Tag: Vibration Analysis
-
FFT Shows No Peaks: 4 Sensor Setup Mistakes That Kill Spectra
Diagnose why your FFT shows no peaks with these 4 critical sensor setup mistakes. Learn proper sampling rates, gain settings, and mounting techniques.
-
CBM Migration Guide: Scheduled to Condition-Based
CBM migration forces you to rethink alerting, data pipelines, and ops workflows โ not just swap sensors. Here's what actually breaks and how to fix it.
-
FFT Analysis for Bearing Fault Detection: 2048-Point Setup
Master FFT-based bearing fault diagnosis: 2048-point setup, frequency bin analysis, and practical vibration signal processing for predictive maintenance
-
CWRU Bearing Dataset: End-to-End PHM Portfolio Project
Build a complete PHM pipeline with CWRU bearing data: fault detection, feature engineering, and RUL prediction from raw vibration signals.
-
Gearbox Fault Classification: Why Voting Beat Stacking
Soft voting beat stacking by 0.7% on real gearbox fault data. Why simpler ensembles outperform complex ones in multi-fault PHM systems.
-
Spectral Kurtosis for Bearing Faults: Outperforming FFT
Spectral kurtosis caught bearing failure 3 weeks before FFT showed symptoms. When it works, when it fails, and what runs in production.
-
Envelope Analysis vs FFT for Bearing Fault Detection
Envelope analysis caught inner race faults FFT missed โ then nearly failed on outer race. Why band selection breaks or saves your diagnosis.
-
Feature Engineering for Predictive Maintenance: Health Indicators
Extract FFT peaks, RMS trends, and thermal gradients from vibration data for RUL predictionโfeatures that beat raw signals by 40% accuracy.