A body-in-white virtual matching method and assembly system

Abstract

The application discloses a body-in-white virtual matching method and an assembling system. The method comprises the following steps: S1, on-line monitoring a first identification point on a body; S2, on-line monitoring a second identification point on a door; S3, virtually matching the monitored body and a plurality of doors to obtain an optimal door capable of matching the body; and S4, assembling the body and the optimal door. The application can solve the problems in the background art and can match the body and the door in a better way.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, specifically to a virtual matching method and assembly system for a body-in-white. Background Technology

[0002] In existing technologies, the main quality control method for body-in-white is manual assembly and adjustment of doors, with offline dimensional monitoring. After the body welding is completed, the doors are assembled on the adjustment line. First, at one station, the door is positioned onto the body using installation tools, and then bolts are tightened. Because there are certain fluctuations in both body and door dimensions, there is a subsequent adjustment station where employees need to measure the matching dimensions between the door and the body, loosen the bolts, and make minor adjustments to the gaps and steps until the adjustment is satisfactory before tightening the bolts. Offline, the body is measured in the measurement room using a double-cantilever coordinate measuring machine to collect relevant dimensional information (including key matching surfaces on the body, key tooling positioning holes, etc.). The door is measured on a fixture using a triangular feeler gauge to collect the door circumference gaps, steps, and hinge surface dimensions. The collected body and door data are used for dimensional problem analysis.

[0003] The existing technologies mentioned above have the following problems: the vehicle body size information and door size information collected offline are not matched one-to-one; the size problems of the vehicle body and doors are difficult to correspond to the whole vehicle matching problem; the output of the problem cause judgment and rectification direction is mostly based on experience and there is no effective corresponding data support. Summary of the Invention

[0004] The purpose of this invention is to provide a virtual matching method and assembly system for a white body to overcome the shortcomings of the prior art. It can solve the problems in the background art and enable the body and doors to match in a better way.

[0005] This invention provides a virtual matching method for vehicle body-in-white, comprising the following steps:

[0006] S1, monitors the first identification point on the vehicle body online;

[0007] S2, performs online monitoring of the second identification point on the car door;

[0008] S3, perform virtual matching on the monitored vehicle body and multiple doors to obtain the optimal door that can match the vehicle body;

[0009] S4, assemble the vehicle body with the optimal door.

[0010] In the virtual matching method for white body as described above, optionally, step S1 includes,

[0011] S11, Collect data from the first identification points on each of the vehicle bodies;

[0012] S12, calculate the first deviation between the collected data of the first identification point and the first design value, determine whether the first deviation is greater than the set first parameter, and if so, issue an alarm.

[0013] In the virtual matching method for the white body described above, optionally, the first identification point includes a first mounting point and a first appearance matching point on the vehicle body.

[0014] In the virtual matching method for white body as described above, optionally, step S2 includes,

[0015] S21, collect data from the second identification points on each of the vehicle doors;

[0016] S22, calculate the second deviation between the collected data of the second identification point and the second design value, determine whether the second deviation is greater than the set second parameter, and if so, issue an alarm.

[0017] In the virtual matching method for the white body described above, optionally, the second identification point includes a second mounting point and a second appearance matching point on each of the doors.

[0018] In the virtual matching method for white body as described above, optionally, step S3 includes,

[0019] S31, the data of each of the first identification points are virtually matched with the data of each of the second identification points;

[0020] S32, Based on the results of the virtual matching, determine the best door that matches the vehicle body.

[0021] In the virtual matching method for white body as described above, optionally, step S32 includes,

[0022] S321, Virtually measure the matching dimensions of the circumferential gap and step difference measurement points between the virtually matched vehicle body and each of the doors;

[0023] S322, determine the optimal door based on the matching dimensions of the circumferential gap and step difference measuring points.

[0024] In the virtual matching method for white body described above, optionally, step S4 includes:

[0025] S41, Calculate the optimal posture data when the optimal door is assembled;

[0026] S42 transmits the optimal posture data to the execution robot;

[0027] S43, the robot assembles the optimal door onto the vehicle body according to the optimal posture data.

[0028] The present invention also proposes a body-in-white assembly system, which includes a first sensor, a second sensor, a door online monitoring unit, a body online monitoring unit, a control unit, and an execution robot;

[0029] The first sensor is electrically connected to the vehicle door online monitoring unit;

[0030] The second sensor is electrically connected to the vehicle body online monitoring unit;

[0031] Both the door online monitoring unit and the body online monitoring unit are electrically connected to the control unit.

[0032] The first sensor is used to collect door data; the second sensor is used to collect vehicle body data.

[0033] The online door monitoring unit is used to acquire door data collected by the first sensor, determine whether the deviation of the door meets the requirements based on the door data, and issue an alarm when the deviation of the door data does not meet the requirements.

[0034] The vehicle body online monitoring unit is used to acquire vehicle body data collected by the second sensor, determine whether the deviation of the vehicle body meets the requirements based on the vehicle body data, and issue an alarm when the deviation of the vehicle body data does not meet the requirements.

[0035] The control unit is used to virtually match the vehicle body and doors based on the vehicle body data and door data; and select the best door; the control unit is also used to calculate the best assembly posture of the door and output the data corresponding to the assembly posture to the execution robot so that the execution robot can install the best door according to the assembly posture.

[0036] In the body-in-white assembly system described above, optionally, the control unit is also used to perform virtual measurements on the virtual matching results and select the optimal door based on the virtual measurement results;

[0037] The virtual measurements include the matching dimensions of the surrounding gaps and step difference measurement points.

[0038] Compared to existing technologies, this invention monitors the vehicle body and doors online and performs virtual matching between them. Based on the virtual matching results, it identifies the door that best matches the vehicle body and installs it onto the body. This method allows for the selection of the most compatible door from several options before actual assembly, automatically achieving optimal matching and reducing the occurrence of size mismatch issues between the vehicle body and doors.

[0039] By identifying the dimensions of car doors and the body, and determining in advance whether the dimensions meet the requirements, an alarm is issued for any non-compliant doors and bodies, thus providing early warning of size issues.

[0040] During operation, this invention also generates optimal posture data through virtual matching, and the robot grasps the car door and positions it in the optimal posture, which can save adjustment time and reduce the workload of adjustment personnel. Attached Figure Description

[0041] Figure 1 This is a flowchart of the steps of the virtual matching method for the white body proposed in Embodiment 1 of the present invention;

[0042] Figure 2 This is a flowchart illustrating the specific steps of step S1 of the present invention;

[0043] Figure 3 This is a flowchart illustrating the specific steps of step S2 in this invention;

[0044] Figure 4 This is a flowchart illustrating the specific steps of step S3 in this invention;

[0045] Figure 5 This is a flowchart illustrating the specific steps of step S32 of the present invention;

[0046] Figure 6 This is a flowchart illustrating the specific steps of step S4 in this invention;

[0047] Figure 7 This is a schematic diagram of the distribution of the first identification point on the vehicle body as proposed in Embodiment 1 of the present invention;

[0048] Figure 8 This is a schematic diagram showing the distribution of the second identification point on the car door as proposed in Embodiment 1 of the present invention;

[0049] Figure 9 This is a schematic diagram of the structure of the high-precision sensor proposed in Embodiment 2 of the present invention;

[0050] Figure 10 This is a structural block diagram of the body-in-white assembly system proposed in Embodiment 2 of the present invention.

[0051] Explanation of reference numerals in the attached figures:

[0052] 1-Main body, 2-Data cable, 3-Light aperture, 4-Illumination aperture. Detailed Implementation

[0053] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0054] In existing technology, vehicle body dimensions are collected offline using a dual-cantilever coordinate measuring machine in a measuring chamber, and door dimensions are measured using a triangular feeler gauge on a fixture. This method has at least the following problems:

[0055] 1) The collection of body and door size information is carried out offline, resulting in a lag in monitoring the size variations of the body and doors during production;

[0056] 2) The body and door dimension information collected by different devices is stored in a scattered manner, and the dimension information cannot be shared for analysis;

[0057] 3) The current collection frequency of body and door size information is one unit per day, which is small for a production volume of about 1,000 units per day.

[0058] 4) The vehicle body size information and door size information collected offline are not matched one-to-one; the size problems of the vehicle body and doors are difficult to correspond to the overall vehicle matching problems. The output of the problem cause and rectification direction is mostly based on experience and lacks effective corresponding data support.

[0059] 5) The quality of manually assembled car doors depends on the skill level of the employees, and the installation quality varies greatly among different employees.

[0060] To address the above problems, the present invention proposes the following embodiments.

[0061] Example 1

[0062] Please refer to Figures 1 to 8 This embodiment proposes a virtual matching method for vehicle body-in-white, which includes the following steps:

[0063] S1, perform online monitoring of the first identification point on the vehicle body; in specific implementation, the first identification point includes the first mounting point and the first appearance matching point on the vehicle body. Of course, the first identification point is not limited to the first mounting point and the first appearance matching point. In application, to obtain the vehicle body number more clearly and accurately...

[0064] It is understood that the first mounting point can also include all other data at the door opening of the vehicle body, but this method will result in an excessive amount of data. In terms of the assembly of the vehicle body and the door, it is sufficient to include the first mounting point and the first appearance matching point.

[0065] Specifically, the first mounting point is the hinge connection, and its value can be one or more.

[0066] Specifically, with Figure 7 For example, there are two door openings on each of the left and right sides of the vehicle body, and a total of 10 first identification points are set in the two door openings on each side.

[0067] Please refer to Figure 2In specific implementation, the monitoring of the vehicle body includes the following five steps: S11, collecting data from the first identification points on each of the vehicle bodies. During implementation, this can be achieved through high...

[0068] Precision sensors collect data.

[0069] S12, calculate the first deviation between the collected data of the first identification point and the first design value, and determine whether the first deviation is greater than the set first parameter. If so, issue an alarm. That is, during implementation, in

[0070] During the line monitoring process, data from the first identification point is used to determine whether the vehicle body meets the requirements. Specifically, if the first deviation is too large, it indicates that the vehicle body dimensions do not meet the requirements, and an alert is issued.

[0071] The alarm provides rapid feedback on the problem. If the first deviation is not greater than the set first parameter, it indicates that the data of the first identification point meets the design requirements and can be used for virtual matching in step S3. In specific implementation, the first parameter can be the tolerance of the first identification point. In specific implementation, there are multiple data points for the first identification point, which are related to...

[0072] There are multiple first deviations. In practical applications, during step S12, each first deviation is compared with its corresponding first parameter. If any first deviation is greater than its corresponding first parameter, the first deviation is determined.

[0073] An alarm will be triggered immediately.

[0074] S2, perform online monitoring of the second identification point on the vehicle door. In specific implementation, the second identification point includes a second mounting point and a second appearance matching point on each of the vehicle doors. The second mounting point corresponds to the first mounting point on the vehicle body, and the second appearance matching point corresponds to the first appearance matching point. That is, when the vehicle door is installed into the corresponding door opening on the vehicle body, the second mounting point on the vehicle door corresponds to the second mounting point on the vehicle body, and the second appearance matching point on the vehicle door corresponds to the first appearance matching point on the vehicle body.

[0075] Please refer to Figure 3 In practical implementation, to quickly eliminate car doors whose dimensions do not meet the installation requirements, this step further includes, S21, collecting data from the second identification points on each of the car doors. The data from the second identification points is used to determine whether the car door installation requirements are met, and virtual matching is performed based on the correspondence between the second identification points and the first identification points.

[0076] S22, calculate the second deviation between the collected data from the second identification point and the second design value, and determine whether the second deviation is greater than the set second parameter. If so, issue an alarm. The purpose of this step is to make a preliminary judgment on the data from the second identification point to identify doors that do not meet installation requirements in advance. That is, when the second deviation is greater than the second parameter, the door size does not meet the installation requirements, and an alarm is issued to facilitate the early removal of doors that do not meet the installation requirements from the production line. In practical implementation, since there are multiple data points for the second identification point, there are also multiple corresponding second deviations, and multiple second deviations are associated with multiple second parameters. In actual application, each second deviation is compared with its corresponding second parameter. When any second deviation is greater than its corresponding second parameter, an alarm is issued.

[0077] Furthermore, it also includes S3, which involves performing virtual matching on the monitored vehicle body and multiple doors to obtain the optimal door that matches the vehicle body. That is, virtual matching is performed using data from the monitored first and second identification points. In practical applications, the more first identification points there are, and the more data they contain, the more accurate the matching will be. Virtual matching helps to find the door that best matches the vehicle body, which is then selected as the optimal door. In implementation, the selection of the optimal door is based on matching accuracy; preferably, it is based on the matching dimensions of the circumferential gap and step difference measurement points. Please refer to... Figure 4 This step includes the following specific steps:

[0078] S31, the data of each of the first identification points are virtually matched with the data of each of the second identification points. In implementation, the virtual matching can be calculated based on the data of the first and second identification points to obtain the matching dimensions of the circumferential gap and step difference measurement points. Specifically, the more first and second identification points there are, the higher the accuracy of the virtual matching. In practical applications, the circumferential gap can be represented by several points. Of course, with sufficient data, the continuous circumferential gap of the car door can also be obtained.

[0079] S32, based on the virtual matching results, determine the optimal door that matches the vehicle body. Specifically, the optimal door refers to the door that best matches the vehicle body among multiple doors; more specifically, it refers to the door with the smallest circumferential gap after virtual matching with the vehicle body. For details, please refer to... Figure 5 This step includes:

[0080] S321, Virtually measure the matching dimensions of the circumferential gaps and step differences between the virtual-matched vehicle body and each of the doors. In this step, the matching dimensions of the circumferential gaps and step differences are virtually measured, and the doors that best match the vehicle body are determined using these dimensions.

[0081] S322, determine the optimal door based on the matching dimensions of the circumferential gap and the step difference measuring points. In practice, the gaps corresponding to several points of the circumferential gap and the matching dimensions of the step difference measuring points can be selected, normalized first, and then the index parameters that can represent the fit can be calculated using a weighted summation method. Then, the door corresponding to the minimum value of each index parameter is selected as the optimal door. That is, the smaller the circumferential gap and the smaller the matching dimensions of the step difference measuring points, the higher the matching accuracy between the car body and the door.

[0082] S4, assemble the vehicle body with the optimal door. That is, after selecting the optimal door, assemble the optimal door with the vehicle body. Please refer to... Figure 6 The specific installation process includes the following steps:

[0083] S41, calculate the optimal posture data for the optimal door assembly. That is, calculate the optimal posture data for the optimal door assembly based on the correspondence between the data of the first identification point and the second identification point. In specific implementation, the optimal posture data includes data for representing the installation position and data for representing the posture during installation.

[0084] S42 transmits the optimal posture data to the execution robot. The execution robot is a robotic arm capable of grasping the car door as required. The optimal posture data can be transmitted to the execution robot via either a wireless network or a wired network.

[0085] S43, the robot assembles the optimal car door onto the vehicle body according to the optimal posture data. That is, after the robot grasps the optimal car door, it grasps the optimal car door to the designated position and adjusts it into place according to the optimal posture data so that the optimal car door can be assembled onto the vehicle body.

[0086] In practice, to facilitate identification of whether the optimal door is in the optimal position and posture, the vehicle body and the optimal door can be monitored in real time, and the corresponding data can be used as feedback data for adjustment.

[0087] Example 2

[0088] This embodiment proposes a body-in-white assembly system based on Embodiment 1. The virtual matching method for body-in-white proposed in Embodiment 1 can be applied to the body-in-white assembly system proposed in this embodiment.

[0089] Please refer to Figure 9 and Figure 10This embodiment proposes a body-in-white assembly system, which includes a first sensor, a second sensor, a door online monitoring unit, a body online monitoring unit, a control unit, and an execution robot. Both the first and second sensors are high-precision sensors. The first sensor is used to collect door data, such as data from the second identification point in Embodiment 1; the second sensor is used to collect body data, such as data from the first identification point in Embodiment 1.

[0090] In a specific implementation, the high-precision sensor includes a body 1 and a data cable 2 connected to the body 1. The body 1 is provided with at least two light holes 3 and at least one illumination hole 4. Specifically, the first sensor is electrically connected to the vehicle door online monitoring unit.

[0091] The second sensor is electrically connected to the vehicle body online monitoring unit. The second sensor outputs the collected data to the vehicle body online monitoring unit, enabling the unit to determine whether the vehicle body meets assembly requirements based on the data collected by the second sensor.

[0092] Both the door online monitoring unit and the body online monitoring unit are electrically connected to the control unit. The door online monitoring unit is used to input to the control unit the door that meets the installation requirements after being judged by the door online monitoring unit. The body online monitoring unit is used to input to the control unit the body that meets the installation requirements after being judged by the body online monitoring unit.

[0093] Furthermore, the first sensor is used to collect door data; the second sensor is used to collect vehicle body data; in specific implementation, the door data includes data from the second identification point, and the vehicle body data includes data from the first identification point.

[0094] The online door monitoring unit acquires door data collected by the first sensor, determines whether the door deviation meets requirements based on the data, and issues an alarm when the deviation does not meet requirements. When the door data deviation does not meet requirements, it indicates that the door does not meet assembly requirements and should be promptly removed from the assembly line for rework or disposal as scrap. In practice, an alarm can be issued to notify workers to remove the corresponding door. To facilitate identifying the cause of non-compliance, the corresponding door data can be stored simultaneously with the alarm for analysis, enabling improvements to the door manufacturing process and increasing product yield. When the door data deviation meets requirements, it indicates that the door meets assembly requirements, and the online door monitoring unit outputs the compliant door data to the control unit.

[0095] The vehicle body online monitoring unit is used to acquire vehicle body data collected by the second sensor, determine whether the deviation of the vehicle body meets the requirements based on the vehicle body data, and issue an alarm when the deviation of the vehicle body data does not meet the requirements. If the deviation of the vehicle body data does not meet the requirements, it indicates that the vehicle body does not meet the assembly requirements and should be promptly removed from the assembly line for rework or disposal as scrap. In specific implementation, an alarm can be issued to notify workers to remove the corresponding vehicle body. Furthermore, to facilitate finding the cause of the non-compliant vehicle body, additional measures can be taken.

[0096] While issuing an alarm, the corresponding vehicle body data is stored for analysis to identify the reasons for non-compliance with requirements. This facilitates improvements in vehicle body manufacturing processes and increases product yield. When the deviation of the vehicle body data meets the requirements, it indicates that the vehicle body meets the assembly requirements, and the online vehicle body monitoring unit outputs the compliant vehicle body data to the control unit.

[0097] The control unit is used to virtually match the vehicle body and doors based on vehicle body data and door data; and select the optimal door; the control unit is also used to calculate the optimal assembly posture of the door, and output the data corresponding to the assembly posture to the execution robot, so that the execution robot can install the door according to the assembly posture.

[0098] The best car door.

[0099] In practice, the virtual matching between vehicle body data and door data can be achieved by calculating the assembly relationship based on the vehicle body data and door data according to assembly requirements. Alternatively, it could be...

[0100] The vehicle body and door data are directly input into the simulation software for virtual simulation. Ultimately, it all boils down to calculating the vehicle body and door data using pre-set formulas to achieve a matching effect. The optimal door is then selected based on this matching effect. The optimal door is the one that best fits the vehicle body.

[0101] After determining the optimal door type, the best door assembly posture is calculated based on the vehicle body data and door data.

[0102] The system controls the robot to grasp and assemble the car door in the optimal door assembly posture. More specifically, the data corresponding to the door assembly posture mentioned in Example 1 is the optimal posture data, which includes data indicating the door installation position and data indicating the door posture during installation.

[0103] In practical implementation, to facilitate intuitive selection of the optimal door, the control unit also performs virtual measurements on the virtual matching results and selects the optimal door based on these results; in practical implementation,

[0104] Three-dimensional graphics can be generated using software by combining door and body data. Virtual measurement includes matching dimensions of surrounding gaps and step difference measurement points. This virtual measurement can be performed using software. In practical implementation, calculations can also be performed according to pre-set formulas to achieve the purpose of virtual measurement.

[0105] The structure, features, and effects of the present invention have been described in detail above with reference to the embodiments shown in the figures.

[0106] The above description is only a preferred embodiment of the present invention. However, the present invention is not limited to the scope of implementation shown in the drawings. Any changes made in accordance with the concept of the present invention, or equivalent embodiments modified to have equivalent changes, shall be within the protection scope of the present invention as long as they do not exceed the spirit covered by the specification and drawings.

Claims

1. A body-in-white virtual matching method, characterized by: The method comprises the following steps, S1, monitoring the first identification points on the vehicle body online; S2, monitoring the second identification points on the vehicle door online; S3, virtually matching the monitored vehicle body and the plurality of vehicle doors to obtain the best vehicle door that can match the vehicle body; S4, assembling the vehicle body and the best vehicle door.

2. The body-in-white virtual matching method according to claim 1, characterized in that: Step S1 comprises, S11, collecting data of the first identification points on each vehicle body; S12, calculating the first deviation of the collected first identification point data from the first design value, and determining whether the first deviation is greater than the set first parameter, and if so, issuing an alarm.

3. The body-in-white virtual matching method according to claim 2, characterized in that: The first identification points include first mounting points and first appearance matching points on the vehicle body.

4. The body-in-white virtual matching method according to claim 1, characterized in that: Step S2 comprises, S21, collecting data of the second identification points on each vehicle door; S22, calculating the second deviation of the collected second identification point data from the second design value, and determining whether the second deviation is greater than the set second parameter, and if so, issuing an alarm.

5. The body-in-white virtual matching method according to claim 4, characterized in that: The second identification points include second mounting points and second appearance matching points on each vehicle door.

6. The body-in-white virtual matching method according to claim 1, characterized in that: Step S3 comprises, S31, virtually matching the data of each first identification point with the data of each second identification point respectively; S32, determining the best vehicle door that matches the vehicle body according to the virtual matching result.

7. The body-in-white virtual matching method according to claim 6, characterized in that: Step S32 comprises, S321, virtually measuring the matching size of the circumferential gap and the step difference measuring point between the virtually matched vehicle body and each vehicle door; S322, determining the best vehicle door according to the matching size of the circumferential gap and the step difference measuring point.

8. The body-in-white virtual matching method according to any one of claims 1-7, characterized in that: Step S4 comprises, S41, calculating the best posture data of the best vehicle door when assembled; S42, transmitting the best posture data to the execution robot; S43, assembling the best vehicle door to the vehicle body according to the best posture data by the execution robot.

9. A body-in-white assembly system characterized by: It comprises a first sensor, a second sensor, a vehicle door online monitoring unit, a vehicle body online monitoring unit, a control unit and an execution robot; The first sensor is electrically connected with the vehicle door online monitoring unit; The second sensor is electrically connected with the vehicle body online monitoring unit; The vehicle door online monitoring unit and the vehicle body online monitoring unit are both electrically connected with the control unit; The first sensor is used to collect vehicle door data, and the second sensor is used to collect vehicle body data; The vehicle door online monitoring unit is used to obtain the vehicle door data collected by the first sensor, determine whether the deviation of the vehicle door data meets the requirements, and issue an alarm when the deviation of the vehicle door data does not meet the requirements; The vehicle body online monitoring unit is used to obtain the vehicle body data collected by the second sensor, determine whether the deviation of the vehicle body data meets the requirements, and issue an alarm when the deviation of the vehicle body data does not meet the requirements; The control unit is used to virtually match the vehicle body and the vehicle door according to the vehicle body data and the vehicle door data, and select the best vehicle door; the control unit is also used to calculate the assembly posture of the best vehicle door, and output the data corresponding to the assembly posture to the execution robot, so that the execution robot can install the best vehicle door according to the assembly posture.

10. The body-in-white assembly system of claim 9, wherein: The control unit is further configured to virtually measure the virtual matching result, and select the best vehicle door according to the virtual measurement result; The virtual measurement includes matching sizes of the surrounding gaps and the step measurement points.

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