Volume 7, Number 3, 2010
Special Issue on Digital Manufacturing Technology (pp.261-341)
Display Mode： |
The general computer-aided design (CAD) software cannot meet the mould design requirement of the autoclave process for composites, because many parameters such as temperature and pressure should be considered in the mould design process, in addition to the material and geometry of the part. A framed-mould computer-aided design system (FMCAD) used in the autoclave moulding process is proposed in this paper. A function model of the software is presented, in which influence factors such as part structure, mould structure, and process parameters are considered; a design model of the software is established using object oriented (O-O) technology to integrate the stiffness calculation, temperature field calculation, and deformation field calculation of mould in the design, and in the design model, a hybrid model of mould based on calculation feature and form feature is presented to support those calculations. A prototype system is developed, in which a mould design process wizard is built to integrate the input information, calculation, analysis, data storage, display, and design results of mould design. Finally, three design examples are used to verify the prototype.
Drill wear not only affects the surface smoothness of the hole, but also influences the life of the drill. Drill wear state recognition is important in the manufacturing process, which consists of two steps: first, decomposing cutting torque components from the original signals by wavelet packet decomposition (WPD); second, extracting wavelet coefficients of different wear states (i.e., slight, normal, or severe wear) with signal features adapting to Welch spectrum. Finally, monitoring and recognition of the feature vectors of cutting torque signal are performed by using the K-means cluster and radial basis function neural network (RBFNN). The experiments on different tool wears of the multivariable features reveal that the results of monitoring and recognition are significant and effective.
The above-knee intelligent bionic leg is very helpful to amputees in the area of rehabilitation medicine. This paper first introduces the functional demand of the above-knee prosthesis design. Then, the advantages of the four-bar link mechanism and the magneto-rheological (MR) damper are analyzed in detail. The fixed position of the MR damper is optimized and a virtual prototype of knee joint is given. In the end, the system model of kinematics, dynamics, and controller are given and a control experiment is performed. The control experiment indicates that the intelligent bionic leg with multi-axis knee is able to realize gait tracking of the amputee s healthy leg based on semi-active control of the MR damper.
Pneumatic muscle (PM) of flexible actuators used in bionic robot is an active area of recent research. A novel PM with shape memory alloy (SMA) braided sleeve is proposed in this paper, and SMA is used to improve PM working characteristics. Based on the principle of virtual work, output force model of PM and relationship with braided wire inner-stress are established, and analysis of PM deformation has shown that braided wire length is the key factor of output force characteristic. Based on the crystal structure transitions, the relationship of temperature with wire shrinkage is derived. Then, the synthetic dynamics of novel PM is established. A physical prototype of PM with SMA braided sleeve is developed, and test platform that is built for the experiment. Experiment and simulation test of static isometric-length, static isobaric-pressure, and dynamic characteristics are done. The experimental results are compared with the simulation of theoretical model. Moreover, based on experiment, model of output force was improved by adding a correction factor to deal with the elastic force of rubber tube. The results analysis demonstrates that the established models are correct, and SMA wires can reinforce PM and make PM working characteristics adjustable. PM proposed in this paper has greater output force and is beneficial to achieve more accurate control that is useful for manipulating fragile things.
This paper presents an extended object model for case-based reasoning (CBR) in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products.
Sheet bulk metal forming processes have been widely developed to the facilitate manufacture of complicated 3D parts. However, there is still not enough know-how available. In this paper, as one of the typical sheet bulk metal forming processes, the sheet metal extrusion process was studied. A reasonable finite element method (FEM) model of sheet metal extrusion process taking the influence of flow-stress curve with wide range of plastic strain and ductile damage into consideration was established and simulated by an arbitrary Lagrangian-Eulerian (ALE) FEM implemented in MSC.Marc. Validated by comparing the results with experiment, some phenomenological characteristics, such as metal flow behavior, shrinkage cavity, and the influence of different combinations of diameter of punch, diameter of extrusion outlet, and diameter of pre-punched hole were analyzed and concluded, which can be used as theoretical fundamental for the design of the sheet metal extrusion process.
The interoperation among enterprises in e-business could block the ambient semantic collaboration and cause a big problem since varying information descriptions and different data models may be used in different enterprises information systems. Ontology is an important tool to overcome the above mentioned syntax and semantic misunderstanding problem. Our goal is to provide a user-friendly environment supporting syntax and neutral format data model for business information. In this paper, two scenarios are discussed and a unified description of data model is developed to solve the gap in interoperation through mapping from logical data of enterprise s information system. It provides the methods to realize the mapping among different types of data or information. First, database and other types of information are transformed into neutral format that are described by web ontology language (OWL). Second, the neutral format can be mapped into the semantic entities and semantic linking through the process of extraction and annotation and added into ontology and then described in a standard format that makes the collaboration be understood easily.
This paper presents a new algorithm of path planning for mobile robots, which utilises the characteristics of the obstacle border and fuzzy logical reasoning. The environment topology or working space is described by the time-variable grid method that can be further described by the moving obstacles and the variation of path safety. Based on the algorithm, a new path planning approach for mobile robots in an unknown environment has been developed. The path planning approach can let a mobile robot find a safe path from the current position to the goal based on a sensor system. The two types of machine learning: advancing learning and exploitation learning or trial learning are explored, and both are applied to the learning of mobile robot path planning algorithm. Comparison with A* path planning approach and various simulation results are given to demonstrate the efficiency of the algorithm. This path planning approach can also be applied to computer games.
A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.
Direct piezoelectricity of electro-active papers (EAPap) is analysed in this paper. The test setups for direct effect are designed and determined. Different ambient factors impacting the piezoelectricity of EAPap, such as temperature, humidity, and strain rate, are applied and analyzed. Strong piezoelectricity of EAPap is found on the basis of the test results and in comparison with polyvinylidene fluoride (PVDF) and lead zirconate titanate (PZT)-5H. The maximum piezoelectric constant is achieved to be 504 pC/N. The reason of strong piezoelectricity of EAPap is discussed in this paper. The potential of EAPap as a biomimetic actuator and sensor is also investigated.
In the course of network supported collaborative design, the data processing plays a very vital role. Much effort has been spent in this area, and many kinds of approaches have been proposed. Based on the correlative materials, this paper presents extensible markup language (XML) based strategy for several important problems of data processing in network supported collaborative design, such as the representation of standard for the exchange of product model data (STEP) with XML in the product information expression and the management of XML documents using relational database. The paper gives a detailed exposition on how to clarify the mapping between XML structure and the relationship database structure and how XML-QL queries can be translated into structured query language (SQL) queries. Finally, the structure of data processing system based on XML is presented.
Modelling based on multi-agent system (MAS) was built for the current production management and process of Shenyang Songyang Paper Cup Co., Ltd. It can transmit the information instantly via order agent (OA), manager agent (MA), production agent (PA), and service agent (SA), and realize information sharing. The PA is also built on MAS, and it includes two agents, task agent (TA), and resource agent (RA). It has been found that the modelling is superior to the old one. It can improve the working flow and production efficiency, and shorten the time of delivery.
This paper describes the design and experimental tests of a path planning and reference tracking algorithm for autonomous ground vehicles. The ground vehicles under consideration are equipped with forward looking sensors that provide a preview capability over a certain horizon. A two-level control framework is proposed for real-time implementation of the model predictive control (MPC) algorithm, where the high-level performs on-line optimization to generate the best possible local reference respect to various constraints and the low-level commands the vehicle to follow realistic trajectories generated by the high-level controller. The proposed control scheme is implemented on an indoor testbed through networks with satisfactory performance.
This paper presents the results of an on-going project and investigates modelling and remote control issues of an industry excavator. The details of modelling, communication, and control of a remotely controllable excavator are studied. The paper mainly focuses on trajectory tracking control of the excavator base and robust control of the excavator arm. These will provide the fundamental base for our next research step. In addition, extensive simulation results for trajectory tracking of the excavator base and robust control of the excavator arm are given. Finally, conclusions and further work have been identified.
The technique for order performance by similarity to ideal solution (TOPSIS) is one of the major techniques in dealing with multiple criteria decision making (MCDM) problems, and the belief structure (BS) model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.
During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television (CCTV) data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today s approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called pre-suspicion mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.
This paper focuses on improving decision tree induction algorithms when a kind of tie appears during the rule generation procedure for specific training datasets. The tie occurs when there are equal proportions of the target class outcome in the leaf node s records that leads to a situation where majority voting cannot be applied. To solve the above mentioned exception, we propose to base the prediction of the result on the naive Bayes (NB) estimate, k-nearest neighbour (k-NN) and association rule mining (ARM). The other features used for splitting the parent nodes are also taken into consideration.
For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control (MRAC) with normalized adaptive law are investigated. The main work includes three parts. Firstly, it is shown that the constructed parameter estimation algorithm not only possesses the same properties as those of traditional estimation algorithms, but also avoids the possibility of division by zero. Secondly, by establishing a relationship between the plant parameter estimate and the controller parameter estimate, some similar properties of the latter are also established. Thirdly, by using the relationship between the normalizing signal and all the signals of the closed-loop system, and some important mathematical tools on discrete-time systems, as in the continuous-time case, a systematic stability and robustness analysis approach to the discrete indirect robust MRAC scheme is developed rigorously.
Software engineering s lifecycle models have proven to be very important for traditional software development. However, can these models be applied to the development of Web-based applications as well? In recent years, Web-based applications have become more and more complicated and a lot of efforts have been placed on introducing new technologies such as J2EE, PhP, and .NET, etc., which have been universally accepted as the development technologies for Web-based applications. However, there is no universally accepted process model for the development of Web-based applications. Moreover, shaping the process model for small medium-sized enterprises (SMEs), which have limited resources, has been relatively neglected. Based on our previous work, this paper presents an expanded lifecycle process model for the development of Web-based applications in SMEs. It consists of three sets of processes, i.e., requirement processes, development processes, and evolution processes. Particularly, the post-delivery evolution processes are important to SMEs to develop and maintain quality web applications with limited resources and time.
This paper presents the first application of the bees algorithm to the optimisation of parameters of a two-dimensional (2D) recursive digital filter. The algorithm employs a search technique inspired by the foraging behaviour of honey bees. The results obtained show clear improvement compared to those produced by the widely adopted genetic algorithm (GA).
In this paper, we have successfully presented a fuzzy Petri net (FPN) model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition (HFT) to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.
IJAC CiteScore keeps raising in 2018
IJAC receives a CiteScore as high as 2.34 in 2018 which is 1.37 times higher than that in 2017. Being in the top 15%, it ranks #69 among 460 journals in respective categories.
【Open Access】Download highlight papers for free
During the past two years, IJAC has published a series of high-quality papers by famous scholars around the world, including professor Tomaso Poggio from MIT, professor Brian Anderson from Australian National University, professor Yike Guo from Imperial College London, etc.. All the papers are open access, covering topics of Deep Learning, Artificial Intelligence, Neural Networks, and so on. You’ll never miss it!
2019 International Academic Conference List
International Journal of Automation and Computing (IJAC) maintains this list of conferences at the beginning of each year that are highly relevant to current hot research topics, including artificial intelligence, machine learning, computer vision, pattern recognition, robotics and automatic control.