Category: CBM/PHM
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Transformer vs CNN-LSTM: CWRU Bearing 96% vs 92% Accuracy
Compare Transformer vs CNN-LSTM for bearing fault detection on CWRU dataset. Discover which architecture achieves 96% accuracy and why it wins.
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FFT vs Envelope Analysis: Bearing Fault Trade-offs
Compare FFT and envelope analysis for bearing fault detection. Discover which method excels at catching early-stage defects in noisy industrial environments.
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Transfer Learning CWRU to Custom Bearings: 89% to 67% Drop Fix
Transfer learning CWRU bearings to custom hardware hits 67% accuracy? Learn the domain gap fix with synthetic data and fine-tuning strategies.
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FFT vs CWT vs Wavelet Packet: CWRU Bearing Speed Test
Compare FFT, CWT, and Wavelet Packet on CWRU bearing data across speeds. Discover which method wins for fault detection under varying RPMs.
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Predictive Maintenance Python Tutorial: FFT Pipeline
Build a Python FFT pipeline for predictive maintenance with NumPy and SciPy. Detect bearing faults from vibration signals using spectral analysis.
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LSTM vs GRU vs Transformer RUL: NASA CMAPSS Memory Test
Compare LSTM, GRU, and Transformer models for RUL prediction on NASA CMAPSS dataset. Which architecture wins the turbofan memory test?
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FFT vs Welch: Legacy Vibration Code Migration Pitfalls
Migrated legacy FFT code to scipy.signal.welch โ false alarms tripled. Here's the window scaling trap that broke production thresholds.
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1D-CNN Bearing Fault Classifier: CWRU 3-Sensor Pipeline
Build a 1D-CNN bearing fault classifier using CWRU dataset's 3-sensor vibration data. Complete PyTorch pipeline with preprocessing and evaluation.