CN116342609B - Real-time detection method, system and storage medium based on cutting device - Google Patents
Real-time detection method, system and storage medium based on cutting device Download PDFInfo
- Publication number
- CN116342609B CN116342609B CN202310625249.0A CN202310625249A CN116342609B CN 116342609 B CN116342609 B CN 116342609B CN 202310625249 A CN202310625249 A CN 202310625249A CN 116342609 B CN116342609 B CN 116342609B
- Authority
- CN
- China
- Prior art keywords
- detected
- information
- area
- product quality
- characteristic value
- 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.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20132—Image cropping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Image Analysis (AREA)
Abstract
The application is applicable to the technical field of data processing, and provides a real-time detection method, a real-time detection system and a storage medium based on a cutting device, wherein the method comprises the steps of obtaining a first image to be detected of a target workpiece, wherein the target workpiece comprises at least one cutting area to be detected; dividing the first to-be-detected image based on the to-be-detected cutting area to generate a plurality of second to-be-detected images, wherein the second to-be-detected images comprise the to-be-detected cutting area; comparing a to-be-detected cutting area in the second to-be-detected image with a reference cutting area in a preset reference image to generate first deviation characteristic information, wherein the first deviation characteristic information is used for describing a first deviation degree between the to-be-detected cutting area and the reference cutting area; inputting the first deviation characteristic information into a product quality characteristic value calculation formula to determine a product quality characteristic value of the target workpiece; and uploading the product quality characteristic value to a designated cloud server. The application is beneficial to timely finding out the quality problem of the product.
Description
Technical Field
The application relates to the technical field of data processing, in particular to a real-time detection method and system based on a cutting device and a storage medium.
Background
The fuel cell mainly uses oxygen as raw material, the discharged harmful gas is very little, the fuel cell is one of the most promising power generation technologies from the viewpoints of effective energy saving and ecological environment protection, the membrane electrode is a multiphase substance transmission and electrochemical reaction place in the fuel cell, and a frame membrane is usually arranged on the membrane electrode, and one of the functions of the frame membrane is to keep the membrane electrode in tension.
Currently, in the production process of the frame film, a cutting device (such as a frame coil material cutting machine) is generally required to cut the frame film; because the frame film has certain elasticity, the frame film is easy to deform in the cutting process, and then the cutting deviation phenomenon occurs, so that the tightness of the frame film is greatly reduced; because the current production process of the frame film generally only detects the product quality of the frame film at the extreme end of the production line, the product quality problem is not easy to discover in time, and the frame film needs to be further improved.
Disclosure of Invention
In order to facilitate timely finding out of product quality problems, the embodiment of the application provides a real-time detection method, a real-time detection system and a storage medium based on a cutting device.
In a first aspect, an embodiment of the present application provides a real-time detection method based on a cutting device, where the method includes:
acquiring a first image to be detected of a target workpiece, wherein the target workpiece comprises at least one cutting area to be detected;
dividing the first to-be-detected image based on the to-be-detected cutting area to generate a plurality of second to-be-detected images, wherein the second to-be-detected images comprise the to-be-detected cutting area, and the second to-be-detected images correspond to the to-be-detected cutting areas one by one;
comparing the to-be-detected cutting area in the second to-be-detected image with a reference cutting area in a preset reference image to generate first deviation characteristic information, wherein the first deviation characteristic information is used for describing a first deviation degree between the to-be-detected cutting area and the reference cutting area;
inputting the first deviation characteristic information into a preset product quality characteristic value calculation formula, and determining a product quality characteristic value of the target workpiece;
And uploading the product quality characteristic value to a designated cloud server.
Compared with the prior art, the beneficial effects that exist are: according to the real-time detection method based on the cutting device, the terminal equipment firstly acquires the first to-be-detected image of the target workpiece, then segments the first to-be-detected image based on the to-be-detected cutting area to generate a plurality of second to-be-detected images, compares the to-be-detected cutting area in the second to-be-detected image with the reference cutting area in the preset reference image to generate first deviation characteristic information, inputs the first deviation characteristic information into a preset product quality characteristic value calculation formula to determine the product quality characteristic value of the target workpiece, and finally uploads the product quality characteristic value to the specified cloud server, so that a precise reference quantity related to the product quality of the target workpiece is provided for a user in time, and the user can find the product quality problem in time.
In a second aspect, an embodiment of the present application provides a real-time detection system based on a cutting device, where the system includes:
the first image acquisition module to be detected: the method comprises the steps of acquiring a first to-be-detected image of a target workpiece, wherein the target workpiece comprises at least one to-be-detected cutting area;
The second image generation module to be detected: the method comprises the steps of dividing the first to-be-detected image based on the to-be-detected cutting area to generate a plurality of second to-be-detected images, wherein the second to-be-detected images correspond to the to-be-detected cutting area;
a first deviation characteristic information generation module: the method comprises the steps of comparing the second image to be detected with a preset reference image to generate first deviation characteristic information;
the product quality characteristic value determining module: the first deviation characteristic information is input into a preset product quality characteristic value calculation formula, and the product quality characteristic value of the target workpiece is determined;
and a product quality characteristic value uploading module: and uploading the product quality characteristic value to a designated cloud server.
In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to the first aspect as described above when the processor executes the computer program.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method of the first aspect described above.
It will be appreciated that the advantages of the second to fourth aspects may be found in the relevant description of the first aspect and are not repeated here.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments or the prior art will be briefly described below.
FIG. 1 is a flow chart of a real-time detection method according to an embodiment of the application;
FIG. 2 is a schematic view of a first cutting area according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a first image to be detected according to an embodiment of the present application;
fig. 4 is a flowchart of step S301 in the real-time detection method according to an embodiment of the present application;
fig. 5 (a) is a schematic diagram of a first unit block to be detected according to an embodiment of the present application, and fig. 5 (b) is a schematic diagram of a reference image block according to an embodiment of the present application;
fig. 6 (a) is a first schematic diagram of a second unit block to be detected according to an embodiment of the present application, and fig. 6 (b) is a first schematic diagram of a target reference image block according to an embodiment of the present application;
fig. 7 is a flowchart of step S410 in a real-time detection method according to an embodiment of the present application;
Fig. 8 (a) is a second schematic diagram of a second unit block to be detected according to an embodiment of the present application, and fig. 8 (b) is a second schematic diagram of a target reference image block according to an embodiment of the present application;
FIG. 9 is a third schematic diagram of a second unit block to be detected according to an embodiment of the present application;
FIG. 10 is a third schematic diagram of a target reference image block according to an embodiment of the present application;
fig. 11 (a) is a fourth schematic diagram of a second unit block to be detected according to an embodiment of the present application, and fig. 11 (b) is a fourth schematic diagram of a target reference image block according to an embodiment of the present application;
FIG. 12 is a block diagram of a real-time detection system according to an embodiment of the present application;
fig. 13 is a schematic diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In the description of the present specification and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In order to illustrate the technical scheme of the application, the following description is made by specific examples.
Referring to fig. 1, fig. 1 is a flowchart of a real-time detection method based on a cutting device according to an embodiment of the application. In this embodiment, the execution body of the real-time detection method is a terminal device. It will be appreciated that the types of terminal devices include, but are not limited to, cell phones, tablet computers, notebook computers, ultra-mobile personal computer (UMPC), netbooks, personal digital assistants (personal digital assistant, PDA), etc., and embodiments of the present application do not limit any particular type of terminal device.
Referring to fig. 1, the real-time detection method provided by the embodiment of the application includes, but is not limited to, the following steps:
in S100, a first image to be detected of a target workpiece is acquired.
Specifically, the target workpiece can be a frame film, or can be a part (such as a proton exchange film) which has certain elasticity in the membrane electrode and needs cutting treatment; for easy understanding, the cutting device in the embodiment of the application takes a frame coil stock cutting machine as an example; a high-precision camera suitable for moving objects, such as a high-precision camera of the model PhoXi XS, may be pre-installed on the table of the frame coil cutter; the terminal equipment can acquire a first image to be detected of a target workpiece through a preset high-precision camera, wherein the target workpiece comprises at least one cutting area to be detected; for example, referring to fig. 2, all three first cutting areas in fig. 2 represent cutting areas after the frame coil cutting machine has been used for cutting, and the first cutting areas are to-be-detected cutting areas, and the second cutting areas in fig. 2 represent preselected areas where the frame coil cutting machine has not been used for cutting.
In S200, the first image to be detected is divided based on the cutout area to be detected, and a plurality of second images to be detected are generated.
For example, referring to fig. 3, after the terminal device acquires the first to-be-detected image of the target workpiece, the terminal device acquires first pixel gray value information in the first to-be-detected image, where the first pixel gray value information is used for describing gray values of various pixel points in the first to-be-detected image, and the first pixel gray value information includes second pixel gray value information of a to-be-detected trimming area and third pixel gray value information of the first to-be-detected image except for the to-be-detected trimming area; because the second pixel gray value information and the third pixel gray value information are obviously different, the terminal equipment can compare gray values between adjacent pixel points, accurately determine each to-be-detected cutting area in the first to-be-detected image, then divide the first to-be-detected image based on the to-be-detected cutting areas, and generate two second to-be-detected images, wherein each second to-be-detected image comprises to-be-detected cutting areas, each second to-be-detected image corresponds to each to-be-detected cutting area one by one, and accordingly adverse effects of invalid data or low-value data on subsequent accurate discovery of product quality problems are reduced.
In S300, the to-be-detected clipping region in the second to-be-detected image is compared with the reference clipping region in the preset reference image, and first deviation characteristic information is generated.
Specifically, the terminal device may compare the to-be-detected cutting area in the second to-be-detected image with a reference cutting area in a preset reference image to generate first deviation characteristic information, where the reference image is used as a key indicator for measuring whether the product quality of the target workpiece is qualified, and the reference image may be an image obtained by photographing a border film with qualified product quality in advance by using a high-precision camera, or the reference image may be a high-precision simulation image for the border film with qualified product quality; and the first deviation characteristic information is used to describe a first degree of deviation between the to-be-detected trimming area and the reference trimming area.
In some possible implementations, referring to fig. 4, in order to achieve accurate discovery of product quality problems, the method further includes, but is not limited to, the following steps:
in S301, for each to-be-detected trimming area in the second to-be-detected image: and acquiring the coordinate information of the edge points of the cutting area to be detected.
Specifically, the terminal device may perform the following processing for the to-be-detected trimming area in each second to-be-detected image: and acquiring the coordinate information of the edge points of the cutting area to be detected, wherein the coordinate information of the edge points is used for describing the coordinates of the outline boundary points of the cutting area to be detected.
In S302, the to-be-detected trimming area in the second to-be-detected image and the reference trimming area in the preset reference image are respectively subjected to gridding division to obtain a plurality of first to-be-detected unit blocks forming the to-be-detected trimming area, and a plurality of reference image blocks forming the reference trimming area are obtained.
For example, referring to fig. 5 (a) and (B), after the terminal device obtains the coordinate information of the edge point of the to-be-detected cutting area, the terminal device may respectively grid-divide the to-be-detected cutting area in the second to-be-detected image and the reference cutting area in the preset reference image according to grid units of the same size and shape, so as to obtain a plurality of first to-be-detected unit blocks forming the to-be-detected cutting area, that is, a plurality of rectangles with letters "a", "B", "C", "D", "E", "F", "G", "H", "I" and "J" in fig. 5 (a); and obtaining a plurality of reference image blocks constituting a reference trimming area, that is, a plurality of rectangles having letters "K", "L", "M", "N", "O", "P", "Q", "R", "S" and "T" inside in (b) of fig. 5; it should be noted that, each unit block to be detected corresponds to each reference image block one by one, for example, a first unit block to be detected corresponding to a rectangle with letter "a" corresponds to a reference image block corresponding to a rectangle with letter "K"; the first unit block to be detected corresponding to the rectangle with the letter "B" corresponds to the reference image block corresponding to the rectangle with the letter "L"; the first unit block to be detected corresponding to the rectangle with the letter "C" corresponds to the reference image block corresponding to the rectangle with the letter "M".
In S303, based on the plurality of first unit blocks to be detected, the first unit blocks to be detected including the edge point coordinate information are selected as the second unit blocks to be detected.
Specifically, after the terminal device obtains the plurality of first unit blocks to be detected and the plurality of reference image blocks, the terminal device may select, based on the plurality of first unit blocks to be detected, the first unit blocks to be detected including the edge point coordinate information as the second unit blocks to be detected; for example, referring to fig. 5 (a), when the to-be-detected cutting area is as shown in fig. 5 (a), the terminal device may select a first to-be-detected unit block corresponding to each of a plurality of rectangles with letters "a", "B", "C", "D", "E", "F", "G", "H", "I", and "J" as a second to-be-detected unit block; referring to fig. 6 (a), when the to-be-detected cutting area is shown in fig. 6 (a), the terminal device may select a plurality of rectangular first to-be-detected unit blocks with letters "A1", "B1", "C1", "D1", "E1", "F1", "G1", "H1", "I1", "P1", "Q1", "R1", "S1", "T1", "U1", "V1", "W1" and "X1" as the second to-be-detected unit blocks.
In S304, a reference image block corresponding to the second unit block to be detected is selected as a target reference image block based on the plurality of reference image blocks.
Specifically, the terminal device may select, based on the plurality of reference image blocks, the reference image block corresponding to the second unit block to be detected as the target reference image block, and for example, referring to (b) in fig. 5, when the reference trimming area is as shown in (b) in fig. 5, the terminal device may select, as the target reference image block, the reference image block corresponding to each of the plurality of rectangles having letters "K", "L", "M", "N", "O", "P", "Q", "R", "S" and "T"; referring to fig. 6 (B), when the reference trimming area is as shown in fig. 6 (B), the terminal device may select the reference image blocks corresponding to each of the rectangles with letters "A2", "B2", "C2", "D2", "E2", "F2", "G2", "H2", "I2", "P2", "Q2", "R2", "S2", "T2", "U2", "V2", "W2" and "X2" as the target reference image block.
Accordingly, step S300 includes, but is not limited to, the following steps:
In S310, the second unit block to be detected and the target reference image block are compared to generate second deviation characteristic information.
Specifically, the terminal device may compare the second unit block to be detected with the target reference image block to generate second deviation characteristic information, where the second deviation characteristic information is used to describe a second deviation degree between the second unit block to be detected and the target reference image block, referring to (a) in fig. 5, the terminal device may first compare the second unit block to be detected corresponding to the rectangle with the letter "a" with the reference image block corresponding to the rectangle with the letter "K", then compare the second unit block to be detected corresponding to the rectangle with the letter "B" with the reference image block corresponding to the rectangle with the letter "L", and so on until the second unit block to be detected corresponding to the rectangle with the letter "J" is compared with the reference image block corresponding to the rectangle with the letter "T", to generate ten pieces of second deviation characteristic information.
In S400, the first deviation characteristic information is input into a preset product quality characteristic value calculation formula, and a product quality characteristic value of the target workpiece is determined.
Specifically, after the terminal device generates the first deviation characteristic information, the terminal device can input the first deviation characteristic information into a preset product quality characteristic value calculation formula to determine a product quality characteristic value of the target workpiece, wherein the product quality characteristic value is used for quantifying the product quality of the target workpiece, so that a reference value capable of accurately quantifying the product quality of the target workpiece is provided for a user, and the user can find out a product quality problem in time.
In some possible implementations, referring to fig. 7, in order to accurately determine the product quality characteristic value, step S400 includes, but is not limited to, the following steps:
in S410, first area information corresponding to a to-be-detected trimming area in the second to-be-detected unit block is acquired.
Specifically, the terminal device may first obtain first area information corresponding to the to-be-detected cutting area in the second to-be-detected unit block, where the first area information is used to describe an area of the to-be-detected cutting area in the second to-be-detected unit block; for example, referring to fig. 8 (a), the area with the cross hatching indicates the area corresponding to the to-be-detected trimming area in the second to-be-detected unit block, and the terminal device may obtain the first area information corresponding to the to-be-detected trimming area in the second to-be-detected unit block by using a preset fan-shaped area calculation formula.
In S420, second area information corresponding to the reference trimming area in the target reference image block is acquired.
Specifically, after the terminal device acquires the first area information, the terminal device may acquire second area information corresponding to the reference trimming area in the target reference image block, the second area information being used to describe the area of the reference trimming area in the target reference image block; for example, referring to fig. 8 (b), the area with the cross hatching indicates an area corresponding to the reference trimming area in the target reference image block, and the terminal device may acquire the second area information corresponding to the reference trimming area in the target reference image block using a preset fan-shaped area calculation formula.
In S430, the first area information, the second area information, and the second deviation characteristic information are input into a preset product quality characteristic value calculation formula, and a product quality characteristic value of the target workpiece is determined.
Specifically, after the terminal device obtains the first area information, the second area information, and the second deviation characteristic information, the terminal device may input the first area information, the second area information, and the second deviation characteristic information into a preset product quality characteristic value calculation formula, and accurately determine a product quality characteristic value of the target workpiece.
In some possible implementations, in order to facilitate improvement of correlation and accuracy of the product quality characteristic values, the product quality characteristic value calculation formula may be:
，
in the method, in the process of the invention,representing a product quality characteristic value; />Representing a preset first weight factor of the vehicle,i.e. +.>The value of (a) is any real number (including 0.5 and 1) between 0.5 and 1. For example, referring to fig. 9, the second unit block to be detected in fig. 9 is the first unit block to be detected with the letter "D1" in fig. 6 (a), and the terminal device may compare the area of the cutting area to be detected and the area outside the cutting area to be detected in the second unit block to be detected, and if the area inside the area is smaller than the area outside the area, the terminal device may not be able to detect the cutting area>Can be 0.5, if the area in the region is larger than or equal to the area outside the region, the ratio of +.>1 may be taken.
In the method, in the process of the invention,representing first area information, i.e., the area within the region in fig. 9; />Representing a preset second weight factor, < ->I.e. +.>Is any real number (including 0.5 but not including 0) ranging from 0 to 0.5. For example, referring to fig. 10, the target reference image block in fig. 10 is the reference image block with letter "D2" in fig. 6 (b), and the terminal device may compare the area of the reference trimming area in the target reference image block with the area outside the reference trimming area, and if the area inside the area is smaller than the area outside the area, the area inside the area outside the reference trimming area is equal to >Can be 0.05, if the area in the region is larger than or equal to the area outside the region, the ratio of +.>0.5 may be taken.
In the method, in the process of the invention,representing second area information, i.e., the area within the region in fig. 10; />Indicating the number of times the difference between the first area information and the second area information is greater than or equal to a preset phase difference threshold. For example, referring to fig. 11 (a) and (b), there are eighteen second unit blocks to be detected in fig. 11 (a), and there are eighteen target reference image blocks corresponding to the second unit blocks to be detected in fig. 11 (b), respectively; at the positions "D3" and "E3" in fig. 11 (a), it is indicated that the frame film is deformed due to its elasticity during the cutting process, and then a cutting offset phenomenon occurs; the first area information corresponding to the second unit block to be detected with the letter "D3" in (a) of fig. 11 corresponds to the target reference image block with the letter "D4" in (b) of fig. 11The difference between the two area information is larger than the phase difference threshold, and the difference between the first area information corresponding to the second unit block to be detected with the letter "E3" in (a) of FIG. 11 and the second area information corresponding to the target reference image block with the letter "E4" in (b) of FIG. 11 is larger than the phase difference threshold, so ∈ - >The value of (2).
In the method, in the process of the invention,representing a preset hyperbolic cosine function, wherein the value range of the hyperbolic cosine function is 1 to plus infinity;indicating the number of times the difference between the first area information and the second area information is smaller than a preset phase difference threshold. For example, referring to fig. 11 (a), except "D3" and "E3", the difference between the first area information corresponding to the second unit block to be detected and the second area information of the corresponding target reference image block is smaller than the phase difference threshold, so->The value of (2) is 16.
In the method, in the process of the invention,representing a preset penalty factor,/->I.e. +.>The range of values of (a) is any real number between 0 and 2 (including 2 but not including 0). Exemplary, when->Is greater than->At the time of (a)>The value of (2) may be 0.02 whenLess than or equal to->At the time of (a)>The value of (2) may be 2./>The second deviation characteristic information is represented by a quotient of the first area information divided by the second area information, and for example, referring to fig. 9 and 10, the value of the second deviation characteristic information may be a quotient of an area of the second unit block to be detected having the letter "D1" divided by an area of the target reference image block having the letter "D2".
In S500, the product quality characteristic value is uploaded to a designated cloud server.
Specifically, after the terminal device determines a product quality characteristic value of a target workpiece, the terminal device may upload the product quality characteristic value to a specified cloud server; in another possible implementation manner, the terminal device may upload the plurality of product quality characteristic values to the designated cloud server after determining the product quality characteristic values of the plurality of target workpieces.
In some possible implementations, to facilitate the user to intuitively learn the product quality of the bezel film in combination with the product quality characteristic value, after step S400, the method further includes, but is not limited to, the following steps:
in S401, a product quality characteristic value is input into a preset workpiece state diagnosis formula, and quality state information of a target workpiece is determined.
Specifically, after the terminal device determines the product quality characteristic value of the target workpiece, the terminal device may input the product quality characteristic value into a preset workpiece state diagnosis formula, and determine quality state information of the target workpiece, where the quality state information is qualified information or unqualified information, and a user may intuitively learn the product quality of the frame film according to the quality state information.
In some possible implementations, to improve accuracy of the quality status information, the above-mentioned workpiece status diagnostic formula may be:
，
in the method, in the process of the invention,representing quality status information->Representing a product quality characteristic value; for example, for any one of the second unit blocks to be detected in any one of the cut areas to be detected in the target workpiece, for ease of understanding, this one second unit block to be detected is named a test unit block, when->Taking 0.5%>Take 10>Taking 0.5%>Get 3>Get 3>1.2%>Take 0.04%>At the time of taking the 27 f,is 286.364, ">In order to be unqualified, namely, the quality state information is unqualified information, a user can know that the quality of a product in a target workpiece is unqualified according to the unqualified information, and the position of a test unit block with the quality problem of the product in the target workpiece is known, so that the quality problem of the product is timely found, the reworking or destruction of the workpiece with the quality problem is facilitated in time, the condition that a production line directly executes subsequent processing on the workpiece with the serious quality problem is reduced, and the waste of production resources is reduced.
In some possible implementations, to further facilitate timely discovery of product quality problems, if the quality status information is failure information, the method further includes, but is not limited to, the following steps after step S401:
In S402, alarm information is generated from the reject information.
Specifically, the terminal device may generate alarm information for informing the user based on the reject information: the product quality of the target workpiece is not qualified.
Accordingly, step 500 includes, but is not limited to, the following steps
In S510, the product quality characteristic value and the alarm information are uploaded to a designated cloud server.
Specifically, after the terminal device generates the alert information, the terminal device may upload the product quality characteristic value and the alert information to a designated cloud server.
The implementation principle of the real-time detection method based on the cutting device in the embodiment of the application is as follows: the terminal equipment can firstly acquire a first to-be-detected image of the target workpiece, which comprises at least one to-be-detected cutting area, then divide the first to-be-detected image to generate a plurality of second to-be-detected images, then compare the to-be-detected cutting area in the second to-be-detected image with a reference cutting area in a preset reference image to generate first deviation characteristic information, then acquire first area information corresponding to the to-be-detected cutting area in the second to-be-detected image, acquire second area information corresponding to the reference cutting area in the reference image, input the first area information, the second area information and the first deviation characteristic information into a preset product quality characteristic value calculation formula to determine a product quality characteristic value of the target workpiece, and then upload the product quality characteristic value to a specified cloud server, so that a precise reference quantity related to the product quality of the target workpiece is provided for a user, and the user can find a product quality problem in time.
It should be noted that, the sequence number of each step in the above embodiment does not mean the sequence of execution sequence, and the execution sequence of each process should be determined by its function and internal logic, and should not limit the implementation process of the embodiment of the present application in any way.
The embodiment of the present application further provides a real-time detection system based on a cutting device, for convenience of explanation, only the part related to the present application is shown, as shown in fig. 12, the system 120 includes:
the first to-be-detected image acquisition module 121: the method comprises the steps of acquiring a first image to be detected of a target workpiece, wherein the target workpiece comprises at least one cutting area to be detected;
the second to-be-detected image generation module 122: the method comprises the steps of dividing a first image to be detected based on a cutting area to be detected, and generating a plurality of second images to be detected, wherein the second images to be detected correspond to the cutting area to be detected;
the first deviation characteristic information generating module 123: the method comprises the steps of comparing a second image to be detected with a preset reference image to generate first deviation characteristic information;
product quality characteristic value determination module 124: the method comprises the steps of inputting first deviation characteristic information into a preset product quality characteristic value calculation formula, and determining a product quality characteristic value of a target workpiece;
Product quality characteristic value uploading module 125: and uploading the product quality characteristic value to a designated cloud server.
Optionally, the system 120 further includes:
the edge point coordinate information acquisition module: for each second image to be detected, a crop area to be detected: acquiring edge point coordinate information of a cutting area to be detected, wherein the edge point coordinate information is used for describing coordinates of outline boundary points of the cutting area to be detected;
gridding dividing module: the method comprises the steps of respectively carrying out gridding division on a to-be-detected cutting area in a second to-be-detected image and a reference cutting area in a preset reference image to obtain a plurality of first to-be-detected unit blocks forming the to-be-detected cutting area and a plurality of reference image blocks forming the reference cutting area, wherein the to-be-detected unit blocks correspond to the reference image blocks one by one;
the second unit block to be detected is selected from the module: the method comprises the steps of selecting a first unit block to be detected containing edge point coordinate information as a second unit block to be detected based on a plurality of first unit blocks to be detected;
the target reference image block selection module: the method comprises the steps of selecting a reference image block corresponding to a second unit block to be detected as a target reference image block based on a plurality of reference image blocks;
Accordingly, the first deviation characteristic information generating module includes:
a second deviation characteristic information generation sub-module: and comparing the second unit block to be detected with the target reference image block to generate second deviation characteristic information, wherein the second deviation characteristic information is used for describing a second deviation degree between the second unit block to be detected and the target reference image block.
Optionally, the product quality characteristic value determining module 124 includes:
a first area information acquisition sub-module: the method comprises the steps of acquiring first area information corresponding to a cutting area to be detected in a second unit block to be detected;
a second area information acquisition sub-module: the method comprises the steps of acquiring second area information corresponding to a reference cutting area in a target reference image block;
product quality characteristic value determination submodule: the method comprises the steps of inputting first area information, second area information and second deviation characteristic information into a preset product quality characteristic value calculation formula to determine a product quality characteristic value of a target workpiece, wherein the product quality characteristic value calculation formula is as follows:
，
in the method, in the process of the invention,is the product quality characteristic value; />For a preset first weight factor, < ->；Is the first area information; />For a second weight factor, which is preset, +. >；/>Is the second area information; />The number of times that the difference between the first area information and the second area information is greater than or equal to a preset phase difference threshold; />For a preset penalty factor, < >>；/>For a preset doubleA curved cosine function; />The number of times that the difference between the first area information and the second area information is smaller than a preset phase difference threshold value; />The second deviation characteristic information has a value that is a quotient of the first area information divided by the second area information.
Optionally, the system 120 further includes:
the quality state information determining module: the quality state information of the target workpiece is determined by inputting the product quality characteristic value into a preset workpiece state diagnosis formula; the quality state information is qualified information or unqualified information, and the workpiece state diagnosis formula is as follows:
，
in the method, in the process of the invention,for quality status information->Is the product quality characteristic value.
Optionally, if the quality status information is failure information, the system 120 further includes:
an alarm information generation module: the alarm information is generated according to the unqualified information;
accordingly, the upload product quality characteristic value upload module 125 includes:
and a product quality characteristic value and alarm information uploading sub-module: and uploading the product quality characteristic value and the alarm information to a designated cloud server.
It should be noted that, because the content of information interaction and execution process between the modules and the embodiment of the method of the present application are based on the same concept, specific functions and technical effects thereof may be referred to in the method embodiment section, and details thereof are not repeated herein.
The embodiment of the present application further provides a terminal device, as shown in fig. 13, where the terminal device 130 of this embodiment includes: a processor 131, a memory 132, and a computer program 133 stored in the memory 132 and executable on the processor 131. The steps in the above-described flow processing method embodiment, such as steps S100 to S500 shown in fig. 1, are implemented when the processor 131 executes the computer program 133; alternatively, the processor 131, when executing the computer program 133, performs the functions of the modules in the above apparatus, for example, the functions of the modules 121 to 125 shown in fig. 12.
The terminal device 130 may be a desktop computer, a notebook computer, a palm computer, a cloud server, etc., and the terminal device 130 includes, but is not limited to, a processor 131 and a memory 132. It will be appreciated by those skilled in the art that fig. 13 is merely an example of terminal device 130 and is not limiting of terminal device 130, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., terminal device 130 may also include input-output devices, network access devices, buses, etc.
The processor 131 may be a central processing unit (Central Processing Unit, CPU), other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.; a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 132 may be an internal storage unit of the terminal device 130, for example, a hard disk or a memory of the terminal device 130, or the memory 132 may be an external storage device of the terminal device 130, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like provided on the terminal device 130; further, the memory 132 may also include both an internal storage unit and an external storage device of the terminal device 130, the memory 132 may also store the computer program 133 and other programs and data required by the terminal device 130, and the memory 132 may also be used to temporarily store data that has been output or is to be output.
An embodiment of the present application also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the various method embodiments described above. Wherein the computer program comprises computer program code, the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc.; the computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
The above embodiments are not intended to limit the scope of the present application, so: all equivalent changes in the method, principle and structure of the present application should be covered by the protection scope of the present application.
Claims (6)
1. A real-time detection method based on a cutting device, the method comprising:
acquiring a first image to be detected of a target workpiece, wherein the target workpiece comprises at least one cutting area to be detected;
Dividing the first to-be-detected image based on the to-be-detected cutting area to generate a plurality of second to-be-detected images, wherein the second to-be-detected images comprise the to-be-detected cutting area, and the second to-be-detected images correspond to the to-be-detected cutting areas one by one;
comparing the to-be-detected cutting area in the second to-be-detected image with a reference cutting area in a preset reference image to generate first deviation characteristic information, wherein the first deviation characteristic information is used for describing a first deviation degree between the to-be-detected cutting area and the reference cutting area;
inputting the first deviation characteristic information into a preset product quality characteristic value calculation formula, and determining a product quality characteristic value of the target workpiece;
uploading the product quality characteristic value to a designated cloud server;
before comparing the to-be-detected trimming area in the second to-be-detected image with a reference trimming area in a preset reference image to generate first deviation characteristic information, the method comprises:
for the to-be-detected trimming area in each of the second to-be-detected images:
acquiring edge point coordinate information of the cutting area to be detected, wherein the edge point coordinate information is used for describing coordinates of outline boundary points of the cutting area to be detected;
Respectively carrying out gridding division on the to-be-detected cutting area in the second to-be-detected image and a reference cutting area in a preset reference image to obtain a plurality of first to-be-detected unit blocks forming the to-be-detected cutting area and a plurality of reference image blocks forming the reference cutting area, wherein the to-be-detected unit blocks correspond to the reference image blocks one by one;
selecting a first unit block to be detected containing the edge point coordinate information as a second unit block to be detected based on the plurality of first unit blocks to be detected;
selecting a reference image block corresponding to the second unit block to be detected as a target reference image block based on the plurality of reference image blocks;
correspondingly, the comparing the to-be-detected cutting area in the second to-be-detected image with a reference cutting area in a preset reference image to generate first deviation characteristic information includes:
comparing the second unit block to be detected with the target reference image block to generate second deviation characteristic information, wherein the second deviation characteristic information is used for describing a second deviation degree between the second unit block to be detected and the target reference image block;
The step of inputting the first deviation characteristic information into a preset product quality characteristic value calculation formula to determine the product quality characteristic value of the target workpiece comprises the following steps:
acquiring first area information corresponding to the cutting area to be detected in the second unit block to be detected;
acquiring second area information corresponding to a reference cutting area in the target reference image block;
inputting the first area information, the second area information and the second deviation characteristic information into a preset product quality characteristic value calculation formula to determine a product quality characteristic value of the target workpiece, wherein the product quality characteristic value calculation formula is as follows:
，
in the method, in the process of the invention,is the product quality characteristic value; />For a preset first weight factor, < ->；Is the first area information; />For a second weight factor, which is preset, +.>；/>For the second area information; />The number of times that the difference between the first area information and the second area information is greater than or equal to a preset phase difference threshold; />For a preset penalty factor, < >>；/>Is a preset hyperbolic cosine function;times when the difference between the first area information and the second area information is smaller than a preset phase difference threshold value; The second deviation characteristic information has a value that is a quotient of the first area information divided by the second area information.
2. The method according to claim 1, wherein after determining the product quality characteristic value of the target workpiece in the input of the first deviation characteristic information to a preset product quality characteristic value calculation formula, the method further comprises:
inputting the product quality characteristic value into a preset workpiece state diagnosis formula, and determining the quality state information of the target workpiece; wherein the quality state information is qualified information or unqualified information, and the workpiece state diagnosis formula is as follows:
，
in the method, in the process of the invention,for quality status information->Is the product quality characteristic value.
3. The method of claim 2, wherein if the quality status information is reject information, after the inputting the product quality characteristic value to a predetermined workpiece status diagnostic formula, the method further comprises:
generating alarm information according to the unqualified information;
correspondingly, the uploading the product quality characteristic value to a designated cloud server includes:
And uploading the product quality characteristic value and the alarm information to a designated cloud server.
4. A real-time detection system based on a cutting device, the system comprising:
the first image acquisition module to be detected: the method comprises the steps of acquiring a first to-be-detected image of a target workpiece, wherein the target workpiece comprises at least one to-be-detected cutting area;
the second image generation module to be detected: the method comprises the steps of dividing the first to-be-detected image based on the to-be-detected cutting area to generate a plurality of second to-be-detected images, wherein the second to-be-detected images correspond to the to-be-detected cutting area;
a first deviation characteristic information generation module: the method comprises the steps of comparing the second image to be detected with a preset reference image to generate first deviation characteristic information;
the product quality characteristic value determining module: the first deviation characteristic information is input into a preset product quality characteristic value calculation formula, and the product quality characteristic value of the target workpiece is determined;
and a product quality characteristic value uploading module: the cloud server is used for uploading the product quality characteristic value to a designated cloud server;
the system comprises:
the edge point coordinate information acquisition module: for each of the second to-be-detected image, the to-be-detected trimming area: acquiring edge point coordinate information of the cutting area to be detected, wherein the edge point coordinate information is used for describing coordinates of outline boundary points of the cutting area to be detected;
Gridding dividing module: the method comprises the steps of respectively carrying out gridding division on the to-be-detected cutting area in the second to-be-detected image and a reference cutting area in a preset reference image to obtain a plurality of first to-be-detected unit blocks forming the to-be-detected cutting area and a plurality of reference image blocks forming the reference cutting area, wherein the to-be-detected unit blocks correspond to the reference image blocks one by one;
the second unit block to be detected is selected from the module: the method comprises the steps of selecting a first unit block to be detected containing the edge point coordinate information as a second unit block to be detected based on the plurality of first unit blocks to be detected;
the target reference image block selection module: the method comprises the steps of selecting a reference image block corresponding to a second unit block to be detected as a target reference image block based on the plurality of reference image blocks;
accordingly, the first deviation characteristic information generating module includes:
a second deviation characteristic information generation sub-module: the method comprises the steps of comparing the second unit block to be detected with the target reference image block to generate second deviation characteristic information, wherein the second deviation characteristic information is used for describing a second deviation degree between the second unit block to be detected and the target reference image block;
The product quality characteristic value determining module comprises:
a first area information acquisition sub-module: the first area information corresponding to the cutting area to be detected in the second unit block to be detected is obtained;
a second area information acquisition sub-module: the second area information corresponding to the reference cutting area in the target reference image block is acquired;
product quality characteristic value determination submodule: the method comprises the steps of inputting the first area information, the second area information and the second deviation characteristic information into a preset product quality characteristic value calculation formula to determine a product quality characteristic value of the target workpiece, wherein the product quality characteristic value calculation formula is as follows:
，
in the method, in the process of the invention,is the product quality characteristic value; />For a preset first weight factor, < ->；Is the first area information; />For a second weight factor, which is preset, +.>；/>For the second area information; />For the difference between the first area information and the second area information to be greater than or equal to a preset phase differenceA threshold number of times; />For a preset penalty factor, < >>；/>Is a preset hyperbolic cosine function;times when the difference between the first area information and the second area information is smaller than a preset phase difference threshold value; The second deviation characteristic information has a value that is a quotient of the first area information divided by the second area information.
5. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 3 when the computer program is executed.
6. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310625249.0A CN116342609B (en) | 2023-05-30 | 2023-05-30 | Real-time detection method, system and storage medium based on cutting device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310625249.0A CN116342609B (en) | 2023-05-30 | 2023-05-30 | Real-time detection method, system and storage medium based on cutting device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116342609A CN116342609A (en) | 2023-06-27 |
| CN116342609B true CN116342609B (en) | 2023-08-15 |
Family
ID=86882697
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310625249.0A Active CN116342609B (en) | 2023-05-30 | 2023-05-30 | Real-time detection method, system and storage medium based on cutting device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116342609B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116625243B (en) * | 2023-07-26 | 2023-09-19 | 湖南隆深氢能科技有限公司 | Intelligent detection method, system and storage medium based on frame coil stock cutting machine |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| BE678421A (en) * | 1966-03-24 | 1966-05-31 | Cockerill | |
| DE2729509A1 (en) * | 1976-07-09 | 1978-01-12 | Hughes Aircraft Co | DEVICE FOR GENERATING CHARACTERISTIC SIGNALS FOR CROSS STRIPS OF A MATERIAL TRAIL |
| EP1477297A2 (en) * | 2003-05-16 | 2004-11-17 | Bobst S.A. | Method for controlling the quality of flat articles and apparatus for carrying out said method |
| CN102897582A (en) * | 2012-11-07 | 2013-01-30 | 江苏嘉盛光伏科技有限公司 | Automatic cutting machine for producing solar battery element |
| CN106064400A (en) * | 2016-07-18 | 2016-11-02 | 湖北玉立砂带集团股份有限公司 | A kind of adjustable flexibility plate step cut device |
| CN107009407A (en) * | 2017-05-23 | 2017-08-04 | 浙江久石工研建材科技有限公司 | Guillotine and cut-off control |
| CN107719803A (en) * | 2017-11-13 | 2018-02-23 | 陈炜广 | A kind of cell-shell cutting mechanism of paper-plastic packing machine |
| JP2019022956A (en) * | 2017-07-24 | 2019-02-14 | コニカミノルタ株式会社 | Image forming system, image forming method ans image forming device |
| CN112621863A (en) * | 2021-01-18 | 2021-04-09 | 天津大学 | Automatic cutting system |
| CN113414819A (en) * | 2021-08-24 | 2021-09-21 | 航天云网数据研究院(广东)有限公司 | Substrate material processing method and system, electronic device and storage medium |
| JP2021169192A (en) * | 2020-04-17 | 2021-10-28 | コニカミノルタ株式会社 | Image formation device, image formation system, control method and program |
| CN215816057U (en) * | 2021-07-14 | 2022-02-11 | 恒大新能源技术(深圳)有限公司 | Packaging film cutting mechanism and packaging device |
| CN216271399U (en) * | 2021-10-28 | 2022-04-12 | 广东利元亨智能装备股份有限公司 | Conveying device and cutting equipment |
| CN218395737U (en) * | 2022-10-12 | 2023-01-31 | 常州华数锦明智能装备技术研究院有限公司 | Servo utmost point ear cutting device |
| CN115829906A (en) * | 2022-04-18 | 2023-03-21 | 宁德时代新能源科技股份有限公司 | Method, device and system for detecting defects of cathode pole piece of composite material belt |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109366567A (en) * | 2018-11-30 | 2019-02-22 | 广州市普理司科技有限公司 | Automatic product examine machine and its control method |
| US11461992B2 (en) * | 2020-11-12 | 2022-10-04 | Samsung Electronics Co., Ltd. | Region of interest selection for object detection |
-
2023
- 2023-05-30 CN CN202310625249.0A patent/CN116342609B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| BE678421A (en) * | 1966-03-24 | 1966-05-31 | Cockerill | |
| DE2729509A1 (en) * | 1976-07-09 | 1978-01-12 | Hughes Aircraft Co | DEVICE FOR GENERATING CHARACTERISTIC SIGNALS FOR CROSS STRIPS OF A MATERIAL TRAIL |
| EP1477297A2 (en) * | 2003-05-16 | 2004-11-17 | Bobst S.A. | Method for controlling the quality of flat articles and apparatus for carrying out said method |
| CN102897582A (en) * | 2012-11-07 | 2013-01-30 | 江苏嘉盛光伏科技有限公司 | Automatic cutting machine for producing solar battery element |
| CN106064400A (en) * | 2016-07-18 | 2016-11-02 | 湖北玉立砂带集团股份有限公司 | A kind of adjustable flexibility plate step cut device |
| CN107009407A (en) * | 2017-05-23 | 2017-08-04 | 浙江久石工研建材科技有限公司 | Guillotine and cut-off control |
| JP2019022956A (en) * | 2017-07-24 | 2019-02-14 | コニカミノルタ株式会社 | Image forming system, image forming method ans image forming device |
| CN107719803A (en) * | 2017-11-13 | 2018-02-23 | 陈炜广 | A kind of cell-shell cutting mechanism of paper-plastic packing machine |
| JP2021169192A (en) * | 2020-04-17 | 2021-10-28 | コニカミノルタ株式会社 | Image formation device, image formation system, control method and program |
| CN112621863A (en) * | 2021-01-18 | 2021-04-09 | 天津大学 | Automatic cutting system |
| CN215816057U (en) * | 2021-07-14 | 2022-02-11 | 恒大新能源技术(深圳)有限公司 | Packaging film cutting mechanism and packaging device |
| CN113414819A (en) * | 2021-08-24 | 2021-09-21 | 航天云网数据研究院(广东)有限公司 | Substrate material processing method and system, electronic device and storage medium |
| CN216271399U (en) * | 2021-10-28 | 2022-04-12 | 广东利元亨智能装备股份有限公司 | Conveying device and cutting equipment |
| CN115829906A (en) * | 2022-04-18 | 2023-03-21 | 宁德时代新能源科技股份有限公司 | Method, device and system for detecting defects of cathode pole piece of composite material belt |
| CN218395737U (en) * | 2022-10-12 | 2023-01-31 | 常州华数锦明智能装备技术研究院有限公司 | Servo utmost point ear cutting device |
Non-Patent Citations (1)
| Title |
|---|
| 李光明等.基于机器视觉的自动裁切机精定位算法研究.《机电工程》.2019,第36卷(第02期),全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116342609A (en) | 2023-06-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116342609B (en) | Real-time detection method, system and storage medium based on cutting device | |
| CN109697468B (en) | Sample image labeling method and device and storage medium | |
| CN111323751B (en) | Sound source positioning method, device and storage medium | |
| CN116523908B (en) | Safe production method, system, equipment and medium based on coil coating production line | |
| CN110632582A (en) | Sound source positioning method, device and storage medium | |
| CN109871941B (en) | Data processing method and device and related products | |
| CN116168041B (en) | Real-time detection method and system applied to laminating device | |
| CN110910375A (en) | Detection model training method, device, equipment and medium based on semi-supervised learning | |
| CN114170303A (en) | Combined calibration method, device, system, equipment and medium for radar and camera | |
| CN115937167A (en) | Method and device for detecting defects of battery pole piece ceramic and electronic equipment | |
| CN116379927B (en) | Accurate detection method and system applied to laminating production line and storage medium | |
| CN116901170A (en) | Intelligent control method, system, terminal and medium based on CCM coiled material slitting machine | |
| CN109613577B (en) | Position determination method, device, terminal equipment and storage medium | |
| CN111985439A (en) | Face detection method, device, equipment and storage medium | |
| US20230401670A1 (en) | Multi-scale autoencoder generation method, electronic device and readable storage medium | |
| CN114549429B (en) | Depth data quality evaluation method and device based on hypergraph structure | |
| CN113420604B (en) | Multi-person posture estimation method and device and electronic equipment | |
| CN116625243B (en) | Intelligent detection method, system and storage medium based on frame coil stock cutting machine | |
| CN114519520A (en) | Model evaluation method, model evaluation device and storage medium | |
| CN111709955A (en) | Image segmentation inspection method, device, terminal and storage medium | |
| CN116700196B (en) | Real-time control method, system, terminal equipment and medium for GDL sintering production line | |
| CN116883398B (en) | Detection method, system, terminal equipment and medium based on galvanic pile assembly production line | |
| CN117351180B (en) | Modular building augmented reality auxiliary construction method and device based on deep learning | |
| CN110068575B (en) | Judging method and device for multiphase mixing uniformity and terminal | |
| US20240203091A1 (en) | External parameter determination method and image processing device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |