Applied Mechanics and Materials Vol. 697

Abstract: For reasons of low accuracy of traditional leakage, a pipeline leakage diagnosis method based on multi-weight neural networks is presented to recognized leak signal in city gas pipelines. By using analysis and modeling a multi-weight neural networks are established at normal node to simplify network structure. The Information entropy of leakage characteristic parameters of negative pressure wave was used as input eigenvector respectively for primary diagnosis. It has been applied for leakage diagnosis in city gas pipelines with the whole computational process done by a computer. Results of simulation and tests show that this method has its advantage in dealing with multi-coupled fault situations and is featured by a high probability of accuracy, which not only proves the method to be effective, but also provides a theoretical basis and a new way for leak diagnosis of other pipelines.

Abstract: In order to improve the localization capability of the robot, digital image matching which based on the frequency domain was adopted, the method could reduce the impact of environmental factors, and adopts the sub-pixel subdivision pixel matching technology through curve fitting, Experimental results show that this method can achieve accurate localization in manipulator assembly working .

Abstract: This article which compares four different schemes of storage in virtualization environment tests the efficiency of system storage from application and management. The article based on test data analyses the advantages, the disadvantages and the suitable application scenarios of each scheme and gives some feasible advice of comprehensive application in various storage styles. It deserves strong theoretical and practical value.

Abstract: In the era of knowledge economy, under the network environment project collaborative knowledge construction has been paid more and more attention. Project team knowledge transfer between form a knowledge network, in line with the basic core in complex network theory goal-directed (edge network structure), has its uniqueness. In this paper, this paper discusses the knowledge network formation, network evolution stage, according to the knowledge sharing, knowledge transfer, knowledge learning and knowledge creation of four phases of the micro mechanism of knowledge collaboration, and points out that the body of knowledge of the cooperative intention, attitude and sense of trust, the body of knowledge of the network structure, location and neighborhood structure, the overall network effect and the types of knowledge, is an important factor affecting the knowledge synergy. Discusses the co-evolution of knowledge network project in cooperation, use the interpretative structural model to construct collaborative knowledge construction process of analogy model.

Abstract: Knowledge resources are the key elements of the enterprise core competencies, and knowledge loss is easy to overlook the problems of enterprises, many enterprises have to pay this end expensive price, knowledge loss problem has become an important issue of the impact the survival and development of enterprises (especially in knowledge-intensive enterprises). Knowledge Grid research focus on intelligent information processing, its goal is to eliminate isolated island of information and knowledge, to realize the intelligent sharing of information resources and knowledge resources, avoid knowledge loss. From the research direction of knowledge loss and knowledge grid, this paper analysis knowledge loss based on BP neural network, discusses the open grid services architecture, knowledge grid services architecture, system architecture, in order to provide a reference for related research.

Abstract: Two-sided assembly lines are widely applied in plants for producing large-sized high volume products, such as trucks and buses. Since the two-sided assembly line balancing problem (TALBP) is NP-hard, it is difficult to get an optimal solution in polynomial time. Therefore, a novel swarm based heuristic algorithm named gravitational search algorithm (GSA) is proposed to solve this problem with the objective of minimizing the number of mated-stations and the number of stations simultaneously. In order to apply GSA to solving the TALBP, an encoding scheme based on the random-keys method is used to convert the continuous positions of the GSA into the discrete task sequence. In addition, a new decoding scheme is implemented to decrease the idle time related to sequence-dependent finish time of tasks. The corresponding experiment results demonstrate that the proposed algorithm outperforms other well-known algorithms.

Abstract: In order to obtain proper text information consistent with the users’ cognitive level, a new personalized retrieval method is proposed for the distant learners. At first the user’s personalized cognitive structure is established and this structure can represent the users’ cognitive level formally. Then related concept can be extended around the keywords, which usually reflect their focus of attention. How to extend depennd on the semantic distance which should be measured by some new formula in this article. At last these queried documents should be ranked according to the user’s cognitive level and the difficulty of the document containt. Experiments show that even if some different learners use the same keywords, the query result is consistent with their cognitive level respectively.

Abstract: This paper puts forward an improved optimization algorithm for batch scheduling problem in flexible workshop. Code is designed as batch selection probability of different production tasks and defined as production plan through effective decoding procedure. Simulation experiment on the performance of this algorithm is conducted in instances generated randomly. The results show that this algorithm has good performance.

Abstract: Batch production in chemical flow shop is conducted with batch as processing unit. It is characterized by multi-stage production flow, intermediate inventory limit as well as product switching time. This paper presents heuristic difference evolution algorithm which adopts 2-D codes to represent batch size constraint. The experimental results show that the model and algorithm put forward in this paper has good performance.

Abstract: A mixed-model assembly line (MMAL) is a type of production system that is capable of producing different models of a common base product simultaneously. Mixed-model assembly line level scheduling problem (MMALSP) is a challenge for Just-in-time (JIT) production systems. In the paper, a mixed-model assembly line level scheduling model is proposed which considers multiple objectives simultaneously. The considered objectives include the variation in parts consumption considering the batch part supply, inventory cost and maximum transportation load. An approach based on genetic algorithm is proposed to solve the multiple objectives problem. In order to translate individuals in the GA population into candidate scheduling schemes a delivery scheduling algorithm (DSA) is proposed. In addition, dimensionless processing technique is employed in the design of the fitness function in order to comprehensively evaluate different individual considering three objectives simultaneously. The approach’s performance is validated through comprehensive experiment.