The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.B...The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.Based on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring instruments.The technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.展开更多
The COVID-19 pandemic has exposed vulnerabilities within our healthcare structures. Healthcare facilities are often faced with staff shortages and work overloads, which can have an impact on the collection of health d...The COVID-19 pandemic has exposed vulnerabilities within our healthcare structures. Healthcare facilities are often faced with staff shortages and work overloads, which can have an impact on the collection of health data and constants essential for early diagnosis. In order to minimize the risk of error and optimize data collection, we have developed a robot incorporating artificial intelligence. This robot has been designed to automate and collect health data and constants in a contactless way, while at the same time verifying the conditions for correct measurements, such as the absence of hats and shoes. Furthermore, this health information needs to be transmitted to services for processing. Thus, this article addresses the aspect of reception and collection of health data and constants through various modules: for taking height, temperature and weight, as well as the module for entering patient identification data. The article also deals with orientation, presenting a module for selecting the patient’s destination department. This data is then routed via a wireless network and an application integrated into the doctors’ tablets. This application will enable efficient queue management by classifying patients according to their order of arrival. The system’s infrastructure is easily deployable, taking advantage of the healthcare facility’s local wireless network, and includes encryption mechanisms to reinforce the security of data circulating over the network. In short, this innovative system will offer an autonomous, contactless method for collecting vital constants such as size, mass, and temperature. What’s more, it will facilitate the flow of data, including identification information, across a network, simplifying the implementation of this solution within healthcare facilities.展开更多
Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineeri...Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.展开更多
In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propag...In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).展开更多
To compensate for the limitations of previous studies,a complex network-based method is developed for determining importance measures,which combines the functional roles of the components of a mechatronic system and t...To compensate for the limitations of previous studies,a complex network-based method is developed for determining importance measures,which combines the functional roles of the components of a mechatronic system and their topological positions.First,the dependencies among the components are well-represented and well-calculated.Second,a mechatronic system is modeled as a weighted and directional functional dependency network(FDN),in which the node weights are determined by the functional roles of components in the system and their topological positions in the complex network whereas the edge weights are represented by dependency strengths.Third,given that the PageRank algorithm cannot calculate the dependency strengths among components,an improved PageRank importance measure(IPIM)algorithm is proposed,which combines the node weights and edge weights of complex networks.IPIM also considers the importance of neighboring components.Finally,a case study is conducted to investigate the accuracy of the proposed method.Results show that the method can effectively determine the importance measures of components.展开更多
The dynamic parameters of a roller rig vary as the adhesion level changes.The change in dynamics parameters needs to be analysed to estimate the adhesion level.One of these parameters is noise emanating from wheel–ra...The dynamic parameters of a roller rig vary as the adhesion level changes.The change in dynamics parameters needs to be analysed to estimate the adhesion level.One of these parameters is noise emanating from wheel–rail interaction.Most previous wheel–rail noise analysis has been conducted to mitigate those noises.However,in this paper,the noise is analysed to estimate the adhesion condition at the wheel–rail contact interface in combination with the other methodologies applied for this purpose.The adhesion level changes with changes in operational and environmental factors.To accurately estimate the adhesion level,the influence of those factors is included in this study.The testing and verification of the methodology required an accurate test prototype of the roller rig.In general,such testing and verification involve complex experimental works required by the intricate nature of the adhesion process and the integration of the different subsystems(i.e.controller,traction,braking).To this end,a new reduced-scale roller rig is developed to study the adhesion between wheel and rail roller contact.The various stages involved in the development of such a complex mechatronics system are described in this paper.Furthermore,the proposed brake control system was validated using the test rig under various adhesion conditions.The results indicate that the proposed brake controller has achieved a shorter stopping distance as compared to the conventional brake controller,and the brake control algorithm was able to maintain the operational condition even at the abrupt changes in adhesion condition.展开更多
A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current defin...A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current definition of a mechatronic system.The focus of the present paper is the optimal matching of sensors with other hardware in the system.Sensor matching may be based on several concepts such as the operating frequency range(operating bandwidth),speed of response(and the corresponding rate of data sampling in digital conversion),the device sensitivity(or gain or data amplification),and the effect of component acc uracy on the overall accuracy of the system.The present paper explores all these concepts and presents suit able approaches for sensor matching through those criteria.The relevant procedures are illustrated using case studies.展开更多
This paper deals with instrumenting a mechatronic system,through the incorporation of suitable sensors,actuators,and other required hardware.Sensors(e.g.,semiconductor strain gauges,tachometers,RTD temperature sensors...This paper deals with instrumenting a mechatronic system,through the incorporation of suitable sensors,actuators,and other required hardware.Sensors(e.g.,semiconductor strain gauges,tachometers,RTD temperature sensors,cameras,piezoelectric accelerometers)are needed to measure(sense)unknown signals and parameters of a system and its environment.The information acquired in this manner is useful in operating or controlling the system,and also in process monitoring;experimental modeling(i.e.,model identification);product testing and qualification;product quality assessment;fault prediction,detection and diagnosis;warning generation;surveillance,and so on.Actuators(e.g.,stepper motors,solenoids,dc motors,hydraulic rams,pumps,heaters/coolers)are needed to"drive"a plant.Control actuators(e.g.,control valves)perform control actions,and in particular they drive control devices.Micro-electromechanical systems(MEMS)use microminiature sensors and actuators.MEMS sensors commonly use piezoelectric,capacitive,electromagnetic and piezoresistive principles.MEMS devices provide the benefits of small size and light weight(negligible loading errors),high speed(high bandwidth),and convenient mass-production(low cost).The process of instrumentation involves the identification of proper sensors,actuators,controllers,signal modification/interface hardware,and software with respect to their functions,operation,parameters,ratings,interaction with each other,so as to achieve the performance requirements of the overall system,and interfacing/integration/tuning of the selected devices into the system,for a given application.This paper presents the key steps of instrumenting a mechatronic system,in a somewhat general and systematic manner.Examples are described to illustrate several key procedures of instrumentation.展开更多
Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall...Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist them.The rehabilitation and occupational therapy equipments utilize the electromyography(EMG)signals to measure the muscle activity potential.This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the system.Limb characteristics extraction from EMG signal and prediction of optimal controller parameters are modeled.Time and frequency based approach of EMG signal are considered for feature extraction.The models used for estimating motion and muscle parameters from EMG signal for carrying out limb movement predictions are validated.Based on the extracted features,optimal parameters are selected by Modified Lion Optimization(MLO)for controlling the HAM system.Finally,supervised machine learning makes predictions at different points in time for individual sensing using Support Vector Neural Network(SVNN).This model is also evaluated based on optimal parameters of motion estimation and the accuracy level along with different optimization models for various upper limb movements.The proposed model of human adaptive controller predicts the limb movement by 96%accuracy.展开更多
The paper briefly addresses DLR' s ( German Aerospace Center) expertise in space robotics by handof corresponding milestone projects including systems on the International Space Station ISS. It then discussesthe k...The paper briefly addresses DLR' s ( German Aerospace Center) expertise in space robotics by handof corresponding milestone projects including systems on the International Space Station ISS. It then discussesthe key technologies needed for the development of an artificial "robonaut" generation with mechatronic ultra-light weight arms and multifingered hands. The third arm generation is nearly finished now, approaching thelimits of what is technologically achievable today with respect to light-weight and power losses. In a similar wayDLR' s second generation of artificial 4-fingered hands was a big step towards higher reliability, manipulabilityand overall performance.展开更多
The conceptual design of mechatronic systems is addressed under the thrust of concurrent engineering and an enhanced conceptual design methodology describing the early design stage of mechatronic systems is presented ...The conceptual design of mechatronic systems is addressed under the thrust of concurrent engineering and an enhanced conceptual design methodology describing the early design stage of mechatronic systems is presented through an example illustration of a pick and place robot.This methodology treats each feasible solution as a solution strategy.In the methodology,Quality Function Deployment(QFD)is used as a baseline for the analysis of the mapping from customers to engineering requirements,Axiomatic Design(AD)is adopted as a guideline to generate feasible,good design solution alternatives,and Theory of Inventive Problem Solving(TRIZ)is applied to deal with domain conflicts in design.展开更多
IoT is considered as one of the key enabling technologies for the fourth industrial revolution that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system comp...IoT is considered as one of the key enabling technologies for the fourth industrial revolution that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system composition hierarchy that tightly integrates mechanics with the electronics and software required to convert the mechanics to intelligent (smart) object offering well defined services to its environment. For this mechatronic component to be integrated in the IoT-based industrial automation environment, a software layer is required on top of it to convert its conventional interface to an IoT compliant one. This layer, which we call IoT wrapper, transforms the conventional mechatronic component to an Industrial Automation Thing (IAT). The IAT is the key element of an IoT model specifically developed in the context of this work for the manufacturing domain. The model is compared to existing IoT models and its main differences are discussed. A model-to-model transformer is presented to automatically transform the legacy mechatronic component to an IAT ready to be integrated in the IoT-based industrial automation environment. The UML4IoT profile is used in the form of a Domain Specific Modelling Language to automate this transformation. A prototype implementation of an Industrial Automation Thing using C and the Contiki operating system demonstrates the effectiveness of the proposed approach.展开更多
Software is becoming the driving force in today’s mechatronic systems. It does not only realize a significant part of their functionality but it is also used to realize their most competitive advantages. However, the...Software is becoming the driving force in today’s mechatronic systems. It does not only realize a significant part of their functionality but it is also used to realize their most competitive advantages. However, the traditional development process is wholly inappropriate for the development of these systems that impose a tighter coupling of software with electronics and mechanics. In this paper, a synergistic integration of the constituent parts of mechatronic systems, i.e. mechanical, electronic and software is proposed though the 3+1 SysML view-model. SysML is used to specify the cen-tral view-model of the mechatronic system while the other three views are for the different disciplines involved. The widely used in software engineering V-model is extended to address the requirements set by the 3+1 SysML view-model and the Model Integrated Mechatronics (MIM) paradigm. A SysML profile is described to facilitate the application of the proposed view-model in the development of mechatronic systems.展开更多
Middle Tennessee State University(MTSU)started a Mechatronics Engineering program four years ago.Over those four years,enrollment has grown exponentially and has increased to over 400 students.One major factor that dr...Middle Tennessee State University(MTSU)started a Mechatronics Engineering program four years ago.Over those four years,enrollment has grown exponentially and has increased to over 400 students.One major factor that draws interest to this new program is the university’s Experimental Vehicles Program(EVP),created by Dr.Saeed Foroudastan.The EVP includes different student teams that work to design and build the four projects the EVP has evolved to:human-powered lunar rover(formerly known as The Great Moonbuggy Race),powered off-road Baja,gasoline-powered formula car,and all-electric solar boat.These projects are designed to greatly enhance each student’s classroom experience.The EVP provides students hands-on experience that allows them to apply what they have learned in the classroom to something in real life.The students are responsible for designing and building each project with their team,which also provides them with skills like effective communication,teamwork,project management and more.Each project also has a competition that members of the team normally travel to and are able to compete on an international level.The Mechatronics Engineering program and the EVP at MTSU are both providing truly great opportunities and preparing students well that wish to enter the engineering field after college.展开更多
The development of modern science and technology has promoted the overlapping and mutual penetration among different disciplines, which led to the technological innovations in the field of mechanical engineering. The ...The development of modern science and technology has promoted the overlapping and mutual penetration among different disciplines, which led to the technological innovations in the field of mechanical engineering. The mechatronics technology conforms to the law of development of science and technology in today, and combines the mechanical technology and electronic technology together to integrate the logistics, energy flow and information flow. This paper briefly describes the concept of mechatronics and the elements of mechatronics technology, and elaborates on the application of mechatronics technology in three different areas of the Machinery Industry in the form of living examples, finally introduces the future developing direction of mechatronics technology.展开更多
The presented work will show the highest relevance of solving all the issues related to this problem and present the results of the analysis of the main expected potential problems,which may occur in the implementatio...The presented work will show the highest relevance of solving all the issues related to this problem and present the results of the analysis of the main expected potential problems,which may occur in the implementation of the INDUSTRY-4.0 reform.It is proved that the pace and level of development of this reform will be determined to a large extent by the effectiveness of the individual nodes used and the entire mechatronic system.It has also been established that as a result of systematic miniaturization of the nodes of radio-electronic equipment and microelectronic equipment and microelectronic technology,the main problem of these reforms and the implementation of complex technological processes is instrumental and technological support,especially with cutting micro-tools and equipment.Therefore,on the example of these investigations,methods for improving their performance are shown.展开更多
An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.Th...An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.展开更多
The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in th...The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in the multi-physics sense,but involves other physical domains such as fluid and thermal.This paper summarizes the mechatronic approach to modeling.Linear graphs facilitate the development of state-space models of mechatronic systems,through this approach.The use of linear graphs in mechatronic modeling is outlined and an illustrative example of sound system modeling is given.Both time-domain and frequency-domain approaches are presented for the use of linear graphs.A mechatronic model of a multi-physics system may be simplified by converting all the physical domains into an equivalent single-domain system that is entirely in the output domain of the system.This approach of converting(transforming)physical domains is presented.An illustrative example of a pressure-controlled hydraulic actuator system that operates a mechanical load is given.展开更多
Health facilities are generally short-staffed and overworked. This has a significant impact on the reliability of the acquisition of health constants required at the start of diagnosis. Manual acquisition and transmis...Health facilities are generally short-staffed and overworked. This has a significant impact on the reliability of the acquisition of health constants required at the start of diagnosis. Manual acquisition and transmission of these constants and other data leads to delays in the execution of successive care-related tasks. What’s more, the quality of service is sometimes compromised by a lack of communication between patients and staff. In pediatrics, this is compounded by the difficulty of diagnosis in the face of children’s silence, intimidated by the hospital environment. Technological assistance would relieve healthcare staff of the need to perform certain repetitive tasks. The solution proposed in this document studies a robot, based on electrical, electronic, computer and artificial intelligence resources, with human-machine interaction for taking vitals and health data in health facilities. This system enables height, mass and temperature to be taken autonomously and without contact. The algorithm we’ve developed uses artificial intelligence to check the conditions for correct measurements, both bareheaded and barefoot. This solution also alerts you to epidemic trends such as obesity. This health data is made available in the healthcare facility on terminals such as tablets, smartphones and computers used by nursing staff. This work will help healthcare staff to take automatic health vitals without contact, and to acquire and circulate data via a computer network.展开更多
基金supported by National Natural Science Foundation of China(No.51275052)Beijing Natural Science Foundation(No.3131002)
文摘The safety and reliability of mechatronics systems,particularly the high-end,large and key mechatronics equipment in service,can strongly influence on production efficiency,personnel safety,resources and environment.Based on the demands of development of modern industries and technologies such as international industry 4.0,Made-in-China 2025 and Internet + and so on,this paper started from revealing the regularity of evolution of running state of equipment and the methods of signal processing of low signal noise ratio,proposed the key information technology of state monitoring and earlyfault-warning for equipment,put forward the typical technical line and major technical content,introduced the application of the technology to realize modern predictive maintenance of equipment and introduced the development of relevant safety monitoring instruments.The technology will play an important role in ensuring the safety of equipment in service,preventing accidents and realizing scientific maintenance.
文摘The COVID-19 pandemic has exposed vulnerabilities within our healthcare structures. Healthcare facilities are often faced with staff shortages and work overloads, which can have an impact on the collection of health data and constants essential for early diagnosis. In order to minimize the risk of error and optimize data collection, we have developed a robot incorporating artificial intelligence. This robot has been designed to automate and collect health data and constants in a contactless way, while at the same time verifying the conditions for correct measurements, such as the absence of hats and shoes. Furthermore, this health information needs to be transmitted to services for processing. Thus, this article addresses the aspect of reception and collection of health data and constants through various modules: for taking height, temperature and weight, as well as the module for entering patient identification data. The article also deals with orientation, presenting a module for selecting the patient’s destination department. This data is then routed via a wireless network and an application integrated into the doctors’ tablets. This application will enable efficient queue management by classifying patients according to their order of arrival. The system’s infrastructure is easily deployable, taking advantage of the healthcare facility’s local wireless network, and includes encryption mechanisms to reinforce the security of data circulating over the network. In short, this innovative system will offer an autonomous, contactless method for collecting vital constants such as size, mass, and temperature. What’s more, it will facilitate the flow of data, including identification information, across a network, simplifying the implementation of this solution within healthcare facilities.
文摘Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.
基金Project(2017JBZ103)supported by the Fundamental Research Funds for the Central Universities,China
文摘In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).
基金The National Natural Science Foundation of China(No.51875429)General Program of Shenzhen Natural Science Foundation(No.JCYJ20190809142805521)Wenzhou Major Program of Scientific and Technological Innovation(No.ZG2021021).
文摘To compensate for the limitations of previous studies,a complex network-based method is developed for determining importance measures,which combines the functional roles of the components of a mechatronic system and their topological positions.First,the dependencies among the components are well-represented and well-calculated.Second,a mechatronic system is modeled as a weighted and directional functional dependency network(FDN),in which the node weights are determined by the functional roles of components in the system and their topological positions in the complex network whereas the edge weights are represented by dependency strengths.Third,given that the PageRank algorithm cannot calculate the dependency strengths among components,an improved PageRank importance measure(IPIM)algorithm is proposed,which combines the node weights and edge weights of complex networks.IPIM also considers the importance of neighboring components.Finally,a case study is conducted to investigate the accuracy of the proposed method.Results show that the method can effectively determine the importance measures of components.
基金The authors greatly appreciate the financial support from the Rail Manufacturing Cooperative Research Centre(funded jointly by participating rail organisations and the Australian Federal Government’s Business Cooperative Research Centres Programme)through Project R1.7.1–“Estimation of adhesion conditions between wheels and rails for the development of advanced braking control systems”.
文摘The dynamic parameters of a roller rig vary as the adhesion level changes.The change in dynamics parameters needs to be analysed to estimate the adhesion level.One of these parameters is noise emanating from wheel–rail interaction.Most previous wheel–rail noise analysis has been conducted to mitigate those noises.However,in this paper,the noise is analysed to estimate the adhesion condition at the wheel–rail contact interface in combination with the other methodologies applied for this purpose.The adhesion level changes with changes in operational and environmental factors.To accurately estimate the adhesion level,the influence of those factors is included in this study.The testing and verification of the methodology required an accurate test prototype of the roller rig.In general,such testing and verification involve complex experimental works required by the intricate nature of the adhesion process and the integration of the different subsystems(i.e.controller,traction,braking).To this end,a new reduced-scale roller rig is developed to study the adhesion between wheel and rail roller contact.The various stages involved in the development of such a complex mechatronics system are described in this paper.Furthermore,the proposed brake control system was validated using the test rig under various adhesion conditions.The results indicate that the proposed brake controller has achieved a shorter stopping distance as compared to the conventional brake controller,and the brake control algorithm was able to maintain the operational condition even at the abrupt changes in adhesion condition.
基金supported by research grants from the Natural Sciences and Engineering Research Council(NSERC)of Canada
文摘A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current definition of a mechatronic system.The focus of the present paper is the optimal matching of sensors with other hardware in the system.Sensor matching may be based on several concepts such as the operating frequency range(operating bandwidth),speed of response(and the corresponding rate of data sampling in digital conversion),the device sensitivity(or gain or data amplification),and the effect of component acc uracy on the overall accuracy of the system.The present paper explores all these concepts and presents suit able approaches for sensor matching through those criteria.The relevant procedures are illustrated using case studies.
基金supported by the Natural Sciences and Engineering Research Council of Canadathe India-Canada Centre of Excellence for Innovative Multidisciplinary Partnership to Accelerate Community Transformation and Sustainability(IC-IMPACTS)research grantsary D.Eng.degree from University of Waterloo,Canada(2008).He has been a Professor of Mechanical Engineering and Senior Canada Research Chair and NSERC-BC Packers Chair in Industrial Automation,at the University of British Columbia,Vancouver,Canada since 1988.He has authored 24 books and about 540 papers,approximately half of which are in joumals.His recent books published by Taylor&Francis/CRC are:Modeling of Dynamic Systems-with Engineering Applications(2018),Sensor Systems(2017),Sensors and Actuators-Engineering System Instrumentation,2nd edition(2016),Mechanics of Materials(2014),Mechatronics-A Foundation Course(2010),Modeling and Control of Engineering Systems(2009),VIBRATION-Fundamentals and Practice,2nd Ed.(2007),and by Addison Wesley:Soft Computing and Intelligent Systems Design-Theory,Tools,and Applications(with F.Karray,2004).Email:desilva@mech.ubc.ca.
文摘This paper deals with instrumenting a mechatronic system,through the incorporation of suitable sensors,actuators,and other required hardware.Sensors(e.g.,semiconductor strain gauges,tachometers,RTD temperature sensors,cameras,piezoelectric accelerometers)are needed to measure(sense)unknown signals and parameters of a system and its environment.The information acquired in this manner is useful in operating or controlling the system,and also in process monitoring;experimental modeling(i.e.,model identification);product testing and qualification;product quality assessment;fault prediction,detection and diagnosis;warning generation;surveillance,and so on.Actuators(e.g.,stepper motors,solenoids,dc motors,hydraulic rams,pumps,heaters/coolers)are needed to"drive"a plant.Control actuators(e.g.,control valves)perform control actions,and in particular they drive control devices.Micro-electromechanical systems(MEMS)use microminiature sensors and actuators.MEMS sensors commonly use piezoelectric,capacitive,electromagnetic and piezoresistive principles.MEMS devices provide the benefits of small size and light weight(negligible loading errors),high speed(high bandwidth),and convenient mass-production(low cost).The process of instrumentation involves the identification of proper sensors,actuators,controllers,signal modification/interface hardware,and software with respect to their functions,operation,parameters,ratings,interaction with each other,so as to achieve the performance requirements of the overall system,and interfacing/integration/tuning of the selected devices into the system,for a given application.This paper presents the key steps of instrumenting a mechatronic system,in a somewhat general and systematic manner.Examples are described to illustrate several key procedures of instrumentation.
基金This work was supported by the Deanship of Scientific Research,King Khalid University,Kingdom of Saudi Arabia under research Grant Number(R.G.P.2/100/41).
文摘Human Adaptive Mechatronics(HAM)includes human and computer system in a closed loop.Elderly person with disabilities,normally carry out their daily routines with some assistance to move their limbs.With the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist them.The rehabilitation and occupational therapy equipments utilize the electromyography(EMG)signals to measure the muscle activity potential.This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the system.Limb characteristics extraction from EMG signal and prediction of optimal controller parameters are modeled.Time and frequency based approach of EMG signal are considered for feature extraction.The models used for estimating motion and muscle parameters from EMG signal for carrying out limb movement predictions are validated.Based on the extracted features,optimal parameters are selected by Modified Lion Optimization(MLO)for controlling the HAM system.Finally,supervised machine learning makes predictions at different points in time for individual sensing using Support Vector Neural Network(SVNN).This model is also evaluated based on optimal parameters of motion estimation and the accuracy level along with different optimization models for various upper limb movements.The proposed model of human adaptive controller predicts the limb movement by 96%accuracy.
文摘The paper briefly addresses DLR' s ( German Aerospace Center) expertise in space robotics by handof corresponding milestone projects including systems on the International Space Station ISS. It then discussesthe key technologies needed for the development of an artificial "robonaut" generation with mechatronic ultra-light weight arms and multifingered hands. The third arm generation is nearly finished now, approaching thelimits of what is technologically achievable today with respect to light-weight and power losses. In a similar wayDLR' s second generation of artificial 4-fingered hands was a big step towards higher reliability, manipulabilityand overall performance.
文摘The conceptual design of mechatronic systems is addressed under the thrust of concurrent engineering and an enhanced conceptual design methodology describing the early design stage of mechatronic systems is presented through an example illustration of a pick and place robot.This methodology treats each feasible solution as a solution strategy.In the methodology,Quality Function Deployment(QFD)is used as a baseline for the analysis of the mapping from customers to engineering requirements,Axiomatic Design(AD)is adopted as a guideline to generate feasible,good design solution alternatives,and Theory of Inventive Problem Solving(TRIZ)is applied to deal with domain conflicts in design.
文摘IoT is considered as one of the key enabling technologies for the fourth industrial revolution that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system composition hierarchy that tightly integrates mechanics with the electronics and software required to convert the mechanics to intelligent (smart) object offering well defined services to its environment. For this mechatronic component to be integrated in the IoT-based industrial automation environment, a software layer is required on top of it to convert its conventional interface to an IoT compliant one. This layer, which we call IoT wrapper, transforms the conventional mechatronic component to an Industrial Automation Thing (IAT). The IAT is the key element of an IoT model specifically developed in the context of this work for the manufacturing domain. The model is compared to existing IoT models and its main differences are discussed. A model-to-model transformer is presented to automatically transform the legacy mechatronic component to an IAT ready to be integrated in the IoT-based industrial automation environment. The UML4IoT profile is used in the form of a Domain Specific Modelling Language to automate this transformation. A prototype implementation of an Industrial Automation Thing using C and the Contiki operating system demonstrates the effectiveness of the proposed approach.
文摘Software is becoming the driving force in today’s mechatronic systems. It does not only realize a significant part of their functionality but it is also used to realize their most competitive advantages. However, the traditional development process is wholly inappropriate for the development of these systems that impose a tighter coupling of software with electronics and mechanics. In this paper, a synergistic integration of the constituent parts of mechatronic systems, i.e. mechanical, electronic and software is proposed though the 3+1 SysML view-model. SysML is used to specify the cen-tral view-model of the mechatronic system while the other three views are for the different disciplines involved. The widely used in software engineering V-model is extended to address the requirements set by the 3+1 SysML view-model and the Model Integrated Mechatronics (MIM) paradigm. A SysML profile is described to facilitate the application of the proposed view-model in the development of mechatronic systems.
文摘Middle Tennessee State University(MTSU)started a Mechatronics Engineering program four years ago.Over those four years,enrollment has grown exponentially and has increased to over 400 students.One major factor that draws interest to this new program is the university’s Experimental Vehicles Program(EVP),created by Dr.Saeed Foroudastan.The EVP includes different student teams that work to design and build the four projects the EVP has evolved to:human-powered lunar rover(formerly known as The Great Moonbuggy Race),powered off-road Baja,gasoline-powered formula car,and all-electric solar boat.These projects are designed to greatly enhance each student’s classroom experience.The EVP provides students hands-on experience that allows them to apply what they have learned in the classroom to something in real life.The students are responsible for designing and building each project with their team,which also provides them with skills like effective communication,teamwork,project management and more.Each project also has a competition that members of the team normally travel to and are able to compete on an international level.The Mechatronics Engineering program and the EVP at MTSU are both providing truly great opportunities and preparing students well that wish to enter the engineering field after college.
文摘The development of modern science and technology has promoted the overlapping and mutual penetration among different disciplines, which led to the technological innovations in the field of mechanical engineering. The mechatronics technology conforms to the law of development of science and technology in today, and combines the mechanical technology and electronic technology together to integrate the logistics, energy flow and information flow. This paper briefly describes the concept of mechatronics and the elements of mechatronics technology, and elaborates on the application of mechatronics technology in three different areas of the Machinery Industry in the form of living examples, finally introduces the future developing direction of mechatronics technology.
基金This work was supported by Shota Rustaveli National Science Foundation(SRNSF)[PHDF-19-2224,Improving the efficiency of mechatronic systems in order to ensure the reform of“Industry-4.0”].
文摘The presented work will show the highest relevance of solving all the issues related to this problem and present the results of the analysis of the main expected potential problems,which may occur in the implementation of the INDUSTRY-4.0 reform.It is proved that the pace and level of development of this reform will be determined to a large extent by the effectiveness of the individual nodes used and the entire mechatronic system.It has also been established that as a result of systematic miniaturization of the nodes of radio-electronic equipment and microelectronic equipment and microelectronic technology,the main problem of these reforms and the implementation of complex technological processes is instrumental and technological support,especially with cutting micro-tools and equipment.Therefore,on the example of these investigations,methods for improving their performance are shown.
基金supported by research grants from the Natural Sciences and Engineering Research Council(NSERC)of Canada
文摘An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.
基金supported by research grants from the Natural Sciences and Engineering Research Council(NSERC)of Canada
文摘The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in the multi-physics sense,but involves other physical domains such as fluid and thermal.This paper summarizes the mechatronic approach to modeling.Linear graphs facilitate the development of state-space models of mechatronic systems,through this approach.The use of linear graphs in mechatronic modeling is outlined and an illustrative example of sound system modeling is given.Both time-domain and frequency-domain approaches are presented for the use of linear graphs.A mechatronic model of a multi-physics system may be simplified by converting all the physical domains into an equivalent single-domain system that is entirely in the output domain of the system.This approach of converting(transforming)physical domains is presented.An illustrative example of a pressure-controlled hydraulic actuator system that operates a mechanical load is given.
文摘Health facilities are generally short-staffed and overworked. This has a significant impact on the reliability of the acquisition of health constants required at the start of diagnosis. Manual acquisition and transmission of these constants and other data leads to delays in the execution of successive care-related tasks. What’s more, the quality of service is sometimes compromised by a lack of communication between patients and staff. In pediatrics, this is compounded by the difficulty of diagnosis in the face of children’s silence, intimidated by the hospital environment. Technological assistance would relieve healthcare staff of the need to perform certain repetitive tasks. The solution proposed in this document studies a robot, based on electrical, electronic, computer and artificial intelligence resources, with human-machine interaction for taking vitals and health data in health facilities. This system enables height, mass and temperature to be taken autonomously and without contact. The algorithm we’ve developed uses artificial intelligence to check the conditions for correct measurements, both bareheaded and barefoot. This solution also alerts you to epidemic trends such as obesity. This health data is made available in the healthcare facility on terminals such as tablets, smartphones and computers used by nursing staff. This work will help healthcare staff to take automatic health vitals without contact, and to acquire and circulate data via a computer network.