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: 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.

Abstract: System, method and computer product for incremental improvement of algorithm performance during algorithm development. In one aspect of this disclosure, there is a system, method and computer readable medium that stores instructions for instructing a computer system, to assess the performance of an algorithm during development. In this embodiment, a design of experiments component establishes an acceptable number of experiments for analyzing incremental improvements of the algorithm. An experiment performance component runs the established number of experiments for the algorithm. A simulation component simulates the behavior of the algorithm using results from the experiment performance component.

Abstract: A technique is provided for reducing motion-related artifacts present in CT images attributable to the dynamic nature of the imaged tissue or the time-varying concentration of a contrast agent. A region of interest that encompasses a structure of diagnostic significance is selected. For projections acquired by the various rows of detectors in a multi-slice CT imaging system, the portions of the projections attributable to the projection of the region of interest are averaged for each view angle. The projections containing these averaged values are then combined with the projections which do not encompass the region of interest. The combined projection set may be reconstructed to form a CT image of the dynamic tissue. In addition, a smoothing step may be performed to interpolate projection values around the region of interest to smooth the visual transition to the unaveraged portions of the image.

Abstract: The present invention provides methods and tools to aggregate information stemming from a plurality of different classification tools and supportive evidential information to arrive at a unified classification estimate. The information fusion system according to the present invention has a plurality of sensors associated with the system, where each sensor is related to at least one class of the system and is data-related to the at least one class. A plurality of classification tools are each designed to receive selected and pre-processed outputs from the sensors and to generate classification outputs representing a state of at least one class of the system. An information fusion tool is configured to receive the outputs of the classification tools as well as evidential information as inputs, and has an hierarchical architecture which manipulates the inputs to generate an output of aggregated fused information for a particular class of the system.

Abstract: A technique is provided for minimizing or eliminating motion-related artifacts present in CT images due to the dynamic nature of the imaged tissue or the time-varying concentration of a contrast agent used for imaging. The technique allows for the selection of a region of interest that may encompass a structure of diagnostic interest. For projections acquired by the various rows of detectors in a multi-slice CT imaging system, the portions of the projections attributable to the projection of the region of interest within the detector are averaged for each view angle. The projections containing these averaged values are then combined with the projections which do not encompass the region of interest and the combined projection set may be reconstructed to form a CT image of the dynamic tissue. In addition, a smoothing step may be performed to interpolate projection values around the region of interest to smooth the visual transition to the unaveraged portions of the image.

Abstract: System, method and computer product for incremental improvement of algorithm performance during algorithm development. In one aspect of this disclosure, there is a system, method and computer readable medium that stores instructions for instructing a computer system, to assess the performance of an algorithm during development. In this embodiment, a design of experiments component establishes an acceptable number of experiments for analyzing incremental improvements of the algorithm. An experiment performance component runs the established number of experiments for the algorithm. A simulation component simulates the behavior of the algorithm using results from the experiment performance component.

Abstract: A system and method for classifying unknown data patterns in a multi-variate feature space. An observer 12 evaluates the closeness of the data to any one of a plurality of known classes in a multi-variate feature space. A classifier 14 classifies the evaluated data into one of the plurality of known classes. A flagger 16 flags data having an unknown classification. A label requester 18 requests that the flagged data be interpreted into either a new class or one of the plurality of known classes. If the interpretation is a new fault, then a new class adder 22 sets up a new cluster representative of the fault and inputs the new class to the classifier 14. Alternatively, if the interpretation is that the flagged data belongs to one of the plurality of known classes, then a class resetter 24 resets the boundaries of this class and informs the classifier 14 of the change.

Abstract: This invention provides an improved alert generation system and method for trend performance analysis. A multi-variate abnormal condition detector normalizes data obtained from a process and classifies the data in a multi-dimensional space defined for the variables in the process. The normalized data are classified into either a normal or abnormal class. An alert evaluator evaluates the data classified in the abnormal class and determines whether the data are a true alert or a false alert. In another embodiment, the multi-variate abnormal condition detector and alert evaluator are used in parallel with a trend performance analysis tool to validate alerts generated therefrom.

Abstract: This invention provides a system and method for generating alerts through multi-variate assessment. A normalizer normalizes data obtained from a process. A classifier classifies the correlated data in a multi-dimensional space defined for the variables in the process. The normalized data are classified into a normal cluster indicative of normal operating conditions and at least one alert cluster each indicative of alert conditions. An alert verifier verifies correlated data classified as an alert condition. In another embodiment of this invention, a tracker is used for addressing drifting data sets that arise in the process over time which allows the adaptation of classifiers to the shifted state. In a third embodiment, the multi-variate generator is used in parallel with a trend performance analysis tool to validate alerts generated therefrom.