Optimizing the Finishing Treatment of Potato Harvester Transmission Shafts

The potato harvester’s distinctive specifications include the spatially segregated drive of its units from an external engine, operating under stochastic conditions. This setup complicates the loading of its components, including transmission shafts, and creates the prerequisites for decreased durability, leading to an upsurge in fatigue failures. To counteract this process, transmission shafts undergo a special treatment aimed at mitigating concentrated defects. (Research purpose) The purpose of this research is to formulate an objective function for controlling the finishing treatment of transmission shafts in a potato harvester. This function is designed to maximize potato yield while monitoring concentrated defects. (Materials and methods) The implementation of the method requires equipment capable of being controlled through a technical vision channel. The control scheme employs mathematical tools for describing discrete and continuous random variables, Markov processes with discrete time and continuous state space, the maximum likelihood method, and methods of numerical optimization in multifactor space. (Results and discussion) The research has yielded formulas for calculating the probabilities of successful and unsuccessful outcomes of finishing treatment based on the criterion of concentrated defect presence. The paper provides the results of testing the proposed algorithm for predicting the yield of viable products using the proposed method based on interim measurements of defect characteristics during the treatment process. Additionally, a scheme is proposed for integrating the obtained results into the production process of manufacturing transmission shafts for potato harvesters. (Conclusions) An algorithm has been proposed to control the finishing treatment of the transmission shaft based on a predictive assessment of the probability of manufacturing a product that adheres to the specified technical criteria regarding geometry and surface cleanliness. The predictive probability of achieving a surface with the required cleanliness without exceeding permissible defect limits is considered as the objective function. The solution to the problem is achieved through the selection of appropriate technological parameters.

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