Online monitoring, diagnostic and predictive analytics data system for locomotive-hauled passenger coach equipment
Late detection of equipment malfunctions and pre-failure conditions of passenger coach equipment can lead to failures en route, schedule delays, increased repair time and cost. It also potentially reduces passenger safety and comfort. Meanwhile, standard equipment of modern passenger coaches collects and transmits to the control system a significant number of telemetry parameters and self-diagnosis results, which are used in control algorithms but usually are not analyzed by the train personnel or maintenance personnel. The proposed solution allows: 1. To collect and store all important telemetry parameters, self-diagnostic results, and a list of installed coach equipment on the standard coach equipment. Data of each coach is stored from the moment of its connection to the system throughout its entire lifecycle (up to 28 years). Data is stored and processed in in-house data center. A server can be deployed in the customer’s corporate network, if required. 2. To transmit telemetry data to a remote server using GSM in real-time (data is transmitted minutely, and if there is no network coverage, it is accumulated and transmitted later) or via flash drive retrospectively. 3. To analyze automatically incoming data in real-time to detect equipment malfunctions, pre-failure conditions, and incidents that can threaten passenger safety and comfort. Both data processing algorithms and self-learning mathematical models are used. 4. To monitor automatically the condition of thousands of rolling stock units at once by means of detailed information and visualized telemetry diagrams of each particular coach. 5. To inform users about detected malfunctions and recommended actions anywhere in the world via a web interface without installing specialized software. 6. To create tools for manual telemetry analysis to identify the root causes of detected malfunctions, determine necessary corrective actions, and to improve the design of coach equipment (also in the web interface). 7. To generate, route, and control the execution of requests for troubleshooting. 8. To generate reports and diagrams using the entire volume of collected big data.
Artificial Intelligence And Digital Services
Big data storage and analysis
Start of the trial period: 2023. Completion of the trial period for the Online Data System “Passenger Coaches Condition Monitoring” – December 2024 (planned). Commercial operation of the Onlina Data System “Passenger Coaches Condition Monitoring” – January 2025 (planned).
During the trial period: In cooperation with the largest passenger coach operators – depots in Samara, Adler (trains on various routes), Sevastopol and Simferopol. A similar data system was developed by KSC IT for the “Ivolga 3.0” electric trains’ equipment in cooperation with the Moscow service company for electric trains maintenance. In commercial operation – all regions of Russia where locomotive-hauled coaches and “Ivolga 3.0” electric trains produced by CJSC “Transmashholding” are used. When scaling the Practice to the rolling stock of BRICS countries – their territories.
Competitive advantages There are no direct competitors for passenger coaches. Still there are competitive advantages over indirect competitors (for example, existing telemetry analysis solutions). Technological advantages (also compared to Siemens train solutions): • use of standard coach equipment without retrofitting of the rolling stock; • ability to transmit and analyze data in real-time; • ability to monitor the composition of coach equipment, to carry out its replacement and ensure its operability; • ability to perform mass observation of telemetry; • auto-detection of equipment malfunctions and pre-failure conditions; • ability to adjust existing and develop new tools for automated telemetry analysis; • use of self-learning mathematical models that evaluate Health Index of the equipment that represents its current and predicted condition; • availability of data to all participants of the coach lifecycle via a web interface; • centralized storage and processing of big data for the entire period of rolling stock use; • interoperability with external information systems of carriers, depots, and manufacturers; • ability to analyze big data for rolling stock maintenance purposes and management reporting. Market advantages: - consideration and solving of key user problems; - full range of services – from the software development to connecting rolling stock to the system and technical support; - effective economic model; - ability to scale to other types of rolling stock (metros, trams, buses, rail buses, high-speed transport). - ability to develop similar solutions for rolling stock of Member states of BRICS: to analyze the composition of equipment and available telemetry free of charge to determine project implementation timelines.
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Patent for an invention RU 2 770 948 C1 Passenger coach electrical equipment complex. Rightholder: KSC Elcom; Patent for an invention No. 2707423 Method and system of diagnostics of industrial object. Rightholder: Clover Group Patent for utility model No. 213716 Interface and communication converter of railway car. Rightholder: KSC Elcom; Certificate of state registration of computer program No. 2022613760 SmartMaintenance. Rightholder: Clover Group; and others. Generated Intellectual Property: Certificate of state registration of computer program No. 2023680041 Automated information system for monitoring the condition of passenger cars. Rightholder: KSC Elcom
