Automatic control system of screw gluing equipment

Abstract

The application relates to the technical field of screw gluing processing, and provides a screw gluing equipment automatic control system, the screw gluing equipment comprises a vibrating disc feeder, a feeder, a gluing machine and a heating device, the system comprises multiple image detection modules, which are used for acquiring screw images and obtaining quality detection results according to the screw images; an automatic control module is used for obtaining a feedback control signal according to the quality detection results and an analysis model; a vibrating disc control module is used for adjusting the vibration frequency of the vibrating disc feeder according to the feedback control signal; a heating control module is used for adjusting the heating power of the heating device according to the feedback control signal; and a gluing control module is used for controlling the glue feeding power of the gluing machine according to the feedback control signal. The application scheme reduces the output probability of unqualified screws and improves the gluing quality of precision screws.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of screw gluing processing, in particular to a screw gluing equipment automatic control system. BACKGROUND

[0002] Screws are common mechanical parts, which are simple, reliable and easy to use, and are widely used in modern mechanical equipment. With the continuous development of science and technology, the production and processing of screws have changed with the application demand, thus various screws have been born, and the glued screw belongs to one of them.

[0003] In order to ensure the stability of screw connection, the common method is to pre-glue the screw, and the counteracting force is generated by extruding the anti-loosening glue during the screw locking process, so as to increase the friction between the threads, thereby achieving the anti-loosening effect.

[0004] Although the glued screw has multiple advantages, the production process requirements are also improved, for example, during the gluing process, the gluing quality of each screw needs to be controlled, and if the gluing is uneven or the gluing position is wrong, it will greatly affect the use effect of the glued screw.

[0005] Although there are many screw gluing equipment at present, most of them are applied to the gluing production of large screws, and it is still difficult to achieve precise automatic gluing control for some precision screws, for example, screws with a total length of less than 1 mm, especially M1.2X0.8 mm screws, because the screw volume is small, it is difficult to glue, and in the production line process, it is difficult to guarantee the gluing quality of the screw. SUMMARY

[0006] The application aims to provide a screw gluing equipment automatic control system, which can improve the gluing quality of the output product in the automatic gluing production process of the screw.

[0007] The above application purpose of the application is realized by the following technical scheme:

[0008] In a first aspect, the screw gluing equipment automatic control system provided by the application adopts the following technical scheme.

[0009] A screw gluing equipment automatic control system, the screw gluing equipment comprises a vibrating disc feeder, a feeder, a glue applicator and a heating device, and the system comprises:

[0010] A plurality of image detection modules are used to acquire the screw image and obtain a quality detection result according to the screw image;

[0011] An automatic control module is used to obtain a feedback control signal according to the quality detection result and an analysis model;

[0012] a vibration control module configured to adjust a vibration frequency of the vibration plate feeder according to the feedback control signal;

[0013] a heating control module configured to adjust a heating power of the heating device according to the feedback control signal;

[0014] and a glue application control module configured to control a glue feeding power of the glue applicator according to the feedback control signal.

[0015] In one preferred example, obtaining the quality detection result according to the screw image comprises:

[0016] performing feature extraction on the screw image to obtain target feature information of the screw image;

[0017] obtaining the quality detection result through the screw image, the target feature information and the trained neural network model.

[0018] In one preferred example, the target feature information of the screw image obtained by performing feature extraction on the screw image comprises a profile map of a glue application position of the screw.

[0019] In one preferred example, training the neural network model comprises:

[0020] collecting sample images and extracting feature information in the sample images;

[0021] generating a training sample set by increasing diversity of the feature information through random transformation of the images;

[0022] obtaining the neural network model by inputting the training sample set and the quality detection result matched with the feature information into a deep convolutional neural network.

[0023] In one preferred example, increasing diversity of the feature information through random transformation of the images comprises randomly scaling a length of a side of the internal thread on both sides of the feature information by using an image processing function, and setting a scaling factor range to be 15%-100%; and generating scaled feature information by randomly scaling each image.

[0024] In one preferred example, the quality detection result comprises a profile difference, a thread difference, a color application depth and a spot.

[0025] In one preferred example, obtaining the feedback control signal according to the quality detection result and the analysis model comprises: generating a vibration adjustment reference value, a heating adjustment reference value and a glue feeding adjustment reference value according to the profile difference, the thread difference, the color application depth and whether the spot exists by using the analysis model.

[0026] In a preferred example, the probability Q1 that the screw is unqualified product is calculated according to the profile height difference;

[0027] The probability Q2 that the profile height difference of a preset number of threads is greater than a preset thread difference value is calculated according to the thread height difference;

[0028] The probability Q3 that the color depth of a preset number of threads is greater than a preset gray scale difference value is calculated according to the color depth;

[0029] The vibration adjustment reference value, the heating adjustment reference value and the glue feeding adjustment reference value are generated according to the Q1, Q2 and Q3.

[0030] In a preferred example, the glue applying machine comprises a vertically arranged glue outlet pipe, and the sealant overflows from the top of the glue outlet pipe. The glue outlet pipe is symmetrically provided with a material passing groove on both sides of the top end, and the screw sequentially passes through the two material passing grooves to complete the glue applying.

[0031] In a preferred example, the heating device is arranged between the glue applying machine and the image detection module, and is used for heating the screw after the glue applying.

[0032] In summary, the present application has the following beneficial technical effects: in the process of applying glue to the precision screw, the glue applying method of the glue outlet pipe is used to apply glue to the precision screw, and then the profile height difference, thread height difference, color depth and spot of the screw are analyzed to automatically adjust the vibration plate feeder, heating device and glue applying machine in the screw glue applying equipment, thereby improving the glue applying quality of the precision screw in cooperation with the glue applying method of the glue outlet pipe. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 is a structural arrangement diagram of the screw glue applying equipment in the embodiment of the present application.

[0034] Figure 2 is a structural arrangement diagram of the screw glue applying equipment in the embodiment of the present application.

[0035] Figure 3 is a system topology diagram of the automatic control system in the embodiment of the present application.

[0036] Figure 4 is a schematic diagram of the height difference h in the profile diagram in the embodiment of the present application.

[0037] Marked with 1, vibration plate feeder; 2, feeder; 3, glue applying machine; 31, glue outlet pipe; 32, material passing groove; 4, camera; 5, heating device. DETAILED DESCRIPTION

[0038] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0039] In addition, the term "and / or" in the present application is only used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " in the present application generally represents an "or" relationship between the associated objects unless otherwise specified.

[0040] At present, many service enterprises will construct a service platform according to the needs of the customers served, and the customers served by the enterprise will upload their own information to the platform or the platform will automatically obtain the customer information through the crawler technology. After obtaining the customer information on the platform, the derived data service can be generated through the customer information, and the technology transfer analysis is an important part of the derived data service. The present application provides a regional innovation capability evaluation and classification method based on technology transfer through the customer information in the platform.

[0041] With reference to Figure 1 and Figure 2 The present application provides an automatic control system of a screw gluing equipment, wherein the gluing equipment comprises a vibrating tray feeder 1, a feeder 2, a gluing machine 3 and a heating device 5. The screws in the vibrating tray feeder 1 enter the feeder 2 one by one through the vibrating tray feeder 1, the feeder 2 sends the screws into the gluing machine 3 one by one, the heating device 5 completes the heating of the screws, and the gluing machine 3 completes the gluing of the screws. In the present application, the gluing machine 3 completes the gluing through a vertically arranged glue outlet pipe 31, the sealant overflows from the top of the glue outlet pipe 31, and two material passing grooves 32 are symmetrically arranged at the top of the glue outlet pipe 31. The screws pass through the glue outlet pipe 31 under the driving of the feeder 2, and the bottom of the screws passes through the two material passing grooves 32 in turn to complete the gluing.

[0042] It should be noted that the screw described in the present application is a precision screw, that is, the total length and diameter of the screw are less than a certain threshold. Such screws are characterized by small size and light weight. The mutual friction of a large number of screws in the vibration plate feeder 1, the slight vibration of the conveying process, the screw heating effect, the glue output power of the glue output pipe 31, and the size and depth of the slot of the material passing groove 32 all affect the gluing process of the screw through the glue output pipe 31. However, in order to reduce the production cost of the screw, the resource consumption of the screw gluing equipment needs to be controlled as much as possible. Based on this, the automatic control system of the screw gluing equipment provided by the present application is to improve the gluing quality of the precision screw while reducing the cost of screw gluing.

[0043] Referring to Figure 1 and Figure 3 , the automatic control system comprises a plurality of image detection modules for obtaining the screw image and obtaining a quality detection result according to the screw image; an automatic control module for obtaining a feedback control signal according to the quality detection result and an analysis model; a vibration plate control module for adjusting the vibration frequency of the vibration plate feeder 1 according to the feedback control signal; a heating control module for adjusting the heating power of the heating device 5 according to the feedback control signal; and a glue coating control module for controlling the glue feeding power of the glue coating machine 3 according to the feedback control signal.

[0044] The image detection module comprises a plurality of cameras 4 arranged behind the glue coating machine 3 to obtain the screw image after gluing. The plurality of cameras 4 realize image shooting of the screw from multiple directions, and at the same time, the camera 4 of the image detection module is at the same horizontal height as the screw, so that the screw image can clearly show the screw thread structure. The method of obtaining the quality detection result according to the screw image by the image detection module comprises: extracting features from the screw image to obtain target feature information of the screw image; obtaining the quality detection result by the screw image, target feature information and a trained neural network model.

[0045] After the screw is glued, the color of the glued part is different from that of the rest of the screw. After obtaining the screw image, the target feature information is obtained by sequentially performing gray scale processing and binaryzation processing on the screw image. The target feature information includes a screw gluing part contour graph, and the contour graph expresses the clear gluing part height and the gluing part thread structure. Specifically, for each screw, a plurality of screw images are obtained, and the quality detection result of the screw is calculated by the gluing part contour graph of the plurality of screw images. The quality detection result includes contour height difference, thread height difference, gluing color depth and spots.

[0046] The profile height of the screw can be directly identified through the profile image. When the screw is being glued, the height of the screw gluing position needs to be ensured to ensure the gluing of the preset position of the screw. In the embodiment of the application, the camera 4 of the image detection module is fixedly arranged, and the screw image obtained by the camera can also directly reflect the minimum gluing height of the gluing position through the profile image of the gluing position. The profile height difference in the quality detection result indicates that the minimum gluing height is less than the preset gluing height, which is height qualified, and vice versa, which is height unqualified.

[0047] The color depth can be represented by the gray value after gray processing. Since the uniformity of gluing needs to be ensured when the screw is glued, whether the gray value of the gluing position in the screw image is uniform can be identified through the gray value. The color depth in the quality detection result indicates the difference between the maximum gray value and the minimum gray value of the gluing position in all screw images of the same screw.

[0048] The spot indicates that the gluing position is not glued. When the gray value of the gluing position is the same as the gray value of the screw image outside the gluing position, it indicates that there is a spot in the gluing position.

[0049] The thread height difference indicates the maximum difference between the height differences of the two side edge endpoints of the inner thread of all threads in the profile image of all gluing positions of the screw. The height difference of the two side edge endpoints refers to the height difference h in the Figure 4 The thread height difference is the difference between the maximum height difference h and the minimum height difference h in all gluing positions of the screw. Since the volume of the precision screw is small and the volume of the thread is smaller, the gluing method using the glue outlet pipe 31 is easy to cause the deformation of the thread structure of the gluing position. Therefore, the neural network model needs to be designed to identify the position of the inner thread and the height difference h. The method for training the neural network model is as follows:

[0050] Collect sample images and extract feature information in the sample images. Increase the diversity of the feature information through random transformation of the images to generate a training sample set. Enter the quality detection result matched with the feature information into the deep convolutional neural network to obtain the neural network model. Increasing the diversity of the feature information through random transformation of the images includes randomly scaling the lengths of the two side edges of the inner thread in the feature information using an image processing function, and setting the scaling factor range to 15%-100%. Randomly scale each image to generate scaled feature information.

[0051] The sample pattern is a standard glued screw image. In the random transformation process, the lengths of the two sides are randomly scaled to simulate the uneven glue coating of the screw thread pattern. It should be noted that the scaling of the two sides of the screw thread is not related to each other, that is, the scaling of the two sides is not simultaneous. When the screw thread is not glued, the length of the side corresponds to the scaling factor value of 100%. The neural network model identifies the screw thread structure by identifying the two sides of the screw thread, and the screw thread height difference is obtained after the two sides are identified.

[0052] According to the quality detection result and the analysis model, a feedback control signal is obtained, including: generating a vibration disc adjustment signal, a heating adjustment signal and / or a glue feeding adjustment signal through an analysis model according to the profile height difference, the screw thread height difference, the color coating depth and whether there are spots. The process of generating a feedback control signal by the analysis model is as follows,

[0053] According to the profile height difference, the probability Q1 that the screw is an unqualified product is calculated. In a preferred example, the number of unqualified products appearing within a preset number is calculated, and the probability of the appearance of the unqualified product is calculated according to the number of unqualified products and the preset number. It should be noted that when an unqualified product appears, the unqualified screw is removed by a subsequent screw removal device, and the screw removal device is not described in the embodiments of the present application.

[0054] According to the screw thread height difference, the probability Q2 that the screw thread height difference is greater than a preset screw thread difference value within a preset number is calculated. Specifically, the number of screws whose screw thread height difference is greater than the preset screw thread difference value within the preset number is calculated, and the probability that the screw thread height difference is greater than the preset screw thread difference value within the preset number is calculated according to the number of screws whose screw thread height difference is greater than the preset screw thread difference value and the preset number.

[0055] According to the color coating depth, the probability Q3 that the color coating depth is greater than a preset gray scale difference value within a preset number is calculated. Specifically, the number of screws whose color coating depth is greater than the preset gray scale difference value within the preset number is calculated, and the probability Q3 is calculated according to the number of screws whose color coating depth is greater than the preset gray scale difference value and the preset number.

[0056] When any one of Q1>K11, Q2>K21, Q3>K31 occurs, it means that it is necessary to start automatic adjustment of the screw gluing equipment; when any one of Q1>K12, Q2>K22, Q3>K32 and spot exists occurs, it means that the screw gluing equipment has a major accident, and the screw gluing equipment needs to be shut down for maintenance, wherein K11, K12, K21, K22, K31, K32 are all preset probability thresholds.

[0057] When it is necessary to start automatic adjustment of the screw gluing equipment:

[0058] Fz = a1 * Q1 + b1 * Q2 + g1 * Q3;

[0059] Ft = a2 * Q1 + b2 * Q2 + g2 * Q3;

[0060] Fm = a3 * Q1 + b3 * Q2 + g3 * Q3;

[0061] Fz, Ft, Fm are vibration adjustment reference value, heating adjustment reference value and glue feeding adjustment reference value respectively; a1, a2, a3, b1, b2, b3, g1, g2, g3 are all preset adjustment bases.

[0062] The feedback control signal comprises a vibration adjustment reference value, a heating adjustment reference value and a glue feeding adjustment reference value.

[0063] The vibration disc control module adjusts the vibration frequency of the vibration disc feeder 1 according to the vibration adjustment reference value, and the vibration adjustment reference value corresponds to the power supply frequency of the vibration motor of the vibration disc feeder 1.

[0064] The heating control module adjusts the heating power of the heating device according to the heating adjustment reference value, and the heating adjustment reference value corresponds to the effective value of the heating power supply current of the heating device.

[0065] The glue coating control module adjusts the glue feeding power of the glue coating machine 3 according to the glue feeding adjustment reference value, and the glue feeding adjustment reference value corresponds to the power supply frequency of the glue feeding motor.

[0066] By adopting the above technical scheme, in the process of precise screw gluing, the screw is first glued by the glue coating mode of the glue outlet pipe 31, then the profile height difference, thread height difference, color coating depth and spot of the screw are analyzed, so that the vibration disc feeder 1, the heating plate 22 and the glue coating machine 3 in the screw gluing equipment are automatically adjusted, thereby cooperating with the glue coating mode of the glue outlet pipe 31 to reduce the output probability of unqualified screws, and the gluing quality of the precise screw is improved.

Claims

1. A screw gluing equipment automatic control system, characterized in that, The screw gluing equipment comprises a vibrating tray feeder (1), a feeder (2), a glue applicator (3) and a heating device (5), and the system comprises: a plurality of image detection modules for acquiring the screw image and obtaining a quality detection result according to the screw image; an automatic control module for obtaining a feedback control signal according to the quality detection result and an analysis model; a vibrating tray control module for adjusting the vibration frequency of the vibrating tray feeder (1) according to the feedback control signal; a heating control module for adjusting the heating power of the heating device (5) according to the feedback control signal; and a glue application control module for controlling the glue feeding power of the glue applicator (3) according to the feedback control signal; the quality detection result comprises profile height difference, thread height difference, color depth and spot; obtaining a feedback control signal according to the quality detection result and an analysis model comprises: generating a vibration adjustment reference value, a heating adjustment reference value and a glue feeding adjustment reference value according to the profile height difference, the thread height difference, the color depth and whether there is a spot through the analysis model; the glue applicator (3) comprises a vertically arranged glue outlet pipe (31), the sealant overflows from the top of the glue outlet pipe (31), and two overflow grooves (32) are symmetrically arranged at the top of the glue outlet pipe (31), and the screw bottom sequentially passes through the two overflow grooves (32) to complete the gluing; The profile height of the screw can be directly identified by the profile image. When the screw is glued, the height of the screw gluing part needs to be ensured to ensure the gluing of the preset part of the screw. The color depth can be represented by the gray value after gray processing. The spot represents the situation that the gluing part is not glued. The thread height difference represents the maximum difference of the height difference of the two side edge endpoints of the inside thread of all the threads in the profile image of the entire gluing part of the screw image.

2. The automatic control system of the screw gluing equipment according to claim 1, characterized in that, obtaining a quality detection result according to the screw image comprises: extracting features from the screw image to obtain target feature information of the screw image; obtaining the quality detection result through the screw image, the target feature information and the trained neural network model.

3. The automatic control system of the screw gluing equipment according to claim 2, characterized in that, extracting features from the screw image to obtain target feature information of the screw image comprises: a screw gluing part profile image.

4. The automatic control system of the screw gluing equipment according to claim 3, characterized in that, training the neural network model comprises: collecting sample images and extracting feature information from the sample images; increasing the diversity of feature information through random transformation of images to generate a training sample set; entering the training sample set and the quality detection result matched with the feature information into a deep convolutional neural network to obtain the neural network model.

5. The automatic control system of the screw gluing equipment according to claim 4, characterized in that, increasing the diversity of feature information through random transformation of images comprises: using an image processing function to randomly scale the side edge length of the inside thread on both sides in the feature information, and setting the scaling factor range to 15%-100%; randomly scaling each image to generate scaled feature information.

6. The automatic control system of the screw gluing equipment according to claim 5, wherein: calculating the probability Q1 that the screw is unqualified product according to the profile height difference; calculating the probability Q2 that the thread height difference of a preset number of threads is greater than a preset thread difference value according to the thread height difference; According to the color depth, a probability Q3 that the color depth of a preset number is greater than a preset gray scale difference value is calculated; According to the Q1, Q2 and Q3, the vibration adjustment reference value, the heating adjustment reference value and the glue feeding adjustment reference value are generated.

7. The automatic control system of the screw gluing equipment according to claim 6, characterized in that, The heating device (5) is arranged between the glue spreading machine (3) and the image detection module, and is used for heating the screw after the glue spreading.

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