Technical Blog
Automating Vibration Analysis to Support Condition-Based Maintenance
Automating vibration analysis holds significant potential for improving condition-based maintenance (CBM) programs, but the path to full automation is not without its challenges. Vibration analysis has been a trusted method for understanding the health of rotating machinery for years, offering insights into machine performance without requiring deep knowledge of the process conditions. However, scaling and automating this process introduces new levels of complexity.
Here are some key insights and takeaways on the benefits, challenges, and future potential of automating vibration analysis for CBM.
Vibration Measurements: A Powerful Diagnostic Tool
Vibration monitoring allows companies to detect potential equipment failures early, preventing unplanned downtime. Vibration data is reliable, easy to collect, and widely applicable across machinery types. Standards like ISO 10816 provide useful guidelines for interpreting these measurements, and vibration analyzers are easy to transport and use in the field.
However, despite these benefits, deciding which parameters to monitor and at what frequency remains a challenge. Understanding the weaknesses of the system and establishing appropriate thresholds—whether static or dynamic—is essential for successful vibration monitoring.
.
Data Complexity: From Simple Metrics to Advanced Analysis
Vibration data can be analyzed at various levels of complexity.
- Level 1: Basic Metrics – Simple measurements like root-mean-square (RMS) and peak-to-peak values quantify overall vibration but lack specificity about failure sources.
- Level 2: Spectrum Analysis – Fast Fourier Transform (FFT) analysis highlights vibration frequencies, helping identify particular faults in components like gears and bearings.
- Level 3: Intrinsic Parameters – Advanced techniques, such as Operational Modal Analysis (OMA), reveal machinery-specific characteristics, essential for understanding complex vibration patterns
However, as the complexity of data analysis increases, so does the difficulty of maintaining consistency. Factors like calibration, measurement location, probe contact, and sampling rate all influence the quality of the data collected, making consistency a key challenge in automated vibration monitoring.
Automation: A Requirement for Efficiency
As the need for scalability grows, so does the need for automating vibration analysis. Manual data collection during route-based monitoring can be inconsistent, leading to missed trends or misinterpretations. By implementing fixed vibration monitoring systems, the process becomes more reliable and efficient, reducing the need for field technicians to physically walk the plant.
Automating vibration analysis also reduces risk exposure. With automation in place, condition monitoring analysts can focus on analyzing the data rather than collecting it, improving decision-making while reducing time spent on manual tasks.
Wireless Vibration Sensors: Opportunities and Challenges
The introduction of wireless sensors into vibration monitoring presents new opportunities. Wireless sensors mitigate the cons of manual vibration routes and enable automation. However, choosing the right wireless technology can be a challenge, and can become a story of compromise. For example, increasing the frequency of data acquisition might improve accuracy, but at the cost of reduced battery life. It is also important to make sure the sensor output matches your expectations (RMS or waveform / spectrum).
The Future of Vibration Analysis: Machine Learning
As vibration monitoring systems become more advanced, the ability to capture and analyze more data will improve. Machine learning models and predictive analytics hold promise for enabling systems to learn from previous failures and automatically adjust thresholds. However, this future isn’t without its challenges. One of the most significant obstacles is the limited availability of existing failure data needed to train these models. However, one way to combat this is by leveraging a hybrid workflow, which blends generalized models with equipment-specific adaptations:
- Data Collection and Extraction: The process begins by leveraging a generalized model, and combining it with features from literature, industry experience and knowledge, as well as R&D data, in lieu of historical operating data.
- Model in Training: Using both collected and real-time data, models are trained to recognize normal and abnormal vibration signatures.
- Ongoing Model Learning: As more sensors are added, additional failure data and anomalies are detected. The feedback loop to the model is essential to improve model accuracy.
Over time, this approach improves diagnostic precision and reduces false alarms.
Conclusions and Recommendations
Automation in vibration analysis holds immense potential for condition-based maintenance, but it requires a thoughtful approach. As companies integrate vibration analysis into their operations, they should remember these top recommendations to maximize reliability and return on investment:
- Optimize Sensor Selection for the Application: Choose sensors that provide data aligned with your diagnostic needs and strike a balance between data frequency and battery life for wireless options.
- Prioritize Consistent Sensor Placement and Calibration: Ensure reliable and repeatable data by standardizing sensor installation, calibration, and configuration.
- Implement Layered Data Analysis: Use a multi-level data processing approach (from basic metrics to advanced analysis) to capture meaningful insights at each stage of machinery health.
- Leverage Machine Learning for Dynamic Thresholds: Dynamic thresholds and anomaly detection through machine learning improve fault detection accuracy, especially in varying operating conditions.
- Treat Vibration Analysis as a Reliability Tool, Not a Standalone Solution: Automating vibration analysis should complement a broader reliability strategy, enhancing an already robust program rather than compensating for gaps in other areas.
Related Cognascents Solutions
At Cognascents, we have the expertise to meet your needs. Explore the variety of related services we offer and discover how our tailored approach can support your business.
Our mission is to empower our clients with innovative solutions that enhance process safety, reliability, asset integrity, and technical business acumen. To elevate your engineering solutions, please contact us today.
