Progresivní metody uplatnění diagnostických metod pro řízení metalurgických procesů

Abstract

The doctoral thesis deals with decision support when control mold’s plates service life in continuous steel casting device. There are used methods and instruments of technical diagnostics and artificial intelligence. In this thesis was proposed new diagnostics methodology for evaluation of mold’s plates surface faults based on fuzzy knowledge system. The results is automated diagnosis in form of qualitative scale which is proportional to actual technical state of mold’s plates surface. The diagnosis is originator for decision, if the mold’s plates can be in service without repairs or must be replaced. To eliminate human factor fault was developed and create handheld measurement device with laser sensor, capable to measure necessary quantities which serves as inputs for knowledge system. The measurement device is called ZMPV-01. The base of the device is laser sensor optoNCDT - ILD1300 E from Micro-Epsilon Czech Republic, which can sense defects depth with acceptable accuracy and sensitivity.