Hollow glass intelligent gluing control method

Abstract

The application discloses a kind of hollow glass intelligent glueing control method, belong to hollow glass processing technical field, this method is first by operation end entry glass type, running speed, preset glue surface parameter;Head operation, front first detector collects glue groove section data feedforward calculation basic glue discharge flow, after two-stage glue adjustment by quantitative glue supply system, mixer, glue amount fine controller, glue is applied;Rear second detector real-time acquisition glue surface form feedback correction glue amount, form closed loop glue amount control;Third detector real-time detection glass edge straightness, drive glue outlet dynamic centering.Three groups of detectors are integrated in 360 ° rotatable head, controller is built-in autonomous learning unit, adaptive temperature, glue viscosity fluctuation, glueing depth fluctuation.The application automatically compensates glass deformation deviation, and has high glueing consistency, reduces manual intervention, and is suitable for general, special-shaped, multi-cavity and other types of hollow glass glueing production.

Description

Technical Field

[0001] This invention relates to the field of insulating glass processing technology, and in particular to an intelligent adhesive coating control method for insulating glass. Background Technology

[0002] Insulating glass is widely used in building doors, windows, and curtain walls due to its excellent heat insulation, sound insulation, and light transmission performance. With the increasing market demand for large light transmission and wide field of vision, insulating glass is gradually developing towards larger sizes, irregular shapes, and multi-cavity designs. As the core process in the production of insulating glass, the precision and consistency of the adhesive application directly determine the sealing life, heat insulation performance, and appearance quality of the glass.

[0003] Existing insulated glass adhesive coating control technologies have the following drawbacks: poor open-loop adhesive control accuracy. Traditional adhesive coating machines mostly adopt open-loop control, and the adhesive output is easily affected by factors such as ambient temperature, adhesive viscosity, and fluctuations in the adhesive tank size. During production, operators need to visually observe the adhesive output and manually adjust parameters, resulting in strong adjustment lag, low accuracy, difficulty in ensuring consistent adhesive coating quality, and high labor costs. Insufficient robustness of formula parameters. Some adhesive coating equipment can preset the operating formula based on the glass adhesive tank size and coating speed, but the formula can only serve as a basic parameter. In actual production, continuous manual correction is still required, resulting in long production changeover and debugging cycles and an inability to adapt to dynamic changes in external working conditions. Large-size insulated glass is prone to elastic deformation during production, transportation, and processing. Deviations in the straightness of the glass edges can cause the adhesive outlet to fail to align with the adhesive tank, leading to problems such as adhesive overflow and uneven sealing width, which seriously affect the sealing performance and appearance quality of the glass. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent adhesive coating control method for insulating glass. By constructing a multi-dimensional closed-loop control system through multiple sets of detectors, it can achieve precise control of adhesive output and dynamic alignment of the adhesive outlet, thus solving the technical problems of low accuracy of traditional open-loop adhesive control, adhesive deviation due to large glass deformation, and cumbersome manual parameter adjustment.

[0005] To achieve the above objectives, the present invention provides an intelligent adhesive coating control method for insulating glass, comprising the following steps: S1. Input the glass type, basic operating speed of the equipment, and preset adhesive surface shape parameters to the controller via the operating terminal; S2. When the glue applicator head moves along the edge of the glass, the first detector set on the forward side of the glue outlet collects the cross-sectional depth and width data of the glass glue tank in real time and feeds it back to the controller. S3. The controller calculates the basic dispensing flow rate by combining the glue tank cross-section data and the preset running speed, and sends flow rate instructions and motion control instructions to the quantitative glue supply system. S4. The quantitative glue supply system extrudes the two-component glue liquid according to the set ratio and delivers it to the mixer to complete the initial mixing. The mixed glue liquid flows into the glue quantity fine controller for fine flow adjustment, and finally is coated into the glass glue tank through the glue outlet. S5. The second detector set on the back side of the glue outlet collects the shape and depth data of the glued surface in real time and feeds it back to the controller. The controller compares the measured glue surface data with the preset glue surface parameters and corrects the glue dispensing amount in real time through the quantitative glue supply system and the glue quantity fine controller. S6. A third detector located on the back of the glass, below the glue outlet, collects the straightness data of the glass edge in real time and feeds it back to the controller. The controller controls the glue outlet to adjust its lateral position in real time so that the glue outlet is always aligned with the center of the glue tank.

[0006] Preferably, the first detector, the second detector, and the third detector are all integrated and installed on the glue applicator head, moving synchronously with the head and supporting 0-360° rotation operation.

[0007] Preferably, the glue output control adopts a two-stage adjustment architecture, with the quantitative glue supply system completing the coarse adjustment for large flow rates and the glue quantity fine controller completing the fine adjustment for small flow rates, taking into account both the flow rate adjustment range and adjustment accuracy.

[0008] Preferably, in step S6, the controller outputs a position compensation command in real time based on the glass edge offset fed back by the third detector, driving the glue outlet to move laterally to follow the center of the glue groove, thereby eliminating the glue application deviation caused by the elastic deformation of the glass.

[0009] Preferably, the method constructs a closed-loop glue control system, using the glue tank cross-sectional data collected by the first detector as the feedforward input to pre-match the basic glue dispensing flow rate; and using the measured glue surface data collected by the second detector as the feedback input to correct the glue dispensing deviation in real time.

[0010] Preferably, the controller has a built-in self-learning unit that continuously accumulates historical glue application parameters and glue surface effect data, iteratively optimizes the glue flow calculation logic, and adapts to fluctuations in ambient temperature and glue viscosity.

[0011] Preferably, the first detector, the second detector, and the third detector employ a mechanical detection structure or an optical detection structure.

[0012] Preferably, in step S4, the mixer is a static mixer or a dynamic mixer; the metering adhesive supply system precisely controls the displacement or rotation speed to extrude the A group main agent and the B group curing agent in a proportional and quantitative manner.

[0013] Preferably, the operating terminal adopts an HMI touch screen or a PC industrial display. The operating terminal interacts with the controller in real time, issues control commands, and provides feedback on the equipment's operating status.

[0014] Therefore, the present invention employs the above-mentioned intelligent adhesive coating control method for insulating glass, which has the following technical effects: (1) The present invention uses a closed-loop glue volume control system to pre-determine the basic flow rate by detecting the cross section of the glue tank and to detect the glue surface in real time to correct the deviation. Combined with a two-stage flow adjustment mechanism, it can effectively offset the influence of external factors such as temperature and glue viscosity fluctuations, significantly improve the consistency of glue application, and eliminate the need for frequent manual parameter adjustments.

[0015] (2) This invention can automatically compensate for the elastic deformation deviation of large-size glass by real-time detection of the straightness of the glass edge and dynamic tracking of the glue outlet position, ensuring that the glue outlet is always aligned with the glue tank, thus avoiding glue overflow and uneven sealing from the source, and improving sealing reliability and appearance quality.

[0016] (3) The controller of this invention has a built-in self-learning function, which can continuously optimize the flow calculation model based on historical operation data and adapt to different working conditions; multiple detectors are integrated into the glue coating head that can rotate 360°, which can adapt to the glue coating needs of all types of insulating glass, including ordinary, irregular, multi-cavity, and large and small pieces.

[0017] (4) The closed-loop automatic control of this invention replaces manual visual adjustment, reducing manual intervention; the production changeover and debugging cycle is short, reducing the dependence on the operator's experience and improving overall production efficiency.

[0018] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0019] Figure 1 This is a flowchart of an intelligent adhesive coating control method for insulating glass according to the present invention; Figure 2 This is a schematic diagram of the adhesive applicator head of an intelligent adhesive applicator system for insulating glass according to the present invention; Figure 3 This is a diagram showing the adhesive surface control mode of an intelligent adhesive coating control method for insulating glass according to the present invention, wherein (a) is a concave surface, (b) is a flat surface, and (c) is a convex surface.

[0020] Figure Labels 1. Controller; 2. Operating terminal; 3. Quantitative glue supply system; 4. Mixer; 5. Glue quantity fine controller; 6. Glue outlet; 7. First detector; 8. Second detector; 9. Third detector; 10. Glass; 11. Glue applicator head. Detailed Implementation

[0021] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0023] like Figures 1 to 3 As shown, an intelligent adhesive application control method for insulating glass is implemented based on a multi-detection closed-loop intelligent adhesive application system. This system mainly includes a controller 1, an operating terminal 2, a quantitative adhesive supply system 3, a mixer 4, an adhesive quantity fine controller 5, an adhesive outlet 6, a first detector 7, a second detector 8, a third detector 9, and an adhesive application head 11. The controller 1 adopts a combined architecture of a PLC programmable controller and a PC industrial control host. The first detector 7, second detector 8, third detector 9, adhesive quantity fine controller 5, and adhesive outlet 6 are all integrated and installed on the adhesive application head 11, moving synchronously with the head and supporting 0-360° rotation operation. The specific control method implementation steps are as follows: S1. Parameter Preset Operators input production parameters into controller 1 via operator terminal 2 (HMI touchscreen or PC industrial monitor), including glass type (normal, irregular, multi-cavity, large and small sheets), basic equipment operating speed, and preset adhesive surface shape (convex, flat, concave). Operator terminal 2 maintains real-time data interaction with controller 1. Operators issue control commands, and controller 1 provides real-time feedback on equipment operating status, detection data, and alarm information.

[0024] S2. Feedforward detection of glue tank cross-section After the glue application operation is started, the glue applicator head 11 moves along the edge of the glass 10. The first detector 7, located on the forward side of the glue outlet 6, moves synchronously with the head, collecting real-time data on the cross-sectional depth and width of the glue tank in front of the glass, and transmitting the detection data to the controller 1 in real time. The first detector 7 can adopt a mechanical contact detection structure or an optical non-contact detection structure, depending on the glue type and accuracy requirements.

[0025] S3. Basic Flow Calculation The controller 1 receives the data of the glue tank cross-sectional depth h and width w collected by the first detector 7, and calculates the basic glue discharge flow rate Q by combining it with the preset basic operating speed v of the equipment through the built-in flow calculation model. Then, it sends the flow rate command and position speed command to the quantitative glue supply system 3.

[0026] The flow calculation model is based on the geometrically fundamental flow rate, and incorporates temperature correction factors, viscosity correction factors, and pressure compressibility correction factors for operating condition correction. The complete calculation formula is as follows: The parameters in the formula are defined as follows: This refers to the depth of the glue tank, in mm. Width of the glue tank, in mm; Linear speed for adhesive application, in mm / s; The actual operating temperature of the colloid is expressed in °C. For reference calibration temperature, the default value is 25℃; The dynamic viscosity of the colloid at the operating temperature, in Pa·s; The reference viscosity of the colloidal solution is given at the reference temperature, in Pa·s. This is the temperature-viscosity coefficient, in units of 1 / ℃, calibrated by adhesive experiments, with a value range of 0.02~0.061 / ℃; The rheological index is 1 for Newtonian fluids and greater than 1 for pseudoplastic fluids, and is calibrated by rheological testing. The pressure used for applying the adhesive is measured in MPa. The pressure is atmospheric pressure, and the default value is 0.1013 MPa. This represents the isothermal compressibility of the colloid, in units of 1 / MPa, with a range of values. 1 / MPa, calibrated by actual measurement.

[0027] Controller 1 and metering glue supply system 3 form a bottom-level PID closed-loop control: The controller converts the calculated target flow rate into the target value of the pump speed or plunger displacement of the metering glue supply system and sends it down; The metering glue supply system has built-in pressure sensors, position encoders and speed sensors to collect status parameters such as fluid pressure, extrusion position and operating speed in real time and feed them back to the controller; The controller calculates the deviation between the feedback value and the target value, and adjusts the output command in real time through proportional-integral-derivative control logic, forming a closed loop of command issuance-status feedback-deviation adjustment to ensure stable basic flow output.

[0028] S4. Adhesive Supply and Coating After receiving instructions from the controller, the metering adhesive supply system 3 precisely controls the displacement or rotation speed to quantitatively extrude the main agent (Group A) and the curing agent (Group B) according to a preset ratio, and delivers them to the mixer 4 for initial uniform mixing. The mixer 4 can be selected as a static mixer or a dynamic mixer depending on the characteristics of the adhesive. The adhesive after the initial mixing flows into the fine adhesive quantity controller 5, which has both secondary fine mixing and flow rate fine adjustment functions. After micron-level fine adjustment of the adhesive flow rate, the final adhesive is extruded from the outlet 6 and coated into the adhesive tank of the glass 10.

[0029] S5. Surface Feedback Correction The second detector 8, located on the retracting side of the dispensing port 6, moves synchronously with the head to collect real-time data on the newly coated adhesive surface, including the surface shape (convex / flat / concave) and the depth of the adhesive surface, and feeds the measured data back to the controller 1.

[0030] Controller 1 compares and calculates the measured adhesive surface data with the preset adhesive surface parameters, and generates a flow correction command. The triggering conditions and adjustment rules for the correction command are as follows: Triggering condition: When the relative deviation between the measured adhesive surface parameters and the preset parameters exceeds the allowable threshold of ±5%, the controller immediately generates a flow correction command; when the deviation is within the threshold range, the current flow output remains stable.

[0031] Two-level correction rule: A graded adjustment strategy linking coarse and fine adjustment is adopted: When the absolute value of the deviation is greater than 10%, the quantitative glue supply system 3 is prioritized to perform large-flow coarse adjustment by adjusting the pump speed or plunger displacement to quickly reduce the flow deviation; when the absolute value of the deviation is in the range of 5% to 10%, the glue quantity fine controller 5 is controlled to perform small-flow fine adjustment by adjusting the opening of the internal throttling valve core to ensure adjustment accuracy; the two-level adjustment is synchronized and linked to correct the glue quantity in real time so that the glue surface always meets the preset requirements.

[0032] Therefore, the feedforward detection of the first detector 7 and the feedback detection of the second detector 8 together constitute a closed-loop adhesive control system. The feedforward stage predicts and eliminates most of the deviation in advance, while the feedback stage eliminates residual fluctuations and the influence of unpredictable factors. Combined with the two-stage adjustment mechanism, high-precision adhesive control is achieved. S6. Dynamic centering adjustment The third detector 9, located on the back of the glass 10 and below the glue outlet 6, moves synchronously with the head to detect the straightness data of the glass edge in real time and feeds back the position deviation to the controller 1. The controller 1 outputs a position compensation command in real time based on the offset, driving the glue outlet 6 to make lateral position fine adjustments, ensuring that the glue outlet 6 always moves with the center of the glue tank. This automatically compensates for edge offset caused by the elastic deformation of large-sized glass, fundamentally preventing glue overflow and misalignment. The third detector 9 can also be a mechanical or optical detection structure. During continuous production, the built-in self-learning unit of controller 1 continuously accumulates parameter data and corresponding adhesive surface effect data for each glue application operation, and iteratively optimizes the glue flow calculation logic through incremental parameter optimization algorithm.

[0033] The self-learning algorithm uses the temperature-viscosity coefficient in the flow calculation model. Isothermal compressibility rheological index The parameters to be optimized are as follows: After each complete glue application operation, the system uses the input parameters such as ambient temperature, glue application pressure, running speed, and glue tank cross-sectional data of this operation, along with the final glue surface effect data collected by the second detector, as a set of training samples. The system then uses the least squares method to fit and iterate the accumulated sample data, update the coefficient parameters of each correction factor, and gradually optimize the accuracy of the flow calculation model in adapting to its own equipment and operating conditions.

[0034] The optimized calculation model can adapt to external factors such as changes in ambient temperature, batch differences in adhesive, fluctuations in adhesive viscosity, and changes in the size of the adhesive tank, gradually reducing the need for manual parameter correction and achieving intelligent and autonomous adhesive control.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for intelligent adhesive application control of insulating glass, characterized in that, Includes the following steps: S1. Input the glass type, basic operating speed of the equipment, and preset adhesive surface shape parameters to the controller via the operating terminal; S2. When the glue applicator head moves along the edge of the glass, the first detector set on the forward side of the glue outlet collects the cross-sectional depth and width data of the glass glue tank in real time and feeds it back to the controller. S3. The controller calculates the basic dispensing flow rate by combining the glue tank cross-section data and the preset running speed, and sends flow rate instructions and motion control instructions to the quantitative glue supply system. S4. The quantitative glue supply system extrudes the two-component glue liquid according to the set ratio and delivers it to the mixer to complete the initial mixing. The mixed glue liquid flows into the glue quantity fine controller for fine flow adjustment, and finally is coated into the glass glue tank through the glue outlet. S5. The second detector set on the back side of the glue outlet collects the shape and depth data of the glued surface in real time and feeds it back to the controller. The controller compares the measured glue surface data with the preset glue surface parameters and corrects the glue dispensing amount in real time through the quantitative glue supply system and the glue quantity fine controller. S6. A third detector located on the back of the glass, below the glue outlet, collects the straightness data of the glass edge in real time and feeds it back to the controller. The controller controls the glue outlet to adjust its lateral position in real time so that the glue outlet is always aligned with the center of the glue tank.

2. The intelligent adhesive coating control method for insulating glass according to claim 1, characterized in that: The first detector, the second detector, and the third detector are all integrated and installed on the glue applicator head, moving synchronously with the head and supporting 0-360° rotation operation.

3. The intelligent adhesive coating control method for insulating glass according to claim 1, characterized in that: The glue output control adopts a two-stage adjustment architecture, with the quantitative glue supply system completing the coarse adjustment for large flow rates and the glue quantity fine controller completing the fine adjustment for small flow rates, taking into account both the flow rate adjustment range and adjustment accuracy.

4. The intelligent adhesive application control method for insulating glass according to claim 1, characterized in that: In step S6, the controller outputs a position compensation command in real time based on the glass edge offset fed back by the third detector, driving the glue outlet to move laterally to follow the center of the glue tank, thereby eliminating the glue application deviation caused by the elastic deformation of the glass.

5. The intelligent adhesive coating control method for insulating glass according to claim 1, characterized in that: The method constructs a closed-loop glue volume control system, using the glue tank cross-section data collected by the first detector as the feedforward input to pre-match the basic glue discharge flow rate; The measured data of the adhesive surface collected by the second detector is used as feedback input to correct the adhesive dispensing deviation in real time.

6. The intelligent adhesive coating control method for insulating glass according to claim 1, characterized in that: The controller has a built-in self-learning unit that continuously accumulates historical glue application parameters and glue surface effect data, iteratively optimizes the glue flow calculation logic, and adapts to fluctuations in ambient temperature and glue viscosity.

7. The intelligent adhesive application control method for insulating glass according to claim 1, characterized in that: The first detector, the second detector, and the third detector employ mechanical or optical detection structures.

8. The intelligent adhesive coating control method for insulating glass according to claim 1, characterized in that: In step S4, the mixer is either a static mixer or a dynamic mixer; the metering adhesive supply system precisely controls the displacement or rotation speed to extrude the A group main agent and the B group curing agent in a proportional and quantitative manner.

9. The intelligent adhesive coating control method for insulating glass according to claim 1, characterized in that: The operating terminal adopts an HMI touch screen or a PC industrial display. The operating terminal interacts with the controller in real time, issues control commands, and provides feedback on the equipment's operating status.

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