yzbbj/Fault-prognosis-using-LSTM-and-CNN
Fault prognosis using LSTM and CNN
This tool helps maintenance engineers and operations managers predict when rotating machinery, like industrial bearings, are likely to fail. By analyzing vibration sensor data, it classifies the type of potential fault, providing early warnings to schedule maintenance proactively and avoid unexpected downtime.
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Use this if you manage industrial machinery and need to predict specific bearing faults based on vibration data to optimize maintenance schedules.
Not ideal if you are looking for a general-purpose anomaly detection tool for various sensor types beyond mechanical vibration.
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MATLAB
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Last pushed
May 15, 2022
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