ABSTRACT

This paper covers different methods to evaluate the power consumption of several conveyor belt systems (CBSs) used in the Turkish Mining Industry (TMI). Based on each CBS’s operational features, the power consumption (P_c, kW) was measured directly on motorised head-pulleys. The P_c was investigated through several conventional, statistical, and machine learning methods. This study shows that the DIN 22,101 could be the most convenient conventional method for the investigated CBSs. On the other hand, based on the nonlinear regression (NLR) and genetic expression programming (GEP) models, two new approaches were suggested for the design and optimisation of the P_c.

摘要

本文介绍了评估土耳其矿业 (TMI) 中使用的几种传送带系统 (CBS) 的功耗的不同方法。根据每个 CBS 的操作特性，直接在电动头滑轮上测量功率消耗 (P _c , kW)。P _c是通过几种传统的、统计的和机器学习方法进行研究的。这项研究表明，DIN 22,101 可能是所研究的 CBS 最方便的常规方法。另一方面，基于非线性回归（NLR）和遗传表达编程（GEP）模型，提出了两种新的方法来设计和优化 P _c。