Predictive maintenance is essential for the implementation of an innovative and efficient structural health monitoring strategy.Models capable of accurately interpreting new data automatically collected by suitably pl...Predictive maintenance is essential for the implementation of an innovative and efficient structural health monitoring strategy.Models capable of accurately interpreting new data automatically collected by suitably placed sensors to assess the state of the infrastructure represent a fundamental step,particularly for the railway sector,whose safe and continuous operation plays a strategic role in the well-being and development of nations.In this scenario,the benefits of a digital twin of a bonded insu-lated rail joint(IRJ)with the predictive capabilities of advanced classification algorithms based on artificial intelligence have been explored.The digital model provides an accurate mechanical response of the infrastructure as a pair of wheels passes over the joint.As bolt preload conditions vary,four structural health classes were identified for the joint.Two parameters,i.e.gap value and vertical displacement,which are strongly correlated with bolt preload,are used in different combinations to train and test five predictive classifiers.Their classification effectiveness was assessed using several performance indica-tors.Finally,we compared the IRJ condition predictions of two trained classifiers with the available data,confirming their high accuracy.The approach presented provides an interesting solution for future predictive tools in SHM especially in the case of complex systems such as railways where the vehicle-infrastructure interaction is complex and always time varying.展开更多
Charge dynamics at interfaces in high voltage direct current(HVDC)cable joints consisting of cable,joint insulation and lubricant may have an impact on the overall joint reliability.Although interactions between diffe...Charge dynamics at interfaces in high voltage direct current(HVDC)cable joints consisting of cable,joint insulation and lubricant may have an impact on the overall joint reliability.Although interactions between different lubricants and the joint insulation have been studied in recent years,the effect of lubricant diffusion on the electrical properties and charge dynamics at interfaces remains unclear and is therefore investigated in this paper.Different lubricants were applied at the interface of crosslinked polyethylene(XLPE)and silicone rubber(SIR)samples,and mass,electrical conductivity,and space charge were measured over a 96 h ageing period.The mass of the samples was found to exhibit nonmonotonic behaviour,indicating complex interactions between the lubricant and material.XLPE experiences a decrease in conductivity while there is an increase in conductivity for SIR,which is linked to the migration of lubricant and therefore changes in trap distribution.Space charge measurements indicate changes in trap characteristics,which depend strongly on the used type of lubricant.The findings highlight that lubricant diffusion affects both the bulk properties and charge accumulation at the interface,and underline the large effect of the type of lubricant.These results are crucial for understanding the long-term performance of cable joints and insulating materials in HVDC cable systems.展开更多
基金the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4-Call for tender No. 3138 of 16/12/2021 of Italian Ministry of University and Research funded by the European Union-Next Generation EU. Award Number: Project code CN00000023Concession Decree No. 1033 of 17/06/2022 adopted by the Italian Ministry of University and Research, CUP D93C22000400001, “Sustainable Mobility Center” (CNMS). Spoke 4-Rail Transportation
文摘Predictive maintenance is essential for the implementation of an innovative and efficient structural health monitoring strategy.Models capable of accurately interpreting new data automatically collected by suitably placed sensors to assess the state of the infrastructure represent a fundamental step,particularly for the railway sector,whose safe and continuous operation plays a strategic role in the well-being and development of nations.In this scenario,the benefits of a digital twin of a bonded insu-lated rail joint(IRJ)with the predictive capabilities of advanced classification algorithms based on artificial intelligence have been explored.The digital model provides an accurate mechanical response of the infrastructure as a pair of wheels passes over the joint.As bolt preload conditions vary,four structural health classes were identified for the joint.Two parameters,i.e.gap value and vertical displacement,which are strongly correlated with bolt preload,are used in different combinations to train and test five predictive classifiers.Their classification effectiveness was assessed using several performance indica-tors.Finally,we compared the IRJ condition predictions of two trained classifiers with the available data,confirming their high accuracy.The approach presented provides an interesting solution for future predictive tools in SHM especially in the case of complex systems such as railways where the vehicle-infrastructure interaction is complex and always time varying.
文摘Charge dynamics at interfaces in high voltage direct current(HVDC)cable joints consisting of cable,joint insulation and lubricant may have an impact on the overall joint reliability.Although interactions between different lubricants and the joint insulation have been studied in recent years,the effect of lubricant diffusion on the electrical properties and charge dynamics at interfaces remains unclear and is therefore investigated in this paper.Different lubricants were applied at the interface of crosslinked polyethylene(XLPE)and silicone rubber(SIR)samples,and mass,electrical conductivity,and space charge were measured over a 96 h ageing period.The mass of the samples was found to exhibit nonmonotonic behaviour,indicating complex interactions between the lubricant and material.XLPE experiences a decrease in conductivity while there is an increase in conductivity for SIR,which is linked to the migration of lubricant and therefore changes in trap distribution.Space charge measurements indicate changes in trap characteristics,which depend strongly on the used type of lubricant.The findings highlight that lubricant diffusion affects both the bulk properties and charge accumulation at the interface,and underline the large effect of the type of lubricant.These results are crucial for understanding the long-term performance of cable joints and insulating materials in HVDC cable systems.
