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Road-quality classification and motion tracking with inertial sensors in the deep underground mine

EasyChair Preprint no. 2299

12 pagesDate: January 2, 2020


For many years now the mining industry has seen boost in exploring and developing the systems for monitoring operational parameters of mining machines, in particular of load-haul-dumping machines. Therefore, further researches on algorithmics have also advanced dynamically regarding effective performance management as well as predictive maintenance. Nonetheless, the issue of road conditions is still being neglected. That issue has substantial impact on both the overall operator’s convenience, their performance and machinery reliability, especially its construction node and tyres damages. Moreover, such negligence pertains also to the maintenance of mine infrastructure, including the network of passages. The paper explains the use of the portable inertial measurement unit (IMU) in evaluating road conditions in the deep underground mine. The detailed descriptions of the road quality classification procedure and bump detection have been included. The paper outlines the basic method of tracking motion trajectory of vehicles and suggests the method of visualisation the results of the road conditions evaluation. This paper covers the sample results collected by the measurements unit in the deep underground mine.

Keyphrases: Bump Detection, IMU, Load-Haul-Dumping Machines, motion tracking, Road-Quality Classification

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Paweł Stefaniak and Dawid Gawelski and Sergii Anufriiev and Paweł Śliwiński},
  title = {Road-quality classification and motion tracking with inertial sensors in the deep underground mine},
  howpublished = {EasyChair Preprint no. 2299},

  year = {EasyChair, 2020}}
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