Welding is one of the important processes in the automobile manufacturing process and has high technical requirements. Therefore, the welding quality must be carefully tested. The traditional detection method usually uses a fixed coordinate measuring machine, but this method is complicated in operation, slow in speed, long in cycle, and can only be used for sampling. As a new type of detection method, robot detection has the advantages of large-scale, non-contact, intuitive, fast and high precision. It can be applied to the online detection of automobile body and timely feedback the error information of the product, which not only improves the qualification rate of the product, At the same time, it also provides closed-loop feedback size control means for process improvement and error reduction, which meets the quality engineering requirements of modern manufacturing. Therefore, our company has added the application of robot infrared detection system in the automatic production line of Tongyue Car Welding.
Robot online detection system
The measurement system consists of two diagonally arranged KUKA robots, vision sensors, measurement control cabinets (including measurement computer and image processing system, user interface program, server module, etc.), PLC control cabinet system (security gate module, grating, RFID system). , Z-direction sensor) and other parts. The laser vision probe is a direct device for acquiring image information of the object under test. A probe using a semiconductor laser as a light source can measure the spatial three-dimensional coordinates or functional dimensions of the edges and positioning holes of the vehicle body in a non-contact, on-line manner. The main technical parameters are: resolution 0.01mm, accuracy Â±0.05mm, measuring time 0.5s, working distance 200mm, the total mass of laser probe and sensor bracket is about 12kg.
1. System layout
Two detection robots are arranged on both sides of the MB110 station body of Tongyue Automation. In order to measure some important feature points inside the body, and take into account the key function points before and after the body, through the three-dimensional simulation of the robot, combined with the site layout, determine the layout of the inspection station as shown in Figure 1.
Figure 1 Online inspection workstation layout
2. Measurement point scheme and simulation
(1) Calculation of measuring points The production cycle of the A-welding automation line is 130s/set, the sled transport time is 20s, and the detection time of the single feature point of the robot is about 2.5s. According to this calculation, the maximum number of measurement points of the two robots is: (130-20) / 2.5 = 88 points.
(2) Selection, simulation and confirmation of measurement points The entire welding production line has four key assembly states: side wall assembly, engine compartment assembly, floor assembly and body assembly. We only use an online detection system, that is, the on-line detection system of the body-in-white. Therefore, the more points are measured, the wider the field of view of online monitoring. Before the computer simulation, based on the fixed three-coordinate measuring point, and according to the importance of the measuring point, through the computer three-dimensional simulation and on-site debugging, a total of 77 measuring points were determined.
3. Implementation of detection and achievable functions
(1) Detection process As shown in Fig. 2, the body-in-white moves on the sliding block until the detection station stops and is accurately positioned. The line controller sends a â€œin placeâ€ signal to the detection station controller â†’ the station controller sends a â€œmodelâ€ to the robot. And the "start" signal â†’ the robot starts to work after receiving the signal, and the robot sends a â€œmeasurement requestâ€ and a â€œmeasurement point IDâ€ signal to the measurement controller at each measurement point, waiting for the â€œmeasurement completion signalâ€ sent back by the measurement controller â†’ After the measurement system receives the signal, it starts measuring and recording the data, and then passes it to the measurement analysis software for processing. After the measurement is finished, the â€œmeasurement completionâ€ signal is sent to the robot â†’ the robot receives the â€œmeasurement completion signalâ€ and starts to move to the next measurement point. This completes the measurement of all points to be measured.
Figure 2 shows the online detection process
(2) The functions that the detection system can achieve. There are three functions:
1) Vehicle data query and analysis. The vehicle data query is based on the entire body and reflects the entire body. The vehicle data query can be inquired according to the production time of the vehicle body, or can be inquired according to the number of the vehicle body. The list of query data can be sorted in a variety of ways: body number and point number, point and body number, production time and production shifts. The display of the data uses three different background colors to reflect the manufacturing error of the measurement point.
2) Functional size analysis. Functional size analysis is a comprehensive evaluation of multiple points in a body. The body size produced in a certain period of time can be selected for functional size evaluation, and the body size in a certain body number segment can also be selected for functional size evaluation. Finally, the body number, production time and each function size are listed in the evaluation form. The display of the data in the table can be sorted according to the selected function size item, or the icon display can be selected.
3) Statistical function. The statistics of the test data of the whole production line can be divided into monthly statistics and annual statistics: for the monthly statistics of the products, you can select statistical conditions, such as the month of statistics and the number of different grids. The form of the chart display can be either the pass rate or the daily output; the annual number is counted according to the number of months, so each month's data is counted and appears in the annual chart.
4. Measurement of influencing factors and precautions
In the measurement process, repeated verification, summed up the main factors affecting measurement accuracy have the following four aspects:
(1) The attitude of the sensor when collecting pictures is the highest when perpendicular to the detection of the feature surface, and the measurement accuracy decreases as the tilt angle increases.
(2) Influence of temperature The influence of ambient temperature can be neglected, but the temperature change during the operation of the robot body has a great influence on the measured value. The temperature change mainly causes deviation in the normal direction of the detection characteristic surface (in the vertical measurement). Under extreme conditions, the maximum effect on accuracy is approximately 0.2 mm. Usually, the temperature has little effect.
(3) Influence of measurement characteristics The more obvious the measurement characteristics, the higher the measurement accuracy. For example, the measurement accuracy of the measurement points on the ridge line is higher than that on the edge line, and the measurement accuracy of the plane hole is higher than that of the nut hole.
(4) Robot The higher the repeatability of the robot itself, the higher the accuracy of the measurement.
5. Actual effect
In-line inspection system with increased MB110 station in the A-line welding automation line, real-time monitoring of the critical dimensions of the body-in-white body. The experience has the following effects: fast measurement speed and high precision, realizing online products. 100% detection. When there is a small batch deviation between the test data and the reference data, the control station will automatically alarm and the staff can find the problem in time. According to the trend graph analysis of the monitoring, the field engineer can roughly determine the cause of the problem, guide the direction of solving the problem, compress the scope of the problem, and shorten the time to solve the problem.
Through the system, problems can be found in time, and the repair rate and scrap rate of the body-in-white are reduced. Since the installation of this measurement system, no batch rework and scrapping of the product has occurred.
At present, the visual inspection technology based on industrial robots has become a hotspot for large foreign companies. Moreover, the major automobile manufacturers have also set the flexible visual inspection of industrial robots as the application trend of online detection in the future. At present, the industrial robot vision detection technology has realized the online flexible detection of the automobile body-in-white, the automatic installation of the windshield, the automatic installation of the car door, the detection of the laser weld seam, etc., and has been successfully applied to international famous such as BMW, DaimlerChrysler, GM, etc. Automobile manufacturers are gradually applying them in independent brand automobile manufacturers.
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