Material analysis including density and moisture content determinations

• US 20050267700A1
• Filed: 05/12/2005
• Published: 12/01/2005
• Est. Priority Date: 05/26/2004
• Status: Active Grant

• Current Assignee: TransTech Systems, Inc.
• Original Assignee: TransTech Systems, Inc.
• Inventors: Gamache, Ronald W., Hosterman, Richard, Pluta, Sarah
• Granted Patent: US 7,219,024 B2
• Time in Patent Office: Days
• US Class Current: 702/65
• CPC Class Codes: G01N 27/028 Circuits therefor measuring impedance per se G01R27/02

Abstract

A system, method and program product for determining the in-place engineering properties such as density and moisture content of many varieties of engineering materials, are disclosed. The invention also includes a database, material model and sensor model for use with the above-described aspects. In one embodiment, the invention determines a compaction indication of the material based on an effect of impedance characteristics of the material on an electrical field, and corrects the compaction indication for at least one of a sensor depth-sensitivity inaccuracy and a compaction process inaccuracy. The compaction indication is determined based on a material model, and the corrections are based on mathematical and empirical models of the compaction process and the sensor.

Claims

1. A material analyzer system comprising:

a sensor; and

an analyzer unit including;

an electronic circuit operatively coupled to the sensor for generating an electrical field from the sensor proximate the material; and

a data analyzer, operatively coupled to the electronic circuit, that determines a compaction indication of the material based on an effect of impedance characteristics of the material on the electrical field,

wherein the data analyzer corrects the compaction indication for at least one of a sensor depth-sensitivity inaccuracy and a compaction process related inaccuracy in one of a first mode and a second mode.

2. The system of claim 1, wherein the electronic circuit includes a sensor circuit for causing the electrical field to transmit from the sensor and a measurement circuit for receiving the electrical field from the material.

3. The system of claim 1, wherein the sensor includes at least one element to transmit an electric field into the material, at least one element to receive an electric field from the material, and at least one element to shape and direct the electric field.

4. The system of claim 1, wherein the electronic circuit generates the electrical field over a set of frequencies that is based on the material.

5. The system of claim 1, wherein the data analyzer includes:

a measurer configured to control the electronic circuit; and

a data processor for calculating the compaction indication of the material.

6. The system of claim 1, wherein the data analyzer includes a sensor/mode configurator for determining a mode of operation for the system, wherein the system further includes at least one of the following operating modes:

the first mode in which the compaction indication includes an accurate absolute density as determined based on a material model;

the second mode in which the compaction indication includes an estimated absolute density as determined based on an approximated material model; and

a third mode in which the compaction indication indicates whether further compaction is required based on a percentage of additional compaction achieved compared to a prior compaction pass.

7. The system of claim 6, wherein in the case that the compaction indication is one of the accurate absolute density and the estimated absolute density, the data analyzer corrects a raw density by a correction factor including:

a compaction process correction term representative of a ratio of each density reading to a relative mean density for a lift of the material; and

a sensor depth-sensitivity correction term by which a contribution of the sensor at each increment of lift depth must be multiplied to obtain an equal increment contribution.

8. The system of claim 7, wherein the compaction process correction term is calculated based on a compaction process model for determining a mean density of a lift.

9. The system of claim 1, wherein the data analyzer further determines a moisture content of the material based on a material model.

10. The system of claim 1, wherein the data analyzer corrects a raw impedance measurement for contributions of the sensor.

11. The system of claim 1, wherein the compaction process related inaccuracy includes a non-uniform volumetric density profile from the compaction process.

12. The system of claim 1, further comprising a temperature sensor.

13. A method for determining a compaction of a material, the method comprising the steps of:

measuring an impedance of the material using a sensor;

determining a compaction indication of the material based on the impedance; and

correcting the compaction indication with at least one of a sensor depth-sensitivity correction and a compaction process correction.

14. The method of claim 13, wherein the compaction indication includes at least one of:

an accurate absolute density as determined based on a material model; and

an estimated absolute density as determined based on an approximated material model.

15. The method of claim 14, wherein the accurate absolute density is determined in the case that a material model for the material is available.

16. The method of claim 13, further comprising the step of determining whether a material model is available for the material, wherein the material model includes a non-linear multiple variable-parameter estimator for determining an absolute density based on the impedance.

17. The method of claim 16, wherein in the case that the material model for the material is unavailable, the method further comprises the steps of:

querying a user for a material type;

determining whether the material type is valid; and

determining the approximated material model based on a closest material model in the case that the material type is valid.

18. The method of claim 17, wherein in the case that the material type is invalid, further comprising the steps of:

querying a user to run a field Proctor test; and

determining the approximated material model based on a closest material model in the case that the field Proctor test is run.

19. The method of claim 13, wherein the measuring step includes measuring the impedance of the material over a set of frequencies.

20. The method of claim 13, further comprising the step of determining an engineering property of the material other than the compaction indication.

21. The method of claim 20, wherein the engineering property includes at least one of a moisture content and a conductivity.

22. The method of claim 13, wherein the sensor depth-sensitivity correction includes an incremental contribution for a particular sensor at each increment of a lift depth.

23. The method of claim 13, wherein the compaction process correction includes a factor by which each increment reading differs from a relative mean density for an entire lift of the material.

24. The method of claim 13, further comprising the step of correcting the impedance for contributions of the sensor.

25. A computer program product comprising a computer useable medium having computer readable program code embodied therein for determining a compaction indication of a material, the program product comprising:

program code configured to measure an impedance of the material based on a reading by a sensor; and

program code configured to determine a compaction indication of the material based on the impedance, wherein the compaction indication is corrected using at least one of a sensor depth-sensitivity correction and a compaction process correction.

26. The program product of claim 25, wherein the compaction indication includes one of:

an accurate absolute density as determined based on a material model; and

an estimated absolute density as determined based on an approximated material model.

27. The program product of claim 25, wherein the determining program code determines the accurate absolute density in the case that a material model for the material is available and the estimated absolute density in the case that the material model for the material is unavailable.

28. The program product of claim 25, wherein in the case that the material model for the material is unavailable, the determining program code further:

queries a user for a material type;

determines whether the material type is valid; and

determines the approximated material model based on a closest material model in the case that the material type is valid.

29. The program product of claim 28, wherein in the case that the material type is invalid, the determining program code further:

queries a user to run a field Proctor test; and

determines the approximated material model based on a closest material model in the case that the field Proctor test is run.

30. The program product of claim 25, wherein the determining program code includes a non-linear multiple variable-parameter estimator for determining an absolute density based on the impedance.

31. The program product of claim 25, wherein the measuring program code measures the impedance of the material at a plurality of frequencies.

32. The program product of claim 25, wherein the determining program code further determines an engineering property of the material other than the compaction indication.

33. The program product of claim 32, wherein the engineering property includes at least one of a moisture content and a conductivity.

34. A database for use with a material analyzer system that determines an engineering property of the material based on an impedance reading of the material, the database comprising at least one of:

a sensor model for determining a sensor depth-sensitivity correction for the engineering property; and

a compaction process model for determining a compaction process correction for the engineering property.

35. The database of claim 34, wherein the sensor depth-sensitivity correction includes n incremental contribution for a particular sensor at each increment of a lift depth.

36. The database of claim 35, wherein the compaction process correction includes a factor by which each increment reading differs from a relative mean density for an entire lift of the material.

37. The database of claim 34, further comprising a material model for determining the engineering property of the material based on the impedance reading.

38. The database of claim 37, wherein the engineering property includes at least one of an absolute density, a moisture content and a conductivity.

39. A material model for use with a material analyzer system, the material model comprising:

an empirical model for converting a complex impedance value of the material to an engineering property of the material, the empirical model implemented using a non-linear multiple variable-parameter estimator, wherein model parameters used by the estimator are based on known samples of the material.

40. The material model of claim 39, wherein the engineering property includes at least one of an absolute density, a moisture content and a conductivity.

41. The material model of claim 39, wherein inputs to the empirical model include at least one of:

frequency of a Maxwell-Wagner resonance, a slope at the Maxwell-Wagner resonance, a magnitude and a slope of a real part of a permittivity in a frequency region below the Maxwell-Wagner resonance, a magnitude and a slope of the real part of the permittivity in a frequency region above the Maxwell-Wagner resonance, and an imaginary part of the permittivity at a frequency above the Maxwell-Wagner resonance.

42. A sensor model for use with a material analyzer system, the sensor model comprising:

an incremental contribution for a particular sensor at each increment of a lift depth.

43. A material analyzer system comprising:

a sensor; and

an analyzer unit including;

an electronic circuit operatively coupled to the sensor for generating an electrical field from the sensor proximate the material; and

a data analyzer, operatively coupled to the electronic circuit, that determines a property of the material by implementing a material model capable of determining the property based on an effect of impedance characteristics of the material on the electrical field,

wherein the material model implements a non-linear multiple variable-parameter estimator.