CN117032151A - Dispensing path planning method and system based on attitude control - Google Patents
Dispensing path planning method and system based on attitude control Download PDFInfo
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- CN117032151A CN117032151A CN202311299422.9A CN202311299422A CN117032151A CN 117032151 A CN117032151 A CN 117032151A CN 202311299422 A CN202311299422 A CN 202311299422A CN 117032151 A CN117032151 A CN 117032151A
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Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by quality surveillance of production
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
- B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
- B05C11/1005—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to condition of liquid or other fluent material already applied to the surface, e.g. coating thickness, weight or pattern
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
- B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
- B05C11/1007—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to condition of liquid or other fluent material
- B05C11/1013—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to condition of liquid or other fluent material responsive to flow or pressure of liquid or other fluent material
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
- B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
- B05C11/1015—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to a conditions of ambient medium or target, e.g. humidity, temperature ; responsive to position or movement of the coating head relative to the target
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C11/00—Component parts, details or accessories not specifically provided for in groups B05C1/00 - B05C9/00
- B05C11/10—Storage, supply or control of liquid or other fluent material; Recovery of excess liquid or other fluent material
- B05C11/1002—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves
- B05C11/1015—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to a conditions of ambient medium or target, e.g. humidity, temperature ; responsive to position or movement of the coating head relative to the target
- B05C11/1018—Means for controlling supply, i.e. flow or pressure, of liquid or other fluent material to the applying apparatus, e.g. valves responsive to a conditions of ambient medium or target, e.g. humidity, temperature ; responsive to position or movement of the coating head relative to the target responsive to distance of target
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C—APPARATUS FOR APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05C5/00—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work
- B05C5/02—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work the liquid or other fluent material being discharged through an outlet orifice by pressure, e.g. from an outlet device in contact or almost in contact, with the work
- B05C5/0208—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work the liquid or other fluent material being discharged through an outlet orifice by pressure, e.g. from an outlet device in contact or almost in contact, with the work for applying liquid or other fluent material to separate articles
- B05C5/0212—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work the liquid or other fluent material being discharged through an outlet orifice by pressure, e.g. from an outlet device in contact or almost in contact, with the work for applying liquid or other fluent material to separate articles only at particular parts of the articles
- B05C5/0216—Apparatus in which liquid or other fluent material is projected, poured or allowed to flow on to the surface of the work the liquid or other fluent material being discharged through an outlet orifice by pressure, e.g. from an outlet device in contact or almost in contact, with the work for applying liquid or other fluent material to separate articles only at particular parts of the articles by relative movement of article and outlet according to a predetermined path
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- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
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Abstract
The application discloses a dispensing path planning method and system based on gesture control, comprising the following steps: constructing a workpiece three-dimensional model, and acquiring a workpiece adhesive dispensing position and a defect position based on the workpiece three-dimensional model; generating an optimal glue dispensing path by using a path planning algorithm based on the glue dispensing position of the workpiece, and performing glue dispensing test on the workpiece based on the optimal glue dispensing path to realize the optimization treatment of the glue dispensing process; and finally, carrying out glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection. According to the application, a dispensing path with good dispensing effect can be generated based on the characteristics of the workpiece and the gesture of the dispensing machine, so that the dispensing operation of the workpiece is realized, and the dispensing treatment efficiency is improved.
Description
Technical Field
The application relates to the field of path planning, in particular to a dispensing path planning method and system based on gesture control.
Background
At the joints on some metal and plastic workpieces, it is often necessary to use glue to bond the workpieces together, and the purpose of the dispensing process during the production of the workpieces is to apply the glue at specific locations. The glue dispensing machine has the function of coating glue on the workpiece according to a set route to finish the manufacture of the workpiece. Because the shape and the size of the workpiece are inconsistent, and the positions where dispensing is required are also inconsistent, the dispensing mode, the glue consumption and the dispensing sequence are also different. Different dispensing paths are planned according to different workpieces, and meanwhile, the working parameter memory dispensing paths of the dispensing machine are required to be updated in real time, so that the efficiency and the speed of the dispensing process are improved.
Disclosure of Invention
The application overcomes the defects of the prior art and provides a dispensing path planning method and system based on gesture control.
In order to achieve the above purpose, the application adopts the following technical scheme:
the first aspect of the application provides a dispensing path planning method based on gesture control, which comprises the following steps:
constructing a workpiece three-dimensional model, analyzing the workpiece three-dimensional model to obtain a workpiece spot-gluing position, and marking a defect position in the workpiece spot-gluing position;
analyzing the workpiece adhesive dispensing position and the marking position, and generating an optimal adhesive dispensing path based on a path planning algorithm;
combining and analyzing the optimal glue path and the marking position, controlling the glue consumption in the glue dispensing process, and optimizing the glue dispensing process by performing a glue dispensing test on a workpiece sample;
and (3) performing glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection.
Further, in a preferred embodiment of the present application, the construction of the three-dimensional model of the workpiece, the analysis of the three-dimensional model of the workpiece, the obtaining of the position where the workpiece can be dispensed, and the marking of the defect position in the position where the workpiece can be dispensed, specifically:
acquiring all workpiece surface images, and performing image preprocessing on the workpiece surface images to obtain preprocessed workpiece surface images;
performing image threshold segmentation processing on the preprocessed workpiece surface image to obtain workpiece surface parameters, constructing a workpiece three-dimensional model in a three-dimensional space, acquiring specification parameters of the workpiece, and constructing a standard workpiece three-dimensional model;
performing model comparison analysis on the workpiece three-dimensional model and the standard workpiece three-dimensional model to obtain a model deviation value, and reserving the workpiece with the model deviation value within a preset range to define the workpiece as a spot-size-capable workpiece;
acquiring a preset dispensing position of the workpiece based on the historical data, and defining a corresponding position in the workpiece capable of dispensing as a workpiece capable of dispensing based on the preset dispensing position of the workpiece;
and obtaining a defect position of the workpiece which can be dispensed according to the model deviation value, and marking the corresponding position when the defect position exists in the dispensing position of the workpiece, so as to define the marking position.
Further, in a preferred embodiment of the present application, the analyzing the workpiece dispensing position and the marking position, and generating the optimal dispensing path based on the path planning algorithm specifically includes:
analyzing the workpiece spot-gluing position, obtaining the inflection point position of the workpiece spot-gluing position, and taking the inflection point position as the starting point and the end point of a spot-gluing branch path;
introducing a linear path planning algorithm and a B spline curve path planning algorithm, acquiring all dispensing branch paths of the workpiece based on the inflection point position of the workpiece at the dispensing position, and removing the dispensing branch paths which do not accord with the dispensing property;
guiding all reserved dispensing branch paths into a convolutional neural network for random permutation and combination prediction to obtain a first dispensing path set;
obtaining dispensing completion degrees of all dispensing paths in a first dispensing path set, removing dispensing paths with the dispensing completion degrees smaller than a preset value, and enabling the dispensing completion degrees to be in a dispensing path set within a preset range to obtain a second dispensing path set;
analyzing the second dispensing path set, obtaining dispensing time of all dispensing paths, constructing a dispensing time sorting table, analyzing the dispensing time sorting table, and defining the dispensing path with the minimum dispensing time as the optimal dispensing path.
Further, in a preferred embodiment of the present application, the combination analysis of the optimal glue path and the marking position is performed, the glue consumption in the glue dispensing process is controlled, and the glue dispensing process is optimized by performing a glue dispensing test on the workpiece sample, which specifically includes:
obtaining the path length of the optimal glue path of the workpiece, obtaining the flow of a dispensing machine nozzle in the dispensing process, and combining to obtain the initial required glue consumption of the workpiece;
obtaining the defect depth and the defect area of the workpiece marking position, obtaining the glue consumption required by the workpiece marking position according to the defect depth and the defect area, and combining the preliminary required glue consumption of the workpiece to obtain the required glue consumption of the workpiece;
randomly extracting a workpiece to serve as a workpiece sample, acquiring the solidification rate of glue at room temperature, introducing the solidification rate of the glue at room temperature, the required glue amount of the workpiece, the required glue amount of a workpiece marking position and the path length of a workpiece optimal glue path into a convolutional neural network model for convolutional processing, generating a workpiece dispensing rate, and performing a dispensing test on the workpiece sample by a dispensing machine according to the workpiece dispensing rate;
in the dispensing test process, if the glue attaching position is not in the range of the optimal glue path of the workpiece, defining the corresponding glue attaching position as a glue attaching abnormal position, and acquiring the shortest distance between the glue attaching abnormal position and the optimal glue path of the workpiece;
judging the glue consumption of the abnormal glue adhesion position, if the glue consumption of the abnormal glue adhesion position is smaller than a preset value and the shortest distance is within a preset range, acquiring the temperature parameter of the position of the workpiece, and acquiring the correlation value of the temperature parameter of the position of the workpiece and the glue consumption of the abnormal glue adhesion position by using a gray correlation method;
if the correlation value is larger than the preset value, the temperature parameter of the position where the workpiece is located is intelligently regulated and controlled, so that outflow of glue is prevented;
if the association value is smaller than the preset value, regulating and controlling the glue flow direction posture of the abnormal glue adhesion position, and preventing the glue from flowing out;
if the glue consumption of the glue adhesion abnormal position is smaller than a preset value and the shortest distance is larger than the preset value, recording the nozzle gesture corresponding to the current glue adhesion abnormal position, and defining the nozzle gesture as a nozzle type abnormal gesture;
if the glue consumption of the glue adhesion abnormal position is larger than a preset value, recording the nozzle gesture corresponding to the current glue adhesion abnormal position, and defining the nozzle gesture as a nozzle type II abnormal gesture;
based on the abnormal gestures of the nozzle and the abnormal gestures of the nozzle, the gesture of the dispensing machine is intelligently regulated and controlled to obtain the optimized dispensing machine.
Further, in a preferred embodiment of the present application, the intelligent posture adjustment and control are performed on the dispensing machine according to the abnormal postures based on the nozzle type and the abnormal postures based on the nozzle type, so as to obtain an optimized dispensing machine, which specifically comprises:
when the nozzle gesture of the dispensing machine is in an abnormal gesture such as a nozzle gesture, proving that the dispensing machine has glue sputtering in the dispensing process, acquiring the height distance between the nozzle and the surface of a workpiece, and presetting a standard height distance threshold;
controlling the height distance between the nozzle and the surface of the workpiece within the standard height distance threshold, acquiring the sputtering quantity of the glue adhesion abnormal positions corresponding to different height distances, and taking the height distance with the minimum sputtering quantity of the glue adhesion abnormal positions as the working height of the nozzle;
when the nozzle is positioned at the working height of the nozzle, but the sputtering quantity of the abnormal positions of the adhesion of the glue is still larger than a preset value, performing anti-sputtering treatment on the abnormal positions of the adhesion of the glue, and preventing the glue from sputtering on the surface of a workpiece;
when the nozzle posture of the dispensing machine is in the second abnormal nozzle posture, acquiring an included angle between the working direction of the nozzle and the surface of the workpiece, defining the included angle as a working included angle of the nozzle, and re-fixing the nozzle and re-performing the dispensing test based on the working included angle of the nozzle;
if the abnormal position of the glue adhesion still occurs, a Bayesian network is introduced, the abnormal position of the glue dispensing machine is obtained by combining the working included angle of the nozzle and the working parameters of the glue dispensing machine, the working parameters of the abnormal position of the glue dispensing machine are obtained, the abnormal parameters are defined as abnormal parameters, the abnormal parameters are regulated and controlled until the abnormal position of the glue adhesion does not occur on the workpiece, and the optimized glue dispensing machine is obtained.
Further, in a preferred embodiment of the present application, the glue quality detection is performed on the workpiece after the glue dispensing, and the reworking is performed on the workpiece with unqualified glue quality detection, specifically:
performing dispensing treatment on all the dispensing workpieces by using an optimized dispensing machine to obtain dispensing workpieces after dispensing, wherein the dispensing workpieces are defined as finished workpieces;
performing glue quality detection on glue on a finished workpiece, wherein the glue quality detection comprises glue solidification state detection, glue color detection and glue adhesion performance detection;
acquiring a glue solidification state and the surface temperature of a workpiece, and if the glue solidification state is smaller than a preset solidification state, regulating and controlling the temperature of the surface of the workpiece, reducing the surface temperature of the workpiece, and accelerating the solidification of the glue;
using a spectrophotometer to obtain the glue color of the finished workpiece, obtaining the standard color of the glue after dispensing and solidification based on big data retrieval, calculating the color difference value of the glue color of the finished workpiece and the standard color, and obtaining the distribution rate of the glue with the color difference value larger than a preset value in the finished workpiece;
if the distribution rate of the glue of which the color difference value of the finished workpiece is larger than the preset value, removing the glue of the corresponding finished workpiece, replacing the glue batch and the glue type, and performing glue re-dispensing treatment on the glue-dispensing workpiece;
and randomly extracting a finished workpiece sample to detect the adhesive property of the glue, if the adhesive property of the glue is unqualified, removing the glue of the finished workpiece, stirring the glue to obtain the glue with bubbles removed, and performing re-dispensing treatment on the glue-dispensing workpiece by using the glue with bubbles removed by the optimized dispensing machine.
The second aspect of the present application also provides a dispensing path planning system based on gesture control, the dispensing path planning system includes a memory and a processor, the memory stores a dispensing path planning method based on gesture control, and when the dispensing path planning method based on gesture control is executed by the processor, the following steps are implemented:
constructing a workpiece three-dimensional model, analyzing the workpiece three-dimensional model to obtain a workpiece spot-gluing position, and marking a defect position in the workpiece spot-gluing position;
analyzing the workpiece adhesive dispensing position and the marking position, and generating an optimal adhesive dispensing path based on a path planning algorithm;
combining and analyzing the optimal glue path and the marking position, controlling the glue consumption in the glue dispensing process, and optimizing the glue dispensing process by performing a glue dispensing test on a workpiece sample;
and (3) performing glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection.
The application solves the technical defects in the background technology, and has the following beneficial effects: constructing a workpiece three-dimensional model, and acquiring a workpiece adhesive dispensing position and a defect position based on the workpiece three-dimensional model; generating an optimal glue dispensing path by using a path planning algorithm based on the glue dispensing position of the workpiece, and performing glue dispensing test on the workpiece based on the optimal glue dispensing path to realize the optimization treatment of the glue dispensing process; and finally, carrying out glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection. According to the application, a dispensing path with good dispensing effect can be generated based on the characteristics of the workpiece and the gesture of the dispensing machine, so that the dispensing operation of the workpiece is realized, and the dispensing treatment efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other embodiments of the drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a flow chart of a dispensing path planning method based on attitude control;
FIG. 2 shows a flow chart of a method for dispensing test and dispensing optimization of a workpiece sample;
fig. 3 shows a view of a dispensing path planning system based on gesture control.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.
Fig. 1 shows a flow chart of a dispensing path planning method based on gesture control, comprising the following steps:
s102: constructing a workpiece three-dimensional model, analyzing the workpiece three-dimensional model to obtain a workpiece spot-gluing position, and marking a defect position in the workpiece spot-gluing position;
s104: analyzing the workpiece adhesive dispensing position and the marking position, and generating an optimal adhesive dispensing path based on a path planning algorithm;
s106: combining and analyzing the optimal glue path and the marking position, controlling the glue consumption in the glue dispensing process, and optimizing the glue dispensing process by performing a glue dispensing test on a workpiece sample;
s108: and (3) performing glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection.
Further, in a preferred embodiment of the present application, the construction of the three-dimensional model of the workpiece, the analysis of the three-dimensional model of the workpiece, the obtaining of the position where the workpiece can be dispensed, and the marking of the defect position in the position where the workpiece can be dispensed, specifically:
acquiring all workpiece surface images, and performing image preprocessing on the workpiece surface images to obtain preprocessed workpiece surface images;
performing image threshold segmentation processing on the preprocessed workpiece surface image to obtain workpiece surface parameters, constructing a workpiece three-dimensional model in a three-dimensional space, acquiring specification parameters of the workpiece, and constructing a standard workpiece three-dimensional model;
performing model comparison analysis on the workpiece three-dimensional model and the standard workpiece three-dimensional model to obtain a model deviation value, and reserving the workpiece with the model deviation value within a preset range to define the workpiece as a spot-size-capable workpiece;
acquiring a preset dispensing position of the workpiece based on the historical data, and defining a corresponding position in the workpiece capable of dispensing as a workpiece capable of dispensing based on the preset dispensing position of the workpiece;
and obtaining a defect position of the workpiece which can be dispensed according to the model deviation value, and marking the corresponding position when the defect position exists in the dispensing position of the workpiece, so as to define the marking position.
After the image preprocessing and the image threshold segmentation processing are performed on the workpiece, the obtained workpiece surface parameters reflect the parameters such as lines, colors and the like of the workpiece surface, and then the workpiece three-dimensional model and the standard workpiece three-dimensional model can be constructed by combining the specification parameters of the workpiece. The workpiece may have defects in the production process, deviation values are obtained through model comparison, and the defect positions and defect conditions of the workpiece can be judged by analyzing the deviation values, so that the workpiece which can be dispensed, the workpiece dispensing position and the marking position are obtained.
Further, in a preferred embodiment of the present application, the analyzing the workpiece dispensing position and the marking position, and generating the optimal dispensing path based on the path planning algorithm specifically includes:
analyzing the workpiece spot-gluing position, obtaining the inflection point position of the workpiece spot-gluing position, and taking the inflection point position as the starting point and the end point of a spot-gluing branch path;
introducing a linear path planning algorithm and a B spline curve path planning algorithm, acquiring all dispensing branch paths of the workpiece based on the inflection point position of the workpiece at the dispensing position, and removing the dispensing branch paths which do not accord with the dispensing property;
guiding all reserved dispensing branch paths into a convolutional neural network for random permutation and combination prediction to obtain a first dispensing path set;
obtaining dispensing completion degrees of all dispensing paths in a first dispensing path set, removing dispensing paths with the dispensing completion degrees smaller than a preset value, and enabling the dispensing completion degrees to be in a dispensing path set within a preset range to obtain a second dispensing path set;
analyzing the second dispensing path set, obtaining dispensing time of all dispensing paths, constructing a dispensing time sorting table, analyzing the dispensing time sorting table, and defining the dispensing path with the minimum dispensing time as the optimal dispensing path.
It should be noted that, the workpiece needs to be at the position where the workpiece can be dispensed to perform dispensing treatment. The purpose of taking the inflection point position as the starting point and the end point of the dispensing branch path is that the inflection point position is convenient for dispensing in a plurality of directions, and the efficiency is higher. The dispensing branch path is a path from a starting point to an ending point in the dispensing process, and is formed by combining a plurality of dispensing branch paths. The linear path planning algorithm is used for acquiring the linear dispensing branch path, and the B-spline curve path planning algorithm is used for acquiring the curve dispensing branch path. The dispensing property is a dispensing branch path requiring manual intervention in the dispensing process. The dispensing completion degrees of different dispensing paths are different, and the lower the dispensing completion degree is, the higher the rejection rate of the workpiece is. The faster the dispensing time, the higher the efficiency, so the dispensing path with the least dispensing time is obtained and defined as the optimal dispensing path.
Further, in a preferred embodiment of the present application, the glue quality detection is performed on the workpiece after the glue dispensing, and the reworking is performed on the workpiece with unqualified glue quality detection, specifically:
performing dispensing treatment on all the dispensing workpieces by using an optimized dispensing machine to obtain dispensing workpieces after dispensing, wherein the dispensing workpieces are defined as finished workpieces;
performing glue quality detection on glue on a finished workpiece, wherein the glue quality detection comprises glue solidification state detection, glue color detection and glue adhesion performance detection;
acquiring a glue solidification state and the surface temperature of a workpiece, and if the glue solidification state is smaller than a preset solidification state, regulating and controlling the temperature of the surface of the workpiece, reducing the surface temperature of the workpiece, and accelerating the solidification of the glue;
using a spectrophotometer to obtain the glue color of the finished workpiece, obtaining the standard color of the glue after dispensing and solidification based on big data retrieval, calculating the color difference value of the glue color of the finished workpiece and the standard color, and obtaining the distribution rate of the glue with the color difference value larger than a preset value in the finished workpiece;
if the distribution rate of the glue of which the color difference value of the finished workpiece is larger than the preset value, removing the glue of the corresponding finished workpiece, replacing the glue batch and the glue type, and performing glue re-dispensing treatment on the glue-dispensing workpiece;
and randomly extracting a finished workpiece sample to detect the adhesive property of the glue, if the adhesive property of the glue is unqualified, removing the glue of the finished workpiece, stirring the glue to obtain the glue with bubbles removed, and performing re-dispensing treatment on the glue-dispensing workpiece by using the glue with bubbles removed by the optimized dispensing machine.
It should be noted that, after the dispensing treatment is performed on the workpiece capable of being dispensed by using the optimized dispensing machine, a finished workpiece is obtained. In order to ensure the qualification rate, quality detection needs to be carried out on finished workpieces, wherein the quality detection comprises glue solidification state detection, glue color detection and glue adhesion performance detection. The better the solidification state of the glue, the better the effect of the adhesion between the workpieces by means of the glue. The solidification state of the glue is related to the surface temperature of the workpiece, and the surface temperature of the workpiece is reduced, so that the solidification of the glue can be accelerated. The spectrophotometer can obtain the color value of the glue of a finished workpiece, and the glue can be subjected to oxidation reaction with air, so that color change is generated. If the color difference between the glue color and the standard color is larger, it proves that other oxidation reactions may occur in the glue, so that the adhesiveness of the glue is reduced, and therefore, the glue of the finished workpiece needs to be removed, the glue batch or the glue type is replaced, and the glue which is not easy to oxidize is selected to perform the glue re-dispensing treatment on the glue-dispensing workpiece. And detecting the adhesiveness of the glue, if the glue is unqualified, the workpiece may have potential safety hazards, and the glue of the finished workpiece needs to be clear. The reason for the disqualification of the adhesive property of the glue is that bubbles exist between the glue, which affects the adhesive property of the glue. Stirring treatment is carried out on the glue, and bubbles can be removed from the glue. The application can detect the quality of the finished workpiece and rework the workpiece with unqualified glue quality detection.
FIG. 2 shows a flow chart of a method for dispensing test and dispensing optimization of a workpiece sample, comprising the steps of:
s202: the glue consumption in the glue dispensing process is obtained, and the glue dispensing process is optimized by carrying out glue dispensing test on a workpiece sample;
s204: repairing and regulating abnormal postures such as nozzles;
s206: and repairing and regulating the abnormal states of the nozzle type II.
Further, in a preferred embodiment of the present application, the method includes the steps of obtaining a glue amount in a dispensing process, and optimizing the dispensing process by performing a dispensing test on a workpiece sample, specifically:
obtaining the path length of the optimal glue path of the workpiece, obtaining the flow of a dispensing machine nozzle in the dispensing process, and combining to obtain the initial required glue consumption of the workpiece;
obtaining the defect depth and the defect area of the workpiece marking position, obtaining the glue consumption required by the workpiece marking position according to the defect depth and the defect area, and combining the preliminary required glue consumption of the workpiece to obtain the required glue consumption of the workpiece;
randomly extracting a workpiece to serve as a workpiece sample, acquiring the solidification rate of glue at room temperature, introducing the solidification rate of the glue at room temperature, the required glue amount of the workpiece, the required glue amount of a workpiece marking position and the path length of a workpiece optimal glue path into a convolutional neural network model for convolutional processing, generating a workpiece dispensing rate, and performing a dispensing test on the workpiece sample by a dispensing machine according to the workpiece dispensing rate;
in the dispensing test process, if the glue attaching position is not in the range of the optimal glue path of the workpiece, defining the corresponding glue attaching position as a glue attaching abnormal position, and acquiring the shortest distance between the glue attaching abnormal position and the optimal glue path of the workpiece;
judging the glue consumption of the abnormal glue adhesion position, if the glue consumption of the abnormal glue adhesion position is smaller than a preset value and the shortest distance is within a preset range, acquiring the temperature parameter of the position of the workpiece, and acquiring the correlation value of the temperature parameter of the position of the workpiece and the glue consumption of the abnormal glue adhesion position by using a gray correlation method;
if the correlation value is larger than the preset value, the temperature parameter of the position where the workpiece is located is intelligently regulated and controlled, so that outflow of glue is prevented;
if the correlation value is smaller than the preset value, regulating and controlling the glue flow direction and the gesture of the abnormal glue adhesion position, and preventing the glue from flowing out.
It should be noted that, the preliminary required glue amount of the workpiece means the glue amount required for dispensing the workpiece in a perfect and defect-free state. Because the workpiece may have defects, the mark positions are defect positions, and the defect positions need to be larger in glue amount to ensure the consistency of the glue. It is necessary to obtain the glue amount required for the marking position of the workpiece, so as to obtain the glue amount required by the craftsman. In the dispensing process, the angular rate of the dispensing point needs to be determined, so that the glue can be better solidified, is not diffused in the dispensing process, and the utilization rate of the glue is better improved. Therefore, the workpiece dispensing speed is obtained through the convolutional neural network model, and a dispensing test is carried out on a workpiece sample, so that the possible problems in the dispensing process are found and corrected. In the process of dispensing the workpiece by the dispensing machine, the glue should be dispensed along the optimal glue path. The shortest distance between the abnormal position of glue adhesion and the preliminary glue dispensing path of the workpiece is obtained, and the occurrence reason of the abnormal position of glue adhesion can be judged. The abnormal positions of the adhesion of the glue are caused by slower solidification speed of the glue after dispensing, so that the glue flows to other positions. Another occurrence is that the nozzle posture of the dispensing machine is problematic, the nozzle inclination causes the error of the dispensing position, or the glue is sputtered to other positions during the dispensing. When the glue quantity at the abnormal position of the glue adhesion is small and the shortest distance is within the preset range, the flowing state of the glue is proved, and the glue is prevented from flowing out to other positions by regulating and controlling the temperature or regulating and controlling the glue flow direction and the gesture at the abnormal position of the glue adhesion. The glue flow direction posture regulation and control on the abnormal glue adhesion position can be realized by installing a glue outflow-preventing protection facility. According to the application, the dispensing test can be carried out on the workpiece sample, so that the dispensing process is optimized.
Further, in a preferred embodiment of the present application, the repairing and controlling for the abnormal gesture of the nozzle includes:
if the glue consumption of the glue adhesion abnormal position is smaller than a preset value and the shortest distance is larger than the preset value, recording the nozzle gesture corresponding to the current glue adhesion abnormal position, and defining the nozzle gesture as a nozzle type abnormal gesture;
when the nozzle gesture of the dispensing machine is in an abnormal gesture such as a nozzle gesture, proving that the dispensing machine has glue sputtering in the dispensing process, acquiring the height distance between the nozzle and the surface of a workpiece, and presetting a standard height distance threshold;
controlling the height distance between the nozzle and the surface of the workpiece within the standard height distance threshold, acquiring the sputtering quantity of the glue adhesion abnormal positions corresponding to different height distances, and taking the height distance with the minimum sputtering quantity of the glue adhesion abnormal positions as the working height of the nozzle;
when the nozzle is at the working height of the nozzle, but the sputtering quantity of the abnormal positions of the adhesion of the glue is still larger than a preset value, the abnormal positions of the adhesion of the glue are subjected to sputtering prevention treatment, and the glue is prevented from sputtering on the surface of the workpiece.
It should be noted that, the nozzle height is too high, can make glue sputter in the point gum in-process, and the state of nozzle is the unusual gesture of nozzle class this moment. The spray nozzle is highly regulated and controlled, the sputtering condition of glue is reduced, if the spray nozzle still has the sputtering condition at the optimal height, the anti-sputtering treatment is carried out on the abnormal position of the adhesion of the glue, the anti-sputtering treatment can be realized by installing a glue anti-sputtering protection facility on the optimal glue path, and the glue anti-sputtering protection facility can protect workpieces from the sputtering influence of the glue. The application can analyze abnormal gestures of the nozzle and optimize the dispensing machine, thereby improving the qualification rate of key finished products.
Further, in a preferred embodiment of the present application, the repairing and controlling the abnormal gesture of the second class of nozzle specifically includes:
if the glue consumption of the glue adhesion abnormal position is larger than a preset value, recording the nozzle gesture corresponding to the current glue adhesion abnormal position, and defining the nozzle gesture as a nozzle type II abnormal gesture;
when the nozzle posture of the dispensing machine is in the second abnormal nozzle posture, acquiring an included angle between the working direction of the nozzle and the surface of the workpiece, defining the included angle as a working included angle of the nozzle, and re-fixing the nozzle and re-performing the dispensing test based on the working included angle of the nozzle;
if the abnormal position of the glue adhesion still occurs, a Bayesian network is introduced, the abnormal position of the glue dispensing machine is obtained by combining the working included angle of the nozzle and the working parameters of the glue dispensing machine, the working parameters of the abnormal position of the glue dispensing machine are obtained, the abnormal parameters are defined as abnormal parameters, the abnormal parameters are regulated and controlled until the abnormal position of the glue adhesion does not occur on the workpiece, and the optimized glue dispensing machine is obtained.
It should be noted that, the glue dosage at the abnormal position of glue adhesion is larger, and the working direction and the angle of the nozzle of the dispensing machine are proved to be askew, so that correction is required. The larger the angle of the working included angle of the nozzle, the larger the deviation degree of the working direction of the nozzle is proved. Based on the angle of the working included angle of the nozzle, the nozzle is re-fixed, so that the nozzle cannot deviate in the dispensing process. If the abnormal positions of the glue adhesion still occur after the fixing, the problem that the inside of the dispensing machine is possibly solved is judged, and the deviation is easy to occur in the dispensing process of the nozzle. And analyzing working parameters of the dispensing machine and a working included angle of the nozzle by using a Bayesian network, and tracing the abnormal position of the dispensing machine so as to perform targeted repair. According to the application, the dispensing operation optimization can be realized by controlling the working included angle of the nozzle, and the fault tracing and repairing are performed on the dispensing machine through a Bayesian network.
In addition, the dispensing path planning method based on gesture control further comprises the following steps:
acquiring the surface color of the workpiece capable of being dispensed based on the workpiece three-dimensional model, and acquiring the surface standard color of the workpiece capable of being dispensed;
if the color difference between the surface color of the workpiece capable of being dispensed and the standard surface color is larger than a preset value, defining the corresponding workpiece capable of being dispensed as a surface polluted workpiece;
performing surface sampling and detection treatment on the abnormal surface color position of the spot-size-adjustable workpiece to obtain chemical components of the abnormal surface color position of the spot-size-adjustable workpiece, and discarding the corresponding spot-size-adjustable workpiece if the coverage rate of the abnormal surface color position of the spot-size-adjustable workpiece is larger than a preset value;
if the coverage rate of the abnormal color position on the surface of the workpiece capable of being subjected to dispensing is within a preset range, searching a corresponding processing method based on big data, and performing surface cleaning treatment on the workpiece capable of being subjected to dispensing;
analyzing the color abnormal position of the surface of the dispensing workpiece if the surface of the dispensing workpiece is still abnormal after the surface cleaning treatment is carried out on the dispensing workpiece, analyzing the dispensing time sorting table if the color abnormal position of the surface of the dispensing workpiece is coincident with the optimal dispensing path, selecting a dispensing path which is not coincident with the color abnormal position of the surface of the dispensing workpiece, and outputting a dispensing path with relatively minimum dispensing time;
and if all the dispensing paths coincide with the abnormal surface color positions of the workpiece capable of being dispensed, discarding the corresponding workpiece capable of being dispensed.
It should be noted that, the workpiece may be careless during the production process, so that the surface of the workpiece may be attached with pollutants such as oil stains, and the pollutants such as oil stains may affect the appearance of the workpiece on the surface of the workpiece, and the adhesiveness of the glue may be reduced, so that the curing process of the glue is interfered, and the workpiece is not qualified. It is necessary to clean contaminants such as oil stains. If the coverage rate of pollutants such as greasy dirt is large, the workpiece is unqualified and is directly abandoned; if the pollutants such as oil stains on the surface of the workpiece cannot be completely cleaned, determining whether the pollutants coincide with the dispensing paths or not is needed, if not, the dispensing operation can be normally performed, if so, additional dispensing paths are needed to be selected, and if all the dispensing paths coincide with the pollutants, the corresponding workpiece which can be dispensed is proved to be unqualified and is needed to be directly discarded. The application can clean the workpiece by judging the color of the surface of the workpiece and optimize the dispensing path.
In addition, the dispensing path planning method based on gesture control further comprises the following steps:
acquiring factory order information, wherein the factory order information comprises dispensing precision of a target workpiece;
acquiring rated working parameters of all dispensing machines in a factory, and generating a training set and a testing set;
introducing the training set into a convolution layer of a convolution neural network model for convolution processing to obtain a convolution value, and carrying out maximum pooling processing on the convolution value to obtain a pooling value;
performing reverse training on the pooling value by using a cross entropy function until the error converges to the minimum, and performing testing by using a testing set to obtain the working precision prediction parameter of the dispensing machine;
according to the working precision prediction parameters of the dispensing machine, the working precision change rate of the dispensing machine is obtained, and based on the dispensing precision of the target workpiece, the dispensing machine with the working precision smaller than a preset value and the working precision meeting the dispensing precision of the workpiece is selected as the dispensing machine of the target workpiece and defined as the target dispensing machine;
and (3) performing dispensing treatment on the target point glue workpiece by using the target point glue machine, monitoring the dispensing precision of the target point glue machine in real time, and replacing the dispensing machine to perform dispensing treatment on the target workpiece when the dispensing precision of the target point glue machine is smaller than the preset dispensing precision.
It should be noted that, the dispensing precision of the workpieces of different orders is different, the dispensing precision of each dispensing machine is also different, the working precision change condition of the dispensing machine can be obtained by using the convolutional neural network, the dispensing precision of each dispensing machine is combined, the target point dispensing machine of the target workpiece can be determined, the dispensing precision is required to be selected to meet the dispensing precision of the target workpiece, and the working precision change rate is smaller. If the dispensing precision of the dispensing machine is smaller than the preset dispensing precision in the dispensing process, the target workpiece becomes an unqualified product after the dispensing process is continued, so that the dispensing machine needs to be replaced to perform the dispensing process on the target workpiece.
As shown in fig. 3, the second aspect of the present application further provides a dispensing path planning system based on gesture control, where the dispensing path planning system includes a memory 31 and a processor 32, the memory 31 stores a dispensing path planning method based on gesture control, and when the dispensing path planning method based on gesture control is executed by the processor 32, the following steps are implemented:
constructing a workpiece three-dimensional model, analyzing the workpiece three-dimensional model to obtain a workpiece spot-gluing position, and marking a defect position in the workpiece spot-gluing position;
analyzing the workpiece adhesive dispensing position and the marking position, and generating an optimal adhesive dispensing path based on a path planning algorithm;
combining and analyzing the optimal glue path and the marking position, controlling the glue consumption in the glue dispensing process, and optimizing the glue dispensing process by performing a glue dispensing test on a workpiece sample;
and (3) performing glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection.
The foregoing is merely illustrative embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present application, and the application should be covered. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (7)
1. The dispensing path planning method based on gesture control is characterized by comprising the following steps of:
constructing a workpiece three-dimensional model, analyzing the workpiece three-dimensional model to obtain a workpiece spot-gluing position, and marking a defect position in the workpiece spot-gluing position;
analyzing the workpiece adhesive dispensing position and the marking position, and generating an optimal adhesive dispensing path based on a path planning algorithm;
combining and analyzing the optimal glue path and the marking position, controlling the glue consumption in the glue dispensing process, and optimizing the glue dispensing process by performing a glue dispensing test on a workpiece sample;
and (3) performing glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection.
2. The dispensing path planning method based on gesture control according to claim 1, wherein the constructing a three-dimensional model of the workpiece, analyzing the three-dimensional model of the workpiece to obtain a workpiece dispensing position, and marking a defect position in the workpiece dispensing position comprises:
acquiring all workpiece surface images, and performing image preprocessing on the workpiece surface images to obtain preprocessed workpiece surface images;
performing image threshold segmentation processing on the preprocessed workpiece surface image to obtain workpiece surface parameters, constructing a workpiece three-dimensional model in a three-dimensional space, acquiring specification parameters of the workpiece, and constructing a standard workpiece three-dimensional model;
performing model comparison analysis on the workpiece three-dimensional model and the standard workpiece three-dimensional model to obtain a model deviation value, and reserving the workpiece with the model deviation value within a preset range to define the workpiece as a spot-size-capable workpiece;
acquiring a preset dispensing position of the workpiece based on the historical data, and defining a corresponding position in the workpiece capable of dispensing as a workpiece capable of dispensing based on the preset dispensing position of the workpiece;
and obtaining a defect position of the workpiece which can be dispensed according to the model deviation value, and marking the corresponding position when the defect position exists in the dispensing position of the workpiece, so as to define the marking position.
3. The dispensing path planning method based on gesture control according to claim 1, wherein the analyzing the workpiece dispensing position and the marking position and generating the optimal dispensing path based on the path planning algorithm specifically comprises:
analyzing the workpiece spot-gluing position, obtaining the inflection point position of the workpiece spot-gluing position, and taking the inflection point position as the starting point and the end point of a spot-gluing branch path;
introducing a linear path planning algorithm and a B spline curve path planning algorithm, acquiring all dispensing branch paths of the workpiece based on the inflection point position of the workpiece at the dispensing position, and removing the dispensing branch paths which do not accord with the dispensing property;
guiding all reserved dispensing branch paths into a convolutional neural network for random permutation and combination prediction to obtain a first dispensing path set;
obtaining dispensing completion degrees of all dispensing paths in a first dispensing path set, removing dispensing paths with the dispensing completion degrees smaller than a preset value, and enabling the dispensing completion degrees to be in a dispensing path set within a preset range to obtain a second dispensing path set;
analyzing the second dispensing path set, obtaining dispensing time of all dispensing paths, constructing a dispensing time sorting table, analyzing the dispensing time sorting table, and defining the dispensing path with the minimum dispensing time as the optimal dispensing path.
4. The dispensing path planning method based on gesture control according to claim 1, wherein the combining analysis of the optimal dispensing path and the marking position, the controlling of the glue consumption in the dispensing process, and the optimizing of the dispensing process by the dispensing test on the workpiece sample, specifically comprises:
obtaining the path length of the optimal glue path of the workpiece, obtaining the flow of a dispensing machine nozzle in the dispensing process, and combining to obtain the initial required glue consumption of the workpiece;
obtaining the defect depth and the defect area of the workpiece marking position, obtaining the glue consumption required by the workpiece marking position according to the defect depth and the defect area, and combining the preliminary required glue consumption of the workpiece to obtain the required glue consumption of the workpiece;
randomly extracting a workpiece to serve as a workpiece sample, acquiring the solidification rate of glue at room temperature, introducing the solidification rate of the glue at room temperature, the required glue amount of the workpiece, the required glue amount of a workpiece marking position and the path length of a workpiece optimal glue path into a convolutional neural network model for convolutional processing, generating a workpiece dispensing rate, and performing a dispensing test on the workpiece sample by a dispensing machine according to the workpiece dispensing rate;
in the dispensing test process, if the glue attaching position is not in the range of the optimal glue path of the workpiece, defining the corresponding glue attaching position as a glue attaching abnormal position, and acquiring the shortest distance between the glue attaching abnormal position and the optimal glue path of the workpiece;
judging the glue consumption of the abnormal glue adhesion position, if the glue consumption of the abnormal glue adhesion position is smaller than a preset value and the shortest distance is within a preset range, acquiring the temperature parameter of the position of the workpiece, and acquiring the correlation value of the temperature parameter of the position of the workpiece and the glue consumption of the abnormal glue adhesion position by using a gray correlation method;
if the correlation value is larger than the preset value, the temperature parameter of the position where the workpiece is located is intelligently regulated and controlled, so that outflow of glue is prevented;
if the association value is smaller than the preset value, regulating and controlling the glue flow direction posture of the abnormal glue adhesion position, and preventing the glue from flowing out;
if the glue consumption of the glue adhesion abnormal position is smaller than a preset value and the shortest distance is larger than the preset value, recording the nozzle gesture corresponding to the current glue adhesion abnormal position, and defining the nozzle gesture as a nozzle type abnormal gesture;
if the glue consumption of the glue adhesion abnormal position is larger than a preset value, recording the nozzle gesture corresponding to the current glue adhesion abnormal position, and defining the nozzle gesture as a nozzle type II abnormal gesture;
based on the abnormal gestures of the nozzle and the abnormal gestures of the nozzle, the gesture of the dispensing machine is intelligently regulated and controlled to obtain the optimized dispensing machine.
5. The dispensing path planning method based on gesture control according to claim 4, wherein the intelligent gesture control is performed on the dispensing machine according to the nozzle-based abnormal gesture and the nozzle-based abnormal gesture, so as to obtain an optimized dispensing machine, specifically:
when the nozzle gesture of the dispensing machine is in an abnormal gesture such as a nozzle gesture, proving that the dispensing machine has glue sputtering in the dispensing process, acquiring the height distance between the nozzle and the surface of a workpiece, and presetting a standard height distance threshold;
controlling the height distance between the nozzle and the surface of the workpiece within the standard height distance threshold, acquiring the sputtering quantity of the glue adhesion abnormal positions corresponding to different height distances, and taking the height distance with the minimum sputtering quantity of the glue adhesion abnormal positions as the working height of the nozzle;
when the nozzle is positioned at the working height of the nozzle, but the sputtering quantity of the abnormal positions of the adhesion of the glue is still larger than a preset value, performing anti-sputtering treatment on the abnormal positions of the adhesion of the glue, and preventing the glue from sputtering on the surface of a workpiece;
when the nozzle posture of the dispensing machine is in the second abnormal nozzle posture, acquiring an included angle between the working direction of the nozzle and the surface of the workpiece, defining the included angle as a working included angle of the nozzle, and re-fixing the nozzle and re-performing the dispensing test based on the working included angle of the nozzle;
if the abnormal position of the glue adhesion still occurs, a Bayesian network is introduced, the abnormal position of the glue dispensing machine is obtained by combining the working included angle of the nozzle and the working parameters of the glue dispensing machine, the working parameters of the abnormal position of the glue dispensing machine are obtained, the abnormal parameters are defined as abnormal parameters, the abnormal parameters are regulated and controlled until the abnormal position of the glue adhesion does not occur on the workpiece, and the optimized glue dispensing machine is obtained.
6. The dispensing path planning method based on gesture control according to claim 1, wherein the glue quality detection is performed on the workpiece after dispensing, and reworking is performed on the workpiece with unqualified glue quality detection, specifically:
performing dispensing treatment on all the dispensing workpieces by using an optimized dispensing machine to obtain dispensing workpieces after dispensing, wherein the dispensing workpieces are defined as finished workpieces;
performing glue quality detection on glue on a finished workpiece, wherein the glue quality detection comprises glue solidification state detection, glue color detection and glue adhesion performance detection;
acquiring a glue solidification state and the surface temperature of a workpiece, and if the glue solidification state is smaller than a preset solidification state, regulating and controlling the temperature of the surface of the workpiece, reducing the surface temperature of the workpiece, and accelerating the solidification of the glue;
using a spectrophotometer to obtain the glue color of the finished workpiece, obtaining the standard color of the glue after dispensing and solidification based on big data retrieval, calculating the color difference value of the glue color of the finished workpiece and the standard color, and obtaining the distribution rate of the glue with the color difference value larger than a preset value in the finished workpiece;
if the distribution rate of the glue of which the color difference value of the finished workpiece is larger than the preset value, removing the glue of the corresponding finished workpiece, replacing the glue batch and the glue type, and performing glue re-dispensing treatment on the glue-dispensing workpiece;
and randomly extracting a finished workpiece sample to detect the adhesive property of the glue, if the adhesive property of the glue is unqualified, removing the glue of the finished workpiece, stirring the glue to obtain the glue with bubbles removed, and performing re-dispensing treatment on the glue-dispensing workpiece by using the glue with bubbles removed by the optimized dispensing machine.
7. The dispensing path planning system based on the gesture control is characterized by comprising a memory and a processor, wherein the memory stores a dispensing path planning method based on the gesture control, and when the dispensing path planning method based on the gesture control is executed by the processor, the following steps are realized:
constructing a workpiece three-dimensional model, analyzing the workpiece three-dimensional model to obtain a workpiece spot-gluing position, and marking a defect position in the workpiece spot-gluing position;
analyzing the workpiece adhesive dispensing position and the marking position, and generating an optimal adhesive dispensing path based on a path planning algorithm;
combining and analyzing the optimal glue path and the marking position, controlling the glue consumption in the glue dispensing process, and optimizing the glue dispensing process by performing a glue dispensing test on a workpiece sample;
and (3) performing glue quality detection on the workpiece subjected to glue dispensing, and reworking the workpiece with unqualified glue quality detection.
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