Abstract: A wind anemometer comprises a light source for transmitting pulsed light signals, a receiver for receiving backscattered signals from airborne particles for each pulse of the transmitted pulsed light signals, a detector for detecting the received backscattered signals, and a processor to determine location of the airborne particles with respect to the anemometer based on the detected backscattered signals. The processor estimates wind velocity using changes in location of the airborne particles over at least one time interval.

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 biometric sample training device, a biometric sample quality assessment device, a biometric fusion recognition device, an integrated biometric fusion recognition system and example processes in which each may be used are described. Wavelets and a boosted classifier are used to assess the quality of biometric samples, such as facial images. The described biometric sample quality assessment approach provides accurate and reliable quality assessment values that are robust to various degradation factors, e.g., such as pose, illumination, and lighting in facial image biometric samples. The quality assessment values allow biometric samples of different sample types to be combined to support complex recognition techniques used by, for example, biometric fusion devices, resulting in improved accuracy and robustness in both biometric authentication and biometric recognition.

Abstract: A method of analyzing partial discharge data collected from an electrical device includes collecting partial discharge data from a first electrical device belonging to a group of electrical devices. The group of electrical devices is at least partially defined by at least one electrical device classification. The method also includes generating a comparison of at least a portion of the partial discharge data collected from the first electrical device with at least a portion of the partial discharge data collected from at least one second electrical device. The at least one second electrical device is selected from the group of electrical devices that includes the first electrical device. The method further includes transmitting the results.

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 and system for automatically developing a fault classification system from time series data. The sensors need not have been intended for diagnostic purposes (e.g., control sensors). These methods and systems are functionally independent of knowledge related to a particular equipment system, thereby allowing seamless application to multiple systems, regardless of the suite of sensors in each system. Because this algorithm is totally automated, substantial savings in time and development cost can be achieved. The algorithm results in a classification system and a set of features that might be used to develop alternative classification systems without human intervention.

Abstract: A method and system for performing model-based multi-objective asset optimization and decision-making is provided. The method includes building at least two predictive models for an asset. The building includes categorizing operational historical data via at least one of: controllable variables, uncontrollable variables, output objectives, and constraints. The building also includes selecting at least two output objectives or constraints, and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints. The method also includes validating each predictive model and performing multi-objective optimization using the predictive models. The multi-objective optimization includes specifying search constraints and applying a multi-objective optimization algorithm. The method further includes generating a Pareto Frontier, and selecting a Pareto optimal input-output vector.

Abstract: A method of analyzing partial discharge data collected from an electrical device includes collecting partial discharge data from a first electrical device belonging to a group of electrical devices. The group of electrical devices is at least partially defined by at least one electrical device classification. The method also includes generating a comparison of at least a portion of the partial discharge data collected from the first electrical device with at least a portion of the partial discharge data collected from at least one second electrical device. The at least one second electrical device is selected from the group of electrical devices that includes the first electrical device. The method further includes transmitting the results.

Abstract: A circuit interrupter for interrupting current on a line conductor is provided. The circuit interrupter includes separable contacts, a trip mechanism, a bimetal, a microprocessor, a series arc detection sequence, a low-pass filter circuit, and a high-pass filter circuit. The trip mechanism selectively opens the separable contacts when activated. The series arc detection sequence is resident on the microprocessor and includes a plurality of series fault detection algorithms. The low-pass filter circuit provides a low-pass signal to the series arc detection sequence. The high-pass filter circuit provides a high-pass signal to the series arc detection sequence. The sequence selects a particular algorithm from the plurality of algorithms based on the low-pass signal. The sequence calculates a plurality of statistical features from the high-pass signal and sends an output signal to activate the trip mechanism based on a comparison of the plurality of statistical features to the particular algorithm.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A circuit interrupter for interrupting current on a line conductor is provided. The circuit interrupter includes separable contacts, a trip mechanism, a bimetal, a microprocessor, a series arc detection sequence, a low-pass filter circuit, and a high-pass filter circuit. The trip mechanism selectively opens the separable contacts when activated. The series arc detection sequence is resident on the microprocessor and includes a plurality of series fault detection algorithms. The low-pass filter circuit provides a low-pass signal to the series arc detection sequence. The high-pass filter circuit provides a high-pass signal to the series arc detection sequence. The sequence selects a particular algorithm from the plurality of algorithms based on the low-pass signal. The sequence calculates a plurality of statistical features from the high-pass signal and sends an output signal to activate the trip mechanism based on a comparison of the plurality of statistical features to the particular algorithm.

Abstract: A method for switching route and a network device are disclosed, wherein the method comprises: setting a relationship between a port number of each destination port and a port number of the transmitting port, the port number of each transmitting port is the port number of the corresponding destination port; when there is a service failure in any destination port, modifying the port number of the transmitting port corresponding to a fault destination port into the port number of the backup port corresponding to the fault destination port in the set relationship, and saving the modified relationship; after receiving a data packet, the network device transmitting the data packet based on the saved relationship. The network device comprises a CPU, a first routing unit and a second routing unit. In accordance with the present invention, the time consumed by modifying routing data can be reduced, enabling the network device to switch route quickly and the user services to recover quickly.

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 of detecting a series arc in an alternating current electrical system is provided. The method is a pattern-recognition based approach and includes passing raw current signals from a conductor in the electrical system through one or more filters to provide a filtered signal; extracting one or more features from the filtered signal; and classifying the features to a known state representative of the series arc.

Abstract: A circuit interrupter for interrupting current on a line conductor is provided. The circuit interrupter includes separable contacts, a trip mechanism, a bimetal, a microprocessor, a series arc detection sequence, a low-pass filter circuit, and a high-pass filter circuit. The trip mechanism selectively opens the separable contacts when activated. The series arc detection sequence is resident on the microprocessor and includes a plurality of series fault detection algorithms. The low-pass filter circuit provides a low-pass signal to the series arc detection sequence. The high-pass filter circuit provides a high-pass signal to the series arc detection sequence. The sequence selects a particular algorithm from the plurality of algorithms based on the low-pass signal. The sequence calculates a plurality of statistical features from the high-pass signal and sends an output signal to activate the trip mechanism based on a comparison of the plurality of statistical features to the particular algorithm.

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 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 and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.