| With the rapid development of China's railway industry,the amount of data related to the railway has shown an explosive growth trend.The traditional means of data maintenance and management can no longer meet the needs of the railway industry.How to apply new information technologies such as cloud computing and big data to the field of railway train maintenance in our country to promote the railway train maintenance industry Development has become an important direction for the development of China's railway train maintenance industry in the future.Nowadays,the storage systems of maintenance-related data of the major train service depots are isolated from each other,the data integration and sharing are weak,and the platform for unified data management is lacking.And technically,the traditional railway maintenance system still uses the traditional database and data processing technology,data processing timeliness and availability is not strong,the lack of specialized technology and tool support for the application and deep analysis of big data,for data mining and utilization Stay in the primary stage.And with the continuous increase of the number of train operation in our country,the workload of the train station also increases day by day,which also puts forward higher requirements on the overhauling ability and work efficiency of the station.How to improve the capacity and efficiency of the station is Promote the train maintenance industry's core issues.Aiming at the above problems,this paper proposes a big data platform can be applied to the train maintenance.The main work and innovation lies in:(1)Aiming at the collection and storage of multi-type data of many types of intelligent maintenance equipment in the station section,a special configuration and transmission mechanism is proposed,which enables the platform to collect multiple types of data of multiple devices in a compatible and real-time manner and implement multiple types Data offload transmission and classification storage.(2)Combined with big data technology,the platform can provide technical and tool support for the mining and analysis of maintenance related data,which can make up for the shortcomings that the traditional maintenance industry is limited to the common statistical means for data analysis,so that the data can be deeply tapped and utilized and managed Who provide application-based data mining capabilities.(3)Aiming at the characteristics of flaw detection of hollow shaft flaw detector,a matching model of working flaw detector based on clustering algorithm is proposed,which improves the control ability and monitoring accuracy of flaw detector.(4)Aiming at the optimization of flaw detection workflow of hollow shaft flaw detector,a prediction model of working flaw detector based on machine learning algorithm is proposed.The working procedure of flaw detector optimization is optimized to improve the efficiency of flaw detector maintenance.This paper first surveys the development and present situation of railway maintenance,and summarizes the urgent need for the introduction of big data technology and "smart factory" in the field of railway maintenance.Secondly,according to the requirements and objective conditions of big data application in the field of railway maintenance,a set of big data platform architecture is designed.Then,with the platform,the design and verification of working state model and working result prediction model of hollow shaft flaw detection machine are carried out.After that,the platform has been functionally tested and performance tested to ensure the availability and stability of the platform and to ensure that the performance of the platform is sufficient to meet the needs of the current platform of the train maintenance industry.Finally,summarize the full text,clear the paper needs to be strengthened and perfect place,and put forward the tentative plan for the future research direction. |
PDF Full Text Request