Abstract: Deep Convolutional Neural Networks (CNNs) can be used to identify a non-linear control valve event in a control loop of a chemical process. Identifying the non-linear control valve event can be based on a predetermined feature of a red, green and blue (RGB) image, where the RGB image is obtained by merging respective matrices assembled from continuous wavelet transform coefficients derived from chemical plant operation controller signals. Once the non-linear control valve event is identified in a control loop, controller settings can be modified to minimize the non-linear control valve event and/or a root cause investigation can be conducted to address the issue.