关键词: 个体状态, 组合状态, 制造情景, 概率因果, 贝叶斯网络

Abstract: Aiming at the problem that the manufacturing resource's individual states and their combinations were complex and variable,and there was no linear logic relationship between individual states and manufacturing situations,which led to the difficulty to directly map individual states to manufacturing situations,a recognition method for manufacturing situation based on Bayesian network was proposed,in which the probability causality between individual states and manufacturing situations was established.The proposed method considered the coexistence of continuous states and discrete states fully,and the equal-interval discrete method was used to deal with continuous states.Through the maximum posterior probability,the manufacturing situation was confirmed.The effectiveness of the proposed method was verified by a case study.

Key words: individual states, combined states, manufacturing situations, probabilistic causality, Bayesian Network