Abstract: A method for presenting a targeted message includes establishing communications with a user computer to obtain, from the user computer, information on an application running on the user computer, analyzing the information on the application to identify an opportunity to present a message to the user computer, selecting one or more targeted messages in response to identifying the opportunity to present the message, and providing the one or more targeted messages to the user computer for presentation at the user computer.

Abstract: A machine-learned method and system for use in operating an industrial plant. A digital twin of the industrial plant is configured to simulate plant operations based on operating variables from a data store. A machine-learned model comprises a stabilizing agent and a disrupting agent. The stabilizing agent modifies the operating variables within the digital twin to perform a stabilizing action for limiting a degree of shutdown and the disrupting agent modifies the operating variables within the digital twin to perform a disruptive action for increasing the degree of shutdown. A composite action reward is configured to reward the machine-learned model for reducing the degree of shutdown from an initial state of the digital twin to a post-action-state of the digital twin.

Abstract: A virtual plant operator system for use in an industrial plant. A data aggregator monitors operating data within the industrial plant and sends the operating data as a current state of the industrial plant to an operator assistant. The operator assistant includes a digital twin of the industrial plant and an artificial intelligence engine. The digital twin of the industrial plant receives the current state and simulates plant operations based on the current state. The artificial intelligence engine has at least one machine-learned model. The machine-learned model processes the simulated plant operations based on the current state to determine a recommendation output. The recommendation output includes stabilizing actions to the plant operations in the industrial plant and/or a predicted degree of shutdown responsive to each of the stabilizing actions.

Abstract: Systems/methods for real-time monitoring and control of a well site provide an event monitor and detector for progressing cavity pump (PCP) operations at the well site. The event monitor and detector uses machine learning (ML) based anomaly detection to detect operations that fall outside normal PCP operating space. The event monitor and detector then computes novelty scores for the anomalies and checks whether the novelty scores exceed a threshold novelty score. If the number of novelties detected within a given detection window exceeds a minimum threshold count, then the event monitor and detector flags an “event” and automatically responds accordingly. The event monitor and detector also provides an explanation with the alerts that quantifies the extent to which various PCP parameters contributed to the event. The event monitor and detector further performs drift detection to determine whether an event may be due to operator-initiated adjustments to PCP parameters.

Abstract: An autonomously or semi-autonomously performed method of orchestration in a process control system (PCS) is provided, including performing tasks for monitoring an industrial system, including the PCS, each of the tasks being performed using inputs related to functionality of controller(s) of the PCS, the controller(s) having at least one control function related to a physical aspect of the PCS. For each of the tasks performed, dynamic state(s) of the PCS and the PCS's controller(s) are analyzed using machine learning (ML) algorithm(s), the dynamic state(s) being affected by the inputs. The method further includes performing, causing to be performed, or advising performance of an action responsive to an output of the ML algorithm(s), the action adjusting at least one of functionality of the controller(s) and functionality of or a setting used by or affecting a component of the PCS that affects the controller(s).

Abstract: A flow meter system and method are provided for monitoring gas flow in a conduit. The flow meter system includes a plurality of components including: a sensor for sensing a flow rate of the gas flow; a communication device for transmitting information corresponding to the sensed flow rate to a remote device; an energy harvesting device for producing electrical energy from the gas flow to power operation of the communication device or other component of the flow meter system; and an energy storage device for storing electrical energy generated by the energy harvesting device.

Abstract: A mode selector permits deactivating a run-time operational mode and activating a privileged operational mode on a remote terminal unit (RTU). One or more functionalities associated with the privileged operational mode are performed via a local and/or a remote computing device communicatively coupled to the RTU. The functionalities include at least one of developing and deploying content for the RTU, loading security certificates for the RTU, enabling Linux root account access to the RTU, and performing system maintenance on the RTU. The mode selector switch returns the RTU to the run-time operational mode after the functionalities are performed.

Abstract: A self-adaptive security system for a control system executing a plurality of Industrial of Internet of Things (IIoT) applications. A security processor communicatively coupled to the control system assesses a current security posture of the control system and determines if the current security posture is within or outside an acceptable risk tolerance as a function of a current threat landscape affecting the control system. In response to determining the current security posture is outside the acceptable risk tolerance, the security processor executes a risk weighting model to determine a modified cybersecurity strategy and autonomously executes the modified cybersecurity strategy to improve the current security posture of the control system relative to changes in the current threat landscape. The security processor also executes a digital twin to simulate operations of the control system and assesses a potential impact of the modified cybersecurity strategy on the operations before executing it.

Abstract: Methods and system for configuring a remote terminal unit (RTU) device of a Supervisory Control and Data Acquisition (SCADA) system. The RTU device transmits an initial message payload to a SCADA server of the SCADA system via a broker server in accordance with a Message Queuing Telemetry Transport (MQTT) messaging protocol. The initial message payload complies with a Sparkplug specification for MQTT and includes at least one metric name and initial data and at least one PropertySet object associated with the metric name indicative of at least one parameter of the RTU device to be configured. In response to the initial message payload, the SCADA server transmits a subsequent message payload to the RTU device via the broker server. The subsequent message payload also complies with the Sparkplug specification and includes one or more values for the PropertySet object for configuring the at least one parameter of the RTU device.

Abstract: A system and method for providing abnormality diagnosis of a mechanical device having one or more components. A sensor system, having one or more sensor devices, detects movement/vibration of one or more observed components of the mechanical device. A control system determines vibration measurements of the one or more components based on their detected motion/vibration. One or more Machine Learning (ML) and/or Artificial Intelligence (AI) techniques are utilized to determine abnormal operation of the one or more components by comparing a determined vibration measurement of an observed component against that component's expected normal vibration measurement value during operation of the mechanical device. Abnormal operation is determined when the determined vibration measurement of an observed component exceeds its expected normal vibration measurement by a threshold value.

Abstract: Systems and methods for real-time monitoring and control of well site operations employ well site edge analytics to detect abnormal operations. The systems and methods use machine learning (ML) based analytics on an edge device directly at the well site to detect possible occurrence of abnormal events and automatically respond to such events. The event detection may be based on trends identified in the data acquired from the well site operations in real time. The trends may be identified by correlation and by fitting line segments to the data and analyzing the slopes of the line segments. Upon detecting an unusual event, the edge device can issue alerts regarding the event and take predefined steps to reduce potential damage resulting from such event. This can help decrease downtime and minimize lost productivity and cost as well as reduce health and safety risks for field personnel.

Abstract: System and method for determining a probability of an alarm being shelved using a weighting algorithm taking into account relevant factors or characteristics associated with an industrial process. Support for rendering a decision is provided, including determining an estimated time duration before the alarm is un-shelved if the alarm is likely to be shelved, a rationale for the alarm to be shelved, and relevant information supporting the rationale. A machine learning model learns from operator actions relating to alarms to capture the knowledge of the operator and to update or refine the weighting algorithm.

Abstract: An industrial wireless instruments network connects a plurality of industrial wireless instruments to a monitoring and control application. The network employs wireless relay nodes that operate as dedicated proxies for the wireless instruments to which they are connected in the network. In some embodiments, the wireless relay nodes are Bluetooth Low Energy (BLE) devices that are capable of implementing Bluetooth version 4.0 or higher. In some embodiments, the relay nodes are deployed in a multi-hop arrangement to extend the range between the wireless instruments and the monitoring and control application. In some embodiments, the relay nodes are deployed in parallel so as to provide easy scale out, redundancy, and load-balancing. Such an arrangement has several advantages over conventional solutions like mesh networks.

Abstract: Systems and methods for simultaneously analyzing time-series and dominant frequency data from both a process domain and an electrical domain of a facility, such as an industrial plant, to detect instances of deviation from optimal, normal, or other predefined process conditions or electrical trips. Detecting when changes in frequencies occur in the time-series data creates a time-series of the changes in dominant frequencies. A data analysis server detects instances of deviation from the predefined process conditions or electrical trips by detecting one or more of correlations, patterns, clusters, and the like in the rates of change. The data analysis server employs one or more of statistical analyses, data mining, machine learning, deep neural networks, parallel coordinate analyses, etc. to identify the deviations and predict or detect onset of an undesired event such as a process perturbation or electrical trip.

Abstract: A method is provided for autonomous anomaly management of an industrial site having industrial equipment in its field, including identifying industrial equipment to be inspected in the field, obtaining select autonomous sensor data about the identified industrial equipment from at least one mobile autonomous device routed along respective routes for accessing the identified industrial equipment, processing the autonomous sensor data to identify a potential anomaly, and in response to identifying a potential anomaly, taking action(s) to address the potential anomaly, wherein, as a combination, identifying the equipment, processing the autonomous sensor data, identifying the potential anomaly, and determining the action(s) use historical measurement and/or control data from the industrial equipment, historical autonomous sensor data, extrinsic data including at least one of guidance and/or constraint data about the industrial site, and supervisory and/or control data generated and/or collected by supervisory co

Abstract: A menu navigation engine that enables user configuration of a vortex flowmeter. The vortex flowmeter includes a memory device and a processor, among other hardware components. Software instructions stored on the memory device and executable by the processor implement the menu navigation engine by displaying use case identifiers on the user interface, receiving selections of use case identifiers via the user interface, generating a formatted hierarchical tree of vortex flowmeter configuration nodes associated with the selected use case, and displaying the generated tree on the user interface.

Abstract: An image generation processor of an automation system executes a tag-to-image tool for visualizing status information associated with an industrial operation. A SCADA server monitors telemetry data from a remote industrial asset and provides supervisory control via a private network. The SCADA server also stores textual status information relating to the industrial operation in one or more tags. The image generation processor executes the tag-to-image tool to automatically generate at least one visual indicator representative of the textual status information stored in the tags and causes the generated visual indicator to be dynamically displayed on a display of a client display device associated with the industrial operation.

Abstract: Systems and methods for controlling industrial process automation and control systems can automatically, through the use of machine learning (ML) models and algorithms, extract plant assets from engineering diagrams and other plant engineering data sources. The systems and methods can establish asset relationships to create a plant asset registry and build an asset hierarchy from the plant assets. The systems and methods can generate an ontological knowledge base from the plant asset hierarchy, and provide an HMI for controlling the industrial process based on the plant asset hierarchy and the ontological knowledge base.

Abstract: Methods and systems for implementing one-time pad (OTP) encryption in industrial wireless instruments advantageously make use of data storage devices now available that can store a large number of encryption keys or pads in a small enough package to fit within an industrial wireless instrument. In some embodiments, the wireless instruments use solid-state memory devices that can easily hold a sufficient number of pads to last the expected lifetime of the wireless instruments. The solid-state memory devices are installed only during manufacturing of the wireless instruments where tamper-resistant manufacturing and assembly techniques may be used to ensure security for the pads. Likewise, the solid-state memory devices of the wireless instruments are also replaced or replenished only at an authorized manufacturer should additional pads be needed.

Abstract: A smart controller continuously monitors data for determining in real time if there is a likelihood that an asset will be shut down and, if so, recommends a new setpoint at which the asset will continue to operate but will not lead to tripping of the system. The smart controller executes a simulation engine to test the new setpoint before implementation to optimize performance while avoiding a shutdown. In this manner, the smart controller provides early warning of possible shutdowns and ensures that key assets are less likely to be shut down.