Systems, methods, and computer-readable media for providing a maintenance recommendation for a catalyst

A system comprising:

• at least one system configured to:
• extract training data comprising one or more parameters from each catalyst of a plurality of catalysts, wherein each parameter is collected from a respective catalyst of the plurality of catalyst;
• classify the training data in accordance with at least one catalyst feature at least one of the contaminations of the catalyst and the aging time of the catalyst;
• determine a feature vector from the classified training data based on the one or more parameters extracted from catalyst of the plurality of catalysts, wherein the feature vector is indicative of whether the catalyst performs normally or abnormally;
• generate a machine learning model, wherein the machine learning model is trained based on the feature vector, to predict the function and performance of a catalyst;
• generate a performance baseline curve from the training data in accordance with the destruction or removal efficiency (DRE) of a gas;
• and
• provide based on the trained machine learning model a maintenance recommendation for the catalyst.

A non-transitory computer readable medium comprising:

• a computer program code segment used to extract training data comprising one or more parameters from each catalyst of a plurality of catalysts, wherein each parameter is collected from a respective catalyst of the plurality of catalyst;
• a computer program code segment used to classify the training data in accordance with at least one catalyst feature at least one of the contaminations of the catalyst and the aging time of the catalyst;
• determine a feature vector from the classified training data based on the one or more parameters extracted from catalyst of the plurality of catalysts, wherein the feature vector is indicative of whether the catalyst performs normally or abnormally;
• a computer program code segment used to generate a machine learning model, wherein the machine learning model is trained based on the feature vector, to predict the function and performance of a catalyst;
• a computer program code segment used to generate a performance baseline curve from the training data in accordance with the destruction or removal efficiency (DRE) of a gas;
• and
• a computer program code segment used to provide based on the trained machine learning model a maintenance recommendation for the catalyst.