CN111331225A - Welding seam tracking method for welding inner circular tube of boiler - Google Patents
Welding seam tracking method for welding inner circular tube of boiler Download PDFInfo
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- CN111331225A CN111331225A CN202010057226.0A CN202010057226A CN111331225A CN 111331225 A CN111331225 A CN 111331225A CN 202010057226 A CN202010057226 A CN 202010057226A CN 111331225 A CN111331225 A CN 111331225A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- 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
- B23K9/00—Arc welding or cutting
- B23K9/12—Automatic feeding or moving of electrodes or work for spot or seam welding or cutting
- B23K9/127—Means for tracking lines during arc welding or cutting
- B23K9/1272—Geometry oriented, e.g. beam optical trading
- B23K9/1274—Using non-contact, optical means, e.g. laser means
Abstract
The invention provides a weld joint tracking method for welding an inner circular pipe of a boiler, which can realize the weld joint tracking of the welding of the inner circular pipe of the boiler. The system adopted by the method mainly comprises a laser vision combined initial positioning module, a welding gun position and posture adjusting module, an ultrasonic welding seam real-time tracking module, a robot arm and a computer control module. According to the method, under the cooperation of a computer control module and a robot arm, a laser vision combined positioning method is adopted to complete initial positioning before welding according to an autonomously designed multi-angle comprehensive weighted average method algorithm, then an ultrasonic tracking method is adopted to realize accurate positioning and real-time deviation correction in the welding process, and finally tracking of the welding seam of the inner circular tube of the boiler is realized. The invention has the advantages that the laser vision combined positioning method is adopted to realize the positioning of the circular tube and the acquisition of the welding seam information, the ultrasonic tracking method is used in the welding process to realize the welding seam tracking of the circular tube and avoid the interference of arc light, electric sparks, magnetic fields and the like during welding.
Description
Technical Field
The invention relates to a welding seam tracking method for welding an inner circular pipe of a boiler.
Background
With the arrival of a new industrial revolution, automation and intellectualization have become the future development trend of the machine manufacturing industry, and a welding technology is also developing towards automation and intellectualization as one of important manufacturing processes of the machine manufacturing industry, and manual welding gradually fades out the visual field of people, and replaces automatic and intellectualized welding equipment such as an intelligent welding robot, an automatic special welding machine and the like and an intelligent welding technology with a great prospect.
Boiler welding is one of the important processes of boiler manufacturing, and improving boiler welding quality has important significance for guaranteeing performance parameter requirements of the boiler and reducing boiler cost. One difficulty of boiler welding is the welding of round pipes on the inner wall, and because the shape of a welding seam between the round pipes in the boiler and a boiler barrel is a space curve, and the installation accuracy of the round pipes on the boiler barrel is not unified standard, the realization of automatic welding is very difficult, so that the automation degree of the existing boiler inner round pipe welding is low, manual welding is mainly used, and a small part of the boiler inner round pipe welding also adopts semi-automatic welding. However, the internal working environment of the boiler is high temperature and high pressure, and the space inside the boiler barrel is narrow, so that a welder who enters the boiler barrel for welding can stay in an uncomfortable working posture for bending the body for a long time and also can bear the high temperature and waste gas generated by welding. The welding efficiency of workers is low under the severe working environment, so that the welding quality cannot be guaranteed, and the health of workers and people can be damaged after long-time work, so that the automatic welding technology of a machine, which can meet the welding requirement of a boiler and realize higher welding efficiency and welding quality, is required to replace manual welding.
The invention provides a weld joint tracking method for welding inner circular pipes of a boiler, aiming at the problem that how to realize the tracking of weld joints between circular pipes and boiler barrels is the biggest difficulty in automatic welding of the inner circular pipes of the boiler. The method has the advantages that the laser vision combined positioning method is used for realizing the positioning of the circular tube and the acquisition of the welding seam information, the ultrasonic tracking method is used in the welding process for realizing the welding seam tracking of the circular tube and avoiding the interference of arc light, electric sparks, magnetic fields and the like during welding.
In addition, in order to meet the requirement of weld joint information fusion in the initial positioning stage in the method, a multi-angle comprehensive weight-weighted average method is designed. The algorithm is a multi-sensor information fusion algorithm. Multi-sensor information fusion algorithms can be divided into two broad categories: probability statistical method, artificial intelligence. The probability statistical method comprises a weighted average method, a Kalman filtering method, a multi-Bayesian estimation method, D-S evidence reasoning, a production rule and the like; the artificial intelligence includes fuzzy logic theory, neural network and expert system.
Therefore, the algorithm is a novel algorithm designed aiming at the welding seam information fusion based on a weighted average method in a probability statistical method, is simple and easy to implement compared with an artificial intelligence algorithm, and is more suitable for the welding seam information fusion compared with other algorithms based on the probability statistical method. The Kalman filtering method is used for comparison, the information fusion algorithm based on the Kalman filtering method is an algorithm which is widely applied, but the defect is that the algorithm can only be used for a linear system, the information fusion effect of the nonlinear system is poor, the welding seam information fusion belongs to the information fusion of the nonlinear system, a good fusion result cannot be obtained by using the Kalman filtering method, the algorithm obtains a plurality of fusion weighting coefficients from multiple angles, the fusion weighting coefficients are divided into two categories according to the relation between the angle of a sensor and the angle of a sensor, firstly, the weighted calculation is carried out on each fusion weighting coefficient in the two categories, then, the obtained result is subjected to the second weighted calculation so as to obtain the comprehensive fusion weighting coefficient, so that the weighted average information fusion from one angle is more accurate and comprehensive, and the information fusion of the linear system and the nonlinear system can be well processed, the finally obtained fusion result has high precision and small loss and can completely meet the requirement of the method.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, improve the welding quality of a boiler and the automation degree of the welding of an inner circular pipe of the boiler, and provide a welding seam tracking method for the welding of the inner circular pipe of the boiler. The welding of the circular tube on the inner wall of the boiler is a great difficulty in the important process of boiler welding in the boiler manufacturing nowadays, and the automatic welding is very difficult to realize due to the fact that the shape of the welding seam between the circular tube and the boiler barrel in the boiler is a space curve and the installation accuracy of the circular tube on the boiler barrel is not unified, so that the automatic welding degree of the circular tube in the boiler is low at present.
Aiming at the problems, the invention provides a welding seam tracking method for welding a circular tube in a boiler. According to the method, under the cooperation of a computer control module and a robot arm, a laser vision combined positioning method is adopted to complete initial positioning before welding according to an autonomously designed multi-angle comprehensive weighted average method algorithm, then an ultrasonic tracking method is adopted to realize accurate positioning and real-time deviation correction in the welding process, and finally tracking of the welding seam of the inner circular tube of the boiler is realized. The invention has the advantages that the laser vision combined positioning method is used for realizing the positioning of the circular tube and the acquisition of the welding seam information, and the ultrasonic tracking method is used in the welding process to realize the welding seam tracking of the circular tube and avoid the interference of arc light, electric sparks, magnetic fields and the like during welding.
The invention is characterized by the following three main points:
firstly, the system adopted by the invention mainly comprises a laser vision combined preliminary positioning module, a welding gun position and posture adjusting module, an ultrasonic welding seam real-time tracking module (the three modules form a welding seam tracking device of the method), a robot arm, a computer control module and a multi-angle comprehensive weighted average algorithm; the laser vision combined primary positioning module comprises a machine vision camera, a device main body part, a positioning rod (which is a telescopic mechanism), a structured light laser, a laser mounting rack, a focusing lens and an annular CCD sensor; the welding gun position and posture adjusting module comprises a welding gun spatial position moving mechanism, a welding gun swinging mechanism and a welding gun; the computer control module comprises a processor and a controller and is responsible for processing information obtained by the sensor in the whole tracking process and carrying out communication coordination and control on each module; the ultrasonic welding seam real-time tracking module comprises a disc mounting rack fixed below the telescopic part on the positioning rod and four ultrasonic sensors which are orthogonally distributed and arranged on the disc mounting rack; according to the method, under the cooperation of a computer control module and a robot arm, a laser vision combined positioning method is adopted to complete initial positioning before welding according to an autonomously designed multi-angle comprehensive weighted average method algorithm, then an ultrasonic tracking method is adopted to realize accurate positioning and real-time deviation correction in the welding process, and finally tracking of the welding seam of the inner circular tube of the boiler is realized.
Secondly, the working process of the system is as shown in fig. 2 and is divided into two stages, namely a primary positioning stage and an accurate positioning stage, wherein the primary positioning is used as a pilot stage of the accurate positioning to make necessary preparation work for the accurate positioning, so that the accurate positioning stage is started after the primary positioning stage is finished; the primary purpose of the primary positioning stage is to make the welding gun in a proper welding initial position and posture, and the method comprises three processes: the positioning rod is centered, the ultrasonic tracking module reaches a preset working position, and the welding initial position and the posture of a welding gun are determined; the main purpose in the accurate positioning stage is to correct the welding point position in the welding process in real time, thereby realizing the accurate positioning of the welding point and realizing the welding seam tracking, which mainly comprises two processes: the ultrasonic sensor acquires welding line deviation, and the welding gun position and posture adjusting module corrects the deviation in real time.
Thirdly, in order to meet the requirement of welding seam information fusion in the initial positioning stage in the method, a multi-angle comprehensive weight-solving weighted average method is designed. The algorithm is a novel information fusion algorithm improved on the basis of the prior person, three weighted fusion coefficients are obtained from three different angles by referring to the information fusion algorithm of people who scribble at home, Liu, and the like, the three weighted fusion coefficients are divided into two types to be subjected to weight obtaining operation twice to obtain a comprehensive weighted fusion coefficient, and finally the comprehensive weighted fusion coefficient is used for completing the welding seam information fusion by using a weighted average method.
The obvious advantages of the invention are:
the invention provides a welding seam tracking method for welding an inner circular pipe of a boiler. In the initial positioning stage, a laser vision combined positioning method is adopted, namely welding seam information obtained by a laser tracking (CCD) sensor and a machine vision camera is fused through an autonomously designed multi-angle comprehensive weighted average algorithm, the welding initial position and the welding attitude of a welding gun are adjusted according to the fused result to complete initial positioning, the positioning precision before welding is ensured to be high, and the welding quality is improved. In the accurate positioning stage, an ultrasonic tracking method is used in the welding process, the echo is processed by taking the welding seam information fusion result obtained in the initial positioning stage as a basis to obtain deviation information, the interference of arc light, electric sparks, magnetic fields and the like during welding can be avoided while the tracking of the welding seam of the circular tube is realized, and the accuracy and reliability of the tracking of the welding seam are ensured.
Secondly, a multi-angle comprehensive weight-obtaining weighted average method algorithm obtains various fusion weighting coefficients from multiple angles, the fusion weighting coefficients are divided into two categories according to the relation between the self angle of a sensor and the sensor, firstly, the weight-obtaining operation is carried out on each fusion weighting coefficient in the two categories, then, the obtained result is subjected to the second weight-obtaining operation, and the comprehensive fusion weighting coefficient is obtained.
Drawings
Fig. 1 is a scenario in which the present invention is applied.
Fig. 2 is a schematic structural diagram of a system apparatus employed in the present invention.
In the figure: 1-a robot arm, 2-a processor, 3-a controller, 4-a machine vision camera, 5-a device main body part, 6-a laser mounting rack, 7-an annular CCD sensor, 8-a positioning rod, 9-a circular tube, 10-a structured light laser, 11-a focusing lens, 12-a welding gun spatial position movement mechanism, 13-a disc mounting rack, 14-a boiler barrel, 15-a welding gun swing mechanism, 16-a welding gun, 17-an ultrasonic sensor and 18-a welding line.
FIG. 3 is a system flow diagram of a weld tracking method for boiler inner tube welding.
Fig. 4 is a control flow block diagram of the present invention.
FIG. 5 is a block diagram of the "multi-angle comprehensive weighted average method".
Detailed Description
In order to better express the technical scheme and the advantages of the whole invention, the invention is further described in detail with reference to the accompanying drawings.
Fig. 1 is a scenario in which the present invention is applied, i.e., a drum having a large number of circular tubes mounted on a drum wall. The method provided by the invention is used for tracking the welding seam of the inner circular tube of the boiler barrel.
Fig. 2 is a schematic structural diagram of a system apparatus employed in the present invention. The system device mainly comprises a laser vision combined initial positioning module, a welding gun position and posture adjusting module, an ultrasonic welding seam real-time tracking module (the three modules form the welding seam tracking device of the method), a robot arm 1 and a computer control module. As shown in fig. 2, the laser vision combined primary positioning module includes a machine vision camera 4, a device body part 5, a laser mounting frame 6, an annular CCD sensor 7, a positioning rod 8 (of a telescopic structure), a structured light laser 10, and a focusing lens 11; the welding gun position and posture adjusting module comprises a welding gun spatial position moving mechanism 12, a welding gun swinging mechanism 15 and a welding gun 16, wherein the welding gun spatial position moving mechanism is a double-cross sliding table combined mechanism, and the welding gun swinging mechanism is a ball hinge mechanism; the computer control module comprises a processor 2 and a controller 3 and is responsible for processing information obtained by the sensor in the whole tracking process and carrying out communication coordination and control on each module; the real-time ultrasonic welding seam tracking module comprises a disc mounting frame 13 fixed at a position below the telescopic part on the positioning rod and four ultrasonic sensors 17 which are orthogonally distributed and mounted on the disc mounting frame.
FIG. 3 is a system flow diagram of a weld tracking method for boiler inner tube welding.
As shown in fig. 3, the method comprises the steps of:
firstly, a robot arm connected with a welding seam tracking device moves the device to a proper position with a proper height above a circular pipe, and then machine vision cameras with different installation heights and installation inclination angles on two sides of a device main body downwards photograph the welding seam and the circular pipe. The processor processes the received image information of the three-dimensional imaging obtained by photographing, stores the processed welding seam information in a register of the processor, and outputs the processed information of the center position of the section of the circular tube to the controller.
And step two, the controller outputs a centering starting signal to the robot arm after receiving the information, and the robot arm starts to work after receiving the signal containing the central position of the section to drive the device to move so that the lower part of the device is superposed with the central axis of the section. After the robot arm stops working, the two cameras take pictures to judge whether the positioning rod is superposed with the axis of the round pipe. And if the position deviation between the positioning rod and the axis is judged to be not superposed, the position deviation between the positioning rod and the axis is obtained according to the image information obtained by photographing, and then the control arm commands the robot arm to work for correction. So far, the positioning rod is centered and finished.
And step three, after centering is finished, the ultrasonic sensor starts to work to measure whether the distance between the probe of the ultrasonic sensor and the section of the circular tube is the same as the required working distance, if the distance is not the same, the positioning rod stretches out and draws back to enable the distance to be the same as the working distance, and if the distance is the same, no action is performed. At this point, the ultrasound tracking module reaches a predetermined operating position.
And step four, after the ultrasonic tracking module reaches a preset working position, the ultrasonic sensor stops working, the controller issues an instruction to the laser and the robot arm, and the laser starts to emit laser and the robot arm enables the device to start rotating. The annular CCD sensor at the lower part of the device picks up a characteristic line image formed by irradiating laser on a welding seam through the focusing lens, and welding seam information is obtained after processing and is output to the processor.
And step five, the processor fuses the information stored in the register and the welding seam information output to the processor by the CCD sensor through an algorithm, and then outputs the result obtained after fusion to the controller. The controller outputs a rotation stop instruction to the robot arm to stop the device, and simultaneously issues a working instruction to the welding gun position and posture adjusting module, and the module adjusts the welding gun to a proper welding initial position and to be in a proper posture after the device stops. By this, the preliminary positioning is completed.
Step six, after the preliminary positioning is finished, the controller issues a command to start welding, the robot arm enables the device to rotate, and the welding gun starts to work; meanwhile, the controller outputs an accurate positioning starting signal to the ultrasonic welding seam tracking module to start welding seam tracking.
And step seven, in the welding process, the welding gun can be rotated around the circular welding line of the circular tube to weld by rotating the main body of the device, the disc mounting rack fixed on the positioning rod can also rotate along with the rotation, the ultrasonic sensors which are arranged on the disc mounting rack in an orthogonal distribution mode continuously downwards emit ultrasonic waves to rotationally scan the welding line, the sensors receive the welding line information fusion result obtained in the preliminary positioning stage after receiving the return wave and process the welding line information fusion result as the basis to obtain deviation information, and the deviation information is output to the controller.
And step eight, the controller receives the deviation information and then gives an instruction to the welding gun position and posture adjusting module, the position and posture of the welding gun are adjusted to correct in real time, and real-time tracking of the welding seam of the inner circular tube of the boiler is achieved.
Wherein, the first to the fifth steps belong to the preliminary positioning stage, and the sixth to the eighth steps belong to the precise positioning stage. Centering a positioning rod in the first step and the second step, enabling the ultrasonic tracking module to reach a preset working position in the third step, and determining the welding initial position and the welding attitude of the welding gun in the fourth step and the fifth step; and step six, the ultrasonic sensor acquires welding line deviation, and step seven and step eight are real-time deviation correction of the welding gun position and posture adjusting module.
Fig. 4 is a control flow block diagram of the present invention, and as shown in fig. 4, fig. 4 uses a block diagram format to briefly and clearly describe how the controller works during the whole implementation process of the method, i.e., to illustrate the control flow of the system adopted by the method.
FIG. 5 is a "multi-angle comprehensive weighted average algorithm", as shown in FIG. 5, the specific contents of the algorithm are as follows:
since the weld information includes various information such as width, depth, shape, etc., the algorithm whose object is to find the width fusion estimation value is described here by taking the width as an example
It is also one of the weld information fusion results.
Assuming that n sensors detect the width from different positions, the measurement equation of the ith sensor is:
Xi＝Y+Wi,i＝1,2,3,...,n
where Y is the true value of the estimated width, XiIs a measure of width; wiTo satisfy E [ W ]i]0 and E [ W ═iWj]0 gaussian noise vector, and
firstly, m measurement values can be obtained by using one sensor to perform m times of measurement, and X can be setimFor the result of the mth measurement measured by the ith sensor, the arithmetic mean value of the measurements of the sensors at the mth measurement is:
the estimate of the measurement variance for the ith sensor measurement at the mth measurement is assigned as:
Rim＝[Xim-Xm]2
assigning a value R to the estimation of the variance of each sensor measurement over the course of the measurementimAnd (3) calculating an arithmetic mean value:
the above equation is the estimated value of the measurement variance of the ith sensor in the mth measurement.
When m is large enough
Will tend to be a constant
We refer to this as the estimate limit of the i-th sensor measurement variance.
Then the ith transmission based on the sensor measurement variance estimation value limit can be solved according to the measurement variance estimation valueFusion weighting coefficient a of sensori：
Then, a weighted estimation value based on the variance of the noise measurement is set as
Fusion weighting coefficient b of ith sensor based on noise measurement varianceiThen, because it is guaranteed that the weighted estimated variance is smaller than the variance of the measured noise of any sensor in the system, two conditions must be satisfied:
(1) the estimation is unbiased, i.e.:
(2) the weighted estimate has the smallest variance, i.e.:
b can be obtained from the above two formulaei：
Then considering the degree of support between sensors, d is generally usedij，djiAs mutual support of data between sensor i and sensor j.
In the upper two formulas Pi(X|Xi) Is a conditional probability.
Thereby obtaining the distanceThe matrix D ═ Dij) The relationship matrix R ═ R (R) between the sensors can be defined by Dij)
Wherein
Let ci' is the importance of the ith sensor, ciFor the fusion weighting coefficient of the ith sensor based on the support degree between the sensors, then
ci′＝X1r1j+X2r2j+…+Xbrnj
j＝1,2,…,n
Let c ═ c1，c2，…，cn)2，
X＝(X1,X2,…，Xn)2，
Then c is R ' X and R ' is an inseparable non-negative matrix, as can be seen by Perron-Frobenius theorem, R ' has a maximum modulo eigenvalue λ >0, and λ corresponds to the positive eigenvector X, with
λX＝R′X,
Thus, λ X can be used as a measure of the overall support of the sensor.
Therefore, the first and second electrodes are formed on the substrate,
finally, because the weighting coefficients a are fusediAnd biAll belonging to a class of fusion weighting coefficients derived from the individual sensors themselves, and fusion weighting coefficient ciThen belong to a class of fusion weighting coefficients derived from the relationship between the sensors, so first the fusion weighting coefficient a is fusediAnd biFor each sensor, summing them individually, and using the sum SiCarrying out one-time weighting operation to obtain the self angle type fusion weighting coefficient d of the ith sensoriThen d isiAnd ciFor each sensor, the sum is summed, and the sum S is usedi' conducting a weighting operation to obtain the firstComprehensive fusion weighting coefficient e of i sensorsiThe specific process is as follows:
Si＝ai+bi，
Si′＝ci+di，
wherein eiSatisfy the relation
Then by eiMethod for obtaining width fusion estimated value to be obtained by using weighted average method
Claims (3)
1. The invention provides a welding seam tracking method for welding an inner circular pipe of a boiler, which is characterized by comprising the following steps of: the system adopted by the method mainly comprises a laser vision combined preliminary positioning module, a welding gun position and posture adjusting module, an ultrasonic welding seam real-time tracking module, a robot arm and a computer control module; the laser vision combined primary positioning module comprises a machine vision camera, a device main body part, a positioning rod, a structured light laser, a laser mounting rack, a focusing lens and an annular CCD sensor; the welding gun position and posture adjusting module comprises a welding gun spatial position moving mechanism, a welding gun swinging mechanism and a welding gun; the computer control module comprises a processor and a controller and is responsible for processing information obtained by the sensor in the whole tracking process and carrying out communication coordination and control on each module; the ultrasonic welding seam real-time tracking module comprises a disc mounting rack fixed below the telescopic part on the positioning rod and four ultrasonic sensors which are orthogonally distributed and arranged on the disc mounting rack; according to the method, under the cooperation of a computer control module and a robot arm, a laser vision combined positioning method is adopted to complete primary positioning before welding is started according to an autonomously designed multi-angle comprehensive weighted average method algorithm, then an ultrasonic tracking method is used to realize accurate positioning and real-time deviation correction in the welding process, and finally tracking of the welding seam of the inner circular tube of the boiler is realized.
2. The method for tracking the weld joint for the welding of the inner circular tube of the boiler according to claim 1, wherein: the method comprises two stages, namely a primary positioning stage and an accurate positioning stage, wherein the primary positioning is used as a pilot stage of the accurate positioning to make necessary preparation work for the accurate positioning; the initial positioning stage comprises three processes: the positioning rod is centered, the ultrasonic tracking module reaches a preset working position, and the welding initial position and the posture of a welding gun are determined; the accurate positioning stage mainly comprises two processes: the ultrasonic sensor acquires welding line deviation, and the welding gun position and posture adjusting module corrects the deviation in real time.
3. The method for tracking the weld joint for the welding of the inner circular tube of the boiler according to claim 1, wherein: in the method, a multi-angle comprehensive weight-obtaining weighted average method algorithm obtains three weighted fusion coefficients from three different angles, then divides the three weighted fusion coefficients into two types to carry out weight-obtaining operation twice to obtain the comprehensive weighted fusion coefficient, and finally uses the weighted average method to complete the weld information fusion by the comprehensive weighted fusion coefficient.
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