Knowledge Graph-based Process Knowledge Reasoning Method for Intelligent Production System

doi:10.16182/j.issn1004731x.joss.21-1305

Abstract

Abstract:

Aiming at the disadvantages of high redundancy and weakness between knowledge and data in intelligent production system, and the difficulty to perform knowledge reasoning, a process knowledge reasoning method for knowledge maps is proposed. The input information is semantically labeled and classified, the characteristics of the information match are extracted, the extracted local feature and global feature are associated through graph convolution method, and the feature of the difference value information is integrated and mapped with the constructed knowledge graph. Different reasoning rules are used according to different reasoning types, and the association and topology information between instances are deduced, and the properties and values of input information are generated. Compared with the recommended system algorithm and fusion knowledge map, the algorithm has higher predictive rates on Movielens-1M, Book-Crossing, Last.FM data set. The feasibility of the reasoning model is verified by the process instance knowledge.

Key words: knowledge graph, knowledge reasoning, process knowledge, graph convolution, graph matching

CLC Number:

TP391.9

Weikai Yang, Yan Wang, Zhicheng Ji. Knowledge Graph-based Process Knowledge Reasoning Method for Intelligent Production System[J]. Journal of System Simulation, 2023, 35(4): 773-785.

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模型	MovieLens-1M	Book-Crossing	Last.FM
RippleNet	0.843 6	0.646 9	0.722 3
KGCN	0.832 7	0.635 5	0.723 8
EIM	0.849 7	0.697 3	0.746 5

属性	描述
ID	5bb578b6831b973a137e3ee6
零件名称	导轴
特征	外圆、边槽、孔
表面粗糙度/mm	2.5、10、1.5
制造精度	IT9、IT10、IT7
加工工序	粗车-半精车-精车、精磨、钻孔-铣孔
加工车床	AD-35型全功能数控车床
是否淬火	否
有色金属	不存在

ID	零件名称	特征	表面粗糙度/mm	精度	加工工序
133	导轴	外圆	2.5	IT9	粗车-半精车-精车
133	导轴	边槽	10	IT10	精磨
133	导轴	孔	1.5	IT7	钻孔-铣孔
134	主轴	外螺纹	2	IT10	粗车-半精车-车螺纹
134	主轴	轴段	8	IT9	粗车-半精车-精车-精磨
134	主轴	键槽	1.5	IT9	粗车-半精车
134	主轴	螺纹孔	0.5	IT8	粗车-车螺纹

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