Abstract: A transferable hybrid method for prognostics of engineering systems based on fundamental degradation modes is provided. The method includes developing a degradation model that represents degradation modes shared in different domains of application through the integration of physics and machine learning. The system measures sensor signals and data processing provides for extracting health indicators correlated with the fundamental degradation modes from sensors data. For the integration of physics and machine learning, the degradation mode is separated into different phases. Before the accelerated degradation phase of a system, the method is looking out to detect when the accelerated phase begins. When accelerated phase is active, the system applies a machine-learning model to provide information on the accelerated degradation phase, and evolves the degradation towards a failure threshold in a simulation of the updated physics-based model to predict the degradation progression.

Abstract: A flexible device mounting kit allows to securely attach a sensor or another device to an arbitrary surface, including a surface that is very uneven. The kit includes a scaffolding assembly which includes a scaffolding guide and scaffolding teeth attached to the guide in a way that allows some of the teeth to move relative to the guide when the bottom of the teeth is pressed against uneven surface. When the assembly is pressed against the surface, the positions of the teeth adjust, forming, together with the surface, a cavity into which a gluing compound can be filled. A device mount to which a sensor (or another device) can be attached is pressed into the gluing compound before the gluing compound solidifies. As the gluing compound securely connects the sensor mount to the surface, the device can be securely placed within the mount regardless of how uneven the surface is.

Abstract: One embodiment provides a system for processing natural-language entries. The system obtains a plurality of historical natural-language entries associated with a first domain and pre-processes the historical natural-language entries to obtain a set of generic terms and a set of domain-specific terms. The system trains a machine learning model in the first domain using the plurality of historical natural-language entries associated with the first domain. The training comprises learning weight values of one or more generic terms, a weight value of a respective generic term indicating likelihood that the generic term is related to a trigger event. The system generalizes the machine learning model trained in the first domain, thereby allowing the model to be applied to a second domain.

Abstract: One embodiment provides a method and a system for automated design of a physical system. During operation, the design system obtains qualitative and quantitative design requirements associated with the physical system and inputs the qualitative design requirements to a trained machine-learning model to generate a topology of the physical system. The topology specifies a number of components and connections among the components. The design system then determines parameters of the components based on the quantitative design requirements.

Abstract: A system and method for performing hybrid reasoning to predict remaining useful life of a target system. During operation, the system measures, via a set of sensors associated with the target system, sensor signals before a prediction start time. The system updates, based on the measured sensor signals, a first set of parameters of a physics-based model associated with the target system. The system in response to determining that the target system current time is less than a prediction start time: apply a machine-learning model to estimate a second aspect of the health of the target system; and update a second set of parameters of the physics-based model. The system can perform a time simulation of the updated physics-based model to predict a wear/degradation pattern of the target system after the prediction start time; and determine, based on the predicted wear/degradation pattern, a remaining useful life of the target system.

Abstract: One embodiment provides a system for processing natural-language entries. The system obtains a plurality of historical natural-language entries associated with a first domain and pre-processes the historical natural-language entries to obtain a set of generic terms and a set of domain-specific terms. The system trains a machine learning model in the first domain using the plurality of historical natural-language entries associated with the first domain. The training comprises learning weight values of one or more generic terms, a weight value of a respective generic term indicating likelihood that the generic term is related to a trigger event. The system generalizes the machine learning model trained in the first domain, thereby allowing the model to be applied to a second domain.

Abstract: A flexible device mounting kit allows to securely attach a sensor or another device to an arbitrary surface, including a surface that is very uneven. The kit includes a scaffolding assembly which includes a scaffolding guide and scaffolding teeth attached to the guide in a way that allows some of the teeth to move relative to the guide when the bottom of the teeth is pressed against uneven surface. When the assembly is pressed against the surface, the positions of the teeth adjust, forming, together with the surface, a cavity into which a gluing compound can be filled. A device mount to which a sensor (or another device) can be attached is pressed into the gluing compound before the gluing compound solidifies. As the gluing compound securely connects the sensor mount to the surface, the device can be securely placed within the mount regardless of how uneven the surface is.

Abstract: A method to estimate damage propagation is disclosed. The method includes making available a set of input parameters to a computational model, executing the computational model with defined changes within a range of an input parameter of the set of input parameters to define a range of at least one modeled output, receiving at least one signal responsive to and representative of a respective one of an actual sensor output, and estimating damage propagation based upon a correlation of the received signal to the modeled output.

Abstract: A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine.

Abstract: A method to predict remaining life of a target is disclosed. The method includes receiving information regarding a behavior of the target, and identifying from a database at least one piece of equipment having similarities to the target. The method further includes retrieving from the database data prior to an end of the equipment useful life, the data having a relationship to the behavior, evaluating a similarity of the relationship, predicting the remaining life of the target based upon the similarity, and generating a signal corresponding to the predicted remaining equipment life.

Abstract: A system and method for monitoring the vibrations of a machine that includes a reflective patch affixed to the machine and a vibration detection unit including an optics module. The optics module may be positioned remotely from the machine such that the optics module transmits an electromagnetic beam to the reflective patch and reflected from the reflective patch to the optics module. The optics module demodulates the electromagnetic beam to determine the vibration of the machine.

Abstract: A method to reduce uncertainty bounds of predicting a remaining life of a probe using a set of diverse models is disclosed. The method includes generating an estimated remaining life output by each model of the set of diverse models, aggregating each of the respective estimated remaining life outputs via a fusion model, and in response to the aggregating, predicting the remaining life, the predicting having reduced uncertainty bounds based on the aggregating. The method further includes generating a signal corresponding to the predicted remaining life of the probe.

Abstract: A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine.

Abstract: A method for multi-objective deterioration accommodation using predictive modeling is disclosed. The method uses a simulated machine that simulates a deteriorated actual machine, and a simulated controller that simulates an actual controller. A multi-objective process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a deteriorated condition of the simulated machine.

Abstract: A method to reduce uncertainty bounds of predicting a remaining life of a probe using a set of diverse models is disclosed. The method includes generating an estimated remaining life output by each model of the set of diverse models, aggregating each of the respective estimated remaining life outputs via a fusion model, and in response to the aggregating, predicting the remaining life, the predicting having reduced uncertainty bounds based on the aggregating. The method further includes generating a signal corresponding to the predicted remaining life of the probe.

Abstract: A method to predict equipment life is disclosed. The method includes making available a set of input parameters, and defining a model of a health of the equipment as a function of the set of input parameters. The method continues with receiving at least one signal representative of a respective one of an actual sensor output relating to an actual operation attribute margin of the equipment, predicting a remaining useful equipment life based upon a sequence of outputs of the model of the health of the equipment, and generating a signal corresponding to the remaining useful equipment life.

Abstract: A method to predict equipment life is disclosed. The method includes making available a set of input parameters, and defining a model of a health of the equipment as a function of the set of input parameters. The method continues with receiving at least one signal representative of a respective one of an actual sensor output relating to an actual operation attribute margin of the equipment, predicting a remaining useful equipment life based upon a sequence of outputs of the model of the health of the equipment, and generating a signal corresponding to the remaining useful equipment life.

Abstract: A method to predict remaining life of a target is disclosed. The method includes receiving information regarding a behavior of the target, and identifying from a database at least one piece of equipment having similarities to the target. The method further includes retrieving from the database data prior to an end of the equipment useful life, the data having a relationship to the behavior, evaluating a similarity of the relationship, predicting the remaining life of the target based upon the similarity, and generating a signal corresponding to the predicted remaining equipment life.

Abstract: A method to estimate damage propagation is disclosed. The method includes making available a set of input parameters to a computational model, executing the computational model with defined changes within a range of an input parameter of the set of input parameters to define a range of at least one modeled output, receiving at least one signal responsive to and representative of a respective one of an actual sensor output, and estimating damage propagation based upon a correlation of the received signal to the modeled output.

Abstract: A method, system, and computer program product for performing prognosis and asset management services is provided. The method includes calculating an accumulated damage estimate for a component via a diagnostics function and applying future mission data for the component to at least one model that calculates accumulated damage or remaining life of the component. The method also includes inputting the accumulated damage estimate to the model and aggregating damage over time and quality assessments produced by the model. The method further includes calculating a damage propagation profile and remaining life estimate for the component based on the aggregating and providing an uncertainty estimate for the damage estimate and the remaining life estimate.