Modeling random processes induced by the support surface profile in transport and technological systems - Yu. P. Kornyushin; A. V. Lavrov; A. V. Sidorova (Сельскохозяйственные машины и технологии, 2023)
The research article demonstrates that agricultural transport and technological systems are susceptible to external random inﬂuences during their operation. By accurately describing and modeling these eﬀects, the performance of the tool can be enhanced during the research and design stages. (Research purpose) The objective of this research is to generate random processes with predeﬁned correlation functions that simulate the proﬁle of the supporting surface under the wheels of agricultural transport and technological systems during operations. Additionally, the study aims to visually represent the resulting random implementations of the support surface proﬁle height. (Materials and methods) The proposed approach considers the variation in support surface proﬁle height along the trajectory of agricultural transport and technological systems, while maintaining a constant speed, as a stationary random process. The selection of the correlation function type and its parameters is dependent on the speciﬁc characteristics of the support surface. Subsequently, using the Matlab environment, the model for the support surface proﬁle height under the wheels is developed. (Results and discussion) Successful implementations of support surface proﬁle height have been achieved for two distinct scenarios: asphalt and wheat stubble. A comparative analysis is conducted between the correlation function of the simulated implementation of the random process and the original correlation function. (Conclusions) The proposed algorithm has demonstrated its capability to generate a random process with speciﬁed correlation function properties, accurately describing the height ﬂuctuations of the support surface proﬁle under the wheels of agricultural transport and technological systems. The adequacy of the algorithm has been conﬁrmed through a comprehensive analysis of at least 50 implementations, highlighting its eﬀectiveness and reliability.