DE4415004A1 - Arrangement and method for characterising surfaces and for characterising and classifying surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media - Google Patents

Arrangement and method for characterising surfaces and for characterising and classifying surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media

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Publication number
DE4415004A1
DE4415004A1 DE19944415004 DE4415004A DE4415004A1 DE 4415004 A1 DE4415004 A1 DE 4415004A1 DE 19944415004 DE19944415004 DE 19944415004 DE 4415004 A DE4415004 A DE 4415004A DE 4415004 A1 DE4415004 A1 DE 4415004A1
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DE
Germany
Prior art keywords
characterized
unit
control
measured values
surface
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
DE19944415004
Other languages
German (de)
Inventor
Ingo Dr Rer Nat Bradl
Thomas Dr Schroeter
Lothar Beyerlein
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Friedrich Schiller Universtaet Jena
Original Assignee
Friedrich Schiller Universtaet Jena
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to DE4314825 priority Critical
Application filed by Friedrich Schiller Universtaet Jena filed Critical Friedrich Schiller Universtaet Jena
Priority to DE19944415004 priority patent/DE4415004A1/en
Publication of DE4415004A1 publication Critical patent/DE4415004A1/en
Withdrawn legal-status Critical Current

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Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/02Investigating particle size or size distribution
    • G01N15/0205Investigating particle size or size distribution by optical means, e.g. by light scattering, diffraction, holography or imaging
    • G01N15/0211Investigating a scatter or diffraction pattern
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical means
    • G01B11/30Measuring arrangements characterised by the use of optical means for measuring roughness or irregularity of surfaces
    • G01B11/303Measuring arrangements characterised by the use of optical means for measuring roughness or irregularity of surfaces using photoelectric detection means
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47Scattering, i.e. diffuse reflection
    • G01N2021/4704Angular selective
    • G01N2021/4711Multiangle measurement
    • G01N2021/4721Multiangle measurement using a PSD
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/47Scattering, i.e. diffuse reflection
    • G01N2021/4735Solid samples, e.g. paper, glass
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/8851Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/84Systems specially adapted for particular applications
    • G01N21/88Investigating the presence of flaws or contamination
    • G01N21/93Detection standards; Calibrating baseline adjustment, drift correction
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00Features of devices classified in G01N21/00
    • G01N2201/10Scanning
    • G01N2201/102Video camera
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00Features of devices classified in G01N21/00
    • G01N2201/12Circuits of general importance; Signal processing
    • G01N2201/129Using chemometrical methods
    • G01N2201/1296Using chemometrical methods using neural networks

Abstract

The arrangement consists of a device under test (item under test) (1), a measured-value picked-up (2), a unit for displaying measured values and storing measured values (5), and preferably a measured-value preprocessing system (3) and a control and regulating unit (6). It is characterised in that a measured value pickup (2) is connected to an evaluation unit having elements of fuzzy logic (4), and that the evaluation unit having elements of fuzzy logic (4) is connected to the unit for measured value display and measured value storage (5). <IMAGE>

Description

The invention relates to an arrangement for the characterization of surfaces and Characterization and classification of surface defects and near-surface Defects and inhomogeneities in the volume of transparent media according to the Preamble of claim 1 and an associated method according to the preamble of claim 8.

The invention serves for the evaluation of measurement data, which during the scanning one characterizing surface or volume to be characterized (this only for transparent media). It enables characterization of surfaces with regard to their roughness and characterization and Classification of surface defects and near-surface defects (scratches, Cracks, point defects, etc.) from measurement data, which are carried out using scattered light measurements or other methods for surface scanning can be obtained. Still allowed the invention the analysis of inhomogeneities in transparent media (Suspended particles or other particles in liquids, pores in the glass, etc.).

Various methods are currently known, with the aid of which surfaces or Surface defects can be examined.

First of all, relatively sophisticated profilometric methods should be mentioned here which the surface to be examined with a special measuring tip (usually Diamond) is touched.  

Such a method is described, for example, in JP 59-30008 A, the weight being based on an online determination of the profile of a surface and certain roughness parameters. Due to the measuring principle, however, only low relative speeds between the measuring tip and the surface are permitted (in this case 2.15 mm * s -1 ). Similar sampling rates can be found in other applications.

The T1000 measuring device offered by Hommel-Werke GmbH is known (Hommel tester) with which, depending on the probe tip used Resolution of up to 0.02 µm can be realized.

All touching measuring methods are in addition to the minor Scanning speed, which in many cases prevents online use, common that the measuring principle always irreversible and undefined Changes occur on the surface of the measurement object. These can be in one large number of applications, for example when testing optical Functional areas, are not tolerated. Besides this is a crucial disadvantage further notice that defects that lie in the surface (e.g. color defects) or are in layers near the surface (e.g. micro cracks under one transparent thin layer) cannot be detected with such methods in principle are. In cases where the surface to be examined is due to its own can not be touched (for example, the temperature), are such Procedure cannot be used from the start.

The disadvantages mentioned can be overcome by touching the Surface with a probe tip is replaced by a non-contact process. This significantly increases the possible measuring speed. Especially because of their universal applicability to optical processes To be received.  

The current state of the art is determined here on the one hand by methods that pure intensity weakening for the purpose of indicating surface defects use (see the published documents DE 41 33 315 A1 and DE 41 30 217 A1). With such methods, singular defects on or in otherwise homogeneous Surfaces can be detected. However, a prerequisite for this is sufficient big difference in the absorption behavior of the surface to be examined on the one hand and defects to be recognized on the other. The disadvantage of this It is also a method that the information that can be obtained only Absence of defects is. No statements can be made regarding the type or form of the Defects can be derived. There are only qualitative statements on the roughness of the surface expected.

More precise information about surfaces and near-surface layers can be found gain through the use of scattered light methods. These procedures are about that also for the investigation of volume properties of transparent media suitable. In addition to the integral detection of the surface to be examined backscattered light in almost the entire half space for the purpose of Calculation of roughness parameters (see the published documents DD 2 86 861 AS and DD 2 86 862 AS) are special procedures in this context for angle-resolved scattered light measurement. A sophisticated arrangement and the associated method are described in DE 41 39 641 A1. These The invention presented represents an improvement in the arrangement and the method from DE 41 05 509 A1. Both inventions have a relatively high angle resolution Scattered light measurement. The measuring principle has the advantage that it is very detailed Statements can be made about the surface to be examined. In addition to the roughness parameters, this also includes the type and the Distribution of defects.  

The disadvantages of the arrangement from DE 41 05 509 A1 with regard to the location of the Individual receivers or the complexity of the sensor head are described in DE 41 39 641 A1 remedied that in an integrated optics optical fibers arcuate be arranged, the scattered light to be detected on linear receiver arrays conduct. In this way, a relatively exact measurement of the from investigating surface of backscattered light at high angular resolution and short measurement time can be realized. In addition, the expenses for the Manufacturing of the sensor reduced.

A major problem that also with this arrangement or this method remains, is the evaluation of the mass of data generated with each measurement. Even with simple problems, this requires considerable effort to be driven. Even when determining roughness parameters technically or mathematically complicated procedures are used. With that from the outset considerable restrictions regarding the commercial Applicability of the procedure given. In addition, in many cases, none clear connection between, for example, scatter index, defect shape and Surface material exists.

The same can be done using various known methods for examining Volume properties of transparent media, for example the analysis of Floating particles in liquids using scattered light can be said. See also in particular the published documents DE 30 29 678 A1 and DE 42 10 041 C1.

The possibility of complex processes using means of fuzzy logic is known control possible addition of neural networks or complex or fuzzy To work on structures with exactly these means.  

Applications in the field of pattern recognition are particularly in / Tilli 1993 / to be found. However, they relate to pure image processing tasks mainly medical diagnosis, fault diagnosis in plants or business concerns. Work in the field of pure Measurement data processing by means of fuzzy logic are not yet known. Also in the published patent application DE 33 43 335 A1, in which a method and an arrangement for "Acquisition and / or recognition of complex structures on the basis of" fuzzy "- Theory "is explained, no such information can be found. When using fuzzy logic, it is customary to use the process or measurement object reduce the data obtained in order to convert it into linguistic variables and to process in this form. This is inevitable a loss of information connected, which is significant in many cases. Preprocessing and Most of the time, the conversion of the data, especially in the case of process controls, does not negligible period.

The invention is intended to analyze surfaces and near-surface regions as well further simplify the analysis of volume properties of transparent media and accelerate.

This is intended to demonstrate the commercial applicability of such analyzes to characterize Surface defects, near-surface defects and inhomogeneities in volume can be improved by reducing the effort. Scattered light measuring methods are said to qualified for in-process control / regulation of systems.

The object of the invention is achieved by the characterizing features of the claim 1 and claim 8 solved.  

The complicated mathematical algorithms used up to now become partial replaced by methods from the theory of fuzzy logic. If necessary, the Support of the evaluation of the measurement results also used neural networks.

The present invention significantly reduces the disadvantages of the prior art by severely restricting or completely eliminating data preprocessing and Depending on the object, measured values supplied by the sensor almost directly to the Evaluation unit can be passed on using fuzzy logic.

The above tasks are accomplished with the arrangement by the features of Claims 1 to 4 solved.

The above objects are in the method according to the invention by the Features of claims 8 to 12 solved.

The data obtained, for example, in the case of a scattered-light measurement are after a simple preprocessing fed to an evaluation unit based on elements of the Fuzzy logic based. In this unit, the first are those for the problem essential information extracted directly from the measurement data and in Form of linguistic variables. These are created with the help of a Problem tailored inference machine evaluated and then in Output in the form of linguistic variables. If necessary, the Result variables can be defuzzified in a simple manner and thus as sharp Output values, for example for control purposes, are made available. The processing of data with a structure that is not known a priori, for example, can through a modification within the evaluation unit with elements of the fuzzy logic get supported. If necessary, neural networks can also be used for this become.  

By using elements of the fuzzy logic, the temporal and Equipment expenditure for evaluating the data obtained from the measurement be significantly reduced. Through the cost reduction and the good manageability the principle of scattered light measurement for the characterization of surfaces and regions close to the surface and for the characterization of inhomogeneities in the Volume of transparent fabrics opened up for commercial use. The arrangement and the method for the characterization of surfaces and for Characterization and classification of surface defects and near-surface Defects and inhomogeneities in the volume of transparent media include a detector, preferably optical, starting from the object to be measured Intercepts signals, a device for preprocessing the intercepted signals, an evaluation unit in which the preprocessed signals using Elements of the fuzzy logic and possibly neural networks are evaluated as well Units for displaying and storing the measured values in preprocessed and / or evaluated form. The arrangement can also be a control unit included, with the help of the evaluated signals in control signals be implemented, a process that runs simultaneously with the measurement influence.

The invention is described in more detail below. The description is based on proceeded from figures. It shows

Fig. 1 measuring arrangement and data flow,

Fig. 2 illumination unit and receiver unit with Meßdatenvorverarbeitung,

FIG. 3, data,

Fig. 4 example of fuzzy variables and rules,

Fig. 5 arrangement for examining volume properties of transparent media.

The arrangement initially consists of five main assemblies. Corresponding to FIG. 1, these are the measured value pick-up ( 2 ) for recording the signals (object data OD) emanating from the measured object ( 1 ), the measured value preprocessing ( 3 ), the evaluation unit with elements of fuzzy logic ( 4 ), the unit for displaying measured values and storing measured values ( 5 ) and the control unit ( 6 ) for influencing processes running simultaneously with the measurement.

The object data (OD) coming from the measurement object ( 1 ), mainly scattered light distributions, are recorded by the measurement value sensor ( 2 ). This object data (OD) is either recorded directly by the transducer ( 2 ) or fed to it via conventional optics (lenses, objectives), or via optical fibers or integrated optics (according to DE 41 39 641 A1) or a combination of the aforementioned components. The transducer ( 2 ) consists of at least one optical receiver (CCD elements, photodiodes, photodiode arrays or SEVs) and is designed in such a way that the scattered light distribution in the entire half space, with the exception of narrow areas around the incident laser beam and directly above the surface of the measurement object during a measurement or in the course of a measuring cycle can be recorded in an angle-resolved or partially integrated manner and possibly in an azimuthally resolved manner. The transducer can therefore be designed so that sensors are arranged rotatably around the laser beam, or that receiver arrays are arranged azimuthally.

A surface is scanned by moving the measurement object (see FIG. 2).

The arrangement according to FIG. 2 can also be used when examining volume properties of transparent media. An arrangement with transmitted light illumination according to FIG. 5 can also be used. The laser is arranged below the measurement object 1 and the receiver 2 is arranged above the measurement object 1 .

This has the advantage that otherwise undetectable stray light components are measured and the information content of the scattered light is therefore greater.

After the measured values (M) have been forwarded to the measured value preprocessing ( 3 ), they are subjected to preprocessing. This can include simple filtering, partial integration, averaging, or similar operations. These operations are carried out partly via the hardware and partly via the software in the measured value preprocessing ( 3 ). Complex mathematical algorithms are not implemented in preprocessing ( 3 ).

The measured values (M) or the preprocessed measured values (MV) are fed to an evaluation unit with elements of the fuzzy logic ( 4 ), in which the information directly contained in the measured values (M) or preprocessed measured values (MV) is fuzzified. Depending on the problem, various linguistic variables are defined with the fuzzy sets assigned to them. These linguistic variables are linked to one another via an inference machine, which contains a set of rules and regulations for evaluating the rules. In a first step of the measurement data evaluation, the data are assigned to the sets of the linguistic variables and linked according to the set of rules. The resulting individual compatibilities are aggregated for each rule (e.g. with the min operator). From this, the individual results are determined via the inference (e.g. fuzzy AND), which are finally combined to form the overall result using a suitable accumulation operator (e.g. max operator). The result (E) is a weighted union of fuzzy sets of the linguistic result variables. If necessary, a suitable initial value can be obtained from this by means of a suitable defuzzification method (e.g. focus method) which can replace the result (E).

The measurement results (E) are fed to a unit for displaying and storing measured values ( 5 ).

This unit ( 5 ) is designed in such a way that the measured values both before (M) and after the preprocessing (MV) are preferably represented graphically and can be stored in files. Furthermore, the measurement results (E) derived from the preprocessed measured values (MV) can also be represented predominantly graphically and saved in files.

The unit ( 6 ) for controlling / regulating processes running simultaneously with the measurement is optional. In it, the sharp measurement results of the evaluation unit with elements of the fuzzy logic ( 4 ) for controlling / regulating the measurement process itself (for example sensor tracking) or of processes which influence the object to be examined (preferably coating processes in which the applied layer the object to be examined represents and which should be controlled in terms of their efficiency).

The specific type of control depends on the specific problem. Furthermore, the control unit ( 6 ) can be used to influence the evaluation unit with elements of the fuzzy logic ( 4 ). Thereby, adjustable operators (fuzzy AND, gamma operator, etc.) are readjusted. To support the learning ability of the evaluation unit with elements of the fuzzy logic ( 4 ), neural networks can also be used within this unit, with the aid of which, for example, new data structures can be taught.

In the following, only the functioning of the evaluation unit ( 4 ) with elements of the fuzzy logic is discussed in more detail. It is assumed that the measured values (M) or the preprocessed measured values (MV) are in a suitably prepared form. If this is not the case, the actual evaluation can be preceded by methods that are implemented in software. In the present case, this could be a logarithmization of the preprocessed measured values.

In the example, the measurement data to be evaluated come from scattered light measurements on smooth surfaces with defects. These defects are to be characterized on the basis of the scattered light distributions. The corresponding curves are shown by way of example in FIG. 3 (normalized intensity Φ over the scattering angle ⌀).

The differences between the curves are significant, but not easy to grasp numerically. For this reason, essential properties of the curves are summarized in fuzzy variables that are linked via a set of rules. Variables and rules are shown in Fig. 4, where µ is the membership function.

Both the variables and the set of rules are special in individual cases Adapt to requirements. A definition of three triangle sets per is sufficient here Variable and a simple link using the minimum operator. As an inference Method, the max-min inference can be applied. Defuzzification is not required as it is a pure classification problem. Farther there is no need to add new data structures during the measurement process, whereby on the use of adjustable operators or neural networks in this Example can be omitted.

Reference list

1 measurement object
2 sensors
3 preprocessing of measured values
4 Evaluation unit with elements of the fuzzy logic
5 Unit for measurement value display and measurement value storage
6 control unit
OD object data
M measured values
MV preprocessed measured values
E measurement results
ST control signals
Φ relative intensity
⌀ angle
µ membership function.

Claims (17)

1. Arrangement for the characterization of surfaces and for the characterization and classification of surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media, consisting of a measurement object ( 1 ), a measurement value sensor ( 2 ), a unit for measurement value display and measurement value storage ( 5 ) and preferably a measured value preprocessing ( 3 ) and preferably a control and / or regulating unit ( 6 ), characterized in that
a transducer ( 2 ) is connected to an evaluation unit with elements of the fuzzy logic ( 4 ) and
the evaluation unit with elements of the fuzzy logic ( 4 ) is connected to the unit for displaying and storing measured values ( 5 ).
2. Arrangement according to claim 1, characterized in that the evaluation unit with elements of the fuzzy logic ( 4 ) is connected to a control / regulating unit ( 6 ) and the control / regulating unit ( 6 ) is connected to control inputs of the measurement object ( 1 ) , wherein preferably a unit for displaying measured values and storing measured values is interposed and / or the control unit ( 6 ) is additionally optionally connected to control inputs of the measured value sensor ( 2 ) and / or the evaluation unit with elements of the fuzzy logic ( 4 ).
3. Arrangement according to claim 1, characterized in that an output of the transducer ( 2 ) and / or an output of the measured value preprocessing ( 3 ) are connected to inputs of the unit for displaying measured values and storing measured values.
4. Arrangement according to claim 1, characterized in that in the evaluation unit with elements of the fuzzy logic ( 4 ) neural networks are included for the purpose of realizing a certain ability to learn the arrangement.
5. Arrangement according to claim 1, characterized in that as a transducer ( 2 ) a preferably angular and / or azimuthally resolving scattered light measuring arrangement or another, preferably non-contact, surface scanning device, for example an optical profilometer or an interference optical device or at least one CCD Matrix camera is used.
6. Arrangement according to claim 1, characterized in that the measurement object ( 1 ) is a transparent medium, the volume of which can be examined for inhomogeneities, the light source (laser) on one side of the measurement object ( 1 ) and the transducer ( 2 ) preferably on are arranged on the opposite side of the measurement object or the transducer ( 2 ) is designed such that an angular range of up to 360 degrees around the measurement object ( 1 ) can be detected.
7. Arrangement according to claims 1 to 5, characterized in that the measuring arrangement is part of an in-process control / regulation of Coating systems, for example systems for thermal spraying, and / or of systems for automated surface inspection and / or Sorting of coated and / or uncoated material surfaces is.  
8. Method for characterizing surfaces and for characterizing and classifying surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media, in which object data (OD) is registered by a measured value sensor ( 2 ) and preferably the measured values (M) of a measured value preprocessing ( 3 ) and preprocessed measured values (MV) are available for evaluation, characterized in that the preprocessed measured values (MV) are fed to an evaluation unit with elements of the fuzzy logic ( 4 ) which are used to obtain information about the surface of the measurement object ( 1 ). Methods of the theory of fuzzy logic are used, the measurement results (E) continue to be supplied to a unit for measurement value display and measurement value storage ( 5 ).
9. The method according to claim 8, characterized in that the measured values (M) and / or preprocessed measured values (MV) of the unit for measured value display and measured value storage ( 5 ) are supplied.
10. The method according to claim 8, characterized in that the measurement results (E) are fed to a control / regulating unit (6) and control signals (ST) are fed (6) to control inputs of the measurement object (1) from the control / regulation unit.
11. The method according to claim 8 or claim 10, characterized in that the control signals (ST) from the control unit ( 6 ) to the control inputs of the sensor ( 2 ) and / or the evaluation unit with elements of the fuzzy logic ( 4 ) are supplied .
12. The method according to claim 8, characterized in that in the evaluation unit with elements of the fuzzy logic ( 4 ) neural networks are included, with the help of which a certain learning ability of the method is realized.
13. The method according to claim 8, characterized in that the measured values (M) are preferably resolved angularly and / or azimuthally Scattered light measurements or from other, preferably non-contact, surface scanning methods, for example optical profilometric Method or interference optical method or image recording with a CCD matrix camera.
14. The method according to claim 8, characterized in that the surface of the measurement object ( 1 ) and / or its near-surface regions are scanned.
15. The method according to claim 14, characterized in that the roughness of the surface and / or surface defects and / or defects near the surface in the range from approximately 1 nm to 1 mm, for example Scratches, cracks, point defects, pores can be determined.
16. The method according to claim 13, characterized in that Structural features in the volume of transparent media (for example Floating particles in liquids, pores and cavities in the glass) can be scanned.  
17. The method according to claims 8 to 15, characterized in that the control / control signals (ST) obtained from the measurement results (E) for in process control of coating systems, for example systems for thermal spraying and / or for automated surface control and / or sorting of coated and / or uncoated Material surfaces can be used.
DE19944415004 1993-04-30 1994-04-29 Arrangement and method for characterising surfaces and for characterising and classifying surface defects and near-surface defects as well as inhomogeneities in the volume of transparent media Withdrawn DE4415004A1 (en)

Priority Applications (2)

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DE4314825 1993-04-30
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DE19824304A1 (en) * 1998-05-28 1999-12-02 Maass Ruth Apparatus for classifying pieces of leather, having a camera to scan the leather on a digitizing bed and a computer to evaluate the data
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US6880207B2 (en) 2002-06-20 2005-04-19 Rieter Ingolstadt Spinneremaschbau Ag Method and device to evaluate signals of a sensor to monitor a textile machine
CN107860727A (en) * 2017-10-25 2018-03-30 宇星科技发展(深圳)有限公司 A kind of method and device for detecting water quality transparency

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