What is Condition Monitoring?
Glossary of Condition Monitoring: Observation of Equipment Condition in Maintenance
Condition monitoring is at the forefront of modern maintenance and reliability engineering. This glossary provides in-depth definitions and practical context for key terms and technologies, drawing from ISO 17359, ICAO standards, and global best practices across industries.
Acoustic Analysis / Acoustic Monitoring
Definition:
Acoustic analysis is a condition monitoring technique that captures and interprets sound waves, both audible and ultrasonic, to assess the operational health of machinery. It utilizes sensors such as microphones and piezoelectric transducers to detect anomalies in noise patterns, which can indicate issues such as bearing wear, leaks, or electrical faults.
Applications:
- Audible Monitoring: Detects abnormal sounds (grinding, squealing) linked to mechanical wear.
- Ultrasonic Monitoring: Identifies high-frequency emissions from compressed air leaks, electrical arcing, or cavitation in pumps, often before issues become audible.
Industry Example:
In aviation, ultrasonic detectors are used to pinpoint fuel system leaks or early material cracks, enhancing safety and reliability.
Asset Criticality
Definition:
Asset criticality is the process of evaluating how essential an asset is to operations, safety, and business objectives. This assessment determines the level of monitoring and maintenance resources allocated to each asset.
Determination Factors:
- Function in process
- Consequence of failure (safety, environment, production)
- Redundancy and repair time
- Spare part availability
Best Practice:
High-criticality assets (e.g., main compressors, aircraft engines) warrant continuous, advanced monitoring. Lower-criticality assets may rely on periodic checks.
Baseline Values
Definition:
Baseline values are reference measurements recorded during ideal operating conditions, serving as the standard for detecting deviations.
How to Establish:
- During commissioning or post-overhaul
- Under stable, controlled conditions
- Capture parameters like vibration, temperature, pressure, and oil quality
Importance:
Comparing current data to baselines allows early detection of wear or faults and supports machine learning algorithms in predictive maintenance.
Condition-Based Maintenance (CbM)
Definition:
CbM is a maintenance strategy that triggers interventions based on actual asset health, as indicated by real-time or periodic monitoring, rather than fixed schedules.
Components:
- Sensors (vibration, temperature, oil, etc.)
- Analytics platforms
- Thresholds for alerting
Advantages:
Reduces unnecessary maintenance, cuts costs, and prevents unexpected failures, endorsed by ICAO and ISO 17359 for critical assets.
Example:
Aircraft components are replaced when data indicates wear, not merely at flight-hour intervals.
Condition Monitoring
Definition:
Condition monitoring is the ongoing process of capturing and analyzing key indicators (vibration, temperature, pressure, lubrication, acoustics) of machinery health to prevent failures and optimize performance.
Parameters & Technologies:
- Vibration, temperature, electrical current, oil quality, acoustic emissions
- Sensors, DAQ systems, analytics platforms
Compliance:
Guided by international standards such as ISO 17359 and ICAO maintenance protocols.
Example:
Jet engines are monitored for vibration anomalies to prevent blade failures.
Condition Monitoring Software
Definition:
A dedicated digital platform that aggregates, visualizes, and analyzes sensor data from industrial assets, enabling real-time diagnostics, alerts, and reporting.
Features:
- Data integration from multiple sensor types
- Real-time visualization dashboards
- Automated alerts and work orders
- Advanced analytics and AI
- Integration with EAM and CMMS systems
Use Case:
Centralized monitoring of thousands of assets, triggering maintenance only when warranted by real data.
Continuous Monitoring
Definition:
A method of real-time, uninterrupted tracking of equipment condition using permanently installed sensors. Essential for high-risk or critical assets.
Benefits:
- Instant detection of faults
- Eliminates missed transient issues
- Required in industries like aviation, nuclear power, and oil & gas
Example:
Wind turbine gearboxes are monitored continuously to detect bearing failures before breakdown.
Data Acquisition (DAQ) System
Definition:
DAQ systems are hardware/software solutions that collect, digitize, and transmit sensor data for condition monitoring.
Components:
- Sensor interfaces (analog/digital)
- Signal conditioning, A/D conversion
- Communication (Ethernet, wireless, serial)
Scalability:
From simple multi-channel loggers to enterprise systems integrating with SCADA, DCS, and cloud analytics.
Detection, Diagnosis, Prognosis, and Programme (The Four Pillars)
Framework:
- Detection: Early identification of abnormal conditions via sensors/analytics
- Diagnosis: Determining root cause (manual, algorithmic, AI)
- Prognosis: Predicting time to failure and intervention window
- Programme: Planning and executing maintenance actions
Value:
Optimizes maintenance, reduces downtime, and supports continuous improvement.
Electrical Monitoring
Definition:
Monitoring of electrical parameters (voltage, current, resistance, power factor) to assess equipment health and prevent failures.
Key Techniques:
- Current signature analysis for motors
- Insulation resistance for windings/cables
- Power quality for voltage/harmonics
Examples:
Detecting insulation breakdown in generator windings, preventing catastrophic short circuits.
Electromagnetic Measurement
Definition:
Non-destructive testing methods using magnetic fields (eddy current, magnetic flux leakage) to detect defects in metal components.
Techniques:
- Eddy current detects cracks/corrosion in conductive materials
- Magnetic flux leakage highlights pitting and cracks in ferromagnetic structures
Industry Use:
Critical in pipelines, storage tanks, aircraft, and railways.
Failure Mode
Definition:
A specific way in which an asset or component can fail. Classification of failure modes informs monitoring and maintenance strategies.
Types:
- Mechanical (bearing wear, misalignment)
- Electrical (insulation breakdown)
- Thermal (overheating)
Standards:
FMEA and ICAO MSG-3 are used for systematic failure mode analysis.
IIoT (Industrial Internet of Things)
Definition:
IIoT integrates networked sensors, edge devices, and cloud analytics for real-time monitoring, optimization, and automation of industrial assets.
Components:
- Smart wireless sensors
- Edge computing devices
- Cloud analytics platforms
- APIs for integration with enterprise systems
Benefits:
Enables scalable, remote monitoring and advanced predictive maintenance.
Additional Key Terms
Infrared Thermography
Non-contact measurement of temperature variations using infrared cameras to detect hot spots, insulation failures, or electrical overloads.
Lubricant Analysis (Oil Analysis)
Examination of lubricant properties (viscosity, contamination, wear particles) to assess machine wear and prevent failures.
Predictive Maintenance
Maintenance strategy that utilizes condition monitoring data and analytics to predict and prevent failures before they occur.
Root Cause Analysis (RCA)
A structured process for investigating and identifying the underlying causes of failures, guiding corrective actions.
Vibration Analysis
Measurement and interpretation of vibration levels and frequencies to detect imbalance, misalignment, or bearing defects in rotating equipment.
Practical Examples
- Aviation: Real-time monitoring of jet engine vibration and oil debris for early failure detection, in compliance with ICAO protocols.
- Manufacturing: Continuous monitoring of pumps and motors for temperature and vibration, preventing costly breakdowns.
- Energy: IIoT-based remote monitoring of wind turbines, enabling predictive maintenance and maximizing uptime.
References
- ISO 17359: Condition monitoring and diagnostics of machines – General guidelines
- ICAO Doc 9760: Maintenance procedures and safety management
- Reliabilityweb, Mobius Institute, Fluke Corporation, AVEVA, National Instruments
Condition monitoring is an evolving discipline, embracing advanced sensors, IIoT connectivity, and analytics, to deliver safer, more reliable, and cost-effective maintenance outcomes across all industries.
Frequently Asked Questions
- What is condition monitoring?
- Condition monitoring is the continuous or periodic measurement and analysis of parameters such as vibration, temperature, electrical current, and lubrication quality to assess the health of machinery. It enables early detection of faults and supports proactive maintenance interventions.
- How does condition-based maintenance (CbM) differ from preventive maintenance?
- Condition-based maintenance schedules interventions based on the actual health of equipment, as indicated by sensor data and analysis, intervening only when necessary. Preventive maintenance, by contrast, relies on fixed schedules or usage intervals regardless of equipment condition.
- What are baseline values in condition monitoring?
- Baseline values are reference measurements that represent the normal, healthy operating state of equipment. These are established when equipment is new or after major maintenance, providing a benchmark for detecting deviations and emerging faults.
- What is asset criticality, and how does it impact monitoring?
- Asset criticality is the assessment of how important an asset is to operational, safety, and business objectives. High-criticality assets receive the most advanced and frequent monitoring, ensuring that failures with major consequences are prevented or promptly addressed.
- What technologies are used in condition monitoring?
- Key technologies include vibration analysis, acoustic (ultrasonic and audible) monitoring, infrared thermography, oil analysis, electrical parameter monitoring, and electromagnetic (eddy current and magnetic flux) testing. Modern systems integrate these with data acquisition platforms and analytics software.
- What is the role of the Industrial Internet of Things (IIoT) in condition monitoring?
- IIoT enables real-time, remote monitoring of assets through smart sensors, edge devices, and cloud-based analytics, supporting scalable deployments and advanced predictive maintenance strategies across multiple sites.