Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

Research of CRP-based irregular 2D seismic acquisition

Seismic exploration in the mountainous areas of western Chinese is extremely difficult because of the complexity of the surface and subsurface, which results in shooting difficulties, seismic data with low signal-to-noise ratio, and strong interference. The complexity of the subsurface structure leads to strong scattering of the refl ection points; thus, the curved-line acquisition method has been used. However, the actual subsurface structural characteristics have been rarely considered. We propose a design method for irregular acquisition based on common refl ection points（CRP） to avoid difficult-to-shoot areas, while considering the structural characteristics and CRP positions and optimizing the surfacereceiving line position. We arrange the positions of the receiving points to ensure as little dispersion of subsurface CRP as possible to improve the signal-to-noise ratio of the seismic data. We verify the applicability of the method using actual data from a site in Sichuan Basin. The proposed method apparently solves the problem of seismic data acquisition and facilitates seismic exploration in structurally complex areas.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.