THEORETICAL FOUNDATIONS FOR ASSESSING THE RELIABILITY OF REFRIGERATION MACHINE EQUIPMENT ON THE BASIS OF THE NEURO-FUZZY METHOD FOR IDENTIFYING THEIR STATE - KHOROLSKY, VALENTYN; KORENETS, YURII; PETRUSHYNA, YULІYA (Herald of Khmelnytskyi National University. Technical sciences, 2022)
In order to design modern smart enterprises such as industrial refrigerators with a high level of reliability of their operation while maintaining the proper quality of cooling, freezing and storage of various types of products, the article analyzes the current level of safety and time to failure of equipment for refrigeration equipment for refrigeration of industrial refrigerators and system analysis of the technical system of equipment of refrigeration machines to determine the requirements for the system for assessing the level of safety of equipment of enterprises - industrial refrigerators.A methodology has been developed for analyzing the state of the equipment of refrigeration machines of industrial refrigerators, as an object of malfunctions.Models of possible malfunctions are constructed with the identification of relationships between technological parameters of operability, reliability and emergency situations.A situational model of the state of the refrigeration machine as a source of malfunctions has been developed, which is distinguished by the ability to identify relationships between parameters, events - the causes of emergencies and the state of refrigeration supply of refrigeration chambers.Knowledge about fuzzy situations is structured and fuzzy reliability models are constructed that characterize the state of the equipment.The practical value of the study lies in the development of a methodology for assessing the reliability and durability of refrigeration equipment based on a neuron-fuzzy identification method, creating a knowledge base and a system for managing the refrigeration plant performance process. Thus, it is possible to manage systems for predicting and monitoring emergency situations in systems for operational monitoring of technological processes for freezing the results of eating.
Keywords: refrigeration supply; refrigerating chambers; reliability; neuron-fuzzy modeling; intelligent system