yzbbj/Sequence-to-Sequence-Classification-Using-LSTM
To find out when was the time that the fault occurs and make predictions to find out early faults,you can use a LSTM network to classify each time step of sequence data
This helps operations engineers and maintenance teams predict when equipment faults are likely to occur by analyzing historical sensor data over time. You input sequences of sensor readings or other time-series data, and it outputs a classification for each time step, indicating whether a fault is present or imminent. This allows for early fault detection and proactive maintenance planning.
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Use this if you need to classify time-series data at each step to identify patterns indicating equipment faults or other critical events.
Not ideal if you are looking for a general-purpose anomaly detection system without a focus on sequential classification or if your data is not time-series based.
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May 15, 2022
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