Abstract: A method for operating an adsorption-based system for removing water and potentially other components from a feed stream. The system includes at least two dehydration units each comprising an adsorption bed. The method includes the steps of: i) obtaining process data from one or more sensors at a predetermined time resolution, the sensors at least comprising at least one moisture sensor at a specified location in each of the dehydration units; ii) dehydrating the feed stream by operating the adsorption-based system in regenerative mode, wherein at least one active unit of the at least two dehydration units is in an adsorption cycle, and wherein at least another one of the at least two dehydration units is being regenerated; iii) estimating an adsorption bed water adsorption capacity during every adsorption cycle; and iv) using the process data to update the estimated adsorption bed water adsorption capacity.

Abstract: A method for predicting a remaining useful life of a bearing involves obtaining a plurality of sets of actual inspection data from the bearing. The method involves obtaining an estimated wear rate from a physics based model of the bearing. The method further involves adjusting the estimated wear rate based on the plurality of sets of actual inspection data to compute an actual wear rate. The method also involves computing a calibration parameter based on the actual wear rate. The method further involves predicting a remaining useful life of the bearing based on the calibration parameter.

Abstract: A method for predicting a remaining useful life of a bearing involves obtaining a plurality of sets of actual inspection data from the bearing. The method involves obtaining an estimated wear rate from a physics based model of the bearing. The method further involves adjusting the estimated wear rate based on the plurality of sets of actual inspection data to compute an actual wear rate. The method also involves computing a calibration parameter based on the actual wear rate. The method further involves predicting a remaining useful life of the bearing based on the calibration parameter.

Abstract: A controller includes a processor and memory. The memory stores instructions that, when executed, are configured to cause the processor to receive measurements pertaining to a measured operation parameter of at least a portion of a turbine system. The instructions are also configured to cause the processor to generate a customized model for the at least the portion of the turbine system. Moreover, the instructions are configured to cause the processor to estimate an estimated value using the received measurements. The estimated value pertains to a parameter of the turbine system. Furthermore, the instructions are configured to cause the processor to using the customized model, reduce or remove at least some environmental conditions from a corrected estimated value derived from the estimated value.

Abstract: A system includes a sensor that may measure one or more engine oil parameters to assess engine oil health of an engine and a processor communicatively coupled to the sensor and that may receive a signal from the sensor. The signal is representative of a real-time measurement of the one or more engine oil parameters. The processor may also estimate the one or more engine oil parameters over time via an adaptive predictive model associated with the one or more engine oil parameters to generate estimated data and reconcile the real-time measurement and the estimated data to generate an integrated engine oil degradation model and predict engine oil remaining useful life based on the integrated engine oil degradation model and one or more condemn limits associated with the one or more engine oil parameters.

Abstract: A controller includes a processor and memory. The memory stores instructions that, when executed, are configured to cause the processor to receive measurements pertaining to a measured operation parameter of at least a portion of a turbine system. The instructions are also configured to cause the processor to generate a customized model for the at least the portion of the turbine system. Moreover, the instructions are configured to cause the processor to estimate an estimated value using the received measurements. The estimated value pertains to a parameter of the turbine system. Furthermore, the instructions are configured to cause the processor to using the customized model, reduce or remove at least some environmental conditions from a corrected estimated value derived from the estimated value.

Abstract: A system includes a sensor that may measure one or more engine oil parameters to assess engine oil health of an engine and a processor communicatively coupled to the sensor and that may receive a signal from the sensor. The signal is representative of a real-time measurement of the one or more engine oil parameters. The processor may also estimate the one or more engine oil parameters over time via an adaptive predictive model associated with the one or more engine oil parameters to generate estimated data and reconcile the real-time measurement and the estimated data to generate an integrated engine oil degradation model and predict engine oil remaining useful life based on the integrated engine oil degradation model and one or more condemn limits associated with the one or more engine oil parameters.

Abstract: A system, method and computer-readable medium for monitoring a life of a gas turbine component is disclosed. A numerical model of the gas turbine component is created and parameter measurements are obtained in real-time for at least a portion of the gas turbine component. The parameter measurements are fused with a subset of the numerical model corresponding to the portion of the gas turbine component to obtain a subset of a fused parameter model corresponding to the portion of the gas turbine component. The subset of the fused parameter model is expanded to obtain the fused parameter model that corresponds to at least a location outside of the portion of the gas turbine component. The life of the gas turbine component is monitored using the fused temperature model.