Inspection process for dimensioning through images and fuzzy logic | Zendy

Amelec Viloria | Zendy; Omar Bonerge Píneda Lezama | Zendy; Danelys Cabrera | Zendy

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Inspection process for dimensioning through images and fuzzy logic

Author(s) -

Amelec Viloria,

Omar Bonerge Píneda Lezama,

Danelys Cabrera

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.07.095

Subject(s) - computer science , expert system , fuzzy logic , process (computing) , data mining , adaptive neuro fuzzy inference system , dimensioning , artificial intelligence , machine learning , fuzzy control system , aerospace engineering , engineering , operating system

This paper presents a hybrid methodology based on a type 1 fuzzy model in singleton version using a 2k factorial design that optimizes the model of the expert system and serves to perform in-line inspection. The factorial design method provides the required database for the creation of the rule base for the fuzzy model and also generates the database to train the expert system. The proposed method was validated in the process of verifying dimensional parameters by means of images compared with the ANFIS and RBFN models which show greater margins of error in the approximation of the function represented by the system compared with the proposed model. The results obtained show that the model has an excellent performance in the prediction and quality control of the industrial process studied when compared with similar expert system techniques as ANFIS and RBFN.

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