PE film packaging machine film abnormity online identification method and system

Abstract

The invention relates to the technical field of film recognition, in particular to a PE film packaging machine film abnormity online recognition method and system, and the method comprises the following steps: collecting image data of a to-be-packaged film, recognizing whether bubble features exist in the to-be-packaged film image, and extracting bubble feature data; performing region division on the image data of the to-be-packaged film, determining bubble distribution data and area size of each region, and outputting to obtain a quality coefficient of each line of the film; qualitatively analyzing the quality of each line of the to-be-packaged film to obtain a signal whether the quality of each line of the to-be-packaged film is qualified or not; based on the determined signal whether the quality of each row of the film to be packaged is qualified or not, the whole film to be packaged is evaluated, and a corresponding identification instruction is generated according to an evaluation result; the recognition speed of the PE packaging machine is controlled; according to the method, the region of the to-be-packaged PE film is qualitatively and quantitatively recognized integrally, the recognition speed of the PE film is adjusted and controlled adaptively according to the recognition result, and the recognition efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of film recognition, and in particular to a method and system for online recognition of film abnormality of a PE film packaging machine. Background Art

[0002] PE film cloth packaging machine is a mechanical equipment specially used for cloth packaging. It uses PE (polyethylene) film as packaging material. Through automatic or manual operation, the cloth is wrapped and heat-sealed to achieve the purpose of protection, fixation and beauty.

[0003] In order to package cloth products with higher quality, it is necessary to set a camera at the loading point of the PE film packaging machine to identify the quality of the PE film waiting for packaging and determine whether it meets the packaging requirements. However, in the current PE film identification process, it is only possible to determine whether the PE film has some defects that affect the cloth packaging, such as bubbles. Therefore, if bubbles appear on the PE film, it will have a great impact on the use of the cloth products during subsequent cloth packaging. Therefore, how to qualitatively identify the quality of the PE film to be packaged is the key to improving the PE film packaging effect. How to regulate the PE film packaging efficiency based on the stability of PE film identification is the key to the current PE film packaging machine film abnormality online identification technology. Summary of the invention

[0004] The object of the present invention is to provide a method and system for online identification of film anomalies of a PE film packaging machine, so as to solve at least one of the above-mentioned problems of the prior art.

[0005] In a first aspect, the present invention provides a method for online identification of film abnormality of a PE film packaging machine, comprising the following steps: An industrial camera is set on the PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; The image data of the packaging film is divided into regions, and the bubble distribution data and area size of each region are determined according to the bubble characteristic data, and the quality coefficient of each row of the film is output; According to the quality coefficient of each row of the film, the quality of each row of the film to be packaged is qualitatively analyzed to obtain a signal of whether the quality of each row of the film to be packaged is qualified; then based on the determined signal of whether the quality of each row of the film to be packaged is qualified, the film to be packaged is evaluated as a whole, and a corresponding recognition instruction is generated according to the evaluation result; According to the generated recognition instructions, the recognition speed of the PE packaging machine is controlled.

[0006] In a second aspect, a PE film packaging machine film abnormality online identification system, the system comprising: Image acquisition module: an industrial camera is set on the PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; Identification and analysis module: divides the image data of the packaging film into regions, determines the bubble distribution data and area size of each region according to the bubble feature data, and outputs the quality coefficient of each row of the film; Quality identification module: According to the quality coefficient of each line of the film, the quality of each line of the film to be packaged is qualitatively analyzed to obtain a signal of whether the quality of each line of the film to be packaged is qualified; then based on the determined signal of whether the quality of each line of the film to be packaged is qualified, the film to be packaged is evaluated as a whole, and the corresponding identification instructions are generated according to the evaluation results; Identification control module: controls the identification speed of the PE packaging machine according to the generated identification instructions.

[0007] Beneficial effects of the present invention: The present invention performs image processing on the film to be packaged, specifically, identifies the bubbles in the film to be packaged, because the bubbles appearing in the packaging film will have a great impact on the packaged products; according to the distribution position and area size of the bubbles in each row of the film to be packaged, the quality of each row of the film is qualitatively identified, and then based on the quality of each row of the film, the film is identified as a whole; then, based on the preliminary identification, fluctuation identification is performed according to the uniformity of the quality of each row of the film to identify the uniformity of the film; finally, according to the uniformity result identified, if the quality of the film to be packaged is good and uniform, the feed speed can be adaptively regulated, thereby improving the efficiency of PE film identification; therefore, the present invention realizes qualitative and quantitative identification of the region and the whole of the PE film to be packaged, and according to the identification result, the PE film identification speed is adaptively regulated, effectively improving the identification efficiency, so that when the cloth is packaged, the PE film to be packaged is identified online, and according to the identification result, the rhythm of cloth packaging is reasonably and effectively controlled. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 This is a flow chart of a method for online identification of film abnormality of a PE film packaging machine provided in Example 1 of the present invention; Figure 2 It is a structural schematic diagram of an online identification system for film anomalies of a PE film packaging machine provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0010] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0011] Embodiment 1 Figure 1 A flowchart of a method for online identification of film anomalies of a PE film packaging machine provided in the first embodiment of the present invention, the embodiment of the present invention can be applied to the case where a PE film cloth packaging machine is used for packaging, the method for online identification of film anomalies of a PE film packaging machine can be performed by an online identification system for film anomalies of a PE film packaging machine, the online identification system for film anomalies of a PE film packaging machine can be implemented by software and / or hardware, and the online identification system for film anomalies of a PE film packaging machine can be configured in an online identification device for film anomalies of a PE film packaging machine. Optionally, an online identification device for film anomalies of a PE film packaging machine can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc., and the embodiment of the present invention does not limit this.

[0012] like Figure 1 As shown, an embodiment of the present invention provides a method for online identification of film abnormalities of a PE film packaging machine, which specifically includes the following steps: S1. An industrial camera is set on a PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; In some embodiments, an industrial camera is provided at the feeding port of the PE film packaging machine, and the image data of the PE film to be packaged is collected by using the image acquisition principle of the industrial camera; the collected image data of the film to be packaged is preprocessed and segmented by using an image segmentation algorithm based on deep learning, and the packaging interference area in the image is extracted; according to the characteristics of the packaging interference area, an image recognition model such as a convolutional neural network is used to determine whether it belongs to the bubble type, and extract bubble feature data, including the area size of the bubble; Specifically, industrial cameras use the linear scanning principle of charge-coupled devices (CCDs) to obtain digital images through digital scanners. They are generally composed of light sources, optical lenses, scanning modules, and analog-to-digital conversion circuits. The core is the use of charge-coupled devices for photoelectric conversion. The principle is that the light emitted by the light source shines on the scene printed circuit board and moves along the y-axis direction. After reflection, it passes through a very narrow gap to form a light band along the x-axis direction. The light band shines on the CCD, and the light intensity signal is converted into an analog voltage signal. After the analog-to-digital conversion, it is input into the electronic equipment for processing; S2. Divide the image data of the packaging film into regions to obtain i*j number of regions. According to the bubble characteristic data, determine the bubble distribution data and area size of each region, and output the quality coefficient Qm of each row of the film. i ; In some embodiments, the image data of the packaging film is divided into regions to obtain a rectangular region of the i-th row and the j-th column, wherein preferably, the value of j is an odd number; First, a two-step method is used to identify the rectangular area. In the first step, whether there is a bubble feature in the rectangular area is identified. In the second step, if there is a bubble feature in the rectangular area, the bubble area corresponding to the rectangular area is identified. Then through the formula , the mass coefficient Qm of each row of the membrane is calculated i ; Where n=1,2,...,j, j is the number of rectangular areas in each row, X n is the packaging impact factor of the nth rectangular area, S n is the bubble area in the nth rectangular area; Specifically, the packaging impact factor X of the nth rectangular area n The acquisition process is: If there is a bubble feature in the nth rectangular area, mark the nth rectangular area as a bubble defect area, and use the formula , calculate the packaging impact factor X of the nth rectangular area n ;in, is a rectangular area in the middle of the row in the image data of the film to be packaged; What needs to be explained is: the packaging impact factor X of the nth rectangular area n It indicates the distance between the bubble area and the center of the film to be packaged. Because the closer the bubble is to the center of the film to be packaged, the bubble area will appear in the center of the package when the PE film passes through the packaging machine. On the contrary, the farther the bubble is from the center of the film to be packaged, the bubble area will appear in the side wall area of ​​the package when the PE film passes through the packaging machine, resulting in different degrees of impact on the packaged product. Membrane quality coefficient per row Qmi It indicates: the distribution position and area size of bubbles in each row of the film to be packaged. The larger the quality coefficient Qmi of each row of the film, the more effective it is that the quality of the row of the film to be packaged is poor, which affects the quality of subsequent packaging after molding. S3, according to the quality coefficient Qm of each row of the membrane i , qualitatively analyze the quality of each row of the film to be packaged, and obtain a signal of whether the quality of each row of the film to be packaged is qualified; then, based on the determined signal of whether the quality of each row of the film to be packaged is qualified, evaluate the film to be packaged as a whole, and generate corresponding recognition instructions according to the evaluation results; In some embodiments, the quality coefficient Qm of each row of the membrane is obtained i , the mass coefficient of each row of the membrane is Qm i , compared with the quality coefficient threshold of each row of the membrane; If the mass coefficient of each row of the membrane is Qm i When it is greater than or equal to the quality coefficient threshold of each row of the film, a signal indicating that the quality of the row of the film to be packaged is unqualified is generated; If the mass coefficient of each row of the membrane is Qm i When it is less than the quality coefficient threshold of each row of the film, a signal indicating that the row of the film to be packaged is of qualified quality is generated; Extract the signal features of the mass of each row of the film to be packaged, and construct a signal feature data set {A1, A2, ..., A i}, where A i The value is 1 or 0, 1 indicates that the quality of the line of film to be packaged is qualified, and 0 indicates that the quality of the line of film to be packaged is unqualified; By formula , calculate and obtain the overall evaluation coefficient XT of the film to be packaged; Where m=1,2,...,i, i is the number of rows of image data, A m The signal characteristics representing the quality of each row of the mth row of films to be packaged; If the overall evaluation coefficient XT of the film to be packaged is equal to 1, it means that the overall quality of the film to be packaged is qualified, and a first recognition instruction is generated; If the overall evaluation coefficient XT of the film to be packaged is equal to 0, it means that there are some areas of unqualified quality in the overall area of ​​the film to be packaged, and a second recognition instruction is generated; S4. According to the generated recognition instruction, the PE film packaging machine executes the corresponding operation instruction; In some embodiments, when the second recognition instruction is obtained, the PE film transmission mechanism on the PE film packaging machine is controlled to stop working, and personnel are arranged to cut the area generating the signal of unqualified quality of the row of the film to be packaged; When the first recognition instruction is obtained, the quality coefficient Qm of each row of the film is obtained. i , the mass coefficient Qm of each row of all membranes under the row number iThe sequence composed of the above mentioned is recorded as the film row number mass coefficient sequence, and the least square method is used to perform curve fitting on the film row number mass coefficient sequence to obtain the mass curve; and each extreme value point on the mass curve is obtained; Calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the previous membrane, recorded as the first difference; calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the next membrane, recorded as the second difference; calculate the sum of the first difference and the second difference, recorded as the first difference amplitude of the mass corresponding to each extreme pointDone a ; Calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the membrane at the previous extreme point, which is recorded as the third difference; calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the membrane at the next extreme point, which is recorded as the fourth difference; calculate the sum of the third difference and the fourth difference, which is recorded as the second difference amplitude Dtwo corresponding to each extreme point a ; By formula , calculate the stability coefficient XW of the film to be packaged; Among them, b=1,2,...,a, a is the number of extreme points on the quality curve, α and β are the first difference amplitude of quality corresponding to each extreme point, Done a The second difference amplitude Dtwo corresponding to each extreme point a The weight ratio coefficient of α is 0.38 and β is 0.62; comparing the stability coefficient of the film to be packaged with a threshold value of the stability coefficient of the film to be packaged; If the stability coefficient of the film to be packaged is greater than or equal to the stability coefficient threshold of the film to be packaged, a uniform quality signal of the film to be packaged is generated; when the uniform quality signal of the film to be packaged is obtained, an identification speed control operation instruction can be generated; If the stability coefficient of the film to be packaged is less than the stability coefficient threshold of the film to be packaged, a signal of uneven quality of the film to be packaged is generated; when a signal of uniform quality of the film to be packaged is obtained, an identification speed maintenance operation instruction can be generated; It should be explained that: the uniform quality signal of the film to be packaged indicates that the quality of the film to be packaged is uniform between the rows through the current graphic analysis, and the non-uniform quality signal of the film to be packaged indicates that the quality of the film to be packaged is non-uniform between the rows through the current graphic analysis, with some fluctuations; S5. Control the recognition speed of the PE packaging machine according to the generated operation instructions; In some embodiments, when the recognition speed maintenance operation instruction is obtained, the current feeding speed of the PE film to the PE packaging machine is maintained unchanged; When the speed control operation instruction is obtained, the formula , the feeding control speed VT of the PE film to the PE packaging machine is calculated; Wherein, b=1,2,...,a, a is the number of extreme points on the quality curve, VD represents the current feeding speed of PE film to the PE packaging machine, QBm represents the quality coefficient threshold of each line of film, Qmmax represents the maximum quality coefficient of each line of film among the extreme points, Qm a It represents the quality coefficient of each row of the membrane corresponding to each extreme point; It needs to be explained that: the feeding speed of the PE film to the PE packaging machine is increased by the proportion of the distance between the maximum film quality coefficient of each row and the threshold value in the distance between the film quality coefficient of each row and the threshold value at all extreme points, thereby achieving the speed of online recognition of the PE film; The technical solution of the embodiment of the present invention is as follows: an industrial camera is arranged on a PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; the image data of the film to be packaged is divided into regions to obtain i*j number of regions, and the bubble distribution data and area size of each region are determined according to the bubble feature data, and the quality coefficient Qm of each row of the film is outputted. i ; According to the quality coefficient Qm of each row of the membrane i , qualitatively analyze the quality of each row of the film to be packaged, and obtain a signal of whether the quality of each row of the film to be packaged is qualified; then, based on the determined signal of whether the quality of each row of the film to be packaged is qualified, evaluate the entire film to be packaged, and generate corresponding recognition instructions according to the evaluation results; according to the generated recognition instructions, the PE film packaging machine executes corresponding operation instructions; according to the generated operation instructions, the PE packaging machine is controlled to complete the corresponding recognition speed; the present invention performs image processing on the film to be packaged, specifically, identifies the bubbles in the film to be packaged, because the appearance of bubbles in the packaging film will have a greater impact on the packaged product; according to the distribution position and area size of the bubbles in each row of the film to be packaged, the quality of each row of the film is qualitatively identified. , and then based on the quality of each row of film, the film is identified as a whole; then, based on the preliminary identification, fluctuation identification is performed according to the uniformity of the quality of each row of the film to identify the uniformity of the film; finally, based on the identified uniformity result, if the quality of the film to be packaged is good and uniform, the feed speed can be adaptively regulated to improve the efficiency of PE film identification; therefore, the present invention realizes qualitative and quantitative identification of the region and the whole of the PE film to be packaged, and according to the identification result, the PE film identification speed is adaptively regulated to effectively improve the identification efficiency, so that when the cloth is packaged, the PE film to be packaged is identified online, and according to the identification result, the rhythm of cloth packaging is reasonably and effectively controlled.

[0013] Embodiment 2 like Figure 2 As shown, an embodiment of the present invention provides an online recognition system for film abnormality of a PE film packaging machine, the system comprising: Image acquisition module: an industrial camera is set on the PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; Identification and analysis module: divides the image data of the packaging film into regions, determines the bubble distribution data and area size of each region according to the bubble feature data, and outputs the quality coefficient of each row of the film; Quality identification module: according to the quality coefficient Qm of each row of the membrane i , qualitatively analyze the quality of each row of the film to be packaged, and obtain a signal of whether the quality of each row of the film to be packaged is qualified; then, based on the determined signal of whether the quality of each row of the film to be packaged is qualified, evaluate the film to be packaged as a whole, and generate corresponding recognition instructions according to the evaluation results; Identification control module: controls the identification speed of the PE packaging machine according to the generated identification instructions.

[0014] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for online identification of film abnormality of a PE film packaging machine, characterized in that: The following steps are involved: An industrial camera is set on the PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; The image data of the packaging film is divided into regions, and the bubble distribution data and area size of each region are determined according to the bubble characteristic data, and the quality coefficient of each row of the film is output; According to the quality coefficient of each row of the film, the quality of each row of the film to be packaged is qualitatively analyzed to obtain a signal of whether the quality of each row of the film to be packaged is qualified; Then, based on the determined quality signal of each row of the film to be packaged, the film to be packaged is evaluated as a whole, and corresponding identification instructions are generated according to the evaluation results; According to the generated recognition instructions, the recognition speed of the PE packaging machine is controlled.

2. The method for online identification of film abnormality of a PE film packaging machine according to claim 1 is characterized in that: The process of determining the mass coefficient of each row of the membrane is: By formula , calculate the mass coefficient Qm of each row of the membrane i ; Where n=1,2,...,j, j is the number of rectangular areas in each row, X n is the packaging impact factor of the nth rectangular area, S n is the bubble area in the nth rectangular area.

3. The method for online identification of film abnormality of a PE film packaging machine according to claim 2 is characterized in that: The packaging impact factor X of the nth rectangular area n The acquisition process is: If there is a bubble feature in the nth rectangular area, mark the nth rectangular area as a bubble defect area, and use the formula , calculate the packaging impact factor X of the nth rectangular area n ;in, It is a rectangular area located in the middle of the row in the image data of the film to be packaged.

4. The method for online identification of film abnormality of a PE film packaging machine according to claim 1, characterized in that: The process of qualitatively analyzing the quality of each row of packaging film is as follows: If the mass coefficient of each row of the membrane is Qm i When it is greater than or equal to the quality coefficient threshold of each row of the film, a signal indicating that the quality of the row of the film to be packaged is unqualified is generated; If the mass coefficient of each row of the membrane is Qm i When it is less than the quality coefficient threshold of each row of the film, a signal indicating that the row of the film to be packaged is of qualified quality is generated.

5. The method for online identification of film abnormality of a PE film packaging machine according to claim 1, characterized in that: The process of evaluating the packaging film as a whole is as follows: Extract the signal features of the mass of each row of the film to be packaged, and construct a signal feature data set {A1, A2, ..., A i }, where A i The value is 1 or 0; By formula , calculate and obtain the overall evaluation coefficient XT of the film to be packaged; Where m=1,2,...,i, i is the number of rows of image data, A m The signal characteristics representing the quality of each row of the mth row of the film to be packaged; 1 represents a signal indicating that the quality of the row of the film to be packaged is qualified, and 0 represents a signal indicating that the quality of the row of the film to be packaged is unqualified; If the overall evaluation coefficient XT of the film to be packaged is equal to 1, it means that the overall quality of the film to be packaged is qualified, and a first recognition instruction is generated.

6. The method for online identification of film abnormality of a PE film packaging machine according to claim 5, characterized in that: The process of the PE film packaging machine executing the corresponding operating instructions is: When the first recognition instruction is obtained, the quality coefficient Qm of each row of all films under the row number is i Perform curve fitting on the composed sequence to obtain a quality curve; obtain each extreme value point on the quality curve; By formula , calculate the stability coefficient XW of the film to be packaged; Among them, b=1,2,...,a, a is the number of extreme points on the quality curve, α and β are the first difference amplitude of quality corresponding to each extreme point, Done a The second difference amplitude Dtwo corresponding to each extreme point a The weight ratio coefficient of If the stability coefficient of the film to be packaged is greater than or equal to the stability coefficient threshold of the film to be packaged, a uniform quality signal of the film to be packaged is generated; when the uniform quality signal of the film to be packaged is obtained, an identification speed control operation instruction is generated.

7. The method for online identification of film abnormality of a PE film packaging machine according to claim 6, characterized in that: The first difference amplitude of the quality corresponding to each extreme point is Done a How to obtain: Calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the previous membrane, which is recorded as the first difference; calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the next membrane, which is recorded as the second difference; Calculate the sum of the first difference and the second difference, and record it as the first difference amplitude of the quality corresponding to each extreme point. a .

8. The method for online identification of film abnormality of a PE film packaging machine according to claim 7, characterized in that: The second difference amplitude Dtwo of the quality corresponding to each extreme point a How to obtain: Calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the membrane at the previous extreme point, which is recorded as the third difference; calculate the difference between the mass coefficient of each row of the membrane corresponding to each extreme point in the membrane row mass coefficient sequence and the mass coefficient of each row of the membrane at the next extreme point, which is recorded as the fourth difference; Calculate the sum of the third difference and the fourth difference, and record it as the second difference amplitude Dtwo corresponding to each extreme point a .

9. The method for online identification of film abnormality of a PE film packaging machine according to claim 8, characterized in that: The control process of the recognition speed of the PE packaging machine is: By formula , the feeding control speed VT of the PE film to the PE packaging machine is calculated; Wherein, b=1,2,...,a, a is the number of extreme points on the quality curve, VD represents the current feeding speed of PE film to the PE packaging machine, QBm represents the quality coefficient threshold of each line of film, Qmmax represents the maximum quality coefficient of each line of film among the extreme points, Qm a It represents the quality coefficient of each row of the membrane corresponding to each extreme point.

10. A PE film packaging machine film abnormality online identification system, characterized in that: The system is used to execute the method described in any one of claims 1 to 9, and the system comprises: Image acquisition module: an industrial camera is set on the PE film packaging machine to collect image data of the film to be packaged, identify whether there are bubble features in the image of the film to be packaged, and extract bubble feature data; Identification and analysis module: divides the image data of the packaging film into regions, determines the bubble distribution data and area size of each region according to the bubble feature data, and outputs the quality coefficient of each row of the film; Quality identification module: According to the quality coefficient of each line of the film, the quality of each line of the film to be packaged is qualitatively analyzed to obtain a signal of whether the quality of each line of the film to be packaged is qualified; then based on the determined signal of whether the quality of each line of the film to be packaged is qualified, the film to be packaged is evaluated as a whole, and the corresponding identification instructions are generated according to the evaluation results; Identification control module: controls the identification speed of the PE packaging machine according to the generated identification instructions.

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