Vibration Signal Processing
Course Overview
This course explains the signal-processing techniques used to transform raw vibration measurements into reliable diagnostic information. It provides a practical understanding of sampling, filtering, FFT processing, spectral resolution, windowing, and advanced methods used in rotating machinery analysis.
Participants learn how incorrect acquisition and processing settings can hide actual machine faults or create misleading results. The course connects mathematical concepts with practical vibration analysis without requiring an advanced background in signal-processing theory.
Key Learning Objectives
Participants will learn how to:
- Configure vibration data acquisition correctly
- Prevent aliasing and improve signal quality
- Select appropriate sampling and frequency parameters
- Apply FFT, filtering, and windowing techniques
- Use advanced processing methods for machinery diagnostics
- Recognize processing errors and misleading vibration patterns
Course Content
- Analog and digital vibration signals
- Sampling rate and sampling duration
- Nyquist frequency and aliasing
- Anti-aliasing filters
- Frequency range and spectral resolution
- Time waveform characteristics
- FFT principles and practical application
- Spectral leakage and window functions
- Linear and exponential averaging
- Digital filtering techniques
- Power Spectral Density
- RMS, peak, crest factor, and kurtosis
- Envelope analysis and Hilbert transform concepts
- Time Synchronous Averaging
- Order tracking for variable-speed machinery
- Spectrograms and time-frequency analysis
- Cepstrum and sideband analysis
- Transient signal processing
- Data-quality verification
- Practical signal-processing exercises
Who Should Attend?
Vibration analysts, instrumentation engineers, condition monitoring specialists, reliability engineers, researchers, and professionals who need a deeper understanding of vibration data acquisition and processing.