Abstract: A virtual sensor system includes one or more electric submersible pumping systems deployed in a reservoir and a computer system that receives data from the one or more electric submersible pumping systems. Field data is provided to computerized statistical models for predicting whether individual electric submersible pumping systems and the reservoir have undergone changes in condition. The statistical models are established with reference data obtained by running electric submersible pumping systems of known working condition in test wells under a variety of controlled conditions.

Abstract: Provided are systems and methods for evaluating risks associated with a manufacturing process including a network interface configured to receive a request to evaluate a purchase order associated with a deliverable that includes one or more components for manufacture, a processor configured to evaluate a set of metrics associated with the deliverable to identify a status of each of the set of metrics, and an output configured to generate a risk evaluation representing a risk of delivery of the deliverable.

Abstract: Systems and methods for determining risk to operating a turbomachine are provided. According to one embodiment of the disclosure, a method may include receiving historical risk profile data associated with a fleet of turbomachines by at least one processor from a repository. The method can also include receiving ambient conditions of an environment in which a turbomachine is to be operated. Based at least in part on the historical risk profile data and in view of the ambient conditions, at least one risk threshold for at least one known operating profile can be developed. The method may continue with determining that the at least one risk threshold for the at least one known operating profile is reached. Based at least in part on a determination that the at least one risk threshold is reached, a mitigating action associated with the turbomachine can be taken.

Abstract: A virtual sensor system includes one or more electric submersible pumping systems deployed in a reservoir and a computer system that receives data from the one or more electric submersible pumping systems. Field data is provided to computerized statistical models for predicting whether individual electric submersible pumping systems and the reservoir have undergone changes in condition. The statistical models are established with reference data obtained by running electric submersible pumping systems of known working condition in test wells under a variety of controlled conditions.

Abstract: An automated prognostics system includes a sensor system configured to obtain measurement data by monitoring one or more parameters at one or more locations on each of one or more movable components of an object when the object is subjected to a first mode of operation. The system also includes a computing device having an input interface and a processor. The input interface receives input information such as spatial coordinates information associated with the one or more locations, the measurement data obtained by the sensor system, operational data associated with the first mode of operation, and structural data associated with the object. The processor processes the input information and generates a prognostics report on at least a first component of the one or more movable components, the prognostics report including at least one of a failure prognostic or a likelihood-of-failure prognostic of the first component.

Abstract: Systems and methods for determining risk to operating a turbomachine are provided. According to one embodiment of the disclosure, a method may include receiving historical risk profile data associated with a fleet of turbomachines by at least one processor from a repository. The method can also include receiving ambient conditions of an environment in which a turbomachine is to be operated. Based at least in part on the historical risk profile data and in view of the ambient conditions, at least one risk threshold for at least one known operating profile can be developed. The method may continue with determining that the at least one risk threshold for the at least one known operating profile is reached. Based at least in part on a determination that the at least one risk threshold is reached, a mitigating action associated with the turbomachine can be taken.

Abstract: A creep life management system includes at least one sensor apparatus coupled to a first component. The at least one sensor apparatus is configured with a unique identifier. The creep life management system also includes at least one reader unit coupled to a second component. The at least one reader unit is configured to transmit an interrogation request signal to the at least one sensor apparatus and receive a measurement response signal transmitted from the at least one sensor apparatus. The creep life management system further includes at least one processor programmed to determine a real-time creep profile of the first component as a function of the measurement response signal transmitted from the at least one sensor apparatus.

Abstract: An automated analytics system can include a sensor system that obtains measurement data by monitoring one or more parameters at each of a number of locations on each of a number of replicated components of an object. A computing device receives the measurement data from the sensor system and uses the measurement data to automatically generate a computerized representation of each of the plurality of replicated components. Thereafter, upon receipt of an input query, the computing device generates a synthesized representation of the object that is specifically directed to a parameter of interest indicated in the query. The synthesized representation may be displayed in a visual format that is interpretable by a human to derive information associated with the parameter of interest.

Abstract: An automated analytics system can include a sensor system that obtains measurement data by monitoring one or more parameters at each of a number of locations on each of a number of replicated components of an object. A computing device receives the measurement data from the sensor system and uses the measurement data to automatically generate a computerized representation of each of the plurality of replicated components. Thereafter, upon receipt of an input query, the computing device generates a synthesized representation of the object that is specifically directed to a parameter of interest indicated in the query. The synthesized representation may be displayed in a visual format that is interpretable by a human to derive information associated with the parameter of interest.

Abstract: An automated prognostics system includes a sensor system configured to obtain measurement data by monitoring one or more parameters at one or more locations on each of one or more movable components of an object when the object is subjected to a first mode of operation. The system also includes a computing device having an input interface and a processor. The input interface receives input information such as spatial coordinates information associated with the one or more locations, the measurement data obtained by the sensor system, operational data associated with the first mode of operation, and structural data associated with the object. The processor processes the input information and generates a prognostics report on at least a first component of the one or more movable components, the prognostics report including at least one of a failure prognostic or a likelihood-of-failure prognostic of the first component.

Abstract: A system and process for optimizing the performance and evaluating the risks of pumping systems includes the steps of measuring the operation and condition of components within a discrete electric submersible pumping system, accumulating these measurements across a field of electric submersible pumping systems, performing statistical analysis on the accumulated measurements and producing one or more selected outputs from the group statistical analysis. In the preferred embodiments, the statistical analysis and data processing occurs at both the individual pumping system and at one or more centralized locations.

Abstract: Solar farms and methods for forecasting solar farm performance are provided. A method may include, for example, the steps of analyzing in a computing device at least one historic or estimated usage parameter and at least one design limit parameter, and determining an estimated failure probability for at least one solar module of the solar farm based on the at least one historic or estimated usage parameter and at least one design limit parameter. A method may further include, for example, the steps of receiving in the computing device at least one real time usage parameter, and calculating an updated failure probability based on the estimated failure probability and the least one real time usage parameter.

Abstract: A creep life management system includes at least one sensor apparatus coupled to a first component. The at least one sensor apparatus is configured with a unique identifier. The creep life management system also includes at least one reader unit coupled to a second component. The at least one reader unit is configured to transmit an interrogation request signal to the at least one sensor apparatus and receive a measurement response signal transmitted from the at least one sensor apparatus. The creep life management system further includes at least one processor programmed to determine a real-time creep profile of the first component as a function of the measurement response signal transmitted from the at least one sensor apparatus.

Abstract: A method, system and computer program product for life management and monitoring of a high temperature gas turbine including components having a thermal barrier coating is disclosed. The method, system and computer program product uses design, monitoring and diagnostics, and inspection data to determine the cumulative damage and remaining useful life of gas turbine components and unit risk and classification probability to determine thermal barrier coating damage probability, remaining useful life, and inspection recommendations.

Abstract: A system and method for enhancing operation of a power generation system. The method includes receiving forecasts at a predictive control unit. The method also includes accessing via a controller real-time lifing models or near real-time lifing models in the predictive control unit. Additionally, the method includes accessing via the controller an enhancer configured to simulate operation of a power generating unit in the power generation system to generate an enhancement of the power generation system based on the forecasts and the real-time or near real-time lifing models.

Abstract: A system for monitoring a gas turbine includes a memory containing information from comparable gas turbines and an input device that generates a unit data signal and a risk signal. A processor in communication with the memory and the input device incorporates the unit data signal into the database, projects information for the gas turbine, and calculates a conditional risk that the gas turbine will reach a limit. An output signal includes repair or maintenance schedules. A method for monitoring a gas turbine includes receiving information from comparable gas turbines, adding information from the gas turbine to the information from comparable gas turbines, and projecting information for the gas turbine. The method further includes calculating a conditional risk that the gas turbine will reach a limit and generating an output signal containing repair or maintenance schedules.

Abstract: Methods and systems for use in predicting wind turbine failures are provided. One example method includes determining a parametric profile for a component of a wind turbine from operating data of a plurality of wind turbines, determining an anomaly profile for the component of the wind turbine from anomaly alerts from a plurality of wind turbines, and determining a probability of failure for the component of the wind turbine based on the parametric profile and the anomaly profile. The parametric profile defines at least one parametric event associated with the component prior to failure of the component, and the anomaly profile defines at least one anomaly associated with the component prior to failure of the component.

Abstract: Methods and systems for use in predicting wind turbine failures are provided. One example method includes determining a parametric profile for a component of a wind turbine from operating data of a plurality of wind turbines, determining an anomaly profile for the component of the wind turbine from anomaly alerts from a plurality of wind turbines, and determining a probability of failure for the component of the wind turbine based on the parametric profile and the anomaly profile. The parametric profile defines at least one parametric event associated with the component prior to failure of the component, and the anomaly profile defines at least one anomaly associated with the component prior to failure of the component.

Abstract: A system for managing risk associated with a full-service agreement (FSA) for at least one wind turbine is provided. The system includes a memory device configured to store data including at least a plurality of service reports regarding the at least one wind turbine and a processor unit coupled to the memory device. The processor unit includes a programmable hardware component that is programmed. The processor unit is configured to analyze, by a text-mining system, text in the plurality of service reports to output failure information regarding the at least one wind turbine, receive, by a top-down simulator, the failure information from the text-mining system to perform a simulation that generates a distribution model, and receive, by a bottom-up simulator, the failure information from the text-mining system to perform a simulation that generates an extrapolation model.

Abstract: A system for use with a risk management system is provided. The system includes a memory device configured to store data including at least historical service records of at least one wind turbine and new service records of the at least one wind turbine and a processor unit coupled to the memory device. The processor unit includes a programmable hardware component that is programmed. The processor unit is configured to analyze, by a processing system, text of the historical service records to generate a prediction model including a plurality of failure categories; and analyze, by a monitoring system, text of the new service records to classify each new service record based on the prediction model.