Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.

Abstract: The present disclosure relates to a multi-modal data retrieval method and apparatus, a medium, and an electronic device. The method includes: inputting target retrieval data into a first feature extraction network corresponding to a modality of the target retrieval data to acquire a data feature of the target retrieval data; inputting the data feature into a second feature extraction network corresponding to the modality of the target retrieval data to acquire a target retrieval feature corresponding to the target retrieval data, wherein second feature extraction networks respectively corresponding to modalities share a weight; and performing retrieval based on the target retrieval feature.

Abstract: A system and method including receiving historical time series sensor data associated with operation of an industrial asset; generating visual representation images of scatter plots based on the historical time series sensor data based on a reference to a digitized knowledge domain associated with the industrial asset; assigning a root cause label to each image; generating a convolutional neural network (CNN) model trained and tested using subsets of the labeled images; and processing, by the CNN model, a real-time image to detect at least one anomaly in the real-time image and one or more root causes associated with the at least one anomaly.

Abstract: Disclosed are a storage apparatus, a mobile terminal and an image processing method thereof. The image processing method comprises the following steps: acquiring a feature index parameter of each image; acquiring an operation instruction, and classifying images according to the operation instruction; determining, according to the classification of the images, whether a user is satisfied with an image; and if it is determined that the user is satisfied with the image, correcting a photographing parameter of a camera of a mobile terminal according to a feature index parameter of the satisfactory image, such that an image photographed thereby better conforms to the requirements of the user. Therefore, the present invention can directly obtain an image that a user is satisfied with, thereby saving on the screening time for a user, and thus improving the user experience.

Abstract: A method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.

Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.

Abstract: A method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.

Abstract: Disclosed are a storage apparatus, a mobile terminal and an image processing method thereof. The image processing method comprises the following steps: acquiring a feature index parameter of each image; acquiring an operation instruction, and classifying images according to the operation instruction; determining, according to the classification of the images, whether a user is satisfied with an image; and if it is determined that the user is satisfied with the image, correcting a photographing parameter of a camera of a mobile terminal according to a feature index parameter of the satisfactory image, such that an image photographed thereby better conforms to the requirements of the user. Therefore, the present invention can directly obtain an image that a user is satisfied with, thereby saving on the screening time for a user, and thus improving the user experience.