Category: CBM/PHM
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FFT vs Wavelet Transform: Which to Learn First for PHM
Compare FFT vs Wavelet Transform for predictive maintenance. Learn which signal processing method works best for machinery fault detection.
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SciPy FFT vs NumPy FFT: 2.3x Speed Gap at 50kHz
NumPy FFT ran 2.3x slower than SciPy on 50kHz bearing data. Here's the benchmark, the gotchas, and a one-line fix for your vibration pipeline.
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Cloud vs Edge PHM: $47K/Year Gap in 100-Sensor Setup
Compare TCO of cloud vs edge PHM architectures for 100-sensor deployments. $47K annual cost gap revealed through real-world analysis.
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CNN vs LSTM Bearing Fault Detection: 8x Training Speed Gap
CNNs train 8x faster than LSTMs on CWRU bearing data with identical 99.5% accuracy. See exact training times, memory usage, and when LSTMs still win.
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Real-Time FFT Pipeline: Vibration to Alert in 100 Lines
Build a streaming FFT pipeline in 100 lines: raw accelerometer data to bearing fault alerts in 2 seconds. No Kafka, just NumPy and signal processing.
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Digital Twin Hype vs Reality: Why Simple FFT Often Wins
A $50K digital twin missed a bearing fault that a $200 FFT setup caught instantly. Here's when physics-based models actually help vs marketing hype.
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FFT Vibration Analysis on Real Bearing Data: Python Setup
Learn FFT vibration analysis on real bearing data with Python. Step-by-step setup using NumPy, SciPy, and Matplotlib for predictive maintenance.
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Sensor Fusion Fails in Production: 3 Data Sync Issues
Vibration, temp, and current fused perfectly in testing โ then 200ms jitter killed production accuracy. Fix these 3 sync issues before deploy.