Airflow control system and method for jig blowing

Abstract

The present invention relates to the field of airflow control technology, and discloses an airflow control system and method for fixture blowing, the system comprising: a collection unit configured to determine the initial airflow flow rate according to surface characteristic data; a judgment unit configured to judge whether to adjust the initial airflow flow rate according to air source pressure data; an adjustment unit configured to compare all pollution distribution characteristic values ​​with historical data respectively, adjust the initial airflow flow rate according to the comparison result, and obtain the adjusted airflow flow rate; a processing unit configured to calculate the similarity between all pollution distribution characteristic values ​​and historical data when there is no data identical to the pollution distribution characteristic value in the historical data, and adjust the initial airflow flow rate according to the similarity. The present invention can achieve effective cleaning of the surface contamination of the fixture, and improve production efficiency and product quality.

Description

Technical Field

[0001] The present invention relates to the technical field of airflow control, and in particular to an airflow control system and method for jig blowing. Background Art

[0002] In automatic loading and unloading machines, the fixture is an important component used to fix automotive workpieces. The surface of the fixture may be contaminated during use, which will affect the positioning accuracy and clamping effect of the automotive workpiece. In order to ensure the cleanliness of the fixture, it is usually necessary to clean it regularly. However, traditional cleaning methods often require manual intervention, which is not only inefficient, but also difficult to ensure the uniformity and thoroughness of cleaning.

[0003] Therefore, it is necessary to design an airflow control system and method for jig blowing to solve the problems existing in the current technology. Summary of the invention

[0004] In view of this, the present invention proposes an airflow control system and method for jig blowing, aiming to improve cleaning efficiency and ensure uniformity and thoroughness of cleaning.

[0005] In one aspect, the present invention provides an airflow control system for a jig blowing system, comprising:

[0006] A fixture body, an automatic loading and unloading machine, a camera group, an air supply device, a sensor group and a control module; the fixture body is arranged inside the automatic loading and unloading machine, and the surface is divided into several monitoring areas, and the fixture body is used to hold the automotive workpiece to be processed; the automatic loading and unloading machine is used to place the automotive workpiece to be processed on the fixture body after the blowing is completed; the camera group is located at the top of the automatic loading and unloading machine and is arranged toward the fixture body, the camera group includes several cameras, and each of the cameras corresponds to one monitoring area; the air supply device includes an air source device, an air duct, an air flow regulating valve and a nozzle, and the nozzle is arranged toward the fixture body; the sensor group includes a flow sensor and a pressure sensor, the flow sensor is arranged inside the air duct, and the pressure sensor is arranged at the outlet end of the nozzle; the control module is connected to the camera group, the air supply device, and the sensor group, and the control module includes a collection unit, a judgment unit, an adjustment unit, and a processing unit;

[0007] The collecting unit is configured to collect surface characteristic data of the fixture body and determine an initial airflow rate according to the surface characteristic data;

[0008] The judgment unit is configured to control the acquisition unit to acquire the gas source pressure data of the pressure sensor, and judge whether to adjust the initial air flow rate according to the gas source pressure data;

[0009] The adjustment unit is configured to, when it is determined that the initial airflow rate is to be adjusted, control the acquisition unit to acquire surface pollution image data of all the monitoring areas, perform feature extraction on the surface pollution image data to obtain pollution distribution feature data, and calculate the pollution distribution feature value of the monitoring area according to the pollution distribution feature data; compare all the pollution distribution feature values ​​with historical data respectively, and adjust the initial airflow rate according to the comparison result to obtain the adjusted airflow rate;

[0010] The processing unit is configured to calculate the similarity between all the pollution distribution characteristic values ​​and the historical data when there is no data identical to the pollution distribution characteristic value in the historical data, and adjust the initial airflow rate according to the similarity.

[0011] Further, when determining the initial airflow rate according to the surface characteristic data and the material characteristic data, it includes:

[0012] The surface characteristic data include surface roughness, surface temperature, and surface humidity;

[0013] The initial air flow rate is obtained by the following formula:

[0014] ;

[0015] in, represents the initial air flow rate; Indicates surface roughness; Indicates the surface temperature; Indicates surface humidity; represents the first empirical coefficient; Represents the second empirical coefficient.

[0016] Further, judging whether to adjust the initial air flow rate according to the air source pressure data includes:

[0017] Extracting features from the air source pressure data to obtain air pressure feature values;

[0018] Obtaining a standard air pressure characteristic value, and subtracting the air pressure characteristic value from the standard air pressure characteristic value to obtain an air pressure characteristic value difference;

[0019] The pressure characteristic value difference is compared with the pressure characteristic value difference threshold, and it is determined whether to adjust the initial air flow rate according to the comparison result.

[0020] Further, judging whether to adjust the initial airflow rate according to the comparison result includes:

[0021] When the pressure characteristic value difference is greater than or equal to the pressure characteristic value difference threshold, determining to adjust the initial air flow rate;

[0022] When the air pressure characteristic value difference is less than the air pressure characteristic value difference threshold, it is determined that the initial air flow rate is not adjusted.

[0023] Furthermore, performing feature extraction on the surface pollution image data to obtain pollution distribution feature data, and calculating the pollution distribution feature value of the monitoring area according to the pollution distribution feature data, includes:

[0024] The surface contamination image data includes surface debris image data and surface dust image data;

[0025] Using an edge algorithm to extract features from the surface debris image data and the surface dust image data, obtaining debris feature data and dust feature data; wherein the debris feature data includes debris size, debris shape and debris distribution density; and the dust feature data includes dust particle size and dust coverage area;

[0026] The pollution distribution characteristic value is obtained by the following formula:

[0027] ;

[0028] in, represents the pollution distribution characteristic value of the kth monitoring area; represents the size of the i-th debris in the k-th monitoring area; represents the area of ​​the kth monitoring area; represents the shape factor of the ith debris in the kth monitoring area; represents the debris distribution density of the kth monitoring area; represents the size of the jth dust particle in the kth monitoring area; represents the coverage area of ​​the jth dust particle in the kth monitoring area; represents the total amount of debris characteristic data and dust characteristic data in the kth monitoring area; represents the number of debris in the kth monitoring area; Represents the number of dust particles in the kth monitoring area.

[0029] Furthermore, all the pollution distribution characteristic values ​​are compared with historical data respectively, and the initial airflow rate is adjusted according to the comparison result, including:

[0030] When there is a historical pollution distribution characteristic value in the historical data that is the same as the pollution distribution characteristic value, determining a first adjustment coefficient according to the historical pollution distribution characteristic value to adjust the initial airflow rate;

[0031] When there are multiple historical pollution distribution characteristic values ​​that are the same as the pollution distribution characteristic value in the historical data, a historical average characteristic value is calculated according to the multiple historical pollution distribution characteristic values ​​to determine a second adjustment coefficient to adjust the initial airflow rate;

[0032] When there is no historical pollution distribution characteristic value identical to the pollution distribution characteristic value in the historical data, a third adjustment coefficient is determined according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow rate.

[0033] Further, when the adjustment coefficient is determined based on the historical average characteristic value calculated according to the plurality of historical pollution distribution characteristic values ​​to adjust the initial airflow flow, it includes:

[0034] Setting a second adjustment coefficient interval, wherein the second adjustment coefficient interval includes a second-level adjustment coefficient, a second-level adjustment coefficient, and a second-level adjustment coefficient;

[0035] Compare the historical average characteristic value with the first historical average characteristic value threshold and the second historical average characteristic value threshold respectively, and determine the adjustment coefficient according to the comparison result to adjust the initial airflow flow; wherein the first historical average characteristic value threshold is less than the second historical average characteristic value threshold;

[0036] When the historical average characteristic value is less than or equal to the first historical average characteristic value threshold, selecting a second first-level adjustment coefficient to adjust the initial airflow flow, and the product of the second first-level adjustment coefficient and the initial airflow flow is the adjusted airflow flow;

[0037] When the historical average characteristic value is greater than the first historical average characteristic value threshold and less than or equal to the second historical average characteristic value threshold, a second secondary adjustment coefficient is selected to adjust the initial airflow flow, and the product of the second secondary adjustment coefficient and the initial airflow flow is the adjusted airflow flow;

[0038] When the historical average characteristic value is greater than the second historical average characteristic value threshold, the second third-level adjustment coefficient is selected to adjust the initial airflow flow, and the product of the second third-level adjustment coefficient and the initial airflow flow is the adjusted airflow flow.

[0039] Further, when determining a third adjustment coefficient to adjust the initial airflow rate according to the similarity between the pollution distribution characteristic value and the historical data, it includes:

[0040] Calculating the similarities between all the pollution distribution characteristic values ​​and the historical data one by one to obtain a similarity data set;

[0041] Calculating an average similarity based on the similarity data set;

[0042] Obtain the number of all pollution distribution characteristic values ​​corresponding to the average similarity that are greater than the average similarity, recorded as the first similarity number; obtain the number of all pollution distribution characteristic values ​​corresponding to the average similarity that are less than or equal to the average similarity, recorded as the second similarity number;

[0043] Calculating the third adjustment coefficient according to the average similarity, the first similarity quantity and the second similarity quantity;

[0044] The product of the third adjustment coefficient and the initial air flow rate is the adjusted air flow rate;

[0045] The third adjustment coefficient is obtained by the following formula:

[0046] ;

[0047] in, represents the third adjustment factor; represents the first similar quantity; represents the second similar quantity; Indicates the total number of similarities; represents the average similarity; Represents the maximum similarity value in the similarity dataset.

[0048] Further, when the third adjustment coefficient is determined according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow flow, the similarity is obtained by the following formula:

[0049] ;

[0050] in, Indicates similarity; Represents the value of the i-th dimension of the current pollution distribution characteristic value; Represents the value of the i-th dimension of the historical data eigenvalue; n represents the number of dimensions of the eigenvalue.

[0051] In another aspect, the present invention further provides an airflow control method for a jig blowing, comprising the following steps:

[0052] S100: collecting surface characteristic data of the fixture body, and determining an initial airflow rate according to the surface characteristic data;

[0053] S200: collecting gas source pressure data of the pressure sensor, and determining whether to adjust the initial air flow rate according to the gas source pressure data;

[0054] S300: When it is determined that the initial airflow rate is to be adjusted, surface pollution image data of all the monitoring areas are collected, and features are extracted from the surface pollution image data to obtain pollution distribution feature data, and pollution distribution feature values ​​of the monitoring areas are calculated according to the pollution distribution feature data; all the pollution distribution feature values ​​are compared with historical data respectively, and the initial airflow rate is adjusted according to the comparison results to obtain an adjusted airflow rate;

[0055] S400: When there is no data identical to the pollution distribution characteristic value in the historical data, the similarity between all the pollution distribution characteristic values ​​and the historical data is calculated, and the initial airflow rate is adjusted according to the similarity.

[0056] Compared with the prior art, the beneficial effect of the present invention is that the airflow control system for jig blowing provided by the present invention can achieve effective cleaning of the surface contamination of the jig body, thereby improving production efficiency and product quality. By real-time monitoring and analysis of the contamination on the jig surface, the system can automatically adjust the airflow flow rate to ensure that the ideal cleaning effect can be achieved. In addition, the method can also reduce manual intervention and reduce operating costs, and due to its intelligent adjustment mechanism, it can adapt to a variety of different production environments and conditions. Ultimately, through the application of this method, production defects caused by jig contamination can be significantly reduced and the product qualification rate can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0058] Figure 1 A structural block diagram of an airflow control system for a jig blowing system provided by an embodiment of the present invention;

[0059] Figure 2 A flow chart of an airflow control method for jig blowing provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0061] See also Figure 1 As shown, in some embodiments of the present application, this embodiment provides an airflow control system for a jig blowing, comprising:

[0062] A fixture body, an automatic loading and unloading machine, a camera group, an air supply device, a sensor group and a control module; the fixture body is arranged inside the automatic loading and unloading machine, and the surface is divided into several monitoring areas, and the fixture body is used to hold the automotive workpiece to be processed; the automatic loading and unloading machine is used to place the automotive workpiece to be processed on the fixture body after the blowing is completed; the camera group is located at the top of the automatic loading and unloading machine and is arranged toward the fixture body, the camera group includes several cameras, and each of the cameras corresponds to one monitoring area; the air supply device includes an air source device, an air duct, an air flow regulating valve and a nozzle, and the nozzle is arranged toward the fixture body; the sensor group includes a flow sensor and a pressure sensor, the flow sensor is arranged inside the air duct, and the pressure sensor is arranged at the outlet end of the nozzle; the control module is connected to the camera group, the air supply device, and the sensor group, and the control module includes a collection unit, a judgment unit, an adjustment unit, and a processing unit;

[0063] The collecting unit is configured to collect surface characteristic data of the fixture body and determine an initial airflow rate according to the surface characteristic data;

[0064] The judgment unit is configured to control the acquisition unit to acquire the gas source pressure data of the pressure sensor, and judge whether to adjust the initial air flow rate according to the gas source pressure data;

[0065] The adjustment unit is configured to, when it is determined that the initial airflow rate is to be adjusted, control the acquisition unit to acquire surface pollution image data of all the monitoring areas, perform feature extraction on the surface pollution image data to obtain pollution distribution feature data, and calculate the pollution distribution feature value of the monitoring area according to the pollution distribution feature data; compare all the pollution distribution feature values ​​with historical data respectively, and adjust the initial airflow rate according to the comparison result to obtain the adjusted airflow rate;

[0066] The processing unit is configured to calculate the similarity between all the pollution distribution characteristic values ​​and the historical data when there is no data identical to the pollution distribution characteristic value in the historical data, and adjust the initial airflow rate according to the similarity.

[0067] In this embodiment, the fixture body is a core component in the automatic loading and unloading machine, and its main function is to carry the automotive workpiece to be processed and provide stable support for the automotive workpiece to be processed during the processing. The function of the camera group is to capture the surface contamination image data of the monitoring area; the air supply device is responsible for providing a continuous and stable airflow to ensure the cleanliness of the fixture surface. The air source device, as the starting point of the airflow, delivers the airflow to each nozzle through the air duct; the airflow regulating valve accurately controls the airflow according to the instructions of the control module to adapt to different surface conditions of the automotive workpiece to be processed and the fixture. The nozzle, as the end of the airflow output, directly acts on the fixture surface to remove impurities and dust on the surface. The flow sensor and pressure sensor in the sensor group are used to monitor the flow and pressure of the airflow in real time, respectively, to ensure the stability and suitability of the airflow.

[0068] It is understandable that the acquisition unit is used to determine the initial airflow rate based on the surface characteristic data, which is crucial for the subsequent airflow control because it will directly affect the cleaning effect of the fixture surface; the judgment unit is used to determine whether the air source pressure is stable, so as to determine whether the airflow rate needs to be adjusted. If the air source pressure is unstable, it will cause the airflow rate to fluctuate, affecting the cleaning effect of the fixture body surface; the adjustment unit is used to calculate the pollution distribution characteristic value of each monitoring area based on the collected pollution distribution characteristic data, and compare it with the historical data to determine whether the airflow rate needs to be adjusted. When there is no historical data that matches the current pollution distribution characteristic value, the processing unit will calculate the similarity and adjust the airflow rate accordingly to adapt to the new pollution conditions. Through such a process, the system can ensure that the surface of the fixture body maintains an appropriate cleanliness during the processing of different automotive workpieces to be processed, thereby improving the processing quality and efficiency.

[0069] Specifically, when determining the initial airflow rate according to the surface characteristic data and the material characteristic data, it includes:

[0070] The surface characteristic data include surface roughness, surface temperature, and surface humidity;

[0071] The initial air flow rate is obtained by the following formula:

[0072] ;

[0073] in, represents the initial air flow rate; Indicates surface roughness; Indicates the surface temperature; Indicates surface humidity; represents the first empirical coefficient; Represents the second empirical coefficient.

[0074] It is understandable that the preferred value of k1 is between 0.05 and 0.15, and the preferred value of k2 is between 0.01 and 0.05. The selection of these empirical coefficients is based on a large number of experiments and practical application experience to ensure that the calculation of the initial airflow rate is both accurate and practical. For example, when the surface roughness is large, a stronger airflow is required to remove impurities on the surface; and when the surface temperature is high, the airflow rate needs to be appropriately reduced to avoid thermal damage to the fixture surface. Through this calculation method, it can be ensured that the fixture surface can be properly cleaned under different processing conditions.

[0075] Specifically, judging whether to adjust the initial air flow rate according to the air source pressure data includes:

[0076] Extracting features from the air source pressure data to obtain air pressure feature values;

[0077] Obtaining a standard air pressure characteristic value, and subtracting the air pressure characteristic value from the standard air pressure characteristic value to obtain an air pressure characteristic value difference;

[0078] The pressure characteristic value difference is compared with the pressure characteristic value difference threshold, and it is determined whether to adjust the initial air flow rate according to the comparison result.

[0079] Specifically, judging whether to adjust the initial airflow rate according to the comparison result includes:

[0080] When the pressure characteristic value difference is greater than or equal to the pressure characteristic value difference threshold, determining to adjust the initial air flow rate;

[0081] When the air pressure characteristic value difference is less than the air pressure characteristic value difference threshold, it is determined that the initial air flow rate is not adjusted.

[0082] It is understandable that the pressure characteristic difference threshold is pre-set to ensure the stability of the air flow rate. When the air source pressure fluctuates, causing the difference between the pressure characteristic value and the standard value to exceed this threshold, the system will automatically adjust the air flow rate to compensate for the impact of pressure changes on the cleanliness of the fixture surface. This automatic adjustment mechanism ensures that the fixture surface maintains a consistent cleaning effect under different pressure conditions, thereby avoiding the problem of inadequate cleaning due to pressure fluctuations.

[0083] Specifically, performing feature extraction on the surface pollution image data to obtain pollution distribution feature data, and calculating the pollution distribution feature value of the monitoring area according to the pollution distribution feature data, includes:

[0084] The surface contamination image data includes surface debris image data and surface dust image data;

[0085] Using an edge algorithm to extract features from the surface debris image data and the surface dust image data, obtaining debris feature data and dust feature data; wherein the debris feature data includes debris size, debris shape and debris distribution density; and the dust feature data includes dust particle size and dust coverage area;

[0086] The pollution distribution characteristic value is obtained by the following formula:

[0087] ;

[0088] in, represents the pollution distribution characteristic value of the kth monitoring area; represents the size of the i-th debris in the k-th monitoring area; represents the area of ​​the kth monitoring area; represents the shape factor of the ith debris in the kth monitoring area; represents the debris distribution density of the kth monitoring area; represents the size of the jth dust particle in the kth monitoring area; represents the coverage area of ​​the jth dust particle in the kth monitoring area; represents the total amount of debris characteristic data and dust characteristic data in the kth monitoring area; represents the number of debris in the kth monitoring area; Represents the number of dust particles in the kth monitoring area.

[0089] It can be seen that the calculation method takes into account multiple characteristics of debris and dust, such as size, shape, distribution density, coverage area, etc., so that the degree of pollution in each monitoring area can be accurately assessed.

[0090] Specifically, all the pollution distribution characteristic values ​​are compared with the historical data respectively, and the initial airflow flow is adjusted according to the comparison results, including:

[0091] When there is a historical pollution distribution characteristic value in the historical data that is the same as the pollution distribution characteristic value, determining a first adjustment coefficient according to the historical pollution distribution characteristic value to adjust the initial airflow rate;

[0092] When there are multiple historical pollution distribution characteristic values ​​that are the same as the pollution distribution characteristic value in the historical data, a historical average characteristic value is calculated according to the multiple historical pollution distribution characteristic values ​​to determine a second adjustment coefficient to adjust the initial airflow rate;

[0093] When there is no historical pollution distribution characteristic value identical to the pollution distribution characteristic value in the historical data, a third adjustment coefficient is determined according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow rate.

[0094] In this embodiment, the first adjustment coefficient is obtained based on the historical pollution distribution characteristic value. The first adjustment coefficient is preferably a value between 0.9 and 1.1, which is used to fine-tune the air flow rate, and the relationship between the first adjustment coefficient and the historical pollution distribution characteristic value is a linear relationship.

[0095] It is understandable that by comparing all the contamination distribution characteristic values ​​with the historical data, and adjusting the initial airflow according to the comparison results, it is possible to ensure that the cleanliness of the fixture surface is consistent with the historical best state. This adjustment mechanism based on historical data can not only adapt to the long-term trend of the contamination level of the fixture surface, but also respond quickly to sudden contamination situations. For example, if historical data shows that the fixture surface usually has a high level of contamination at a specific processing stage, the system will automatically increase the airflow to cope with this situation, thereby avoiding processing defects caused by contamination.

[0096] Specifically, when the adjustment coefficient is determined based on the historical pollution distribution characteristic values ​​to calculate the historical average characteristic value and adjust the initial airflow flow, it includes:

[0097] Setting a second adjustment coefficient interval, wherein the second adjustment coefficient interval includes a second-level adjustment coefficient, a second-level adjustment coefficient, and a second-level adjustment coefficient;

[0098] Compare the historical average characteristic value with the first historical average characteristic value threshold and the second historical average characteristic value threshold respectively, and determine the adjustment coefficient according to the comparison result to adjust the initial airflow flow; wherein the first historical average characteristic value threshold is less than the second historical average characteristic value threshold;

[0099] When the historical average characteristic value is less than or equal to the first historical average characteristic value threshold, selecting a second first-level adjustment coefficient to adjust the initial airflow flow, and the product of the second first-level adjustment coefficient and the initial airflow flow is the adjusted airflow flow;

[0100] When the historical average characteristic value is greater than the first historical average characteristic value threshold and less than or equal to the second historical average characteristic value threshold, a second secondary adjustment coefficient is selected to adjust the initial airflow flow, and the product of the second secondary adjustment coefficient and the initial airflow flow is the adjusted airflow flow;

[0101] When the historical average characteristic value is greater than the second historical average characteristic value threshold, the second third-level adjustment coefficient is selected to adjust the initial airflow flow, and the product of the second third-level adjustment coefficient and the initial airflow flow is the adjusted airflow flow.

[0102] It is understandable that the second-level adjustment coefficient, the second-level adjustment coefficient, and the second-level adjustment coefficient are derived from the statistical analysis of historical data, and they correspond to different pollution levels. The second-level adjustment coefficient is applicable to lower pollution levels, the second-level adjustment coefficient is applicable to medium pollution levels, and the second-level adjustment coefficient is applicable to higher pollution levels. In this way, the system can flexibly adjust the airflow rate according to the actual pollution situation of the fixture surface to achieve the best cleaning effect.

[0103] Specifically, when determining the third adjustment coefficient to adjust the initial airflow according to the similarity between the pollution distribution characteristic value and the historical data, it includes:

[0104] Calculating the similarities between all the pollution distribution characteristic values ​​and the historical data one by one to obtain a similarity data set;

[0105] Calculating an average similarity based on the similarity data set;

[0106] Obtain the number of all pollution distribution characteristic values ​​corresponding to the average similarity that are greater than the average similarity, recorded as the first similarity number; obtain the number of all pollution distribution characteristic values ​​corresponding to the average similarity that are less than or equal to the average similarity, recorded as the second similarity number;

[0107] Calculating the third adjustment coefficient according to the average similarity, the first similarity quantity and the second similarity quantity;

[0108] The product of the third adjustment coefficient and the initial air flow rate is the adjusted air flow rate;

[0109] The third adjustment coefficient is obtained by the following formula:

[0110] ;

[0111] in, represents the third adjustment factor; represents the first similar quantity; represents the second similar quantity; Indicates the total number of similarities; represents the average similarity; Represents the maximum similarity value in the similarity dataset.

[0112] Specifically, when the third adjustment coefficient is determined according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow flow, the similarity is obtained by the following formula:

[0113] ;

[0114] in, Indicates similarity; Represents the value of the i-th dimension of the current pollution distribution characteristic value; Represents the value of the i-th dimension of the historical data eigenvalue; n represents the number of dimensions of the eigenvalue.

[0115] It can be understood that by calculating the similarity, the system is able to evaluate the closeness between the current contamination distribution and the historical data. When the similarity is high, it means that the current contamination level is similar to a specific contamination level in history, and the system will adjust the airflow rate based on this similarity. This similarity-based adjustment mechanism enables the system to respond to contamination distributions that have not directly appeared in historical data, thereby providing a more flexible and comprehensive contamination control strategy. In this way, even in the face of new contamination patterns, the system can effectively adjust the airflow rate to ensure the cleanliness of the fixture surface, thereby improving processing quality and reducing defects.

[0116] See also Figure 2 As shown, in some embodiments of the present application, this embodiment provides an airflow control method for a jig blowing, comprising the following steps:

[0117] S100: collecting surface characteristic data of the fixture body, and determining an initial airflow rate according to the surface characteristic data;

[0118] S200: collecting gas source pressure data of the pressure sensor, and determining whether to adjust the initial air flow rate according to the gas source pressure data;

[0119] S300: When it is determined that the initial airflow rate is to be adjusted, surface pollution image data of all the monitoring areas are collected, and features are extracted from the surface pollution image data to obtain pollution distribution feature data, and pollution distribution feature values ​​of the monitoring areas are calculated according to the pollution distribution feature data; all the pollution distribution feature values ​​are compared with historical data respectively, and the initial airflow rate is adjusted according to the comparison results to obtain an adjusted airflow rate;

[0120] S400: When there is no data identical to the pollution distribution characteristic value in the historical data, the similarity between all the pollution distribution characteristic values ​​and the historical data is calculated, and the initial airflow rate is adjusted according to the similarity.

[0121] It can be understood that the airflow control method for jig blowing provided in this embodiment can achieve effective cleaning of the surface contamination of the jig body, thereby improving production efficiency and product quality. By real-time monitoring and analysis of the contamination on the jig surface, the system can automatically adjust the airflow flow rate to ensure that the ideal cleaning effect can be achieved. In addition, the method can also reduce manual intervention and reduce operating costs, and due to its intelligent adjustment mechanism, it can adapt to a variety of different production environments and conditions. Ultimately, through the application of this method, production defects caused by jig contamination can be significantly reduced, and the product qualification rate can be improved.

[0122] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0123] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0124] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An airflow control system for a jig blowing, characterized in that: include: A fixture body, an automatic loading and unloading machine, a camera group, an air supply device, a sensor group and a control module; the fixture body is arranged inside the automatic loading and unloading machine, and the surface is divided into several monitoring areas, and the fixture body is used to hold the automotive workpiece to be processed; the automatic loading and unloading machine is used to place the automotive workpiece to be processed on the fixture body after the blowing is completed; the camera group is located at the top of the automatic loading and unloading machine and is arranged toward the fixture body, the camera group includes several cameras, and each of the cameras corresponds to one monitoring area; the air supply device includes an air source device, an air duct, an air flow regulating valve and a nozzle, and the nozzle is arranged toward the fixture body; the sensor group includes a flow sensor and a pressure sensor, the flow sensor is arranged inside the air duct, and the pressure sensor is arranged at the outlet end of the nozzle; the control module is connected to the camera group, the air supply device, and the sensor group, and the control module includes a collection unit, a judgment unit, an adjustment unit, and a processing unit; The collecting unit is configured to collect surface characteristic data of the fixture body and determine an initial airflow rate according to the surface characteristic data; The judgment unit is configured to control the acquisition unit to acquire the gas source pressure data of the pressure sensor, and judge whether to adjust the initial air flow rate according to the gas source pressure data; The adjustment unit is configured to, when it is determined that the initial airflow rate is to be adjusted, control the acquisition unit to acquire surface pollution image data of all the monitoring areas, perform feature extraction on the surface pollution image data to obtain pollution distribution feature data, and calculate the pollution distribution feature value of the monitoring area according to the pollution distribution feature data; compare all the pollution distribution feature values ​​with historical data respectively, and adjust the initial airflow rate according to the comparison result to obtain the adjusted airflow rate; The processing unit is configured to calculate the similarity between all the pollution distribution characteristic values ​​and the historical data when there is no data identical to the pollution distribution characteristic value in the historical data, and adjust the initial airflow rate according to the similarity; Comparing all the pollution distribution characteristic values ​​with historical data respectively, and adjusting the initial airflow according to the comparison results, includes: When there is a historical pollution distribution characteristic value in the historical data that is the same as the pollution distribution characteristic value, determining a first adjustment coefficient according to the historical pollution distribution characteristic value to adjust the initial airflow rate; When there is no historical pollution distribution characteristic value identical to the pollution distribution characteristic value in the historical data, determining a third adjustment coefficient according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow rate; When the third adjustment coefficient is determined according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow flow, it includes: Calculating the similarities between all the pollution distribution characteristic values ​​and the historical data one by one to obtain a similarity data set; Calculating an average similarity based on the similarity data set; Obtain the number of all pollution distribution characteristic values ​​corresponding to the average similarity that are greater than the average similarity, recorded as the first similarity number; obtain the number of all pollution distribution characteristic values ​​corresponding to the average similarity that are less than or equal to the average similarity, recorded as the second similarity number; Calculating the third adjustment coefficient according to the average similarity, the first similarity quantity and the second similarity quantity; The product of the third adjustment coefficient and the initial air flow rate is the adjusted air flow rate; The third adjustment coefficient is obtained by the following formula: ； in, represents the third adjustment factor; represents the first similar quantity; represents the second similar quantity; Indicates the total number of similarities; represents the average similarity; Represents the maximum similarity value in the similarity dataset.

2. The airflow control system for jig blowing according to claim 1, characterized in that: When determining the initial airflow rate according to the surface characteristic data and the material characteristic data, it includes: The surface characteristic data include surface roughness, surface temperature, and surface humidity; The initial air flow rate is obtained by the following formula: ； in, represents the initial air flow rate; Indicates surface roughness; Indicates the surface temperature; Indicates surface humidity; represents the first empirical coefficient; Represents the second empirical coefficient.

3. The airflow control system for jig blowing according to claim 1, characterized in that: When judging whether to adjust the initial air flow rate according to the air source pressure data, it includes: Extracting features from the air source pressure data to obtain air pressure feature values; Obtaining a standard air pressure characteristic value, and subtracting the air pressure characteristic value from the standard air pressure characteristic value to obtain an air pressure characteristic value difference; The pressure characteristic value difference is compared with the pressure characteristic value difference threshold, and it is determined whether to adjust the initial air flow rate according to the comparison result.

4. The airflow control system for jig blowing according to claim 3, characterized in that: When judging whether to adjust the initial air flow rate according to the comparison result, it includes: When the pressure characteristic value difference is greater than or equal to the pressure characteristic value difference threshold, determining to adjust the initial air flow rate; When the air pressure characteristic value difference is less than the air pressure characteristic value difference threshold, it is determined that the initial air flow rate is not adjusted.

5. The airflow control system for jig blowing according to claim 1, characterized in that: Extracting features from the surface pollution image data to obtain pollution distribution feature data, and calculating the pollution distribution feature value of the monitoring area according to the pollution distribution feature data, includes: The surface contamination image data includes surface debris image data and surface dust image data; Using an edge algorithm to extract features from the surface debris image data and the surface dust image data, obtaining debris feature data and dust feature data; wherein the debris feature data includes debris size, debris shape and debris distribution density; and the dust feature data includes dust particle size and dust coverage area; The pollution distribution characteristic value is obtained by the following formula: ； in, represents the pollution distribution characteristic value of the kth monitoring area; represents the size of the i-th debris in the k-th monitoring area; represents the area of ​​the kth monitoring area; represents the shape factor of the ith debris in the kth monitoring area; represents the debris distribution density of the kth monitoring area; represents the size of the jth dust particle in the kth monitoring area; represents the coverage area of ​​the jth dust particle in the kth monitoring area; represents the total amount of debris characteristic data and dust characteristic data in the kth monitoring area; represents the number of debris in the kth monitoring area; Represents the number of dust particles in the kth monitoring area.

6. The airflow control system for jig blowing according to claim 1, characterized in that: When the third adjustment coefficient is determined according to the similarity between the pollution distribution characteristic value and the historical data to adjust the initial airflow flow, the similarity is obtained by the following formula: ； in, Indicates similarity; Represents the value of the i-th dimension of the current pollution distribution characteristic value; Represents the value of the i-th dimension of the historical data eigenvalue; n represents the number of dimensions of the eigenvalue.

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