Course Description
Vibration analysis produces rich, high-frequency data that is ideally suited to artificial intelligence. This course shows how AI and machine learning augment traditional vibration analysis — automating fault detection, improving diagnostic accuracy, and enabling prognosis of remaining useful life.
Participants learn how AI models are trained on vibration spectra and waveforms to detect and classify faults automatically, how anomaly detection flags emerging problems, and how AI complements the skilled analyst rather than replacing them. The course bridges established vibration analysis practice (ISO 18436-2) with modern machine learning.
What you will achieve
By the end of this training course, participants will be able to:
- Explain how AI augments vibration analysis
- Prepare vibration data (spectra, waveforms, envelope) for machine learning
- Apply anomaly detection to vibration data
- Train models to classify vibration fault types
- Estimate remaining useful life from vibration trends
- Integrate AI vibration tools into a condition monitoring program
- Interpret and validate AI vibration diagnostics
- Understand the limits of AI in vibration analysis
How the course is delivered
The course combines vibration analysis domain knowledge with practical machine learning applied to real vibration datasets. Participants work through fault classification and anomaly detection on spectra and waveforms.
Designed for vibration professionals without a data science background, focusing on applied AI that complements analyst expertise.
Designed for
This training course is ideal for:
- Vibration analysts and condition monitoring specialists
- Reliability engineers using vibration data
- Analysts extending skills with AI
- CM program managers
- Engineers bridging vibration and data science
Daily programme
- Review of vibration analysis principles
- Why vibration data suits AI
- Types of machine learning for vibration
- AI as analyst augmentation
- Preparing spectra, waveforms, envelope data
- Feature extraction from vibration signals
- Data quality and labelling
- Building the training set
- Anomaly detection in vibration data
- Automated fault classification
- Bearing, imbalance, misalignment detection
- Remaining useful life from vibration trends
- Integrating AI vibration tools into CM
- Validating AI diagnostics
- Limits and pitfalls
- Case study workshop and review
Certification & accreditation
BII Certificate of Completion
BII Certificate of Completion Upon successful completion, participants receive a BII Development Institute Certificate of Completion with a unique reference code that is independently verifiable. Our certificates are recognised internationally and reflect successful completion of your chosen programme.
