This paper devises a scheme which can discover the state association rules of process object. The scheme aims to dig the hidden close relationships of different links in process object. We adopt a method based on diff...This paper devises a scheme which can discover the state association rules of process object. The scheme aims to dig the hidden close relationships of different links in process object. We adopt a method based on difference and extremum to compute the timing. Clustering is used to classifying the adjusted data, and the next is associating the clusters. Based on the rules of clusters, we produce the rules of links. Association degrees between each two links can be determined. It is easy to get association chains according to the degree. The state association rules that can be obtained in accordance with association rules are the final results. Some industry guidance can be directly summarized from the state association rules, and we can apply the guidance to improve the efficiency of production and operational in allied industries.展开更多
To resolve the technical difficulty of managing the product devdoping process,an ob-ject model for product developing process is provided by using the object-oriented methodology.In this model,the constituent objects ...To resolve the technical difficulty of managing the product devdoping process,an ob-ject model for product developing process is provided by using the object-oriented methodology.In this model,the constituent objects including activity,transition,data,partidpant,applica-tion tool and resource as well as the rela tions between them are identified and discussed in detail.According to this model,a function framework of the process managing system is also proposed.Based on the object model and the function framework,product devdoping process and productinformation flow can be efficiently managed and controlled.As a result,costly errors and dupli-cate efforts are avoided in the product developing process,which is useful for shor tening develop-ment cyde and improving product quality.展开更多
Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosi...Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosity, while reducing the secondary dendritic arm spacing of a wheel casting during low-pressure die casting(LPDC) process, was taken as an example of such problem. A commercial simulation software Pro CASTTM was applied to simulate the filling and solidification processes. Additionally, a program for integrating the optimization algorithm with numerical simulation was developed based on SiPESC. By setting pouring temperature and filling pressure as design variables, shrinkage porosity and secondary dendritic arm spacing as objective variables, the multi-objective optimization of minimum volume of shrinkage porosity and secondary dendritic arm spacing was achieved. The optimal combination of AZ91 D wheel casting was: pouring temperature 689 °C and filling pressure 6.5 kPa. The predicted values decreased from 4.1% to 2.1% for shrinkage porosity, and 88.5 μm to 81.2 μm for the secondary dendritic arm spacing. The optimal results proved the feasibility of the developed program in multi-objective optimization.展开更多
In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range pre...In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.展开更多
This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of vari...This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.展开更多
When deciding on the best historic building retrofit,energy savings and thermal comfort can be quantitatively evaluated using an energy model,whereas conservation compatibility is intrinsically qualitative and reflect...When deciding on the best historic building retrofit,energy savings and thermal comfort can be quantitatively evaluated using an energy model,whereas conservation compatibility is intrinsically qualitative and reflects the perspective of the local heritage authority. We present a methodology that permits finding and comparing optimal retrofits for historic buildings in a multi-perspective and quantitative way. We use an analytic hierarchyprocess to quantify conservation compatibility by distilling a conservation score from the opinions of 10 experts in the field. This score,along with energy needs for heating and cooling and thermal comfort,are the three targets of a multi-objective optimization aimed at identifying optimal retrofits for a medieval building in the north of Italy,destined to become a museum. Retrofit measures considered were different kinds of external and internal envelope insulation,improvement of airtightness,replacement of windows,and ventilative cooling. The result is a portfolio of optimal retrofits that cover the whole range of conservation compatibility. We showthat in the analyzed case heritage preservation is compatible with a four-fold reduction in energy needs at a high thermal comfort level. Even higher energy savings are only achievable at the cost of heritage degradation.展开更多
In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Tow objecti...In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Tow objective functions are simultaneously optimized under a set of practical of machining constraints, the first objective function is cutting cost and the second one is the used tool life time. The proposed model deals multi-pass turning processes where the cutting operations are divided into multi-pass rough machining and finish machining. Results obtained from Genetic Algorithms method are presented in Pareto frontier graphic;this technique helps us in decision making process. An example is presented to illustrate the procedure of this technique.展开更多
In view of the lack of research on the information model of tufting carpet machine in China,an information modeling method based on Object Linking and Embedding for Process Control Unified Architecture(OPC UA)framewor...In view of the lack of research on the information model of tufting carpet machine in China,an information modeling method based on Object Linking and Embedding for Process Control Unified Architecture(OPC UA)framework was proposed to solve the problem of“information island”caused by the differentiated data interface between heterogeneous equipment and system in tufting carpet machine workshop.This paper established an information model of tufting carpet machine based on analyzing the system architecture,workshop equipment composition and information flow of the workshop,combined with the OPC UA information modeling specification.Subsequently,the OPC UA protocol is used to instantiate and map the information model,and the OPC UA server is developed.Finally,the practicability of tufting carpet machine information model under the OPC UA framework and the feasibility of realizing the information interconnection of heterogeneous devices in the tufting carpet machine digital workshop are verified.On this basis,the cloud and remote access to the underlying device data are realized.The application of this information model and information integration scheme in actual production explores and practices the application of OPC UA technology in the digital workshop of tufting carpet machine.展开更多
On the basis of characteristics of threat assessment of aerial defense, a kind of MADM (multiple attribute decision making) method with unknown attribute weights and biased project on decision-maker is put forward. It...On the basis of characteristics of threat assessment of aerial defense, a kind of MADM (multiple attribute decision making) method with unknown attribute weights and biased project on decision-maker is put forward. It can be used in dealing with the object threat assessment problem. A computing formula on project preference of decision-maker and one model of obtaining attribute optimization weight are set up. The method improves the veracity and reliability of computing object threat assessment, and the simulating result shows that this method is valid.展开更多
This paper describes how to use the Unified Modeling Language (UML) to modeling software processes in medical insurance MIS, and compares UML Modeling method with classic PO(Process Oriented) Modeling method. It indi...This paper describes how to use the Unified Modeling Language (UML) to modeling software processes in medical insurance MIS, and compares UML Modeling method with classic PO(Process Oriented) Modeling method. It indicates that the whole performance of application system model described by UML is much better than the one described by PO.展开更多
Nowadays, 3D object detection, which uses the color and depth information to find object localization in the 3D world and estimate their physical size and pose, is one of the most important 3D perception tasks in the ...Nowadays, 3D object detection, which uses the color and depth information to find object localization in the 3D world and estimate their physical size and pose, is one of the most important 3D perception tasks in the field of computer vision. In order to solve the problem of mixed segmentation results when multiple instances appear in one frustum in the F-PointNet method and in the occlusion that leads to the loss of depth information, a 3D object detection approach based on instance segmentation and image restoration is proposed in this paper. Firstly, instance segmentation with Mask R-CNN on an RGB image is used to avoid mixed segmentation results. Secondly, for the detected occluded objects, we remove the occluding object first in the depth map and then restore the empty pixel region by utilizing the Criminisi Algorithm to recover the missing depth information of the object. The experimental results show that the proposed method improves the average precision score compared with the F-PointNet method.展开更多
In this study "the leftest trace algorithm " was used to solve the trace of cells edge better. It also overcame the shortage that use sobel operator and laplace operator to detect the edge of wood cells. Thi...In this study "the leftest trace algorithm " was used to solve the trace of cells edge better. It also overcame the shortage that use sobel operator and laplace operator to detect the edge of wood cells. This realized the rapid extraction of the anatologic shape features in across compression and make possible the wood species could be characterized quantitatively.展开更多
This paper shows how a desktop simulation can be migrated into its cloud equivalence using Windows Azure. It is undeniable that simulators are expensive and cost-intensive regarding maintenance and upgrading, and thus...This paper shows how a desktop simulation can be migrated into its cloud equivalence using Windows Azure. It is undeniable that simulators are expensive and cost-intensive regarding maintenance and upgrading, and thus, it is not always feasible to buy such a simulator. Therefore, it will be of great significance if we have an approach, which provides simulators with services through the Internet with the aim of making them accessible from anywhere and at any time. That is, researchers and developers can focus on their actual researches and experiments and the intended output results. The cloud simulation infrastructure of this contribution is capable of hosting different simulations with the ability to be cloned as cloud services. The simulator example used here mimics the process of a distillation column to be seen as a widely used plant in several industrial applications. The cloud simulation core embedded in the cloud environment is fully independent from the developed user-interface of the simulator meaning that the cloud simulator can be connected to any user-interface. This allows simulation users such as process control and alarm management designers to connect to the cloud simulator in order to design, develop and experiment their systems on a “pay-as-you-go” basis as it is the case of most cloud computing services, aimed at providing computing services as utilities like water and electricity. For coding convenience, Windows Azure was selected for both developing the cloud simulation and hosting it in the cloud because of the fact that the source code of the desktop simulator is already available in C# based on dot Net technology. From a software technical point of view, UML graphical notations were applied in order to express the software requirement specifications of the distributed cloud simulation, representing a widespread technology in the object-oriented design and analysis.展开更多
This paper proposes an object-tracking algorithm with multiple randomly-generated features. We mainly improve the tracking performance which is sometimes good and sometimes bad in compressive tracking. In compressive ...This paper proposes an object-tracking algorithm with multiple randomly-generated features. We mainly improve the tracking performance which is sometimes good and sometimes bad in compressive tracking. In compressive tracking, the image features are generated by random projection. The resulting image features are affected by the random numbers so that the results of each execution are different. If the obvious features of the target are not captured, the tracker is likely to fail. Therefore the tracking results are inconsistent for each execution. The proposed algorithm uses a number of different image features to track, and chooses the best tracking result by measuring the similarity with the target model. It reduces the chances to determine the target location by the poor image features. In this paper, we use the Bhattacharyya coefficient to choose the best tracking result. The experimental results show that the proposed tracking algorithm can greatly reduce the tracking errors. The best performance improvements in terms of center location error, bounding box overlap ratio and success rate are from 63.62 pixels to 15.45 pixels, from 31.75% to 64.48% and from 38.51% to 82.58%, respectively.展开更多
The enterprise software need adapt to new requirements from the continuous change management. The recent development methods have increased the flexibility of software. However, previous studies have ignored the stabi...The enterprise software need adapt to new requirements from the continuous change management. The recent development methods have increased the flexibility of software. However, previous studies have ignored the stability of business object and the particular business relationships to support the software development. In this paper, a coarse-grained business object based software development, BOSD, is presented to resolve this problem. By analyzing the characteristics of variable requirement, business objects are abstracted as the separately-developed unit from business process, and are assembled to system through their relationships. The methodology of BOSD is combined with MDA (Model Driven Architecture) and implemented on the semiautomatic platform.展开更多
文摘This paper devises a scheme which can discover the state association rules of process object. The scheme aims to dig the hidden close relationships of different links in process object. We adopt a method based on difference and extremum to compute the timing. Clustering is used to classifying the adjusted data, and the next is associating the clusters. Based on the rules of clusters, we produce the rules of links. Association degrees between each two links can be determined. It is easy to get association chains according to the degree. The state association rules that can be obtained in accordance with association rules are the final results. Some industry guidance can be directly summarized from the state association rules, and we can apply the guidance to improve the efficiency of production and operational in allied industries.
文摘To resolve the technical difficulty of managing the product devdoping process,an ob-ject model for product developing process is provided by using the object-oriented methodology.In this model,the constituent objects including activity,transition,data,partidpant,applica-tion tool and resource as well as the rela tions between them are identified and discussed in detail.According to this model,a function framework of the process managing system is also proposed.Based on the object model and the function framework,product devdoping process and productinformation flow can be efficiently managed and controlled.As a result,costly errors and dupli-cate efforts are avoided in the product developing process,which is useful for shor tening develop-ment cyde and improving product quality.
基金financially supported by the National Key Research and Development Program of China(Grant No.2016YFB0701204)
文摘Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosity, while reducing the secondary dendritic arm spacing of a wheel casting during low-pressure die casting(LPDC) process, was taken as an example of such problem. A commercial simulation software Pro CASTTM was applied to simulate the filling and solidification processes. Additionally, a program for integrating the optimization algorithm with numerical simulation was developed based on SiPESC. By setting pouring temperature and filling pressure as design variables, shrinkage porosity and secondary dendritic arm spacing as objective variables, the multi-objective optimization of minimum volume of shrinkage porosity and secondary dendritic arm spacing was achieved. The optimal combination of AZ91 D wheel casting was: pouring temperature 689 °C and filling pressure 6.5 kPa. The predicted values decreased from 4.1% to 2.1% for shrinkage porosity, and 88.5 μm to 81.2 μm for the secondary dendritic arm spacing. The optimal results proved the feasibility of the developed program in multi-objective optimization.
基金This work was supported by the UK EPSRC (GR/N13319, GR/R10875).
文摘In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.
基金(Nos. 20806040,61073059 and 61034005) supported by the National Natural Science Foundation of China
文摘This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance(ANOVA),a process modeling algorithm by artificial neural network(ANN),and a multi-objective parameter optimization algorithm by genetic algorithm(GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.
文摘When deciding on the best historic building retrofit,energy savings and thermal comfort can be quantitatively evaluated using an energy model,whereas conservation compatibility is intrinsically qualitative and reflects the perspective of the local heritage authority. We present a methodology that permits finding and comparing optimal retrofits for historic buildings in a multi-perspective and quantitative way. We use an analytic hierarchyprocess to quantify conservation compatibility by distilling a conservation score from the opinions of 10 experts in the field. This score,along with energy needs for heating and cooling and thermal comfort,are the three targets of a multi-objective optimization aimed at identifying optimal retrofits for a medieval building in the north of Italy,destined to become a museum. Retrofit measures considered were different kinds of external and internal envelope insulation,improvement of airtightness,replacement of windows,and ventilative cooling. The result is a portfolio of optimal retrofits that cover the whole range of conservation compatibility. We showthat in the analyzed case heritage preservation is compatible with a four-fold reduction in energy needs at a high thermal comfort level. Even higher energy savings are only achievable at the cost of heritage degradation.
文摘In this paper we present a multi-optimization technique based on genetic algorithms to search optimal cuttings parameters such as cutting depth, feed rate and cutting speed of multi-pass turning processes. Tow objective functions are simultaneously optimized under a set of practical of machining constraints, the first objective function is cutting cost and the second one is the used tool life time. The proposed model deals multi-pass turning processes where the cutting operations are divided into multi-pass rough machining and finish machining. Results obtained from Genetic Algorithms method are presented in Pareto frontier graphic;this technique helps us in decision making process. An example is presented to illustrate the procedure of this technique.
文摘In view of the lack of research on the information model of tufting carpet machine in China,an information modeling method based on Object Linking and Embedding for Process Control Unified Architecture(OPC UA)framework was proposed to solve the problem of“information island”caused by the differentiated data interface between heterogeneous equipment and system in tufting carpet machine workshop.This paper established an information model of tufting carpet machine based on analyzing the system architecture,workshop equipment composition and information flow of the workshop,combined with the OPC UA information modeling specification.Subsequently,the OPC UA protocol is used to instantiate and map the information model,and the OPC UA server is developed.Finally,the practicability of tufting carpet machine information model under the OPC UA framework and the feasibility of realizing the information interconnection of heterogeneous devices in the tufting carpet machine digital workshop are verified.On this basis,the cloud and remote access to the underlying device data are realized.The application of this information model and information integration scheme in actual production explores and practices the application of OPC UA technology in the digital workshop of tufting carpet machine.
基金the Ministerial Level Advanced Research Foundation
文摘On the basis of characteristics of threat assessment of aerial defense, a kind of MADM (multiple attribute decision making) method with unknown attribute weights and biased project on decision-maker is put forward. It can be used in dealing with the object threat assessment problem. A computing formula on project preference of decision-maker and one model of obtaining attribute optimization weight are set up. The method improves the veracity and reliability of computing object threat assessment, and the simulating result shows that this method is valid.
基金Supported by the National Natureal Science Foundation of China (6 98730 36 )
文摘This paper describes how to use the Unified Modeling Language (UML) to modeling software processes in medical insurance MIS, and compares UML Modeling method with classic PO(Process Oriented) Modeling method. It indicates that the whole performance of application system model described by UML is much better than the one described by PO.
基金Supported by the National Natural Science Foundation of China(61603242)Collaborative Innovation Center for Economics Crime Investigation and Prevention Technology of Jiangxi Province(JXJZXTCX-030)
文摘Nowadays, 3D object detection, which uses the color and depth information to find object localization in the 3D world and estimate their physical size and pose, is one of the most important 3D perception tasks in the field of computer vision. In order to solve the problem of mixed segmentation results when multiple instances appear in one frustum in the F-PointNet method and in the occlusion that leads to the loss of depth information, a 3D object detection approach based on instance segmentation and image restoration is proposed in this paper. Firstly, instance segmentation with Mask R-CNN on an RGB image is used to avoid mixed segmentation results. Secondly, for the detected occluded objects, we remove the occluding object first in the depth map and then restore the empty pixel region by utilizing the Criminisi Algorithm to recover the missing depth information of the object. The experimental results show that the proposed method improves the average precision score compared with the F-PointNet method.
文摘In this study "the leftest trace algorithm " was used to solve the trace of cells edge better. It also overcame the shortage that use sobel operator and laplace operator to detect the edge of wood cells. This realized the rapid extraction of the anatologic shape features in across compression and make possible the wood species could be characterized quantitatively.
文摘This paper shows how a desktop simulation can be migrated into its cloud equivalence using Windows Azure. It is undeniable that simulators are expensive and cost-intensive regarding maintenance and upgrading, and thus, it is not always feasible to buy such a simulator. Therefore, it will be of great significance if we have an approach, which provides simulators with services through the Internet with the aim of making them accessible from anywhere and at any time. That is, researchers and developers can focus on their actual researches and experiments and the intended output results. The cloud simulation infrastructure of this contribution is capable of hosting different simulations with the ability to be cloned as cloud services. The simulator example used here mimics the process of a distillation column to be seen as a widely used plant in several industrial applications. The cloud simulation core embedded in the cloud environment is fully independent from the developed user-interface of the simulator meaning that the cloud simulator can be connected to any user-interface. This allows simulation users such as process control and alarm management designers to connect to the cloud simulator in order to design, develop and experiment their systems on a “pay-as-you-go” basis as it is the case of most cloud computing services, aimed at providing computing services as utilities like water and electricity. For coding convenience, Windows Azure was selected for both developing the cloud simulation and hosting it in the cloud because of the fact that the source code of the desktop simulator is already available in C# based on dot Net technology. From a software technical point of view, UML graphical notations were applied in order to express the software requirement specifications of the distributed cloud simulation, representing a widespread technology in the object-oriented design and analysis.
文摘This paper proposes an object-tracking algorithm with multiple randomly-generated features. We mainly improve the tracking performance which is sometimes good and sometimes bad in compressive tracking. In compressive tracking, the image features are generated by random projection. The resulting image features are affected by the random numbers so that the results of each execution are different. If the obvious features of the target are not captured, the tracker is likely to fail. Therefore the tracking results are inconsistent for each execution. The proposed algorithm uses a number of different image features to track, and chooses the best tracking result by measuring the similarity with the target model. It reduces the chances to determine the target location by the poor image features. In this paper, we use the Bhattacharyya coefficient to choose the best tracking result. The experimental results show that the proposed tracking algorithm can greatly reduce the tracking errors. The best performance improvements in terms of center location error, bounding box overlap ratio and success rate are from 63.62 pixels to 15.45 pixels, from 31.75% to 64.48% and from 38.51% to 82.58%, respectively.
文摘The enterprise software need adapt to new requirements from the continuous change management. The recent development methods have increased the flexibility of software. However, previous studies have ignored the stability of business object and the particular business relationships to support the software development. In this paper, a coarse-grained business object based software development, BOSD, is presented to resolve this problem. By analyzing the characteristics of variable requirement, business objects are abstracted as the separately-developed unit from business process, and are assembled to system through their relationships. The methodology of BOSD is combined with MDA (Model Driven Architecture) and implemented on the semiautomatic platform.
