WO2011137264A1

WO2011137264A1 - Thermal imaging of molded objects

Info

Publication number: WO2011137264A1
Application number: PCT/US2011/034384
Authority: WO
Inventors: Matthias Walther; Timothy P. White
Original assignee: Mettler-Toledo, Inc.
Priority date: 2010-04-28
Filing date: 2011-04-28
Publication date: 2011-11-03

Abstract

A system and method for the non-destructive testing and detection of thickness and structural variations in opaque and semi-opaque non-metallic composites and plastic materials. Systems and methods of the invention include infrared thermographic methods that may utilize thermal reference templates, either synthetic or acquired, to determine internal and backside material properties and embedded irregularities of, for example, opaque and closed structures. In one exemplary embodiment, a machine vision system and related sensors are employed to yield data relevant to an object molding process, and the data is used to inform operators of the status of the molding process and to allow active feedback mechanisms to optimize the molding process.

Description

THERMAL IMAGING OF MOLDED OBJECTS

TECHNICAL FIELD

[0001] Embodiments of the invention relate generally to the use of thermal imaging for non-destructive testing and detection of thickness and structural variations in opaque and semi-opaque non-metallic composites and plastic materials.

BACKGROUND

[0002] In recent years, non-destructive infrared (IR) measurement techniques have surfaced which allow users to determine the cross-sectional thickness of predominantly translucent PET plastic and glass containers and other translucent objects. In these systems, I R light sources are placed on the inside or outside of IR transparent containers with receiving IR cameras located opposite each light source. The emitted IR light passes through the container walls, undergoing transmissions, reflections, and refractions just as light would within the visual range of the electromagnetic spectrum.

[0003] However, opaque and semi-opaque objects (e.g., containers) are also frequently encountered for which IR measurement techniques would be more suitable than conventional visual inspection methods, especially since IR imaging techniques provide the ability to examine sub-surface, interior and backwall structural characteristics in real time while the object is undergoing thermal changes. Additionally, thermographic techniques provide the ability to determine the size and relative depth of flaws or deviations from a template within an opaque, yet thermally translucent material, provided that at least one region on the object is slightly hotter or cooler than an adjacent region or the surroundings. These conditions have been found to exist, for example, when a plastic or composite part is ejected from an operating mold. Consequently, it has been discovered that thermal monitoring for providing on-line analysis of such parts can be of great value.

[0004] For example, while still in the mold a formed part (e.g., a blow- molded plastic bottle) is rapidly cooled on its surface by the mold in order to facilitate its release therefrom, and is subsequently allowed to cool further in ambient air. Once removed from the mold, the molded part may have a surface skin temperature that is discernibly cooler than its sub-layers or even its surroundings. At this point, the process of heat convection will begin spreading and removing heat from the part until an equilibrium has been reached, first within the molded part and later with the surroundings. It has been found that wall sections having a greater cross-section (i.e., wall thickness) will remain warmer for a longer period of time due to the greater heat capacity of their relative mass, and this phenomenon is easily visible with thermography.

[0005] While this dynamic heat transfer process is known both in theory and in practice, the existing systems and methods for analyzing this phenomenon using imaging techniques are quite basic and do not presently utilize the wealth of information that can be extracted from the thermal data. Distributed IR intensity, also known as total emittance (which is registered by the bolometer array of an uncooled IR camera) is actually composed of the sum of emissivities of the object in the field-of-view (FOV), the atmosphere between the object and the camera, as well as all contributions from nearby IR emitters (such as lighting, nearby machinery, and people) which can be compared to an effect similar to that of a variable complex filter. Thus, it is desirable to develop a system and method that can utilize the IR images of objects and analyze them as if they were embedded within variable and complex filters that modulate the actual electromagnetic I R radiation from within a hot object.

SUMMARY OF THE GENERAL INVENTIVE CONCEPT

[0006] The exemplary embodiments of the invention utilize a system and method for several infrared thermographic techniques that utilize thermal reference templates, either synthetic or acquired, in determining various material properties as well as embedded irregularities of various structures in order to provide structural and material integrity information not accessible without extraordinary visual or mechanical means. One or more IR cameras may be used to measure recently molded objects. A vision processor may compare the measurements from the IR cameras with established templates for the corresponding mold. The vision processor can yield a variety of data relevant to the object molding process where the data can be used to inform operators of the status of the molding process and to allow for active feedback mechanisms for optimizing the molding process.

BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In addition to the features mentioned above, other aspects of the invention will be readily apparent from the following descriptions of the drawings and exemplary embodiments, wherein like reference numerals across the several views refer to identical or equivalent features, and wherein:

[0008] FIGURE 1 is a schematic representation of the basic components of one embodiment of a system of the invention;

[0009] FIGURE 2 is a flow chart illustrating the performance of an exemplary method of the invention, as well as the logic for controlling an exemplary embodiment of a system thereof; and

[0010] FIGURE 3 is a schematic representation of a similar embodiment to that shown in Figure 1 , with the molds and molded products shown with shading indicating the typically-observed heating and cooling of the products while inside and outside of the mold cavities.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENT(S)

[0011] FIGURE 1 schematically represents the basic components of one exemplary embodiment of a system of the invention. In this embodiment, a multi-cavity molding machine 100 is shown to produce molded products 1 10 from a plurality of mold cavities 1 01 . As shown, once a product 1 10 is molded and sufficiently cooled, it is released from its mold cavity and transferred to a downstream process(es) which, in this case, includes thermal imaging.

[0012] Due to variations in such mold cavities 101 , it has been found that the thermal appearance of a given product will reflect the unique characteristics of the mold cavity in which it was produced. Thus, it is desirable to compare each molded product 1 1 0 with the specific mold cavity 101 in which the product 1 1 0 was created. To this end, a visual template 700 corresponding to the normal appearance of a product may be generated for each mold cavity 101 and may be stored within a vision processor 150 or another storage device associated with the system. Such a visual template 700 may be a nominal image of a product from a given mold cavity, the nominal image serving as a unique template against which may be compared run-time products produced by an associated molding machine. When a process employs multiple mold cavities, a nominal image of a product from each mold cavity may be created.

[0013] As shown in FIGURE 1 , this particular system includes two I R cameras 200 and 201 that are located so as to produce thermal images of the products 1 1 0 at various time increments after the molded products 1 10 exit the mold cavities 101 . These images may be referred to as 'run-time' images because they are generated in real-time as actual molded products 1 10 leave the mold cavities 101 .

[0014] Preferably, the IR cameras 200, 201 are located so that the molded products 100 are imaged at the point of maximum thermal emissivity difference between the thicker and thinner portions of the product sidewalls. Such a camera placement is preferable because this point in the product cooling cycle may provide some of the most valuable thermal inspection data with respect to thickness defects in the molded products 1 10. Of course, more than two IR cameras can be used with other embodiments in order to provide additional data and ensure that the point of maximum thermal emissivity difference has been measured. Alternatively, only a single IR camera may be used. [0015] The run-time thermal images from the IR cameras 200, 201 may be sent to the vision processor 150 of the system and compared with a template 700 corresponding to the particular mold cavity 101 in which the molded product 1 10 was created. In case of run-time changes, and since the run-time 5 thermal image will be compared to a corresponding template, the vision processor is capable of selecting a corresponding or pre-defined template based on the thermal age of the object.

[0016] The run-time thermal image may be compared with the template using a number of different image comparison algorithms. An exemplary i o embodiment may use an image subtraction algorithm that subtracts the thermographic image of an object from a corresponding template image, or vice versa, to obtain a 'difference' or 'delta' image that is subsequently stored in memory. The resulting delta image can then be interpreted through many different algorithms to indicate different defect conditions, typically with

15 greater differences corresponding with more significant defect conditions in the molded product 1 10.

[0017] Features in the delta image are detectable with various vision tools that may, for example, measure areas of the image having a greater or lesser brightness value than some pre-selected brightness value. Alternatively, a 20 vision tool may be used to measure the standard deviation of brightness values within a given region or across the entire delta image of the molded product 1 10.

[0018] The resulting information produced by such vision tools may be associated with minimum or maximum acceptable limits, such that when these limits are exceeded, an appropriate control signal is sent to a process controller for automatic process adjustment. In addition to the control signal, an image of a molded product may be presented to an operator on a user interface (Ul), such that the operator may analyze the delta image or any of the data resulting from the vision tools. Defect areas may be highlighted and further analyzed. The Ul may also be in communication with the vision processor 1 50, to allow for appropriate process adjustments to be made by the operator upon review of the delta image and/or related data. In either case, the process may be adjusted in real-time to minimize any product defects or loss of production parts due to quality control issues.

[0019] FIGURE 2 provides a flow chart for performing one exemplary method of the invention, and also illustrates the logic for controlling an exemplary embodiment of an associated system. Initially, optimum inspection point(s) should be selected to optimize the radiance signature for the features of interest in the molded product or other object of interest. Thus, I R cameras should be located so that thermal images captured thereby may be produced at these optimum inspection point(s). Although not essential, it is also preferable to substantially shield the inspection area from interfering ambient radiation.

[0020] As described above, a product template image should be generated and stored for the mold cavity, or for each mold cavity if using a multi-cavity mold machine. A template image may be created in a number of ways. One method for creating a template image is to synthetically create the template image based on user-defined requirements. Another method for creating such a template image is to create a thermographic image of an ideal or normal molded product for each mold cavity involved.

[0021] Once the molding machine begins to produce molded products, the run-time thermal images for mold cavity N are acquired at the inspection 5 point(s). If the molded product is moving while the run-time thermal images are produced, it may be preferable to apply image blur correction (e.g., by using a linear transform algorithm) to the thermal images. It may also be preferable to include an ambient temperature indicator in the FOV of the I R camera(s), such as by employing a piece of thin, blackened aluminum, or a i o calibrated black-body radiation source. The data from this ambient temperature indicator can be used to normalize the grey-scale histogram of the run-time image. Alternatively, a remote temperature sensor could be used to detect the ambient temperature of a thermally sensitive object in the immediate vicinity of the molded product and this could be used to normalize

15 the run-time image.

[0022] The previously-generated template image for mold N should then be accessed. The run-time image and the template image may then be normalized through an analysis of their grey-scale histograms so that the images match as closely as possible. This could be done by normalizing the

20 run-time image to the template or vice versa.

[0023] Preferably, the template image is then normalized with the current ambient radiation environment. Further, it may be preferable to normalize the template image with the ambient temperature. This could be done by using data received from the blackened aluminum, calibrated black-body radiation source, or the remote temperature sensor data.

[0024] If the precise orientation of the molded product cannot be controlled adequately, then it may also be preferable to measure the X-Y location and 5 rotation (Θ) of the molded product in the run-time image and (if necessary) translate and rotate the run-time image in order to match the X-Y location and rotation (Θ) of the molded product in the corresponding template for mold N.

[0025] At this point the delta image may be created, by subtracting the runtime image from the template image or vice versa. The delta image can then 10 be analyzed using a number of different vision tools. For example, tools known as blob, edge, masking, and more advanced vision tools can be implemented to extract detailed image features from these thermal or delta images. Furthermore, statistical vision tools can be applied to desired areas of the delta image for determining maximum/minimum threshold limits, Mini s Max calculations, as well as standard deviation estimates. A statistical approach towards image analysis may accelerate the decision-making process when a decision for discarding a faulty or non-standard object must be made during a time span before the next object arrives.

[0026] The delta image may be displayed and analyzed on the U l 20 according to a preferred false color scheme, such as by manipulating an image of a molded part to highlight various defect conditions by overlaying selected colors on top of a run-time image to indicate good and bad areas thereof, etc. The Ul could display a running average delta image for the most recent X number of molded products issued from any specific mold cavity, according to a preferred false color scheme. The Ul could display a standard deviation image of the most recent X number of molded products issued from any specific mold cavity, according to a preferred false color scheme. The Ul could display a running average delta image of the most recent X number of molded products issued from all mold cavities, according to a preferred false color scheme. The Ul could display a standard deviation image of the most recent X number of molded products issued from all mold cavities, according to a preferred false color scheme. The Ul could display the X most recent molded products displaying data outside the bounds of the acceptable thresholds.

[0027] In an exemplary embodiment, the data from a plurality of running average delta images could be analyzed to provide feed-back signals to the process controller. These feed-back signals may be used to adjust the process in order to minimize the overall intensity and/or standard deviation within selected portions of the images.

[0028] As shown in FIGURE 2, some or all of the processing related to the template and its normalization may occur simultaneously with the normalization and positioning of the molded product thermal image.

[0029] FIGURE 3 is a schematic view showing an embodiment similar to the embodiment shown in FIGURE 1 , with the molds and molded products shown with shading again indicating the typically-observed heating and cooling of the products while inside and outside of the mold cavities.

[0030] Unlike systems and methods that use I R transmission and emittance measurements to analyze visually clear or semi-translucent objects, the exemplary embodiments herein do not require the use of emission- creating IR light sources. In this sense, the invention involves a passive system for thermal analysis of opaque and semi-opaque non-metallic composites and plastic materials.

[0031] When a material is thermally translucent, IR radiation is known to originate from anywhere within the material. Thus, intensity variations originating from sub-surface regions can be detected according to the invention and these images can be processed for display. Exemplary methods could also be used, for example, to produce images showing the inside or back wall of a closed container. Thus, the embodiments herein can interpret the transient depth thermographic data of sub-surface and inside (back wall) structures in order to locate variations and/or flaws, which is especially useful with respect to opaque objects such as containers.

[0032] The delta images of the invention are not limited to creation by subtraction methods. Rather, some delta images may be created using subtraction, division, multiplication, or a combination of these operations via a formula. An exemplary formula could mathematically simulate an optical filter or lens that may be used to compensate for an optical aberration or curvature. One exemplary purpose for this process would be to flatten the images for further processing and analysis.

[0033] Embodiments of the invention may be used as a perspective transformation matrix method of correlating one view of a thermal image with another view of the same thermal image in order to create a 3D view. Thus, two thermal images of the same molded product could be correlated with respect to one camera-specific (also viewer specific) global coordinate system in which case both images may be stereoscopically combined for 3D display within the global coordinate system. The 3D display could be colored based on an assignment of pre-selected colors to a specific image intensity (i.e. temperature) gradient indicating its relative slope. This could be used to automatically make visible contours of sloped areas and their heights. Stereoscopic image analysis can be accomplished with two camera positions, one camera position and sequential thermographs, or one camera position using one sample thermograph and a template thermograph. Using two cameras like two eyes on one object is mathematically similar to using one camera on two shifted views of the same object. Additionally, if only one image is available, it is possible to use a pre-defined template in place of the second image.

[0034] It should be specifically noted, that although shown using a multi- cavity molding machine, the embodiments of the invention described herein could be practiced with a single-cavity molding machine as well.

[0035] As should be apparent to one of skill in the art from a reading of the foregoing written description and a corresponding review of the associated drawing figures, a system and method of the invention may provide various benefits. For example, a method of the invention may be generally used to monitor continuous in-line emissivity variations and image analysis of thermal objects in real time. A method of the invention may also be generally used to interpret thermographic data in specific but selectable regions, lines or points on or within a thermal image; to correlate and compare such selected regions, lines or points to each other; and to align sequential or referential thermographic images based on digital locators such as thermal laser dots within the images. A method of the invention may further be generally used to correlate image regions to each other for the purpose of statistical analysis such as normalization, standard deviation, Min-Max, histrogram, etc. With respect to molding, a method of the invention may also be employed to monitor the rate of demolded parts in order to adjust image analysis processing by taking into account the thermal age of the parts (e.g., in case demolded part conveyor speed changes) or to monitor successive thermographs for variations indicating abnormal mold function.

[0036] While certain embodiments are described in detail above, it should be apparent that the scope of the invention is not to be considered limited by such disclosure, and modifications are possible without departing from the spirit of the invention as evidenced by the following claims:

Claims

WHAT IS CLAIMED IS:

1 . A system for obtaining and analyzing a thermal image of a molded object, the system comprising:

a first IR camera located so as to produce a first thermal image of the 5 molded object at a first period of time after said molded object exits an associated mold cavity;

a thermal reference template associated with the mold cavity; a vision processor and associated program for comparing the thermal image of said molded object with the thermal reference template; and i o at least one program algorithm for detecting differences between the thermal image of the molded object and a thermal reference template, and for creating a delta image that is interpreted by the program to indicate a defect condition of the object.

2. The system of claim 1 , wherein said IR camera is located so that the 15 molded object is imaged at a point of maximum thermal emissivity difference between thicker and thinner portions thereof.

3. The system of claim 1 , wherein said thermal reference template is acquired through a thermal image of an exemplary molded object.

4. The system of claim 1 , wherein said thermal reference template is 20 synthetically generated.

5. The system of claim 1 , further comprising a second I R camera located so as to produce a second thermal image of the molded object at a second period of time after said molded object exits an associated mold cavity, and wherein the vision processor selects between the first and second thermal images to compare with the thermal reference template.

6. The system of claim 1 , wherein said at least one program algorithm is an image subtraction algorithm that subtracts the thermographic image of an

5 object from a corresponding template image, or vice versa, to obtain said delta image.

7. The system of claim 5, wherein said vision processor selects between the first and second thermal images based on which image illustrates the maximum thermal emissivity difference between thicker and thinner portions i o of the molded object.

8. The system of any one of claims 1 -7, wherein features in said delta image are detectable with various vision tools.

9. The system of claim 8, wherein said vision tool is adapted to measure areas of the thermal image having a greater or lesser brightness value than

15 some pre-selected brightness value.

10. The system of claim 8, wherein said vision tool is adapted to measure the standard deviation of brightness values within a given region or across at least a portion of the delta image of a molded object.

1 1 . The system of claim 1 , further comprising a user interface through 20 which a delta image of the molded product is displayed to a user of said system.

12. The system of claim 1 1 , wherein defect areas of a displayed object delta image are highlighted on the user interface for further analysis.

13. The system of claim 1 , further comprising a molding machine process controller in communication with said vision processor, said vision processor providing feedback signals to said molding machine process controller to adjust the molding process based on an analysis of a molded object delta image.

14. A method of obtaining and analyzing thermal images of a molded object, comprising the steps of:

producing thermal images of a molded object at various time increments after said molded object exits an associated mold cavity;

providing a thermal reference template for the associated mold cavity; providing a vision processor adapted to compare the thermal images of said molded object produced by said at least one I R camera with the thermal reference template;

using at least one program algorithm to detect differences between the thermal images of the molded object and the thermal reference template and to create delta images that are interpreted by the program to indicate different defect conditions of the molded object.

15. The method of claim 14, further comprising the step of providing an ambient thermal environment sensor.

16. The method of claim 15, further comprising the step of normalizing said thermal reference template based on data from the ambient thermal environment sensor.

17. The method of claim 15, further comprising the step of normalizing said thermal reference template(s) to the current ambient radiation environment.

18. The method of claim 14, further comprising the step of normalizing said thermal reference template(s) to a captured object image, or vice-versa.

19. The method of any one of claims 14-18, further comprising the step of displaying the delta images on a user interface.

5 20. A method of obtaining and analyzing a thermal image of a molded object, comprising the steps of:

applying linear blur correction to the thermal images to produce i o corrected thermal images;

providing a thermal reference template for the associated mold cavity, the thermal reference template having X,Y, and Θ values;

measuring the X,Y, and Θ values for the molded object;

aligning the corrected thermal images to match the X,Y, and Θ values 15 for the thermal reference template to produce aligned thermal images;

comparing the aligned thermal images with the thermal reference template to produce thermal image variations; and

displaying the thermal image variations with a user interface.