Purpose-With the deepening integration of rail transit systems-encompassing urban rail,regional railways,trunk lines and medium-low capacity transportation-the four-network integration imposes higher demands on operat...Purpose-With the deepening integration of rail transit systems-encompassing urban rail,regional railways,trunk lines and medium-low capacity transportation-the four-network integration imposes higher demands on operation and maintenance systems regarding cross-modal coordination,full-element interconnectivity and dynamic responsiveness.Design/methodology/approach-This paper,based on policy directives and engineering practices,analyzes the operational maintenance characteristics of urban rail traction systems from perspectives including device interconnectivity and fault data mining.A non-intrusive high-frequency diagnostic device independent of vehicle control is proposed,informed by practical onboard operation experience.This innovation significantly enhances diagnostic accuracy for components requiring high sampling frequency,while integrating“Flash”storage with far greater capacity than conventional control chips.Findings-This article will systematically introduces the key points and diagnostic methods for typical faults in urban rail traction systems.Through rational diagnostic algorithms combined with high-precision,highstorage diagnostic instrumentation,the overall safety and reliability of urban rail traction systems have been improved.The proposed non-intrusive high-frequency diagnostic solution has been validated across multiple rail lines.Originality/value-This paper introduces an innovative non-intrusive diagnostic device with a dual-channel design for multi-system compatibility and a high-speed acquisition architecture enabling 400 kHz sampling.Its originality stems from the independent,high-fidelity capture of microsecond-level transient faults like IGBT shoot-through and pantograph arcing;Validated in operational environments,this approach provides a significant leap in diagnostic precision,directly enhancing traction system availability and operational safety by enabling precise fault localization and intelligent,adaptive protection strategies.展开更多
Purpose–This study aims to implement condition monitoring for urban rail train permanent magnet synchronous motors and inverter systems.Through the construction of a digital twin model,it performs fault diagnosis of ...Purpose–This study aims to implement condition monitoring for urban rail train permanent magnet synchronous motors and inverter systems.Through the construction of a digital twin model,it performs fault diagnosis of potential system failures,enabling rapid fault localization and protection.Design/methodology/approach–This research begins with a brief introduction to the structure and classification of permanent magnet synchronous motors(PMSMs),followed by a detailed analysis of their mathematical model.Subsequently,it thoroughly investigates the working principle of three-phase two-level inverters and the distribution of space voltage vectors.Based on the analysis of the main circuit topology,a digital twin model matching the external characteristics of the physical circuit is established using the model predictive control method,achieving accurate system simulation.Furthermore,through theoretical analysis and simulation verification of phase current characteristics under inverter switch tube faults,general patterns of phase currents under fault conditions are summarized.The established digital twin model is then employed to validate these patterns,confirming the model’s effectiveness in fault diagnosis.Findings–This study proposes a fault diagnosis method based on digital twins.Experimental and simulation results demonstrate that the established digital twin model can accurately simulate the external characteristics of the actual physical circuit,validating its effectiveness in inverter fault diagnosis.This approach offers practical value for condition monitoring in actual urban rail train systems.Originality/value–The study innovatively starts from a mathematical model and simulates the actual physical model through a virtual model,requiring only external characteristics to achieve system fault diagnosis,thereby enhancing diagnostic efficiency.展开更多
基金supported by the Fund of China Academy of Railway Sciences Corporation Limited(2023YJ342).
文摘Purpose-With the deepening integration of rail transit systems-encompassing urban rail,regional railways,trunk lines and medium-low capacity transportation-the four-network integration imposes higher demands on operation and maintenance systems regarding cross-modal coordination,full-element interconnectivity and dynamic responsiveness.Design/methodology/approach-This paper,based on policy directives and engineering practices,analyzes the operational maintenance characteristics of urban rail traction systems from perspectives including device interconnectivity and fault data mining.A non-intrusive high-frequency diagnostic device independent of vehicle control is proposed,informed by practical onboard operation experience.This innovation significantly enhances diagnostic accuracy for components requiring high sampling frequency,while integrating“Flash”storage with far greater capacity than conventional control chips.Findings-This article will systematically introduces the key points and diagnostic methods for typical faults in urban rail traction systems.Through rational diagnostic algorithms combined with high-precision,highstorage diagnostic instrumentation,the overall safety and reliability of urban rail traction systems have been improved.The proposed non-intrusive high-frequency diagnostic solution has been validated across multiple rail lines.Originality/value-This paper introduces an innovative non-intrusive diagnostic device with a dual-channel design for multi-system compatibility and a high-speed acquisition architecture enabling 400 kHz sampling.Its originality stems from the independent,high-fidelity capture of microsecond-level transient faults like IGBT shoot-through and pantograph arcing;Validated in operational environments,this approach provides a significant leap in diagnostic precision,directly enhancing traction system availability and operational safety by enabling precise fault localization and intelligent,adaptive protection strategies.
基金supported by the Fund of China State Railway Group Corporation Limited(L2023J001)the Fund of China Academy of Railway Sciences Corporation Limited(2023YJ247).
文摘Purpose–This study aims to implement condition monitoring for urban rail train permanent magnet synchronous motors and inverter systems.Through the construction of a digital twin model,it performs fault diagnosis of potential system failures,enabling rapid fault localization and protection.Design/methodology/approach–This research begins with a brief introduction to the structure and classification of permanent magnet synchronous motors(PMSMs),followed by a detailed analysis of their mathematical model.Subsequently,it thoroughly investigates the working principle of three-phase two-level inverters and the distribution of space voltage vectors.Based on the analysis of the main circuit topology,a digital twin model matching the external characteristics of the physical circuit is established using the model predictive control method,achieving accurate system simulation.Furthermore,through theoretical analysis and simulation verification of phase current characteristics under inverter switch tube faults,general patterns of phase currents under fault conditions are summarized.The established digital twin model is then employed to validate these patterns,confirming the model’s effectiveness in fault diagnosis.Findings–This study proposes a fault diagnosis method based on digital twins.Experimental and simulation results demonstrate that the established digital twin model can accurately simulate the external characteristics of the actual physical circuit,validating its effectiveness in inverter fault diagnosis.This approach offers practical value for condition monitoring in actual urban rail train systems.Originality/value–The study innovatively starts from a mathematical model and simulates the actual physical model through a virtual model,requiring only external characteristics to achieve system fault diagnosis,thereby enhancing diagnostic efficiency.
