General Electric Company

Thomas Alan Early

Waseem Ibrahim Faidi

Nilesh Tralshawala

Thomas Miebach

Necip Doganaksoy

William Thomas Dixon

John Anthony DeLuca

Bernadette Mondragon Bennett

Elizabeth Anne Williams

Structural health monitoring using nuclear quadrupole resonance is disclosed. For example, in one embodiment, a method of monitoring stress is provided. The method includes scanning a composite using an NQR spectrometer, the composite having a polymer matrix and a microcrystalline material disposed in the matrix. The microcrystalline material includes molecules having nuclei with respective nuclear quadrupole moments. The method also includes determining microscopic strain distribution indices of the composite from the NQR scans to quantify stress and identify precursors to failure in the composite.

Nuclear quadrupole resonance system and method for structural health monitoring

An exemplary embodiment of the present invention is a method for calculating at least one confidence interval. The method comprises a set of instructions that activate a calculator. The user selects input data, which the calculator reformats to generate output data. The calculator then generates both a calibration summary and specific calibration summary containing calibration standard measurements from the output data. A linear calibration curve and residual calibration value plot are derived from these calibration standard measurements. The calculator calculates a back-calculated unknown sample value using the information gathered from the linear calibration curve and residual calibration value plot. The calculator can then calculate the confidence interval for the back-calculated unknown sample value.

Method and apparatus for calculating confidence intervals

An exemplary embodiment of the invention is a method and apparatus for calculating at least one confidence interval. The method comprises activating a calculator. The calculator prompts the user to enter at least three pairs of calibration data. The user then specifies a reference for the calibration data. The calculator then generates a list of the calibration data. The calculator then calculates a linear calibration curve derived from the calibration data. The calculator then calculates a residual calibration value plot derived from the calibration data. The user enters an unknown sample output measurement. The calculator calculates a back-calculated unknown sample input measurement. The calculator lastly calculates a confidence interval for the back-calculated unknown sample input measurement.

An exemplary embodiment of the invention is an apparatus and method for calculating confidence intervals. The method comprises activating a calculator. The user selects input data for the calculator. The calculator reformats the input data into output data. The calculator then generates a specific calibration summary using the output data. The calculator plots a linear calibration curve derived from the specific calibration summary. The calculator then plots a calibration residual value plot derived from the specific calibration summary. The calculator calculates a back-calculated unknown sample value. Lastly, the calculator calculates a confidence interval for said at least one back-calculated unknown sample value.

A method and system are provided that can be used at any stage of a manufacturing process to determine physical properties such as crosslink density. The method and system require little or no sample manipulation. The method and system are independent of rubber particle size and matrix composition. In the method and system, physical properties of a material are determined by NMR measurement. A T (spin lattice relaxation time) is measured for a material, a T (spin-spin relaxation time) is measured for the material and a value T /T is calculated that is representative of a physical property of material.

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Clifton Park, NY, United States of America

Thomas Alan Early