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Electromechanics and mechanical engineering

Method for estimating the spectrum density of the resistance moment on the working body of a peat milling unit

Authors:
K. V. Fomin
  • Tver State Technical University
Date submitted:
2019-06-19
Date published:
2020-02-25

Abstract

The main source of dynamic loads in the drive elements and the design of the peat milling unit is the working body. The forces of external resistance arising in the process of performing a technological operation are sharply variable, random in nature. The article proposes a model of formation of the moment of resistance on the mill when interacting with peat. The case when there are several cutting planes with the same radius at the ends of the cutting elements is considered. When developing the model, it was taken into account that the operating conditions of the knives, determined by the type of cutting (blocked, semi-blocked, etc.), their width and type in each cutting plane can vary. Factors that determine the nature of loading, such as the frequency of interaction of the cutting elements with the fallow and the randomness of the operating conditions of the unit, lead to the presentation of the loads in the form of a sequence of pulses with random parameters. Expressions are obtained for determining the spectral density of the moment of resistance on the mill at the design stage, taking into account its design, operating modes, physico-mechanical properties of peat and their probabilistic characteristics. To illustrate the application of the developed approaches, a technique is presented for determining the spectral density of the moment on the working body of deep milling machines and in their drive elements based on a linear model. An example of calculation is given, and the obtained expressions are verified on the basis of experimental data. The probabilistic characteristics of the loads on the mill serve as initial information for the dynamic analysis of the drive system and the design of the unit, its strength analysis, the selection of optimal parameters and operating modes.  

10.31897/pmi.2020.1.58
Go to volume 241

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