In the previous posts, we saw the vibration increase that was associated with anomaly generation. We also saw the Alerts List with their Contributing Factors. This post reveals the scatterplots associated with the contributing factors, where the training data on the CF are shown in green, and the deviations are shown in red. Clearly, there are significant shifts in the scatter plot data (shown in red) during the Alert period. These plots are used by data analysts and the Anomaly Detection Engine (ADE) to find the parameters (tags) with significant deviations from ‘normal’ condition for a machine, sensor, or system. The contributing parameters deviation plots and scores help determine the highest probability failure mode from the Failure Mode and Effects Analysis (FMEA) for the machine or system.
Want to learn more? Contact Mesa Associates and ask about our Artificial Intelligence and Machine Learning hydro generation applications today!