METHOD OF INSPECTING A STEEL STRIP
20180172601 ยท 2018-06-21
Assignee
Inventors
Cpc classification
International classification
Abstract
In a method of inspecting a steel strip, at least one surface of the steel strip is illuminated and scanned by at least one camera so as to generate an image record that defines a two-dimensional image of the scanned surface. The image record is sent to an image processing unit, with the image processing unit subjecting the image record to the detection of defects and, upon detection of a surface defect, classifying the detected surface defect. The steel strip is magnetized and the magnetic flux leakage on the surface of the steel strip is detected by at least one magnetic field-sensitive flux leakage sensor in order to detect inhomogeneities in the interior of the steel strip, with the flux leakage sensor generating a flux leakage record that is sent to the image processing unit and that is subjected by the image processing unit to the detection of defects so as to identify inhomogeneities in the interior of the steel strip.
Claims
1. A method of inspecting a steel strip, wherein at least one surface of the steel strip is illuminated and scanned by at least one camera in order to generate an image record that defines a two-dimensional image of the scanned surface, and wherein the image record is sent to an image processing unit, with the image processing unit subjecting the image record to the detection of defects, and, if a surface defect is detected, classifying the detected surface defect, wherein the steel strip is magnetized and that the magnetic flux leakage on the surface of the steel strip is detected by at least one magnetic field-sensitive sensor in order to detect inhomogeneities in the interior of the steel strip, with the flux leakage sensor generating a flux leakage record that is sent to the image processing unit and that is subjected by the image processing unit to the detection of defects so as to detect inhomogeneities in the interior of the steel strip.
2. The method of claim 1, wherein upon detection of an inhomogeneity in the image processing unit, the detected inhomogeneity is classified.
3. The method of claim 1, wherein the image record and the flux leakage record are combined in the image processing unit, specifically by superimposition, so as to generate a three-dimensional image of the defects of the steel strip.
4. The method of claim 3, wherein the defects captured in the three-dimensional image of the defects are classified into predefined classes of defects.
5. The method of claim 3, wherein the three-dimensional image of the defects is displayed on a display unit.
6. The method of claim 1, wherein the steel strip is moving at a strip speed in a direction of strip travel.
7. The method of claim 6, wherein the camera is a digital line scan camera with a plurality of linearly disposed optical sensors that extend at right angles relative to the direction of strip travel.
8. The method of claim 6, wherein the magnetic sensitive sensor used to detect the magnetic leakage field is a sensor array with a plurality of linearly disposed magnetic sensors that extend at right angles relative to the direction of strip travel.
9. The method of claim 1, wherein the surface of the steel strip is illuminated by a lighting unit that emits light and is scanned by a first camera and a second camera, with the first camera capturing the light that is reflected from the surface of the steel strip and with the second camera capturing the light that is scattered from the surface of the steel strip.
10. The method of claim 1, wherein in order to magnetize the steel strip, the strip is guided about a magnetizing roll and passed through a magnetizing unit comprising an electromagnet or a permanent magnet.
11. The method of claim 10, wherein the flux leakage sensor is disposed opposite to the magnetizing roll and the steel strip is passed through a gap between the magnetizing roll and the flux leakage sensor.
12. A system for inspecting a steel strip, preferably for carrying out the method of claim 1, comprising a lighting unit used to illuminate the steel strip, a magnetizing unit used to magnetize the steel strip, at least one camera used to optically scan a surface of the steel strip and to generate an image record that defines a two-dimensional image of the scanned surface, an image processing unit that is connected to the camera and to which the image record is sent for data processing and that is able to detect optical surface defects in the image record to and classify the detected surface defects, and at least one magnetic field-sensitive flux leakage sensor used to detect the magnetic leakage flux on the surface of the steel strip and to generate a flux leakage record, with the flux leakage sensor being connected to the image processing unit for transmitting the flux leakage record to the image processing unit, and with the image processing unit being configured so as to be able to detect inhomogeneities in the interior of the steel strip from the flux leakage record.
13. The system of claim 12, wherein the flux leakage sensor comprises induction coils, giant magnetoresistive sensors (GMR sensors), anisotropic magnetoresistive sensors (AMR sensors), tunneling magnetoresistive sensors (TMR sensors) or Hall sensors so as to be able to detect the magnetic flux leakage density.
14. The system of claim 12, wherein the magnetizing unit comprises an electromagnet or a permanent magnet and a magnetizing roll disposed at a distance from the flux leakage sensor, with the steel strip being guided about the magnetizing roll and passed through the magnetic field generated by the electromagnet or the permanent magnet and through a gap that is formed between the magnetizing roll and the flux leakage sensor.
15. The method of claim 12, wherein the camera is a digital line scan camera with a plurality of linearly disposed optical sensors and wherein the magnetic field-sensitive flux leakage sensor is a sensor array with a plurality of linearly disposed magnetic sensors.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] These and additional advantages and features of the present invention follow from the embodiment example described in greater detail below with reference to the accompanying drawings. The drawings show:
[0020]
[0021]
[0022]
DETAILED DESCRIPTION
[0023]
[0024] The magnetizing unit 7 shown in
[0025] The electromagnet or permanent magnet of the magnetizing unit 7 can be suitably integrated into the magnetizing roll 8. It is, however, also possible to dispose the electromagnet or permanent magnet downstream of the magnetizing roll 8, as indicated diagrammatically in
[0026] Downstream of the magnetizing unit 7, the steel strip 1 is guided about a guide roll 10 disposed near the lighting unit 6 and the at least one camera 2. The lighting unit 6 illuminates at least one surface of the steel strip 1 with light L.
[0027] In the embodiment example shown in
[0028] The image data acquired by the bright field camera 2a and the dark field camera 2b are transmitted via data lines (wire-bound or wireless) 11 to the image processing unit 3. The image processing unit 3, which suitably comprises a PC or a laptop for data processing and data storage, contains image processing software, which processes the image data of the camera 2, and, based thereon, generates a two-dimensional image record 10 that defines a two-dimensional (optical) image of the surface of the steel strip 1. This two-dimensional image of the surface of the strip can be displayed on a display unit 5, which, for data transmission, is connected to the image processing unit 3.
[0029] The image processing software contained in the image processing unit 3 comprises a classification module, by means of which anomalies in the image data acquired by the camera 2 can be detected and classified. In order to be able to classify the detected anomalies in the image data of the image record 10, the image processing unit 3 comprises a storage unit with a classification database stored therein, in which a large number of typical surface defects as well as surface defects known from previous inspections are stored. To classify the anomalies detected in the image record 10 of the camera 2, these anomalies are compared with the (standardized) surface defects stored in the classification database. If the characteristics of the detected anomaly are consistent with the characteristics of a stored surface defect, the detected anomaly is correlated with a surface defect 11. Thus, a surface defect 11 detected and classified in this manner is marked or otherwise identified in a file containing the image record 10 of the cameras 2. In addition, the detected and classified surface defect 11 can also be displayed on the display unit 5, on which the two-dimensional image of the image record 10 is displayed. In the representation of a surface defect 11 on the display unit 5, both the location and the nature of the surface defect 11 can be marked.
[0030]
[0031] Magnetizing the steel strip 1 in the magnetizing unit 7 produces a magnetic flux leakage on the surface of the steel strip 1. The magnitude of the flux leakage depends on the magnetization and the permeability of the steel strip 1 as well as on the internal structure of the steel strip 1. If the magnetization and the permeability of the steel strip remain constant, the presence of a locally changing flux leakage that is detected on the surface of the steel strip 1 by means of the magnetic field-sensitive flux leakage sensor 4 is indicative of an internal defect, for example, a nonmetallic inclusion in the interior of the steel strip 1. If, for example, a nonmetallic inclusion is present in the interior of the steel strip 1, the magnetic field lines in the interior of the steel strip 1 are directed around the nonmetallic inclusion, which produces an anomaly in the location-dependent flux leakage image on the surface of the steel strip 1. Such anomalies can be detected by the magnetic field-sensitive flux leakage sensor 4. The flux leakage data (location-dependent flux leakage values) generated by the flux leakage sensor 4 are transmitted by a data line 12 to the image processing unit 3, wherein the data are processed to generate a flux leakage record 20. The flux leakage record 20 contains spatially-resolved flux leakage data and thereby defines a location-dependent image of the flux leakage detected by the flux leakage sensor 4. The presence of anomalies in the flux leakage record 20 is indicative of inhomogeneities, particularly nonmetallic influences, in the interior of the steel strip 1. The flux leakage record 20 therefore contains information concerning the location as well as the structure and morphology of inhomogeneities in the interior of the steel strip.
[0032] The flux leakage record 20 generated in the image processing unit 3 is checked for anomalies by the image processing software contained in the image processing unit 3. When an anomaly is detected in the flux leakage record 20, the characteristics of the detected anomaly are compared with the characteristics of anomalies known from previous flux leakage measurements in the flux leakage record that are stored in a flux leakage database. If the characteristics of an anomaly in the currently generated flux leakage record 20 are consistent with the characteristics of an anomaly stored in the flux leakage database, the anomaly detected in the current flux leakage record 20 can be correlated with an anomaly known from and classified in previous inspections in a flux leakage record. In this manner, the detected anomalies can be classified in the current flux leakage record 20 of the steel strip 1 and correlated with a typical inhomogeneity 21 in the interior of the steel strip. This makes it possible to identify not only the presence of a defect in the flux leakage record 20 but also its location as well as the nature, extent and geometry and the morphology of the inhomogeneity 21.
[0033] An example of a diagrammatic representation of a flux leakage record 20 and inhomogeneities 21 present therein can be seen in
[0034] The image processing software of the image processing unit 3 combines the data of the image record 10 and the data of the flux leakage record 20 and, due to this data combination, is able to generate a three-dimensional image 30 of the defects. This three-dimensional image 30 of the defects can be displayed on the display unit 5. The fact that the data of the image record 10 and the data of the flux leakage record 20 are combined has the effect that the three-dimensional image 30 of the defects contains both information concerning optically visible surface defects 11 and inhomogeneities 21 in the interior of the steel strip 1. Thus, the three-dimensional image 30 of the defects contains not only information concerning defects that are optically visible on the surface, but also information concerning the internal structure of the steel strip in the depth direction.
[0035] As a result, it is also possible to detect and to classify contiguous anomalies and defects in the three-dimensional image 30 of the defects, even if a defect appears only in some areas as a surface defect on the surface of the steel strip 1 (and is identifiable as such in the image record 10) and, at the same time, is present at least in some areas as an inhomogeneity (for example, as a nonmetallic inclusion) on the in the interior of the steel strip, without being visible on the surface (as a surface defect).
[0036] An example of such a situation can be seen in
[0037] Due to the fact that the method according to the present invention combines the data of the image record 10 and the data of the flux leakage record 20, it is possible, in the three-dimensional image 30 of the defects, to detect, visualize and classify those defects which are visible only in some areas as surface defects 11 on the surface of the steel strip and which in the remaining area propagate in the form of an inhomogeneity 21 in the interior of the steel strip.
[0038] The three-dimensional image 30 of the defects generated according to the present invention by combining the data of the image record 10 and the data of the flux leakage record 20 can preferably be displayed in-line on the display unit 5, i.e., while the steel strip 1 exiting an ongoing production or finishing process is moving at the predefined strip speed in the direction of strip travel v.
[0039] As a result, it is possible, for example, to detect, classify and visualize both surface defects 11 (from the image record 10) and inhomogeneities 21 in the interior of the steel strip (from the flux leakage record 20) during an ongoing production or finishing process of the steel strip 1 and, if necessary, to intervene in the production or finishing process in order to prevent the development of additional surface defects and/or inhomogeneities in the interior of the steel strip. At the same time, the method according to the present invention also allows the detection of contiguous defects in the three-dimensional image 30 of the defects, which can be identified in some areas as surface defects 11 and in some areas as an inhomogeneity 21 in the interior of the steel strip, as well as their classification.
[0040] To be able to scan the surface of the strip two-dimensionally while the steel strip 1 is moving, the at least one camera 2 is preferably a digital line scan camera having a plurality of linearly disposed optical sensors, with the camera 2 being disposed relative to the moving steel strip 1 in such a way that the optical sensors disposed at a distance from each other extend at right angles relative to the direction of strip travel and across the entire width of the steel strip. Using this design and configuration of the camera 2, the surface of the steel strip 1 moving at the strip speed can be scanned line by line. If a bright field camera 2a and a dark field camera 2b are used as proposed by the embodiment example shown in
[0041] In addition, the flux leakage sensor 4 is preferably configured in the form of a sensor array with a plurality of linearly disposed magnetic sensors, with the magnetic sensors disposed at a distance from each other also extending at right angles relative to the direction of strip travel and across the entire width of the steel strip. Using this design and configuration of the flux leakage sensor 4 in the form of a sensor array, the magnetic flux leakage can also be detected line by line across the entire surface of the strip while the steel strip is moving. The flux leakage sensor 4 can also comprise a plurality of sensor lines which are disposed one behind another in the direction of strip travel v. Depending on the number of magnetic sensors in the sensor matrix (which may comprise far more than a thousand magnetic sensors), a flux leakage sensor 4 that is designed as a multiple line senor matrix makes it possible to detect internal inclusions with a spherical diameter in the range from 50 m to 100 m in steel strips with thicknesses in a range from 100 m to 500 m.
[0042] The magnetic sensors of the flux leakage sensor 4 involved can be, for example, induction coils, giant magnetoresistive sensors (GMR sensors), anisotropic magnetoresistive sensors (AMR sensors), tunneling magnetoresistive sensors (TMR sensors) or Hall sensors.
[0043] The design of the camera 2 as a digital line scan camera and of the flux leakage sensor 4 as a sensor array also offers advantages with respect to the data structure of the generated image record 10 and the flux leakage record 20 since the location dependency of the two-dimensional optical image resulting from the image record 10 and of the magnetic flux leakage resulting from the flux leakage record 20 has the same (line) structure with respect to the location dependency. As a result, it is possible to process both the image record 10 and the flux leakage record 20 using a single image processing software and, by superimposing the data of the image record 10 and the data of the flux leakage record 20 upon each other, to generate a three-dimensional record (three-dimensional image 30 of the defects), which record contains both information about the structure of the steel strip on the surface and information about the depth with respect to internal inclusions or other inhomogeneities.