Patents Assigned to Smartsignal Corporation
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Patent number: 8660980Abstract: A monitoring system for determining the condition of an object includes an empirical model with reference data that indicates the normal operational state of the object, and input pattern arrays. Each input pattern array has a plurality of time-ordered input vectors, while each input vector has input values representing a plurality of parameters indicating the current condition of the object. The empirical model generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. A differencing module compares the estimates values to the corresponding input values so that resulting values from the comparison can be used to determine the condition of the object.Type: GrantFiled: July 19, 2011Date of Patent: February 25, 2014Assignee: Smartsignal CorporationInventor: James P. Herzog
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Patent number: 8620853Abstract: A method for monitoring the condition of an object includes obtaining reference data that indicates the normal operational state of the object, and obtaining input pattern arrays. Each input pattern array has a plurality of time-ordered input vectors, while each input vector has input values representing a plurality of parameters indicating the current condition of the object. Then at least one processor generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. The estimate values are compared to the corresponding input values so that resulting values from the comparison can be used to determine the condition of the object.Type: GrantFiled: July 19, 2011Date of Patent: December 31, 2013Assignee: SmartSignal CorporationInventor: James P. Herzog
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Publication number: 20130031019Abstract: A monitoring system for determining the future behavior of a financial system includes an empirical model to receive reference data that indicates the normal behavior of the system and input pattern arrays. Each input pattern array has a plurality of input vectors, while each input vector represents a time point and has input values representing a plurality of parameters indicating the current condition of the system. The model generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. The estimate values, in the form of an estimate matrix, include at least one estimate vector of inferred estimate values, and represents at least one time point that is not represented by the input vectors. The inferred estimate values are used to determine a future behavior of the financial system.Type: ApplicationFiled: October 5, 2012Publication date: January 31, 2013Applicant: SmartSignal CorporationInventor: SmartSignal Corporation
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Publication number: 20130024166Abstract: A monitoring system for determining the condition of an object includes an empirical model with reference data that indicates the normal operational state of the object, and input pattern arrays. Each input pattern array has a plurality of time-ordered input vectors, while each input vector has input values representing a plurality of parameters indicating the current condition of the object. The empirical model generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. A differencing module compares the estimates values to the corresponding input values so that resulting values from the comparison can be used to determine the condition of the object.Type: ApplicationFiled: July 19, 2011Publication date: January 24, 2013Applicant: SmartSignal CorporationInventor: James P. Herzog
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Publication number: 20130024415Abstract: A method for monitoring the condition of an object includes obtaining reference data that indicates the normal operational state of the object, and obtaining input pattern arrays. Each input pattern array has a plurality of time-ordered input vectors, while each input vector has input values representing a plurality of parameters indicating the current condition of the object. Then at least one processor generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. The estimate values are compared to the corresponding input values so that resulting values from the comparison can be used to determine the condition of the object.Type: ApplicationFiled: July 19, 2011Publication date: January 24, 2013Applicant: SmartSignal CorporationInventor: James P. Herzog
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Publication number: 20130024416Abstract: A method for determining the future operational condition of an object includes obtaining reference data that indicates the normal operational state of the object, and obtaining input pattern arrays. Each input pattern array has a plurality of input vectors, while each input vector represents a time point and has input values representing a plurality of parameters indicating the current condition of the object. At least one processor generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. The estimate values, in the form of an estimate matrix, include at least one estimate vector of inferred estimate values, and represents at least one time point that is not represented by the input vectors. The inferred estimate values are used to determine a future condition of the object.Type: ApplicationFiled: July 19, 2011Publication date: January 24, 2013Applicant: SmartSignal CorporationInventor: James P. Herzog
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Publication number: 20130024414Abstract: A monitoring system for determining the future operational condition of an object includes an empirical model to receive reference data that indicates the normal operational state of the object and input pattern arrays. Each input pattern array has a plurality of input vectors, while each input vector represents a time point and has input values representing a plurality of parameters indicating the current condition of the object. The model generates estimate values based on a calculation that uses an input pattern array and the reference data to determine a similarity measure between the input values and reference data. The estimate values, in the form of an estimate matrix, include at least one estimate vector of inferred estimate values, and represents at least one time point that is not represented by the input vectors. The inferred estimate values are used to determine a future condition of the object.Type: ApplicationFiled: July 19, 2011Publication date: January 24, 2013Applicant: SmartSignal CorporationInventor: James P. Herzog
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Patent number: 8311774Abstract: An apparatus and associated method are utilized for monitoring an operation of a system characterized by operational parameters. A non-parametric empirical model generates estimates of parameter values in response to receiving a query vector of monitored parameters for a model characterizing the system. A distance estimation engine (a) determines robust distances between the query vector and each of a set of predetermined historical vectors for the non-parametric empirical model based on an implementation of an elemental kernel function; (b) determines weights for the monitored parameters based on the robust distances; and (c) combining the weights with the predetermined historical vectors to make predictions for the system.Type: GrantFiled: December 14, 2007Date of Patent: November 13, 2012Assignee: SmartSignal CorporationInventor: J. Wesley Hines
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Patent number: 8275577Abstract: A method and apparatus are provided for diagnosing faults in a monitored system that is monitored by sensors. An empirical model is generated for a targeted component of the monitored system. The empirical model is trained with an historical data source that contains example observations of the sensors. Substantially real-time estimates are generated based on instrumented data corresponding to the targeted component. The substantially real-time estimates are compared and differenced with instrumented readings from the sensors to provide residual values. The residual values are analyzed to detect the faults and determine a location of the faults in the monitored system.Type: GrantFiled: September 18, 2007Date of Patent: September 25, 2012Assignee: SmartSignal CorporationInventor: James P. Herzog
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Patent number: 8239170Abstract: A system, method and program product for monitoring a complex signal for ultrasensitive detection of state changes, or for signature recognition and classification is provided. A complex signal is decomposed periodically for empirical modeling. Wavelet analysis, frequency band filtering or other methods may be used to decompose the complex signal into components. A library of signature data may be referenced for selection of a recognized signature in the decomposed complex signal. The recognized signature may indicate data being carried in the complex signal. Estimated signal data may be generated for determination of an operational state of a monitored process or machine using a statistical hypothesis test with reference to the decomposed input signal.Type: GrantFiled: March 26, 2008Date of Patent: August 7, 2012Assignee: Smartsignal CorporationInventor: Stephan W. Wegerich
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Publication number: 20110119108Abstract: A method for modeling the behavior of a visitor to an e-commerce location includes the steps of automatically obtaining one or more visitor characteristic values, and automatically developing a model of the visitor's behavior according to a nonlinear state estimation technique (NSET). The method also includes then automatically estimating a set of visitor behavior characteristic values with said model that model said visitor's behavior.Type: ApplicationFiled: November 8, 2010Publication date: May 19, 2011Applicant: SmartSignal CorporationInventors: Christopher L. Black, J. Wesley Hines
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Patent number: 7941701Abstract: A method and apparatus are provided for diagnosing faults in a monitored system. Estimates of parameter data are generated from the system with reference parameter data characteristic of known behavior of the system. The generated estimates of the parameter data are compared with measured parameter data. A residual is determined for each of the parameters based on a relationship between the estimates of the parameter data and the measured parameter data. A fuzzy classification rule is implemented to determine a likelihood that a predetermined fault exists by using residuals for parameters used to indicate the existence of the predetermined fault.Type: GrantFiled: August 1, 2008Date of Patent: May 10, 2011Assignee: SmartSignal CorporationInventors: Stephan W. Wegerich, Chad Stoecker, Richard Marcell
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Patent number: 7739096Abstract: System and method for selection of appropriate modeling data from a general data set to characterize a modeled process. The data is typically correlated sensor data, representing a multitude of snapshots of a sensed machine or process. The invention accommodates selection of greater amounts of general data for inclusion in the modeling data where that data exhibits greater dynamics, and selects less data from regions of little change. The system can comprise a computer running a software program, or a microprocessor.Type: GrantFiled: February 16, 2001Date of Patent: June 15, 2010Assignee: SmartSignal CorporationInventors: Stephan W. Wegerich, Alan D. Wilks, Andre Wolosewicz
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Patent number: 7640145Abstract: A method for systematically configuring and deploying an empirical model used for fault detection and equipment health monitoring. The method is driven by a set of data preprocessing and model performance metrics subsystems that when applied to a raw data set, produce an optimal empirical model.Type: GrantFiled: April 24, 2006Date of Patent: December 29, 2009Assignee: SmartSignal CorporationInventors: Stephan W. Wegerich, Andre Wolosewicz, Xiao Xu, James P. Herzog, Robert Matthew Pipke
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Patent number: 7539597Abstract: A system for empirically diagnosing a condition of a monitored system. Estimates of monitored parameters from a model of the system provide residual values that can be analyzed for failure mode signature recognition. Residual values can also be tested for alert (non-zero) conditions, and patterns of alerts thus generated are analyzed for failure mode signature patterns. The system employs a similarity operator for signature recognition and also for parameter estimation. Failure modes are empirically determined, and precursor data is automatically analyzed to determine differentiable signatures for failure modes.Type: GrantFiled: October 9, 2003Date of Patent: May 26, 2009Assignee: SmartSignal CorporationInventors: Stephan W. Wegerich, Andre Wolosewicz, R. Matthew Pipke
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Patent number: 7409320Abstract: A system, method and program product for monitoring a complex signal for ultrasensitive detection of state changes, or for signature recognition and classification is provided. A complex signal is decomposed periodically for empirical modeling. Wavelet analysis, frequency band filtering or other methods may be used to decompose the complex signal into components. A library of signature data may be referenced for selection of a recognized signature in the decomposed complex signal. The recognized signature may indicate data being carried in the complex signal. Estimated signal data may be generated for determination of an operational state of a monitored process or machine using a statistical hypothesis test with reference to the decomposed input signal.Type: GrantFiled: May 11, 2005Date of Patent: August 5, 2008Assignee: Smartsignal CorporationInventor: Stephan W. Wegerich
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Patent number: 7403869Abstract: Reference data observations for given system are used to develop a reference set of such observations. Subsequent observations (comprising, in one embodiment, current observations) are then used to facilitate selection of portions of this reference set to yield a resultant set of observations that serves as a model. This model can then be used in comparison to actual system performance to detect, for example, a trend towards a faulty condition. Pursuant to a preferred approach, the model is recomputed from time to time and, pursuant to a particular embodiment, is recomputed with each new set of current observations.Type: GrantFiled: April 29, 2005Date of Patent: July 22, 2008Assignee: Smartsignal CorporationInventors: Stephan W. Wegerich, Xiao Xu
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Patent number: 7386426Abstract: An NSET method and apparatus for modeling and monitoring the status of a system is disclosed. The NSET employs a nonlinear similarity operator in place of linear matrix multiplication, to estimate a set of sensor data based on learned reference data, responsive to receiving a set of actual sensor data. Regularization is used in the generation of the estimate. The estimated data values and the actual sensor data are differenced to produce residuals, which are statistically tested with a SPRT to detect anomalies. Cluster centers may be used to represent learned reference data. The detection of anomalies can be used advantageously for sensor calibration verification.Type: GrantFiled: April 28, 2000Date of Patent: June 10, 2008Assignee: Smartsignal CorporationInventors: Christopher L. Black, J. Wesley Hines
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Patent number: 7373283Abstract: A method and apparatus for improved monitoring the operational state of instrumented systems is provided. An empirical model characterizes normal or desirable operation of the system, and real-time observations are provided to the model to generate estimates of expected sensor values. Comparison of the estimates with the real-time observations provides advanced warning of discrepancies in the operational state of the instrumented system. The invention provides for incipient failure detection, sensor failure detection and incipient process upset. An improved similarity operator provides for estimates that are not impaired by real-time observations at or beyond the limits of modeled data. The similarity operator comprises a difference function added to a constant, and the result is inverted.Type: GrantFiled: February 22, 2001Date of Patent: May 13, 2008Assignee: Smartsignal CorporationInventors: James P. Herzog, Stephan W. Wegerich
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Publication number: 20080071501Abstract: A method and apparatus are provided for diagnosing faults in a monitored system that is monitored by sensors. An empirical model is generated for a targeted component of the monitored system. The empirical model is trained with an historical data source that contains example observations of the sensors. Substantially real-time estimates are generated based on instrumented data corresponding to the targeted component. The substantially real-time estimates are compared and differenced with instrumented readings from the sensors to provide residual values. The residual values are analyzed to detect the faults and determine a location of the faults in the monitored system.Type: ApplicationFiled: September 18, 2007Publication date: March 20, 2008Applicant: SMARTSIGNAL CORPORATIONInventor: James HERZOG