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Currently, bearings play a crucial role in intelligent operation and maintenance systems (Tajiani et al. in Reliab Eng Syst Saf 245, 2024). As these systems evolve towards greater digitalization and intelligence, the level of automation in maintenance equipment is continuously increasing (Karatug et al. in J Mar Eng Technol 24:12–21, 2025). For example, in high-speed trains, bearings are essential support components in the running gear of locomotives and rolling stock. he condition, dynamic performance, and longevity of bearings are vital to maintain the safe, stable, and efficient operation of trains (Li et al. in Fatigue Fract Eng Mater Struct 46:2112–2120, 2023). Bearing failures in the running gear during operation can lead to severe issues such as axle seizure, axle burning, or axle breakage, which may result in equipment failure and even pose safety risks to both passengers and vehicles (Guo et al. in Eng Appl Artif Intell 138, 2024; Li et al. in Fatigue Fract Eng Mater Struct 46:2112–2120, 2023). Additionally, the maintenance and repair efforts required are substantial, leading to significant losses. Therefore, research into bearing life prediction methods holds substantial practical value.

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Deep Learning Prediction for Bearing Remaining Useful Life

  • 章节

  • 发表日期：

    2025年

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  • Hui Liu,
  • Fang Cheng,
  • Yanfei Li

摘要

Currently, bearings play a crucial role in intelligent operation and maintenance systems (Tajiani et al. in Reliab Eng Syst Saf 245, 2024). As these systems evolve towards greater digitalization and intelligence, the level of automation in maintenance equipment is continuously increasing (Karatug et al. in J Mar Eng Technol 24:12–21, 2025). For example, in high-speed trains, bearings are essential support components in the running gear of locomotives and rolling stock. he condition, dynamic performance, and longevity of bearings are vital to maintain the safe, stable, and efficient operation of trains (Li et al. in Fatigue Fract Eng Mater Struct 46:2112–2120, 2023). Bearing failures in the running gear during operation can lead to severe issues such as axle seizure, axle burning, or axle breakage, which may result in equipment failure and even pose safety risks to both passengers and vehicles (Guo et al. in Eng Appl Artif Intell 138, 2024; Li et al. in Fatigue Fract Eng Mater Struct 46:2112–2120, 2023). Additionally, the maintenance and repair efforts required are substantial, leading to significant losses. Therefore, research into bearing life prediction methods holds substantial practical value.