Determination of structural characteristics of an object
Inventors
Earthman, James C. • Sheets, Cherilyn G. • Quan, Jr., Dennis A.
Assignees
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Publication Number
US-12082940-B1
Publication Date
2024-09-10
Expiration Date
Abstract
The present invention relates generally to a system and method for measuring the structural characteristics of an object. The object is subjected to an energy application processes and provides an objective, quantitative measurement of structural characteristics of an object. The system may include a device, for example, a percussion instrument, capable of being reproducibly placed against the object undergoing such measurement for reproducible positioning. The invention provides for a system and methods for analyzing measured characteristics to identify issues and pathologies in the object, such as a tooth, and to recommend follow-up courses of action.
Core Innovation
The disclosed system predicts at least one structural characteristic of an object using a predictive model generated by compiling test results from a multitude of objects. Each test result is generated by a device having a housing with an open end and a longitudinal axis, an energy application tool with a resting and an active configuration, and a sleeve protruding from the open end with an object contacting portion adapted to rest the device on at least a portion of the object.
For each tested object, a drive mechanism supported inside the housing activates the energy application tool to impact the object when the sleeve is resting on the object and measures a response after impact. The measured response is used to generate a response versus time curve, and the response versus time curve is annotated and validated. A computer coupled to the device captures the response versus time curve and the annotation and validation to generate the predictive model having one or more characteristic ranges.
A transformation function identifies structural characteristics comprising a combination of loss coefficient and normal fit error from the predictive model. The system predicts structural characteristics of a newly tested object using the predictive model’s characteristic ranges when both the loss coefficient and the normal fit error fall into the one or more characteristic ranges without further annotation and validation. The approach is described as computerized for automatically determining structural characteristics in a non-invasive and/or non-destructive manner.
The document also states that a predictive model is created by compiling device-generated test results from a multitude of objects and that a transformation function is automatically applied after loading the model into a test device substantially the same as the predictive modeling device. Structural characteristics are then predicted when the combination of loss coefficient and normal fit error falls within the characteristic ranges without operator participation.
Claims Coverage
The document provides three independent claims. Across these claims, the inventive framework centers on generating predictive-modeling data from a response versus time curve produced by an energy application tool, annotating and validating that curve, deriving a transformation function from the predictive model using loss coefficient and normal fit error, and predicting structural characteristics for newly tested objects without further annotation and validation when the metrics fall within characteristic ranges.
Predictive modeling using response versus time curve and annotated validation
A system or predictive modeling approach compiling test results from a multitude of objects where each test result is generated by a device producing a response versus time curve that has been annotated and validated, and capturing the response versus time curve and the annotation and validation to generate a predictive model having one or more characteristic ranges.
Transformation function based on loss coefficient and normal fit error ranges
A transformation function adapted for identifying structural characteristics comprising a combination of loss coefficient and normal fit error from the predictive model, where a newly tested object is predicted using the predictive model when both the loss coefficient and the normal fit error in the combination fall into the one or more characteristic ranges without the need for further annotation and validation.
Non-invasive and/or non-destructive computerized workflow without operator participation
A computerized method that creates a predictive model by compiling test results, annotating and validating the response versus time curve, capturing the response versus time curve and annotation and validation to create the predictive model, loading the model into a test device substantially the same as the predictive modeling device, and automatically generating and applying a transformation function so that structural characteristics are predicted without operator participation when the loss coefficient and normal fit error fall into the one or more characteristic ranges.
Device configuration for producing response versus time curve from an energy impact
A test device having a housing with an open end and a longitudinal axis, an energy application tool mounted inside the housing for movement with a resting and an active configuration, a sleeve protruding from the open end with an object contacting portion adapted for resting the device on the object, and a drive mechanism supported inside the housing adapted for activating the energy application tool to impact the object and for measuring a response after impact to generate the response versus time curve.
All independent claims share the core inventive concept of predicting structural characteristics from a predictive model derived from an annotated and validated response versus time curve, using a transformation function based on loss coefficient and normal fit error, and applying predictive characteristic ranges to newly tested objects without further annotation and validation when the metrics fall within those ranges.
Stated Advantages
Predicts structural characteristics of a newly tested object without the need for further annotation and validation.
Predicts structural characteristics in a non-invasive and/or non-destructive manner.
Enables automatic determination of structural characteristics without operator participation.
Documented Applications
Predicting at least one structural characteristic of an object for a newly tested object using a device that generates a response versus time curve and applying a loss coefficient/normal fit error transformation function.
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