Complex Electromechanical System Research Articles

Manipulator trajectory tracking based on adaptive sliding mode control

AbstractA manipulator is a complex electromechanical system that is nonlinear, strongly coupled, and uncertain. Achieving its precise and high‐quality trajectory control is difficult. Sliding mode control (SMC) is one of the common control methods for manipulators. However, discontinuities in SMC can cause jitter and vibration in the manipulator system, leading to a reduction in the performance of the control system. For the self‐adaptive capability jitter vibration problem of SMC, the Dobot magician manipulator is treated as the research object in this article. The dynamics equations of the manipulator are established by Lagrange method, and a simplified model of the manipulator dynamics is constructed. The method of self‐adaptive sliding mode control is proposed. Self‐adaptive parameters are added to the SMC to achieve self‐adaptive adjustment of the SMC parameters. In the MATLAB/Simulink simulation environment analysis show that the self‐adaptive SMC method has better self‐tuning ability and trajectory tracking ability than the traditional SMC, and weakens the jitter phenomenon existing in the traditional SMC.

Heat supply of buildings with environmentally friendly sources using solar energy

Taking into account the fact that the volume of traditional fuel energy is not significant and limited, it is important for the present and future generation to introduce new progressive ideas concerning alternative changes in the fuel energy complex in the prism of environmental education. The issues of energy efficiency of alternative fuels in Ukraine is more acute than in the world. The reasons for this are outdated technologies, the exhaustion of resources, the use of fixed assets for electricity and heat generation, which together with low fuel efficiency leads to significant emissions of harmful substances. The use of solar energy in Ukraine will make it less dependent on fluctuations in fuel prices. It is known that, solar installations are often characterized by complex structures or low utilization of the useful space, require complex electro mechanical systems and guidance mechanisms. Currently, there are a significant number of solar collectors, different design and technical and economic indicators. Environmental friendliness and economic benefits of these systems remain the main issue during installation. Taking into account the scientific and technological progress that reduces the cost of energy obtained with the help of solar collectors, the improvement of structures that generate thermal and electrical energy remains an urgent issue today. The paper offers design solutions for improving the translucent facades of buildings, which today play an extremely important role in architectural and structural terms. Such a solution based on the use of solar energy is a solar collector integrated into the light transparent facade of the building, which will save space for its self-installation and allow generating consumer energy by the structure of the building. Theoretical formulas for constructing and calculating the energy characteristics of a solar power supply system are elucidated for the proposed design of a hybrid thermal and photovoltaic solar collector.

Моделирование процесса самозапуска электродвигателей собственных нужд атомной станции для его ускорения и минимизации различных возмущений

The article proposes a solution to the problem of accelerating the processes of self-starting of asynchronous electric motors of pumping equipment with the help of simulation computer modeling tools to reduce the negative impact on the power supply circuit of the auxiliary needs of a nuclear power plant. The features of the run-down transient processes and the interaction of machines of various capacities in the autonomous circuit that occurs after they are turned off, the subsequent transition to a backup power source, and the emerging effects during self-start are considered. It is shown that the most severe mode of such a transition occurs as a result of the operation of automatic switching on of the reserve and disconnection of working power sources by technological protections or actions of operational personnel at the operational level of operating voltage and nominal or close to it load sections. The analysis of emerging modes is carried out using models developed in the MatLab computer mathematics system with a built-in electrical application. The features of the processes of run-down and subsequent self-starting at various favorable and unfavorable moments of time and the magnitude of the mismatch between the voltages of the network and the resulting autonomous circuit are demonstrated. The models make it possible to obtain a reliable mathematical description of the electromagnetic and mechanical processes of motors in a complex electromechanical system of several motors, to measure the instantaneous voltage differences between the network and the run-down circuit, and to predict the optimal time to turn on the backup power source. The results of the studies carried out on the models are the development of recommendations on the technology for monitoring voltage and circuit mismatches for the same phases, the assessment of the root-mean-square deviation of these mismatches and the effective search for the moment of re-enabling the backup source to improve the technological modes of nuclear power plants.

Reliability Synthesis and Prediction for Complex Electromechanical System: A Case Study

The life test of a complex electromechanical system (CEMS) is restricted by many factors, such as test time, test cost, test environment, test site, and test conditions. It is difficult to realize system reliability synthesis and prediction of a CEMS which consists of units with different life distributions. Aiming at the problems, a numerical analysis method based on the computer simulation and the Monte Carlo (MC) method is proposed. First, the unit’s life simulation values are simulated using the MC method with the given each unit’s life distribution and its distribution parameter point estimation. Next, using the unit’s life simulation values, the CEMS life simulation value can be obtained based on the CEMS reliability model. A simulation test is realized instead of the life test of the CEMS when there are enough simulation values of the CEMS life. Then, simulation data are analyzed, and the distribution of the CEMS life is deduced. The goodness-of-fit test, point estimation and confidence interval of the parameters, and reliability measure are estimated. Finally, as a test example of the wind turbine, the practicability and effectiveness of the method proposed in this paper are verified.

SYNTHESIS OF THERMAL DIAGNOSTIC EXPERT COMPONENTS WITH AN ARTIFICIAL NEURON

The article analyzes the automation tools in which artificial neural networks are used. It has been considered examples of effective use of hardware solutions with software versions of artificial neurons and other components, which allow to expand the functional properties of automation, while lowering the requirements for used computing facilities. On the example of electric motors intelligent technical diagnostics, it has been noted the possibility of assessing the technical state of complex electromechanical systems. The purpose of this work was to develop algorithms for computing and logical cycles suitable for the synthesis of a thermal diagnostic expert with an artificial neural network capable of identifying expected faults in electromechanical equipment of any complexity. It has been proposed a modular structure of the neural network software, an algorithm for the rate of temperature change, an artificial neuron module and other components. Simulation modeling and hardware implementation of an artificial neuron confirmed the suitability of the proposed solutions for the implementation of a diagnostic thermal examination device. The use of experimental data in electronic components made it possible to obtain a calibration characteristic for its subsequent use in assessing the development trend of possible non-standardized thermal events that appear when malfunctions are activated in certain parts of the operating equipment. It has been given variants of diagnostic expertise and identification of thermal events, preceding possible faults in the elements of electromechanical devices. It has been considered real examples of the main user program synthesis, taking into account access to the necessary settings of the hardware and control parts of the diagnostic device. It has been presented the illustrations of changing interfaces, which visual advantages lead to increased perception of the provided and associated computational functional properties of the diagnostic device when operating by users without special training. The applied solutions and visual examples of experimental and simulation modeling of the developed components of a thermal diagnostic expert with an artificial neural network are presented in the work.

AI Supported Maintenance and Reliability System in Wind Energy Production

Now a days the technology is advancing at an unbelievable rate. To the point many of us aren’t able to efficiently keep up. With the ever- increasing sophistication of Artificial Intelligence [AI]. The environmental impact of the wind power is relatively minor when we compared to that of the fossil fuel power. When Compared to other low carbon sources, wind turbines have one of the lowest global warming potentials per unit of electricity energy generated per power sources. Among the renewable energy arts wind energy plays a significant role and, as forecasted its ratio within the total energy production will rapidly increase. Wind turbines are relatively complex electro-mechanical systems, their smooth functioning is an important economical factor. This is why the monitoring and diagnosis of wind turbines and wind farms gained extreme importance in the past years.

A failure tracing method with hierarchical digraph and meta action for complex electromechanical systems

AbstractAs an important method for analyzing the failure pervasion mechanism, failure tracing is a powerful tool for locating the failure causes in reliability analysis of complex electromechanical systems (EMS). However, most of the previous studies mainly focus on the failure tracing and identifying of part levels, which are often complicated. Besides, they cannot reflect the product feature that motion determines product function. To fill these gaps, this paper develops a combined dynamic and static failure tracing model based on meta action and hierarchy digraph model. First, the failure propagation directed digraph is constructed based on the structure of the EMS and the interactions of action signals, and the interpretative structural model (ISM) is further applied to obtain the hierarchy failure propagation model based on the directed digraph. Second, the combined dynamic and static failure propagation intensity between meta actions is measured based on the failure propagation probability and edge betweenness, which can effectively extract the crucial pathway and crucial meta actions to facilitate failure tracing. Third, a failure mode and effect analysis (FMEA) method considering the weights of risk elements and experts is proposed to estimate the risks of the crucial meta actions’ failure modes, which can help engineers develop countermeasures for preventing or eliminating failures. Finally, a case study and several comparisons are presented to illustrate the feasibility and benefits of the developed model.

Modeling and Simulation of the NC Feed System based on MATLAB / Simulink

Feed servo system often adopts the CNC system with the digital controller as the core. In such a computer control system, it involves both continuous signal processing and digital signal processing.The numerical control machine tool feed sampling control system is a more complex electromechanical control system, and has nonlinear characteristics, the mathematical model established is a higher-order model, through the simplified transfer to the second-order system model, to facilitate computer simulation operation, so that the numerical control machine tool static performance and dynamic performance parameters to meet the design requirements.

Indirect field-oriented control of twin-screw electromechanical hydrolyzer

Goal. Development of a mathematical model of indirect field-oriented control of a twin-screw electromechanical hydrolyzer. Methodology. The paper presents a mathematical model of Indirect field-oriented control of twin-screw electromechanical hydrolyzer. The mathematical model was developed in the MATLAB / Simulink software environment. The determination of the main parameters of a twin-screw electromechanical hydrolyzer was carried out by developing a finite element model in the Comsol Multiphysics software environment. Results. Based on the results of a mathematical study, graphical dependences of the distribution of magnetic induction in the air gap of a ferromagnetic rotor, a spatial representation of the distribution of magnetic induction on a 3D model of a ferromagnetic rotor of a twin-screw electromechanical hydrolyzer were obtained. The results of finite element modeling were confirmed by a practical study of a mock-up of a ferromagnetic rotor of a twin-screw electromechanical hydrolyzer. By implementing the MATLAB / Simulink model, graphical dependences of the parameters of the ferromagnetic rotor of a twin-screw electromechanical hydrolyzer are obtained under the condition of a stepwise change in the torque and a cyclic change in the angular velocity. Originality. The paper presents an implementation of the method of indirect field-oriented control for controlling the ferromagnetic rotor of a twin-screw electromechanical hydrolyzer. The work takes into account the complex design of the ferromagnetic rotor of a twin-screw electromechanical hydrolyzer. Practical significance. The practical implementation of the results of mathematical modeling makes it possible to achieve effective control of a complex electromechanical system, allows further research to maintain the necessary parameters of the technological process and to develop more complex intelligent control systems in the future.

Electric Circuit-Based Modeling and Analysis of the Translational, Rotational Mechanical and Electromechanical Systems Dynamics

To cope with the rapid development in technology, engineers are dealing with complex and heterogenous systems which composed of blocks that belong to different engineering fields such as electrical, mechanical, chemical, electromechanical, fluid, thermal etc. Mechanical and electrical systems are more often go hand to hand in many industrial systems. For system analyzing and designing purpose, engineers must model and simulate the systems to investigate problems and aim for the best performance before proceeding to the manufacturing stage. In the presence of complex mechanical system blocks, electrical and electronics engineers are often facing difficulties in modeling the mechanical blocks. Although similarity between individual mechanical and electrical elements is recognized since long time, but it has not drawn deserved attention for the use in the system level. In this paper, we investigate in great details how enabling electrical and electronics engineers to easily model and analyze complex mechanical and electromechanical systems through systematic approach. For this objective, thirteen rules are set, established, and elaborated on how to find the electrical circuit equivalent of a given mechanical or electromechanical system in order to be modelled and analyzed. The proposed approach is tested on both complex translational mechanical and electromechanical systems which includes a rotational mechanical system. Findings demonstrate that models generated by the equivalent of electric circuits are matching the models of existing mechanical and electromechanical system by 100%. The proposed systematic approach is promising and can be widely implemented in several industrial fields.

Electromechanical Coupling Dynamic Characteristics of Differential Speed Regulation System Considering Inverter Harmonics Under Variable Operating Conditions

The differential speed regulation system driven by inverters, motors and differential gear trains is a complex electromechanical system that achieves speed regulation and energy savings efficiently and economically. In this paper, the complete drive trains dynamic model of the differential speed regulation system with the inverter power supply-motor-differential gearbox-load is established. The inverter power supply considers constant voltage to frequency ratio control, sinusoidal pulse width modulation and inverter, the motors are modeled based on the equivalent circuit method, and the differential gear trains consider a lateral-torsional model with time-varying meshing stiffness and damping. The dynamic properties of the system are analyzed and compared with the variable frequency drive model considering inverter power supply and the direct drive model using ideal power supply under variable operation conditions. The results show that the variable frequency drive model varies more smoothly in the time domain and contains additional harmonic components in the frequency domain resulting from the coupling of the inverter triangle carrier frequency to the fundamental frequency of the power supply than the direct drive model. It also shows that the variable frequency drive model is a more realistic and rational model than the direct drive model. The complex coupling relationship can be seen in the inverter power supply-motor-differential gearbox-load system, where both inverter harmonics and mechanical meshing force harmonics are found in the dynamic response of the motor’s electromagnetic torque, rotor speed; the inverter harmonics are also reflected in the mechanical meshing force harmonics.

Multiparameter Optimization Framework of Cyberphysical Systems: A Case Study on Energy Saving of the Automotive Engine

Multiparameter optimization of complex electromechanical systems in a physical space is a challenging task. CPS (Cyberphysical system) technology can speed up the solution of the problem based on data interaction and collaborative optimization of physical space and cyberspace. This paper proposed a general multiparameter optimization framework by combining physical process simulation and clustering genetic algorithm for the CPS application. The utility of this approach is demonstrated in the instance of automobile engine energy-saving in this paper. A 1.8-L turbocharged GDI (gasoline direct injection) engine model was established and calibrated according to the test data and physical entity. A joint simulation program combining CGA (Clustering Genetic Algorithm) with the GDI engine simulation model was set up for the engine multiparameter optimization and performance prediction in cyberspace; then, the influential mechanism of multiple factors on engine energy-saving optimization was analyzed at 2000 RPM (Revolutions Per Minute) working condition. A multiparameter optimization with clustering genetic algorithm was introduced for multiparameter optimization among physical and digital data. The trade-off between fuel efficiency, dynamic performance, and knock risk was discussed. The results demonstrated the effectiveness of the proposed method and that it can contribute to develop a novel automotive engine control strategy in the future.

Система «турбина – генератор» с наблюдателем состояния нагрузки

Objective: To generate a mathematical model of a gas turbine engine state observer for a GT1h series gas turbine locomotive. Methods: Calculations and modeling of processes were performed using software packages for mathematical modeling of complex electromechanical systems with implementation in Matlab, while data processing and graph plotting were performed using Microsoft Excel. Results: It has been shown that the use of the mathematical model of the state observer in the automatic control system allows providing conditions for the formation of an optimal power load trajectory of the Gas Turbine Engine — Traction Generator system when regulating the power, taking into account the limitations associated with the physical processes occurring in the gas turbine engine. Practical importance: The use of the mathematical model of the state observer makes it possible to generate rational gas turbine load trajectories in the entire range of its use.

AI Supported Maintenance and Reliability System in Wind Energy Production

Technology is advancing at an unbelievable rate. To the point many of us are not able to efficiently keep up. With the ever-increasing sophistication of Artificial Intelligence [AI]. The environmental impact of wind power is relatively minor when compared to that of fossil fuel power. Compared with other low carbon sources, wind turbines have one of the lowest global warming potentials per unit of electricity energy generated per power sources. Among the renewable energy arts wind energy plays a significant role and, as forecasted its ratio within the total energy production will rapidly increase. Wind turbines are relatively complex electro-mechanical systems, their smooth functioning is an important economical factor. This is why monitoring and diagnosis of wind turbines and wind farms gained extreme importance in the past years.

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Combined propulsion plants get wide spread on modern ships of foreign construction, while in the domestic shipbuilding industry there is practically no experience in the design and testing of these vessels. A distinctive feature of the combined propulsion plants is that the energy for the vessel movement is generated in them in two (or more) different types of ship engines - thermal and electric, working on a common propulsion unit - a propeller. Combined propulsion plants are complex electromechanical systems designed to ensure the movement of the vessel and the production of electricity in the various modes of operation. Combined propulsion plants conjoin the advantages of traditional propulsion systems with heat main engines and electric propulsion plants. A unified electric power system with a combined plant of a work boat is discussed in the paper. The work boat is the first vessel built in the Russian Federation with this type of propulsion system. The feature the combined propulsion plant installed on the work boat is the ability to operate the propeller electric motor in both propulsion and generator modes. The ship uses diesel generators, storage batteries and electric propulsion motor in the generator mode as the sources of electricity. The main modes of the vessel operation, the results of dock and sea trials of the unified electric power system and combined propulsion plant are briefly discussed in the paper. During the trials, the autonomous mode of operation of each electric power source on the auxiliary electric propulsion plant and ship consumers has been checked successfully. New method of synchronization of diesel-generator and autonomous inverter has been realized; it has high speed and accuracy that excludes appearance of current shot when power source connects to the main switchboard.

Quantitative analysis of a process industry’s operating status of based on DCS data set

The process industry represented by energy chemical enterprise is a typical distributed and complex electromechanical system. Its distributed control system (DCS) records overall operating status information of a process industry. It is a challenge to quantitative operating status through analyzing DCS data set. This paper proposed a novel method to calculate fault score of system’s operating status by classifying its DCS data set and forming a classifier matrix. Firstly, define a classifier matrix depends on the baseline of the DCS data. Secondly, calculate the classifier matrix to obtain the fault score. The higher fault score means the lower security of the system. Last but not least, a period of the system operating status trend could be observed by plotting the fault score. A case study of a real chemical plant is introduced to verify the validation of the method.

Testability Modelling and Optimization Technology of Ship Electrical Equipment Based on Multi-Signal Flow Diagram

With the development of ship power systems, the degree of integration, complexity and automation of ship generators has increased significantly, which places higher requirements on its testability. The marine generator is a complex electromechanical system with multiple disciplines including electricity, magnetism, force, heat, and mechanics. Its main features include: various types of fault modes, a wide range of faults, and many types of fault features. Therefore, compared with electronic products, the testability modelling and optimization methods of marine generators are very different. First of all, this paper sorts out 11 typical failure modes of marine generators. Then, analyse the failure characteristics of each failure mode and set up 17 test points initially. Based on this, a multi-signal flow graph model is constructed, and the test point is optimized based on the correlation model. By comparing and analysing the test point optimization results, the feasibility and effectiveness of the proposed method are verified.

Health Status Assessment for LCESs Based on Multidiscounted Belief Rule Base

The emergence of large-scale engineering and macro engineering promotes the development of large-scale complex electromechanical systems (LCESs). The LCES complexity of structures and failure mechanisms makes it difficult to achieve the aim of health management and fault diagnosis of such systems. One of the reasons is lacking detailed consideration of various uncertainties from the process of system assessment. Belief rule base (BRB) shows advantages in modeling nonlinear complex systems under the uncertainty environment. However, the current BRB-based work only focuses on optimizing the initial parameters to deal with the impact of cognitive uncertainty, and issues, such as monitoring and environmental uncertainties, are not considered. Thus, this article proposes the multidiscounted BRB (MBRB) to evaluate the health status of LCESs. Different from traditional BRB, MBRB can reduce the negative influence of cognitive uncertainties on system assessment from another perspective, the so-called expert reliability discount model. In addition, monitoring and environmental uncertainties are also considered in MBRB modeling. Three uncertainties can be quantified by statistical models, and they can be integrated into MBRB by combining with evidence discount theory. Due to the treatment of these uncertainties, MBRB can provide accurate results. In comparison with traditional methods, the proposed method shows superior performance in the health assessment of high-speed trains.

An improved extension neural network methodology for fault diagnosis of complex electromechanical system

An improved extension neural network methodology for fault diagnosis of complex electromechanical system

An improved extension neural network methodology for fault diagnosis of complex electromechanical system

An improved extension neural network methodology for fault diagnosis of complex electromechanical system