Machine Subsystems Research Articles

Experimental Lab Tests on Rabbits for the Optimization and Redesign of Low-Cost Equipment for Automated Peritoneal Dialysis.

This work shows the experiences acquired by the experimental test performed to validate an automated peritoneal dialysis machine using rabbits with kidney damage to find improvements that can be made for future advances. These are listed to understand the direction of the development of the machine. The article shows the device's background and previous tests using a testbed. The rabbit anatomy was prepared for nephrectomy surgery. The tests were practiced by checking all of the APD machine's subsystems. The data were analyzed to develop improvements in the process. The results indicate the importance of the DPA machine as an alternative by implementing peristaltic pumps to substitute disposable cassettes. The identified improvements are the main objectives for research to continue improving the technology.

Instruments for On-line Monitoring of Transformers

The main objective of the paper is to describe the experience with newly developed monitoring system for transformers with oil-paper insulation system. From the view of operation reliability, it is necessary for operators to provide a monitoring of transformer’s failure free operation. The application of monitoring system enables to warn timely of the rising failure and also decrease of degradation of single subsystems of machine. When failure is detected, it is important to support this detection by other measurements that would lead to exact determination of the failure. SFRA analysis (Sweep Frequency Response Analysis) is such additional method in our monitoring.

On Subsystems of a Hybrid Finite State Machine

Humanity’s efforts are manifested in the creation of novel solutions to complex problems in diverse fields. Traditional mathematical methods fail to solve real-world problems due to their complexity. Researchers have come up with new mathematical theories like fuzzy set theory and rough set theory to help them figure out how to model the uncertainty in these fields. Soft set theory is a novel approach to real-world problem solving that does not require the membership function to be specified. This aids in the resolution of a wide range of issues, and significant progress has recently been made. After Jun et al. came up with a hybrid system that combined fuzzy and soft set concepts, many people came up with hybrid ideas in different algebraic structures. In this paper, we introduce the concepts of subsystem and strong subsystem of a hybrid finite state machine (HFSM) and investigate a portion of their significant properties. We also provide an example that shows that every subsystem does not need to be a strong subsystem. Additionally, we study the cyclic subsystem of HFSMs and also obtain their equivalent results and examples. Finally, we define the notions of homomorphism of subsystems and strong subsystems of HFSMs.

Analysing seafarer competencies in a dynamic human-machine system

Human factors have been deemed to affect a variety of unsafe acts and hazardous conditions, with no exceptions in the maritime sector. With increasing applications of automation techniques in shipping, seafarers’ roles are changing, and their competencies require to be assessed and assured for safety at sea accordingly. The studies on seafarer competencies have therefore been tightly bound with a human-machine system which consists of the interaction of seafarers and ship operational systems and sub-systems. To evaluate the seafarer competencies that fit automation systems in shipping, this paper aims to develop a new dynamic human-machine model in shipping that can be used to analyse human factors in a closed-loop system. Based on Crew Resource Management and the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers, it reflects the input, process, and output phases of the human system and its interactions with machine sub-systems. A new tool to analyse seafarer competencies is proposed to rationalise human factor evaluation in the maritime closed-loop system and reflect the dynamic human-machine cooperation process. Two case studies have been conducted to illustrate the feasibility of the new model and in the meantime to investigate seafarer competencies in the dynamic human-machine system. It produces a new human factor analysis tool to investigate maritime accidents. The results and policy implications help explore the adjustment of maritime training to support ship automation and provide guidance on risk management for traditional and autonomous ships.

Comprehensive assessment of the working efficiency of the destructive working element of the construction machine

The article uses approaches to the comparison of rock-crushing working bodies based on the use of complex indicators of the quality of construction machines used on construction sites. The use of such indicators is due to the need for constant improvement of existing equipment and the creation of new ones taking into account existing needs. Today, in Ukraine, there is a need for efficient implementation of construction works related to the laying of main pipelines. This, in turn, poses the task of determining the efficiency of performing mechanized earthworks during the laying of engineering networks. Complex indicators are grouped by characteristics. The first group includes indicators of classification, purpose, reliability, manufacturability, standardization and unification, patent law, aesthetics, ergonomics, safety. The second group consists of economic indicators. The third group is defined by indicators of competitiveness. Indicators of the 4th group and above evaluate the main groups of subsystems of machines or complexes of energy and technological purposes.
 The need to create competitive earthmoving equipment requires the use of modern constructive solutions and their objective comparison at the design stage. In the course of the study, earthmoving working bodies for laying engineering networks of the type "cone cutter" and "end working body" in the form of a disk were compared. A comparison of the nominal and oscillating modes of operation of the end working body is also proposed. Design features of the working body of the type "cone cutter" and "end working body" are described. The results are summarized in the form of tabular data.
 The proposed technical solutions open the possibility of variable use of rock-crushing work equipment of construction machines in accordance with the economic requirements and needs of the end user. The effectiveness of using the methods of comprehensive assessment of technical solutions lies in the possibility of their analysis by individual indicators, in combination, as well as when ranking the values of individual indicators according to significance.

ON THE REPRESENTATIVE SPACE PHASOR CONCEPT FROM THE DYNAMIC MODEL OF THE THREE-PHASE INDUCTION MACHINE

In the paper, based on the linear dynamic behavior models of the electrical and magnetic subsystems of the induction machine with three-phase symmetrical stator winding and polyphase rotor winding (cage type) in short circuit, the values ​​are represented, in the complex plane confused with the cross-sectional plane of the machine and the instantaneous polar angular positions of the amplitudes of the progressive (spinning) plane waves of the instantaneous resultant solenations of the machine windings, and correspondingly, the spatial phasors representative of the instantaneous electrical circuit scalar quantities of the stator phase windings and rotor equivalents of the machine are defined. The metric (length and orientation) of these representative spatial phasors allows their physical significance to be revealed.

MAINTENANCE, TESTING AND AUTOMATIC CONTROL OF THE CUP FILLING MASCHINE

Industrial automation of the production process is based on the fusion of a CNC machine and an industrial robot. The industry of today requires skilled professionals and educators. Special attention is to be paid to the testing of the components and system operation and the maintenance of the system. Robots and automation are omnipresent nowadays and have also taken a significant role in education. The research presented here aims to overhaul the scaled model of the cup-filling machine to make it operate fully automated. The parts and subsystems of the cup-filling machine are explained in detail and their operation was tested. The cup-filling machine is fully automated using a programmable logic controller (PLC) SIEMENS S7 300. The machine can recognize two cup sizes and fills both types without overspilling. Filled cups are transported over a conveyor belt and classified according to their sizes PLCs have mainly replaced relays in industrial automation, bearing in mind that this way, scale-up is much more feasible, and alteration of control is done in PLC program code. This also has contributed to better maintenance and operation verification.

Comparison of Plant Detection Performance of CNN-based Single-stage and Two-stage Models for Precision Agriculture

The fact that arable land is not increasing in proportion to the ever-increasing population will increase the need for food in the coming years. For this reason, it is necessary to increase the yield of crops to make optimum use of arable land. One of the most important reasons for the decrease in yield and quality of crops is weeds. Herbicides are generally preferred for weed management. Due to deficiencies in herbicide application methods, only 0.015-6% of herbicides reach their target. The use of herbicides, which is an important part of the agricultural system, is an issue that needs to be emphasized, considering the risk of residue and environmental damage. In parallel with the rapid development of electronic and computer technologies, artificial intelligence applications have had the opportunity to develop. In this context, the use of artificial intelligence for plant detection in the subsystems of herbicide application machines will contribute to the development of precision agriculture techniques. In this study, the plant detection performances of single-stage and two-stage Convolutional Neural Network (CNN)-based deep learning (DL) models are evaluated. In this context, a dataset was created by taking images of Zea mays, Rhaponticum repens (L.) Hidalgo, and Chenopodium album L. plants in agricultural lands in Konya. With this dataset, the training of the models was carried out by the transfer learning method. The evaluation metrics of the trained models were calculated using the error matrix. In addition, training time and prediction time were used as quantitative metrics in the evaluation of the models. The plant detection performance, training time, and prediction time of the models were 85%, 8 h, 1.21 s for SSD MobileNet v2 and 99%, 22 h, 2.32 s for Faster R-CNN Inception v2, respectively. According to these results, Faster R-CNN Inception v2 is outperform in terms of accuracy. However, in cases where training time and prediction time are important, the SSD MobileNet v2 model can be trained with more data to increase its accuracy.

Conceptual design of the ALIANCE-T mirror experiment

The paper describes the conceptual design of a small-scale experiment within the fusion neutron source project ALIANCE (Axisymmetric LInear Advanced Neutron sourCE). The experimental machine is an axially symmetric magnetic plasma trap with a high mirror ratio, which focuses on the physical and engineering problems of mirror-based gasdynamic neutron sources. The specific research topics covered include the magnetohydrodynamic (MHD) stability of plasmas with high mirror ratios, the operation of the electrodes used for plasma stabilization, and problems related to particle and energy transport. ALIANCE-T features superconducting mirror solenoids that enable it to reach mirror ratios of ∼100 and a helicon plasma source with a power of up to 25 kW installed directly in the confinement zone between the mirrors. The expected plasma parameters are estimated using a simple analytical model, which takes into account gasdynamic axial plasma losses, cross-field transport, and the interaction of the plasma with neutral gas. It is projected that the machine will simultaneously achieve a plasma density >1013 cm−3 and a temperature >10 eV in a continuous discharge lasting for 1–8 h. This paper gives a detailed description of the key machine subsystems and introduces the analytical model used for calculation of the plasma parameters.

Підвищення ефективності використання транспортних машин у агропромисловому виробництві узгодженням їх експлуатаційних характеристик та умов функціонування

This paper examines the issue of increasing the efficiency of the use of transport vehicles in agro-industrial production by harmonizing their operational characteristics and operating conditions. The approach of matching the operational characteristics of machines with the conditions of operation is proposed, which is based on structural and simulation models of the "transport machine-conditions of its operation" system. An iterative solution of the simulation model with the search for optimal parameters is proposed. The specific fuel consumption for carrying out transport work is taken as an integral criterion for the efficiency of the use of a transport vehicle at an agro-industrial production enterprise. The specificity of the operating conditions of transport vehicles is proposed to be characterized by the consistency coefficient, which reflects the influence of operating conditions on the specific fuel consumption during transport operations. This coefficient takes into account the influence of the characteristics of the engine, cargo and external load. the corresponding system of equations is given as a mathematical model, which was supplemented with auxiliary dependencies that determine the boundary conditions of the operation of individual subsystems of transport machines, their control conditions and transitions of the model from a dynamic state based on a simulation model, the characteristics of machines and their structural elements in time are calculated for cases of partial high-speed and loading modes and transitions between them. Matching the characteristics of transport vehicles with the operating conditions, justifying their optimal design parameters, was carried out by selecting the transmission parameters, which ensure the improvement of conditions by partial damping of load fluctuations. The results of the parameters of the damping assembly of the transmission of the KamAZ-4308 car for different driving modes are presented. For these conditions, basic, theoretical, and experimental evaluations of the consistency coefficient were carried out, as well as recommended driving modes of transport vehicles when removing grain from the КамАЗ-4308 combine for cars and МТЗ-82+2ПТС4 tractor units.

Reliability, Availability, Maintainability, and Safety Analysis of Finger Joint Fu-King Furnimate Machine in Wood Manufacturing Industry

The objective of this research was to investigate the performance of the Finger Joint Fu-King Furnimate machine, especially for the most critical component of this machine. Based on historical data of machine damage, the Finger Joint Fu-King Furnimate is the machine that has the highest-level frequency of damage. Reliability, Availability, Maintainability, and Safety (RAMS) methods are proposed to analyze the machine's historical data. The result shows that the reliability of machine performance at t = 160 hours is only 27.42%, but the availability of machines is quite high, which passed the standard of 95%. Meanwhile, the maintainability of the machine is relatively fast, which the repair time of its critical component is 8 hours. The low-reliability critical machine spare part affected the safety of the spare part which the Safety Integrity Level (SIL) in the lowest standard (level 1). In general, the novelty of this research is to combine the application of the RAM method as the basis for analyzing machine performance with a safety analysis of the selected critical machine subsystems.

Energy Consumption Model for pulse-laser Selective Laser Melting

As a widely used additive manufacturing (AM) technology, the selective laser melting (SLM) technology shows great potential for the sustainable development. Therefore, it is essential to conduct an accurate prediction of the AM energy consumption. In this paper, a new prediction method of SLM energy consumption is proposed. Through analysing the working states of each machine subsystem, this method established an energy consumption prediction model concerning the exposure time, point distance, laser power, and hatch spacing based on the characteristics of the pulse-laser-SLM machine. The model contributes to the improvement and optimization of the energy consumption prediction accuracy in the printing stage.

Research on Safety Level Evaluation of Island-type Petrochemical Park Based on ANP

The inherent dangers of the petrochemical industry and the extreme meteorological conditions in the coastal areas make the island-type petrochemical parks have complicated safety hazards. In order to improve the safety management capability of my country’s island-type petrochemical parks, this paper analyzes the risk sources of the island-type petrochemical parks from the four subsystems of human, machine, environment and management, and uses the network analytic hierarchy process (ANP) to calculate the correlation weights between the indicators. The establishment of an evaluation model for the safety level of island-type petrochemical parks and quantitative analysis of the safety level of island-type petrochemical parks are of great significance for guiding the safety work of my country’s island-type petrochemical parks.

Neural decoding on imbalanced calcium imaging data with a network of support vector machines

We present a novel neural decoding system for calcium imaging data. Miniature calcium imaging is of great utility for examining population neural activity of animals. Our neural decoding system is developed using a carefully designed support vector machine subsystem together with dataflow-based techniques for system design, which capture the high-level structure of the application and enable powerful system-level analysis and optimization. Also, we introduce a framework for handling imbalanced data. This addresses a problem of imbalanced datasets, which arises commonly in neural decoding applications, as well as in a wide variety of other applications in biomedical engineering and advanced robotics. We developed an ensemble learning-based method to tackle this problem. The proposed framework systemically incorporates two heterogeneous model characteristics into a combined model. Through extensive experiments, we evaluate the proposed system using calcium imaging datasets in which neural activities of D1 medium spiny neurons in the dorsal striatum were recorded. The results show that the score of the proposed system is significantly better than those of previously developed neural decoding systems for calcium imaging.

Trends in the Development of Biotechnical Systems in Animal Husbandry

The concept of biotechnical systems belongs to the class of human-machine systems or human–machine–plant systems, human–machine–animal systems. The latter relate to agriculture and the livestock industry. In agricultural production, biotechnical systems have the properties of bimodality, when there are two or more biological objects, a person as a managing operator and a service object (plants, animals).(Research purpose) The research purpose is in analyzing trends in the development of biomachine and technical systems in order to further intellectualize and digitalize agricultural production.(Materials and methods) There are two approaches in the study of human-machine systems: anthropocentric and machine-centric; the first one assigns a crucial role to the person, the second one – to the machine.(Results and discussion) The article presents the functionality of the Human and Machine subsystems. Part of the functions of the Human operator will gradually be transferred to the Machine, and the Human operator will be transformed into a human Expert and a human User. The article presents a scheme for an intelligent biotechnical system in animal husbandry, and determines the coefficients of adaptation of local automated and robotic biotechnical systems to biological objects. Authors have created a scheme for the functioning of local biotechnical systems in a partially autonomous multi-agent control mode, and identifies criteria for evaluating the functioning of local biotechnical systems.(Conclusions) We need to strengthen the Machine factor on the basis of developing machine-centric models and convert complex three-tier system of biotech in animal husbandry in two-tier with the polarization of the human Expert, human User and Machine–Animal subsystems. The latter absorbs more and more intelligent functions that are passed by a Man, for which it retained control, coordination and management of the entire system.

Identification of the Wear Margin of a Pipeline–Machine Subsystem

The quality of company asset management is significantly dependent on the quality of a system for asset wear margin identification. A pipeline–machine subsystem may be an essential part of assets in many production companies. It is necessary to build models of pipeline–machine subsystems and models of a system for the identification of subsystem wear margin. The method used consists of a decomposition of desired characteristics of an enterprise into desired characteristics of a pipeline–machine subsystem. Methods for the identification of real characteristics of a subsystem depend on the character of subsystem operation. In this study, hydrodynamic and thermodynamic models of the subsystem are built. Tests are conducted on industrial and laboratory objects. The boundaries of the subsystem are defined and changes in pressure, temperature and mass flow rate in the pipeline are presented. Causes of changes in the mentioned quantities are described. Desired characteristics of the subsystem resulting from decomposition are described. The presented methods of determining efficiency for steady working conditions and open flow use hydrodynamic and thermodynamic models. Energy efficiency of the subsystem is decomposed into efficiencies of main elements of the subsystem. A method is proposed for determining the subsystem’s energy efficiency in the case of the flow into a closed vessel. It is possible to determine the hydraulic efficiency of the subsystem components: the suction pipe, the discharge pipe and the machine. The efficiency of the machine determined by the hydrodynamic method is complementary to the efficiency obtained by the thermodynamic method. The machine set efficiency is composed of hydraulic efficiency of the machine; mechanical efficiency of the machine, the gearbox and motor; and electric efficiency of the motor. Hydraulic efficiency of the pipeline is related to substitute measure of wear margin—the coefficient of resistance. Pressure drop is a diagnostic symptom. Thermal efficiency of the heat exchanger is related to a substitute measure of wear margin—the coefficient of heat penetration. Temperatures and mass flow rate in the heat exchanger are diagnostic symptoms. It is possible to determine the capacity and efficiency of subsystems with one side closed—such as those filling hydrophore and gas vessels.

A novel method to forecast energy consumption of selective laser melting processes

As a promising additive manufacturing (AM) technology, the applications of selective laser melting (SLM) are expanding. Yet, due to the complex structure of SLM machines and low processing rates, the SLM process is highly energy-intensive. Energy forecasting is crucial for accurate evaluation and reduction of SLM energy consumption. However, due to the diversity of SLM machines and their various operating states, the energy consumption of SLM processes is difficult to predict. This article presents a novel method to forecast the energy consumption of SLM processes. The proposed approach is based on the power modelling of machine subsystems and the temporal modelling of sub-processes. Through identifying the working statuses of subsystems of SLM machines in each sub-process, forecast accuracy can be greatly improved. Two cases of aluminium components fabricated by an SLM process using an SLM 280HL facility are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method outperforms specific, stage-based and subsystem-based energy benchmark models in energy consumption forecasting.

КОНТРОЛЬ И УПРАВЛЕНИЕ ПОДСИСТЕМОЙ «ЖИВОТНОЕ» В СЛОЖНОЙ БИОТЕХНИЧЕСКОЙ СИСТЕМЕ «ЧЕЛОВЕК-МАШИНА-ЖИВОТНОЕ» МОЛОЧНОЙ ФЕРМЫ

A modern dairy farm is a complex biotechnical “man-machine-animal” system, where purposeful human activity concentrates mainly on the control of the “machine” and “animal” subsystems, thus making the whole system ergatic. Increasing the interaction effi ciency of machine subsystems with biological objects (animals) requires an in-depth study of the properties and characteristics of the latter, their behavior, adaptive and refl ex mechanisms that ensure the mutual adaptation of machine and biological subsystems. The paper considers general functionality of the “animal” subsystem, which includes lists of monitored parameters (functions) in pre-weaning, pre-lactation and lactation periods. In a similar way, functionals of the subsystems of the general musculoskeletal development of the animal’s body, respiratory and digestive organs, comfort of the habitat, development and control of the reproductive organs of lactating cows were obtained accompanied with a list of controlled functions and parameters. To carry out a set of research activities in this fi eld, FSAC VIM is planning to carry out a complex project that will increase the levels of automation, digitalization and intellectualization of animal husbandry, provide for comfortable environment, optimal rediced-impact service modes for animals and their extended productive longevity, increased quality of milk and autonomous functioning of individual local biotechnical subsystems.

Brittleness Risk Evaluation of Mine Safety Based on Brittle Relational Entropy

Mineral extracting involves lots of uncertain factors which take on the typically nonlinear characteristics. To find out the accidents caused by main factors and make clear of disaster-causing factors and risk sources, a modified risk evaluation model-associated interaction effect analysis method was constructed from four aspects of man subsystem, machine subsystem, working environment subsystem, and operations management subsystem. With this model, the theory of brittleness relation was applied to analyze closely the connection between mine safety and various subsystems and their interaction effects on mine safety. Furthermore, brittleness factors were also proposed according to the characteristics of underground mining. Finally, based on data from working fields and investigation results, taking a typical mine as an example, the analysis was carried out. The results show that their entropies of brittle relation were equal to 0.006 ± 0.201 i, −0.012 ± 0.221 i, 0.142 ± 0.237 i, and 0.041 ± 0.202 i, respectively. More exactly speaking, the main brittleness influenced on its safety is the environment subsystem in the mine. Therefore, the key to controlling mine accidents is to introduce advanced equipment and improve mechanization level to reach the intrinsic safety of the mining enterprise. The research proves that the modified risk analysis model based on brittleness relation theory is an effective approach to making clear of the state of mine safety and keeping accidents away in time by taking corresponding measures.

Modeling and Simulation Approaches for Reliability Analysis of Drilling Machines

Drilling, as the initial stage of exploitation in open-pit mining, has a significant effect on subsequent mining stages. Any failure in a drilling machine stops the drilling operation and, as a result, all following operational phases come to a halt. The drilling system is the most important part of the drilling operation. This study selected two new rotary-type drilling machines (A and B) in Sarcheshmeh Copper Mine in Iran as a case study to perform a reliability and availability analysis of their drilling systems. The drilling system was divided into three independent subsystems; drill string, rotary head, and mast. The reliability modeling used a reliability block diagram and Monte Carlo simulation. Reliability and availability were evaluated, and the importance of each subsystem estimated. A preventive maintenance schedule was proposed using weighed reliability allocation to achieve the reliability target. The results show the mast is the most reliable subsystem. Importance measure analysis indicates the drill string and rotary head are the most critical subsystems of machines A and B, respectively. Finally, under the proposed maintenance policy, the reliability of the drilling systems of machines A and B is improved.