Tag: 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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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.
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Threshold Alarms vs ML: 4-Week Python CBM Migration
Compare threshold vs ML-based condition monitoring in Python. 4-week migration guide with FFT, LSTM anomaly detection, and live industrial examples.
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GNN for Multi-Component RUL: Graph Attention Beats Fixed Topology
Learn how Graph Attention Networks predict multi-component system failures better than fixed-topology GNNs. Attention mechanism key to RUL accuracy.
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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.