Abstract: A condition of an asset including one or more subsystems connected in series is monitored. Each subsystem includes one or more components connected in parallel. The asset has one or more jobs. A probability of the asset surviving a predetermined amount of time is determined based on the monitoring and one or more shared resources. The one or more shared resources are configured to be shared between the subsystems. A model is established using a threshold based heuristic maintenance policy. The model is configured to maximize a number of successful jobs that the asset is able to complete based on the determined probability. The one or more shared resources are allocated to the one or more subsystems based on the model.

Abstract: A condition of an asset including one or more subsystems connected in series is monitored. Each subsystem includes one or more components connected in parallel. The asset has one or more jobs. A probability of the asset surviving a predetermined amount of time is determined based on the monitoring and one or more shared resources. The one or more shared resources are configured to be shared between the subsystems. A model is established using a threshold based heuristic maintenance policy. The model is configured to maximize a number of successful jobs that the asset is able to complete based on the determined probability. The one or more shared resources are allocated to the one or more subsystems based on the model.

Abstract: Systems and methods include monitoring a health of at least one asset. A remaining useful life (RUL) of the at least one asset is estimated based on the monitoring. The RUL of the asset is categorized into categories comprising shorter than a time to complete a current mission and longer than the time to complete the current mission. One or more remedial actions are automatically performed during the current mission if the RUL is categorized as being less than the time to complete the current mission. The remedial actions comprise one or more of initiating a fail-safe mode, adapting a controller of the one or more assets, reconfiguration of the system, and adjusting the current mission of the one or more assets. Maintenance is scheduled for after the current mission of the at least one asset if the RUL is categorized as being greater than or equal to the time to complete the current mission.

Abstract: Systems and methods include monitoring a health of at least one asset. A remaining useful life (RUL) of the at least one asset is estimated based on the monitoring. The RUL of the asset is categorized into categories comprising shorter than a time to complete a current mission and longer than the time to complete the current mission. One or more remedial actions are automatically performed during the current mission if the RUL is categorized as being less than the time to complete the current mission. The remedial actions comprise one or more of initiating a fail-safe mode, adapting a controller of the one or more assets, reconfiguration of the system, and adjusting the current mission of the one or more assets. Maintenance is scheduled for after the current mission of the at least one asset if the RUL is categorized as being greater than or equal to the time to complete the current mission.

Abstract: Monitoring dynamic units that operate in complex, dynamic environments, is provided in order to classify and track unit behavior over time. When domain knowledge is available, feature-based models may be used to capture the essential state information of the units. When domain knowledge is not available, raw data is relied upon to perform this task. By analyzing logs of event messages (without having access to their data dictionary), embodiments allow the identification of anomalies (novelties). Specifically, a Normalized Compression Distance (such as one based on Kolmogorov Complexity) may be applied to logs of event messages. By analyzing the similarity and differences of the event message logs, units are identified that did not experience any abnormality (and locate regions of normal operations) and units that departed from such regions.

Abstract: Monitoring dynamic units that operate in complex, dynamic environments, is provided in order to classify and track unit behavior over time. When domain knowledge is available, feature-based models may be used to capture the essential state information of the units. When domain knowledge is not available, raw data is relied upon to perform this task. By analyzing logs of event messages (without having access to their data dictionary), embodiments allow the identification of anomalies (novelties). Specifically, a Normalized Compression Distance (such as one based on Kolmogorov Complexity) may be applied to logs of event messages. By analyzing the similarity and differences of the event message logs, units are identified that did not experience any abnormality (and locate regions of normal operations) and units that departed from such regions. Of particular interest is the detection and identification of units' epidemics, which is defined as sustained/increasing numbers of anomalies over time.

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.

Abstract: Systems and methods for determining the inspection schedule of a plurality of machines based on at least one operating condition including a monitoring system for determining at least one operating condition for a plurality of machines and a microprocessor programmed to analyze the at least one operating condition to identify whether a machine is unhealthy based on the analysis of at least one operating condition monitored and programmed to determine an optimal schedule for inspecting the plurality of machines using a PDC device.

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 for analyzing vibration including: acquiring a vibration signal; isolating a vibration signal event in the acquired signal; determining a frequency of a damped sinusoid of the vibration signal event, wherein the damped sinusoid characterizes the vibration signal event, and using the characteristic damped sinusoid to identify an occurrence of the vibration signal event in another vibration signal.

Abstract: Methods, systems, and computer program products are provided for implementing condition monitoring activities. Systems include a processor in communication with a machine being monitored. The processor receives signals output by the machine via a signal conversion element associated with the machine. Systems also include a display device in communication with the processor for providing signatures of the signals received from the signal conversion element. Systems further include a means for identifying, isolating, and capturing a signature from the signatures presented on the display device. The systems also include a means for digitizing and recording the signature as an event kernel, normalizing the event kernel by performing a mean removal, and normalizing the energy to unity on results of the mean removal. Systems further include a storage device for storing normalized event kernels.

Abstract: A method, system and computer product for estimating a remaining equipment life is provided. Data are collected relating to the parameters. The data are stored and integrated. Then, the remaining equipment life is estimated using the integrated data.