Patent Application
20250164409
Impurities, such as dirt or particles, that are present in manufacturing equipment or the surrounding production environment can cause defects or otherwise degrade the performance of endless sheets that are used to form, for example, electrochemical cells and capacitors. These same impurities can also damage the equipment rollers, such as calendering rollers and nip rollers, by causing surface indents. The surface integrity of equipment rollers is critical because surface indents on equipment rollers can result in formed sheets for electrochemical cells that are outside of dimensional specifications as a result of improper handling and deformation of the powders used to form such sheets. Furthermore, the impurities themselves can become embedded within the endless sheets. These impurities and roller surface defects in such equipment can reduce electrochemical cell performance and reliability and increase the chance of product failure.
There exists a need for improved detection technologies for identifying and locating defects in manufacturing machine surfaces and/or produced electrodes.
In some embodiments, the system can include at least one camera and at least one processing device configured to detect a presence or absence of one or more defects in the machine surface using image input from the at least one camera.
In some embodiments, the at least one camera comprises two or more cameras.
In some embodiments, the at least one camera can be an optical camera.
In some embodiments, the at least one camera can have a resolution of at least about 0.5 mm.
In some embodiments, the at least one camera can be configured to capture image output periodically.
In some embodiments, the at least one camera can be configured to capture image input based on external input including at least one of sensor input and user input.
In some embodiments, the at least one camera can be configured to transmit the image input to the at least one processing device wirelessly.
In some embodiments, the at least one processing device can be further configured to receive and analyze the image input to detect the presence of one or more defects in the machine surface.
In some embodiments, the at least one processing device can be further configured to output a report or signal on the presence of defects in the machine surface.
In some embodiments, the at least one processing device can be further configured to count defects in the machine surface.
In some embodiments, the at least one processing device is configured to determine a physical location of defects in the machine surface.
In some embodiments, a method of detecting a presence or absence of defects in a machine surface used to produce an electrode can include providing at least one machine surface used to produce an electrode, obtaining at least one image of the machine surface using at least one camera, and analyzing the image using at least one processing device to detect the presence or absence of the defects.
In some embodiments, the method can further include obtaining the at least one image periodically.
In some embodiments, the method can further include obtaining the at least one image based on external input including at least one of sensor input and user input.
In some embodiments, the analyzing can be qualitative.
In some embodiments, the analyzing can be quantitative.
In some embodiments, the method can further include determining if the presence of defects is acceptable.
In some embodiments, the method can further include determining a physical location of defects in the machine surface.
In some embodiments, the method can further include applying a fluid to the machine surface before obtaining the at least one image.
The disclosure will become more fully understood from the following detailed description, taken in conjunction with the accompanying figures, in which:
As used herein, the term “about” when immediately preceding a numerical value means a range of plus or minus 10% of that value, for example, “about 50” means 45 to 55, “about 25,000” means 22,500 to 27,500, etc., unless the context of the disclosure indicates otherwise, or is inconsistent with such an interpretation.
The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that this disclosure is not limited to particular methods, reagents, compounds, compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
As used in this document, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art. Nothing in this disclosure is to be construed as an admission that the embodiments described in this disclosure are not entitled to antedate such disclosure by virtue of prior invention. As used in this document, the term “comprising” means “including, but not limited to.”
While various compositions, methods, and devices are described in terms of “comprising” various components or steps (interpreted as meaning “including, but not limited to”), the compositions, methods, and devices can also “consist essentially of” or “consist of” the various components and steps, and such terminology should be interpreted as defining essentially closed-member groups.
With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.
It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (for example, bodies of the appended claims) are generally intended as “open” terms (for example, the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to embodiments containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (for example, “a” and/or “an” should be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (for example, the bare recitation of “two recitations,” without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (for example, “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B.”
In addition, where features or aspects of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.
As will be understood by one skilled in the art, for any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, etc. As will also be understood by one skilled in the art all language such as “up to,” “at least,” and the like include the number recited and refer to ranges which can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, a group having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.
Various of the above-disclosed and other features and functions, or alternatives thereof, may be combined into many other different systems or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art, each of which is also intended to be encompassed by the disclosed embodiments.
This disclosure is not limited to the particular systems, devices and methods described, as these may vary. The terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope.
Systems can be assembled to aid in the detection of defects in machine surfaces used to manufacture electrodes.
Referring to
Referring to
The number of cameras can generally be any number such as 1 or 2 or more. For example, 1, 2, 3, 4, 5, 6, or more cameras can be used.
The at least one camera can generally be of any type. For example, the at least one camera can be an optical camera. The at least one camera can generally have any minimum resolution. For example, the minimum resolution can be at least about 0.5 mm, at least about 0.4 mm, at least about 0.3 mm, at least about 0.2 mm, or at least about 0.1 mm. The minimum resolution is at least sufficient to detect a defect. For example, a dent may be at least about 0.5 mm in width, so the minimum resolution can be selected to be at least about 0.5 mm to detect the dent.
When two or more cameras are used in the system, the cameras can be configured in generally any orientation. For example, each camera can be oriented relative to the surface to be imaged. Each camera can generally be oriented at any angle relative to the surface to be imaged, such as about 0 degrees, about 5 degrees, about 10 degrees, about 15 degrees, about 20 degrees, about 25 degrees, about 30 degrees, and ranges between any two of these values. In examples where two or more cameras are used, the cameras can be oriented at the same or different angles relative to the surface to be imaged. Referring briefly to
The at least one camera can be configured to obtain at least one image and to transmit the at least one image to the processing device for analysis. The at least one camera can be configured to obtain images periodically or based on external input. In some embodiments, each image can comprise a still image. In some embodiments, the at least one image can comprise a video at a predetermined framerate. Image capture may be prompted based on external input from a sensor (e.g., temperature, humidity, etc.) or a user. For example, a temperature sensor may detect the machine surface has surpassed a predetermined threshold temperature, and capture imagery periodically to analyze product quality until the temperature drops below the threshold. The camera can be configured to transmit the image by wire/cable or wirelessly (such as through a network, Wi-Fi, or Bluetooth connection).
The processing device can generally be any type of processing device, such as a desktop computer, laptop computer, tablet, mobile phone, and so on. The processing device can be configured to receive the at least one image and to analyze the image to detect the presence or absence of one or more defects in the machine surface. The processing device can be configured to correct for any image distortion caused by the positioning of the camera. In some embodiments, image distortion correction can be based on a known placement of the camera. In some embodiments, image distortion correction can be performed automatically. Landmarks, such as those described herein, can aid in the automatic correction for image distortion. The processing device can be further configured to output a report or signal based on the presence and/or absence of defects in the machine surface.
The presence or absence of defects can be determined qualitatively (for example, “no defects” or “defects detected”) or quantitatively (for example, “zero defects”, “one defect”, “two defects”, etc.). In some embodiments, the processing device is configured to count defects in the machine surface. In some embodiments, the processing device can be configured to compare the number of detected defects against a standard or threshold value. Such an embodiment may be used where the machine surface is deemed acceptable if the number of detected defects is below the standard or threshold value and unacceptable if the number of detected defects is above the standard or threshold value. The processing device can additionally or alternatively compare the number of detected defects against an average number of defects over a time period to detect changes in production quality. Detected defects can be measured in a variety of ways. For example, the number of defects in a given area can be measured. In some examples, an acceptable number of defects may be not more than about 1 defect/m2, not more than about 0.5 defects/m2, not more than about 0.4 defects/m2, not more than about 0.3 defects/m2, not more than about 0.2 defects/m2, not more than about 0.1 defects/m2, and so on. In an ideal case, the number of defects would be less than the detection limit of the system, that is, no detected defects/m2.
In some embodiments, the processing device can be configured to identify a number of detected defects. In some embodiments, the processing device can be configured to provide information regarding the physical location of the defect on the machine surface.
The machine surface used to produce an electrode can generally be any machine surface. Illustrative machine surfaces may include calendering rollers.
The system can further include at least one alarm. For example, the alarm can be configured to signal an operator when a machine surface has an unacceptable number of defects. The alarm signal can be auditory, optical, or haptic. The alarm signal can be an electrical signal sent to a remote processing device.
The system can further include at least one database of detected defects. The system can be configured to compare the obtained image or images against the database of previously detected defects. The system can be configured to add newly detected images of defects to the database.
The system can further include a non-transitory storage device storing a template image of the machine surface. The system can be configured to acquire new template images of the machine surface during operation.
Methods can be performed to aid in the detection of defects in the machine surfaces used to manufacture such electrodes.
In an example, methods are provided for detecting the presence or absence of defects in at least one machine surface used for electrode manufacturing. In some embodiments, the methods comprise providing at least one machine surface, obtaining at least one image of the machine surface using at least one camera, and analyzing the at least one image using at least one processing device to detect the presence and/or absence of a defect. The number, types, and orientation of cameras used in such methods can be in the manner described above.
The at least one image can be obtained periodically or based on external input. The at least one image can be a still image or video. The type of image and image capture rate can be selected based on factors such as line speed and roller diameters. In some embodiments, the method further comprises applying a fluid to the machine surface before obtaining the at least one image.
The at least one image may be analyzed qualitatively (for example, “no defects” or “defects detected”) or quantitatively (for example, “zero defects”, “one defect”, “two defects”, etc.). Analyzing the at least one image may include comparing the number of detected defects against a standard or threshold value. In such an embodiment, a machine surface may be deemed acceptable if the number of detected defects in each analyzed image is below the standard or threshold value. Conversely, a machine surface may be deemed unacceptable if the number of detected defects in each analyzed image is above the standard or threshold value. Analyzing each image may additionally or alternatively include comparing the number of detected defects against an average number of defects over a period of time. In such an embodiment, the comparison may enable the detection of changes in production quality. In some embodiments, an image of the entire machine surface may be analyzed for defects. In some embodiments, portions of an image of a machine surface may be sampled.
Analyzing the machine surface can further comprise comparing collected images with a template image. Referring to
Referring to
Image comparison can include preprocessing the images by the processing unit. Preprocessing can further include correcting for alignment and distortion. In embodiments featuring a landmark, the processing unit can distort and align the landmark to match the template image. Preprocessing can further include other image corrections including, but not limited to, saturation, contrast, and color selection.
Image comparison can utilize machine-learning, a neural network, and/or artificial intelligence. Machine-learning for image comparison can include forming a training set. The training set can comprise images with known defects or images created to mimic defects using a template image.
Image comparison can include comparing the collected images and template on a pixel-by-pixel basis. Alternatively, pixels can be clustered an averaged for comparison.
The method can further include flowing a liquid, such as water, across the machine surface to improve detection of defects. The flowing liquid can change the reflective properties of the surface to improve image contrast.
The method can further include comparing the obtained image or images against at least one database of previously detected defects. The method can further include adding any newly detected images of defects to the database.
The present application claims priority to and benefit of U.S. Provisional Application No. 63/315,354 filed Mar. 1, 2022, the disclosure of which is hereby incorporated by reference herein in its entirety.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2023/055161 | 3/1/2023 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63315354 | Mar 2022 | US |
