Abstract:
A system and method for monitoring operating conditions of tubes in a steam generator. The system comprises sensors, affixed to the tubes, for detecting one or more of mechanical strains, pressures, and temperatures in the tubes; or a camera positioned in the steam generator, the camera for capturing thermal images of the tubes; or both the sensors and the camera. The system also comprises one or more computers connected to the sensors, or the camera, or both the sensors and the camera, the computers for receiving one or more of the mechanical strains, pressures, temperatures, and thermal images, and monitoring the operating conditions of the tubes. The method comprises receiving, at one or more times, one or more of pressures, mechanical strains, temperatures, and infrared photon counts of the tubes; identifying segments of the tubes to which pertains the pressures, mechanical strains, temperatures, and infrared photon counts; and monitoring the operating conditions of the tubes.
Abstract:
According to some embodiments, a system, method and non-transitory computer readable medium are provided comprising a memory storing processor-executable steps; and a processor to execute the processor-executable steps to cause the system to: receive a first data value of a plurality of data values from a data store, wherein the first data value is from a digital twin model of an industrial asset; determine, via a vulnerability module, whether the received at least one data value is a near boundary case or not a near boundary case; in a case it is determined the first data value is a near boundary case, generate one or more adversarial samples for the first data value; input each of the one or more adversarial samples to the digital twin model; execute the digital twin model to output a system response for each input adversarial sample; determine whether the system response to each input adversarial sample has a negative impact; in a case it is determined the system response has a negative impact for a given input adversarial sample, update a trained attack detection model with the given input adversarial sample; and generate a second decision boundary based on the updated trained attack detection model. Numerous other aspects are provided.
Abstract:
According to some embodiments, data associated with the operation of a desalter vessel (150), adapted to receive a raw crude input and a water input and facilitate creation of a desalted crude output and a salt water output, may be stored in a computer storage device (630). A computer processor (610) may determine at least one parameter associated with the data in the computer store. The computer processor (610) may then automatically calculate, based on the determined parameter and a physics-based dynamic desalter model (400), an adjustment value for a second parameter associated with operation of the desalter vessel. Using the automatically calculated adjustment value, the computer processor (610) may automatically generate and transmit an indication of the adjustment value so as to improve operation of the desalter vessel (150).