Intelligent process anomaly detection and trend projection system

A system for providing an anomaly detection and trend projection comprising:

• one or more sensors coupled to one or more physical assets, the one or more physical assets configured to produce an output;
• one or more computers comprising one or more processors and one or more non-transitory computer readable media, the one or more non-transitory computer readable media including instructions stored thereon that when executed by the one or more processors configure the one or more computers to:
• receive one or more signals from the one or more sensors coupled to an asset comprising a plurality of components;
• determine if at least one of the plurality of components is a seasonal component by analyzing the signal for a variation in a trend that occurs within the signal at regular intervals during a lifespan of the asset;
• identify a degradation part of the signal and a normal part of the signal in response to a determination that the seasonal component was not detected within the plurality of components of the asset;
• separate the degradation part of the one or more signals from the normal part of the one or more signals;
• identify one or more patterns of a degradation part of the one or more signals and the normal part of the one or more signals;
• input the one or more patterns into an artificial neural network to determine a prediction of a future development of an anomaly;
• determine an estimate remaining useful life based on the prediction of the future development of an anomaly;
• and
• perform a maintenance procedure on at least one of the components of the asset based on the estimate of remaining useful life.

An anomaly detection and trend projection system comprising:

• one or more computers comprising one or more processors and one or more non-transitory computer readable media, the one or more non-transitory computer readable media including instructions stored thereon that when executed by the one or more processors configure the one or more computers to:
• receive a signal from a sensor coupled to a physical asset configured to produce mechanical work within an industrial process, the asset comprising of a plurality of components;
• determine if at least one of the plurality of components is a seasonal component by analyzing the signal for a variation in a trend that occurs within the signal at regular intervals during a lifespan of the asset;
• identify a degradation part of the signal and a normal part of the signal in response to a determination that the seasonal component was not detected within the plurality of components of the asset;
• separate the degradation part of the signal from the normal part of the signal;
• identify one or more patterns of a degradation part of the signal and the normal part of the signal;
• train an artificial neural network using the one or more patterns, the artificial neural network is configured to output an anomaly prediction based on the one or more patterns on a display;
• determine an estimate of remaining useful life for the asset based on the anomaly prediction;
• and
• perform a maintenance procedure on at least one of the components of the asset based on the estimate of remaining useful life.