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DOI

Cone crushers of medium and fine crushing are used at mining enterprises for crushing materials with quite a wide range of physical and mechanical properties. The review and analysis of scientific and technical literature on crushing process regularities in cone crushers has determined the following: the dependence between material grain size distribution and crusher space profile parameters, wear rate of mobile and stationary cone liner, establishment of an optimum crusher space profile, minimisation of high manganese steel consumption, optimisation of crushing equipment repair and maintenance costs. The condition of the liner mantle is one of the determining factors in changing the qualitative and quantitative characteristics of the fine crushing process. It is established that a significant failure number of cone crushers, namely 96% lead to unscheduled repairs. Research objective. In order to implement a new approach in monitoring the liner mantle state. Methods. A complex approach was used, which includes: scientific analysis and generalization of previously published researches. The theory of fuzzy logic and fuzzy sets and methods of the system analysis made a methodological basis of researches. Novelty. The possibility of using the methods of artificial intelligence in the assessment of the liner mantle state in cone crushers has been implemented. Result: The approach in controlling the liner mantle wear in fine and medium cone crushers is defined.
Язык оригиналаАнглийский
Название основной публикацииLecture Notes in Mechanical Engineering
Подзаголовок основной публикацииbook
РедакторыA.A. Radionov, V.R. Gasiyarov
ИздательSpringer
ГлаваChapter 64
Страницы650-660
Число страниц11
ISBN (печатное издание)978-303138125-6
DOI
СостояниеОпубликовано - 28 июл. 2023

Серия публикаций

НазваниеProceedings of the 9th International Conference on Industrial Engineering
ISSN (печатное издание)2195-4356
ISSN (электронное издание)2195-4364

    Предметные области ASJC Scopus

  • Fluid Flow and Transfer Processes
  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering

ID: 46003582