendant sedimentary environments were likely alluvial to nearshore marine. These deposits can be correlated to the seismic unit infilling valleys incised into sedimentary bedrock across much of the study area, and possibly deposited during a transgression following the opening of the Bering Strait. The upper unit from both boreholes contains Holocene 14C ages and is clearly related to the last, postglacial transgression. Holocene sediments in Borehole 2 indicate fast deposition at the early stages of flooding (between ca. 11 and 9 ka) to very low deposition, possibly related to expansive sea ice. Closer to shore, deposition at Borehole 1 resumed much later (ca. 2 ka), likely due to a change in the pattern of coastal erosional processes and/or the demise of a landbridge between the Chukotka Peninsula and the Wrangel Island inferred from studies on mammoth distribution

Soliton-based discriminator of non-coherent optical pulses

We introduce a concept of noncoherent optical pulse discrimination from a coherent (or partially coherent) signal of the same energy using a phenomenon of soliton generation. The impact of randomisation of the optical signal content on the observable characteristics of solitons generation is examined and quantified for a particular example of rectangular pulse.Comment: Submitted to Phys. Rev.

Analysis of the dynamics and structure of morbidity of athletes of the national teams of Moscow based on the results of medical examination

Objective: The aim of the study was to analyze the structure and dynamics of morbidity of athletes, members of sports teams of the city of Moscow based on the results of an in-depth medical examination in the period 2017–2021.Materials and methods: The data of the medical examination of athletes, which took place at the Moscow scientific and Practical Center for Medical Rehabilitation, restorative and sports medicine, including instrumental, functional and laboratory studies from 2017 to 2021, were analyzed. In 2017, 15176 athletes were examined, in 2018 and 2019, 11200, in 2020, 10080 people and in 2021–11922 athletes.Results: The results of the study showed an increase in the proportion of amenorrhea within the triad of athletes, an increase in general therapeutic morbidity, diseases of the gastrointestinal tract, among which the proportion of secondary hyperbilirubinemia in 2021 increased 3 times compared to 2020, which, in our opinion, is also due to the impact of the pandemic and quarantine restrictions.The high prevalence of ophthalmological morbidity of athletes and changes in the cardiovascular system is shown. During 2017–2021, a change in the structure of cardiac morbidity was revealed in the form of an increase in the proportion of cardiac arrhythmias and hypertensive response to stress.An increase in the endocrine morbidity of athletes in 2021 was revealed due to an increase in the proportion of hypothyroidism and more frequent detection of hyperthyroidism, possibly related to the COVID-19 pandemic, which requires further research.There was also an increase in diseases of the skin and genitourinary system in athletes. Psychological problems of athletes increased during the observation period from 2017 to 2021. There was no significant dynamics of surgical and traumatological diseases, otolaryngological pathologу.Conclusion: The results of the study indicate the importance of regular full-fledged examination of athletes, identification of various functional disorders and diseases for their timely prevention and treatment in order to preserve the health of athletes and improve athletic performance

Evolving Recurrent Neural Networks for Pattern Classification

While reaching outstanding prediction rates by means of black-box classifiers is relatively easy nowadays, reaching a proper trade-off between accuracy and interpretability might become a challenge. The most popular approaches reported in the literature to overcome this problem use post-hoc procedures to explain what the classifiers have learned. Less research is devoted to building classification models able to intrinsically explain their decision process. This paper presents a recurrent neural network---termed Evolving Long-term Cognitive Network---for pattern classification, which can be deemed interpretable to some extent. Moreover, a backpropagation learning algorithm to adjust the parameters attached to the model is presented. Numerical simulations using 35 datasets show that the proposed network performs well when compared with traditional black-box classifiers

Social profile of tuberculosis in urban area

Background. Tuberculosis is an infectious socially significant disease. Apart from individual traits of the disease pathology, drug sensitivity and the availability of effective medicine and prevention, an important factor of its control is the patient’s social status. Social patient profiling in various locations across the country is vital for developing and deploying a high-quality and feasible tuberculosis care programme.Objectives. Social profiling of tuberculosis in St. Petersburg as an example of large urban area. Methods. We developed a questionnaire to assess 40 social parameters of a patient with tuberculosis. The study sample was representative and surveyed 666 (63.4%) and 704 (65.7%) patients with primary diagnosis in 2017 and 2018, respectively.Results. The survey showed almost no impact of external migration on tuberculosis epidemiology in St. Petersburg. Internal migrants counted 76 (11.4%) in 2017 and 96 (13.4%) in 2018, thus suggesting the majority of primary tuberculosis patients being permanent residents of St. Petersburg. The contribution of individuals with no fixed abode to the incidence rate was also insignificant, 2.4% and 1.9%. Most patients were unemployed people of working age, 236 (35.4%) in 2017, 261 (37.1%) in 2018. Incidence among students as a younger population was lowest, 2.1% and 2.8%. Smokers accounted for half of total patients, 370 (55.6%) and 368 (52.3%). One in five patients carried HIV infection, with half of them not receiving antiretroviral therapy. Patients with unfinished secondary education and residing in collective dwellings were significantly more frequent, whilst the proportion of persons with high income decreased. Over half of the patients had no family at primary diagnosis, and over a third had never been married.Conclusion. The social profile of primary tuberculosis in an urban area is as follows: single man, near 40 years old, permanent resident, unemployed, working-age, smoker, resides in private abode, has secondary or secondary vocational education, low to average income

Environmental evolution of the southern Chukchi Sea in the Holocene

The molluscan shells from three drill and two piston cores obtained in the southern Russian sector of the Chukchi Sea are dated by the AMS 14C measurement method back to 0.8–3.5 and 9.2–10.5 ka. The period of 9–10 ka was marked by increased sedimentation rates related to the transgression onset. The fossils in the lower Holocene section exhibit the successive upward replacement of brackish-water organisms by their marine counterparts. After the opening of the Bering Strait in the middle Holocene, the sedimentation was under influence of the increased bioproductivity of the waters. The climatic optimum in the Chukotka region corresponds to the early Holocene, while the late Holocene was characterized by the wider development of the ice cover on the shelf