Condition monitoring (CM) uses Industrial Internet of Things (IIoT) sensors and other tools to continuously track machine health and measure vibration levels, temperature, or other measurements. When something changes in the machine, these tools trigger an immediate alert notification, letting maintenance teams act before the asset potentially fails.
Vibration sensors are particularly important condition monitoring tools for identifying the four most common rotating machinery faults: imbalance, looseness, bearing damage, and misalignment.
Condition monitoring using vibration sensors is a scalable way to monitor and gather data from a broad portfolio of production critical and semi-critical assets.
Machine condition monitoring opens the door to predictive maintenance strategies like condition-based maintenance (CBM). Condition-based maintenance studies the health of specific machines and the likelihood of their failures, then uses that real-world data to make maintenance decisions. That stands in contrast to preventive maintenance, or calendar-based maintenance, where work is performed whether it’s necessary or not.
How Does Condition Monitoring Work?
Condition monitoring uses networks of connected sensors, gateways, and software, to collect, process, and analyze machine data. The combined connectivity creates an integrated system that lets maintenance teams collaborate and make decisions from anywhere in what’s called Remote Condition Monitoring.
Remote Condition Monitoring happens when wireless condition monitoring sensors pair with cloud-based software, so technicians and other reliability professionals can access the data remotely using a computer, mobile phone, or laptop.
Benefits of Remote Condition Monitoring
Remote Condition Monitoring lets maintenance teams prioritize and optimize their maintenance schedules based on asset health. Wireless and/or wired sensors placed on machinery can monitor asset health continuously, and if conditions change, an email is automatically sent to a designated maintenance team member. Armed with Remote Condition Monitoring, teams can make data-based decisions.
Remote Condition Monitoring Benefits:
- Early detection of machine problems
- Quick, data-based decisions
- Moves maintenance teams to condition-based maintenance
- Improves maintenance planning to prevent downtime
- Reduces costs tied to maintenance, inventory, and production
- Increases asset lifecycle and ROI
Screening and Analysis Vibration Sensors
All machines vibrate, but excess vibration can cause irreversible damage to machinery and associated components. Under extreme circumstances, vibration can cause a catastrophic failure that shuts down facilities or stops production.
Maintenance teams often implement a combination of two different styles of vibration sensors. A screening vibration sensor alerts maintenance teams to simple vibration changes. And a vibration analysis sensor allows for closer study of vibration frequencies.
Screening vibration sensors offer an important good/bad look at machine health. Analysis vibration sensors work best for finding the most common faults, determining the fault severity, enabling data analysis, and suggesting next steps.
Constantly screening for changes in machine health and analyzing vibration sensor data is especially critical with rotating machinery.
Utilizing the P-F Curve
A variety of condition monitoring sensors, tools, and techniques are used to track and trend the equipment health, from oil analysis and vibration analysis to ultrasound. The goal of using different conditioning monitoring techniques is to extend equipment lifespan as long as possible. The earlier the fault is caught, the more likely the machinery can be restored to its original state.
The potential failure curve, or P-F curve, portrays a machine’s gradual failure over time. The P-F curve is a valuable tool for deciding which condition monitoring technique (modality) to use based on the machine’s expected problems. If a maintenance professional knows what the earliest sign of trouble looks like for a specific asset, they can start searching for those signs of failure using the right tools.
Three standard condition monitoring techniques used to detect potential faults:
- Vibration analysis is used in condition monitoring and to detect mechanical faults in rotating equipment. Vibration analysis using a vibration sensor can be applied to a wide range of rotating machinery and reveal signs of imbalance, misalignment, looseness, and bearing failure.
- Infrared thermography detects machinery temperature changes by studying patterns, like increased motor heat or an abnormally low temperature. Thermography can detect shaft misalignment, gearbox issues, and belt problems.
- Ultrasound uses high-frequency waves to monitor and detect machine defects like cavitation, leaks, and parts seating.
Choosing the Right Type of Vibration Sensor
Machine vibration screening and analysis using sensors are vital technology for successfully implementing condition monitoring and predictive maintenance programs. Different types of vibration sensors offer different capabilities, but they typically involve an accelerometer containing a piezoelectric crystal that senses mechanical vibrations inside an asset.
The crystal changes mechanical movement to an electrical signal which is then amplified and transmitted via a cable or wirelessly. Piezoelectric sensors are known for their hardiness which enables them to function in industrial settings.
To choose the most suitable sensors, an organization should determine how they will fit into their existing technology and maintenance and reliability program, including which assets to monitor and why. An excellent way to determine this is by performing an asset criticality analysis.
Determine Which Machines Need Monitoring with an Asset Criticality Assessment
An asset criticality assessment helps verify which machines are production critical based on business value and overall operations should they fail. The analysis process helps eliminate assumptions about an asset’s importance and instead relies on empirical data, not guesswork.
During the asset criticality assessment, various stakeholders in the organization work together to determine criteria for ranking the assets (1 to 5). With a diverse group, maintenance teams build consensus and cement the asset criticality assessment outcomes. Once ranked, the machinery is grouped and classified as a star, critical, semi-critical, or non-critical asset.
Remote Condition Monitoring Services
Developing a Remote Condition Monitoring program takes time and effort. Starting with a small pilot program can ease the learning curve. Outside experts can also help with implementation and training.
Fluke Reliability has some of the world’s top experts available to help your team with our Remote Condition Monitoring service. We can help with expert data analysis, sensor configuration, commissioning, and installation, or help with understanding the principles of vibration monitoring and data analytics. Contact us to speak with a specialist.