BIM-based intelligent train whole-vehicle service life prediction method and system thereof

Abstract

The invention discloses a BIM-based intelligent train whole-vehicle service life prediction method, which comprises the steps of: acquiring static data and operating performance parameters of a wholetrain and components of the train; extracting a health indicator timing sequence of the components of the train; predicting to obtain remaining service life of the whole train and the components of the train, and correcting the remaining service life; and acquiring a final remaining service life prediction result of the whole train and the components. The invention further discloses a system for implementing the BIM-based intelligent train whole-vehicle service life prediction method. The BIM-based intelligent train whole-vehicle service life prediction method and the system can realize the monitoring of the train service state and external influencing factors, complete the modeling of uncertainty influence of the external factors on the remaining service life, provide comprehensive visualinformation, can realize the prediction of the remaining life of the train, effectively improve the service performance of the train, and have the advantages of high reliability, high applicability and comprehensive and precise evaluation.

Description

technical field [0001] The invention specifically relates to a BIM-based intelligent train service life prediction method and system thereof. Background technique [0002] With the development of economy and technology and the improvement of people's living standards, transportation has become one of the most important components of modern society. With the development of technology, my country's railway industry has also been greatly developed. [0003] Trains are the main transport vehicles in my country's railway industry. Under the current trend of "high-speed passenger transport and heavy-duty freight transport" in our country, high requirements are put forward for the safety performance of train operation. If a train breaks down while it is running, it can lead to dire consequences. The remaining service life prediction of the whole train can evaluate the health status of the train and provide a reference for managers to designate reasonable and feasible maintenance...

AI Technical Summary

Problems solved by technology

In the existing research, the prediction of environmental / load factors and the quantification of influence have not been included, so the remaining service life of the train cannot be accurately modeled, resulting in a decrease in prediction accuracy

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