An intelligent welding quality monitoring system based on laser detection

Abstract

The present invention discloses an intelligent welding quality monitoring system based on laser detection, which relates to the technical field of welding quality monitoring, and includes a non-contact detection module, a contact detection module, a non-contact detection protection module, a contact detection protection module, a data acquisition module, an intelligent analysis module and a feedback control module; the non-contact detection module and the contact detection module are used for contactless and contact acquisition of welding area information, respectively. The present invention provides a comprehensive detection means for the intelligent welding quality monitoring system by setting a non-contact detection module including a visual detection unit and a laser detection unit, and a contact detection module including a sensor unit, an ultrasonic detection unit and an eddy current detection unit, which can solve the problems of incomplete welding quality monitoring during the welding process, inability to simultaneously detect welding internal defects and welding surface defects, and errors caused by human factors, and comprehensively improve the level of welding quality monitoring.

Description

Technical Field

[0001] The invention relates to the technical field of welding quality monitoring, and in particular to an intelligent welding quality monitoring system based on laser detection. Background Art

[0002] Traditional welding quality monitoring systems focus on the quality inspection of the welding surface during the welding process, and it is difficult to effectively detect defects inside the welding joint. This one-sidedness makes it impossible to comprehensively evaluate the welding quality. The welding quality monitoring system of the present application can solve the problems of incomplete welding quality monitoring during the welding process, the inability to simultaneously detect internal defects of the welding and the detection of welding surface defects and errors caused by human factors.

[0003] The defects of the existing welding quality monitoring system are:

[0004] 1. Patent document JP6359189B2 discloses a welding quality monitoring system, method and device. The document mainly considers how to improve the accuracy of monitoring information, but does not consider how to solve the problems of incomplete welding quality monitoring during welding, inability to simultaneously detect welding internal defects and welding surface defects, and errors caused by human factors;

[0005] 2. Patent document CN111070694B discloses a pipeline welding quality monitoring method and system based on big data. The document mainly considers how to monitor pipeline welding quality more effectively, but does not consider how to solve the problem that the detection equipment is easily damaged by sparks, spatter, high temperature, strong light and ultraviolet rays during the welding process;

[0006] 3. Patent document CN108188560B discloses a handheld resistance welding quality monitoring system based on Linux system. The document mainly considers the problem of how to monitor the quality of spot welding online, but does not consider how to solve the problems of low data quality, difficult defect detection, incomplete quality assessment, inaccurate trend prediction and insufficient decision support during welding;

[0007] 4. Patent document CN101767452B discloses an electric fusion welding machine and implementation method for realizing welding quality monitoring through a wireless network. The document mainly considers the problem of how to locate the welding joint or store and manage the welding process data, but does not consider the problems of incomplete data collection, delayed data processing, unsafe data storage, poor synchronization between modules and untimely feedback control encountered during the welding process. Summary of the invention

[0008] The purpose of the present invention is to provide an intelligent welding quality monitoring system based on laser detection to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions: an intelligent welding quality monitoring system based on laser detection, comprising a non-contact detection module, a contact detection module, a non-contact detection protection module, a contact detection protection module, a data acquisition module, an intelligent analysis module and a feedback control module;

[0010] The non-contact detection module and the contact detection module are used for contactless and contact acquisition of welding area information, respectively; the non-contact detection protection module and the contact detection protection module are used for protecting the non-contact detection module and the contact detection module, respectively; the data acquisition module is used for collecting non-contact and contact detection data, converting, processing, analyzing and storing data, and performing clock synchronization at the same time; the intelligent analysis module is used for pre-processing, defect detection, quality assessment, trend prediction and decision support of the collected data, and visualizing the results; the feedback control module is used for adjusting the welding process parameters through the programmable logic controller, the execution unit and the feedback sensor according to the intelligent analysis results;

[0011] The non-contact detection module includes a visual detection unit and a laser detection unit;

[0012] The visual inspection unit includes a high-resolution industrial camera, a light source supply subunit, an image processor, and an image storage and display device. The high-resolution industrial camera is used to collect images of the welding area, the light source supply subunit is used to provide illumination, the image processor is used to process and analyze the collected images, and the image storage and display device is used to store the inspection images and display the inspection results;

[0013] The laser detection unit includes a high-precision laser sensor, a laser controller and an optical subunit. The high-precision laser sensor is used to emit a laser beam and receive reflected light. The laser controller is used to adjust the working parameters of the high-precision laser sensor. The optical subunit is used to guide and focus the laser beam.

[0014] The contact detection module includes a sensor unit, an ultrasonic detection unit and an eddy current detection unit;

[0015] The sensor unit includes a temperature sensor, a stress sensor and a sound sensor, wherein the temperature sensor, the stress sensor and the sound sensor are respectively used for real-time monitoring of welding temperature, welding stress and welding stress sound;

[0016] The ultrasonic testing unit includes an ultrasonic probe, an ultrasonic detector, a coupling agent and a standard test block. The ultrasonic probe contacts the welding surface and is used to transmit and receive ultrasonic signals. The ultrasonic detector is used to process and analyze the ultrasonic signals. The coupling agent is filled between the ultrasonic probe and the welding surface. The standard test block is used to calibrate and verify the ultrasonic testing equipment.

[0017] The eddy current detection unit includes an eddy current probe, an eddy current detector, a signal processor and a comparison test block. The eddy current probe is close to the welding surface and is used to generate and detect eddy current signals. The eddy current detector is used to analyze the eddy current signals. The signal processor is used to process the eddy current signals. The comparison test block is used to calibrate and compare the eddy current detection results.

[0018] Preferably, the non-contact detection and protection module includes a visual detection and protection unit and a laser detection and protection unit;

[0019] The visual inspection protection unit includes a transparent high-temperature resistant and sputter-proof quartz protective cover installed in front of a high-resolution industrial camera and a light source supply subunit. The transparent high-temperature resistant and sputter-proof quartz protective cover is used to block sparks and spatters generated during welding. An air purge device is installed on one side of the transparent high-temperature resistant and sputter-proof quartz protective cover. The air purge device is used to blow compressed air onto the surface of the protective cover.

[0020] Preferably, the laser detection protection unit includes a high-temperature resistant and impact-resistant aluminum alloy protective shell installed on the surface of the high-precision laser sensor. A window is provided on the surface of the high-temperature resistant and impact-resistant aluminum alloy protective shell close to the welding object. Window one is used for the high-precision laser sensor to emit and receive laser beams. A protective lens is installed inside window one. Protective lens one is used to filter out strong light and ultraviolet rays generated during the welding process.

[0021] Preferably, the contact detection protection module includes a ceramic protective cover, a polyurethane protective cover and a copper alloy protective cover respectively installed on the outer surfaces of the temperature sensor, the stress sensor, the sound sensor, the ultrasonic probe and the eddy current probe, and the ceramic protective cover, the polyurethane protective cover and the copper alloy protective cover are respectively used to prevent sparks, spatters and high temperature during the welding process from damaging the temperature sensor, the stress sensor, the sound sensor, the ultrasonic probe and the eddy current probe;

[0022] A second window is provided on the surface of the ceramic protective cover, polyurethane protective cover and copper alloy protective cover close to the welding object. The second window is used for detection by temperature sensors, stress sensors, sound sensors, ultrasonic probes and eddy current probes. A second protective lens is installed inside the second window. The second protective lens is used to further block sparks, spatters, strong light and ultraviolet rays during the welding process.

[0023] Preferably, the data acquisition module includes a sensor interface, a data acquisition card, a data storage unit and a clock synchronization unit;

[0024] The sensor interface includes an analog signal interface and a digital signal interface;

[0025] The data acquisition card is used to convert the analog signal received by the sensor interface into a digital signal, process and analyze the digital signal, and transmit the data to the data storage unit and the intelligent analysis module;

[0026] The data storage unit includes a memory and a solid-state drive;

[0027] The clock synchronization unit includes a clock source and a synchronization signal generator.

[0028] Preferably, the analog signal interface is used to connect to the contact detection module to receive analog signals, and the digital signal interface is used to connect to the non-contact detection module to receive digital signals;

[0029] The memory is used to temporarily store the collected data, and the solid-state drive is used to store the collected data for a long time;

[0030] The clock source is used to provide an accurate clock signal, and the synchronization signal generator is used to generate a synchronization signal according to the signal of the clock source and send it to the non-contact detection module, the contact detection module and the data acquisition card.

[0031] Preferably, the intelligent analysis module includes a data preprocessing unit, a defect detection unit, a quality assessment unit, a trend prediction unit and a decision support unit;

[0032] The data preprocessing unit includes a data cleaning subunit, a data normalization subunit and a feature extraction subunit;

[0033] The defect detection unit includes a pattern recognition subunit, an image analysis subunit and a signal processing subunit;

[0034] The quality assessment unit includes an indicator calculation subunit and a comprehensive assessment subunit;

[0035] The trend forecasting unit includes a time series analysis subunit and a machine learning forecasting subunit;

[0036] The decision support unit includes a rule engine subunit and a visualization display subunit.

[0037] Preferably, the data cleaning subunit is used to remove noise, abnormal values ​​and erroneous data from the collected data, the data normalization subunit is used to normalize different types of data, and the feature extraction subunit is used to extract feature parameters that can reflect welding quality from the original data;

[0038] The pattern recognition subunit is used to classify and identify the extracted feature parameters by using machine learning and pattern recognition algorithms. The image analysis subunit is used to analyze the weld image collected by the visual inspection unit. The signal processing subunit is used to process the signals collected by the ultrasonic inspection unit and the eddy current inspection unit.

[0039] The index calculation subunit is used to calculate the index reflecting the welding quality according to the extracted characteristic parameters and the detected defect information, and the comprehensive evaluation subunit is used to conduct a comprehensive evaluation of the welding quality;

[0040] The time series analysis subunit is used to perform time series analysis on the collected data and predict the changing trend of welding quality. The machine learning prediction subunit is used to use machine learning algorithms to establish a welding quality prediction model and predict future welding quality based on historical data.

[0041] The rule engine subunit is used to judge and make decisions on the analysis results according to preset rules and strategies, and provide control instructions for the feedback control subunit. The visualization subunit is used to display the analysis results in the form of charts.

[0042] Preferably, the feedback control module includes a programmable logic controller, a communication interface, an execution unit and a feedback sensor;

[0043] The programmable logic controller is used to receive the instructions of the intelligent analysis module and the signals of the feedback sensor, generate control signals and send them to the execution unit;

[0044] The communication interface is used for data transmission and communication between the programmable logic controller and the intelligent analysis module and welding equipment.

[0045] Preferably, the execution unit includes a welding power supply controller, a motion control system and a wire feeding system controller, the welding power supply controller is used to adjust the output current and voltage of the welding power supply according to the instructions of the programmable logic controller, the motion control system is used to control the motion trajectory and speed of the welding equipment, and the wire feeding system controller is used to adjust the wire feeding speed and wire feeding pressure;

[0046] The feedback sensors include current sensors, voltage sensors and position sensors, which are used to monitor welding current, welding voltage and the position and motion trajectory of welding equipment respectively, and feed back current signals, voltage signals and position signals to the programmable logic controller.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. The present invention provides a comprehensive detection method for the intelligent welding quality monitoring system by setting a non-contact detection module including a visual detection unit and a laser detection unit, and a contact detection module including a sensor unit, an ultrasonic detection unit and an eddy current detection unit. Through a high-resolution industrial camera and a light source supply subunit, the visual detection unit can capture the image of the welding area in real time, and combine with the image processor for rapid analysis to timely discover the appearance defects in the welding process. The laser detection unit uses the reflection characteristics of the laser beam to detect the flatness and height change of the welding surface, and provides accurate data for the control of welding quality. The ultrasonic detection unit transmits ultrasonic waves to the inside of the weld through an ultrasonic probe and receives the reflected signal. After processing and analysis by the ultrasonic detector, the defects inside the weld can be discovered. This non-destructive detection method can ensure the integrity and safety of the weld structure. The eddy current detection unit uses the eddy current effect to generate eddy currents on the welding surface through an eddy current probe and detects the changes in the eddy currents to determine the defects on the welding surface and near the surface. The sensor unit in the contact detection module, including the temperature sensor, stress sensor and sound sensor, can monitor the temperature, stress and sound in the welding process in real time to ensure that the welding process is carried out within the control range and prevent overheating, overstress and other problems. The combined use of multiple detection methods not only improves the comprehensiveness of the detection, but also significantly improves the detection efficiency and accuracy through automated and intelligent processing methods, and reduces errors caused by human factors. Therefore, it can solve the problems of incomplete welding quality monitoring during the welding process, the inability to simultaneously detect internal welding defects, and the inability to detect welding surface defects and errors caused by human factors, comprehensively improve the welding quality monitoring level, and provide reliable guarantee for welding quality.

[0049] 2. The present invention provides comprehensive protection for the detection equipment in the intelligent welding quality monitoring system by setting a non-contact detection protection module and a contact detection protection module. The non-contact detection protection module includes a visual detection protection unit and a laser detection protection unit. The visual detection protection unit adopts a transparent high-temperature resistant and sputtering-proof quartz protective cover and an air purge device to protect the high-resolution industrial camera and the light source supply subunit. The laser detection protection unit uses a high-temperature resistant and impact-resistant aluminum alloy protective shell and a protective lens to protect the high-precision laser sensor. The contact detection protection module is equipped with a ceramic protective cover, a polyurethane protective cover and a copper alloy protective cover for the temperature sensor, the stress sensor, the sound sensor, the ultrasonic probe and the eddy current probe, and a window 2 is opened on the surface of the protective cover and a protective lens 2 is installed. Therefore, the problem that the detection equipment is easily damaged by sparks, spatters, high temperature, strong light and ultraviolet factors during the welding process can be solved, and at the same time, the stability and accuracy of the detection are improved, ensuring that the intelligent welding quality monitoring system can work normally in a harsh welding environment, providing a strong guarantee for improving the welding quality.

[0050] 3. The present invention sets up an intelligent analysis module. The data preprocessing unit effectively removes noise, abnormal values ​​and erroneous data in the collected data through data cleaning, normalization and feature extraction, thereby improving the accuracy and reliability of the data. At the same time, the feature extraction subunit can extract feature parameters valuable for welding quality assessment from massive raw data, providing strong support for subsequent analysis. The defect detection unit uses a variety of technical means such as pattern recognition, image analysis and signal processing to conduct comprehensive and accurate detection of various defects in the welding process, including not only visual inspection of weld appearance defects, but also ultrasonic inspection of internal defects and eddy current inspection of surface defects. Through these means, quality problems in the welding process can be discovered and located in a timely manner. The quality assessment unit calculates various indicators reflecting welding quality and conducts a comprehensive assessment in combination with defect detection information, providing a scientific basis for the overall judgment of welding quality. Trend prediction The measurement unit predicts the changing trend of welding quality through time series analysis and machine learning algorithms, which helps to discover and respond to quality problems in advance and avoid the adverse effects of quality fluctuations on production. At the same time, the prediction results can also provide a reference for the formulation and adjustment of production plans. The decision support unit realizes intelligent processing and intuitive display of analysis results through rule engines and visual displays. The rule engine can judge and make decisions on the analysis results according to preset rules and strategies, and provide accurate control instructions for the feedback control subunit. The visual display helps operators understand the analysis results more intuitively and improve decision-making efficiency and accuracy. In summary, the intelligent analysis module has comprehensively improved the intelligence level of welding quality monitoring by integrating a variety of advanced technologies and methods, and solved the problems of low data quality, difficult defect detection, incomplete quality assessment, inaccurate trend prediction and insufficient decision support in the welding process.

[0051] 4. The present invention sets a data acquisition module and a feedback control module, and the sensor interface supports the acquisition of analog signals and digital signals, so that the contact detection module and the non-contact detection module can be seamlessly connected, ensuring the accurate acquisition of various key data in the welding process, improving the comprehensiveness and flexibility of data acquisition, and the data acquisition card can instantly convert the analog signal into a digital signal, and perform preliminary processing and analysis to ensure that the data maintains a high degree of real-time and accuracy when transmitted to the data storage unit and the intelligent analysis module, providing a solid foundation for subsequent data analysis and quality assessment. At the same time, the storage method combining memory and solid-state hard disk is adopted, which not only ensures the fast access speed of data, but also ensures the long-term safe storage of data, effectively avoids the risk of data loss, and improves the efficiency and reliability of data management. The clock synchronization unit ensures the non-contact detection module by providing accurate clock signals and synchronization signals. The precise synchronous operation between the block, the contact detection module and the data acquisition card can improve the consistency and accuracy of the data. The feedback control module receives the instructions of the intelligent analysis module and the signal of the feedback sensor through the programmable logic controller, generates a precise control signal and sends it to the execution unit, thereby realizing real-time feedback control of the welding process, which not only ensures the stability and reliability of the welding quality, but also improves the automation level of the welding process. The modules are connected and communicated through standard interfaces, making the system integration more convenient and flexible. In summary, the present invention solves the problems of incomplete data collection, delayed data processing, unsafe data storage, poor synchronization between modules and untimely feedback control encountered in the welding process by optimizing key links such as data collection, processing, storage, synchronization and feedback control, significantly improves the stability and reliability of welding quality, reduces production costs, and improves production efficiency. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present invention are described clearly and completely. 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.

[0053] Embodiment 1:

[0054] An intelligent welding quality monitoring system based on laser detection, comprising a non-contact detection module, a contact detection module, a non-contact detection protection module, a contact detection protection module, a data acquisition module, an intelligent analysis module and a feedback control module;

[0055] The non-contact detection module and the contact detection module are used for contactless and contact acquisition of welding area information, respectively; the non-contact detection protection module and the contact detection protection module are used for protecting the non-contact detection module and the contact detection module, respectively; the data acquisition module is used for collecting non-contact and contact detection data, converting, processing, analyzing and storing data, and performing clock synchronization at the same time; the intelligent analysis module is used for pre-processing, defect detection, quality assessment, trend prediction and decision support of the collected data, and visualizing the results; the feedback control module is used for adjusting the welding process parameters through the programmable logic controller, the execution unit and the feedback sensor according to the intelligent analysis results;

[0056] The non-contact detection module includes a visual detection unit and a laser detection unit;

[0057] The visual inspection unit includes a high-resolution industrial camera, a light source supply subunit, an image processor, and an image storage and display device. The high-resolution industrial camera is used to collect images of the welding area, the light source supply subunit is used to provide illumination, the image processor is used to process and analyze the collected images, and the image storage and display device is used to store the inspection images and display the inspection results;

[0058] The laser detection unit includes a high-precision laser sensor, a laser controller and an optical subunit. The high-precision laser sensor is used to emit a laser beam and receive reflected light. The laser controller is used to adjust the working parameters of the high-precision laser sensor. The optical subunit is used to guide and focus the laser beam.

[0059] The contact detection module includes a sensor unit, an ultrasonic detection unit and an eddy current detection unit;

[0060] The sensor unit includes a temperature sensor, a stress sensor and a sound sensor, wherein the temperature sensor, the stress sensor and the sound sensor are respectively used for real-time monitoring of welding temperature, welding stress and welding stress sound;

[0061] The ultrasonic testing unit includes an ultrasonic probe, an ultrasonic detector, a coupling agent and a standard test block. The ultrasonic probe contacts the welding surface and is used to transmit and receive ultrasonic signals. The ultrasonic detector is used to process and analyze the ultrasonic signals. The coupling agent is filled between the ultrasonic probe and the welding surface. The standard test block is used to calibrate and verify the ultrasonic testing equipment.

[0062] The eddy current detection unit includes an eddy current probe, an eddy current detector, a signal processor and a comparison test block. The eddy current probe is close to the welding surface and is used to generate and detect eddy current signals. The eddy current detector is used to analyze the eddy current signals. The signal processor is used to process the eddy current signals. The comparison test block is used to calibrate and compare the eddy current detection results.

[0063] Furthermore, the non-contact detection module obtains information about the welding process by not directly contacting the welding area, thus avoiding interference and damage that may be caused by physical contact;

[0064] The high-resolution industrial camera in the visual inspection unit is the core equipment of visual inspection. It can capture detailed images of the welding area and provide basic data for subsequent image processing and analysis. The light source supply subunit provides stable and uniform lighting conditions to ensure that the industrial camera can capture clear and high-quality images of the welding area. The image processor pre-processes the collected images, and then uses image processing algorithms to extract features and identify abnormal conditions in the welding process. The image storage and display device stores the processed images and detection results, and displays them to the operator through the display screen for real-time monitoring and recording.

[0065] When using high-resolution industrial cameras for welding quality inspection, high-resolution industrial cameras can capture detailed images of various welding anomalies. These images are then further processed by image processors to identify and evaluate specific problems. The following are the various anomalies and their corresponding processing content:

[0066] A. Welding cracks

[0067] High-resolution industrial camera captures content: The camera captures detailed images of the crack area on the welded part. These images clearly show the shape, length and extension direction of the crack, providing a basis for subsequent accurate analysis;

[0068] Image processor processing content: The image processor extracts the characteristics of the crack through advanced algorithms, and automatically identifies the crack, and finally accurately marks the location of the crack on the image, which is convenient for subsequent quality control and repair;

[0069] B. Welding pores

[0070] High-resolution industrial camera captures content: Porosity appears as obvious black spots or dark areas in the welding area. The camera can capture these subtle defects to ensure that no potential problems are missed;

[0071] Image processor processing content: The image processor identifies and analyzes the dark areas or black spots in the image, determines whether they are welding pores by calculating their size, quantity and distribution characteristics, and gives a corresponding evaluation report;

[0072] C. Welding without fusion

[0073] High-resolution industrial camera captures content: The lack of fusion is manifested as unclearness at the welding interface, with signs of incomplete fusion. The camera can capture this subtle interface change;

[0074] Image processor processing content: The image processor deeply analyzes the pixel changes at the welding interface, identifies the unfused area through a specific algorithm, and evaluates its area size to provide data support for quality assessment;

[0075] D. Welding deformation

[0076] High-resolution industrial camera captures content: The camera captures the overall or local shape changes of the welded parts before and after welding. These changes may be caused by factors such as thermal stress and material properties;

[0077] Image processor processing content: The image processor automatically detects and quantifies shape changes by comparing images before and after welding, assesses the degree and specific location of deformation, and provides a basis for subsequent corrective measures;

[0078] E. Welding spatter

[0079] High-resolution industrial camera captures content: The spatter produced during the welding process will leave obvious tracks and landing points in the image, and the camera can capture these dynamic changes;

[0080] Image processor processing content: The image processor identifies and analyzes the trajectory and landing point of spatter, counts the number and distribution characteristics of spatter, and provides a reference for evaluating the stability of the welding process and optimizing welding parameters;

[0081] F. Welding misalignment

[0082] High-resolution industrial camera captures content: When the position of the welding joint deviates from the predetermined position, the camera can capture this misalignment phenomenon to ensure that the problem is discovered in time;

[0083] Image processor processing content: The image processor uses advanced techniques such as edge detection or template matching to accurately locate the actual position of the weld joint and compare it with the predetermined position to evaluate the degree and direction of misalignment;

[0084] G. Welding overburn

[0085] High-resolution industrial cameras capture content: Overburning appears as color abnormalities in the weld area, such as excessive oxidation or burn marks. The camera can capture these obvious color changes;

[0086] What the image processor does: The image processor deeply analyzes the color and texture characteristics of the weld area, identifies the overburned area by comparing the characteristics of the normal weld area, and evaluates its degree and scope.

[0087] The high-precision laser sensor in the laser detection unit emits a laser beam to the welding area and receives the reflected laser. By analyzing the characteristics of the reflected light, the size, shape and position information of the welding area can be measured. The laser controller is used to control the emission parameters and receiving parameters of the laser sensor to ensure the accuracy and reliability of the detection results. The optical subunit is used to guide and focus the laser beam to ensure that the laser can accurately irradiate the welding area and collect the reflected light.

[0088] When using high-precision laser sensors for welding quality monitoring, the sensors can accurately capture various abnormal conditions in the welding process and process them in real time through the combined effects of the laser controller and the optical subunit. The following is a text description of each abnormal condition and its corresponding collection content, processing content, and the role of the optical subunit:

[0089] A. Welding gap changes

[0090] What is collected: The laser sensor senses the change in the welding gap by measuring the change in the length of the reflected light path;

[0091] Processing content: The laser controller calculates the time difference or phase difference of the reflected light, thereby accurately obtaining the specific size of the gap and providing a basis for adjusting the welding parameters;

[0092] Function of the optical subunit: Ensure that the laser beam can accurately irradiate the surfaces on both sides of the weld to achieve accurate measurement of the gap;

[0093] B. Deformation of welding area

[0094] Collection content: The sensor captures the change in the shape of the reflected light spot, reflecting the deformation of the welding area;

[0095] Processing content: The laser controller analyzes the changes in the spot shape, evaluates the degree and direction of deformation, and provides data support for deformation correction;

[0096] Function of the optical subunit: Keep the laser beam focused in the welding area to ensure the accuracy of deformation detection;

[0097] C. Welding position deviation

[0098] Collection content: The position of the reflected light spot is offset, indicating the deviation of the welding position;

[0099] Processing content: The laser controller calculates the position of the reflected light spot and determines the offset of the welding position, providing a basis for adjusting the welding path;

[0100] Function of the optical subunit: accurately guide and position the laser beam to ensure the accuracy of the welding position;

[0101] D. Insufficient / too deep welding depth

[0102] Content collected: Changes in reflected light intensity or time delay reflect changes in welding depth;

[0103] Processing: The laser controller analyzes the intensity or time delay of the reflected light to assess whether the welding depth is appropriate and adjusts the focus depth and penetration of the laser beam accordingly.

[0104] Function of the optical subunit: adjust the focusing state of the laser beam to ensure accurate control of the welding depth;

[0105] E. Inconsistent welding materials

[0106] Collection content: Differences in reflectivity of different materials lead to changes in reflected light intensity;

[0107] Processing content: The laser controller identifies the reflection characteristics of different materials, distinguishes the material types, and provides a basis for the selection and optimization of welding processes;

[0108] Function of the optical subunit: maintain the stability of the laser beam and reduce the impact of material changes on the test results;

[0109] F. Welding surface contamination / oxidation

[0110] Collection content: The scattering degree of reflected light increases or the intensity decreases, reflecting the cleanliness problem of the welding surface;

[0111] Processing content: The laser controller detects the scattering degree and intensity attenuation of the reflected light, evaluates the cleanliness of the surface, and takes appropriate cleaning measures;

[0112] Function of the optical subunit: Ensure that the laser beam can penetrate the slight contamination layer and detect the true welding surface condition;

[0113] G. Movement / vibration during welding

[0114] What is collected: The reflected light spot moves rapidly or shakes, indicating movement or vibration during the welding process;

[0115] Processing content: The laser controller monitors the position changes of the reflected light spot in real time, evaluates the amplitude of movement or vibration, and takes corresponding stabilization measures;

[0116] Function of the optical subunit: Reduce the impact of external vibration on the laser beam through a stable optical system to ensure the accuracy of detection;

[0117] H. Welding cracks and pores

[0118] Collection content: Abnormal distribution of reflected light at welding defects, such as changes in light intensity caused by cracks and pores;

[0119] Processing content: The laser controller analyzes the distribution of reflected light to identify defects such as cracks and pores in welding, providing a basis for quality assessment;

[0120] Function of the optical subunit: Ensure that the laser beam can cover the entire welding area to achieve complete defect detection.

[0121] The contact detection module obtains information about the welding process by physically contacting the welding surface, and is used to measure welding temperature, stress, and sound parameters;

[0122] The temperature sensor in the sensor unit measures the temperature of the welding area in real time, providing data support for controlling the welding temperature and preventing overheating or underheating. The stress sensor is used to measure the stress changes generated during the welding process and evaluate the strength and stability of the welded structure. The sound sensor detects the sound or vibration signals generated during the welding process.

[0123] During the welding process, temperature sensors, stress sensors and sound sensors can capture and feedback different abnormal conditions to help monitor and control welding quality. The following is a text description of these abnormal conditions and the corresponding sensor performance:

[0124] A. Overheating

[0125] Temperature sensor: detects that the temperature in the welding area continues to rise and exceeds the preset safety threshold, indicating that the welding process may be overheated;

[0126] Stress sensor: Although stress values ​​may fluctuate temporarily due to high temperatures, in this case the main concern is the direct effect of temperature on weld quality, with stress changes serving as an auxiliary reference;

[0127] Acoustic sensors: The sound may change slightly due to thermal expansion or too rapid melting of the material, but these changes are not the only direct indication of overheating;

[0128] B. Underheating

[0129] Temperature sensor: indicates that the temperature of the welding area is lower than the minimum temperature required to achieve effective welding, indicating that the welding may be insufficient;

[0130] Stress sensor: Due to insufficient temperature, the stress value fails to reach the expected welding strength level, reflecting the inadequacy of welding quality;

[0131] Sound sensor: The sound is relatively stable and lacks the specific frequency caused by high temperature melting, which is also an indirect sign of insufficient welding;

[0132] C. Uneven welding

[0133] Temperature sensor: detects significant differences in temperature at different locations within the weld area, indicating an uneven weld process;

[0134] Stress sensor: The stress distribution is also uneven. Some areas have low stress due to insufficient temperature, while other areas may have abnormal stress due to overheating;

[0135] Sound sensor: Sound and vibration will be different in different positions, and these differences can reflect the difference in welding quality;

[0136] D. Crack generation

[0137] Temperature sensor: Before a crack forms, the temperature may remain normal; but once a crack forms, the local temperature may drop due to heat loss;

[0138] Stress sensor: The crack becomes a stress concentration point, and the stress increases significantly, which may exceed the bearing limit of the material;

[0139] Acoustic sensor: When a crack forms, it may be accompanied by a sharp sound or vibration with a sudden change in frequency, which is a direct acoustic manifestation of the crack.

[0140] E. Welding deformation

[0141] Temperature sensor: Uneven temperature distribution is the main cause of overall or local deformation of welded parts;

[0142] Stress sensor: The stress state in the deformed area changes, usually manifested as an increase in tensile or compressive stress;

[0143] Sound sensor: Due to structural deformation, sound may produce abnormal vibration or reverberation, which is an indirect acoustic feedback of deformation;

[0144] F. Bubbles or inclusions

[0145] Temperature sensor: Although temperature has some effect on gas evolution and inclusion melting, the direct correlation is not obvious;

[0146] Stress sensor: Stress distribution can be affected by the presence of bubbles or inclusions, leading to local stress concentration;

[0147] Acoustic sensor: In this case, the sound and vibration usually do not change significantly and are not the primary means of detecting bubbles or inclusions;

[0148] G. Welding fracture

[0149] Temperature sensor: Before breaking, the weld area may experience a sudden temperature change or a long period of high temperature;

[0150] Stress sensor: The stress at the breaking point will increase dramatically until it exceeds the strength limit of the material;

[0151] Acoustic sensor: The moment of fracture produces loud sound and vibration, which is direct acoustic evidence of the fracture event.

[0152] The ultrasonic probe in the ultrasonic testing unit contacts the welding surface, emits ultrasonic waves and receives reflected ultrasonic signals. The ultrasonic detector processes and analyzes the received ultrasonic signals. By measuring the propagation time, amplitude and phase parameters of the ultrasonic waves, the quality of the weld joint can be evaluated. The coupling agent is filled between the ultrasonic probe and the welding surface to ensure that the ultrasonic waves can be transmitted efficiently and reduce energy loss. The standard test block is used to calibrate the precision and accuracy of the ultrasonic testing equipment to ensure the reliability of the measurement results.

[0153] There are many types of defects that may occur during welding. Each type of defect will present a unique signal characteristic on the ultrasonic detector, accompanied by a corresponding description of the welding quality abnormality. The following is an explanation of these defects and their detection signals and abnormal descriptions:

[0154] A. Pores

[0155] Signal characteristics detected by ultrasonic detector: The pores appear as a stable waveform on the ultrasonic detector, with a single and obvious peak. This waveform feature does not change with the movement direction of the probe, indicating the stable nature of the pores as fixed holes.

[0156] Description of abnormal welding quality: The formation of pores is due to the failure of the gas in the molten pool to escape in time during the welding process, thus forming holes inside the weld. These holes will significantly reduce the effective cross-sectional area and bearing capacity of the weld, and have an adverse effect on the overall strength of the welded structure;

[0157] B. Slag inclusion

[0158] Signal characteristics detected by ultrasonic detector: The signal of slag inclusion on ultrasonic detector is similar to the echo of dot trace, with small width and often accompanied by dendritic diffusion characteristics, which indicates the presence of irregularly shaped metal or non-metal impurities in the weld;

[0159] Abnormal welding quality description: Slag inclusion is caused by irregular metal or non-metal impurities remaining in the weld during the welding process. These impurities will reduce the strength and density of the weld and have a negative impact on the performance of the welded joint;

[0160] C. Crack

[0161] Signal characteristics detected by ultrasonic detectors: Cracks appear as high-amplitude and wide-wave signals on ultrasonic detectors, and usually contain multiple peaks. These peaks change with the movement direction of the probe, showing the irregular extension and changes of cracks inside the weld.

[0162] Description of abnormal welding quality: Cracks are cracks inside the weld caused by welding stress or other adverse factors. The existence of cracks will greatly increase the risk of structural fracture and pose a serious threat to the safety and reliability of the welded structure;

[0163] D. Incomplete penetration

[0164] Signal characteristics detected by the ultrasonic detector: Incomplete penetration is manifested on the ultrasonic detector as the absence or significant weakening of the bottom reflection signal, which indicates that the root of the joint was not fully melted during welding, forming an unfused area;

[0165] Description of abnormal welding quality: Incomplete penetration is one of the common problems in the welding process. It will reduce the effective cross-sectional area of ​​the weld, thereby reducing the strength of the joint. This defect is easy to cause fracture when bearing load, posing a potential threat to the safety of the welded structure;

[0166] E. Unfused

[0167] Signal characteristics detected by ultrasonic detector: Lack of fusion is manifested on ultrasonic detector as abnormal reflection signals at the interface between weld and base material or weld. These abnormal signals may include changes in signal intensity, distortion of signal shape or loss of signal, etc.

[0168] Description of abnormal welding quality: Lack of fusion refers to the phenomenon that the weld and the base material or the welds are not completely melted and combined during welding. This defect will significantly reduce the strength of the joint and make the welded structure prone to breakage when bearing load.

[0169] The eddy current probe in the eddy current detection unit is close to the welding surface, and uses the principle of electromagnetic induction to generate eddy current signals and detect changes in eddy current signals. The eddy current detector analyzes the eddy current signals to judge the welding quality. The signal processor filters and amplifies the eddy current signals to improve the signal quality and facilitate subsequent analysis. The comparison test block is used to calibrate and compare the eddy current detection results to ensure the accuracy and consistency of the measurement results.

[0170] In welding quality monitoring, eddy current detection technology collects change information of the welding area through eddy current probes, and the signal processor pre-processes this information. Finally, the eddy current detector performs detailed analysis to identify different welding quality anomalies. The following is a description of each quality anomaly and its corresponding eddy current detection process:

[0171] A. Crack

[0172] What the eddy current probe collects: When the eddy current encounters a crack, its flow is hindered, causing a significant change in the collected signal;

[0173] Signal processor processing content: The processor first filters the collected signal to remove noise interference, and then amplifies the weak signal changes to make it clearer and more discernible;

[0174] Eddy current detector analysis content: By analyzing the distribution of eddy currents in the welding area, the detector can identify areas with uneven eddy current distribution and determine the location of the crack and its approximate size based on this;

[0175] B. Unfused

[0176] What the eddy current probe collects: At the boundary of the unfused area, the flow characteristics of the eddy current will change, causing the collected signal to present a specific pattern;

[0177] Signal processor processing content: The main task of the processor is to remove interference components in the signal and enhance the contrast of the signal to make the features of the unfused area more prominent;

[0178] Eddy current detector analysis content: The detector can accurately determine the location and scope of the unfused area by detecting the interruption of the eddy current path;

[0179] C. Porosity / Slag Inclusion

[0180] Eddy current probe collects information: When the eddy current encounters pores or slag inclusions, it will flow around, causing the signal to attenuate;

[0181] Signal processor processing content: The processor uses filtering technology to smooth the signal while retaining key information that can reflect the characteristics of pores / slag inclusions;

[0182] Eddy current detector analysis content: By analyzing the decay pattern of the eddy current signal, the detector can identify the presence of pores or slag inclusions and may make a preliminary assessment of their number and size;

[0183] D. Welding overheating / overburning

[0184] Eddy current probe collection content: In the area where welding is overheated or overburned, the diffusion range of eddy current will expand, causing the signal characteristics to change;

[0185] What the signal processor does: The processor amplifies these weak but important signal changes and highlights abnormal areas for subsequent analysis;

[0186] Eddy current detector analysis content: The detector detects abnormal patterns of eddy current diffusion, thereby evaluating the degree of overheating or overburning in welding, providing an important basis for quality control;

[0187] E. Uneven welding thickness

[0188] Eddy current probe collection content: Uneven welding thickness will cause changes in the reflection characteristics of eddy currents at the thickness change point;

[0189] What the signal processor does: To accurately measure changes in eddy current path length, the processor adjusts the gain setting to keep the signal consistent across different thickness areas;

[0190] Eddy current detector analysis content: By analyzing the changes in eddy current path length, the detector can accurately determine the distribution of weld thickness and help identify uneven thickness problems during the welding process.

[0191] Embodiment 2:

[0192] An intelligent welding quality monitoring system based on laser detection, the non-contact detection and protection module includes a visual detection and protection unit and a laser detection and protection unit;

[0193] The visual inspection protection unit includes a transparent high-temperature resistant and sputter-proof quartz protective cover installed in front of a high-resolution industrial camera and a light source supply subunit. The transparent high-temperature resistant and sputter-proof quartz protective cover is used to block sparks and spatters generated during welding. An air purge device is installed on one side of the transparent high-temperature resistant and sputter-proof quartz protective cover. The air purge device is used to blow compressed air onto the surface of the protective cover.

[0194] The laser detection protection unit includes a high-temperature resistant and impact-resistant aluminum alloy protective shell installed on the surface of the high-precision laser sensor. A window is provided on the surface of the high-temperature resistant and impact-resistant aluminum alloy protective shell close to the welding object. The window is used for the high-precision laser sensor to emit and receive laser beams. A protective lens is installed inside the window to filter out strong light and ultraviolet rays generated during the welding process.

[0195] Furthermore, the transparent high-temperature resistant and sputter-proof quartz protective cover is made of transparent, high-temperature resistant and sputter-proof quartz material. Quartz has excellent high-temperature resistance and can maintain structural stability in high-temperature environments. At the same time, its transparency ensures that the camera can clearly capture images of the welding area, and the sputter-proof design can effectively block sparks and spatters generated during welding. The protective cover is installed in front of the high-resolution industrial camera and the light source supply subunit to form a protective barrier to isolate the high-resolution industrial camera and the light source supply subunit from the welding area. An air purge device is installed on one side of the protective cover. The air purge device further removes tiny spatters or smoke that may be attached to the protective cover by blowing compressed air to the surface of the protective cover, thereby maintaining the cleanliness and transparency of the protective cover and ensuring the image quality captured by the camera.

[0196] The high temperature and impact resistant aluminum alloy protective shell is made of high temperature and impact resistant aluminum alloy material. Aluminum alloy has good thermal conductivity and mechanical strength, can maintain structural stability in high temperature environment, resist external impact, and protect the internal high-precision laser sensor from damage. A window 1 is opened on the surface of the protective shell close to the welding object. The window 1 is used for the high-precision laser sensor to transmit and receive laser beams. A protective lens 1 is installed inside the window 1. The protective lens 1 can filter out the strong light and ultraviolet rays generated during the welding process, protect the laser sensor from interference from these harmful light, and ensure the accuracy and stability of laser detection;

[0197] The high-temperature-resistant and impact-resistant aluminum alloy protective shell not only provides physical protection for the high-precision laser sensor, but also ensures the smooth emission and reception of the laser beam through the design of window one and protective lens one, while avoiding the intrusion of harmful light, so that the laser detection unit can work stably in harsh welding environments and provide reliable data support for welding quality monitoring.

[0198] Embodiment three:

[0199] An intelligent welding quality monitoring system based on laser detection, wherein the contact detection protection module comprises a ceramic protective cover, a polyurethane protective cover and a copper alloy protective cover respectively installed on the outer surfaces of a temperature sensor, a stress sensor, a sound sensor, an ultrasonic probe and an eddy current probe, wherein the ceramic protective cover, the polyurethane protective cover and the copper alloy protective cover are respectively used to prevent sparks, spatters and high temperature during the welding process from damaging the temperature sensor, the stress sensor, the sound sensor, the ultrasonic probe and the eddy current probe;

[0200] A second window is provided on the surface of the ceramic protective cover, polyurethane protective cover and copper alloy protective cover close to the welding object. The second window is used for detection by temperature sensors, stress sensors, sound sensors, ultrasonic probes and eddy current probes. A second protective lens is installed inside the second window. The second protective lens is used to further block sparks, spatters, strong light and ultraviolet rays during the welding process.

[0201] Furthermore, the ceramic protective sleeve has a high melting point, good thermal insulation and chemical stability, and can effectively resist the high temperature generated during welding, preventing heat from being directly conducted to the inside of the temperature sensor, thereby protecting the temperature sensor from damage;

[0202] The polyurethane protective cover has good impact resistance, wear resistance and certain high temperature resistance. It is used to protect stress sensors and sound sensors, because stress sensors and sound sensors may be directly impacted or vibrated by spatter during welding. The softness and elasticity of polyurethane can also buffer these external impacts to a certain extent.

[0203] The copper alloy protective cover has good electrical conductivity and thermal conductivity, and is used to protect ultrasonic probes and eddy current probes. The copper alloy protective cover can further ensure the stability and accuracy of ultrasonic probes and eddy current probes under extreme conditions. At the same time, the hardness of the copper alloy is sufficient to withstand slight mechanical shocks, effectively protecting ultrasonic probes and eddy current probes.

[0204] A second window is provided on the surface of each protective cover close to the welding object. The second window is a detection channel that allows ultrasonic, eddy current, sound, temperature and stress signals to pass through while maintaining relative isolation from the external environment. A second transparent protective lens is installed inside the second window. The second protective lens is made of high temperature resistant and wear-resistant material, which can further block sparks, spatter, strong light and ultraviolet rays generated during the welding process, protect temperature sensors, stress sensors, sound sensors, ultrasonic probes and eddy current probes from being contaminated or damaged, and ensure the clarity and accuracy of the detection signal.

[0205] Embodiment 4:

[0206] An intelligent welding quality monitoring system based on laser detection, the data acquisition module includes a sensor interface, a data acquisition card, a data storage unit and a clock synchronization unit;

[0207] The sensor interface includes an analog signal interface and a digital signal interface;

[0208] The analog signal interface is used to connect to the contact detection module to receive analog signals, and the digital signal interface is used to connect to the non-contact detection module to receive digital signals;

[0209] The data acquisition card is used to convert the analog signal received by the sensor interface into a digital signal, process and analyze the digital signal, and transmit the data to the data storage unit and the intelligent analysis module;

[0210] The data storage unit includes a memory and a solid-state drive;

[0211] The memory is used to temporarily store the collected data, and the solid-state drive is used to store the collected data for a long time;

[0212] The clock synchronization unit includes a clock source and a synchronization signal generator.

[0213] The clock source is used to provide an accurate clock signal, and the synchronization signal generator is used to generate a synchronization signal according to the signal of the clock source, and send it to the non-contact detection module, the contact detection module and the data acquisition card;

[0214] Furthermore, the analog signal interface is used to connect with the contact detection module, convert the parameters detected by the contact detection module into analog electrical signals, and enhance the signal-to-noise ratio and stability of the signal. Unlike the analog signal interface, the digital signal interface is directly connected to the non-contact detection module that outputs digital signals. The digital signal interface has a high data transmission rate and anti-interference ability, which can ensure the accuracy and reliability of the data.

[0215] The data acquisition card further processes and analyzes all received digital signals, including signal denoising, filtering and feature extraction, in order to provide high-quality data for the subsequent intelligent analysis module. The memory is used as a temporary storage medium to store the data processed by the data acquisition card until the data is transferred to the solid-state drive or the intelligent analysis module for further processing. The memory has high-speed reading and writing performance, which can ensure fast access to data. However, since it is a volatile memory, the data will be lost after power failure, so the data needs to be regularly transferred to the solid-state drive for long-term storage. The solid-state drive is used to store all the data collected during the welding process for a long time. These data can be used for subsequent quality traceability, fault analysis or process optimization. The solid-state drive has high-speed reading and writing performance, high reliability and large storage space. Compared with traditional mechanical hard drives, it is more shock-resistant and drop-resistant, and can operate stably in harsh industrial environments;

[0216] The clock source is the time reference of the entire system. It generates a stable and accurate clock signal to synchronize the operations of various modules in the system. The synchronization signal generator generates a synchronization signal based on the signal of the clock source and sends it to the non-contact detection module, contact detection module and data acquisition card. These synchronization signals are used to ensure the time consistency of each module during data acquisition and processing. In summary, the data acquisition module integrates the sensor interface, data acquisition card, data storage unit and clock synchronization unit to achieve accurate collection, efficient processing and reliable storage of various types of data in the welding process, providing a solid foundation for subsequent intelligent analysis and quality monitoring.

[0217] Embodiment five:

[0218] An intelligent welding quality monitoring system based on laser detection, wherein the intelligent analysis module includes a data preprocessing unit, a defect detection unit, a quality assessment unit, a trend prediction unit and a decision support unit;

[0219] The data preprocessing unit includes a data cleaning subunit, a data normalization subunit and a feature extraction subunit;

[0220] The data cleaning subunit is used to remove noise, outliers and erroneous data from the collected data, the data normalization subunit is used to normalize different types of data, and the feature extraction subunit is used to extract feature parameters that can reflect welding quality from the original data;

[0221] The defect detection unit includes a pattern recognition subunit, an image analysis subunit and a signal processing subunit;

[0222] The pattern recognition subunit is used to classify and identify the extracted feature parameters by using machine learning and pattern recognition algorithms. The image analysis subunit is used to analyze the weld image collected by the visual inspection unit. The signal processing subunit is used to process the signals collected by the ultrasonic inspection unit and the eddy current inspection unit.

[0223] The quality assessment unit includes an indicator calculation subunit and a comprehensive assessment subunit;

[0224] The index calculation subunit is used to calculate the index reflecting the welding quality according to the extracted characteristic parameters and the detected defect information, and the comprehensive evaluation subunit is used to conduct a comprehensive evaluation of the welding quality;

[0225] The trend forecasting unit includes a time series analysis subunit and a machine learning forecasting subunit;

[0226] The time series analysis subunit is used to perform time series analysis on the collected data and predict the changing trend of welding quality. The machine learning prediction subunit is used to use machine learning algorithms to establish a welding quality prediction model and predict future welding quality based on historical data.

[0227] The decision support unit includes a rule engine subunit and a visualization display subunit.

[0228] The rule engine subunit is used to judge and make decisions on the analysis results according to preset rules and strategies, and provide control instructions for the feedback control subunit. The visualization subunit is used to display the analysis results in the form of charts.

[0229] Furthermore, the data cleaning subunit is used to identify and remove noise, outliers and erroneous data in the data set. These bad data are generated due to equipment failure, environmental interference or human error, which will interfere with the accuracy of the analysis results. The data cleaning process includes missing value filling, outlier detection and replacement, and data smoothing. The data normalization subunit is used to convert various types of data collected during the welding process to the same scale for subsequent analysis and comparison, which helps to avoid certain features with large values ​​from dominating the model and improve the generalization ability of the model. The feature extraction subunit is used to extract useful information for welding quality assessment from the original data. Effective feature extraction can significantly reduce the dimension of the data while retaining key information, thereby improving the efficiency and accuracy of subsequent analysis;

[0230] The pattern recognition subunit uses machine learning or pattern recognition algorithms to classify and identify the extracted feature parameters to detect possible defects in the welding process. These algorithms can learn the differences between normal welding samples and defective samples and classify new samples accordingly. The image analysis subunit specializes in processing the weld images collected by the visual inspection unit. It analyzes the features in the images through image processing technology to detect the geometry and surface quality of the welds, thereby identifying potential defects. The signal processing subunit processes the signals collected by the non-contact sensor. These signals contain physical information in the welding process. Through signal processing technology, characteristic parameters related to welding quality can be extracted;

[0231] The index calculation subunit calculates the index reflecting the welding quality based on the extracted characteristic parameters and the detected defect information. These indexes provide a quantitative basis for the subsequent comprehensive evaluation. The comprehensive evaluation subunit considers multiple quality indicators and comprehensively evaluates the welding quality to obtain a comprehensive score or grade, which is used to judge whether the welded parts are qualified.

[0232] The welding quality of different welding positions of three batches A, B and C were monitored at the same time. The results of intelligent welding quality monitoring are as follows:

[0233] Welding batch Batch A Batch A Batch B Batch B Batch C Batch C Welding position Position 1 Position 2 Position 1 Position 2 Position 1 Position 2 Visual Inspection No obvious defects Smooth surface Micro cracks There is no fusion Perfect appearance Slight slag inclusion on the surface Laser Detection Uniform weld Melt pool stability Weld seam fluctuation Insufficient penetration Fine weld The molten pool fluctuates slightly Current stability 98% (stable) 96% (slightly fluctuating) 85% (unstable) 90% (basically stable) 99% (very stable) 95%(stable) Temperature (℃) 1800 1780 1850(fluctuation) 1750 1790 1810 Stress (MPa) 200 210 180 160 220 205 sound Low noise Slight splashing sound Abnormal noise Loud noise Almost no noise Slight slag inclusion sound Ultrasonic testing No internal defects No obvious echo Internal signs of pores Obvious defect echo No defects Slag inclusion reflection signal Eddy Current Testing Stable signal Small signal fluctuation Signal abnormality Signal attenuation Clear signal The signal fluctuates slightly Defect Type none Slight splash crack crack none Slag inclusion Number of defects 0 1 2 1 0 1 Defect severity none slight medium serious none slight Weld strength index 90% 95% 85% 75% 97% 92% Appearance quality score / 10 9.5 9.8 8.5 7.0 9.9 9.3 Overall Rating 88.2 94.5 82.3 72.1 96.8 91.2 grade qualified excellent qualified Failure excellence good

[0234] The time series analysis subunit performs time series analysis on the collected historical data, identifies the periodicity, trend and seasonal characteristics in the data, and predicts the changing trend of welding quality in the future, which helps to discover potential quality problems in advance and take preventive measures. The machine learning prediction subunit uses machine learning algorithms to establish a welding quality prediction model, which can learn the rules and patterns in historical data and predict future welding quality based on them. Machine learning prediction is usually more flexible and accurate than traditional time series analysis, and can handle complex nonlinear relationships;

[0235] The rule engine subunit judges and makes decisions on the analysis results based on preset rules and strategies. The rule engine can automatically match the analysis results with the rules and generate corresponding control instructions or suggestions based on the matching results. The visualization subunit intuitively displays the analysis results in the form of charts, images or animations. The visualization helps users quickly understand complex analysis results, discover patterns and trends in the data, and make more accurate decisions. In addition, the visualization can also improve the interactivity between users and the system and enhance the user experience.

[0236] Embodiment six:

[0237] An intelligent welding quality monitoring system based on laser detection, wherein the feedback control module includes a programmable logic controller, a communication interface, an execution unit and a feedback sensor;

[0238] The programmable logic controller is used to receive the instructions of the intelligent analysis module and the signals of the feedback sensor, generate control signals and send them to the execution unit;

[0239] The communication interface is used for data transmission and communication between the programmable logic controller and the intelligent analysis module and welding equipment.

[0240] The execution unit includes a welding power supply controller, a motion control subunit and a wire feeding system controller. The welding power supply controller is used to adjust the output current and voltage of the welding power supply according to the instructions of the programmable logic controller. The motion control subunit is used to control the motion trajectory and speed of the welding equipment. The wire feeding system controller is used to adjust the wire feeding speed and wire feeding pressure of the welding wire.

[0241] Feedback sensors include current sensors, voltage sensors and position sensors, which are used to monitor welding current, welding voltage and the position and motion trajectory of welding equipment respectively, and feed back current signals, voltage signals and position signals to the programmable logic controller.

[0242] Furthermore, the programmable logic controller receives instructions from the intelligent analysis module and real-time signals from the feedback sensor. Based on these input information, the programmable logic controller calculates the corresponding control signal through the internal preset logic program and algorithm. The programmable logic controller sends the calculated control signal to the execution unit to achieve precise control of the welding process. At the same time, the programmable logic controller also has fault detection, alarm and self-diagnosis functions to ensure the stable operation of the system;

[0243] The communication interface is a bridge for data transmission and communication between the PLC and the intelligent analysis module, welding equipment and other peripheral devices. It supports multiple communication protocols to ensure that data can be transmitted accurately and quickly. Through the communication interface, the PLC can receive instructions and parameter settings from the intelligent analysis module, and feed back real-time data during the welding process to the intelligent analysis module for further analysis. In addition, the communication interface also allows the PLC to be linked with other equipment for control, thereby improving the automation level of the overall system.

[0244] The welding power supply controller adjusts the output current and voltage of the welding power supply according to the instructions of the programmable logic controller. By accurately controlling the welding parameters, it can ensure that the penetration depth, penetration width and appearance quality of the weld meet the predetermined requirements. The motion control subunit is responsible for controlling the motion trajectory and speed of the welding equipment. By accurately controlling the moving path and speed of the welding head, it can achieve accurate welding of complex welds. At the same time, the motion control subunit can also be dynamically adjusted according to the actual situation during the welding process to adapt to different welding requirements. The wire feeding system controller adjusts the wire feeding speed and wire feeding pressure of the welding wire. By accurately controlling the wire feeding parameters, it can ensure that the welding wire is stably and continuously supplied during the welding process.

[0245] The current sensor monitors the current changes during the welding process. The welding current is one of the important factors affecting the penetration depth and width of the weld. By real-time monitoring of the current value, the stability of the welding process can be judged and the welding parameters can be adjusted accordingly. The voltage sensor monitors the voltage changes during the welding process. The welding voltage and welding current work together to affect the forming quality of the weld. The real-time data provided by the voltage sensor helps to achieve precise control of the welding process. The position sensor monitors the position and motion trajectory of the welding equipment. The position sensor is usually used in conjunction with the motion control subunit to achieve precise control of the welding head position. By real-time monitoring of the position information, it can be ensured that the welding head moves along the predetermined path, thereby achieving precise welding of complex welds. In summary, the feedback control module achieves precise control and real-time monitoring of the welding process through the coordinated work of the programmable logic controller, communication interface, execution unit and feedback sensor. This closed-loop control system can be dynamically adjusted according to the actual situation during the welding process to ensure that the welding quality meets the predetermined standards.

[0246] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered exemplary and non-restrictive in all respects, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims be included in the present invention.

Claims

1. An intelligent welding quality monitoring system based on laser detection, characterized in that: It includes a non-contact detection module, a contact detection module, a non-contact detection protection module, a contact detection protection module, a data acquisition module, an intelligent analysis module and a feedback control module; The non-contact detection module and the contact detection module are used for contactless and contact acquisition of welding area information, respectively; the non-contact detection protection module and the contact detection protection module are used for protecting the non-contact detection module and the contact detection module, respectively; the data acquisition module is used for collecting non-contact and contact detection data, converting, processing, analyzing and storing data, and performing clock synchronization at the same time; the intelligent analysis module is used for pre-processing, defect detection, quality assessment, trend prediction and decision support of the collected data, and visualizing the results; the feedback control module is used for adjusting the welding process parameters through the programmable logic controller, the execution unit and the feedback sensor according to the intelligent analysis results; The non-contact detection module includes a visual detection unit and a laser detection unit; The visual inspection unit includes a high-resolution industrial camera, a light source supply subunit, an image processor, and an image storage and display device. The high-resolution industrial camera is used to collect images of the welding area, the light source supply subunit is used to provide illumination, the image processor is used to process and analyze the collected images, and the image storage and display device is used to store the inspection images and display the inspection results; The laser detection unit includes a high-precision laser sensor, a laser controller and an optical subunit. The high-precision laser sensor is used to emit a laser beam and receive reflected light. The laser controller is used to adjust the working parameters of the high-precision laser sensor. The optical subunit is used to guide and focus the laser beam. The contact detection module includes a sensor unit, an ultrasonic detection unit and an eddy current detection unit; The sensor unit includes a temperature sensor, a stress sensor and a sound sensor, wherein the temperature sensor, the stress sensor and the sound sensor are respectively used for real-time monitoring of welding temperature, welding stress and welding stress sound; The ultrasonic testing unit includes an ultrasonic probe, an ultrasonic detector, a coupling agent and a standard test block. The ultrasonic probe contacts the welding surface and is used to transmit and receive ultrasonic signals. The ultrasonic detector is used to process and analyze the ultrasonic signals. The coupling agent is filled between the ultrasonic probe and the welding surface. The standard test block is used to calibrate and verify the ultrasonic testing equipment. The eddy current detection unit includes an eddy current probe, an eddy current detector, a signal processor and a comparison test block. The eddy current probe is close to the welding surface and is used to generate and detect eddy current signals. The eddy current detector is used to analyze eddy current signals. The signal processor is used to process eddy current signals. The comparison test block is used to calibrate and compare eddy current detection results. The intelligent analysis module includes a data preprocessing unit, a defect detection unit, a quality assessment unit, a trend prediction unit, and a decision support unit; The data preprocessing unit includes a data cleaning subunit, a data normalization subunit and a feature extraction subunit; The defect detection unit includes a pattern recognition subunit, an image analysis subunit and a signal processing subunit; The quality assessment unit includes an indicator calculation subunit and a comprehensive assessment subunit; The trend forecasting unit includes a time series analysis subunit and a machine learning forecasting subunit; The decision support unit includes a rule engine subunit and a visualization display subunit; The data cleaning subunit is used to remove noise, outliers and erroneous data from the collected data, the data normalization subunit is used to normalize different types of data, and the feature extraction subunit is used to extract feature parameters that can reflect welding quality from the original data; The pattern recognition subunit is used to classify and identify the extracted feature parameters by using machine learning and pattern recognition algorithms. The image analysis subunit is used to analyze the weld image collected by the visual inspection unit. The signal processing subunit is used to process the signals collected by the ultrasonic inspection unit and the eddy current inspection unit. The index calculation subunit is used to calculate the index reflecting the welding quality according to the extracted characteristic parameters and the detected defect information, and the comprehensive evaluation subunit is used to conduct a comprehensive evaluation of the welding quality; The time series analysis subunit is used to perform time series analysis on the collected data and predict the changing trend of welding quality. The machine learning prediction subunit is used to use machine learning algorithms to establish a welding quality prediction model and predict future welding quality based on historical data. The rule engine subunit is used to judge and make decisions on the analysis results according to preset rules and strategies, and provide control instructions to the feedback control subunit. The visualization subunit is used to display the analysis results in the form of charts; The feedback control module includes a programmable logic controller, a communication interface, an execution unit and a feedback sensor; The programmable logic controller is used to receive the instructions of the intelligent analysis module and the signals of the feedback sensor, generate control signals and send them to the execution unit; The communication interface is used for data transmission and communication between the programmable logic controller and the intelligent analysis module and welding equipment.

2. The intelligent welding quality monitoring system based on laser detection according to claim 1 is characterized in that: The non-contact detection and protection module includes a visual detection and protection unit and a laser detection and protection unit; The visual inspection protection unit includes a transparent high-temperature resistant and sputter-proof quartz protective cover installed in front of a high-resolution industrial camera and a light source supply subunit. The transparent high-temperature resistant and sputter-proof quartz protective cover is used to block sparks and spatters generated during welding. An air purge device is installed on one side of the transparent high-temperature resistant and sputter-proof quartz protective cover. The air purge device is used to blow compressed air onto the surface of the protective cover.

3. The intelligent welding quality monitoring system based on laser detection according to claim 2 is characterized in that: The laser detection protection unit includes a high-temperature resistant and impact-resistant aluminum alloy protective shell installed on the surface of the high-precision laser sensor. A window is provided on the surface of the high-temperature resistant and impact-resistant aluminum alloy protective shell close to the welding object. The window is used for the high-precision laser sensor to emit and receive laser beams. A protective lens is installed inside the window to filter out strong light and ultraviolet rays generated during the welding process.

4. The intelligent welding quality monitoring system based on laser detection according to claim 1 is characterized in that: The contact detection protection module includes a ceramic protective cover, a polyurethane protective cover and a copper alloy protective cover respectively installed on the outer surfaces of the temperature sensor, the stress sensor, the sound sensor, the ultrasonic probe and the eddy current probe, and the ceramic protective cover, the polyurethane protective cover and the copper alloy protective cover are respectively used to prevent sparks, spatters and high temperature from damaging the temperature sensor, the stress sensor, the sound sensor, the ultrasonic probe and the eddy current probe during the welding process; A second window is provided on the surface of the ceramic protective cover, polyurethane protective cover and copper alloy protective cover close to the welding object. The second window is used for detection by temperature sensors, stress sensors, sound sensors, ultrasonic probes and eddy current probes. A second protective lens is installed inside the second window. The second protective lens is used to further block sparks, spatters, strong light and ultraviolet rays during the welding process.

5. The intelligent welding quality monitoring system based on laser detection according to claim 1 is characterized in that: The data acquisition module includes a sensor interface, a data acquisition card, a data storage unit and a clock synchronization unit; The sensor interface includes an analog signal interface and a digital signal interface; The data acquisition card is used to convert the analog signal received by the sensor interface into a digital signal, process and analyze the digital signal, and transmit the data to the data storage unit and the intelligent analysis module; The data storage unit includes a memory and a solid-state drive; The clock synchronization unit includes a clock source and a synchronization signal generator.

6. The intelligent welding quality monitoring system based on laser detection according to claim 5 is characterized in that: The analog signal interface is used to connect to the contact detection module to receive analog signals, and the digital signal interface is used to connect to the non-contact detection module to receive digital signals; The memory is used to temporarily store the collected data, and the solid-state drive is used to store the collected data for a long time; The clock source is used to provide an accurate clock signal, and the synchronization signal generator is used to generate a synchronization signal according to the signal of the clock source and send it to the non-contact detection module, the contact detection module and the data acquisition card.

7. The intelligent welding quality monitoring system based on laser detection according to claim 1 is characterized in that: The execution unit includes a welding power supply controller, a motion control system and a wire feeding system controller. The welding power supply controller is used to adjust the output current and voltage of the welding power supply according to the instructions of the programmable logic controller. The motion control system is used to control the motion trajectory and speed of the welding equipment. The wire feeding system controller is used to adjust the wire feeding speed and wire feeding pressure. The feedback sensors include current sensors, voltage sensors and position sensors, which are used to monitor welding current, welding voltage and the position and motion trajectory of welding equipment respectively, and feed back current signals, voltage signals and position signals to the programmable logic controller.