Fault Detection and Diagnostics
Fault Detection and Diagnostics is the process of identifying abnormal equipment behavior and determining the likely fault or affected component.
What this term means in maintenance
Fault Detection and Diagnostics is the process of identifying abnormal equipment behavior and determining the likely fault or affected component.
Detection and diagnosis
Fault detection identifies that behavior is abnormal.
Diagnostics identifies what fault is likely responsible.
Data sources
FDD may use:
- Sensors
- Alarms
- Trends
- Models
- Rules
- Vibration
- Temperature
- Pressure
- Electrical data
- Process performance
Practical example
A chiller FDD system identifies reduced heat-transfer performance and suggests condenser fouling.
Maintenance workflow
Useful FDD should create understandable findings, priority, evidence, and follow-up maintenance action.
Common mistake
Generating fault messages without confidence, context, or action guidance creates alarm noise.
Related concepts
Related maintenance terms
Keep exploring connected CMMS, reliability, and maintenance planning terms.
Condition Monitoring
Condition monitoring is the systematic collection and review of equipment-condition information to identify deterioration, abnormal operation, or developing failure.
Prognostics and Health Management
Prognostics and Health Management combines condition assessment, diagnostics, prediction, and decision support to manage equipment health and future failure risk.
Predictive Maintenance
Predictive maintenance uses condition data, trends, and analytical methods to estimate when equipment degradation may require maintenance.
Glossary FAQs
- What does FDD stand for?
FDD stands for Fault Detection and Diagnostics.
- What is the difference between detection and diagnosis?
Detection identifies abnormal behavior; diagnosis identifies the likely fault.
- What makes FDD useful?
Clear confidence, evidence, priority, context, and integration with maintenance action.