Abstract: Methods and apparatus are provided for analyzing a complex system that includes a number of subsystems. Each subsystem comprises at least one sensor designed to generate sensor data. Sensor data from at least one of the sensors is processed to generate binary evidence of a sensed event, and complex evidence of a sensed event. The complex evidence has more sophisticated mathematical properties than the binary evidence. The complex evidence comprises one or more of: a condition indicator (CI), a health indicator (HI), and a prognostic indicator (PI). A system fault model (SFM) is provided that defines statistical relationships between binary evidence, complex evidence, and an underlying failure mode (FM) that is occurring in the complex system. The binary evidence and the complex evidence are processed to identify failure modes taking place within one or more of the subsystems.

Abstract: Methods and apparatus are provided for detecting an anomaly in fuel demand data and fuel supply data generated by a fuel metering system for an engine, The method comprises collecting the fuel demand data and the fuel supply data during operation of the fuel metering system, generating expected fuel supply data based on the collected fuel demand data and a nominal response model describing the expected behavior of the fuel metering system, and detecting the anomaly if a difference between the expected fuel supply data and the collected fuel supply data exceeds a predetermined threshold.

Abstract: A method and apparatus are provided for autonomous data download. The method includes the steps of navigating an autonomous data download device to a first data storage device located in a mobile vehicle and parking the autonomous data download device adjacent to the first data storage device. The method further includes the steps of connecting the autonomous data download device to the first data storage device and downloading data from the first data storage device to the autonomous data download device. The method thereafter includes the steps of navigating the autonomous data download device to a location determined to be suitable for transmission of the data and transmitting the data from the autonomous data download device to a second data storage device after determining that the autonomous data download device has reached the location determined to be suitable for transmission of the data.

Abstract: A method for performing diagnostics for an engine comprises the steps of identifying an engine component as potentially being related to operational data of an engine, calculating a deviation from a thermodynamic model, and comparing the deviation with root cause deviation measures. The deviation relates the engine component to an adjustment to the thermodynamic model with respect to a variable of the thermodynamic model, based at least in part on the operational data. Each root cause deviation measure relates one of a plurality of potential root causes to the thermodynamic model with respect to the variable of the thermodynamic model.

Abstract: A sensing system comprising a radar-based vibration sensor and processing unit used to collect and process vibration information from a machine of interest. The radar-based vibration sensor obtains vibration data from mechanical operation of a component or series of components in the machine, and may be steered toward specific regions of interest of the machine. The processing unit analyzes the data, and may fuse data from a plurality of vibration sensors, such as radar-based vibration sensors and multiple machine-mounted sensors such as accelerometers. From this analysis, indications related to a status of the mechanical operation of the components in the machine of interest may be provided to relevant users.

Abstract: An RF beam is used to probe the presence or absence of a rotating blade in a known field of view. Timing of appearance or disappearance or “zero-crossing” of a reflected signal is correlated with timing of the blade movement.

Abstract: A method for benchmarking diagnostic algorithms for a particular application is provided. The diagnostic algorithms are rank ordered based on a specified criterion so as to weed out weak algorithms, selecting more robust algorithms, defined in some sense, for deployment. This is realized by evaluating various parameters subsequently mentioned. A normalized product entropy ratio parameter is obtained. A performance parameter vector is fixed to define a plurality of sensitivity parameters including a plurality of threshold parameters and a plurality of data parameters. The plurality of threshold parameters and the plurality of data parameters are perturbed to obtain a threshold sensitivity parameter and a data sensitivity parameter.

Abstract: Methods and apparatus are provided for analyzing a complex system that includes a number of subsystems. Each subsystem comprises at least one sensor designed to generate sensor data. Sensor data from at least one of the sensors is processed to generate binary evidence of a sensed event, and complex evidence of a sensed event. The complex evidence has more sophisticated mathematical properties than the binary evidence. The complex evidence comprises one or more of: a condition indicator (CI), a health indicator (HI), and a prognostic indicator (PI). A system fault model (SFM) is provided that defines statistical relationships between binary evidence, complex evidence, and an underlying failure mode (FM) that is occurring in the complex system. The binary evidence and the complex evidence are processed to identify failure modes taking place within one or more of the subsystems.

Abstract: Apparatus, systems, and methods for identifying a fault in an electronic system are provided. One apparatus includes memory storing a model of the electronic system, a processor, and a fault module. The processor is configured to pass system inputs through the model to generate corresponding simulated outputs, and the fault module is configured to determine the fault based on a comparison of the system outputs and the simulated outputs. A system includes an electronic system including multiple components generating system outputs based on system inputs and the apparatus for identifying a fault in the electronic system discussed above. One method includes generating a model of the electronic system, passing one or more inputs to the electronic system through the model to generate corresponding simulated outputs, and determining the fault based on a comparison of the one or more simulated outputs and one or more electronic system outputs.

Abstract: A system for obtaining diagnostic information, such as evidence about a mechanism, within an algorithmic framework, including filtering and aggregating the information through, for instance, a stochastic process. The output may be an overall belief value relative to a presence of an item such as, for example, a fault in the mechanism.

Abstract: Methods and apparatus are provided for detecting an anomaly in fuel demand data and fuel supply data generated by a fuel metering system for an engine. The method comprises collecting the fuel demand data and the fuel supply data during operation of the fuel metering system, generating expected fuel supply data based on the collected fuel demand data and a nominal response model describing the expected behavior of the fuel metering system, and detecting the anomaly if a difference between the expected fuel supply data and the collected fuel supply data exceeds a predetermined threshold.

Abstract: A testbed for testing health of software includes an input model, a hardware model, and a resource modeler. The input model represents an input system used in conjunction with the software. The hardware model represents one or more hardware components used in conjunction with the software. The resource modeler is coupled to the input model and the hardware model, and is configured to estimate effects on the software of conditions of the hardware components, the input system, or both.

Abstract: A health monitoring system for a vehicle system includes a plurality of diagnostics systems and a bus. Each of the plurality of diagnostics and prognostics systems corresponding to a different sub-system of the vehicle system and configured to at least facilitate generating diagnostic and prognostic system output pertaining to the sub-system based at least in part on data, each of the plurality of diagnostics and prognostics systems comprises a diagnostics component comprising an analytics framework and a core. The analytics framework is configured to receive formatted data and to generate diagnostic determinations based at least in part thereon. The core is coupled to the analytics framework, and is configured to transform data into formatted data and provide the formatted data to the analytics framework. The bus is coupled to the plurality of diagnostics and prognostics systems, and is configured to at least facilitate providing the data thereto.

Abstract: A Java-MATLAB bridge is provided for enabling utilization of MATLAB® functionality in an enterprise environment. The Java-MATLAB bridge includes a Java® wrapper and a MATLAB wrapper. The MATLAB wrapper is coupled to the Java wrapper and the Java wrapper provides an entry point for invoking the MATLAB functionality in the enterprise environment.

Abstract: Various methods, devices, systems, and computer programs are disclosed relating to the use of models to represent systems and processes (such as manufacturing and production plants). For example, a method may include generating a first model and a second model using operating data associated with a system or process. The method may also include using the first and second models to predict one or more events associated with the system or process. The one or more events are predicted by generating one or more initial event predictions using the first model and adjusting the one or more initial event predictions using the second model. The first model may represent a Principal Component Analysis (PCA) model, and the second model may represent a Fuzzy Logic model.

Abstract: A system and method for fault detection is provided. The fault detection system provides the ability to detect symptoms of fault in turbine engines and other mechanical systems that have nonlinear relationships. The fault detection system uses a neural network to perform a data representation and feature extraction where the extracted features are analogous to principal components derived in a principal component analysis. This neural network data representation analysis can then be used to determine the likelihood of a fault in the system.

Abstract: A system and method is provided to detect surface anomalies. The detection system and method provides the ability to automatically detect and characterize anomalies on a surface, such as detecting and characterizing pitting corrosion on metal surfaces. The surface anomaly detection system and method uses an image of the surface under evaluation. The image data is passed to a noise filter. The noise filter uses an estimated characterization of the background noise to remove the background noise from the image data. The smoothed pixel intensity is then compared to a threshold to identify significant departures. The detected anomalies are then passed to a contour detector, which determines the contours of anomalies in the surface to provide more precise characterization of the detected anomalies. The detected closed contours of anomalies may then be passed to a defect severity estimator that provides an anomaly factor metric.

Abstract: A method of predicting deterioration in a mechanical device includes the steps of providing a health model for the mechanical device, the health model including a plurality of health states for modeling the mechanical device, receiving device data for the mechanical device, estimating values for the plurality of health states, based on the device data, predicting one or more events based on the health model and the device data, each of the one or more events affecting one or more of the plurality of health states, and generating a prediction of deterioration in the mechanical device from the estimated values for the plurality of health states and the one or more predicted events.

Abstract: Apparatus, systems, and methods for identifying a fault in an electronic system are provided. One apparatus includes memory storing a model of the electronic system, a processor, and a fault module. The processor is configured to pass system inputs through the model to generate corresponding simulated outputs, and the fault module is configured to determine the fault based on a comparison of the system outputs and the simulated outputs. A system includes an electronic system including multiple components generating system outputs based on system inputs and the apparatus for identifying a fault in the electronic system discussed above. One method includes generating a model of the electronic system, passing one or more inputs to the electronic system through the model to generate corresponding simulated outputs, and determining the fault based on a comparison of the one or more simulated outputs and one or more electronic system outputs.

Abstract: A method and apparatus are provided for autonomous data download. The method includes the steps of navigating an autonomous data download device to a first data storage device located in a mobile vehicle and parking the autonomous data download device adjacent to the first data storage device. The method further includes the steps of connecting the autonomous data download device to the first data storage device and downloading data from the first data storage device to the autonomous data download device. The method thereafter includes the steps of navigating the autonomous data download device to a location determined to be suitable for transmission of the data and transmitting the data from the autonomous data download device to a second data storage device after determining that the autonomous data download device has reached the location determined to be suitable for transmission of the data.