Condition monitoring is the process of monitoring a parameter of condition in machinery, such as vibration, temperature, etc., to identify changes that are indicative of a developing fault. It is a major component of predictive maintenance, which allows maintenance to be scheduled or other actions to be taken to prevent consequential damages and avoid its consequences. Condition monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure.
Condition monitoring techniques are normally used on rotating equipment, auxiliary systems, and other machinery like belt-driven equipment, compressors, pumps, electric motors, internal combustion engines, and presses. Periodic inspection using non-destructive testing (NDT) techniques and fit for service (FFS) evaluation are used for static plant equipment such as steam boilers, piping, and heat exchangers.
The following list includes the main condition monitoring techniques applied in the industrial and transportation sectors:
- Condition monitoring overview
- Vibration analysis and diagnostics
- Lubricant analysis
- Acoustic emission
- Infrared thermography
- Ultrasound
- Oil condition sensors
- Motor condition monitoring and motor current signature analysis (MCSA)
- Model-based voltage and current systems (MBVI systems)
Condition monitoring software sends an alert whenever a change is detected in machine health, enabling maintenance technicians to immediately assess the situation and determine if corrective action is required. The proactive nature of condition monitoring is an innovative step forward on several levels for some manufacturers. First, plant personnel are safer, and thus, we are all collectively safer. Second, plant managers can prevent unplanned downtime due to machine failure while simultaneously making the most of planned maintenance downtime by servicing multiple machines and addressing all known problems at the same time.
Condition monitoring can lend itself to many benefits, including decreased maintenance costs, reduced downtime, extended asset life, and cost savings on prematurely changed resources. It helps maintenance teams make more informed decisions about performance optimization and maintenance needs. It also gives maintenance and reliability organizations the information they need to improve long-term asset health and to better their maintenance processes and practices.
