[Study on the characteristic parameter of oil spectrometric analysis]

Area of Science:

• Mechanical Engineering
• Analytical Chemistry
• Predictive Maintenance

Context:

• Effective fault diagnosis is crucial for mechanical equipment reliability.
• Traditional oil analysis methods have limitations in precise fault timing.
• Condition-based maintenance strategies require accurate failure prediction.

Purpose:

• To establish a novel mathematical model for fault diagnosis using oil spectrometric analysis.
• To combine laboratory experiments with real-world oil analysis for parameter confirmation.
• To accurately determine fault occurrence times and prevent severe equipment damage.

Summary:

• A new mathematics model for fault diagnosis based on oil spectrometric analysis was developed.
• Characteristic parameters were confirmed by integrating laboratory studies with equipment oil analysis.
• This approach aims to identify fault timing and avoid major failures.

Impact:

• Provides a strong academic and practical foundation for Reliability Centered Maintenance (RCM).
• Enhances the overall dependability and operational lifespan of mechanical equipment.
• Demonstrates high stability and veracity of the oil analysis characteristic parameters, proving its effectiveness.