Driven by national policies and international competitions, China’s winter sports and industry development will enter a new course. How to release the enormous potential skiing demand in China is significant to drive 300 million people to participate in winter sports and promote the development of China’s ice and snow industry, and defining the restrictive factors is a necessary prerequisite to realise the effective transformation of potential demand to actual growth power. Based on the in-depth information, this paper further analyses the influence of environmental factors on the development of winter sports. The research shows that the number of skiers about 20 times is the highest, up to 75.5 %, followed by the number of skiers about five times, up to 67.4 %. Then about ten times accounted for 48.6 %, and finally, about 15 times accounted for 37.6 %. This frequency can fully satisfy skiing enthusiasts to enjoy leisure activities, experience modern life fashion, use skiing to increase social opportunities, delight body and mind, and improve health. Based on the in-depth information, this paper reveals the shortcomings and existing environmental factors of China’s winter sports development. It provides a reference for the rational utilisation and development of ice and snow resources and the scientific and practical development of China’s winter sports.
:A method of dynamic synthesis correction of deviation error is proposed for aircraft wing-fuselage docking assembly by using laser tracker and vision with the object of fork-ear joint. In the stage of wing pose adjustment, the artificial fish swarm particle filter is used to track and estimate coordinates of points on the wing. Trajectory planning in combination with the locator inverse kinematics, dynamic modification model of the wing pose is built. In the stage of wing-fuselage docking, the characteristic parameters of the joint is dynamically detected to get joint position errors by machine vision. The error based on laser tracker and machine vision are fused and filtered, according to the principle of weighted least square of heterogeneous sensor information fusion. By this way, the models of dynamic monitoring of docking quality and comprehensive correction of docking deviation are also built. The experiments show that the proposed method can effectively improve quality of wing-fuselage docking assembly, and dynamic synthesis correction of deviation of wing-fuselage docking assembly is realized.
As an information collection and automatic identification technology, barcode can be used to collect information accurately and quickly. So the barcode technology is introduced into the whole cycle of aircraft manufacturing. This paper puts forward the oriented method of the aircraft development cycle of barcode application and gives the system implementation scheme. The whole development cycle of aircraft analyzes the barcode applications, coupling of logistics and information flow, sharing manufacturing information, establishing the single aircraft sorties quality files. The system will effectively enhance the level of aircraft development and have positive significance for building digital factory.
There are many deviation sources in the assembly process of aircraft complex thin-walled structures. To get important factors that affect quality, it is crucial to diagnose the key deviation resources. The deviation transfer between deviation sources and assembly parts has the characteristics of small sample size, nonlinearity, and strong coupling, so it is difficult to diagnose the key deviation sources by constructing assembly dimension chains. Therefore, based on the deviation detection data, transfer entropy and complex network theory are introduced. Integrating the depth-first traversal algorithm with degree centrality theory, a key deviation diagnosis method for complex thin-walled structures is proposed based on weighted transfer entropy and complex networks. The application shows that key deviation sources that affect assembly quality can be accurately identified by the key deviation source diagnosis method based on complex networks and weighted transfer entropy.
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