An automatic programming spray control system based on intelligent visual recognition

Abstract

The present invention discloses an automatic programming spray control system based on intelligent visual recognition, which specifically relates to the field of spray control technology, including an automatic programming spray area division module, an automatic programming spray data acquisition module, an automatic programming spray data analysis module, an automatic programming spray control module, an automatic programming spray comprehensive analysis module and an automatic programming spray human-computer interaction module; the automatic programming spray area division module is used to take the object to be sprayed as the target area, and divide the target area into a number of monitoring sub-areas according to each spray object; the present invention analyzes the spray accuracy parameters to obtain an indicator to measure the current control performance level of the system, which can comprehensively reflect the accuracy and stability of the visual recognition algorithm in the automatic programming spray control system, and can reflect the effectiveness of the path planning algorithm and the accuracy during the execution process, thereby reducing the proportion of repeated spraying areas and improving the spraying efficiency and coating quality.

Description

Technical Field

[0001] The invention relates to the technical field of spraying control, and in particular to an automatic programming spraying control system based on intelligent visual recognition. Background Art

[0002] Intelligent visual recognition technology is a technology that uses computer vision and pattern recognition theory to process image information, giving machines the ability to "see" and enabling them to obtain useful information from images and make analysis and decisions; automatic programming technology is a method that uses computer technology and algorithms to automatically generate codes and complete specific tasks. In spraying operations, the application of intelligent visual recognition technology provides technical support for automatic programming spraying control.

[0003] In industrial production, spraying is an important surface treatment process. Traditional spraying methods mainly rely on manual operation, which is not only inefficient, but also difficult to ensure the quality of spraying, and prone to problems such as uneven coating, too thick or too thin coating. With the development of science and technology, automatic spraying technology has gradually been applied. When faced with complex-shaped workpieces and diverse spraying requirements, it is often difficult to achieve accurate spraying control. Therefore, it is particularly important to accurately control automatic programming spraying.

[0004] Therefore, the present invention proposes an automatic programming spray control system based on intelligent visual recognition to solve the above problems. It adopts intelligent visual recognition technology to realize three-dimensional scanning and detection of the surface of the object, can quickly and accurately obtain the characteristic information of the workpiece, and improves the pertinence and accuracy of the spraying; the automatic programming function automatically plans the spraying trajectory and controls the spraying equipment for precise spraying, which greatly reduces manual intervention, improves production efficiency, and reduces labor costs; it can be flexibly adjusted according to different workpieces and spraying requirements, and has wide applicability. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an automatic programming spray control system based on intelligent visual recognition to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an automatic programming spray control system based on intelligent visual recognition, including an automatic programming spray area division module, an automatic programming spray data acquisition module, an automatic programming spray data analysis module, an automatic programming spray control module, an automatic programming spray comprehensive analysis module and an automatic programming spray human-computer interaction module;

[0007] The automatic programming spraying area division module is used to take the object to be sprayed as the target area, and divide the target area into a plurality of monitoring sub-areas according to each spraying object, which are sequentially recorded as 1, 2, 3, ..., i, ..., n;

[0008] The automatic programming spraying data acquisition module collects data on the spraying characteristic information of the sub-area through intelligent visual recognition technology, obtains a database of various monitoring parameters for analyzing the automatic programming spraying control performance indicators, and outputs the various monitoring parameters to the automatic programming spraying data analysis module;

[0009] The automatic programming spraying data analysis module is used to analyze various monitoring parameters of the data acquisition module, including a spraying accuracy control index analysis unit, a spraying efficiency control index analysis unit, a spraying quality control index analysis unit, and a system intelligence and adaptability control index analysis unit, and outputs the analysis results to the automatic programming spraying control module;

[0010] The automatic programming spraying control module is used to compare the automatic programming spraying control indicators obtained by the data analysis module with the set values, and output the comparison results to the automatic programming spraying comprehensive analysis module;

[0011] The automatic programming spraying comprehensive analysis module is used to comprehensively analyze the efficiency coefficients of various control indicators obtained by the automatic programming spraying control module to obtain comprehensive performance indicators of automatic programming spraying control, and output the comprehensive analysis results to the automatic programming spraying human-computer interaction module;

[0012] The automatic programming spraying human-computer interaction module is used to output the automatic programming spraying control comprehensive performance index transmitted by the above-mentioned comprehensive analysis module to the engineering administrator information terminal.

[0013] Preferably, the monitoring parameters in the automatic programming spraying data acquisition module include target area information, engineering administrator identity authentication information, spraying accuracy parameters, spraying efficiency parameters, spraying quality parameters and system intelligence and adaptability parameters, wherein the spraying accuracy parameters specifically include the number of pixel sampling points at the edge of the spraying object, the edge error of the sampling points, the number of sampling points on the spraying path, the coordinate points of the path, the number of multiple sprayings, the area of ​​the spraying repeated area, the total area of ​​the spraying area and the number of defects marked before and after spraying; the spraying efficiency parameters specifically include the spraying time per unit area, the spraying setting time, the spraying speed, the spraying response time, the continuous spraying time and the spraying time; the spraying quality parameters specifically include the number of coating thickness measurement points, the coating thickness, the spraying color difference, the standard color value, the number of gloss measurement areas, the gloss of the measurement area, the total area of ​​defects after spraying and the total spraying area; the system intelligence and adaptability parameters specifically include the spraying speed before and after control, the control time interval, the actual response time of emergency failures, the theoretical response time, the number of abnormal working conditions successfully identified and the total number of abnormal working conditions.

[0014] Preferably, the model for obtaining the sub-region spraying precision control index in the spraying precision control index analysis unit is:

[0015]

[0016] Cpi i represents the spraying precision control index, Vra represents the intelligent visual recognition precision index, N represents the number of pixel sampling points at the edge of the sprayed object, e I represents the edge error of the first sampling point, Sdr represents the spraying path deviation index,

[0017] k represents the number of sampling points in the spraying path, (x act,j ,y act,j ) and (x pen,j ,y pen,j ) represent the coordinate points of the preset path and the spraying path of the jth sampling point, respectively, Rsr represents the repeated spraying area ratio index, K represents the number of multiple spraying, s J represents the area of ​​the Jth spraying repetition area, S represents the total spraying area, Mdr represents the defect detection rate index, Nd bef and Nd aft Represents the number of defects marked before and after spraying, respectively.

[0018] Preferably, the model for obtaining the sub-region spraying efficiency control index in the spraying efficiency control index analysis unit is:

[0019]

[0020] Among them Eei i It represents the control index of the sub-area spraying efficiency, t represents the spraying time per unit area, t0 represents the spraying setting time, σ(v) represents the standard deviation of the spraying speed, μ(v) represents the average value of the spraying speed, t1 represents the spraying response time, t2 represents the continuous spraying time, and T represents the spraying time.

[0021] Preferably, the model for the spraying quality control index analysis unit to obtain the sub-region spraying quality control index is:

[0022]

[0023] Among them, C i represents the spraying quality control index of the sub-area, M represents the number of coating thickness measurement points, and D L Indicates the coating thickness at the Lth measuring point, D / represents the average coating thickness at the measuring point, △E represents the spray color difference, E represents the standard color value, m represents the number of gloss measurement areas, G represents the average coating thickness at the measuring point, △E represents the spray color difference, E represents the standard color value, m represents the number of gloss measurement areas, l Indicates the glossiness of the lth measurement area, G / It represents the average glossiness of the measured area, Sd represents the total area of ​​defects after spraying, and S represents the total spraying area.

[0024] Preferably, the model for obtaining the sub-region system intelligence and adaptability control index in the system intelligence and adaptability control index analysis unit is:

[0025]

[0026] Saii i It represents the intelligent and adaptive control index of the sub-area system, V2 represents the spraying speed after control, V1 represents the spraying speed before control, △t represents the control time interval, t3 represents the actual response time of emergency failure, t4 represents the theoretical response time, Na represents the number of abnormal conditions successfully identified, and Tna represents the total number of abnormal conditions.

[0027] Preferably, the control module in the automatic programming spray control module includes the following steps:

[0028] S1: Obtain the sub-area spraying precision control index Cpi from the spraying precision control index analysis unit i Substitute into the formula: η(Cpi i )=ln(Cpi i / Cpi0), where η(Cpi i ) represents the efficiency coefficient of the spraying precision control index, and Cpi0 represents the set value;

[0029] S2: Obtain the sub-area spraying efficiency control index Eei from the spraying efficiency control index analysis unit i Substitute into the formula: η(Eei i )=ln(Eei i / Eei0), where η(Eei i ) represents the efficiency coefficient of the spraying efficiency control index, and Eei0 represents the set value;

[0030] S3: The spraying quality control index analysis unit obtains the sub-area spraying quality control index Cqi i Substitute into the formula: η(Cqi i )=ln(Cqi i / Cqi0), where η(Cqi i ) represents the efficiency coefficient of the spraying quality control index, and Cqi0 represents the set value;

[0031] S4: Obtain the sub-region system intelligence and adaptability control index Saii from the system intelligence and adaptability control index analysis unit i Substitute into the formula: η(Saii i )=ln(Saii i / Saii0), where η(Saii i ) represents the efficiency coefficient of the system intelligence and adaptability control index, Saii0 represents the set value.

[0032] Preferably, the comprehensive analysis model in the automatic programming spray comprehensive analysis module is: Wherein Scci represents the comprehensive performance index of automatic programming spraying control, a1, a2, a3 and a4 represent the weights of the efficiency coefficients of each control index of automatic programming spraying, and n represents the number of sub-areas.

[0033] Technical effects and advantages of the present invention:

[0034] 1. The present invention analyzes the spraying accuracy parameters to obtain an index to measure the current control performance level of the system, which can comprehensively reflect the accuracy and stability of the visual recognition algorithm in the automatic programming spraying control system, and can reflect the effectiveness of the path planning algorithm and the accuracy during the execution process, thereby reducing the proportion of repeated spraying areas and improving spraying efficiency and coating quality;

[0035] 2. The present invention analyzes the spraying efficiency parameters to obtain an index to measure the performance of the system in terms of spraying efficiency and speed control, mainly evaluating the output capacity and production efficiency of the spraying system, evaluating the motion control accuracy and stability of the spraying system, and evaluating the reliability and durability of the spraying system, thereby ensuring the smooth progress of the spraying process;

[0036] 3. The present invention analyzes the spraying quality parameters to obtain an index to measure the accuracy and stability of the control system's adjustment of the spraying speed and spraying thickness during the spraying process, reflecting the automatic programming spraying system's ability to accurately control the color ratio and achieve precise control of the glossiness to achieve the best color matching and improve the spraying quality of the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the overall process of the present invention.

[0038] Figure 2 This is a diagram of the automatic programming spraying data analysis module of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] See also Figure 1 As shown, the present invention provides an automatic programming spray control system based on intelligent visual recognition, including an automatic programming spray area division module, an automatic programming spray data acquisition module, an automatic programming spray data analysis module, an automatic programming spray control module, an automatic programming spray comprehensive analysis module and an automatic programming spray human-computer interaction module.

[0041] The automatic programming spraying area division module is connected to the automatic programming spraying data acquisition module, the automatic programming spraying data analysis module is respectively connected to the automatic programming spraying control module and the automatic programming spraying data acquisition module, the automatic programming spraying control module is respectively connected to the automatic programming spraying comprehensive analysis module and the automatic programming spraying human-computer interaction module, and the automatic programming spraying human-computer interaction module is respectively connected to the automatic programming spraying comprehensive analysis module and the automatic programming spraying data analysis module.

[0042] The automatic programming spraying area division module is used to take the object to be sprayed as the target area, and divide the target area into a plurality of monitoring sub-areas according to each spraying object, which are sequentially recorded as 1, 2, 3, ..., i, ..., n;

[0043] The automatic programming spraying data acquisition module collects data on the spraying characteristic information of the sub-area through intelligent visual recognition technology, obtains a database of various monitoring parameters for analyzing the automatic programming spraying control performance indicators, and outputs the various monitoring parameters to the automatic programming spraying data analysis module;

[0044] The present embodiment needs to be specifically explained that the spraying image is first captured by intelligent recognition technology, and then the image quality is improved by image processing technology to extract feature information related to spraying (such as edges, contours, etc.); then the position and direction of the product are determined; finally, the spraying trajectory is automatically generated according to the recognition result, and the spraying equipment is controlled to perform precise spraying operations.

[0045] What needs to be specifically explained in this embodiment is that various monitoring parameters include target area information, engineering administrator identity authentication information, spraying accuracy parameters, spraying efficiency parameters, spraying quality parameters and system intelligence and adaptability parameters, among which the spraying accuracy parameters are specifically the number of pixel sampling points at the edge of the spraying object, the edge error of the sampling points, the number of sampling points on the spraying path, the coordinate points of the path, the number of multiple sprayings, the area of ​​the spraying repeated area, the total spraying area area and the number of defects marked before and after spraying; the spraying efficiency parameters are specifically the spraying time per unit area, the spraying setting time, the spraying speed, the spraying response time, the continuous spraying time and the spraying time; the spraying quality parameters are specifically the number of coating thickness measurement points, the coating thickness, the spraying color difference, the standard color value, the number of gloss measurement areas, the gloss of the measurement area, the total area of ​​defects after spraying and the total spraying area; the system intelligence and adaptability parameters are specifically the spraying speed before and after control, the control time interval, the actual response time of emergency failures, the theoretical response time, the number of abnormal working conditions successfully identified and the total number of abnormal working conditions.

[0046] See also Figure 2 As shown, the automatic programming spraying data analysis module is used to analyze various monitoring parameters of the data acquisition module, including a spraying accuracy control index analysis unit, a spraying efficiency control index analysis unit, a spraying quality control index analysis unit, and a system intelligence and adaptability control index analysis unit, and outputs the analysis results to the automatic programming spraying control module, and its data analysis includes the following steps;

[0047] What needs to be specifically explained in this embodiment is that the spraying accuracy control index analysis unit is used to calculate the spraying accuracy parameters, the spraying efficiency control index analysis unit is used to calculate the spraying efficiency parameters, the spraying quality control index analysis unit is used to calculate the spraying quality parameters, and the system intelligence and adaptability control index analysis unit is used to calculate the system intelligence and adaptability parameters.

[0048] S1: By analyzing the spraying accuracy parameters, the current control performance level of the system can be measured, the accuracy and stability of the visual recognition algorithm in the automatic programming spraying control system can be comprehensively reflected, and the effectiveness of the path planning algorithm and the accuracy during the execution process can be reflected. Therefore, the model for obtaining the sub-area spraying accuracy control index in the spraying accuracy control index analysis unit is:

[0049]

[0050] Cpi i represents the spraying precision control index, Vra represents the intelligent visual recognition precision index, N represents the number of pixel sampling points at the edge of the sprayed object, e I It represents the edge error of the first sampling point. The edge error is obtained by: using intelligent visual recognition technology, in the recognition result image, the pixel position of the edge of the sprayed object is determined, and then in the real (or reference) image, the pixel position of the edge of the sprayed object is also determined. For the selected sampling point on the edge, the pixel distance between the recognition result and the real result is calculated as the error. Sdr represents the spray path deviation index. k represents the number of sampling points in the spraying path, (x act,j ,y act,j ) and (x pen,j ,y pen,j ) represent the coordinate points of the preset path and the spraying path of the jth sampling point, respectively, Rsr represents the repeated spraying area ratio index, K represents the number of multiple spraying, s J It represents the area of ​​the Jth spraying repetition area, S represents the total spraying area. During multiple spraying processes, the proportion of the repeated spraying area caused by path planning or execution errors to the total spraying area affects the material usage and coating quality. Mdr represents the defect detection rate index. Nd bef and Nd aft Respectively represent the number of defects marked before and after spraying. The number of defects is obtained by: the system detects and marks tiny defects (such as scratches and pits) on the sprayed object through intelligent visual recognition technology;

[0051] S2: By analyzing the spraying efficiency parameters, the system performance in spraying efficiency and speed control can be measured. The output capacity and production efficiency of the spraying system are mainly evaluated, as well as the motion control accuracy and stability of the spraying system, and the reliability and durability of the spraying system. Therefore, the model for obtaining the sub-area spraying efficiency control index in the spraying efficiency control index analysis unit is:

[0052]

[0053] Among them Eei irepresents the control index of the spraying efficiency of the sub-area, t represents the spraying time per unit area, during the spraying process, the time required to spray a specific area (e.g. 1 square meter) is recorded, t0 represents the spraying setting time, σ(v) represents the standard deviation of the spraying speed, μ(v) represents the average value of the spraying speed, during the spraying process, multiple speed samples during the spraying process are recorded, and then the standard deviation or variance of these speed samples is calculated, t1 represents the spraying response time, which is the response time from spraying object recognition to spraying, t2 represents the continuous spraying time, which is obtained by recording the time from the start of spraying to the interruption due to any reason (such as color change, material change, failure, etc.), T represents the spraying time, which is obtained by recording the time from the start of spraying to the end of spraying;

[0054] S3: By analyzing the spraying quality parameters, the accuracy and stability of the control system in regulating the spraying speed and spraying amount during the spraying process can be measured, reflecting the automatic programming spraying system's ability to accurately control the color ratio and achieve accurate control of the glossiness. Therefore, the spraying quality control index analysis unit obtains the model of the sub-area spraying quality control index as follows:

[0055]

[0056] Among them, C i represents the spraying quality control index of the sub-area, M represents the number of coating thickness measurement points, and D L Indicates the coating thickness at the Lth measuring point, D / It indicates the average coating thickness at the measuring point, △E indicates the spray color difference, which combines the color differences in hue, saturation and brightness, E indicates the standard color value, m indicates the number of gloss measurement areas, G l Indicates the glossiness of the lth measurement area, G / It represents the average glossiness of the measured area, Sd represents the total area of ​​defects after spraying, S represents the total spraying area, and the number of surface defects (such as bubbles and sagging) after spraying is counted by visual inspection, and the total area of ​​defects is counted, for example, each defect is regarded as having a fixed area;

[0057] S4: By analyzing the system intelligence and adaptability parameters, the system's intelligence and adaptability in automatic programming spray control can be measured. The control system can respond quickly after detecting an emergency fault, which can reduce the impact of the fault on the production process and ensure the continuity and stability of production. At the same time, the system can identify abnormal conditions such as spray object position offset and spray gun blockage in real time, and control them in time to avoid equipment damage or production accidents. Therefore, the model for obtaining the sub-area system intelligence and adaptability control index in the system intelligence and adaptability control index analysis unit is:

[0058]

[0059] Saii i It represents the control index of the intelligence and adaptability of the sub-area system, V2 represents the spraying speed after control, that is, the spraying area completed per unit time, V1 represents the spraying speed before control, △t represents the control time interval, by spraying the same object multiple times, the control system adaptively controls the spraying speed, and evaluates the intelligence of the control system, t3 represents the actual response time of the emergency fault, that is, the time difference from the system detecting the fault (such as sensor triggering) to the system starting to implement the response measures (such as stopping spraying, issuing an alarm), t4 represents the theoretical response time, Na represents the number of abnormal working conditions successfully identified, Tna represents the total number of abnormal working conditions, such as the position offset of the spraying object, the blockage of the spray gun, etc., all the recorded abnormal working condition data can be obtained through the monitoring system;

[0060] The automatic programming spraying control module is used to compare the automatic programming spraying control indicators obtained by the data analysis module with the set values, and output the comparison results to the automatic programming spraying comprehensive analysis module, and the control module includes the following steps:

[0061] S1: Obtain the sub-area spraying precision control index Cpi from the spraying precision control index analysis unit i Substitute into the formula: η(Cpi i )=ln(Cpi i / Cpi0), where η(Cpi i ) represents the efficiency coefficient of the spraying precision control index, and Cpi0 represents the set value;

[0062] In this embodiment, it is necessary to specifically explain that if η(Cpi i )≥0, indicating that the automatic programming spraying accuracy is well controlled, otherwise it is considered as η(Cpi i )=0, the spraying precision control is abnormal, feedback control is performed, the visual recognition system is calibrated and calibrated regularly, the motion trajectory of the spraying equipment is adjusted in real time according to the deviation, the spraying process is monitored in real time through the online monitoring system, repeated spraying problems are discovered and corrected in time, the stability and accuracy of the system are ensured, and the abnormal signal is transmitted to the automatic programming spraying human-computer interaction module.

[0063] S2: Obtain the sub-area spraying efficiency control index Eei from the spraying efficiency control index analysis unit i Substitute into the formula: η(Eei i )=ln(Eei i / Eei0), where η(Eei i ) represents the efficiency coefficient of the spraying efficiency control index, and Eei0 represents the set value;

[0064] In this embodiment, it should be specifically explained that if η(Eeii )≥0, indicating that the automatic programming spraying efficiency is well controlled, otherwise it is considered as η(Eei i )=0, the spraying efficiency control is abnormal, feedback control is performed to increase the spraying speed, optimize the distance and angle between the spray gun and the workpiece, and reduce the speed fluctuation rate, which can improve the spraying efficiency and transmit the abnormal signal to the automatic programming spraying human-computer interaction module.

[0065] S3: The spraying quality control index analysis unit obtains the sub-area spraying quality control index Cqi i Substitute into the formula: η(Cqi i )=ln(Cqi i / Cqi0), where η(Cqi i ) represents the efficiency coefficient of the spraying quality control index, and Cqi0 represents the set value;

[0066] In this embodiment, it should be specifically explained that if η(Cqi i )≥0, indicating that the automatic programming spraying quality control is good, otherwise it is considered as η(Cqi i )=0, the spraying quality control is abnormal, and feedback control is performed to adjust the spraying process parameters, such as spraying speed, spraying amount, etc., to ensure color consistency and gloss consistency, thereby reducing the occurrence of defects such as bubbles and sagging, and transmitting the abnormal signal to the automatic programming spraying human-computer interaction module.

[0067] S4: Obtain the sub-region system intelligence and adaptability control index Saii from the system intelligence and adaptability control index analysis unit i Substitute into the formula: η(Saii i )=ln(Saii i / Saii0), where η (Saii i ) represents the efficiency coefficient of the system intelligence and adaptability control index, Saii0 represents the set value;

[0068] In this embodiment, it should be specifically explained that if η(Saii i )≥0, indicating that the system intelligence and adaptability are well controlled, otherwise it is considered that η(Saii i )=0, the system intelligence and adaptability control are abnormal, feedback control is performed, and a large amount of spraying data is trained using machine learning algorithms so that the system can automatically learn and predict the optimal spraying parameters, reduce human intervention and adjustment times, increase the number and types of sensors, so as to more comprehensively monitor various parameters and states in the spraying process, improve the recognition rate of abnormal working conditions, and transmit abnormal signals to the automatic programming spraying human-computer interaction module.

[0069] The automatic programming spraying comprehensive analysis module is used to comprehensively analyze the efficiency coefficients of various control indicators obtained by the automatic programming spraying control module to obtain comprehensive performance indicators of automatic programming spraying control, and output the comprehensive analysis results to the automatic programming spraying human-computer interaction module. The comprehensive analysis model is: Where Scci represents the comprehensive performance index of automatic programming spraying control, a1, a2, a3 and a4 represent the weights of the efficiency coefficients of each control index of automatic programming spraying, and n represents the number of sub-areas;

[0070] The automatic programming spraying human-computer interaction module is used to output the automatic programming spraying control comprehensive performance indicators transmitted by the above-mentioned comprehensive analysis module to the engineering administrator information terminal. If the automatic programming spraying control comprehensive performance indicators belong to the set allowable range, it means that the automatic programming spraying control is good. Otherwise, the administrator is prompted to take timely measures to regularly maintain and maintain the spraying system to ensure that it is in good condition, reduce abnormal working conditions caused by equipment failure, and establish a rapid response mechanism to ensure that effective measures can be taken quickly when a failure occurs, thereby improving production efficiency and spraying equipment utilization.

[0071] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0072] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An automatic programming spray control system based on intelligent visual recognition, characterized in that: It includes an automatic programming spraying area division module, an automatic programming spraying data acquisition module, an automatic programming spraying data analysis module, an automatic programming spraying control module, an automatic programming spraying comprehensive analysis module and an automatic programming spraying human-computer interaction module; The automatic programming spraying area division module is used to take the object to be sprayed as the target area, and divide the target area into a plurality of monitoring sub-areas according to each spraying object, which are sequentially recorded as 1, 2, 3, ..., i, ..., n; The automatic programming spraying data acquisition module collects data on the spraying characteristic information of the sub-area through intelligent visual recognition technology, obtains a database of various monitoring parameters for analyzing the automatic programming spraying control performance indicators, and outputs the various monitoring parameters to the automatic programming spraying data analysis module; The automatic programming spraying data analysis module is used to analyze various monitoring parameters of the data acquisition module, including a spraying accuracy control index analysis unit, a spraying efficiency control index analysis unit, a spraying quality control index analysis unit, and a system intelligence and adaptability control index analysis unit, and outputs the analysis results to the automatic programming spraying control module; The automatic programming spraying control module is used to compare the automatic programming spraying control indicators obtained by the data analysis module with the set values, and output the comparison results to the automatic programming spraying comprehensive analysis module; The automatic programming spraying comprehensive analysis module is used to comprehensively analyze the efficiency coefficients of various control indicators obtained by the automatic programming spraying control module to obtain comprehensive performance indicators of automatic programming spraying control, and output the comprehensive analysis results to the automatic programming spraying human-computer interaction module; The automatic programming spraying human-computer interaction module is used to output the automatic programming spraying control comprehensive performance index transmitted by the above-mentioned comprehensive analysis module to the engineering administrator information terminal.

2. According to claim 1, an automatic programming spray control system based on intelligent visual recognition is characterized in that: The monitoring parameters in the automatic programming spraying data acquisition module include target area information, engineering administrator identity authentication information, spraying accuracy parameters, spraying efficiency parameters, spraying quality parameters and system intelligence and adaptability parameters, among which the spraying accuracy parameters are specifically the number of pixel sampling points at the edge of the spraying object, the edge error of the sampling points, the number of sampling points on the spraying path, the coordinate points of the path, the number of multiple sprayings, the area of ​​the spraying repeated area, the total area of ​​the spraying area and the number of defects marked before and after spraying; the spraying efficiency parameters are specifically the spraying time per unit area, the spraying setting time, the spraying speed, the spraying response time, the continuous spraying time and the spraying time; the spraying quality parameters are specifically the number of coating thickness measurement points, the coating thickness, the spraying color difference, the standard color value, the number of gloss measurement areas, the gloss of the measurement area, the total area of ​​defects after spraying and the total spraying area; the system intelligence and adaptability parameters are specifically the spraying speed before and after control, the control time interval, the actual response time of emergency failures, the theoretical response time, the number of abnormal working conditions successfully identified and the total number of abnormal working conditions.

3. According to claim 1, an automatic programming spray control system based on intelligent visual recognition is characterized in that: The model for obtaining the sub-region spraying precision control index in the spraying precision control index analysis unit is: ， Cpi i represents the spraying precision control index, Vra represents the intelligent visual recognition precision index, , N represents the number of pixel sampling points at the edge of the sprayed object, e I represents the edge error of the first sampling point, Sdr represents the spraying path deviation index, , k represents the number of sampling points of the spraying path, (x act,j ,y act,j ) and (x pen,j ,y pen,j ) represent the coordinate points of the preset path and the spraying path of the jth sampling point, respectively, Rsr represents the repeated spraying area ratio index, , K represents the number of multiple spraying, s J represents the area of ​​the Jth spraying repetition area, S represents the total spraying area, Mdr represents the defect detection rate index, , Nd bef and Nd aft Represents the number of defects marked before and after spraying, respectively.

4. The automatic programming spray control system based on intelligent visual recognition according to claim 1 is characterized in that: The model for obtaining the sub-region spraying efficiency control index in the spraying efficiency control index analysis unit is: ， Eei i It represents the control index of the sub-area spraying efficiency, t represents the spraying time per unit area, t0 represents the spraying setting time, σ(v) represents the standard deviation of the spraying speed, μ(v) represents the average value of the spraying speed, t1 represents the spraying response time, t2 represents the continuous spraying time, and T represents the spraying time.

5. The automatic programming spray control system based on intelligent visual recognition according to claim 1 is characterized in that: The model for the spraying quality control index analysis unit to obtain the sub-region spraying quality control index is: ， Among them, C i represents the spraying quality control index of the sub-area, M represents the number of coating thickness measurement points, and D L Indicates the coating thickness at the Lth measuring point, D / represents the average coating thickness at the measuring point, △E represents the spray color difference, E represents the standard color value, m represents the number of gloss measurement areas, G represents the average coating thickness at the measuring point, △E represents the spray color difference, E represents the standard color value, m represents the number of gloss measurement areas, l Indicates the glossiness of the lth measurement area, G / It represents the average glossiness of the measured area, Sd represents the total area of ​​defects after spraying, and S represents the total spraying area.

6. The automatic programming spray control system based on intelligent visual recognition according to claim 1 is characterized in that: The system intelligence and adaptability control index analysis unit obtains the sub The model of regional system intelligence and adaptability control index is: ， Saii i It represents the intelligent and adaptive control index of the sub-area system, V2 represents the spraying speed after control, V1 represents the spraying speed before control, △t represents the control time interval, t3 represents the actual response time of emergency failure, t4 represents the theoretical response time, Na represents the number of abnormal conditions successfully identified, and Tna represents the total number of abnormal conditions.

7. The automatic programming spray control system based on intelligent visual recognition according to claim 1 is characterized in that: The control module of the automatic programming spray control module includes the following steps: S1: Obtain the sub-area spraying precision control index Cpi from the spraying precision control index analysis unit i Substitute into the formula: η(Cpi i )=ln(Cpi i / Cpi0), where η(Cpi i ) represents the efficiency coefficient of the spraying precision control index, and Cpi0 represents the set value; S2: Obtain the sub-area spraying efficiency control index Eei from the spraying efficiency control index analysis unit i Substitute into the formula: η(Eei i )=ln(Eei i / Eei0), where η(Eei i ) represents the efficiency coefficient of the spraying efficiency control index, and Eei0 represents the set value; S3: The spraying quality control index analysis unit obtains the sub-area spraying quality control index Cqi i Substitute into the formula: η(Cqi i )=ln(Cqi i / Cqi0), where η(Cqi i ) represents the efficiency coefficient of the spraying quality control index, and Cqi0 represents the set value; S4: Obtain the sub-region system intelligence and adaptability control index Saii from the system intelligence and adaptability control index analysis unit i Substitute into the formula: η(Saii i )=ln(Saii i / Saii0), where η(Saii i ) represents the efficiency coefficient of the system intelligence and adaptability control index, Saii0 represents the set value.

8. The automatic programming spray control system based on intelligent visual recognition according to claim 7 is characterized in that: The comprehensive analysis model in the automatic programming spray comprehensive analysis module is: , where Scci represents the comprehensive performance index of automatic programming spraying control, a1, a2, a3 and a4 represent the weights of the efficiency coefficients of each control index of automatic programming spraying, and n represents the number of sub-areas.

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