Abstract: A blowout preventer (BOP) health monitoring system includes a controller having a tangible, machine readable-medium storing one or more instructions executable by a processor. The one or more instructions are configured to receive feedback from a sensor, where the feedback is indicative of a pressure within a BOP stack over time, determine a position of a plurality of components of the BOP stack, determine a start point and an end point of a pressure test based on the feedback, determine a decay and a hold duration of the pressure test based on the feedback, the start point, and the end point, determine a health index of the BOP stack based on the decay and the hold duration, and provide an output indicative of a condition of the BOP stack based on the health index.

Abstract: A blowout preventer (BOP) health monitoring system includes a controller having a tangible, machine readable-medium storing one or more instructions executable by a processor. The one or more instructions are configured to receive feedback from a sensor, where the feedback is indicative of a pressure within a BOP stack over time, determine a position of a plurality of components of the BOP stack, determine a start point and an end point of a pressure test based on the feedback, determine a decay and a hold duration of the pressure test based on the feedback, the start point, and the end point, determine a health index of the BOP stack based on the decay and the hold duration, and provide an output indicative of a condition of the BOP stack based on the health index.

Abstract: A method of generating linear models for a physical system of interest is implemented in steps including, first, determining offline, a set of linear models for the physical system of interest by linearization of a nonlinear computational model of the physical system of interest at selected operating points or from desired data; second, analyzing offline, accuracy of each linear model and eliminating inaccurate linear models therefrom to provide a residual set of linear models; third, generating offline, linear models corresponding to grid points of one or more lookup tables based on the residual set of linear models; fourth, associating offline, lookup table grid points with selected scheduling variables, and fifth, generating algorithmic software for the physical system therefrom such that linear models for the physical system generated offline form the basis for online scheduling of linear models.

Abstract: An example downhole tool includes a tool body and a multi-layer sensor coupled to the tool body. The multi-layer sensor may include a first transmitter coupled to a first conformable element and a first receiver coupled to a second conformable element. One of the first conformable element and the second conformable element may overlay the other of the first conformable element and the second conformable element.

Abstract: An example downhole tool includes a tool body and a multi-layer sensor coupled to the tool body. The multi-layer sensor may include a first transmitter coupled to a first conformable element and a first receiver coupled to a second conformable element. One of the first conformable element and the second conformable element may overlay the other of the first conformable element and the second conformable element.

Abstract: A method and systems for engine control of a vehicle propulsion system are provided. The system includes a plurality of engine model modules executing independently and programmed to receive engine operating condition values from a plurality of sensors positioned on an engine wherein each of the plurality of engine model modules is programmed to determine an estimate of a process parameter of a location in the engine where a sensor is not available, not present at the location, has failed, or is determined to be inaccurate. The system also includes an estimate source selector configured to determine model blending factors and a model blending module configured to determine an estimated virtual sensor value using the determined estimates from at least two of the plurality of engine model modules and the model blending factors.

Abstract: A method for estimating an operating parameter of a turbine engine is provided. The method includes receiving at least one sensor input, calculating the operating parameter using at least the one sensor input, and determining whether an anomaly is present in the calculated operating parameter using a redundancy system. An estimated operating parameter is output.

Abstract: A method of generating linear models for a physical system of interest is implemented in steps including, first, determining offline, a set of linear models for the physical system of interest by linearization of a nonlinear computational model of the physical system of interest at selected operating points or from desired data; second, analyzing offline, accuracy of each linear model and eliminating inaccurate linear models therefrom to provide a residual set of linear models; third, generating offline, linear models corresponding to grid points of one or more lookup tables based on the residual set of linear models; fourth, associating offline, lookup table grid points with selected scheduling variables, and fifth, generating algorithmic software for the physical system therefrom such that linear models for the physical system generated offline form the basis for online scheduling of linear models.

Abstract: A method and systems for engine control of a vehicle propulsion system are provided. The system includes a plurality of engine model modules executing independently and programmed to receive engine operating condition values from a plurality of sensors positioned on an engine wherein each of the plurality of engine model modules is programmed to determine an estimate of a process parameter of a location in the engine where a sensor is not available, not present at the location, has failed, or is determined to be inaccurate. The system also includes an estimate source selector configured to determine model blending factors and a model blending module configured to determine an estimated virtual sensor value using the determined estimates from at least two of the plurality of engine model modules and the model blending factors.

Abstract: A method for estimating an operating parameter of a turbine engine is provided. The method includes receiving at least one sensor input, calculating the operating parameter using at least the one sensor input, and determining whether an anomaly is present in the calculated operating parameter using a redundancy system. An estimated operating parameter is output.

Abstract: This invention provides an iteratively clustered interpolation (ICI) algorithm for use with irregularly sampled color data to develop a structured inverse. This algorithm improves device independent color across devices, such as, for example, printers, scanners and displays.