44 results about "Uncertainty estimate" patented technology

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.

Predicting the remaining life of individual aircraft, fleets of aircraft, aircraft components and subpopulations of these components. This is accomplished through the use of precomputed databases of response that are generated from a model for the nonlinear system behavior prior to the time that decisions need to be made concerning the disposition of the system. The database is calibrated with a few data points, to account for unmodeled system variables, and then used with an input variable to predict future system behavior. These methods also permit identification of the root causes for observed system behavior. The use of the response databases also permits rapid estimations of uncertainty estimates for the system behavior, such as remaining life estimates, particularly, when subsets of an input variable distribution are passed through the database and scaled appropriately to construct the output distribution. A specific example is the prediction of remaining life for an aircraft component where the model calculates damage evolution, input variables are a crack size and the number of cycles, and the predicted parameters are the actual stress on the component and the remaining life.

An aspect of the invention provides instantaneous Wi-Fi positioning that is robust to outliar APs using a recursive centroid method. It estimates user position and uncertainty based on the current list of scanned APs. Another aspect of the invention provides a Wi-Fi navigation solution that estimates good Wi-Fi positions even in the areas of low AP density and further improves robustness to outliar APs. Wi-Fi navigation solution improves the estimate of instantaneous Wi-Fi positioning by using a 4-state Kalman filter, which models user dynamics. As a result, the uncertainty estimate of the Wi-Fi positions is accurately estimated, thereby, making it suitable for blending with GNSS.

Systems and methods for computing uncertainty include generating a surface model of a target anatomical object from medical imaging data of a patient. Uncertainty is estimated at each of a plurality of vertices of the surface model. The uncertainty estimated at each of the plurality of vertices is visualized on the surface model.

Method for estimating uncertainty in a physical property model generated by inverting measured geophysical data, for example a resistivity model inferred from electromagnetic field data. The method involves as few as one data inversion (32) coupled with a number of forward simulations (37). Alternative solutions (models) are generated (39) by probing a perturbation space (35) defined from a reduced model space (34), resulting from a principal component decomposition (33) of the inverted model, and selecting some of the larger components. Statistical analysis techniques may be applied (to those alternative solutions remaining after thresholding) to generate quantitative uncertainty estimates (42) applicable to the inverted model (32).

A method of determining an uncertainty estimate of an estimated velocity of an object includes, determining the uncertainty with respect to a first estimated coefficient and a second estimated coefficient of the velocity profile equation of the object. The first estimated coefficient being assigned to a first spatial dimension of the estimated velocity and the second estimated coefficient being assigned to a second spatial dimension of the estimated velocity. The velocity profile equation represents the estimated velocity in dependence of the first estimated coefficient and the second estimated coefficient. The method also includes determining the uncertainty with respect to an angular velocity of the object, a first coordinate of the object in the second spatial dimension, and a second coordinate of the object in the first spatial dimension.

The invention discloses a high-confidence coefficient statistical inference and confirmation method for limited quantity product performance failure rates. The method comprises the following steps of:1, carrying out small sample sampling to obtain performance data; 2, estimating a limited quantity product performance parameter mean value and a standard deviation and quantifying uncertainties: (1)determining reliabilities (as shown in the specification) of binomial distributions, (2) determining relative uncertainties estimated by the reliabilities (as shown in the specification) of the binomial distributions, and (3) estimating performance parameter values and quantifying uncertainties of the performance parameter values; and 3, estimating a limited quantity product performance failure rate (number). The method is an effective method capable of reducing the product performance checking and testing number, correctly judging whether limited quantity product performance failure rates (numbers) achieve stipulated requirements or not and ensuring that the judging results have relatively high credibility in production, acceptance, storage and using of current limited quantity products.

The present invention relates to a smart conversion and calibration of the defect coordinate, diagnosis, sampling system and the method thereof for manufacturing fab is provided. The intelligent defect diagnosis method comprises: receiving pluralities of defect data, design layout data, analyzing the defect data, design layouts, by a Critical Area Analysis (CAA) system, wherein the analyzing step further contains the sub-steps: superposing the defect contour pattern and the design layout, performing CAA to identify a killer or non-killer defect based on the open or short failure probability, defects are classified as high, medium, low, or negligible risk defect based on the Killer Defect Index, defect signal parameters, selecting defect samples based on the defect classification data, selecting alarm defect and filtering false defect with pattern match with defect pattern library and frequent failure defect library, performing coordinate conversion and pattern match between image contour and design layout for coordinate correction, creating a CAA accuracy correction system and defect size calibration system by analyzing original defect size data and defect contour size from image analysis, evaluating the defect size using measurement uncertainty analysis with statistical analysis methods to reach the purposes of increasing CAA accuracy and Killer Defect identification rate.

The invention relates to an uncertainty analysis model for determining heavy metals in capsules with ICP-MS (inductively coupled plasma mass spectrometry) and an establishment method of the uncertainty analysis model, and belongs to the technical field of ICP-MS detection. The method comprises the following steps: data acquisition: designing a recovery rate test, determining the content of heavy metal elements in the recovery test of gelatin hollow capsules with ICP-MS, and collecting data; model establishment: according to the calculation formula of heavy metal element content, analyzing thesource of uncertainty, establishing a measurement model and evaluating and calculating uncertainty. According to the uncertainty analysis model for determining heavy metals in capsules with ICP-MS, bydesigning the recovery rate test, establishing the measurement model, evaluating and calculating uncertainty, factors that can affect test results in the test of determining the content of the heavymetals in the capsules with ICP-MS are analyzed, control of main influencing factors can be enhanced, so that measurement stability is reduced, and reliability of measurement results is guaranteed.

The invention discloses a multi-phase flow measurement method and system based on uncertainty analysis. The method comprises the following steps of: based on an equivalent flow of cross-correlation time delay and a capacitance measurement value, obtaining liquid phase flow and relative standard uncertainty thereof, and gas phase flow and standard uncertainty thereof through multiple linear regression fitting; based on the capacitance measurement value and a differential pressure measurement value, obtaining liquid phase flow and relative standard uncertainty thereof as well as gas phase flow and standard uncertainty thereof through multiple linear regression fitting; on the basis of the differential pressure measurement value and the equivalent flow of cross-correlation time delay, obtaining liquid phase flow and relative standard uncertainty thereof as well as gas phase flow and standard uncertainty thereof through multiple linear regression fitting; and comparing the uncertainties obtained in different modes, and taking the gas and liquid flow corresponding to the minimum uncertainty and the uncertainty as quality indexes for flow measurement. Errors of measurement results can be reduced, and operation and maintenance personnel can be helped to know the accuracy of the measurement results.

The invention discloses a Barkhausen signal randomness measurement and conversion method. The method comprises the following steps: S1, determining an original feature sample space of signal features;s2, calculating a feature probability distribution space of an original feature sample space; s3, reconstructing an original feature sample space; s4, inputting the original feature sample space andthe reconstructed feature sample space into a prediction model for prediction; s5, comparing prediction results to obtain interval indexes, and taking the interval indexes as Barkhausen signal randomness measurement results; and S6, adding ordered quantized noise to the Barkhausen signal of the selected interval index to complete the conversion of the randomness of the Barkhausen signal. The invention relates to research on a randomness measurement and conversion method of a Barkhausen signal which is a nondestructive testing technology, is completed by means of Bayesian uncertainty analysis,is greatly helpful to deeply understand the intrinsic random characteristics of the Barkhausen signal, and enables the characteristics in different states to be more differentiated through probabilityconversion.

A handover notification arrangement is configured to provide a handover notification in a driver environment of a vehicle having autonomous driving capabilities. The handover notification arrangement includes a road information arrangement configured to acquire road information representative of an upcoming road section at which the autonomous driving is likely to become at least partially disabled. The handover notification arrangement further includes a processing unit configured to calculate an estimated time available for autonomous driving and configured to calculate an uncertainty estimate of the estimated time available for autonomous driving. The handover notification arrangement is configured to cause the output unit to provide the handover notification such that the handover notification is provided earlier in cases of high uncertainty estimates than in cases of low uncertainty estimates. The present disclosure also describes a vehicle and a method of providing a handover notification.

The present invention relates to a smart defect calibration, diagnosis, sampling system and the method thereof for manufacturing fab is provided. The intelligent defect diagnosis method comprises: receiving pluralities of defect data, design layout data, analyzing the defect data, design layouts, by a Critical Area Analysis (CAA) system, wherein the analyzing step further contains the sub-steps: superposing the defect contour pattern and the design layout, performing CAA to identify a killer or non-killer defect based on the open or short failure probability, defects are classified as high, medium, low, or negligible risk defect based on the Killer Defect Index, defect signal parameters, selecting defect samples based on the defect classification data, selecting alarm defect and filtering false defect with pattern match with defect pattern library and frequent failure defect library, performing coordinate conversion and pattern match between image contour and design layout for coordinate correction, creating a CAA accuracy correction system and defect size calibration system by analyzing original defect size data and defect contour size from image analysis, evaluating the defect size using measurement uncertainty analysis with statistical analysis methods to reach the purposes of increasing CAA accuracy and Killer Defect identification rate.

A method of mitigating filter inconsistency of a heading estimate in an inertial navigation system is provided. The method includes inputting inertial measurements from at least one low-performance inertial measurement unit (IMU) in the inertial navigation system; inputting an initial-heading from at least one heading-information source; inputting an initial-heading uncertainty level associated with an error in the inputted initial-heading; initializing an initial-heading estimate with the inputted initial-heading; initializing an initial-heading uncertainty estimate with the inputted initial-heading uncertainty level; initializing an accumulated heading-change estimate to zero at a startup of the at least one low-performance IMU; and initializing an accumulated heading-change uncertainty estimate with an initial accumulated heading-change uncertainty level that is a value less than the inputted initial-heading uncertainty level; and periodically updating the accumulated heading-change estimate with the inertial measurements input from the at least one low-performance IMU.

The present invention relates to a method and a device for determining the hydro-dynamic properties of the fluid system surrounding the brain and the spinal cord, the so called cerebrospinal fluid system, whereby the method comprises continuous pressure measurement through a fluid contact passage and active infusion of artificial cerebrospinal fluid through another fluid contact passage to a number of pressure-flow levels, and analysis of the connections between the measured pressures and flows. The method uses an adaptive way of procedure which on each pressure-flow level takes account for the measure time and the patient's fluctuations in physiologic signals for calculating in real time when the relation between the measure time and measure accuracy in pressure and flow on the actual pressure-flow level is sufficient and at an optimum, whereupon the investigation or examination is automatically proceeding to the next level according to a predetermined protocol. In this way, the method gives rise to an investigation with measurements having sufficient pressure and flow information on each level, which forms a base for determination in a correct manner, with an uncertainty estimate, of the patient's hydrodynamic parameters. The device comprises a hose pump (1) for infusion of artificial cerebrospinal fluid in a bottle or bag (2), a standardized hose set including a pump hose (3) and pressure transducers (4) for continuous registration of the intracranial pressure, an invasive contact object (5) for creating fluid contact with the cerebrospinal fluid system and consisting of needles or a catheter, as well as a computer (12) with software for computerized collection and analysis as well as control of pump speed. The device uses a computerized implementation of the above-mentioned adaptive method in order to systematically and safely carry through a standardized protocol which generates pressure and flow information which the software of the measure system then uses for determining in real time and with an uncertainty estimate, the hydrodynamic parameters of the system.

The invention discloses an uncertainty evaluation device and method of an indirect full-optical path spectrum detection system. The uncertainty evaluation device includes a constant temperature oil tank, an optical fiber pressure detection system, a computer, a high-precision platinum resistor and a grating sensor. The evaluation method comprises the following steps that: test data are obtained; a measurement model is established; the uncertainty of the work straight line of the grating sensor is evaluated; and the uncertainty of the optical fiber pressure detection system is evaluated. According to the uncertainty evaluation device and method of the indirect full-optical path spectrum detection system of the invention, the grating sensor is adopted; uncertainty evaluation is performed on the measurement accuracy of picometer-level wavelength shift quantity of a non-removable wavelength modulation type optical fiber pressure detection system through adopting an indirect method; an uncertainty analysis experimental system is designed and constructed; system error sources are analyzed; a theoretical measurement model and an uncertainty analysis method are established; and the uncertainty value of system measurement errors can be obtained.