Provided is a startup control device for adjusting a startup schedule during startup of a power generation plant. This startup control device is provided with: a determining unit which, for a prescribed physical quantity that restricts the startup of the power generation plant, determines, on the basis of a predicted value of a physical quantity corresponding to the elapsed time from startup when the power generation plant has started up on the basis of a prescribed optimal startup schedule, and an observed value of the physical quantity acquired during the startup of the power generation plant, whether the observed value will exceed the predicted value; a speed adjusting unit which, if the determining unit determines that the observed value will exceed the predicted value, issues an instruction to decelerate the speed of progress of elapsed time from the startup in the optimal startup schedule; and a startup timer which progresses the elapsed time from the startup at a speed based on the instruction.

An apparatus, methods and systems for data collection related to an oil and gas process and disclosed. A system may include a multi-sensor acquisition component including a plurality of inputs and a plurality of outputs, a sensor data storage profile circuit structured to determine a data storage profile including a data storage plan for the plurality of inputs, a sensor communication circuit structured to interpret a plurality of inputs, a sensor data storage implementation circuit structured to store at least a portion of the inputs in response to the data storage profile, a data analysis circuit structured to analyze the plurality of inputs and determine a data quality parameter, and a data response circuit structured to adjust at least one of the data storage profile and the data collection routine in response to the data quality parameter.

A platform for facilitating development of intelligence in an Industrial Internet of Things (IIoT) system generally includes a plurality of distinct data-handling layers having an industrial monitoring systems layer that collects data from or about a plurality of industrial entities in an industrial environment; an industrial entity-oriented data storage systems layer that stores the data collected by the industrial monitoring systems layer; and an adaptive intelligent systems layer that facilitates the coordinated development and deployment of intelligent systems in the IIoT system; wherein the adaptive intelligent systems layer includes an adaptive edge compute management system that adaptively manages edge computation, storage, and processing in the IIoT system.

A computer implemented method of administering a complex system includes receiving multivariate data from a plurality of sensors of the system in an ambient state. Event sequences in the received multivariate data are identified. The multivariate event sequences are projected to a lower stochastic latent embedding. A temporal structure of the sequences is learned in a lower latent space. A probabilistic prediction in the lower latent space is provided. The probabilistic prediction in the lower stochastic latent space is decoded to an event prediction in the ambient state.

An anomaly detection method and system for a process instrument, and a storage medium are disclosed. The method includes that: a programmable logic controller (PLC) receives measurement data of a process instrument, the measurement data being periodically stored into a historical database so that a service providing system can perform reading and evaluation. At least one virtual function module is integrated on the PLC, a mapping relation is formed between at least one input channel of each virtual function module and output of at least one anomaly diagnosis algorithm disposed on the service providing system, and each anomaly diagnosis algorithm is used for diagnosing whether an anomaly exists in the process instrument. When an anomaly indication outputted by the service providing system is received via an input channel of the virtual function module, the PLC determines that an anomaly exists in the corresponding process instrument.

A method for operating a redundant automation system having a plurality of subsystems, wherein one subsystem of the plurality of subsystems operates as a master and assumes process control and the other subsystem operates as a reserve during redundant operation, where measures are provided by which the availability of the redundant automation system is increased, and where regardless of whether transient errors occur on the subsystem of the plurality of subsystems operating as the master or on the subsystem operating as the reserve, a total failure of the automation system is largely avoided.

Disclosed are embodiments for automatically resolving faults in a complex network system. Some embodiments monitor one or more of system operational parameter values and message exchanges between network components. A machine learning model detects a fault in the complex network system, and an action is selected based on a cause of the fault. After the action is applied to the complex network system, additional monitoring is performed to either determine the fault has been resolved or additional actions are to be applied to further resolve the fault.

A preventive switchover from a primary controller to a secondary controller even before the primary controller fails system and method includes a server that collects log files comprising operational parameters of the primary controller from the primary controller in real-time. The server determines abnormal patterns or signatures in the operational parameters of the primary controller by comparing the operational parameters with reference patterns or signatures. The reference patterns or signatures are generated by training one or more Artificial Intelligence (AI) based models. After determining the abnormal patterns or signatures, the server predicts events that will lead to switchover from the primary controller to the secondary controller. Thereafter, the server provides a signal to the primary controller to perform preventive switchover to the secondary controller before the primary controller fails.

A method for operating a redundant automation system having a plurality of subsystems, wherein one subsystem of the plurality of subsystems operates as a master and assumes process control and the other subsystem operates as a reserve during redundant operation, where measures are provided by which the availability of the redundant automation system is increased, and where regardless of whether transient errors occur on the subsystem of the plurality of subsystems operating as the master or on the subsystem operating as the reserve, a total failure of the automation system is largely avoided.

Embodiments herein describe coupling traditional fan and shaper control along with aggregated knowledge of the temperature history of a hardware device to optimally manage the temperature of the hardware device to preserve its expected life while also providing the lower power, best performing solution possible. In one embodiment, a cooling application manages the expected life by trading off performance and power versus temperature to achieve a desired (or accepted) lifetime. In one embodiment, the cooling application calculates a historical temperature value for the hardware device which is then used to determine the expected life of the hardware device.