System and method for estimating both thickness and wear state of refractory material of a metallurgical furnace

Patent metadata

Field	Value
Publication number	US-2022404316-A1
Application number	US-202017779033-A
Country	US
Kind code	A1
Filing date	Nov 27, 2020
Priority date	Nov 29, 2019
Publication date	Dec 22, 2022
Grant date	—

Abstract

A system for estimating both thickness and wear state of refractory material ( 1 ) of a metallurgical furnace ( 12 ), including at least on processor including a database of simulated frequency domain data named simulated spectra representing simulated shock waves reflected in simulated refractory materials of known state and thickness, each simulated spectrum being correlated with both known state and thickness data of the considered simulated refractory material, wherein the at least one processor is configured to record a reflected shock wave as a time domain signal, and to convert it into frequency domain data named experimental spectrum, and are further configured to compare the experimental spectrum with at least a plurality of simulated spectra from the database, to determine the best fitting simulated spectrum with the experimental spectrum and to estimate thickness and state of the refractory material ( 1 ) of the furnace ( 12 ) using known state and thickness data correlated with the best fitting simulated spectrum.

First claim

What is claimed is:

1 - 13 . (canceled)

14 . A system for estimating both thickness and wear state of a refractory material of a metallurgical furnace, the system comprising at least:
a shock wave generator configured to generate at least one shock wave propagating into the refractory material; a shock wave sensor configured to sense at least one reflected shock wave into the refractory material; a processor including a database of simulated frequency domain data named simulated spectra representing simulated shock waves reflected in simulated refractory materials of known state and thickness, each simulated spectrum being correlated with both known state and thickness data of the considered simulated refractory material, wherein the processor is configured:
to record the reflected shock wave as a time domain signal, and to convert the time domain signal into frequency domain data so as to define experimental spectrum, and
to compare the experimental spectrum with a plurality of simulated spectra from the database, to determine a best fitting simulated spectrum with the experimental spectrum and to estimate thickness and state of the refractory material of the furnace using known state and thickness data correlated with the best fitting simulated spectrum.

15 . The system as recited in claim 14 wherein the processor is configured to sequentially:
determine resonant frequency peaks position in the frequency domain data;
filter the simulated spectra from the database with the resonant frequency peaks, and select a reduced corresponding group of simulated spectra comprising the resonant frequency peaks; and
determine a unique simulated spectrum from the reduced corresponding group, whose resonant frequency peaks are the closest in height to resonant frequency peaks of the experimental spectrum, the unique simulated spectrum being the best fitting simulated spectrum.

16 . The system as recited in claim 14 wherein the shock wave generator includes an instrumented hammer configured to hit the metallurgical furnace wall in order to generate at least an acoustic shock wave propagating and reflecting into the refractory material.

17 . The system as recited in claim 14 wherein the shock wave sensor includes at least an accelerometer configured to measure the mechanical reaction of the refractory material caused by the reflection of the generated shock wave.

18 . A method for estimating both thickness and wear state of a refractory material of a metallurgical furnace with the system as recited in claim 14 , the method comprising at least the following steps:
generating at least a shock wave that propagates into the refractory material; sensing at least a reflected shock wave into the refractory material; recording the reflected shock wave as a time domain signal; converting the time domain signal into frequency domain data so as to define experimental spectrum; comparing the experimental spectrum with at least a plurality of simulated spectra from the database, each simulated spectrum being correlated with both known state and thickness data of the considered refractory material; determining a best fitting simulated spectrum with the experimental spectrum, and estimating thickness and state of the refractory material of the furnace using known state and thickness data correlated with the best fitting simulated spectrum.

19 . The method as recited in claim 18 wherein the comparing and determining steps are implemented by sequentially:
determining resonant frequency peaks position in the experimental spectrum;
filtering the simulated spectra from the database with the resonant frequency peaks detected, and selecting a reduced corresponding group of simulated spectra including the resonant frequency peaks; and
determining a unique simulated spectrum from the reduced corresponding group, whose resonant frequency peaks are the closest in height to resonant frequency peaks of the experimental spectrum, the unique spectrum being the best fitting simulated spectrum.

20 . The method as recited in claim 18 wherein the estimating step is implemented by at least estimating a total thickness of the refractory material and a position and thickness of at least a layer in which the refractory is weakened by anomalies, the layer being defined as a brittle layer.

21 . The method as recited in claim 18 wherein a plurality of shock waves are generated, a plurality of reflected shock waves are sensed and recorded as time domain signals, and converted into frequency domain signals.

22 . The method as recited in claim 19 wherein the determination of the resonant frequency peaks position in the experimental spectrum is implemented following the steps of:
arithmetically averaging the experimental spectra and selecting a first set of representative peaks;
geometrically averaging the experimental spectra and selecting a second set of representative peaks; and
selecting a final set of peaks selected both in the first set and the second set, the final set of peaks being the resonant frequency peaks.

23 . The method as recited in claim 22 wherein the peaks of the first set are selected if their width is greater than a threshold value of between ten and twenty hertz.

24 . The method as recited in claim 22 wherein the simulated spectra from the database are filtered with the resonant frequency peaks detected using at least a numerical dispersion curves model in order to determine propagation modes of the simulated shock waves, to filter them with the resonant frequency peaks detected, and to select the reduced corresponding group of simulated spectra.

25 . The method as recited in claim 22 wherein the unique simulated spectrum is determined from the reduced corresponding group using at least a numerical transient model.

26 . The method as recited in claim 25 wherein the spectra of the reduced corresponding group are selected then compared with the experimental spectrum by implementing at least one of the following steps:
direct difference between simulated spectra and experimental spectrum;
comparison of the overall shape of the simulated spectra and of the experimental spectrum;
determination of the differences between the maximum height peak positions of respectively the simulated spectra and the experimental spectrum; and
cross correlation between the simulated spectra and the experimental spectrum.

27 . The method as recited in claim 24 wherein the spectra of the reduced corresponding group are selected then compared with the experimental spectrum by implementing at least one of the following steps:
direct difference between simulated spectra and experimental spectrum;
comparison of the overall shape of the simulated spectra and of the experimental spectrum;
determination of the differences between the maximum height peak positions of respectively the simulated spectra and the experimental spectrum; and
cross correlation between the simulated spectra and the experimental spectrum.

Assignees

• Arcelormittal

Inventors

• Gómez García Pablo
• Fernandez Alvarez José Paulino
• Baquet González Ignacio
• Símaro José Tomás
• Herrero Blanco Ignacio
• Fernández Diéguez Enol
• Suárez Lázare Carlos Javier

Classifications

• F27D21/0021 Primary

  Devices for monitoring linings for wear · CPC title

• C21B7/24

  Test rods or other checking devices · CPC title

• G01M7/08

  Shock-testing · CPC title

• C21C5/44

  Refractory linings · CPC title

• C21C2005/448

  Lining wear indicators · CPC title