Wireless temperature measurement-based friction stir welding seam forming quality prediction method and system

Abstract

The application provides a kind of based on wireless temperature measurement's friction stir welding seam forming quality prediction method and system, comprising: selecting two temperature detection points on stir head respectively to process and form temperature detection through-hole;Thermocouple is installed in temperature detection through-hole;Thermocouple is connected with wireless temperature measurement system, and temperature-time curve in friction stir welding process is acquired;Select temperature characteristic quantity, analyze temperature-time curve in welding stable stage, and obtain the temperature change rate of each temperature detection point;First temperature change rate and second temperature change rate are used to predict and determine the forming quality of friction stir welding seam surface and inside respectively.The application solves the problem that traditional detection method is difficult to directly predict whether there is defect in the inside of weld, directly evaluates the quality of weld by analyzing the thermal cycle curve detected in the welding process;Based on wireless temperature measurement technology, the temperature change in the inside of weld during welding process is accurately detected, and the result is more accurate compared with infrared temperature measurement technology.

Description

Technical Field

[0001] This invention belongs to the field of friction welding technology, and particularly relates to a method and system for predicting the forming quality of friction stir welds based on wireless temperature measurement. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the continuous development of modern industry, reliable joining between similar or dissimilar materials has received increasing attention in fields such as shipbuilding, transportation, aerospace, marine engineering, and petrochemicals, in order to meet requirements such as resource conservation, lightweighting, cost reduction, multi-condition operation, and extended service life. Friction stir welding, as a novel solid-state joining method, effectively solves the problems of porosity and hot cracking that easily occur in traditional fusion welding. It has significant advantages in welding materials such as aluminum alloys, magnesium alloys, and titanium alloys, and is widely used in aerospace, high-speed trains, and shipbuilding.

[0004] Due to the inherent characteristics of friction stir welding (FSW), the workpiece is significantly affected by upsetting forces and shoulder friction during the welding process, requiring clamping and fixing. However, the clamping force applied by the fixtures is typically substantial, easily leading to deformation. Furthermore, the welding process parameters have a significant impact on the material's fluidity during welding, which directly affects the weld formation quality. To improve welding efficiency, welding speeds are often set too high, resulting in lower material temperatures and reduced fluidity, thus causing weld defects. Therefore, to improve weld formation, enhance welding quality, and achieve welding automation, reliable assessment methods need continuous innovation. Incorporating weld formation monitoring during the welding process is of great significance. Wireless temperature measurement-based prediction of friction stir weld formation quality is a reliable assessment method.

[0005] Defects generated during friction stir welding, such as incomplete penetration, voids, and cracks, are difficult to detect due to the very small size of some defects at a certain scale, and there are currently no reliable non-destructive testing methods. Although relatively conservative friction stir welding parameters can be used in engineering applications to control the occurrence of these defects, this also leads to a certain degree that the performance of friction stir welded joints is lower than that of joints with optimal parameters.

[0006] Researchers have designed a closed-loop control system for friction stir welding (FSW) weld formation based on vision sensing, enabling real-time monitoring and parameter adjustment of the weld surface during the welding process. However, due to the unique nature of FSW, it is impossible to fully monitor the changes in the internal materials during welding. Only the weld surface can be monitored and evaluated in real time. The presence or absence of internal defects is inferred by monitoring the quality of the weld surface, and direct monitoring and evaluation of internal defects are not possible. This limits the monitoring of the quality of FSW weld formation.

[0007] With the continuous development of temperature measurement technology and wireless signal transmission technology, temperature monitoring of friction stir welding based on wireless temperature measurement technology has gradually begun to develop. Some researchers have achieved temperature monitoring of the friction stir welding process through infrared temperature measurement technology. However, due to the technical limitations of infrared temperature measurement technology itself, it is greatly affected by environmental interference factors, resulting in low accuracy of temperature monitoring results, which cannot meet the need for accurate measurement of internal temperature changes in the weld. In addition, some researchers have used thermocouples to measure the temperature of the welding process. In order to avoid contact and damage to the thermocouple by the high-speed rotating stirring head, the thermocouple is usually placed at a certain distance from the stirring head. It is not possible to directly measure the temperature change at the interface between the stirring head and the workpiece. No method or system for predicting the forming quality of friction stir welds has been developed. Summary of the Invention

[0008] To overcome the shortcomings of the prior art, this invention provides a method and system for predicting the forming quality of friction stir welds based on wireless temperature measurement. By monitoring the temperature change at the interface between the stirring head and the workpiece during the actual welding process and analyzing the temperature change curve inside the weld, the forming quality of the friction stir weld can be directly predicted, such as whether there are defects such as holes or tunnels. The operation is simple and safe.

[0009] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0010] The first aspect of this invention provides a method for predicting the formation quality of friction stir welds based on wireless temperature measurement, comprising:

[0011] Two temperature detection points are selected on the stirring head, and temperature detection through holes are formed at each point.

[0012] Install a thermocouple inside the temperature sensing through-hole;

[0013] Connect thermocouples to a wireless temperature measurement system to obtain temperature-time curves during friction stir welding.

[0014] Temperature characteristic quantities were selected, and the temperature-time curves during the welding stabilization stage were analyzed to obtain the temperature change rate at each temperature detection point.

[0015] The surface forming quality of friction stir welds is predicted and determined using the first temperature change rate.

[0016] The second temperature change rate is used to predict and determine the internal forming quality of friction stir welds.

[0017] The second aspect of the present invention provides a system for predicting the forming quality of friction stir welds based on wireless temperature measurement, comprising: a stirring head, a thermocouple, a wireless temperature measurement system, and a computing terminal;

[0018] The stirring head has two temperature detection through holes, and thermocouples for detecting temperature data during friction stir welding are installed in the temperature detection through holes.

[0019] The thermocouple is connected to a wireless temperature measurement system, which is used to transmit temperature data to a computing terminal.

[0020] The computing terminal is configured to integrate temperature data into a temperature-time curve, analyze the temperature-time curve during the welding stabilization phase, obtain the temperature change rate at each temperature detection point, predict and determine the surface forming quality of the friction stir weld using a first temperature change rate, and predict and determine the internal forming quality of the friction stir weld using a second temperature change rate.

[0021] The above one or more technical solutions have the following beneficial effects:

[0022] (1) This invention utilizes the weld temperature change curve obtained from the temperature measurement system to establish the relationship between weld quality and temperature change rate, predicting the generation of weld defects during the welding process. This solves the problem that traditional visual monitoring methods cannot directly predict whether there are defects inside the weld. By analyzing the thermal cycle curve during the welding process, it directly predicts the changes that occur inside the workpiece during the welding process and evaluates the weld quality.

[0023] (2) Based on wireless temperature measurement technology, this invention can accurately understand the temperature change inside the weld during the welding process, and the results are more accurate than infrared temperature measurement technology.

[0024] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0025] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0026] Figure 1 This is a flowchart of the method for predicting the forming quality of friction stir welds based on wireless temperature measurement in Example 1.

[0027] Figure 2 (a) is a schematic diagram of the perforation of the stirring head in Example 1;

[0028] Figure 2 (b) is a front view of the perforated stirring head in Example 1;

[0029] Figure 2 (c) is a top view of the perforated stirring head in Example 1;

[0030] Figure 3 (a) is the time-temperature curve of the welding stabilization stage at temperature measurement point 1 under the welding parameters of stirring head speed of 500 rpm and welding speed of 40 mm / min in Example 1.

[0031] Figure 3 (b) is Figure 3 (a) Enlarged view of the time-temperature curve for a certain period of time;

[0032] Figure 4 (a) The time-temperature curve of the welding stabilization stage at temperature measurement point 2 under welding parameters of 500 rpm stirring head speed and 40 mm / min welding speed.

[0033] Figure 4 (b) is Figure 4 (a) Enlarged view of the time-temperature curve for a certain period of time;

[0034] Figure 5 (a) is a macroscopic morphology diagram of the weld;

[0035] Figure 5 (b) is a diagram of the internal morphology of the weld;

[0036] Figure 6 This is a structural diagram of the friction stir weld formation quality prediction system based on wireless temperature measurement in Example 2. Detailed Implementation

[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0038] Example 1

[0039] like Figure 1 As shown, this invention proposes a method for predicting the forming quality of friction stir welds based on wireless temperature measurement, comprising:

[0040] Step 1, machining the thermocouple through hole in the stirring head;

[0041] Determining the location of the through-hole determines the location of the measured temperature data, which is the basis for predicting the weld formation quality. For example... Figure 2As shown in (a), the present invention uses an electrical discharge machining method to machine two through holes with a diameter of 0.8 mm on the stirring head. One of the through holes is located on the bottom surface of the shoulder and at a suitable distance from the edge of the shoulder, forming a suitable angle with the axis of the stirring head. The other through hole is located on the side of the stirring pin and at a suitable distance from the bottom surface of the stirring pin, forming a suitable angle with the axis of the stirring head. The two through holes are located in the same plane and on the same side of the axis of the stirring head.

[0042] Specifically, such as Figure 2 (b) and Figure 2 As shown in (c), the first temperature detection through hole is located on the bottom surface of the shoulder, 1.95 mm away from the edge of the shoulder, and the angle between it and the axis of the stirring head is 37°; the first temperature detection through hole is located on the side of the stirring needle, 1.7 mm away from the bottom surface of the stirring needle, and the angle between it and the axis of the stirring head is 45°.

[0043] Step 2, clamping and fixing the thermocouple:

[0044] The thermocouple measuring end needs to be fixed to the end face of the through hole that can contact the workpiece interface, and the reference end is fixed to the other end of the through hole. Use heat insulation tape to wrap it, and use OB-400 high temperature glue to fix and seal the thermocouple.

[0045] Step 3, Assembly of the wireless temperature measurement system:

[0046] The specific steps for assembling the wireless temperature measurement system are as follows:

[0047] Step 301 integrates the thermocouple signal amplifier, microcontroller, and wireless transmission module onto a printed circuit board to create an integrated circuit board;

[0048] Step 302: Connect the thermocouple signal transmission end to the signal interface of the integrated circuit board, connect the integrated circuit board to the power supply, and put it into standby mode;

[0049] Step 303: Fix the integrated circuit board and power supply to the side of the stirring head;

[0050] Step 304: Connect the USB serial port to the computer.

[0051] Step 4, Temperature acquisition and processing during friction stir welding;

[0052] The steps for acquiring and processing temperature during friction stir welding are as follows: First, turn on the power supply to put the integrated circuit board into operation; then, turn on the USB serial port on the computer to put it into operation, and input the appropriate serial port program on the computer to start receiving electrical signals and converting them into temperature data; set the welding process parameters, start the welding machine, and the integrated circuit board and thermocouple rotate and move together with the stirring head. At the same time, the thermocouple collects the temperature and transmits the temperature signal through the wireless transmission module; then, process the acquired temperature data.

[0053] The specific steps for temperature data processing are as follows:

[0054] Step 401: On the computer, use MATLAB software to convert the acquired hexadecimal digital signal into decimal temperature data.

[0055] Step 402: On the computer, generate a "time-temperature" curve from the converted temperature data;

[0056] Step 5, Processing the time-temperature curve and extracting characteristic quantities (peak temperature, temperature fluctuation amplitude at measurement points):

[0057] The specific steps for processing the time-temperature curve and extracting characteristic quantities (peak temperature, temperature fluctuation amplitude at measurement points, and temperature difference at measurement points) are as follows:

[0058] First, obtain all peak temperature values ​​of the time-temperature curve during a certain period of the welding stabilization phase. Arrange them from largest to smallest, discard the first 5% and the last 5% of values, and calculate the average of the remaining 90% of peak temperature values. This average will be taken as the peak temperature T for this period. Max Then, obtain all the trough temperature values ​​within this period, arrange them from largest to smallest, discard the first 5% and the last 5% of values, and calculate the average of the remaining 90% of trough temperature values. This average will be used as the lowest temperature T during this period. Min The peak temperature T Max With the lowest temperature T Min The difference is taken as the temperature change amplitude T during this period. AM The peak temperature T Max With the lowest temperature T Min The average value is taken as the average temperature T during this period. A The ratio of the temperature change amplitude at each temperature measuring point to the average temperature at the corresponding temperature measuring point is defined as the rate of temperature change, denoted as n, where n = T. AM / T A Temperature change rate is a key predictive indicator for weld formation quality.

[0059] Step 6, Prediction and judgment of weld formation quality:

[0060] Predicting and judging the weld formation quality is a key step in this invention. In friction stir welding, the fluidity of the workpiece material is a crucial indicator, determining the quality of the weld formation. When the material has poor fluidity, it cannot fill the gaps in time with the rotation of the stirring head, easily forming plough-groove defects on the weld surface and tunnel and void-type defects inside the weld. Due to the significant difference in thermal conductivity between air and the workpiece material, when defects occur in the weld, the defective areas are filled with air instead of material, preventing timely heat transfer. Consequently, there is a significant temperature difference between the defective parts and the well-formed parts of the weld. When the weld formation quality is poor, with plough-groove and tunnel defects, the stirring head will pass through the defect location at least twice in one rotation cycle, resulting in significant fluctuations in the temperature curve within a certain range. Conversely, when the weld formation quality is good, the temperature curve shows almost no defects within the measurement accuracy range.

[0061] This invention, combining preliminary experimental data and fitting a large amount of experimental data beforehand, and pre-setting it in a computer terminal, comprehensively compares the relationship between temperature change rate and weld formation quality, and derives the following prediction criteria:

[0062] (1) Temperature measurement point 1 (shoulder part): The surface forming quality of the friction stir weld is predicted and judged using the first temperature change rate n1:

[0063] When n1 < 3.0%, the weld formation quality is good, with no obvious macroscopic defects;

[0064] When 3.0% ≤ n1 < 5.5%, the weld formation quality is moderate and the surface is relatively rough.

[0065] When n1 ≥ 5.5%, the weld formation quality is poor, and obvious plough-groove defects are present on the surface.

[0066] (2) Temperature measurement point 2 (stirring needle side): The second temperature change rate n2 is used to predict and determine the internal forming quality of the friction stir weld.

[0067] When n2 < 0.8%, the weld formation quality is good, with no obvious macroscopic defects;

[0068] When 0.8% ≤ n2 < 1.5%, the weld formation quality is moderate, and small holes or discontinuous holes and tunnels appear inside the weld.

[0069] When n2 ≥ 1.5%, the weld formation quality is poor, and obvious tunnel-type defects appear inside the weld.

[0070] In this embodiment, the friction stir welding process parameters are set as follows: stirring head rotation speed 500 rpm, welding speed 40 mm / min, and stirring head tilt angle 0°. The temperature data collected at temperature measurement point 1 (shoulder portion) is plotted on the computer to obtain a time-temperature curve, as shown below. Figure 3 As shown in (a).

[0071] The thermal cycling curve obtained by selecting a period of time during the welding stabilization phase and then magnifying the curve is shown below. Figure 3 As shown in (b).

[0072] First, obtain the temperature change amplitude T during a certain period of the welding stabilization phase. AM =30℃; then calculate the average temperature T during this period. A =358℃; Calculate the rate of temperature change. At this point, n1 ≥ 5.5%, the weld formation quality is poor, and there are obvious plough-groove defects on the surface. Experimental observation shows that the predicted results are consistent with the experimental observation results, as follows: Figure 5 As shown in (a).

[0073] The temperature data collected at temperature measurement point 2 (stirring needle side) is plotted on the computer to obtain a time-temperature curve, as shown below. Figure 4 As shown in (a).

[0074] The thermal cycling curve obtained by selecting a period of time during the welding stabilization phase and then magnifying the curve is shown below. Figure 4 As shown in (b), first, the temperature change amplitude T during a certain period of the welding stabilization phase is obtained. AM =12℃; then calculate the average temperature T during this period. A =378℃; Calculate the rate of temperature change. At this point, when n² ≥ 1.5%, the weld formation quality is poor, and obvious tunnel-type defects appear inside the weld. Experimental observations show that the predicted results are consistent with the experimental observations, as detailed below. Figure 5 As shown in (b).

[0075] Example 2

[0076] like Figure 6 As shown, this invention proposes a system for predicting the forming quality of friction stir welds based on wireless temperature measurement, including a stirring head, a thermocouple, a wireless temperature measurement system, and a computing terminal.

[0077] Two temperature detection holes are provided on the stirring head. A thermocouple for detecting temperature data during friction stir welding is installed in the temperature detection holes. The thermocouple is connected to a wireless temperature measurement system, which transmits the temperature data to a computing terminal.

[0078] The computing terminal is configured to integrate temperature data into a temperature-time curve, analyze the temperature-time curve during the welding stabilization phase, and obtain the temperature change rate at each temperature detection point; use the first temperature change rate to predict and determine the surface forming quality of the friction stir weld; and use the second temperature change rate to predict and determine the internal forming quality of the friction stir weld.

[0079] The wireless temperature measurement system includes: a thermocouple amplifier, a microcontroller, a wireless transmission and reception system, a printed circuit board, and a power supply. The thermocouple signal amplifier, microcontroller, and wireless transmission module are all integrated onto a single printed circuit board, forming an integrated circuit board.

[0080] Two K-type thermocouples, designated T36-CAXL-010U, are inserted into two pre-machined through holes, allowing direct contact between the temperature sensing endpoints and the workpiece interface. Preferably, OB-400 high-temperature adhesive is used to fix and seal the thermocouples. Since the signal generated by the thermocouples is a weak mV-level electrical signal, it must be amplified before it can be properly sampled by the analog-to-digital converter circuit.

[0081] The AD8495 is a precision K-type thermocouple signal amplifier with cold junction temperature compensation. To accommodate the nonlinear behavior of thermocouples, the AD8495 incorporates a fixed-gain instrumentation amplifier with a gain of 122.4 to amplify the small voltage of the K-type thermocouple, providing an output voltage of 5mV / ℃. This amplifier features high common-mode rejection, suppressing common-mode noise that may be picked up by the long leads of the thermocouple, achieving an output error of less than ±2℃.

[0082] The STC15F408AD microcontroller is used to convert the analog signal from the amplifier into a digital signal.

[0083] In the wireless transmission and reception system, 2.4GHz Bluetooth wireless transmission is adopted, and an appropriate frequency is selected to maximize the integrity and accuracy of data transmission. The signal receiver uses a USB-to-serial chip CH340, directly upgrading ordinary serial devices to the USB bus, facilitating the reception of signals from the customized circuit board using a serial port program on a computer. Preferably, the serial port baud rate is 38400B / s.

[0084] To secure the printed circuit board (PCB) to the stirring head, the PCB measures 100mm in length and 40mm in width. Threaded holes are pre-machined into the stirring head, and the PCB and power supply battery are assembled onto the stirring head using screws. The system is separated from the stirring head surface by heat-insulating gaskets to prevent overheating damage.

[0085] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A friction stir welding seam formation quality prediction method based on wireless temperature measurement, characterized by, The method comprises the following steps: Two temperature detection points are selected on the stirring head, and temperature detection holes are formed by machining respectively; A thermocouple is installed in the temperature detection hole; The thermocouple is connected with a wireless temperature measurement system to obtain a temperature-time curve during the friction stir welding process; Temperature characteristic quantities are selected to analyze the temperature-time curve in the stable welding stage, and the temperature change rate of each temperature detection point is obtained; The first temperature change rate is used to predict and judge the surface forming quality of the friction stir welding seam; The second temperature change rate is used to predict and judge the internal forming quality of the friction stir welding seam; The two temperature detection points are selected on the stirring head, and the temperature detection holes are formed by machining respectively, which comprises: Two temperature detection points are machined to form temperature detection holes with a diameter of 0.8 mm respectively, wherein the first temperature detection hole is located on the bottom surface of the shaft shoulder and is at a distance from the edge of the shaft shoulder and at an angle with the axis of the stirring head; the second temperature detection hole is located on the side surface of the stirring pin and is at a distance from the bottom surface of the stirring pin and at an angle with the axis of the stirring head; the two temperature detection holes are located in the same plane and on the same side of the axis of the stirring head; The thermocouple is installed in the temperature detection hole, which comprises that the measuring end of the thermocouple is fixed on the end face of the hole which can contact the workpiece interface, the reference end is fixed on the other end of the hole, the heat insulation tape is wound, and the thermocouple is fixed and sealed by using high-temperature glue; The wireless temperature measurement system comprises an integrated circuit board and a power supply, and the integrated circuit board is printed with a thermocouple signal amplifier, a single-chip microcomputer and a wireless transmission module; The signal transmission end of the thermocouple is connected with the thermocouple signal amplifier of the integrated circuit board, and the integrated circuit board is connected with a computing terminal through the wireless transmission module.

2. The friction stir welding seam formation quality prediction method based on wireless temperature measurement according to claim 1, characterized in that, The temperature characteristic quantities are selected to analyze the temperature-time curve in the stable welding stage, and the temperature change rate of each temperature detection point is obtained, which comprises: respectively calculate the temperature variation amplitude of two temperature detection points in a certain time period of the welding stable stage ; The temperature average value T of the two temperature detection points in this period of time is calculated respectively A ; The temperature change amplitude of each temperature detection point The ratio of the temperature change amplitude of each temperature detection point to the temperature average of the corresponding temperature detection point is defined as the temperature change rate , .​ 3. The friction stir welding seam formation quality prediction method based on wireless temperature measurement according to claim 1, characterized in that, Utilizing a first temperature rate of change The method for predicting and judging the surface forming quality of a friction stir welding seam comprises: When When < 3.0%, the weld forming quality is good, and there is no obvious macroscopic defect; When 3.0%≤ When 3.0%≤ When 3.0%≤ When 3.0%≤ When 3.0%≤ When 3.0%≤ < When ≥ 5.5%, the weld forming quality is poor, and there are obvious furrow-shaped defects on the surface.

4. The friction stir welding seam formation quality prediction method based on wireless temperature measurement according to claim 1, characterized in that, Utilizing a second temperature rate of change The method for predicting and judging the internal forming quality of a friction stir welding seam comprises: When When <0.8%, the weld forming quality is good, and there is no obvious macroscopic defect; When 0.8%≤ When <1.5%, the weld forming quality is medium, and small holes or discontinuous holes, tunnels appear in the weld interior; When ≥ 1.5%, the weld forming quality is poor, and obvious tunnel type defects appear in the weld.

5. A friction stir welding seam formation quality prediction system based on wireless temperature measurement, characterized by, It comprises: a stirring head, a thermocouple, a wireless temperature measurement system and a computing terminal; The stirring head is provided with two temperature detection holes, and a thermocouple for detecting temperature data during the friction stir welding process is installed in the temperature detection hole; The thermocouple is connected with the wireless temperature measurement system, and the wireless temperature measurement system is used to transmit the temperature data to the computing terminal; The computing terminal is configured to integrate the temperature data into a temperature-time curve, analyze the temperature-time curve in the stable welding stage, obtain the temperature change rate of each temperature detection point, and use the first temperature change rate to predict and judge the surface forming quality of the friction stir welding seam; The second temperature change rate is used to predict and judge the internal forming quality of the friction stir welding seam; The two temperature detection points are selected on the stirring head, and the temperature detection holes are formed by machining respectively, which comprises: Two temperature detection points are machined to form temperature detection holes with a diameter of 0.8 mm respectively, wherein the first temperature detection hole is located on the bottom surface of the shaft shoulder and is at a distance from the edge of the shaft shoulder and at an angle with the axis of the stirring head; the second temperature detection hole is located on the side surface of the stirring pin and is at a distance from the bottom surface of the stirring pin and at an angle with the axis of the stirring head; the two temperature detection holes are located in the same plane and on the same side of the axis of the stirring head; The temperature detection through hole is internally provided with a thermocouple, including: a thermocouple measurement end fixed at a through hole end face capable of contacting a workpiece interface, and a reference end fixed at another end of the through hole, wrapped with a heat insulation tape, and fixed and sealed with a high-temperature adhesive; The wireless temperature measurement system comprises an integrated circuit board and a power supply, and the integrated circuit board is printed with a thermocouple signal amplifier, a single-chip microcomputer and a wireless transmission module; The signal transmission end of the thermocouple is connected with the thermocouple signal amplifier of the integrated circuit board, and the integrated circuit board is connected with a computing terminal through the wireless transmission module.

6. The friction stir welding seam formation quality prediction system based on wireless temperature measurement according to claim 5, characterized in that, Utilizing a first temperature rate of change The method for predicting and judging the surface forming quality of a friction stir welding seam comprises: When <3.0%, the weld forming quality is good, and there is no obvious macroscopic defect; When 3.0%≤ When 3.0%≤ When 3.0%≤ When 3.0%≤ When 3.0%≤ When 3.0%≤ < When ≥ 5.5%, the weld forming quality is poor, and there are obvious furrow-shaped defects on the surface.

7. The friction stir welding seam formation quality prediction system based on wireless temperature measurement of claim 5, wherein, Utilizing a second temperature rate of change The method for predicting and judging the internal forming quality of a friction stir welding seam comprises: When When the weld seam is less than 0.8%, the weld seam forming quality is good and has no obvious macroscopic defects. When 0.8%≤ When <1.5%, the weld forming quality is medium, and small holes or discontinuous holes, tunnels appear in the weld interior; When ≥ 1.5%, the weld forming quality is poor, and obvious tunnel type defects appear in the weld.

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