Following the successful holding of the “2020 Urban Rail Transit Signal Operation and Maintenance and Innovation Seminar in Networked Operation Mode” on August 20, 2020, rail transit expert representatives came to visit and exchange opinions in Shanghai Rail Transit Longyang Road Base – CRSC Intelligent Operation and Maintenance Line Network Center in the morning of the next day.

A group of more than one hundred expert representatives observed the CRSC intelligent operation and maintenance platform of Shanghai Metro. The equipment management intelligent application platform jointly created by the Shanghai STDecaux Maintenance CRSC Branch Company and the Thales SEC Transport (TST) was also used as one of the main modules of CRSC intelligent operation and maintenance. Yang Jiagen, BIM leader of TST, explained the concept of equipment management holographic data to the expert representatives and demonstrated basic operations of the platform.

In the whole life cycle of equipment, APP is used to collect the information of equipment procurement, design, construction and operation and maintenance data, record the installation history, failure history, repair history and equipment location history during the whole equipment circulation process, extract index information in the operation process, and evaluate the health and use area of the equipment itself.

In addition, it analyzes and accumulates the law of equipment failure rate. In the future, through AI learning and big data analysis and other technologies, it will predict the trend of equipment failure rate, and then test the deduction of equipment service life, which provides data support for maintenance/retirement/renovation cost decision-making.

The dashed and solid lines represent the predicted and actual failure rates. By adjusting the attenuation rate of equipment, combined with the background model formula, the curve is predicted in a linked way to make the predicted curve infinitely close to the actual failure rate curve. The theoretical formula is used to predict failure laws, and then actual failure information is used to verify the theoretical formula, and the accuracy of the formula is continuously enhanced through big data positive and negative fitting calculations. The data base is accumulated for predicting the trend of equipment service life.

The display incorporates BIM visualization + information integration technology. Through the linkage of models, data and documents, the coherence of information capture is enhanced and the integration of business applications is improved. At the same time, it reflects TST’s innovation in the deep integration of data visualization and equipment visualization.

Once the concept of intelligent equipment management was introduced, it was recognized by the CRSC and expert representatives in all domains, and resonated with the attendees. Many leaders and experts believed that this application has long-term significance.
This time, the equipment management intelligent application platform developed by cooperating with CRSC has been strongly supported by the STDecaux Maintenance CRSC Branch Company. Combining the professional equipment research foundation and data of TST, and rich experience in the Shanghai project, the main information nodes (equipment technical parameter information, circulation information, failure information, on-site maintenance information, and environmental evaluation information) is extracted in the entire life cycle of the equipment for business integration with maintenance CRSC. The two parties jointly build an equipment management platform that provides intelligent services, realize the collaboration of related businesses between customers and suppliers and partial data linkage, provide more reliable technical support for the operation of the whole life cycle of equipment, and allow the aggregation of holographic data to cast light on an intelligent application prospect!

In the future, this part of function will be used as a sub-module of TST’s self-developed IOM (Intelligent Operation and Maintenance) system to help the company’s intelligent applications move forward!
Note: The above projects/station names/data are used for demonstration only, and they are not real information.