scholarly journals Development of a Method for Evaluating the Technical Condition of a Car’s Hybrid Powertrain

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2356
Author(s):  
Oleksiy Bazhinov ◽  
Juraj Gerlici ◽  
Oleksandr Kravchenko ◽  
Yevhen Haiek ◽  
Tetiana Bazhynova ◽  
...  
Keyword(s):  
Neural Network ◽  
Control Sample ◽  
Technical Condition ◽  
Diagnostic Methods ◽  
Technical State ◽  
Optimal Controls ◽  
Hybrid Powertrain ◽  
Linear Inversion ◽  
Hybrid Propulsion ◽  
Diagnostic Parameters

The article presents the results of a study performed and substantiated based on the principles of a new method of diagnostics of technical conditions of a hybrid powertrain regardless of the structural diagram and design features of a hybrid vehicle. The presented new technology of the diagnostics of hybrid powertrains allows an objective complex assessment of their technical condition by diagnostic parameters in contrast to existing diagnostic methods. In the proposed method, a mechanism for the general standardization of diagnostic parameters has been developed as well as for determining the numerical values of the parameters of the powertrain. The control subset was used to control the learning error. As a result of debugging the system, the scatter of experimental and calculated points has decreased, which confirms the quality of debugging the tested fuzzy model. As a result of training the artificial neural network, the standard deviation of the error in the control sample was 0.012·Pk. A symmetry method of diagnostics of the technical state of a hybrid propulsion system was developed based on the concept of a neural network together with a neuro-fuzzy control with an adaptive criteria based on the method of training a neural network with reinforcement. The components of the vector functional include the criteria for control accuracy, the use of traction battery energy, and the degree of toxicity of exhaust gases. It is proposed to use the principle of symmetry of the guaranteed result and the linear inversion of the vector criterion into a supercriterion to determine the technical state of a hybrid powertrain on a set of Pareto-optimal controls under unequal conditions of optimality.

scholarly journals Methods of clustering parameters in the creation of neural network multi-mode dynamic models of aircraft engines

2021 ◽  
pp. 71-78
Author(s):  
Александр Анатолиевич Тамаргазин ◽  
Людмила Борисовна Приймак ◽  
Валерий Владиславович Шостак
Keyword(s):  
Neural Network ◽  
Cluster Analysis ◽  
Gas Turbine ◽  
Technical Condition ◽  
Technical State ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Aircraft Engines ◽  
Clustering Methods ◽  
Aviation Engines

The presence on modern aviation gas-turbine engines of dozens and even hundreds of sensors for continuous registration of various parameters of their operation makes it possible to collect and process large amounts of information. This stimulates the development of monitoring and diagnostic systems. At the same time the presence of great volumes of information is not always a sufficient condition for making adequate managerial decisions, especially in the case of evaluation of the technical condition of aviation engines. Thus it is necessary to consider, that aviation engines it is objects which concern to individualized, i.e. to such which are in the sort unique. Therefore, the theory of creating systems to assess the technical state of aircraft engines is formed on the background of the development of modern neural network technology and requires the formation of specific methodological apparatus. From these positions in the article the methods which are used at carrying out clustering of the initial information received at work of modern systems of an estimation and forecasting of a technical condition of aviation gas-turbine engines are considered. This task is particularly relevant for creating neural network multimode models of aircraft engines used in technical state estimation systems for identification of possible failures and damages. Metric, optimization and recurrent methods of input data clustering are considered in the article. The main attention is given to comparison of clustering methods in order to choose the most effective of them for the aircraft engine condition evaluation systems and suitable for implementation of systems with meta-learning. The implementation of clustering methods of initial data allows us to breakdown diagnostic images of objects not by one parameter, but by a whole set of features. In addition, cluster analysis, unlike most mathematical-statistical methods do not impose any restrictions on the type of objects under consideration, and allows us to consider a set of raw data of almost arbitrary nature, which is very important when assessing the technical condition of aircraft engines. At the same time cluster analysis allows one to consider a sufficiently large volume of information and sharply reduce, compress large arrays of parametrical information, make them compact and visual.

scholarly journals Analysis of Diagnostic Methods and Energy of Production Systems Drives

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 843
Author(s):  
Ivan Kuric ◽  
Ivana Klačková ◽  
Yury Rafailovich Nikitin ◽  
Ivan Zajačko ◽  
Miroslav Císar ◽  
...  
Keyword(s):  
Fuzzy Inference ◽  
Diagnostic System ◽  
Sensory Systems ◽  
Technical Condition ◽  
Repair Time ◽  
Diagnostic Methods ◽  
Technical Diagnostics ◽  
Inference System ◽  
Diagnostic Parameters ◽  
Industrial Enterprises

This article deals with solving the urgent scientific problem of the diagnostics of drives of technological robotized workplaces with support of sensors. The dependence of diagnostic parameters on the technical state of drives of automated technological systems, which is of great economic importance for industrial enterprises, is being investigated. Diagnostic models have been developed based on sensory systems to diagnose drive models of technological robotized workplaces. The use of these models may also include monitoring systems in which it is possible to build a system for identifying detected changes. These systems identify many contradictory changes and thereby reduce the false alarm frequency of monitoring sensory systems. Numerous methods for solving technical diagnostics problems are often based on methods based on mathematical models describing work processes, as well as on spectral analysis of measured parameters, such as vibrations, noise, and electric current. A fuzzy inference system for assessing the technical condition, a system for estimating the residual resource of drives, and asystem for calculating diagnostic intervals based on fuzzy knowledge have been developed. Based on the historical trend of the diagnostic parameters, the intelligent diagnostic system determines the current technical condition of the actuator and predicts future technical condition changes, determines the remaining service life and the time intervals for diagnostics. The analysis of the time spent on planned preventive maintenance of technological equipment makes it possible to conclude that, after the modernization of equipment in 2018, the repair time was reduced from 350 h to 260 h per year (26%). Since 2019, there is a tendency to increase repair time by 30 h each year.

scholarly journals Analysis of vibrodiagnostics methods in the technical state study of designed multimedia mobile scenes

2019 ◽  
Vol 302 ◽  
pp. 01011
Author(s):  
Marcin Łukasiewicz ◽  
Michał Liss ◽  
Natalia Dluhunovych
Keyword(s):  
Modal Analysis ◽  
Diagnostic Tests ◽  
Research Process ◽  
Technical Condition ◽  
Technical State ◽  
Normal Operation ◽  
Design Stage ◽  
Analysis Methods ◽  
State Study ◽  
Diagnostic Research

The paper presents the possibilities of using vibroacoustic methods in the study of the technical condition of designed multimedia mobile scenes. In particular, the possibility of implementing modal analysis methods in modelling and diagnostic research process has been presented. The use of virtual methods enables diagnostic tests both at the design stage and at the stage of normal operation, whereas modal methods help to explain the nature of the work of the element under investigation.

Application of neural network expert systems for monitoring, diagnostics and forecasting of technical condition of aircraft engines

2020 ◽  
pp. 51-59
Author(s):  
Д.О. Пушкарёв
Keyword(s):  
Neural Network ◽  
Expert Systems ◽  
Gas Turbine ◽  
Technical Condition ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Fuzzy Interference System ◽  
Interference System ◽  
Monitoring And Diagnostics ◽  
Technical Operation

Рассматривается применение нейросетевых экспертных систем в области контроля, диагностики и прогнозирования технического состояния авиационных ГТД на основе нечеткой логики. Показана методика для решения таких задач в области технической эксплуатации авиационной техники совместно с использованием фаззи-интерференсной системы программы MATLAB. Используя статистические данные о работе двигателя формируется экспертная система на основе нейронной сети позволяющая осуществлять контроль и диагностику ГТД, а также прогнозировать дальнейшее техническое состояния анализируемого двигателя. The application of neural network expert systems in the field of monitoring, diagnostics and forecasting of the technical condition of aviation gas turbine engines based on fuzzy logic is considered. The technique for solving such problems in the field of technical operation of aircraft and using the fuzzy-interference system of the MATLAB program is shown. Using statistical data on the operation of the engine, an expert system is based on the fundamental of a neural network that provide monitoring and diagnostics of gas turbine engines, as well as predicting the further technical condition of the analyzed engine.

Development of hydraulic cylinder diagnostic methods by modeling methods

2021 ◽  
pp. 41-45
Author(s):  
Keyword(s):  
Hydraulic Drive ◽  
Hydraulic Cylinder ◽  
Technical Condition ◽  
Diagnostic Methods ◽  
Technical Diagnostics ◽  
Remaining Service Life ◽  
Construction Machine ◽  
Piston Speed ◽  
Variable Nature ◽  
Hydraulic Cylinders

The hydraulic drive of a construction machine is a complex dynamic system that is subjected to many dynamic loads of a variable nature and operates under conditions of variable external influences caused by various factors. During operation, these loads cause failure of the hydraulic transmission elements. To prevent these malfunctions, technical diagnostics should be applied by determining their current technical condition and remaining service life. The article assesses the working condition of hydraulic cylinders using a mathematical model. Using matlab/simulink software to simulate the hydraulic cylinder and hydraulic piston speed when changing the hydraulic cylinder clearance. The simulation results are presented. Keywords: diagnostic, hydraulic cylinder, simulation, development

scholarly journals Virus detection and identification in minutes using single-particle imaging and deep learning

2020 ◽  
Author(s):  
Nicolas Shiaelis ◽  
Alexander Tometzki ◽  
Leon Peto ◽  
Andrew McMahon ◽  
Christof Hepp ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Single Particle ◽  
Virus Detection ◽  
Diagnostic Methods ◽  
Clinical Samples ◽  
Promising Alternative ◽  
Detection And Identification ◽  
Particle Imaging ◽  
Single Particle Imaging

AbstractThe increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive viral diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in less than five minutes and does not require any lysis, purification or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses, with high accuracy. Single-particle imaging combined with deep learning offers a promising alternative to traditional viral diagnostic methods, and has the potential for significant impact.

scholarly journals Impact of the Engine Tuning on its Technical Condition Assessment Based on Limited Number of Available Parameters

2018 ◽  
Vol 1 (1) ◽  
pp. 721-728
Author(s):  
Marek Łutowicz
Keyword(s):  
Fuel Injection ◽  
Cooling Water ◽  
Technical Condition ◽  
Technical State ◽  
Injection Timing ◽  
Injection Equipment ◽  
Cooling Water Temperature ◽  
Exhaust Temperature ◽  
Marine Diesel ◽  
Engine Components

Abstract Due to the limited scope of the diagnostic equipment on the ship, the technical condition of the engine is based on the measurement of pressure and temperature at the available measuring points. Usually it is the exhaust temperature at the outlet of individual cylinders, supercharging pressure, oil temperature and cooling water temperature. Sometimes the bearing temperature and turbocharger speed are also measured. Normally, if the engine is adapted to this, the maximum combustion pressure is measured periodically although distorted through the channels with the indicator valves. The paper presents examples of the exploitation of marine diesel engines, where there is a discrepancy between the actual technical state of the engine and the technical state of the engine based on the traditional diagnostic method based on a limited set of available parameters. These discrepancies resulted, inter alia, from the regular fuel injection timing and fuel dose adjustment, so that the measured parameters were adequate to the actual load of the engine. This adjustment is justified, but leads to masking engine components wear symptoms. In this situation, it can only be stated that the state of the fuel injection equipment is suitable for the current technical state of the some engine components and does not provide a sufficient basis for the extension of the repair interval.

scholarly journals Definition of Set of diagnostic Parameters of System based on the Functional Spaces Theory

2019 ◽  
Vol 18 (4) ◽  
pp. 949-975 ◽  
Author(s):  
Valentin Senchenkov ◽  
Damir Absalyamov ◽  
Dmitriy Avsyukevich
Keyword(s):  
Fourier Series ◽  
Experimental Studies ◽  
Numerical Procedure ◽  
Physical Nature ◽  
Convergent Series ◽  
Technical Condition ◽  
Partial Sums ◽  
Diagnostic Tools ◽  
Diagnostic Parameters ◽  
Integrable Functions

The development of methodical and mathematical apparatus for formation of a set of diagnostic parameters of complex technical systems, the content of which consists of processing the trajectories of the output processes of the system using the theory of functional spaces, is  considered in this paper. The trajectories of the output variables are considered as Lebesgue measurable functions. It ensures a unified approach to obtaining diagnostic parameters regardless  a physical nature of these variables and a set of their jump-like changes (finite discontinuities of trajectories). It adequately takes into account a complexity of the construction, a variety of physical principles and algorithms of systems operation. A structure of factor-spaces of measurable square Lebesgue integrable functions, ( spaces) is defined on sets of trajectories. The properties of these spaces allow to decompose the trajectories by the countable set of mutually orthogonal directions and represent them in the form of a convergent series. The choice of a set of diagnostic parameters as an ordered sequence of coefficients of decomposition of trajectories into partial sums of Fourier series is substantiated. The procedure of formation of a set of diagnostic parameters of the system, improved in comparison with the initial variants, when the trajectory is decomposed into a partial sum of Fourier series by an orthonormal Legendre basis, is presented. A method for the numerical determination of the power of such a set is proposed. New aspects of obtaining diagnostic information from the vibration processes of the system are revealed. A structure of spaces of continuous square Riemann integrable functions ( spaces) is defined on the sets of vibrotrajectories. Since they are subspaces in the afore mentioned factor-spaces, the general methodological bases for the transformation of vibrotrajectories remain unchanged. However, the algorithmic component of the choice of diagnostic parameters becomes more specific and observable. It is demonstrated by implementing a numerical procedure for decomposing vibrotrajectories by an orthogonal trigonometric basis, which is contained in spaces. The processing of the results of experimental studies of the vibration process and the setting on this basis of a subset of diagnostic parameters in one of the control points of the system is provided. The materials of the article are a contribution to the theory of obtaining information about the technical condition of complex systems. The applied value of the proposed development is a possibility of their use for the synthesis of algorithmic support of automated diagnostic tools.

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