This paper proposes a novel cluster-tube self-adaptive robot hand (CTSA Hand). The CTSA Hand consists of a base, a motor, a transmission mechanism, multiple elastic tendons, and a group of sliding-tube assemblies. Each sliding-tube assembly is composed of a sliding tube, a guide rod, two springs and a hinge. When the hand grasping an object, the object pushes some sliding tubes to different positions according to the surface shape of the object, the motor pulls the tendons tight to cluster tubes. The CTSA Hand can realize self-adaptive grasping of objects of different sizes and shapes. The CTSA Hand can grasp multiple objects simultaneously because the grasping of the hand acts as many grippers in different directions and heights. The grasping forces of the hand are adjusted by a closed-loop control system with potentiometer. Experimental results show that the CTSA Hand has the features of highly self-adaption and large grasping forces when grasping various objects.

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Error compensation can improve the accuracy of machine tools effectively. Among the error sources affecting the accuracy of CNC machine tool, geometric error is always set as a key performance criterion. This paper summarizes several methods of geometric error modeling and reviews the characteristics of different methods. Furthermore, available methods for measuring geometric errors have been reviewed also based on the advanced instruments. This work aims at enhancing the efficiency of error detection and give a perspective for the application of error compensation in the future.

A review of methods used for fault recognition of the rolling elements in gearbox, namely gear and bearing, is presented in this paper. The procedure of the fault recognition can be classified into three phases, which are data acquisition, data processing or important features extraction, and the fault mode detection. Many different methods have been developed in dealing with each phase, so that the arrangement of the entire process has different strategies. This paper summarizes some general used and recently popular developed methods of each phase, and makes comparison between them. This work also aims at giving a perspective in such area in the future, based on the known researches.

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Abstract. The coming of big data has brought opportunities and challenges to competitive intelligence. This paper sums up the research status of competitive intelligence in big data era on the basis of existing research and practice, analyzes the innovation and development of intelligence service, big data applications in the field of intelligence, growing trend of big data, opportunities and challenges that brings to information industry through the method of literature analysis. At last, it puts forward the impact of big data on intelligence research. Competitive Intelligence in Big Data EraIntelligence research is the process of extracting valuable information from bulk data and information, and providing related solutions for decision-making, i.e., it's the process of data processing, organization and interpretation, to reveal the potential knowledge, and then turn into usable information. Innovation oriented intelligence analysis is an important subject in area of intelligence and strategic management, and owns a lot of research results. It is the key value in intelligence activities to transform information to intelligence. However, in the face of big data environment with accumulated information socialization, traditional intelligence analysis based on the experience of simple statistics can no longer abstract semantic content and associated knowledge form vast open source information, which largely affected the depth of the intelligence analysis and efficiency. The only effective way to improve intelligence service under the big data environment is to fuse processing theory and method of knowledge, and realize the intelligent of the information analysis.

This paper outlines a conceptual framework of STEP-NC manufacturing system, which integrates the entire manufacturing process including CAD, CAPP, CAM and CNC, to make full use of the advantages of the new generation of data model. The STEP-NC manufacturing system consists of five parts and the STEP-NC standard is used to transport the complete product information. The intelligent CNC in this system can parse STEP-NC program directly so that no translation is needed and the part programs are reusable. Networked manufacturing can be realized by implementing this new framework of STEP-NC manufacturing system.