Elaboration of a method of electromechanical drive systems status estimation (at an example of a roll-table roller) by application statistical analysis of electric motor current signal

Abstract

Loss enhancement because of extraordinary stoppage of technological equipment due to breakage of separate equipment units is an actual task. Existing methodologies of equipment status estimation, based on planning systems, instrumental checks, and personal experience do not ensure always revealing of the incipient of breakdown status in separate elements of the equipment, which often results in breakdown situations and extraordinary repairs. Studies of analysis statistical methods application were accomplished for early revealing indications of electromechanical equipment failure at an example of predicting breakdown status of rollers of rolling mill roll-table. As a parameter under the study, the current signal was chosen, measured at the electric motor of a roller, since it reacts practically without inertia on external oscillations in mechanical part of the facility. The variations of the current curve form reflect any variations of the equipment operation character. From this point of view, the electrical motor itself can be considered as a technical mean of diagnostics of mechanical oscillations in the load with a short response time. Statistical analysis of electric motors current data within one month of roll-table rollers operation, within which 14 jams took place, was carried out. Based on the results of the analysis it was determined, that the process of the jams intensification for various rollers has a similar character. A possibility wa shown to predict the developing and identification of a roller defect by a type of a jam several hours before commencement of the breakdown status, based on one parameter – the load current. Based on sampling of the rollers statistical data in various operation modes and mark of breakdown stops, it is possible to learn the nonlinear machine model for classification of a roller breakdown degree by extracted from the distribution form of statistical current characteristics. The elaborated models in the form of software products and machine codes can be implemented in algorithms of existing at a plant automation systems and technological process and equipment status control systems.