Cloud model for risk monitoring of mining electric traction rubber-wheel vehicles

With the emergence of the electric era, electric traction rubber-wheel vehicles are increasingly replacing traditional rubber wheel vehicles. However, one significant obstacle hindering their widespread adoption is the issue of risk control. In order to effectively monitor the risk status of electric traction rubber-wheel vehicles in mining environments, a comprehensive approach was developed by integrating relevant standards, literature research findings, and existing monitoring methods. This approach clarifies the path of risk evolution, selects appropriate monitoring indicators, determines low, medium and high-risk evaluation domains, and establishes a rating index system for assessing risks. By considering both the probability of triggering events along with their potential severity consequences, a weighted comprehensive cloud model has been constructed. Simulation results from various scenarios demonstrate that this model can intuitively and reasonably reflect the level of risk within vehicle systems while also allowing for comparisons between different scenarios. It is important to note that mine environments pose greater dangers compared to daily harsh environments. Sensitivity analysis on key indices reveals that gas concentration levels, battery temperature fluctuations and ambient temperature have a significant impact on overall system risk. Furthermore, when battery temperature interacts with gas concentration levels simultaneously it leads to an even more pronounced influence on system risk states. In the future, as operation monitoring data becomes standardized and increases in volume over time, additional risk factors will gradually be incorporated into the index system resulting in improvements to its applicability while optimizing performance.