Abstract

<div class="section abstract"><div class="htmlview paragraph">Mining dozers are heavy-duty machines that operate in harshenvironments and under extreme loads. The durability of their powertraincomponents is critical for their performance and reliability. To ensure thedurability of these components, they need to be tested under realisticoperating conditions. However, field testing is time-consuming, costly andoften impractical due to the limited availability of test sites and machines.Therefore, there is a need to develop an accelerated durability cycle that cansimulate the field conditions in a laboratory setting. This paper presents amethodology to develop an accelerated powertrain durability cycle for miningdozers based on the integration of customer usage patterns and road load data.</div><div class="htmlview paragraph">The methodology consists of the following steps: system study to identifythe powertrain components and their failure modes; instrumentation of arepresentative mining dozer with sensors and data acquisition system; datacollection from field testing for mining, ripping and dozing operations;data processing for usage pattern analysis and road load extraction; accelerated duty cycle creation using customer usage correlation data andfatigue damage models. The methodology was applied to a mining dozer model andthe results showed that the accelerated cycle can reproduce the field damage ina shorter time and with less variability. The paper also discusses thechallenges and limitations of the methodology and suggests future directionsfor improvement. The paper contributes to the literature on durability testingof heavy-duty vehicles by proposing a novel approach that combines customerusage patterns and road load data to create an accelerated powertraindurability cycle for mining dozers.</div></div>

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