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Назив: Relations between pulverizing process parameters and beater wheel mill vibration for predictive maintenance program setup
Аутори: Bajrić R.
Zuber, Ninoslav 
Šostakov R.
Датум издавања: 8-јан-2014
Часопис: Eksploatacja i Niezawodnosc
Сажетак: Beater wheel mills are designed to prepare a coal powder air fuel mixture for combustion in furnace chambers of coal-freed power plants by coal drying, pulverizing, classifying and transport. Their multipurpose function usually results in operation instability accompanied by unacceptable vibration. This usually is a signifcant problem due to unplanned shutdowns. Beater wheel mill maintenance program requires special attention due to operation under non-stationary conditions. The purpose of this paper was to identify pulverizing process parameter that affect the beater wheel mill vibration level and severity at the same time by using statistical principles under a wide range of operating conditions. This paper intends to establish the foundations to investigate correlation of pulverizing process parameter with beater wheel mill vibration in order to setup a better predictive maintenance program. To achieve this goal, the beater wheel mill vibration under different combinations of selected pulverizing process parameters are analyzed using statistical tools. Experiments were carried out under different conditions for two identical but separated beater wheel mills. The infuence of pulverizing process parameter, such as electrical current of the driving motor, mill capacity, boiler production, coal types on mill vibration are investigated to identify the potential malfunction of beater wheel mills and their associated components for predictive maintenance purposes. The results have demonstrated that the selected pulverizing process parameters do not have signifcant infuence on beater wheel mill vibration severity. Unlike most coal mills where pulverizing process parameters must take into account, here with beater wheel impact mills it is not the case and condition monitoring of these mills could be conducted offline or online using standard vibration condition monitoring methods.
URI: https://open.uns.ac.rs/handle/123456789/7369
ISSN: 15072711
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