CN112729106A - Intelligent weld joint real-time detection method and system based on pulse welding - Google Patents
Intelligent weld joint real-time detection method and system based on pulse welding Download PDFInfo
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- CN112729106A CN112729106A CN202011473428.XA CN202011473428A CN112729106A CN 112729106 A CN112729106 A CN 112729106A CN 202011473428 A CN202011473428 A CN 202011473428A CN 112729106 A CN112729106 A CN 112729106A
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- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
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Abstract
The invention discloses an intelligent welding line real-time detection method and system based on pulse welding, wherein the method comprises the following steps: acquiring a pulse welding signal, and generating a camera trigger signal according to the pulse welding signal; triggering a camera to take a picture according to the camera trigger signal to obtain a weld image; and determining the position of the welding seam according to the welding seam image. According to the invention, the camera trigger signal is generated according to the pulse welding signal, and the camera is triggered to take a picture according to the camera trigger signal, so that not only can a clear welding seam image be obtained, but also the welding quality can be detected in real time, the welding quality is improved, and the welding cost is reduced.
Description
Technical Field
The invention relates to the technical field of weld positioning, in particular to an intelligent weld real-time detection method and system based on pulse welding.
Background
Welding is the most used processing method in manufacturing industry, and is widely applied to the fields of mechanical manufacturing, aerospace, water conservancy and hydropower, ocean drilling, ship manufacturing, electronic technology and the like. Traditional welding mainly relies on the manpower, and welding quality depends on workman's technical skill degree, and along with the continuous development of science and technology, welding process is by manual operation to automatic and intelligent orientation development gradually.
As one of the key problems in the automatic welding process, the welding precision and speed are crucial to the welding quality and efficiency, and the position coordinates of the welding seam directly determine the welding precision and quality. In the existing automatic welding process, the problem of inaccurate detection of the position of a welding seam exists due to the influence of high temperature and strong arc light in the welding process on the imaging quality.
Thus, there is still a need for improvement and development of the prior art.
Disclosure of Invention
The invention aims to solve the technical problem that the detection of the position of a welding seam is inaccurate due to the influence of high temperature and strong arc light on the imaging quality in the welding process in the prior art.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides an intelligent weld joint real-time detection method based on pulse welding, where the method includes:
acquiring a pulse welding signal, and generating a camera trigger signal according to the pulse welding signal; the pulse welding signal is a pulse welding voltage signal or a pulse welding current signal;
triggering a camera to take a picture according to the camera trigger signal to obtain a weld image;
and determining the position of the welding seam according to the welding seam image.
The intelligent welding seam real-time detection method based on pulse welding comprises the following steps of:
processing the pulse welding signal to generate a TTL level signal;
and generating a camera trigger signal according to the TTL level signal.
The intelligent welding seam real-time detection method based on pulse welding is characterized in that the TTL level signals comprise TTL peak value level signals and TTL base value level signals, and the step of generating camera trigger signals according to the TTL level signals comprises the following steps:
acquiring TTL peak value level time corresponding to the TTL peak value level signal and TTL base value level time corresponding to the TTL base value level signal;
and generating a camera trigger signal according to the TTL peak value level time and the TTL base value level time.
The intelligent welding seam real-time detection method based on pulse welding is characterized in that the camera trigger signal comprises a peak value trigger signal and a base value trigger signal, and the step of generating the camera trigger signal according to the TTL peak value level time and the TTL base value level time comprises the following steps:
when the TTL level signal is detected to be converted from the TTL base value level signal to the TTL peak value level signal, waiting for a preset first time to generate a peak value trigger signal; wherein the preset first time is half of the TTL peak level time;
when the TTL level signal is detected to be converted from the TTL peak level signal to the TTL base level signal, a preset second time is waited to generate a base trigger signal; and the preset second time is half of the level time of the TTL base value.
The intelligent welding seam real-time detection method based on pulse welding is characterized in that a camera is triggered to shoot according to the camera trigger signal, and the step of obtaining the welding seam image comprises the following steps:
and when the camera trigger signal is detected to be converted from the peak trigger signal to the base trigger signal, triggering the camera to shoot to obtain a welding seam image.
The intelligent welding seam real-time detection method based on pulse welding comprises the following steps that a plurality of structural light bars are contained in a welding seam image, and the step of determining the position of a welding seam according to the welding seam image comprises the following steps:
preprocessing the welding seam image to obtain a preprocessed image;
extracting central lines of a plurality of structural light bars in the preprocessed image, and determining the characteristic types of the plurality of structural light bars according to the preprocessed image after the central lines are extracted;
and determining the position of the welding seam according to the characteristic type.
The intelligent welding seam real-time detection method based on pulse welding is characterized in that the step of preprocessing the welding seam image to obtain a preprocessed image comprises the following steps:
carrying out gray level processing on the welding seam image to obtain a gray level image;
filtering the gray level image to obtain a filtered image;
and performing morphological operation on the filtered image to obtain a preprocessed image.
The intelligent welding seam real-time detection method based on pulse welding comprises the following steps of determining the position of a welding seam according to the welding seam image:
and controlling the welding gun to move to the welding seam position for welding.
In a second aspect, the present invention further provides an intelligent real-time weld seam detection system based on pulse welding, which is characterized by comprising: the intelligent terminal comprises a sensor and an intelligent terminal, wherein the sensor comprises a camera and a laser; wherein the intelligent terminal includes: a processor, a storage medium communicatively coupled to the processor, the storage medium adapted to store a plurality of instructions; the processor is suitable for calling instructions in the storage medium to execute the steps of implementing the intelligent welding seam real-time detection method based on pulse welding.
The intelligent welding seam real-time detection system based on pulse welding is characterized in that the sensor is a monocular vision sensor, a binocular vision sensor or a 3D structured light vision sensor.
The invention has the beneficial effects that: according to the embodiment of the invention, firstly, a pulse welding signal is obtained, a camera trigger signal is generated according to the pulse welding signal, then, a camera is triggered to shoot according to the camera trigger signal to obtain a welding seam image, and finally, the position of the welding seam is determined according to the welding seam image. According to the embodiment, the camera trigger signal is generated according to the pulse welding signal, and the camera is triggered to shoot according to the camera trigger signal, so that clear weld images can be obtained, the welding quality can be detected in real time, the welding quality is improved, and the welding cost is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent weld joint real-time detection method based on pulse welding according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a welding pulse current signal provided by an embodiment of the present invention.
FIG. 3 is a schematic diagram of a TTL level signal generated from the pulsed welding current signal of FIG. 2;
fig. 4 is a schematic diagram of a structure for generating a camera trigger signal from the TTL level signal in fig. 3;
fig. 5 is a functional schematic diagram of an intelligent terminal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indications are changed accordingly.
As one of the key problems in the automatic welding process, the welding precision and speed are crucial to the welding quality and efficiency, and the position coordinates of the welding seam directly determine the welding precision and quality. In the existing automatic welding process, the problem of inaccurate detection of the position of a welding seam exists due to the influence of high temperature and strong arc light in the welding process on the imaging quality.
In order to solve the problems in the prior art, the embodiment provides an intelligent real-time welding seam detection method based on pulse welding, and a clear welding seam image can be obtained through the method, so that the welding seam position detection accuracy is improved. During specific implementation, firstly, a pulse welding signal is obtained, a camera trigger signal is generated according to the pulse welding signal, then, a camera is triggered to shoot according to the camera trigger signal to obtain a welding seam image, and finally, the position of the welding seam is determined according to the welding seam image.
Exemplary method
The embodiment provides an intelligent welding seam real-time detection method based on pulse welding, and the method can be applied to an intelligent terminal. As shown in fig. 1 in detail, the method includes:
s100, acquiring a pulse welding signal, and generating a camera trigger signal according to the pulse welding signal; the pulse welding signal is a pulse welding voltage signal or a pulse welding current signal.
Specifically, the pulse welding signal is a signal generated during the welding process to control the welding torch to perform pulse welding, and the pulse welding signal may be a pulse welding current signal or a pulse welding voltage signal, and when the pulse welding signal is a pulse welding voltage signal, the pulse welding signal is composed of a base voltage signal and a peak voltage signal. As shown in fig. 2, when the pulse welding signal is a pulse welding current signal, the pulse welding signal is composed of a base current and a peak current, the base current is small and can only maintain the arc not to be extinguished, the light intensity at the welding position is weak at this time, the peak current is large and plays a role in melting the base material of the welding wire, and the arc light at the welding position is strong at this time. The pulse welding voltage signal is a voltage signal converted by the pulse welding current signal or a voltage signal for controlling the generation of the pulse welding current signal, and the welding gun is controlled to weld through the pulse welding signal, so that the penetration of a weldment can be ensured, the defects of incomplete fusion, incomplete penetration and the like can be avoided, and the burnthrough of the weldment can be avoided.
Considering that the light intensity is weak when the pulse welding signal is at the base voltage or the current, clear welding seam images can be obtained by triggering the camera to shoot, and the light intensity is strong when the pulse welding signal is at the peak voltage or the current, so that the imaging quality is poor due to the influence of the light temperature and the strong arc light when the pulse welding signal is triggered to shoot. In order to obtain a clear weld image, in the welding process, a pulse welding signal is obtained in real time, and a camera trigger signal is generated according to the pulse welding signal, so that a camera is triggered to take a picture according to the camera trigger signal in the subsequent steps, and the clear weld image is obtained. According to the embodiment, the camera is triggered to shoot according to the pulse welding signal, so that a clear welding seam image can be obtained, the welding seam quality can be detected in real time, the welding quality is improved, and the welding cost is reduced.
In a specific embodiment, the step of generating a camera trigger signal according to the pulse welding signal in step S100 includes:
step S110, performing signal processing on the pulse welding signal to generate a TTL level signal;
and step S120, generating a camera trigger signal according to the TTL level signal.
Specifically, the TTL level signal (transistor-transistor logic level signal) is a level signal in binary representation, and is an ideal data transmission technology inside a computer processor controlled device. In this embodiment, after the pulse welding signal is acquired, the pulse welding signal is subjected to signal processing to generate a TTL level signal that can be recognized by a computer processor, and then a camera trigger signal is generated according to the TTL level signal. As shown in fig. 3, the TTL level signals generated for the pulsed welding current signal of fig. 2 include a TTL peak level signal and a TTL base level signal, as can be seen from fig. 3.
In an embodiment, step S120 specifically includes:
step S121, acquiring TTL peak value level time corresponding to the TTL peak value level signal and TTL base value level time corresponding to the TTL base value level signal;
and S122, generating a camera trigger signal according to the TTL peak value level time and the TTL base value level time.
Specifically, as can be seen from fig. 3, the TTL level signal is similar to the pulse welding signal and is a periodic pulse signal, and in one time period, it is at a TTL peak level signal for a period of time and at a TTL base level signal for another period of time, and the TTL peak level time is the time when the TTL level signal is at the TTL peak level signal for a period of time; and the TTL base value level time is the time when the TTL level signal is in the TTL base value level signal in a time period. As shown in fig. 4, the TTL peak level time corresponding to the TTL peak level signal is TH, and the TTL base level time corresponding to the TTL base level signal is TL.
In this embodiment, after generating the TTL level signal, a TTL peak level time corresponding to a TTL peak level in the TTL level signal and a TTL base level time corresponding to a TTL base level signal are first obtained, and then a camera trigger signal is generated according to the TTL peak level time and the TTL base level time.
In an embodiment, step S122 specifically includes:
step S1221, after the TTL level signal is detected to be converted from the TTL base value level signal to the TTL peak value level signal, waiting for a preset first time to generate a peak value trigger signal; wherein the preset first time is half of the TTL peak level time;
step S1222, after detecting that the TTL level signal is converted from the TTL peak level signal to the TTL base level signal, waiting for a preset second time to generate a base trigger signal; and the preset second time is half of the level time of the TTL base value.
Specifically, the camera trigger signal includes a peak trigger signal and a base trigger signal, similar to the pulse welding signal and the TTL level signal. Considering that the welding arc at the central point of the fundamental voltage or current of the pulse welding signal is weak and stable, a camera is triggered to take a picture at the point to obtain a clearer weld image. In the embodiment, when the camera trigger signal is generated, the time for converting the TTL level signal from the TTL base level signal to the TTL peak level signal and the time for converting the TTL peak level signal to the TTL base level signal are detected in real time. When the TTL level signal is detected to be converted from a TTL base value level signal to a TTL peak value level signal, waiting for a preset first time to generate a peak value trigger signal, wherein the preset first time is half of the TTL peak value level time; when the TTL level signal is detected to be converted into a TTL base value level signal from a TTL peak value level signal, a base value trigger signal is generated after a preset second time is waited; and the preset second time is half of the level time of the TTL base value. For example, with reference to fig. 4, after detecting that the TTL level signal is converted from the TTL base level signal to the TTL peak level signal, the peak trigger signal is generated after waiting for TH/2 time, and after detecting that the TTL level signal is converted from the TTL peak level signal to the TTL base level signal, the base trigger signal is generated after waiting for TL/2 time, so that the time for generating the base trigger signal is exactly located at the center point of the TTL base level signal, i.e., the base voltage or current.
And S200, triggering a camera to shoot according to the camera trigger signal to obtain a welding seam image.
Specifically, after a camera trigger signal is generated according to the pulse welding signal, the camera is triggered to shoot according to the camera trigger signal to obtain a weld image.
In an embodiment, the step S200 specifically includes:
and S210, triggering a camera to shoot to obtain a welding seam image after the camera trigger signal is detected to be converted from the peak trigger signal to the base trigger signal.
Specifically, in the foregoing step, it is mentioned that the time when the peak level trigger signal is converted into the base level trigger signal is exactly located at the central point of the TTL base level signal, i.e., the base voltage or current, at this time, the welding arc is weak and stable, and a camera is triggered to take a picture at this point, so that a clearer weld image can be obtained. Therefore, in the embodiment, when the camera is triggered to photograph according to the camera trigger signal, the time for converting the peak value trigger signal into the base value trigger signal of the camera trigger signal is detected in real time, and when the camera trigger signal is detected to be converted from the peak value trigger signal into the base value trigger signal, the camera is triggered to photograph, so that a clear weld image can be obtained.
And S300, determining the position of the welding seam according to the welding seam image.
Specifically, the weld image obtained in this embodiment includes a plurality of structural light bars, after the weld image is obtained, the weld image is first preprocessed to obtain a preprocessed image, then the preprocessed image is refined by using the existing Hilditch algorithm, the center lines of the plurality of structural light bars in the preprocessed image are extracted, then the feature detection method of priori knowledge is used to perform feature detection on the weld structural light image with the center lines to obtain feature types of the plurality of structural light bars, and finally the position of the weld is determined according to the feature types.
Further, when the position of the weld is determined based on the characteristic types of the plurality of structured light bars, there are two cases. When the characteristic type is that the plurality of linear light strips are all linear light strips, the slope of each linear light strip is obtained, the product of the slopes of any two linear light strips is obtained, and when the product of the slopes is smaller than zero, the intersection position of the two linear light strips is determined as the position of the welding line. And when the characteristic type is that the plurality of structured light bars comprise a linear structured light bar and a curve structured light bar, determining the intersection point position of the linear structured light bar and the curve structured light bar as the position of the welding seam.
In a specific embodiment, the preprocessing the weld image in step S300 to obtain a preprocessed image includes:
step S311, carrying out gray level processing on the welding seam image to obtain a gray level image;
step S312, filtering the gray level image to obtain a filtered image;
and step S313, performing morphological operation on the filtered image to obtain a preprocessed image.
Specifically, in this embodiment, after the weld image is obtained, the weld image is first subjected to gray scale processing to obtain a gray scale image, then the gray scale image is subjected to gaussian filtering to obtain a filtered image, and finally, the filtered image is subjected to expansion processing and then to corrosion processing by using morphological closing operation to obtain a binarized preprocessed image.
In a specific embodiment, after step S300, the method further includes:
and S400, controlling the welding gun to move to the welding seam position for welding.
Specifically, after the welding position is determined, the welding gun can be controlled to move to the welding position for welding, in the embodiment, the camera is triggered to shoot when the pulse welding signal is at the central point of the base value voltage or current, so that a clear welding line image can be obtained, the welding line quality can be monitored in real time, secondary repair welding is performed on problematic welding, and the welding quality is improved.
Exemplary device
Based on the above embodiment, the present invention further provides an intelligent real-time weld joint detection system based on pulse welding, which includes: sensor and intelligent terminal, the sensor includes camera and laser instrument. A schematic block diagram of the intelligent terminal may be as shown in fig. 5. The intelligent terminal comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein, the processor of the intelligent terminal is used for providing calculation and control capability. The memory of the intelligent terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the intelligent terminal is used for being connected and communicated with an external terminal through a network. The computer program is executed by a processor to realize an intelligent welding seam real-time detection method based on pulse welding. The display screen of the intelligent terminal can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the intelligent terminal is arranged inside the intelligent terminal in advance and used for detecting the operating temperature of internal equipment.
It will be understood by those skilled in the art that the block diagram shown in fig. 5 is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation to the intelligent terminal to which the solution of the present invention is applied, and a specific intelligent terminal may include more or less components than those shown in the figure, or combine some components, or have a different arrangement of components.
In one embodiment, an intelligent terminal is provided that includes a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
acquiring a pulse welding signal, and generating a camera trigger signal according to the pulse welding signal; the pulse welding signal is a pulse welding voltage signal or a pulse welding current signal;
triggering a camera to take a picture according to the camera trigger signal to obtain a weld image;
and determining the position of the welding seam according to the welding seam image.
In a specific embodiment, the sensor is a monocular vision sensor, a binocular vision sensor or a 3D structured light vision sensor, and the camera is triggered to take a picture by a camera trigger signal to obtain a clear weld image.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses an intelligent welding seam real-time detection method and system based on pulse welding, and the method comprises the following steps: acquiring a pulse welding signal, and generating a camera trigger signal according to the pulse welding signal; triggering a camera to take a picture according to the camera trigger signal to obtain a weld image; and determining the position of the welding seam according to the welding seam image. According to the invention, the camera trigger signal is generated according to the pulse welding signal, and the camera is triggered to take a picture according to the camera trigger signal, so that not only can a clear welding seam image be obtained, but also the welding quality can be detected in real time, the welding quality is improved, and the welding cost is reduced.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (10)
1. An intelligent welding seam real-time detection method based on pulse welding is characterized by comprising the following steps:
acquiring a pulse welding signal, and generating a camera trigger signal according to the pulse welding signal; the pulse welding signal is a pulse welding voltage signal or a pulse welding current signal;
triggering a camera to take a picture according to the camera trigger signal to obtain a weld image;
and determining the position of the welding seam according to the welding seam image.
2. The intelligent weld seam real-time detection method based on pulse welding according to claim 1, wherein the step of generating a camera trigger signal according to the pulse welding signal comprises:
processing the pulse welding signal to generate a TTL level signal;
and generating a camera trigger signal according to the TTL level signal.
3. The pulse welding-based intelligent weld real-time detection method according to claim 1, wherein the TTL level signals include TTL peak level signals and TTL base level signals, and the step of generating a camera trigger signal according to the TTL level signals includes:
acquiring TTL peak value level time corresponding to the TTL peak value level signal and TTL base value level time corresponding to the TTL base value level signal;
and generating a camera trigger signal according to the TTL peak value level time and the TTL base value level time.
4. The method of claim 3, wherein the camera trigger signal comprises a peak trigger signal and a base trigger signal, and wherein the step of generating the camera trigger signal according to the TTL peak level time and the TTL base level time comprises:
when the TTL level signal is detected to be converted from the TTL base value level signal to the TTL peak value level signal, waiting for a preset first time to generate a peak value trigger signal; wherein the preset first time is half of the TTL peak level time;
when the TTL level signal is detected to be converted from the TTL peak level signal to the TTL base level signal, a preset second time is waited to generate a base trigger signal; and the preset second time is half of the level time of the TTL base value.
5. The intelligent real-time welding seam detection method based on pulse welding as claimed in claim 4, wherein the step of triggering the camera to take a picture according to the camera trigger signal and obtaining the welding seam image comprises:
and when the camera trigger signal is detected to be converted from the peak trigger signal to the base trigger signal, triggering the camera to shoot to obtain a welding seam image.
6. The intelligent real-time detection method for the weld seam based on the pulse welding as claimed in claim 5, wherein the weld seam image comprises a plurality of structured light bars, and the step of determining the position of the weld seam according to the weld seam image comprises:
preprocessing the welding seam image to obtain a preprocessed image;
extracting central lines of a plurality of structural light bars in the preprocessed image, and determining the characteristic types of the plurality of structural light bars according to the preprocessed image after the central lines are extracted;
and determining the position of the welding seam according to the characteristic type.
7. The intelligent real-time welding seam detection method based on pulse welding as claimed in claim 6, wherein the step of preprocessing the welding seam image to obtain a preprocessed image comprises:
carrying out gray level processing on the welding seam image to obtain a gray level image;
filtering the gray level image to obtain a filtered image;
and performing morphological operation on the filtered image to obtain a preprocessed image.
8. The intelligent real-time detection method for the weld based on the pulse welding as claimed in claim 1, wherein the step of determining the weld position according to the weld image is followed by the steps of:
and controlling the welding gun to move to the welding seam position for welding.
9. The utility model provides an intelligence welding seam real-time detection system based on pulse welding which characterized in that includes: the intelligent terminal comprises a sensor and an intelligent terminal, wherein the sensor comprises a camera and a laser; wherein the intelligent terminal includes: a processor, a storage medium communicatively coupled to the processor, the storage medium adapted to store a plurality of instructions; the processor is adapted to call instructions in the storage medium to execute the steps of implementing the pulse welding-based intelligent weld real-time detection method according to any one of the preceding claims 1-8.
10. The pulse welding-based intelligent real-time weld joint detection system according to claim 9, wherein the sensor is a monocular vision sensor, a binocular vision sensor or a 3D structured light vision sensor.
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