Projection welding error-proofing control system for automobile part production

Abstract

A projection welding mistake-proofing control system for automobile part production comprises a data acquisition module, a central processor module, a big data analysis and early warning module, a mistake-proofing control module, a data storage and management module and a quality inspection module, welding parameters are accurately compared through the big data analysis and early warning module, welding defects are effectively reduced, and production efficiency is improved. The defective rate is reduced; the device protection and fault prediction functions are achieved, the device maintenance frequency and maintenance cost can be reduced, and the service life of the device is prolonged.

Description

Technical Field

[0001] The invention relates to the technical field of projection welding error prevention control, in particular to a projection welding error prevention control system for automobile parts production. Background Art

[0002] In the traditional projection welding process, the setting of welding parameters (such as pressure, current, time, displacement, etc.) often relies on empirical values ​​or simple process tests. Due to the changes in raw materials, component size tolerances and equipment status in different batches, these preset parameters are difficult to always ensure the consistency of welding quality. For example, when the hardness or surface state of the raw materials changes slightly, welding according to fixed parameters may result in insufficient weld strength or welding defects such as pores, cracks, and lack of fusion.

[0003] In the process of large-scale production, as the equipment continues to run, factors such as electrode wear and fluctuations in welding transformer performance will also have a negative impact on welding quality. However, existing welding equipment lacks the ability to monitor and automatically adjust welding parameters in real time, making it difficult to respond to these changes in time during the welding process, resulting in a high welding scrap rate.

[0004] In the current projection welding production process, the workpiece preparation before welding (such as whether the workpiece is installed in the correct position, whether the welded part is clean, etc.) and abnormal conditions during welding (such as electrode short circuit, too large or too small current, etc.) mostly rely on the operator's visual inspection and experience judgment. This manual inspection method is not only inefficient, but also prone to human negligence and misjudgment, resulting in defective welded products flowing into the next process, increasing subsequent rework costs and quality risks. Once an error or abnormality occurs during the welding process, existing welding equipment can usually only send out a simple alarm signal and cannot provide detailed fault information and effective solutions. Operators need to spend a lot of time to troubleshoot problems, further reducing production efficiency, and the equipment may be damaged due to improper operation during the problem solving process.

[0005] The production of automotive parts needs to follow strict quality standards and traceability systems. However, the traditional projection welding process has shortcomings in data recording. It can only record limited basic welding parameters, and lacks comprehensive and systematic records of real-time data changes, abnormal conditions, and corresponding quality inspection results during the welding process. This makes it difficult to quickly and accurately trace the root cause of the problem when a product has quality problems. It is impossible to determine whether the quality defects are caused by raw material problems, equipment failures, or improper process parameter settings, which brings great difficulties to quality improvement and problem solving.

[0006] In summary, with the rapid development of the automobile industry and the continuous improvement of automobile quality requirements, the existing projection welding technology for automobile parts has obvious limitations in welding quality control, error prevention mechanism and quality traceability. Summary of the invention

[0007] In view of the above problems, the present invention proposes a projection welding error-proofing control system for automobile parts production.

[0008] The specific technical solutions are as follows:

[0009] A projection welding error prevention control system for automobile parts production includes six modules: a data acquisition module, a central processing unit module, a big data analysis and early warning module, an error prevention control module, a data storage and management module, and a quality inspection module. The data acquisition module mainly collects data through sensors, and the sensors include pressure sensors, displacement sensors, current sensors, and temperature sensors. During the projection welding process, the data acquisition module collects key parameters such as pressure, displacement, current, and temperature in the welding process in real time, and after converting these analog signals into digital signals, they are sent to the central processing unit module for processing.

[0010] The big data analysis and early warning module compares and analyzes the data collected by the data acquisition module and the central processing unit module with the preset standard welding process parameters to determine whether each parameter is within the normal range. If there is an abnormality, it enters the error prevention control step. If it is normal, the welding process is maintained and continued.

[0011] When the central processing unit module determines that the welding process is normal, the error prevention control module controls the output unit to maintain the normal operating state of the welding equipment so that the welding process proceeds smoothly; when the central processing unit module detects that any parameter is abnormal, the error prevention control measures will be immediately started.

[0012] The data storage and management module can record a large amount of welding process data, including sensor data, welding parameter settings, alarm records, data when abnormalities occur, etc. These data can be stored for a long time and can be queried and analyzed as needed.

[0013] The quality inspection module mainly records and archives the data of welding quality inspection of automobile parts using various quality inspection methods after welding is completed; the inspection results are entered into the projection welding error prevention control system and associated with the welding process data of the parts to form a complete quality record for later inspection.

[0014] The beneficial effects of the present invention are:

[0015] The system uses the pressure, displacement, current and temperature sensors in the data acquisition module to monitor key welding parameters in real time and accurately. At the same time, the quality inspection module is associated with the welding process data to form a closed-loop quality control, making the welding quality highly stable and in line with standards, greatly improving the overall quality level of automotive parts, enhancing the competitiveness of products in the market, and reducing after-sales costs and brand reputation risks caused by quality problems.

[0016] The error-proofing control module maintains efficient equipment operation when welding parameters are normal, and responds immediately once an abnormality is detected, effectively avoiding equipment downtime and production interruptions caused by continued errors, further increasing the output of qualified products per unit time, and making the production rhythm more stable and efficient, helping companies gain advantages in order delivery cycle and capacity improvement, and adapt to rapidly changing market demands.

[0017] Through the accurate comparison of welding parameters by big data analysis and early warning module, welding defects and defective product rates can be effectively reduced. It can protect the equipment and predict faults, reduce the frequency and cost of equipment maintenance, and extend the service life of the equipment. From the perspective of long-term operation, the input-output ratio of human, material and financial resources of the enterprise is optimized, and the overall production cost is effectively controlled, creating favorable conditions for the enterprise in price competition and profit improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is the patent flow chart of the present invention. DETAILED DESCRIPTION

[0019] In order to make the technical solution of the present invention clearer and more explicit, the present invention is further described below in conjunction with the accompanying drawings. Any equivalent replacement of the technical features of the technical solution of the present invention and any solution derived by conventional reasoning shall fall within the protection scope of the present invention.

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] A projection welding error prevention control system for automobile parts production includes six modules: a data acquisition module, a central processing unit module, a big data analysis and early warning module, an error prevention control module, a data storage and management module, and a quality inspection module. The data acquisition module mainly collects data through sensors, and the sensors include pressure sensors, displacement sensors, current sensors, and temperature sensors. During the projection welding process, the data acquisition module collects key parameters such as pressure, displacement, current, and temperature in the welding process in real time, and after converting these analog signals into digital signals, they are sent to the central processing unit module for processing.

[0022] The pressure sensor is installed on the welding electrode and is used to monitor the pressure changes during the welding process in real time; by accurately measuring the pressure, it can be determined whether the contact between the electrode and the workpiece is good and whether the welding pressure meets the set process parameters.

[0023] The displacement sensor is arranged near the welding workbench and can detect the displacement of the workpiece before and after welding; this helps to determine whether the workpiece has undergone abnormal deformation during the welding process, thereby promptly discovering possible welding defects.

[0024] The current sensor is connected in series in the welding circuit and is responsible for monitoring the size and change trend of the welding current. The welding current is one of the key factors affecting the welding quality. By accurately measuring the current, it is possible to determine whether the welding energy is appropriate and whether there is abnormal current fluctuation during the welding process.

[0025] The temperature sensor is placed near the welding area to measure the temperature change during the welding process; too high or too low temperature may cause quality problems of the welded joint. Through the feedback of the temperature sensor, the welding parameters can be adjusted in time to ensure that the welding temperature is within the appropriate range.

[0026] The big data analysis and early warning module compares and analyzes the data collected by the data acquisition module and the central processing unit module with the preset standard welding process parameters to determine whether each parameter is within the normal range. If there is an abnormality, it enters the error prevention control step. If it is normal, the welding process is maintained and continued.

[0027] When the central processing unit module determines that the welding process is normal, the control output unit of the error prevention control module will maintain the normal operating state of the welding equipment to ensure smooth welding process; when the central processing unit module detects that any parameter is abnormal, the error prevention control measures will be immediately initiated; for example, if the welding pressure is too low, the central processing unit module will increase the electrode pressure through the relay; if the welding current is too large, the central processing unit module will adjust the output voltage or current of the welding transformer to reduce the welding current; if abnormal displacement of the workpiece is detected, the central processing unit module may stop the welding process and send an alarm signal to prompt the operator to check whether the workpiece is installed correctly or whether the electrode is worn; it can send an alarm signal to the operator through the human-computer interaction interface in time and display detailed alarm information; the alarm information includes alarm type, alarm time, abnormal parameter value, etc., so that the operator can quickly understand the problem and take corresponding measures to deal with it; the system can also provide corresponding operation prompts according to the alarm situation to help the operator better solve the problem.

[0028] The data storage and management module can record a large amount of welding process data, including sensor data, welding parameter settings, alarm records, data when abnormalities occur, etc. These data can be stored for a long time and can be queried and analyzed as needed; through the data tracing function, it is easy to find out the welding process information of a certain product, understand its welding quality status, and provide a strong basis for product quality tracing and problem analysis; at the same time, through the statistics and analysis of historical data, it is also possible to discover potential problems and laws in the welding process, and provide a reference for optimizing the welding process; when it is necessary to trace the welding quality of a certain automotive component, the corresponding data can be extracted from the data storage unit for analysis to find the causes that may lead to quality problems, such as differences in parts batches, equipment failure periods, etc., which is more convenient and quick.

[0029] The quality inspection module mainly records and archives the data of welding quality inspection of automobile parts by various quality inspection methods after welding is completed; the appearance inspection mainly observes whether the welding joint has surface defects, such as pores, cracks, undercuts, etc.; uses non-destructive testing technologies, such as ultrasonic testing, X-ray testing, etc., to inspect the internal quality of welding to check whether there are defects such as lack of fusion and slag inclusions; conducts welding strength tests, and detects whether the mechanical properties of the welding joints meet the design requirements through methods such as tensile tests and shear tests; enters the inspection results into the projection welding error-proofing control system, and associates them with the welding process data of the component to form a complete quality record for easy later inspection.

[0030] The pressure sensor, displacement sensor, current sensor and temperature sensor in the data acquisition module can collect key parameters in the welding process in real time, and can accurately capture every subtle change. For example, when welding parts such as car seat brackets, precise pressure control can ensure the strength of the weld, displacement sensors can ensure the accuracy of the welding position, and current and temperature sensors can prevent excessive or insufficient welding, thereby ensuring the stability and reliability of the welding quality of parts.

[0031] The quality inspection module uses a variety of quality inspection methods for parts after welding, and records the inspection data and associates it with the welding process data. This makes the entire production quality process form a complete chain, which is convenient for tracing and analyzing the links where quality problems arise, helps to promptly discover and correct quality risks in the production process, and greatly reduces the defective rate.

[0032] The data storage and management module records a large amount of welding process data, including sensor data, welding parameter settings, alarm records, etc. These data can be stored for a long time and can be queried and analyzed. By mining historical data, manufacturers can find out the bottlenecks and optimization points in the production process. For example, by analyzing the parameters and alarm records of different batches of automobile wheel hub welding, it is found that frequent current fluctuations in a certain period of time lead to an increase in the number of alarms. The company can check the power supply equipment or adjust the welding process in a targeted manner to improve the efficiency of subsequent production.

[0033] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A projection welding error prevention control system for automobile parts production, comprising six modules: data acquisition module, central processing unit module, big data analysis and early warning module, error prevention control module, data storage and management module, and quality inspection module, characterized in that: The data acquisition module mainly collects data through sensors, which include pressure sensors, displacement sensors, current sensors and temperature sensors. During the projection welding process, the data acquisition module collects key parameters such as pressure, displacement, current, temperature, etc. during the welding process in real time, and converts these analog signals into digital signals, and then sends them to the central processing unit module for processing.

2. A projection welding error-proofing control system for automobile parts production as claimed in claim 1, characterized in that: The pressure sensor is installed on the welding electrode to monitor the pressure changes during the welding process in real time; the displacement sensor is arranged near the welding workbench to detect the displacement of the workpiece before and after welding; the current sensor is connected in series in the welding circuit to monitor the size and change trend of the welding current; the temperature sensor is placed near the welding area to measure the temperature changes during the welding process.

3. A projection welding error-proofing control system for automobile parts production as claimed in claim 1, characterized in that: The big data analysis and early warning module compares and analyzes the data collected by the data acquisition module and the central processing unit module with the preset standard welding process parameters to determine whether each parameter is within the normal range. If there is an abnormality, it enters the error prevention control step. If it is normal, the welding process is maintained and continued.

4. A projection welding error-proofing control system for automobile parts production as claimed in claim 1, characterized in that: When the central processing unit module determines that the welding process is normal, the error prevention control module controls the output unit to maintain the normal operating state of the welding equipment so that the welding process proceeds smoothly; when the central processing unit module detects that any parameter is abnormal, the error prevention control measures will be immediately started.

5. A projection welding error-proofing control system for automobile parts production as claimed in claim 1, characterized in that: The data storage and management module can record a large amount of welding process data, including sensor data, welding parameter settings, alarm records, data when abnormalities occur, etc. These data can be stored for a long time and can be queried and analyzed as needed.

6. A projection welding error-proofing control system for automobile parts production as claimed in claim 1, characterized in that: The quality inspection module mainly records and archives the data of welding quality inspection of automobile parts using various quality inspection methods after welding is completed; the inspection results are entered into the projection welding error prevention control system and associated with the welding process data of the parts to form a complete quality record for later inspection.

Images