Prior knowledge-embedded first-layer interpretable paradigm for rail transit vehicle human–computer collaboration fault monitoring

Key Points

• Effective fault monitoring enhances human-computer collaboration, improving operational safety.
• The system utilizes a first-layer interpretable model, allowing real-time analysis of transit vehicle faults.
• Assessment involved knowledge-embedded approaches tailored for rail transit contexts, ensuring reliability of outcomes.
• Highlights the potential for real-world applications, suggesting further testing may solidify these findings.