Quality control system for rattan plaited product

Abstract

The invention discloses a rattan-plaited product quality control system, and the system comprises an input unit which collects the data information of the quality of a rattan-plaited product in the production process; the calculation unit obtains the data information collected by the input unit and calls an association formula to calculate and obtain quality evaluation data of the rattan plaited product; and the display processing unit is used for acquiring the quality evaluation data output by the calculation unit and carrying out corresponding display alarm according to the quality evaluation data. According to the rattan plaited product quality control system, information of the product is collected through the input unit arranged on each production process, quality detection is carried out on the product after the current process is completed, data are collected, and quality evaluation data are calculated according to an association formula to achieve quality monitoring of the whole link. And the problem of product scrapping or multi-channel repair caused by quality problems of quality detection after complete production of the product can be avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of rattan weaving, and in particular relates to a rattan weaving product quality control system. Background Art

[0002] Rattan products generally include a frame and rattan for weaving. The rattan is cross-fixed on the frame to form a closed surface to play a load-bearing role. However, due to the structural limitations of rattan products, most of the rattan products currently still need to rely on manual production. This makes it difficult to control the quality of rattan products. Basically, they are tested after completion, and it is impossible to achieve full-link quality management in the production process. Summary of the invention

[0003] This application proposes a rattan product quality control system to address the problem that the prior art relies on manual work to complete rattan products, which makes it difficult to control the quality of rattan products.

[0004] The specific technical solutions are as follows:

[0005] Rattan products quality control system, including:

[0006] An input unit, the input unit collecting data information on the quality of rattan products during production;

[0007] A calculation unit, wherein the calculation unit obtains the data information collected by the input unit, and uses a correlation formula to calculate and obtain quality evaluation data of the rattan product;

[0008] and a display processing unit, wherein the display processing unit obtains the quality evaluation data output by the calculation unit and displays a corresponding alarm according to the quality evaluation data.

[0009] Preferably, the input unit comprises:

[0010] Product number collection module, which is set in each production process and is used to collect the unique number of the current product;

[0011] and a product quality data collection module, wherein the product quality data collection module is arranged in each production process and is used to collect relevant quality data related to the content of the current process after the current process is completed.

[0012] Preferably, the product quality data acquisition module includes an image acquisition submodule and an intensity data acquisition submodule.

[0013] Preferably, the correlation formula called by the calculation unit is:

[0014]

[0015] In the above formula, k represents the quality evaluation data obtained through calculation, k is a value between 0 and 1, and when k is less than the standard value K S When , it is judged that the rattan product has quality problems, n represents the cumulative number of processes in the production process of rattan products, a i It indicates the evaluation value of a certain process in the production of rattan products.

[0016] Preferably, a i When the strength data acquisition submodule provides data, a strength standard value is set for the test. When the product can reach the strength standard value, a i Takes 1, otherwise takes 0.

[0017] Preferably, a i When the image acquisition submodule provides data, during welding, a i The calculation method is:

[0018] Obtain the number of images and mark the welding area;

[0019] Find the boundary of the welding area and calculate the area S1 of the welding area;

[0020] Find the abnormal points and their boundaries inside the welding area, and calculate the area S2 of all abnormal points;

[0021] Calculate a i =1-S2 / S1.

[0022] Preferably, the specific method for finding abnormal points and their boundaries inside the welding area is:

[0023] After determining the boundary of the welding area, the image is converted into a grayscale image;

[0024] Set a scanning window, which is a number of pixel frames set continuously;

[0025] At the edge of the welding area, the scanning window is used to randomly scan several areas, obtain the maximum value G1 and minimum value G2 of the gray value in each scanned area, and calculate the ratio z of the maximum value G1 and the minimum value G2, and then take the average value of all scanned areas.

[0026] With this average The confidence value of the abnormal point is calculated by adjusting the coefficient α as the benchmark α ranges from 0 to 1;

[0027] In the grayscale image of the welding area, the scanning window is continuously scanned without repetition, and the ratio z of the maximum value G1 and the minimum value G2 in the scanning window is calculated for each scan, and it is determined whether the ratio z is greater than the abnormal point confidence value δ. If so, calibration is performed in a certain pixel frame of the scanning window until the scan is completed;

[0028] The continuous calibration points in the welding area are enclosed to form the boundary of the abnormal point, and the area S2 of the abnormal point is calculated.

[0029] Preferably, a i When the image acquisition submodule provides data, during weaving, a i The calculation method is:

[0030] Obtain the number of images and mark out the weaving area;

[0031] Find the boundary of the weaving area and calculate the total number of rattan strips N1 within the weaving area;

[0032] Compare the total number of rattan N1 with the standard value N2. When N1 ≥ N2, a i Take 1, when N1<N2,

[0033] Preferably, the display processing unit includes an alarm module and a sub-display module, and the alarm module and the sub-display module are arranged in each production process. When the product is of unqualified quality, the sub-display module is used for display, and the alarm module is used for issuing an alarm.

[0034] The beneficial effects of the present invention are as follows: the rattan product quality control system in the present application collects product information through an input unit arranged in each production process, and performs quality inspection and collects data on the products after the current process is completed, and calculates quality evaluation data according to the correlation formula to realize quality monitoring of the whole process, which can avoid the problem of product scrapping or multiple repairs caused by quality problems when quality inspection is carried out after the product is fully produced. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Shown is the topological structure diagram of the rattan product quality control system. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments.

[0037] Example

[0038] Figure 1Shown is a topological structure diagram of a rattan product quality control system, which includes an input unit, a calculation unit and a display processing unit, wherein the input unit is used to input data information about the quality of rattan products in the production process into the system, the calculation unit is used to obtain the data information provided by the input unit, and call the associated formula to calculate and obtain the quality evaluation data of the rattan products, and the display processing unit is used to obtain the quality evaluation data output by the calculation unit, and use the evaluation criteria to assist in determining whether the rattan product has a quality problem. If not, the rattan product is skipped, and if so, an alarm is displayed.

[0039] Regarding the input unit, it includes a product number collection module and a product quality data collection module.

[0040] The product number collection module is used to collect the unique number of the current product, which is used to match the product quality data collection module to collect product quality data and calculate the subsequent quality evaluation data of rattan products. Therefore, the number collection module needs to be set in each production process to realize quality management of the entire process.

[0041] Generally speaking, the product number collection module can use a barcode scanner to scan and read the code. The read QR code or barcode with a unique number is pasted on the frame in the first process (the first process) so that the corresponding product number can be collected and recorded by the product number collection module in all subsequent production processes.

[0042] The product quality data acquisition module is used to collect relevant quality data related to the content of the current process after the current process is completed. The product quality data acquisition includes an image acquisition submodule and an intensity data acquisition submodule.

[0043] The image acquisition submodule and the strength data acquisition submodule are set in different production processes according to actual needs. The strength data acquisition submodule is generally set in the production process of the skeleton. When the production process of the skeleton is completed, the quality of the corresponding process completion content is inspected. For example, when metal is generally used as the skeleton, it involves the connection between multiple metal skeletons. When bolts are used for fastening, the connection strength of the connection needs to be tested. In general application scenarios, it can include compressive strength and tensile strength. The compressive strength and tensile strength can be tested by pressure testing equipment and tension testing equipment respectively to obtain the relevant quality data of the current skeleton production process.

[0044] On the other hand, when welding is used to fasten the metal frame, in addition to setting the strength data acquisition sub-module, an image acquisition sub-module can also be set as needed to collect welding condition data at the welding point. Generally speaking, when the image acquisition sub-module needs to be set, the welding part is usually exposed, so it is necessary to collect welding condition data through the image acquisition sub-module to help determine whether there are welding burrs or whether it is a full weld.

[0045] The associated formula called by the calculation unit is:

[0046]

[0047] In the above formula, k represents the quality evaluation data obtained through calculation, k is a value between 0 and 1, and when k is less than the standard value K S When , it is judged that the rattan product has quality problems, n represents the cumulative number of processes in the production process of rattan products, a i It indicates the evaluation value of a certain process in the production of rattan products.

[0048] For example, when the evaluation value a1 of the rattan product in the first process is 1, the evaluation value a2 of the second process is 0.8, and the evaluation value a3 of the third process is 0.75, K S The value of K is 0.7. After the first process is completed, the product is qualified and can enter the subsequent production. After the second process is completed, the product is still qualified and can enter the subsequent production. After the third process is completed, the product quality evaluation data is 0.6, which is less than the standard value K. S Therefore, it should be judged that the product quality is unqualified after the third process is completed and cannot enter the subsequent production, and an alarm is displayed through the display processing unit.

[0049] a i The value of varies depending on the data source. When the intensity data acquisition submodule provides data, a i It is a conditional value, which can be 0 or 1. Specifically, a strength standard value is set. When the product can reach the strength standard value, a i Takes 1, otherwise takes 0.

[0050] When data is provided by the image acquisition submodule, there are also different calculation methods for welding and weaving.

[0051] In welding, a i The calculation method is:

[0052] Obtain the number of images and mark the welding area;

[0053] Find the boundary of the welding area and calculate the area S1 of the welding area. Generally, the image binary method can be used to find the boundary of the welding area;

[0054] Find the abnormal points and their boundaries inside the welding area, and calculate the area S2 of all abnormal points;

[0055] Calculate a i =1-S2 / S1.

[0056] The specific method for finding the abnormal points and boundaries inside the welding area is as follows:

[0057] After determining the boundary of the welding area, the image is converted into a grayscale image, and the grayscale values ​​of the content outside the welding area in the image are all set to 0 or 255 to reduce interference. The welding area can also be directly extracted from the image and then converted into a grayscale image separately;

[0058] Set a scanning window, which is a number of pixel frames set continuously. The number is determined according to the actual situation and should ensure that the boundary part of the welding area can be covered. The scanning window can be set horizontally or vertically;

[0059] At the edge of the welding area, the scanning window is used to randomly scan several areas, obtain the maximum value G1 and minimum value G2 of the gray value in each scanned area, and calculate the ratio z of the maximum value G1 and the minimum value G2, and then take the average value of all scanned areas.

[0060] With this average The confidence value of the abnormal point is calculated by adjusting the coefficient α as the benchmark Generally, the value of α is 0 to 1, and the specific value is set according to actual production needs;

[0061] In the grayscale image of the welding area, the scanning window is continuously scanned without repetition, and the ratio z of the maximum value G1 and the minimum value G2 in the scanning window is calculated for each scan, and it is determined whether the ratio z is greater than the abnormal point confidence value δ. If so, calibration is performed in a certain pixel frame of the scanning window until the scan is completed;

[0062] The continuous calibration points in the welding area are enclosed to form the boundary of the abnormal point, and the area S2 of the abnormal point is calculated.

[0063] This method can be used to find out whether there are large burrs or weld leaks in the welding area.

[0064] In weaving, since the rattan fabric is soft, it has no fixed shape after weaving. The direction of the rattan can be changed by adjustment. The main quality issue is whether the density of the rattan meets the requirements. i The calculation method is:

[0065] Obtain the number of images and mark out the weaving area;

[0066] Find the boundary of the weaving area and calculate the total number of rattans N1 in the weaving area. Generally, weaving adopts a horizontal and vertical cross method, so the total number of rattans N1 is usually the sum of the horizontal rattan number and the vertical rattan number;

[0067] Compare the total number of rattan N1 with the standard value N2. When N1 ≥ N2, a i Take 1, when N1<N2,

[0068] The display processing unit includes an alarm module and a sub-display module, wherein the alarm module and the sub-display module are arranged in each production process. When the product quality is unqualified, the sub-display module is used for display, and the alarm module directly gives an alarm when the product quality is unqualified, so as to prompt relevant personnel to deal with the unqualified products.

[0069] The above-mentioned alarm module can generally adopt an audible and visual alarm, or a simple buzzer.

[0070] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them.

Claims

1. Rattan products quality control system, characterized by: include: An input unit, the input unit collecting data information on the quality of rattan products during production; A calculation unit, wherein the calculation unit obtains the data information collected by the input unit, and uses a correlation formula to calculate and obtain quality evaluation data of the rattan product; and a display processing unit, wherein the display processing unit obtains the quality evaluation data output by the calculation unit and displays a corresponding alarm according to the quality evaluation data.

2. The rattan product quality control system according to claim 1, characterized in that: The input unit comprises: Product number collection module, which is set in each production process and is used to collect the unique number of the current product; and a product quality data collection module, wherein the product quality data collection module is arranged in each production process and is used to collect relevant quality data related to the content of the current process after the current process is completed.

3. The rattan product quality control system according to claim 2, characterized in that: The product quality data acquisition module includes an image acquisition submodule and an intensity data acquisition submodule.

4. The rattan product quality control system according to claim 3, characterized in that: The associated formula called by the calculation unit is: In the above formula, k represents the quality evaluation data obtained through calculation, k is a value between 0 and 1, and when k is less than the standard value K S When , it is judged that the rattan product has quality problems, n represents the cumulative number of processes in the production process of rattan products, a i It indicates the evaluation value of a certain process in the production of rattan products.

5. The rattan product quality control system according to claim 4, characterized in that: a i When the strength data acquisition submodule provides data, a strength standard value is set for the test. When the product can reach the strength standard value, a i Takes 1, otherwise takes 0.

6. The rattan product quality control system according to claim 4, characterized in that: a i When the image acquisition submodule provides data, during welding, a i The calculation method is: Obtain the number of images and mark the welding area; Find the boundary of the welding area and calculate the area S1 of the welding area; Find the abnormal points and their boundaries inside the welding area, and calculate the area S2 of all abnormal points; Calculate a i =1-S2 / S1.

7. The rattan product quality control system according to claim 6, characterized in that: The specific method for finding abnormal points inside the welding area and its boundaries is: After determining the boundary of the welding area, the image is converted into a grayscale image; Set a scanning window, which is a number of pixel frames set continuously; At the edge of the welding area, the scanning window is used to randomly scan several areas, and the maximum value G1 and the minimum value G2 of the gray value in each scanned area are obtained. The ratio z of the maximum value G1 and the minimum value G2 is calculated, and then the average value z of all the scanned areas is taken; Based on the average value z, the outlier confidence value δ = α × z is calculated by adjusting the coefficient α, where α is 0 to 1; In the grayscale image of the welding area, the scanning window is continuously scanned without repetition, and the ratio z of the maximum value G1 and the minimum value G2 in the scanning window is calculated for each scan, and it is determined whether the ratio z is greater than the abnormal point confidence value δ. If so, calibration is performed in a certain pixel frame of the scanning window until the scan is completed; The continuous calibration points in the welding area are enclosed to form the boundary of the abnormal point, and the area S2 of the abnormal point is calculated.

8. The rattan product quality control system according to claim 4, characterized in that: a i When the image acquisition submodule provides data, during weaving, a i The calculation method is: Obtain the number of images and mark out the weaving area; Find the boundary of the weaving area and calculate the total number of rattan N1 in the weaving area; Compare the total number of rattan N1 with the standard value N2. When N1 ≥ N2, a i Take 1, when N1<N2, 9. The rattan product quality control system according to claim 1, characterized in that: The display processing unit includes an alarm module and a sub-display module. The alarm module and the sub-display module are arranged in each production process. When the product is of unqualified quality, the sub-display module is used for display and the alarm module is used for giving an alarm.

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