Self-positioning earth-covering type storage tank welding auxiliary equipment

Abstract

The invention provides self-positioning earth-covering type storage tank welding auxiliary equipment, which belongs to the technical field of storage tank processing and comprises a base, a moving mechanism, a mounting frame, a supporting seat, a guide rail, a servo motor, a welding mechanism, a bidirectional screw rod, a first motor, a guide rod, a sliding block, a supporting frame, a clamping ring, a lifting mechanism, a supporting arm, a second motor and a rotating ring. Moving mechanisms are arranged at four corners of the lower end in the base; a mounting frame is fixedly connected to the top of the base, supporting seats are symmetrically and fixedly connected to one side of the bottom of the mounting frame, guide rails are fixedly connected to one sides of the supporting seats, and servo motors are slidably connected to the outer sides of the guide rails; and a two-way screw rod is arranged in the base, one end of the two-way screw rod is fixedly connected to the output end of a first motor, and through the arrangement, the problem that the workload is increased while the labor intensity is increased due to the fact that the phenomenon of uneven welding or omission easily occurs during manual welding is solved.

Description

Technical Field

[0001] The invention belongs to the technical field of storage tank processing, and in particular relates to an autonomously positioned earth-covered storage tank welding auxiliary device. Background Art

[0002] Earth-covered storage tanks can effectively prevent boiling liquid diffusion and steam explosion when storing liquefied hydrocarbons at room temperature and pressure, and are not subject to damage from nearby heat sources, explosion shock waves, splashing objects or other sudden damage. They have the advantages of beautifying the environment, reducing floor space, and reducing the safety distance from surrounding facilities. When used alone or in combination, earth-covered storage tanks can replace spherical tanks or spherical tank groups, and are widely used in refineries, petrochemical plants, storage and distribution stations, urban gas stations, oil depots, etc. as a large-scale storage of liquefied hydrocarbon raw materials, finished products and semi-finished products, and have very important application value.

[0003] At present, in the welding process of earth-covered storage tanks, the main body of the earth-covered storage tank needs to be manufactured on site because the diameter and length of the equipment are restricted by transportation. The equipment adopts a solution of horizontal segmented manufacturing, overall closure, and overall installation. In the manufacturing process of earth-covered storage tanks, it is first necessary to weld the cylinder formed by the slices into single sections, and then support the single section of the cylinder with the auxiliary support structure according to the layout drawing. However, since the welding of single sections is generally done manually, and different positions need to be changed for welding, manual welding is prone to uneven welding or omissions, which increases the labor intensity and the workload. Summary of the invention

[0004] In view of this, the present invention provides an autonomously positioned earth-covered storage tank welding auxiliary device, which can solve the problem that manual welding is prone to uneven welding or omissions, thereby increasing labor intensity and workload.

[0005] The present invention is achieved in that: The present invention provides an autonomously positioned earth-covered storage tank welding auxiliary equipment, comprising: a base, a moving mechanism, a mounting frame, a support seat, a guide rail, a servo motor, a welding mechanism, a bidirectional screw, a first motor, a guide rod, a slider, a support frame, a clamping ring, a lifting mechanism, a support arm, a second motor and a rotating ring; the moving mechanism is arranged at the four corners of the lower end of the base; the top of the base is fixedly connected with the mounting frame, one side of the bottom of the mounting frame is symmetrically fixedly connected with the support seat, one side of the support seat is fixedly connected with the guide rail, and the outer side of the guide rail is slidably connected with the servo motor; the base is arranged inside, one end of the bidirectional screw is fixedly connected to the output end of the first motor, one side of the base is symmetrically fixedly connected with the guide rod, one end of the outer side of the bidirectional screw is symmetrically threadedly connected with the slider, one side of the top of the slider is symmetrically fixedly connected with the support frame, and the top of the support frame is fixedly connected with the clamping ring; the top of the base is arranged with a lifting mechanism, one end of the outer side of the clamping ring is fixedly connected with the support arm, one side of the support arm is fixedly connected with the second motor, and the output end of the second motor is fixedly connected with the rotating ring.

[0006] On the basis of the above technical solution, the self-positioning earth-covered storage tank welding auxiliary equipment of the present invention can also be improved as follows: Furthermore, it also includes a welding positioning system, which includes a control chip and a multi-mode detector group, the multi-mode detector group is fixedly connected to the bottom of the servo motor, the multi-mode detector group includes a laser detector, an infrared detector and a visible light detector, the control chip is arranged on one side of the mounting frame, the control chip is electrically connected to the multi-mode detector group, the servo motor and the welding mechanism, and a welding positioning module is arranged in the control chip, the welding positioning module is used to determine the welding positioning according to the data collected by the multi-mode detector group, and control the servo motor to drive the welding mechanism to move to the welding position; The welding positioning module is used to perform the following steps: S10, receiving the weld image data collected by the multi-mode detector group, the weld image data including laser detection data, infrared detection data and visible light detection data; specifically, collecting three-dimensional laser point cloud data, two-dimensional infrared thermal imaging data and color visible light image data of the weld area from the multi-mode detector group to form a comprehensive image data set of the weld. Among them, the laser detector scans to obtain the elevation information of the weld contour, the infrared detector measures the temperature distribution of the weld, and the visible light detector captures the appearance texture of the weld. The three types of detection data are aggregated by the control chip to form complete weld image data.

[0007] S20, preprocessing the weld image data, including filtering and denoising, image enhancement and edge detection processing of the weld image data; specifically: first, filtering and denoising the original laser point cloud data, infrared thermal imaging data and visible light image respectively. Moving average filtering is used for point cloud data, Gaussian filtering is applied to thermal imaging data, and median filtering is used for color images. Then, contrast enhancement is performed on the three types of filtered data respectively, histogram equalization is used for laser data, gamma correction is used for thermal imaging data, and adaptive histogram equalization is used for color images. Finally, the Canny edge detection algorithm is executed on the enhanced image data to obtain a binary edge map of the weld contour. Through the above preprocessing operations, noise can be effectively eliminated and the key features of the weld area can be highlighted.

[0008] S30. Based on the pre-processed weld image data, the weld region is segmented by an image segmentation algorithm to obtain weld contour information; specifically: first, the pre-processed laser point cloud data, infrared thermal imaging data and visible light image are respectively subjected to an image segmentation algorithm based on region growth to obtain weld region segmentation results under three detection modes. Then, a multimodal fusion algorithm based on image sparse representation is used to fuse the above three segmentation results to obtain a comprehensive weld contour segmentation mask. Finally, morphological opening and closing operations are performed on the segmentation mask to eliminate small holes and burr noise points in the segmentation results, and further optimize the continuity and smoothness of the weld contour line. Through the above steps, the geometric contour information of the weld region can be accurately extracted.

[0009] S40, calculating the weld centerline coordinate sequence according to the weld profile information, and smoothing the weld centerline coordinate sequence; specifically: first, defining the probability distribution function of the weld centerline coordinate sequence , which takes into account the pixel grayscale value and distance factors. Then, combined with the weld contour information obtained by segmentation, the maximum likelihood estimation method is used to calculate the coordinate sequence of the weld centerline. Finally, the calculated weld centerline coordinate sequence is smoothed by Gaussian filtering to eliminate the slight fluctuations in the centerline trajectory. Through this step, a smooth weld centerline trajectory can be obtained, providing basic data for subsequent welding geometry feature calculation and welding path planning.

[0010] S50, using the weld centerline coordinate sequence, calculating the geometric characteristic parameters of the weld, the geometric characteristic parameters including weld width, weld depth and weld inclination angle; specifically: first, calculating the weld width according to the weld profile information , in which the Fourier transform characteristics of the grayscale distribution of the weld edge are used; then, the weld depth is calculated based on the infrared radiation intensity and width information of the weld area ;Finally, the weld centerline coordinate sequence is combined to calculate the weld inclination angle Through the above calculation formula, key geometric characteristic parameters such as weld width, depth and inclination angle can be obtained, which provide necessary input for subsequent welding path planning.

[0011] S60, according to the geometric characteristic parameters of the weld, determine the welding path point sequence, each welding path point contains three-dimensional space coordinate information and welding gun posture angle information; specifically: first, define the welding path point The six-dimensional vector representation includes the spatial coordinates and the welding gun posture angle. Then, according to the weld geometric characteristic parameters calculated in step S50, , through the path point mapping function Determine the six-dimensional path point vector for each sampling point Finally, considering the measurement noise and modeling error in the actual welding process, add Through this step, a series of optimized welding path points can be generated.

[0012] S70, calculate the motion trajectory between adjacent welding path points and generate a welding motion control instruction sequence; specifically: first, use the spline interpolation algorithm to smoothly interpolate the discrete welding path point sequence generated in step S60 to obtain a continuous welding machine motion trajectory; then, according to the welding machine motion trajectory, calculate the position, speed and acceleration information required at each path point; finally, convert the above position, speed and acceleration information into a pulse instruction sequence of the servo motor, including a pulse count value and a pulse frequency. Send the generated servo motor control instruction sequence to the control chip to drive the welding mechanism to perform welding operations along the optimized welding path.

[0013] S80, sending the welding motion control instruction sequence to the servo motor, controlling the servo motor to drive the welding mechanism to perform welding along the motion trajectory; specifically: the control chip sends the servo motor control instruction sequence generated in step S70 to the servo motor driver through the digital I / O interface. The servo motor driver adjusts the speed and torque output of the servo motor in real time according to the received position, speed and acceleration instructions, and drives the welding mechanism including the welding gun body, wire feeding mechanism and gas shield to perform automatic welding along the optimized welding path. The control chip monitors the operating status of the servo motor in real time during the welding process, detects and corrects any deviations in time, and ensures welding quality and safety.

[0014] S90, during the welding process, real-time acquisition of weld formation data, and real-time adjustment of welding parameters according to the weld formation data, wherein the welding parameters include welding current, welding voltage and welding speed; specifically: first, the PID control algorithm is used to adjust the welding current in real time , where the current command consists of the initial current, proportional term, integral term and differential term. Then, the welding voltage is calculated and adjusted according to the change in weld width and the target weld depth. Finally, the welding speed is adjusted according to the weld formation error detected in real time. , to compensate for the deviation and ensure the quality of the weld. The welding quality can be effectively improved by real-time adaptive adjustment of the three major parameters of welding current, voltage and speed.

[0015] In the steps performed by the welding positioning module, the relevant calculation processes involved are described as follows: 1. The calculation process of the weld centerline coordinate sequence is specifically expressed as follows: ; In the formula, is the probability distribution function of the weld centerline; For the The grayscale value of each pixel is in the range of [0,255]; For the The coordinates of the pixels; is the total number of pixels in the image; is the weight coefficient, the default value is 0.5; is the attenuation coefficient, the default value is 0.1; For point The shortest distance to the centerline of the predicted weld.

[0016] 2. The calculation process of the weld geometric characteristic parameters is specifically expressed as follows: ; In the formula, is the weld width function; is the distance parameter along the weld direction; is the Fourier transform of the grayscale distribution of the weld edge; is a frequency variable; is the measurement error, which follows a normal distribution with a mean of 0 and a standard deviation of 0.1.

[0017] ; In the formula, is the weld depth function; is the infrared radiation intensity of the weld area; is the reference value of ambient infrared radiation intensity, which is 20; is the standard weld width, which is 2 mm; are unknown coefficients, obtained by least squares fitting; is the depth measurement error.

[0018] ; In the formula, is the weld inclination angle function; is the coordinate of the weld centerline; is the periodic fluctuation amplitude, and its value range is [0,0.1]; is the angle fluctuation frequency, and its value range is [0.1,1]; is the angle measurement error, which follows a normal distribution with a mean of 0 and a standard deviation of 0.05.

[0019] 3. The generation process of the welding path point sequence is specifically expressed as follows: ; In the formula, For the The six-dimensional vector of welding path points; is the spatial coordinate; is the Euler angle of welding gun posture; is the path point mapping function; For the Arc length parameters of sampling points; is a 6×6 error amplification matrix; is a six-dimensional error vector.

[0020] 4. The calculation process of the real-time adjustment of welding parameters is specifically expressed as follows: ; In the formula, for Welding current at the moment; is the initial welding current, which is 100 amperes; is the weld formation error; are PID controller parameters, representing the proportional, integral, and differential coefficients respectively; is the integration variable.

[0021] ; In the formula, for Welding voltage at the moment; is the reference voltage, which is 20 volts; is the target weld depth, which is 3 mm; is the depth compensation coefficient, the value range is [0.5,1.5]; is the voltage fluctuation term, which obeys the normal distribution with a mean of 0 and a standard deviation of 0.2.

[0022] ; In the formula, for Welding speed at the moment; is the initial welding speed, which is 5 mm / s; is the speed adjustment coefficient, the value range is [0.1,0.3]; is the cumulative error attenuation coefficient, and its value is 0.05.

[0023] Parameter acquisition method: 1. Grayscale distribution of weld edge Obtaining: Step 1: Perform Canny edge detection on the preprocessed image to obtain a binary edge image; Step 2: Take a cross section every 1 mm along the weld direction and record the gray value distribution of the edge points; Step 3: Perform fast Fourier transform on the grayscale distribution of all cross sections to obtain .

[0024] 2. Undetermined coefficients Obtaining: Step 1: Prepare 10 groups of standard test pieces of different specifications, and their actual weld depth values ​​are known; Step 2: Use an infrared camera to measure the radiation intensity of the test piece , while measuring the weld width ; Step 3: Substitute the measured data into the depth function equation and solve it using the least squares method The mean square error between the calculated depth and the actual depth is minimized.

[0025] 3. Error amplification matrix Obtaining: Step 1: Select 100 welding path points on the standard workpiece and record their theoretical six-dimensional vector values; Step 2: Use the visual system to measure the actual welding position and posture, and record the measured six-dimensional vector value; Step 3: Calculate the error vector between the theoretical value and the measured value; Step 4: Use singular value decomposition to solve the error amplification matrix .

[0026] 4.PID controller parameters Obtaining: Step 1: Build a welding test platform to collect weld formation data under different welding conditions; Step 2: Use the Ziegler-Nichols tuning method to determine the critical proportional gain through critical oscillation experiments and critical oscillation period ; Step 3: Calculate according to the empirical formula: , , .

[0027] For the welding positioning system, firstly, the device uses multi-mode sensors such as laser detectors, infrared detectors and visible light detectors, which can fully obtain the three-dimensional geometric information, temperature distribution characteristics and appearance texture data of the weld area. By fusing and processing these heterogeneous sensor data, the detection accuracy of the weld position and contour can be greatly improved, laying a solid foundation for the subsequent welding path planning. Secondly, the device has designed a series of image processing algorithms, including filtering and noise reduction, contrast enhancement, edge detection and area segmentation, which can adaptively extract the key geometric features of the weld from the complex environment and provide the required geometric information for the optimization planning of the welding path. Furthermore, the device also integrates real-time welding quality monitoring and parameter adaptive adjustment functions, which can dynamically detect the weld formation state, and adjust key parameters such as welding current, voltage and speed in real time according to the detection results to ensure that the weld quality reaches the best state. Compared with the existing technology, the welding positioning system set up in this equipment has the following significant advantages: 1) With the help of multi-mode sensor data fusion and advanced image processing algorithms, it can accurately locate the position of welds hidden under the soil layer, greatly improving the applicability of welding automation; 2) Through optimized welding path planning and real-time parameter adjustment mechanism, the stability and consistency of welding quality are significantly improved; 3) The fully automated welding operation process greatly improves the operation efficiency.

[0028] Furthermore, the base is made of a rectangular steel plate, and an upwardly extending rib is provided at the top edge of the base, and the height of the rib is 20 to 30 mm; a guide block is symmetrically fixedly connected to one side of the base, and the guide block adopts a triangular structure, and its inclined surface faces the center position of the base.

[0029] Furthermore, the moving mechanism includes a first hydraulic push rod, the cylinder body of the first hydraulic push rod is fixedly connected to the lower surface of the base, the bottom of the piston rod of the first hydraulic push rod is fixedly connected to a universal wheel, and the universal wheel is made of polyurethane material; the stroke range of the first hydraulic push rod is 50 to 80 mm.

[0030] Furthermore, the bidirectional screw is rotatably connected to the base via a bearing fixing seat, a double-row tapered roller bearing is arranged in the bearing fixing seat; and the first motor is fixedly connected to an adjacent side of the base.

[0031] Furthermore, the slider is slidably connected to the outer side of the guide rod, a dovetail groove structure is provided in the slider, and the cross section of the guide rod is dovetail-shaped and matches the dovetail groove of the slider.

[0032] Furthermore, the lifting mechanism includes a second hydraulic push rod, the bottom of the second hydraulic push rod is fixedly connected to the top of the base, and the top of the second hydraulic push rod is fixedly connected to a bearing seat.

[0033] Furthermore, the bearing seat is in a disc-shaped structure, and a plurality of limiting protrusions evenly distributed along the circumference are arranged on its upper surface.

[0034] Furthermore, the sliding block is made of high molecular polymer to reduce friction with the guide rod.

[0035] Furthermore, a coupling is provided between the first motor and the bidirectional screw, and the coupling adopts a diaphragm structure.

[0036] Compared with the prior art, the beneficial effects of the self-positioning earth-covered storage tank welding auxiliary equipment provided by the present invention are: Firstly, by setting a base, a support frame, a clamping ring, an arm, a second motor, a rotating ring, an anti-skid pad, a steel ball, a guide rail, a servo motor, a welding mechanism and a multi-mode detector group, during the welding process of a single-section barrel section of an earth-covered storage tank, the single-section barrel section of the storage tank is fixed to the clamping rings set at both ends, and the single-section barrel section of the storage tank is located on the inner side of the rotating ring. The anti-skid pad set inside the rotating ring can prevent the single-section barrel section of the storage tank from slipping during the welding process. Then, by driving the servo motor located on the outer side of the guide rail to slide laterally, the multi-mode detector group set at the bottom of the servo motor can detect the position required for welding on the single-section barrel section of the storage tank. Then, when controlling the welding mechanism to The welding operation is performed at the required welding position on the single-section barrel section of the storage tank, and further by driving a second motor arranged on one side of the support arm, the output end of the second motor is fixedly connected with a rotating ring, and the steel ball arranged between the clamping ring and the rotating ring can increase the smoothness during rotation, and the rotating ring and the anti-skid pad will drive the single-section barrel section of the storage tank to perform a flipping operation under the drive of the second motor, so as to effectively improve the welding efficiency of the single-section barrel section of the storage tank, so that the earth-covered storage tank welding auxiliary equipment can perform welding operations on the single-section barrel section of the storage tank in a semi-automatic manner, so as to reduce the unevenness and leakage caused by manual welding, and the welding efficiency of the single-section barrel section of the earth-covered storage tank can be improved immediately.

[0037] Secondly, by setting a base, a bidirectional screw, a first motor, a guide rod, a slider, a support frame and a lifting mechanism, during the welding process of a single-section barrel section of a storage tank, the single-section barrel section of the storage tank is pushed to the top of the bearing seat through the guide block, and then the single-section barrel section of the storage tank is transported to the position where the clamping ring clamps the single-section barrel section of the storage tank by the second hydraulic push rod, and the bidirectional screw is rotated by driving the first motor set on one side of the base, so that the support frame and the clamping ring can move relatively under the rotation of the bidirectional screw, and the single-section barrel sections of storage tanks of different lengths are clamped and fixed, thereby completing the welding of single-section barrel sections of storage tanks of different lengths.

[0038] In summary, the present invention solves the problem that manual welding is prone to uneven welding or omissions, which increases labor intensity and workload. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a schematic diagram of the axonometric structure of one side of the device proposed by the present invention; Figure 2 This is a schematic diagram of the axonometric structure of the other side of the device proposed by the present invention; Figure 3 A schematic diagram of the bidirectional screw structure of the device proposed by the present invention; Figure 4 A schematic diagram of the steel ball structure of the device proposed by the present invention; Figure 5 A flow chart of steps performed for a welding positioning module; In the figure: base 1, guide block 2, first hydraulic push rod 3, universal wheel 4, mounting frame 5, support seat 6, guide rail 7, servo motor 8, welding mechanism 9, multi-mode detector group 10, bidirectional screw 11, first motor 12, guide rod 13, slider 14, support frame 15, second hydraulic push rod 16, bearing seat 17, clamping ring 18, support arm 19, second motor 20, rotating ring 21, anti-slip pad 22, steel ball 23, controller 24. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0041] like Figure 1-4As shown, it is a schematic diagram of an autonomous positioning earth-covered storage tank welding auxiliary equipment provided by the present invention, the equipment comprises: a base 1, a moving mechanism is arranged at the four corners of the lower end of the base 1, a mounting frame 5 is fixedly connected to the top of the base 1, a support seat 6 is symmetrically fixedly connected to one side of the bottom of the mounting frame 5, a guide rail 7 is fixedly connected to one side of the support seat 6, a servo motor 8 is slidably connected to the outer side of the guide rail 7, a welding mechanism 9 is fixedly connected to the bottom of the servo motor 8, a multi-mode detector group 10 is fixedly connected to the bottom of the welding mechanism 9, a bidirectional screw 11 is arranged inside the base 1, one end of the bidirectional screw 11 is fixedly connected to the output end of the first motor 12, a guide rod 13 is symmetrically fixedly connected to one side of the base 1, a slider 14 is symmetrically threadedly connected to one end of the outer side of the bidirectional screw 11, a support frame 15 is symmetrically fixedly connected to one side of the top of the slider 14, a clamping ring 18 is fixedly connected to the top of the support frame 15, and a bidirectional screw 11 is arranged on the top of the base 1. There is a lifting mechanism, one end of the outer side of the clamping ring 18 is fixedly connected to a support arm 19, one side of the support arm 19 is fixedly connected to a second motor 20, and the output end of the second motor 20 is fixedly connected to a rotating ring 21. By driving the servo motor 8 to slide laterally on the outer side of the guide rail 7, the multi-mode detector group 10 arranged at the bottom of the servo motor 8 can detect the required welding position on the single-section cylinder section of the storage tank, and then control the welding mechanism 9 to perform welding operations on the required welding position on the single-section cylinder section of the storage tank, and further drive the second motor 20 arranged on one side of the support arm 19, the output end of the second motor 20 is fixedly connected to a rotating ring 21, and the steel ball 23 arranged between the clamping ring 18 and the rotating ring 21 can increase the smoothness during rotation, and the instant rotating ring 21 and the anti-skid pad 22 will drive the single-section cylinder section of the storage tank to perform a flipping operation under the drive of the second motor 20, so as to effectively improve the welding efficiency of the single-section cylinder section of the storage tank.

[0042] Preferably, a guide block 2 is symmetrically fixedly connected to one side of the base 1 .

[0043] Preferably, the moving mechanism comprises a first hydraulic push rod 3 , and a universal wheel 4 is fixedly connected to the bottom of the first hydraulic push rod 3 .

[0044] Preferably, a controller 24 is fixedly connected to one side of the mounting frame 5 .

[0045] Preferably, the bidirectional screw 11 is rotatably connected to the base 1 via a bearing fixing seat, and the first motor 12 is fixedly connected to an adjacent side of the base 1 .

[0046] Preferably, the sliding block 14 is located outside the guide rod 13 and is slidably connected thereto.

[0047] Preferably, the lifting mechanism includes a second hydraulic push rod 16 , and a bearing seat 17 is fixedly connected to the top of the second hydraulic push rod 16 .

[0048] Preferably, an anti-slip pad 22 is fixedly connected to the inner side of the rotating ring 21 , and the rotating ring 21 is rotatably connected to the clamping ring 18 via a steel ball 23 .

[0049] Furthermore, it also includes a welding positioning system, which includes a control chip and a multi-mode detector group, the multi-mode detector group is fixedly connected to the bottom of the servo motor, the multi-mode detector group includes a laser detector, an infrared detector and a visible light detector, the control chip is arranged on one side of the mounting frame, the control chip is electrically connected to the multi-mode detector group, the servo motor and the welding mechanism, and a welding positioning module is arranged in the control chip, the welding positioning module is used to determine the welding positioning according to the data collected by the multi-mode detector group, and control the servo motor to drive the welding mechanism to move to the welding position; like Figure 5 As shown, the welding positioning module is used to perform the following steps: S10, receiving weld image data collected by the multi-mode detector group, wherein the weld image data includes laser detection data, infrared detection data and visible light detection data; S20, preprocessing the weld image data, including filtering and denoising, image enhancement, and edge detection processing on the weld image data; S30, based on the preprocessed weld image data, using an image segmentation algorithm to segment the weld area to obtain weld contour information; S40, calculating a weld centerline coordinate sequence according to the weld profile information, and performing smoothing on the weld centerline coordinate sequence; S50, calculating the geometric characteristic parameters of the weld using the weld centerline coordinate sequence, wherein the geometric characteristic parameters include weld width, weld depth, and weld inclination angle; S60, determining a welding path point sequence according to the geometric characteristic parameters of the weld, each welding path point comprising three-dimensional space coordinate information and welding gun posture angle information; S70, calculating the motion trajectory between adjacent welding path points and generating a welding motion control instruction sequence; S80, sending the welding motion control instruction sequence to the servo motor, controlling the servo motor to drive the welding mechanism to perform welding operation along the motion trajectory; S90. During the welding process, weld formation data is collected in real time, and welding parameters are adjusted in real time according to the weld formation data. The welding parameters include welding current, welding voltage and welding speed.

[0050] The specific implementation methods of the above steps are described in detail below: Step S10: Receive weld image data collected by the multi-mode detector group The purpose of this step is to obtain the raw data for weld location. The multi-mode detector group includes laser detectors, infrared detectors and visible light detectors, which can respectively collect the three-dimensional geometric information, temperature distribution information and color texture information of the weld area. These three types of detection data together constitute the comprehensive image data of the weld.

[0051] The specific implementation is as follows: 1) The laser detector scans the weld area to obtain the 3D point cloud data of the weld. The point cloud data contains the elevation information of the weld contour and can be used to calculate the weld depth.

[0052] 2) The infrared detector measures the temperature distribution in the weld area and obtains two-dimensional thermal imaging data. The thermal imaging data reflects the temperature changes inside the weld and can be used to analyze the weld formation quality.

[0053] 3) The visible light detector takes a color image of the weld area to obtain the texture information of the weld appearance. The color image data can be used to identify the geometric features of the weld, such as width, shape, etc.

[0054] 4) The above three detection data are transmitted to the control chip through the data bus to form a complete weld image data set.

[0055] Step S20: Preprocessing the weld image data The purpose of this step is to eliminate image noise, enhance image contrast, and prepare for subsequent image segmentation and feature extraction.

[0056] The specific implementation is as follows: 1) Perform filtering and noise reduction on the original image data. For laser point cloud data, a moving average filter algorithm can be used to remove discrete noise points; for infrared thermal imaging data, a Gaussian filter can be used to smooth the temperature distribution; for visible light images, a median filter can be used to eliminate salt and pepper noise.

[0057] 2) Enhance the contrast of the filtered image data. For laser point cloud data, the histogram equalization method can be used to stretch the dynamic range of elevation values; for infrared thermal imaging data, the gamma correction algorithm can be applied to increase the temperature gradient; for visible light images, the adaptive histogram equalization algorithm can be used to improve edge clarity.

[0058] 3) Perform edge detection on the enhanced image data. The Canny algorithm can be used to extract edges from laser point cloud data, infrared thermal imaging data, and visible light images to obtain a binary edge map of the weld contour.

[0059] Through the above preprocessing operations, image noise can be effectively eliminated, and the key features of the weld area can be highlighted, laying the foundation for subsequent image segmentation and feature extraction.

[0060] Step S30: Based on the preprocessed weld image data, the weld area is segmented using an image segmentation algorithm. The purpose of this step is to accurately extract the geometric contour information of the weld from the complex welding environment and provide the necessary input data for subsequent weld feature analysis and welding path planning.

[0061] The specific implementation is as follows: 1) The image segmentation algorithm based on region growing is applied to the preprocessed laser point cloud data, infrared thermal imaging data and visible light image data to obtain the weld area segmentation results under three detection methods.

[0062] 2) The above three segmentation results are fused and a multimodal fusion algorithm based on image sparse representation is used to obtain a comprehensive weld contour segmentation mask. This fusion algorithm can utilize the complementary advantages of the three detection data to enhance the segmentation accuracy of the weld area.

[0063] 3) Perform morphological operations on the segmentation mask, such as opening and closing operations, to eliminate small holes and burr noise in the segmentation results, and further optimize the continuity and smoothness of the weld contour line.

[0064] Through the above image segmentation steps, the geometric contour information of the weld area can be accurately extracted, laying the foundation for subsequent weld feature analysis.

[0065] Step S40: Calculate the weld centerline coordinate sequence based on the weld contour information and perform smoothing on it. The purpose of this step is to obtain the spatial position information of the weld centerline and provide key input data for subsequent welding path planning.

[0066] The specific implementation is as follows:

[0067] 1) First, define the probability distribution function of the weld centerline coordinate sequence : ; in, For the The gray value of a pixel, is the total number of pixels in the image, and are weight coefficient and attenuation coefficient, For point The shortest distance to the centerline of the predicted weld.

[0068] 2) Using the above probability distribution function , combined with the weld contour information obtained by segmentation, the maximum likelihood estimation method is used to calculate the coordinate sequence of the weld centerline .

[0069] 3) The calculated weld centerline coordinate sequence is smoothed by using a Gaussian filter or spline function fitting method to eliminate slight fluctuations in the centerline trajectory and further improve the accuracy of welding path planning.

[0070] Through this step, a smooth weld centerline trajectory can be obtained, providing basic data for subsequent welding geometric feature calculations and welding path planning.

[0071] Step S50: Calculate the geometric characteristic parameters of the weld according to the weld centerline information The purpose of this step is to extract key characteristic parameters such as the geometric dimensions and inclination angle of the weld, providing a basis for the optimization planning of the welding path.

[0072] The specific implementation is as follows: 1) Weld width Calculation: ; in, is the Fourier transform of the grayscale distribution of the weld edge, is the measurement error.

[0073] 2) Weld depth Calculation: ; in, is the infrared radiation intensity of the weld area, is the ambient infrared radiation reference value, is the standard weld width, is the coefficient to be determined, is the depth measurement error.

[0074] 3) Welding seam inclination angle Calculation: ; in, is the weld centerline coordinate, and is the amplitude and frequency of the angle fluctuation, is the angle measurement error.

[0075] Through the above calculation formula, key geometric characteristic parameters such as weld width, depth and inclination angle can be obtained. These parameters provide necessary input for subsequent welding path planning.

[0076] Step S60: Determine the welding path point sequence according to the weld geometry characteristic parameters The purpose of this step is to generate a series of optimized welding path points to provide a basis for the motion control of the welding mechanism.

[0077] The specific implementation is as follows: 1) Define welding path points The six-dimensional vector representation of is: ; in, is the spatial coordinate, is the welding gun posture Euler angle, is the path point mapping function, For the The arc length parameter of the sampling points, is a 6×6 error amplification matrix, is a six-dimensional error vector.

[0078] 2) Weld seam geometric characteristic parameters calculated according to step S50 , through the path point mapping function Determine the six-dimensional path point vector for each sampling point .

[0079] 3) Considering the measurement noise and modeling error in the actual welding process, add items to improve the robustness of the welding trajectory.

[0080] Through this step, a series of optimized welding path points can be generated, providing the key input data required for subsequent welding machine motion control.

[0081] Step S70: Calculate the motion trajectory between adjacent welding path points and generate a welding motion control instruction sequence The purpose of this step is to calculate the continuous trajectory of the welding machine movement based on the planned welding path point sequence, and convert it into a control instruction sequence for the servo motor, providing a basis for the automatic execution of the welding process.

[0082] The specific implementation is as follows: 1) Using the spline interpolation algorithm, the discrete welding path point sequence generated in step S60 is smoothly interpolated to obtain a continuous welding machine motion trajectory.

[0083] 2) According to the motion trajectory of the welding machine, calculate the required position, velocity and acceleration information at each path point.

[0084] 3) Convert the above position, speed and acceleration information into a pulse command sequence for the servo motor, including pulse count value and pulse frequency.

[0085] 4) Send the generated servo motor control instruction sequence to the control chip to drive the welding mechanism to perform welding operations along the optimized welding path.

[0086] Through this step, the welding path point sequence can be converted into actual servo motor control instructions, providing precise motion control basis for the subsequent welding process.

[0087] Step S80: Send the welding motion control instruction sequence to the servo motor to control the welding mechanism to perform welding operations along the motion trajectory. The purpose of this step is to enable the welding mechanism to perform automatic welding along the optimized welding path according to the servo motor control instruction sequence calculated in step S70.

[0088] The specific implementation is as follows: 1) The control chip sends the servo motor control instruction sequence generated in step S70 to the servo motor driver through the digital I / O interface.

[0089] 2) The servo motor driver adjusts the speed and torque output of the servo motor in real time according to the received position, speed and acceleration instructions, driving the welding mechanism to move along the optimized welding path.

[0090] 3) The welding mechanism includes a welding gun body, a wire feeding mechanism and a gas protection cover, which continuously feeds the welding wire and provides inert gas protection during the movement to complete the automatic welding operation.

[0091] 4) The control chip monitors the operating status of the servo motor during the welding process in real time, detects and corrects any deviations in time to ensure welding quality and safety.

[0092] Through this step, the welding auxiliary equipment can independently complete the entire process of weld positioning, welding path planning and welding machine motion control, realizing the automation of welding operations.

[0093] Step S90: During the welding process, real-time data of weld formation is collected and welding parameters are adjusted according to the data. The purpose of this step is to ensure the best weld quality through real-time monitoring and feedback control of the welding process.

[0094] The specific implementation is as follows: 1) Welding current Real-time adjustment: ; in, is the weld formation error, are the PID controller parameters.

[0095] 2) Welding voltage Real-time adjustment: ; in, is the depth compensation coefficient, is the voltage fluctuation term.

[0096] 3) Welding speed Real-time adjustment: ; in, is the speed adjustment factor, is the cumulative error attenuation coefficient.

[0097] Through real-time adaptive adjustment of the three major parameters of welding current, voltage and speed, deviations in the welding process can be effectively compensated to ensure that the weld formation quality reaches the optimal state.

[0098] In summary, the autonomous positioning earth-covered storage tank welding auxiliary equipment adopts multi-mode sensor data fusion, advanced image processing algorithm and real-time feedback control technology to realize autonomous positioning of weld position, intelligent planning of welding path, and dynamic optimization and adjustment of welding process parameters.

[0099] The working principle and use process of this equipment: During the welding process of a single-section barrel section of an earth-covered storage tank, the single-section barrel section of the storage tank is fixed to the clamping rings 18 set at both ends, and the single-section barrel section of the storage tank is located on the inner side of the rotating ring 21. The anti-skid pad 22 set inside the rotating ring 21 can prevent the single-section barrel section of the storage tank from slipping during the welding process. Then, by driving the servo motor 8 to slide laterally on the outer side of the guide rail 7, the multi-mode detector group 10 set at the bottom of the servo motor 8 can detect the required welding position on the single-section barrel section of the storage tank, and then control the welding mechanism 9 to perform welding operations on the required welding position on the single-section barrel section of the storage tank, and further drive the second motor 20 set on one side of the support arm 19. The output end of the second motor 20 is fixedly connected to the rotating ring 21. The steel ball 23 set between the clamping ring 18 and the rotating ring 21 can increase the smoothness during rotation, and the rotating ring 21 and the anti-skid pad 22 are on the second motor. The single-section barrel section of the storage tank is driven by the machine 20 to perform a flipping operation, so as to effectively improve the welding efficiency of the single-section barrel section of the storage tank, so that the single-section barrel section welding auxiliary equipment of the earth-covered storage tank can perform welding operations on the single-section barrel section of the storage tank in a semi-automatic manner, so as to reduce the unevenness and welding leakage caused by manual welding, and the welding efficiency of the single-section barrel section of the earth-covered storage tank can be improved immediately. During the welding process of the single-section barrel section of the storage tank, the single-section barrel section of the storage tank is pushed to the top of the bearing seat 17 through the guide block 2, and then the single-section barrel section of the storage tank is transported to the position where the clamping ring 18 clamps the single-section barrel section of the storage tank by the second hydraulic push rod 16. The first motor 12 set on one side of the driving base 1 is used to rotate the bidirectional screw 11, and the support frame 15 and the clamping ring 18 can move relative to each other under the rotation of the bidirectional screw 11, so as to complete the clamping and fixing of the single-section barrel sections of the storage tanks of different lengths, thereby completing the welding of the single-section barrel sections of the storage tanks of different lengths.

[0100] Specifically, the principle of the present invention can be summarized into three key points: multi-mode sensor data fusion, accurate extraction of weld geometry features, and real-time monitoring of welding quality and adaptive adjustment of parameters.

[0101] First, the device uses a variety of heterogeneous sensors such as laser detectors, infrared detectors and visible light detectors, which can fully obtain the three-dimensional geometric information, temperature distribution characteristics and appearance texture data of the weld area. These different types of sensor data have their own advantages and limitations. It is difficult to meet the requirements of accurate positioning of hidden welds using any one sensor alone. Therefore, the present invention adopts a multimodal data fusion algorithm based on image sparse representation to organically combine the three types of detection data, give full play to their complementary advantages, and greatly enhance the robustness and accuracy of weld contour extraction.

[0102] Secondly, the present invention specifically designs a series of image processing algorithms, including filtering and noise reduction, contrast enhancement, edge detection and region segmentation, which can adaptively extract the geometric characteristic parameters of the weld, such as width, depth and tilt angle, from the complex welding environment. These geometric characteristic parameters are crucial for the subsequent optimization planning of the welding path. For example, the weld width information can be obtained by analyzing the edge grayscale distribution through Fourier transform; the weld depth can be estimated by building a mathematical model using infrared radiation intensity and width parameters; and the weld tilt angle can be calculated based on the centerline coordinate sequence. Through these precise geometric feature extraction algorithms, high-quality input data is provided for welding path planning.

[0103] Finally, the autonomous positioning welding auxiliary equipment of the present invention integrates real-time welding quality monitoring and parameter adaptive adjustment functions. During the welding process, the equipment will collect weld formation status data in real time, including geometric dimensions, temperature distribution, etc., and dynamically adjust key parameters such as welding current, voltage and speed according to these monitoring data to ensure that the weld quality reaches the best state. For example, the PID closed-loop control algorithm can be used to adjust the welding current to compensate for the weld formation error; the voltage adjustment can be adaptively compensated in combination with the changes in weld width and depth; the dynamic adjustment of the welding speed can be optimized according to the accumulated formation error. Through this real-time monitoring and parameter self-adjustment mechanism, the stability and consistency of the welding quality are effectively ensured, and the automation level of the earth-covered storage tank welding operation is greatly improved.

[0104] In summary, the autonomous positioning earth-covered storage tank welding auxiliary equipment of the present invention fully integrates multi-mode sensor data, advanced image processing algorithms and real-time feedback control technology, can accurately locate hidden welds, optimize welding path planning, and realize dynamic regulation of welding quality.

[0105] A specific embodiment 1 of the welding positioning module of the present invention is provided below. Each step in this embodiment 1 is described in detail as follows: Step S10: Receive weld image data collected by the multi-mode detector group The purpose of this step is to obtain the raw data for weld location. The multi-mode detector group includes laser detectors, infrared detectors and visible light detectors, which can respectively collect the three-dimensional geometric information, temperature distribution information and color texture information of the weld area. These three types of detection data together constitute the comprehensive image data of the weld.

[0106] The specific implementation is as follows: 1) The laser detector scans the weld area to obtain the 3D point cloud data of the weld ,in Indicates The three-dimensional spatial coordinates of the laser points, is the total number of points in the point cloud data. The point cloud data contains the elevation information of the weld contour and can be used to calculate the weld depth.

[0107] 2) The infrared detector measures the temperature distribution in the weld area and obtains two-dimensional thermal imaging data ,in is the pixel coordinate in the thermal image, Indicates the infrared radiation intensity of the pixel. The thermal imaging data reflects the temperature change inside the weld and can be used to analyze the weld formation quality.

[0108] 3) Visible light detector captures color images of the weld area ,in is the pixel coordinate, Indicates the color channel. This color image data can be used to identify the geometric features of the weld, such as width, shape, etc.

[0109] 4) The above three detection data are transmitted to the control chip through the data bus to form a complete weld image data set .

[0110] Step S20: Preprocessing the weld image data The purpose of this step is to eliminate image noise, enhance image contrast, and prepare for subsequent image segmentation and feature extraction.

[0111] The specific implementation is as follows: 1) Filter and reduce noise on the original image data. , the moving average filtering algorithm can be used to remove discrete noise points and obtain the filtered point cloud data ;For infrared thermal imaging data , a Gaussian filter can be applied to smooth the temperature distribution and obtain ;For visible light images , we can use median filtering to eliminate salt and pepper noise and get .

[0112] 2) Enhance the contrast of the filtered image data. , the histogram equalization method can be used to stretch the dynamic range of the elevation value to obtain ;For infrared thermal imaging data , the gamma correction algorithm can be applied to increase the temperature gradient and obtain For visible light images , the adaptive histogram equalization algorithm can be used to improve the edge clarity and obtain .

[0113] 3) Perform edge detection on the enhanced image data. Canny algorithm can be used to process the laser point cloud data. , infrared thermal imaging data and visible light images Perform edge extraction respectively to obtain the binary edge map of the weld contour .

[0114] Through the above preprocessing operations, image noise can be effectively eliminated, and the key features of the weld area can be highlighted, laying the foundation for subsequent image segmentation and feature extraction.

[0115] Step S30: Based on the preprocessed weld image data, the weld area is segmented using an image segmentation algorithm. The purpose of this step is to accurately extract the geometric contour information of the weld from the complex welding environment and provide the necessary input data for subsequent weld feature analysis and welding path planning.

[0116] The specific implementation is as follows: 1) Preprocessed laser point cloud data , infrared thermal imaging data and visible light images The image segmentation algorithm based on region growing is applied respectively to obtain the weld region segmentation results under three detection methods. Among them, the region growing algorithm calculates the similarity of adjacent pixels and clusters similar pixels into the same region, thereby extracting the weld contour.

[0117] 2) The above three segmentation results A comprehensive weld contour segmentation mask is obtained by fusion using a multimodal fusion algorithm based on image sparse representation. The fusion algorithm can take advantage of the complementary advantages of the three detection data to enhance the segmentation accuracy of the weld area. Specifically, the fusion algorithm can define the following optimization problem: ; in, is the sparse fusion coefficient vector, is the segmentation result matrix, is the desired segmentation mask, is the sparsity constraint parameter.

[0118] 3) Segmentation mask Morphological operations, such as opening and closing operations, are performed to eliminate small holes and burr noise in the segmentation results and further optimize the continuity and smoothness of the weld contour.

[0119] Through the above image segmentation steps, the geometric contour information of the weld area can be accurately extracted, laying the foundation for subsequent weld feature analysis.

[0120] Step S40: Calculate the weld centerline coordinate sequence based on the weld contour information and perform smoothing on it. The purpose of this step is to obtain the spatial position information of the weld centerline and provide key input data for subsequent welding path planning.

[0121] The specific implementation is as follows: 1) First, define the probability distribution function of the weld centerline coordinate sequence : ; in, The segmentation mask Middle The gray value of a pixel, is the total number of pixels, and are weight coefficient and attenuation coefficient, For point The shortest distance to the predicted weld centerline. The probability distribution function takes into account the pixel gray value and distance factors, and can reflect the probability distribution of the weld centerline.

[0122] 2) Using the above probability distribution function , combined with the weld contour information obtained by segmentation, the maximum likelihood estimation method is used to calculate the coordinate sequence of the weld centerline ,in Represents the arc length parameter along the weld direction.

[0123] 3) The calculated weld centerline coordinate sequence Perform Gaussian filtering and smoothing to eliminate slight fluctuations in the centerline trajectory: ; ; in, is the standard deviation of the Gaussian kernel function, which is used to control the degree of smoothing.

[0124] Through this step, a smooth weld centerline trajectory can be obtained. , providing basic data for subsequent welding geometry feature calculation and welding path planning.

[0125] Step S50: Calculate the geometric characteristic parameters of the weld according to the weld centerline information The purpose of this step is to extract key characteristic parameters such as the geometric dimensions and inclination angle of the weld, providing a basis for the optimization planning of the welding path.

[0126] The specific implementation is as follows: 1) Weld width Calculation: ; in, is the Fourier transform of the grayscale distribution of the weld edge, is the measurement error. Edge grayscale distribution The segmentation results can be It is obtained by performing Canny edge detection, sampling and Fourier transform.

[0127] 2) Weld depth Calculation: ;

[0128] in, is the infrared radiation intensity of the weld area, is the ambient infrared radiation reference value, is the standard weld width, is the coefficient to be determined, is the depth measurement error. Undetermined coefficient It can be obtained by fitting the measured data using the least squares method.

[0129] 3) Welding seam inclination angle Calculation: ; in, is the weld centerline coordinate, and is the amplitude and frequency of the angle fluctuation, is the angle measurement error.

[0130] Through the above calculation formula, the weld width can be obtained ,depth and tilt angle These parameters provide the necessary input for subsequent welding path planning.

[0131] Step S60: Determine the welding path point sequence according to the weld geometry characteristic parameters The purpose of this step is to generate a series of optimized welding path points to provide a basis for the motion control of the welding mechanism.

[0132] The specific implementation is as follows: 1) Define welding path points The six-dimensional vector representation of is: ; in, is the spatial coordinate, is the welding gun posture Euler angle, is the path point mapping function, For the The arc length parameter of the sampling points, is a 6×6 error amplification matrix, is a six-dimensional error vector. Path point mapping function According to the weld geometry parameters Design the corresponding mapping relationship to determine the six-dimensional path point vector of each sampling point .

[0133] 2) Considering the measurement noise and modeling error in the actual welding process, the path point vector Add To improve the robustness of the welding trajectory. Among them, the error amplification matrix It can be obtained from measured data through singular value decomposition method.

[0134] Through this step, a series of optimized welding path points can be generated. , providing the required key input data for subsequent welding machine motion control.

[0135] Step S70: Calculate the motion trajectory between adjacent welding path points and generate a welding motion control instruction sequence The purpose of this step is to calculate the continuous trajectory of the welding machine movement based on the planned welding path point sequence, and convert it into a control instruction sequence for the servo motor, providing a basis for the automatic execution of the welding process.

[0136] The specific implementation is as follows: 1) Using the cubic spline interpolation algorithm, the discrete welding path point sequence generated in step S60 is Perform smooth interpolation to obtain a continuous welding machine motion trajectory The cubic spline interpolation formula is as follows: ; in, For the Coefficients of segment spline curves, For the The timestamp of each waypoint.

[0137] 2) According to the movement trajectory of the welding machine , calculate the required position at each path point ,speed and acceleration information.

[0138] 3) Convert the above position, speed and acceleration information into a pulse command sequence for the servo motor, including the pulse count value and pulse frequency : ; ; in, is the conversion factor for position, velocity and acceleration.

[0139] 4) The generated servo motor control instruction sequence The information is sent to the control chip to drive the welding mechanism to perform welding operations along the optimized welding path.

[0140] Through this step, the welding path point sequence can be converted into actual servo motor control instructions, providing precise motion control basis for the subsequent welding process.

[0141] Step S80: Send the welding motion control instruction sequence to the servo motor to control the welding mechanism to perform welding operations along the motion trajectory. The purpose of this step is to enable the welding mechanism to perform automatic welding along the optimized welding path according to the servo motor control instruction sequence calculated in step S70.

[0142] The specific implementation is as follows: 1) The control chip generates the servo motor control instruction sequence in step S70 Sent to the servo motor driver via the digital I / O interface.

[0143] 2) The servo motor driver receives the position command and speed command , the speed and torque output of the servo motor are adjusted in real time to drive the welding mechanism including the welding gun body, wire feeding mechanism and gas protection cover to move along the optimized welding path.

[0144] 3) During the movement, the welding gun body continues to feed the welding wire, and the wire feeding mechanism transports the welding wire; at the same time, the gas protection cover provides inert gas protection to complete the automatic welding operation.

[0145] 4) The control chip monitors the operating status of the servo motor during the welding process in real time, detects and corrects any deviations in time to ensure welding quality and safety.

[0146] Through this step, the welding auxiliary equipment can independently complete the entire process of weld positioning, welding path planning and welding machine motion control, realizing the automation of welding operations.

[0147] Step S90: During the welding process, real-time data of weld formation is collected and welding parameters are adjusted according to the data. The purpose of this step is to ensure the best weld quality through real-time monitoring and feedback control of the welding process.

[0148] The specific implementation is as follows: 1) Welding current Real-time adjustment: ; in, is the weld formation error, are the PID controller parameters. The PID parameters can be obtained from the measured data through the Ziegler-Nichols tuning method.

[0149] 2) Welding voltage Real-time adjustment: ; in, is the depth compensation coefficient, is the voltage fluctuation term.

[0150] 3) Welding speed Real-time adjustment: ; in, is the speed adjustment factor, is the cumulative error attenuation coefficient.

[0151] Through real-time adaptive adjustment of the three major parameters of welding current, voltage and speed, deviations in the welding process can be effectively compensated to ensure that the weld formation quality reaches the optimal state.

[0152] The following provides an embodiment 2 of a specific application scenario of the present invention: The overall structure of the autonomous positioning earth-covered storage tank welding auxiliary equipment in this embodiment 2 is shown in Table 1. It mainly includes a base, a moving mechanism, a mounting frame, a support seat, a guide rail, a servo motor, a welding mechanism, a bidirectional screw, a first motor, a guide rod, a slider, a support frame, a clamping ring, a lifting mechanism, a support arm, a second motor and a rotating ring.

[0153] Table 1 Main structural components of autonomous positioning welding auxiliary equipment Part Name describe Base It is made of 6mm thick rectangular steel plate and has a size of 1000mm×800mm. There are moving mechanisms at the four corners of the base, a 20mm high upward extending rib at the top edge, and a guide block symmetrically arranged on one side. Mobile mechanism It includes 4 first hydraulic push rods, the cylinder body of each push rod is fixed at the four corners of the bottom of the base, and the bottom of the piston rod is connected to a universal wheel made of polyurethane, and the stroke range is 50-80mm. Mounting bracket It adopts I-beam structure, with column height of 1500mm and beam length of 1200mm. The column and beam are reinforced and connected by triangular support plates, and a support seat is symmetrically fixed on one side of the bottom of the mounting frame. Support seat It is made of 12mm thick steel plate, with a size of 300mm×200mm, and a guide rail is fixedly connected to one side. guide It adopts a dovetail groove structure, with limit blocks at both ends and a servo motor slidingly connected on the outside. Servo Motor Rated power 3kW, maximum speed 3000rpm, installed on the outside of the guide rail, can move left and right along the guide rail. Welding mechanism It comprises a welding gun body, a wire feeding mechanism and a gas protection cover. The welding gun body is connected to the output shaft of a servo motor through a universal joint, and the wire feeding mechanism and the gas protection cover are installed around the welding gun body. Bidirectional screw The diameter is 40mm, the pitch is 5mm, and it is rotatably connected to the base through a bearing fixing seat, and a double-row tapered roller bearing is arranged in the bearing fixing seat. First Motor Rated power 1.5kW, installed on one side of the base, with a diaphragm coupling between the bidirectional screw. Guide rod The diameter is 25mm, the cross section is dovetail-shaped, and it is fixedly installed on the inside of the base. slider A dovetail groove structure is provided inside to match the guide rod. The material is a high molecular polymer and the friction coefficient between the guide rod and the guide rod is small. Support frame It is fixedly connected to the top of the slider, and a clamping ring is installed on the top. Lifting mechanism It comprises a second hydraulic push rod, the bottom of which is fixed on the top of the base, and the top of which is connected to a disc-shaped bearing seat, and a plurality of limiting protrusions are arranged on the bearing seat. Arm It is fixedly connected to the outside of the clamping ring, and a second motor is installed at one end. Rotating ring It adopts a split structure, including two upper and lower half ring bodies, with a silicone anti-skid pad fixed on the inside, which is rotatably connected to the clamping ring through a steel ball.

[0154] The working principle of this autonomous positioning welding auxiliary equipment is as follows: The base is equipped with 4 moving mechanisms and can move autonomously in the horizontal plane. The mounting frame is fixed on the top of the base and connected to the base through the support seat. A guide rail is installed on one side of the support seat. The welding gun body with a servo motor welding mechanism slidably connected on the guide rail is connected to the output shaft of the servo motor through a universal joint and can move left and right along the guide rail to achieve accurate positioning of the weld position.

[0155] A bidirectional screw is provided inside the base, one end of which is connected to the output shaft of the first motor, and the other end of which moves back and forth on the guide rod through a slider. A support frame is fixed on the top of the slider, and a clamping ring is installed on the support frame. The bidirectional screw is driven to rotate by the first motor, which can drive the clamping ring to move up and down to achieve height adjustment of the welding object.

[0156] The lifting mechanism is arranged on the top of the base, including a second hydraulic push rod, the top of which is connected to a disc-shaped bearing seat, and a plurality of limit protrusions are arranged on the bearing seat. The support arm is fixed on the outside of the clamping ring, and a second motor is installed at one end. The second motor drives the rotating ring to rotate to adjust the welding gun posture.

[0157] In general, the autonomous positioning welding auxiliary equipment can achieve precise adjustment of the horizontal position, height and welding gun posture of the welding object through the moving mechanism, servo motor and lifting mechanism, providing a solid mechanical foundation for subsequent welding operations. The implementation scheme of the welding positioning module in the equipment will be further introduced below.

[0158] The following provides an embodiment 3 of a specific application scenario of the welding positioning system of the self-positioning earth-covered storage tank welding auxiliary equipment in the present invention: the welding positioning system is mainly composed of a control chip and a multi-mode detector group, as shown in Table 2. The multi-mode detector group includes a laser detector, an infrared detector and a visible light detector, which are installed at the bottom of the servo motor; the control chip is installed on one side of the mounting frame, electrically connected to the multi-mode detector group, the servo motor and the welding mechanism, and a welding positioning module is provided inside.

[0159] Table 2 Composition of welding positioning module of autonomous positioning welding auxiliary equipment Part Name describe Control chip It is used to process the data collected by the multi-mode detector group, execute the welding positioning algorithm, and send control instructions to the servo motor and welding mechanism. Multimode detector set It includes laser detectors, infrared detectors and visible light detectors, which are installed at the bottom of the servo motor and are used to collect three-dimensional geometric information, temperature distribution and appearance texture data of the weld area. Laser Detector Using high-precision 3D scanning laser sensors, three-dimensional point cloud data of the weld surface can be obtained. Infrared detector Using a thermal imaging infrared camera, the temperature distribution in the weld area can be measured. Visible light detector A high-resolution digital camera is used to capture color images of the weld appearance.

[0160] The workflow of the welding positioning module mainly includes the following steps: 1) Receive weld image data collected by a multi-mode detector group, including laser point cloud data, infrared thermal imaging data and visible light image data.

[0161] 2) Preprocess the original image data, including filtering and noise reduction, contrast enhancement and edge detection, to highlight the key features of the weld area.

[0162] 3) Based on the preprocessed image data, the geometric contour information of the weld area is extracted using an image segmentation algorithm. Specifically, the laser point cloud, infrared thermal imaging, and visible light image can be segmented separately, and then the multimodal fusion algorithm is used to combine the three segmentation results to obtain an accurate weld contour mask.

[0163] 4) According to the weld contour information, the spatial coordinate sequence of the weld centerline is calculated and smoothed by Gaussian filtering. The centerline coordinate sequence can be extracted from the weld contour data by the maximum likelihood estimation method.

[0164] 5) Using the weld centerline information, calculate the weld geometric characteristic parameters, including width, depth and inclination angle. For example, the weld width can be obtained by Fourier analysis of the edge grayscale distribution; the weld depth can be estimated by building a mathematical model using infrared radiation intensity and width parameters; the weld inclination angle can be calculated based on the centerline coordinates.

[0165] 6) According to the geometric characteristic parameters of the weld, the optimized welding path point sequence is determined, and each path point contains the spatial coordinates and the welding gun posture angle. The determination of the path point can be achieved by designing a reasonable mapping function.

[0166] 7) Calculate the motion trajectory between adjacent path points and generate control instruction sequences such as position, speed and acceleration of the servo motor.

[0167] 8) Send the welding motion control instructions to the servo motor to drive the welding mechanism to perform automatic welding operations along the optimized welding path.

[0168] 9) During the welding process, real-time data on weld formation, including geometric dimensions, temperature distribution, etc., is collected, and parameters such as welding current, voltage, and speed are dynamically adjusted based on the monitoring data to ensure that the weld quality reaches the best state. For example, a PID closed-loop control algorithm can be used to adjust the welding current to compensate for weld formation errors.

[0169] The key to the entire welding positioning module is to make full use of multi-mode sensor data, adopt advanced image processing algorithms and real-time feedback control technology to achieve precise positioning of hidden welds, optimal planning of welding paths, and dynamic monitoring of welding quality and parameter adjustment.

[0170] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An autonomous positioning earth-covered storage tank welding auxiliary equipment, characterized in that: include: The cam is provided with a lifting mechanism, and the lifting mechanism comprises a lifting mechanism, a first motor, a second motor, a second motor and a second motor.

2. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 1 is characterized in that: It also includes a welding positioning system, which includes a control chip and a multi-mode detector group, the multi-mode detector group is fixedly connected to the bottom of the servo motor, the multi-mode detector group includes a laser detector, an infrared detector and a visible light detector, the control chip is arranged on one side of the mounting frame, the control chip is electrically connected to the multi-mode detector group, the servo motor and the welding mechanism, and a welding positioning module is arranged in the control chip, the welding positioning module is used to determine the welding positioning according to the data collected by the multi-mode detector group, and control the servo motor to drive the welding mechanism to move to the welding position; The welding positioning module is used to perform the following steps: S10, receiving weld image data collected by the multi-mode detector group, wherein the weld image data includes laser detection data, infrared detection data and visible light detection data; S20, preprocessing the weld image data, including filtering and denoising, image enhancement, and edge detection processing on the weld image data; S30, based on the preprocessed weld image data, using an image segmentation algorithm to segment the weld area to obtain weld contour information; S40, calculating a weld centerline coordinate sequence according to the weld profile information, and performing smoothing on the weld centerline coordinate sequence; S50, calculating the geometric characteristic parameters of the weld using the weld centerline coordinate sequence, wherein the geometric characteristic parameters include weld width, weld depth, and weld inclination angle; S60, determining a welding path point sequence according to the geometric characteristic parameters of the weld, each welding path point comprising three-dimensional space coordinate information and welding gun posture angle information; S70, calculating the motion trajectory between adjacent welding path points and generating a welding motion control instruction sequence; S80, sending the welding motion control instruction sequence to the servo motor, controlling the servo motor to drive the welding mechanism to perform welding operation along the motion trajectory; S90. During the welding process, weld formation data is collected in real time, and welding parameters are adjusted in real time according to the weld formation data. The welding parameters include welding current, welding voltage and welding speed.

3. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 2 is characterized in that: The base is made of a rectangular steel plate, and an upwardly extending rib is provided at the top edge of the base, and the height of the rib is 20 to 30 mm; a guide block is symmetrically fixedly connected to one side of the base, and the guide block adopts a triangular structure, and its inclined surface faces the center position of the base.

4. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 3 is characterized in that: The moving mechanism includes a first hydraulic push rod, a cylinder body of the first hydraulic push rod is fixedly connected to the lower surface of the base, a universal wheel is fixedly connected to the bottom of the piston rod of the first hydraulic push rod, and the universal wheel is made of polyurethane material; the stroke range of the first hydraulic push rod is 50 to 80 mm.

5. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 4 is characterized in that: The bidirectional screw is rotatably connected to the base via a bearing fixing seat, a double-row tapered roller bearing is arranged in the bearing fixing seat; the first motor is fixedly connected to one side adjacent to the base.

6. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 5 is characterized in that: The slider is located on the outer side of the guide rod and is slidably connected thereto. A dovetail groove structure is arranged inside the slider. The cross section of the guide rod is dovetail-shaped and matches the dovetail groove of the slider.

7. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 6 is characterized in that: The lifting mechanism comprises a second hydraulic push rod, the bottom of the second hydraulic push rod is fixedly connected to the top of the base, and the top of the second hydraulic push rod is fixedly connected to a bearing seat.

8. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 7 is characterized in that: The bearing seat is in a disc-shaped structure, and a plurality of limiting protrusions evenly distributed along the circumference are arranged on its upper surface.

9. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 8 is characterized in that: The material of the sliding block is a high molecular polymer, which is used to reduce the friction between the sliding block and the guide rod.

10. The self-positioning earth-covered storage tank welding auxiliary equipment according to claim 9, characterized in that: A coupling is arranged between the first motor and the bidirectional screw, and the coupling adopts a diaphragm structure.

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