Robot-based pipe groove self-adaptive polishing control method

Abstract

The application provides a pipe groove self-adaptive polishing control method based on a robot, belongs to the polishing control technical field, and relies on a multi-dimensional parameter acquisition device to realize real-time and accurate acquisition of pipe groove appearance, polishing mechanical parameters and grinding tool state parameters. Through a constructed multivariate coupling self-adaptive polishing control model, three parameters of robot polishing pressure, polishing rotating speed and feeding speed are dynamically optimized, different initial defects of the groove, different pipe specifications and different loss states of the grinding tool can be adapted without manual intervention, the polishing amount of the groove is accurate, uniform and controllable, the problems of uneven polishing and excessive polishing are completely eliminated, the groove forming precision and subsequent welding quality are greatly improved, and the automation, intelligent level and operation efficiency of the polishing operation are improved.

Description

Technical Field

[0001] This invention belongs to the field of grinding control technology, specifically relating to a robot-based adaptive grinding control method for pipe beveling. Background Technology

[0002] Pipeline welding is a major construction process in fields such as oil and gas transportation, municipal engineering, power grids, and chemical equipment. As an important forming structure of welded joints, the grinding precision, uniformity, and forming consistency of pipeline beveling directly determine the weld fusion quality, welding mechanical properties, and the sealing and safety of pipelines during long-term operation. At present, pipeline beveling operations in the industry are still mainly carried out by two modes: manual grinding and robot fixed trajectory grinding. Both of these modes have significant technical defects and are difficult to adapt to the needs of high-precision, standardized, and batch pipeline construction.

[0003] Manual grinding relies entirely on the operator's skill level, experience, and real-time working conditions. Different workers exhibit significant differences in grinding intensity, angle, and duration. Even when the same worker works continuously, fatigue, visual errors, and hand tremors can lead to uneven grinding, localized over-grinding, bevel angle deviations, and burr residue on the bevel end face. Over-grinding results in thinning of the pipe wall and insufficient effective welding allowance at the bevel, reducing the weld's load-bearing strength. Insufficient grinding leaves behind oxide scale, cutting burrs, and unevenness, leading to quality defects such as incomplete fusion, porosity, slag inclusions, and cracks in subsequent welding. This significantly increases the pipe welding rework rate and the risk of operational leaks. Furthermore, manual grinding operates in a dusty and noisy environment, is extremely labor-intensive, and has very low safety and production efficiency, failing to meet the construction standards of modern pipeline engineering.

[0004] Existing conventional robotic grinding technologies mostly employ a control mode with preset fixed trajectories, fixed grinding pressures, and fixed grinding speeds. This mode can only adapt to ideal pipe bevels with standard specifications and regular shapes. In actual construction, after pipes are cut, transported, and placed, there are generally unstructured chemical conditions such as initial bevel forming deviations, slight pipe deformations, differences in end face flatness, and uneven oxide layer thickness. Fixed parameter grinding modes cannot dynamically adjust grinding parameters according to real-time working conditions. When there are local protrusions in the bevel and the oxide layer is thick, the amount removed by grinding is insufficient; when there are local depressions in the bevel and the substrate is thin, over-grinding can easily damage the substrate. Ultimately, the problems of poor grinding consistency and low forming accuracy still exist, and the shortcomings of manual grinding and traditional robotic grinding cannot be solved at the root.

[0005] Based on this, the present invention proposes a robot-based adaptive grinding control method for pipe beveling. By real-time acquisition of multiple parameters, coupling control model and dynamic parameter iterative adjustment, it completely solves the technical problems of existing technology such as grinding accuracy relying on manual labor, uneven grinding, over-grinding and poor adaptability. Summary of the Invention

[0006] The purpose of this invention is to address the technical shortcomings of existing pipe beveling techniques, such as reliance on manual skills for grinding quality, poor grinding uniformity, susceptibility to over-grinding or under-grinding, weak adaptability to working conditions, and low welding quality. This invention provides a robot-based adaptive grinding control method for pipe beveling. Utilizing multi-dimensional parameter acquisition equipment, the invention achieves real-time and accurate acquisition of pipe beveling morphology, grinding mechanical parameters, and grinding tool state parameters. Through a constructed multivariate coupled adaptive grinding control model, it dynamically optimizes three key parameters: robot grinding pressure, grinding speed, and feed rate. Without manual intervention, it can adapt to different initial defects in beveling, different pipe specifications, and different grinding tool wear states, achieving accurate, uniform, and controllable beveling amount. This completely eliminates uneven grinding and over-grinding problems, significantly improving beveling accuracy and subsequent welding quality, while also enhancing the automation, intelligence, and efficiency of the grinding operation.

[0007] The present invention employs the following technical solution.

[0008] A robot-based adaptive grinding control method for pipe beveling includes:

[0009] Step 1: Before grinding the pipe bevel, calibrate the equipment and preset the standard parameters;

[0010] Step 2: While the grinding robot is grinding the pipe to be ground, perform real-time acquisition of multi-dimensional working parameters;

[0011] Step 3: The control system performs parameter calculations using a multivariable coupled adaptive grinding control model;

[0012] Step 4: The control system generates the grinding trajectory of the grinding head for adaptive grinding.

[0013] Furthermore, step 1 specifically includes: before the pipe beveling operation, completing the collaborative calibration of the grinding robot, speed sensor, line laser profile scanner, six-dimensional force sensor and laser rangefinder, that is, connecting the programmable logic controller of the grinding robot with the speed sensor, line laser profile scanner, six-dimensional force sensor and laser rangefinder; according to the specifications of the pipe to be processed, preset the beveling standard parameters in the programmable logic controller of the grinding robot, which is the control system.

[0014] Furthermore, in step 1, the preset bevel standard parameters include the standard bevel grinding allowance. Standard bevel angle Reference grinding pressure Reference grinding speed Reference feed rate and initial thickness of the mold .

[0015] Furthermore, step 2 specifically includes: fixing the pipe to be ground to the tooling fixture, the grinding robot driving the grinding head to the starting position of the beveling operation, and starting multiple devices to simultaneously collect multi-dimensional working parameters.

[0016] Furthermore, in step 2, the method of simultaneously collecting multi-dimensional working parameters from multiple devices specifically includes: scanning the entire bevel area using a line laser profile scanner to obtain the actual grinding allowance at each point. and actual bevel angle The data is then transmitted to the control system; the tangential resistance of the grinding head is collected in real time by a six-dimensional force sensor at the end of the grinding robot. The data is then transmitted to the control system; the real-time thickness of the mold is collected in real time by a laser rangefinder. The data is then transmitted to the control system; the real-time feed speed is collected by the speed sensor and the servo encoder of the grinding robot. and the real-time rotation speed of the grinding head And transmit it to the control system.

[0017] Furthermore, step 3 specifically includes:

[0018] Three sets of coupled calculation formulas are constructed for a multivariable coupled adaptive grinding control model, which are used to solve for the bevel grinding correction coefficient, optimal grinding pressure, optimal feed rate and optimal grinding speed.

[0019] Furthermore, in step 3, the three sets of coupled calculation formulas include the comprehensive correction coefficient formula for the bevel condition, which is:

[0020] ;

[0021] In this formula, The comprehensive correction coefficient for the bevel condition at the i-th grinding point; This represents the actual amount of material to be polished at the i-th polishing point. Preset grinding allowance as per standard; The actual bevel angle at the i-th grinding point; The standard bevel angle is preset; This represents the real-time thickness of the mold. Let be the initial thickness of the mold, and max() be the MAX function.

[0022] Furthermore, in step 3, the three sets of coupled calculation formulas also include an adaptive optimal grinding pressure formula, which is:

[0023] ;

[0024] In this formula, To determine the optimal grinding pressure for the grinding head in real time; Use the benchmark grinding pressure; The comprehensive correction coefficient for the bevel condition at the i-th grinding point; To reduce the tangential resistance of the grinding head; The tangential resistance is preset for standard operating conditions.

[0025] Furthermore, in step 3, the three sets of coupled calculation formulas also include an adaptive dynamic grinding parameter coupling formula, which is:

[0026] ;

[0027] In this formula, The optimal grinding feed speed for the grinding head; β is the base feed rate; β is the feed rate adjustment index; The optimal grinding head speed for grinding; γ is the reference grinding speed; γ is the speed adjustment index.

[0028] Furthermore, step 4 specifically includes:

[0029] Before grinding the pipe bevel, the control system uses point cloud data of the pipe bevel acquired and transmitted by a line laser profile scanner. It then applies a cubic B-spline curve fitting algorithm to the point cloud data to generate the grinding trajectory of the grinding head. Finally, it combines the calculated real-time optimal grinding pressure at each grinding point along the grinding trajectory. Optimal feed rate and optimal grinding speed The grinding pressure, feed rate, and grinding speed of the grinding head of the grinding robot at a specific grinding point are adjusted in real time to achieve the optimal grinding pressure at that point. Optimal feed rate and optimal grinding speed .

[0030] The beneficial effects of the present invention are as follows, compared with the prior art:

[0031] This invention completely overcomes the inherent defects of existing pipe beveling and grinding technologies. Compared with manual grinding and traditional robot grinding with fixed parameters, it has significant technical advantages in multiple dimensions. The specific technical effects are as follows:

[0032] Completely eliminating reliance on manual labor, this invention achieves highly stable and controllable grinding quality. The entire process utilizes robotic automated adaptive grinding, eliminating the need for manual hand-held grinding, parameter calibration, and defect identification. It completely avoids quality fluctuations caused by differences in human skill, worker fatigue, and operational errors. Grinding quality is determined by the equipment's precise algorithms and sensor-collected data, achieving standardized and homogeneous bevel grinding production and completely solving the problem of poor quality consistency in traditional processes. It eliminates uneven grinding and over-grinding defects, significantly improving bevel forming accuracy. Through a multivariate coupled adaptive model, it addresses the 360° all-around bevel grinding process. Differentiated precision grinding is achieved by addressing unevenness and angular deviations at specific points. Excess material is precisely removed from raised areas, while the substrate is precisely protected in recessed areas. Automatic parameter compensation is provided after the grinding tool wears down. This significantly optimizes subsequent welding quality, reduces pipeline operation risks, and ensures uniform weld fusion and full filler material during welding. It completely eliminates welding quality problems such as incomplete fusion, porosity, slag inclusions, and cracks caused by defects in beveling. The tensile strength, impact toughness, and sealing performance of the welded joints are significantly improved, reducing the rework rate of pipeline welding and effectively extending the service life of oil and gas, chemical, and municipal pipelines. This invention addresses safety hazards such as pipe leaks and bursts, and is suitable for the stringent construction standards of high-pressure and long-distance pipelines. It boasts exceptional adaptability and a wide range of applications, adapting to various pipe materials and handling complex unstructured conditions such as pipe cutting deformation, uneven end faces, inconsistent oxide layer thickness, and progressive wear of grinding tools. It eliminates the need for reprogramming and teaching for different pipes and conditions, making its versatility and flexibility far superior to traditional grinding equipment. Furthermore, it significantly improves operational efficiency and safety while reducing production costs. This invention achieves automated operation without human intervention, improving the efficiency of single-pipe beveling compared to manual grinding and surpassing traditional robotic grinding methods. The fixed-track grinding process has also been improved, significantly reducing the intensity of manual labor and labor costs. At the same time, the entire process is unmanned, completely avoiding operational safety risks such as grinding dust, noise, and mechanical injuries, improving the working environment at the construction site, and adapting to the standardized production needs of modern industrial assembly lines. This invention adopts a high-frequency real-time correction mechanism to dynamically monitor the grinding conditions and equipment status throughout the process, continuously optimizing grinding parameters. It can effectively offset the cumulative interference from progressive wear of grinding tools, minor differences in pipeline conditions, and slight errors in equipment operation, ensuring the grinding accuracy and consistency of the equipment during long-term continuous operation, without any operational attenuation issues, and is suitable for batch and routine industrial production.

[0033] In summary, this invention, through an adaptive coupling control method, with rigorous physical logic and precise algorithmic regulation, completely solves the technical bottlenecks of existing pipe beveling grinding quality, such as reliance on manual labor, uneven grinding, over-grinding, and poor welding quality. It also features high precision, high stability, high efficiency, and high adaptability. Attached Figure Description

[0034] Figure 1This is a partial flowchart illustrating the principle of the robot-based adaptive grinding control method for pipe beveling in this invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, other embodiments obtained by those skilled in the art without creative effort are all within the protection scope of this invention.

[0036] like Figure 1 As shown, this invention proposes a robot-based adaptive grinding control method for pipe beveling, comprising the following steps:

[0037] Step 1: Before grinding the pipe bevel, calibrate the equipment and preset the standard parameters;

[0038] In a preferred but non-limiting embodiment of the present invention, step 1 specifically includes: before the pipe beveling and grinding operation, completing the collaborative calibration of the grinding robot, speed sensor, line laser profile scanner, six-dimensional force sensor, and laser rangefinder, that is, the programmable logic controller of the grinding robot is connected to the speed sensor, line laser profile scanner, six-dimensional force sensor, and laser rangefinder, and the coordinate systems of the line laser profile scanner, six-dimensional force sensor, and laser rangefinder are unified with the robot base coordinate system of the grinding robot to eliminate acquisition deviation and motion deviation; according to the specifications of the pipe to be processed (pipe diameter, wall thickness, preset beveling angle or standard grinding allowance, etc.), the standard beveling parameters are preset in the programmable logic controller of the grinding robot, which serves as the control system.

[0039] In a preferred but non-limiting embodiment of the present invention, in step 1, the preset bevel standard parameters include the standard bevel grinding allowance. Standard bevel angle Reference grinding pressure Reference grinding speed Reference feed rate and initial thickness of the mold .

[0040] It should be noted that the standard bevel grinding allowance The standard nominal grinding thickness that needs to be removed by grinding after pipe beveling is the target benchmark value for controlling the amount of material removed by grinding at a single point in this invention; standard bevel angle. The nominal angle of the standard weld bevel between the bevel of the pipe end face and the radially perpendicular plane of the pipe is the optimal bevel forming angle specified in the welding process; reference grinding pressure. The rated reference grinding pressure for a standard flat bevel is the standard no-load reference force control parameter for robotic grinding; the reference grinding speed... The rated reference grinding speed and reference feed rate of the grinding head of the grinding robot under standard working conditions. The standard reference feed rate for the grinding head of the grinding robot to travel along the bevel profile; initial thickness of the grinding wheel. The initial effective grinding thickness for a brand new, unused grinding head of a grinding robot.

[0041] Step 2: While the grinding robot is grinding the pipe to be ground, perform real-time acquisition of multi-dimensional working parameters;

[0042] In a preferred but non-limiting embodiment of the present invention, step 2 specifically includes: fixing the pipe to be ground to the tooling fixture, the grinding robot driving the grinding head to move to the starting position of the beveling operation, and starting multiple devices to simultaneously collect multi-dimensional working condition parameters.

[0043] In a preferred but non-limiting embodiment of the present invention, step 2, the method for simultaneously acquiring multi-dimensional working condition parameters using multiple devices, specifically includes: scanning the entire bevel area using a line laser profile scanner to obtain the actual grinding allowance at each point. and actual bevel angle The data is then transmitted to the control system; the tangential resistance of the grinding head is collected in real time by a six-dimensional force sensor at the end of the grinding robot. The data is then transmitted to the control system; the real-time thickness of the grinding wheel (grinding head) is collected in real time via a laser rangefinder. The data is then transmitted to the control system; the real-time feed speed is collected by the speed sensor and the servo encoder of the grinding robot. and the real-time rotation speed of the grinding head And transmit it to the control system.

[0044] Step 3: The control system performs parameter calculations using a multivariable coupled adaptive grinding control model;

[0045] In a preferred but non-limiting embodiment of the present invention, step 3 specifically includes:

[0046] This invention constructs three sets of coupled calculation formulas for a multivariable coupled adaptive grinding control model, which are used to solve for the bevel grinding correction coefficient, optimal grinding pressure, optimal feed speed and optimal grinding speed, thereby achieving dynamic adaptive control of multiple parameters.

[0047] In a preferred but non-limiting embodiment of the present invention, in step 3, the three sets of coupled calculation formulas include a comprehensive correction coefficient formula for the bevel condition, which is:

[0048] ;

[0049] In this formula, The comprehensive correction coefficient for the bevel condition at the i-th grinding point; This represents the actual amount of material to be polished at the i-th polishing point. Preset grinding allowance as per standard; The actual bevel angle at the i-th grinding point; The standard bevel angle is preset; The real-time thickness of the abrasive (grinding head); Let be the initial thickness of the mold, and max() be the MAX function.

[0050] It should be noted that the first term of the comprehensive correction coefficient formula for beveling conditions... This is a grinding allowance correction item, which adapts to bevel unevenness deviations. > (Bevel protrusion, excessive allowance), this value is greater than 1, increase the correction factor, and increase the grinding intensity; when < (Bevel concavity, insufficient allowance) This value is less than 1, so reduce the correction factor, decrease the grinding intensity, and accurately match the material removal requirements of different grinding points; the second term of the comprehensive correction factor formula for bevel conditions. This is the third term in the formula for the comprehensive correction factor for bevel angle deviation, used to prevent bevel distortion caused by forced grinding at angle deviation points and to ensure the regularity of the bevel angle. This is a correction term for grinding wheel wear; the more severe the grinding wheel wear ( The smaller the value, the smaller the correction coefficient, which compensates for the decrease in grinding efficiency and insufficient grinding force after the grinding wheel wears out, and avoids uneven grinding caused by grinding wheel wear; the actual grinding allowance is the thickness to be ground.

[0051] Furthermore, the comprehensive correction coefficient formula for beveling conditions breaks through the limitations of single-parameter correction in existing technologies. It couples the three major interference variables—beveling allowance, angle deviation, and grinding tool wear—into a unified correction coefficient, achieving coordinated control of multiple working condition variables. This solves the problem that single-dimensional control cannot adapt to complex composite working conditions. The correction logic is consistent with the actual grinding physical process, with no blind spots in mechanical control.

[0052] In a preferred but non-limiting embodiment of the present invention, step 3 further includes an adaptive optimal grinding pressure formula for the three sets of coupled calculation formulas, which is:

[0053] ;

[0054] In this formula, To determine the optimal grinding pressure for the grinding head in real time; Use the benchmark grinding pressure; The comprehensive correction coefficient for the bevel condition at the i-th grinding point; To reduce the tangential resistance of the grinding head; The tangential resistance is preset for standard operating conditions.

[0055] It should be noted that the tangential resistance is preset under standard operating conditions. This refers to the rated grinding tangential resistance under standard reference grinding conditions. Standard reference conditions include: a regular pipe bevel morphology, no unevenness or dents, no thick oxide layer, brand new unworn grinding tools, reference grinding pressure, and reference feed rate. The rated tangential grinding resistance generated by the grinding head when grinding the pipe base material under the specified parameters.

[0056] Furthermore, the adaptive optimal grinding pressure formula, based on the benchmark grinding pressure, incorporates a comprehensive working condition correction coefficient to achieve basic correction of the bevel morphology and grinding tool condition. Simultaneously, it introduces a square root correction term for tangential resistance. During grinding, in areas with bevel protrusions, thick oxide layers, and high material hardness, the tangential resistance... Significantly increased, the resistance correction effect is amplified through the square root, and the grinding pressure is moderately increased to ensure thorough removal of excess material and oxide layer; areas with smooth bevels and uniform material are achieved. near The pressure is finely adjusted to ensure smooth grinding. The square root model is used instead of the nonlinear model to avoid sudden pressure rises and falls caused by abrupt changes in resistance. This prevents excessive pressure fluctuations from causing scratches on the bevel and damage to the substrate, and adapts to the flexible mechanical properties of the grinding process.

[0057] Furthermore, the adaptive optimal grinding pressure formula realizes three-dimensional adaptive pressure control based on morphological conditions, mold status, and real-time mechanical feedback. Unlike the existing fixed pressure and single force control feedback modes, the pressure adjustment is smooth and precise, ensuring thorough grinding of defective areas while preventing over-grinding of normal areas, thus solving the problem of uneven grinding from a mechanical perspective.

[0058] In a preferred but non-limiting embodiment of the present invention, in step 3, the three sets of coupling calculation formulas further include an adaptive dynamic grinding parameter coupling formula, which is:

[0059] ;

[0060] In this formula, The optimal grinding feed speed for the grinding head; β is the base feed rate; β is the feed rate adjustment index; The optimal grinding head speed for grinding; γ is the reference grinding speed; γ is the speed adjustment index.

[0061] It should be noted that the value range of the feed rate adjustment index β in the adaptive dynamic grinding parameter coupling formula can be 1.2~1.85, and the value range of the rotation speed adjustment index γ can be 0.3~0.6. The principle for their selection is as follows: the harder the material and the higher the removal difficulty, the larger the values ​​of β and γ, which improves the sensitivity of parameter adjustment response and ensures that defects in hard materials can be completely removed by grinding; the softer the material and the easier it is to over-grind the substrate, the smaller the values ​​of β and γ, which weakens the parameter adjustment range and avoids substrate scratches, over-grinding and grinding ripple defects caused by sudden parameter changes.

[0062] Furthermore, in the adaptive dynamic grinding parameter coupling formula, For the residual inverse ratio adjustment term, when For larger (protruding defects), reduce the feed rate and extend the grinding contact time to ensure complete removal of excess material; when A smaller value (for concave areas) increases the feed rate, shortens the grinding time, and avoids over-grinding. A smaller value for the exponent β weakens the abrupt changes in feed rate, ensuring smooth grinding motion and avoiding bevel ripple defects caused by speed fluctuations. The rotational speed formula achieves bidirectional coupling control of pressure and working conditions, and is the comprehensive correction coefficient for the bevel working conditions at the i-th grinding point. Increase the rotation speed (requiring intensive polishing) by using a reciprocal exponential term, while simultaneously matching the optimal polishing pressure to achieve a high-pressure, high-speed intensive polishing mode; when Reduce (requires weakening grinding), lower the speed and pressure to form a low-pressure, low-speed lightweight grinding mode. The exponential γ is adapted to the sensitivity adjustment of the speed, matching the grinding characteristics of pipes of different materials, avoiding the problems of excessive speed burning the substrate and excessive speed resulting in low grinding efficiency.

[0063] Furthermore, the adaptive dynamic grinding parameter coupling formula realizes the dynamic coupling and linkage of multiple parameters such as grinding pressure, rotation speed, feed speed and working condition morphology, breaking the defects of independent adjustment and mismatch of existing technical parameters. All parameters are synchronously adapted to the real-time working conditions, the grinding parameter matching accuracy is greatly improved, and the uniformity and consistency of bevel grinding across the entire domain are significantly optimized.

[0064] Step 4: The control system generates the grinding trajectory of the grinding head for adaptive grinding.

[0065] In a preferred but non-limiting embodiment of the present invention, step 4 specifically includes:

[0066] Before grinding the pipe bevel, the control system uses point cloud data of the pipe bevel acquired and transmitted by a line laser profile scanner. It then applies a cubic B-spline curve fitting algorithm to the point cloud data to generate the grinding trajectory of the grinding head. Finally, it combines the calculated real-time optimal grinding pressure at each grinding point along the grinding trajectory. Optimal feed rate and optimal grinding speed The grinding pressure, feed rate, and grinding speed of the grinding head of the grinding robot at a specific grinding point are adjusted in real time to achieve the optimal grinding pressure at that point. Optimal feed rate and optimal grinding speed .

[0067] It should be noted that the grinding path of the grinding head is a collection of all grinding points.

[0068] Furthermore, when For larger (protruding defects), reduce the feed rate and extend the grinding contact time to ensure complete removal of excess material; when A smaller value (for concave areas) increases the feed rate, shortens the grinding time, and avoids over-grinding. A smaller value for the exponent β weakens the abrupt changes in feed rate, ensuring smooth grinding motion and avoiding bevel ripple defects caused by speed fluctuations. The rotational speed formula achieves bidirectional coupling control of pressure and working conditions, and is the comprehensive correction coefficient for the bevel working conditions at the i-th grinding point. Increase the rotation speed (requiring intensive polishing) by using a reciprocal exponential term, while simultaneously matching the optimal polishing pressure to achieve a high-pressure, high-speed intensive polishing mode; when Reduce (requires weakened grinding), lower the rotation speed and pressure to form a low-pressure, low-speed lightweight grinding mode. The exponential γ mode is used to adjust the rotation speed sensitivity, matching the grinding characteristics of different pipe materials, avoiding the problems of excessively high rotation speeds causing substrate ablation and excessively low rotation speeds resulting in low grinding efficiency; addressing the issue of worn grinding tools ( (Reduce) and automatically weaken the adjustment range of grinding parameters to compensate for the reduction in grinding efficiency caused by grinding tool wear, and ensure consistent grinding across the entire area.

[0069] This invention's multivariable coupled adaptive control model integrates three major interference factors: bevel morphology deviation, grinding tool wear, and grinding mechanical feedback. Unlike existing single vision or single force control technologies, it achieves full-dimensional adaptation to complex unstructured bevel conditions, fundamentally solving the problems of uneven grinding and over-grinding. Through corresponding formulas, it achieves synchronous optimization of grinding pressure, rotation speed, and feed rate, with parameter adjustments matching and coordinating with each other to avoid grinding defects caused by single parameter adjustments. The control logic conforms to the actual physical grinding laws, with no blind spots or lags in control. Based on existing mature industrial sensors, it achieves real-time parameter acquisition across the entire domain, high-frequency closed-loop iteration, and requires no manual intervention or pre-set complex trajectories. It automatically adapts to different pipe specifications, different initial bevel defects, and different grinding tool wear states, completely eliminating the dependence of grinding quality on manual skills.

[0070] The beneficial effects of the present invention are as follows, compared with the prior art:

[0071] This invention completely overcomes the inherent defects of existing pipe beveling and grinding technologies. Compared with manual grinding and traditional robot grinding with fixed parameters, it has significant technical advantages in multiple dimensions. The specific technical effects are as follows:

[0072] Completely eliminating reliance on manual labor, this invention achieves highly stable and controllable grinding quality. The entire process utilizes robotic automated adaptive grinding, eliminating the need for manual hand-held grinding, parameter calibration, and defect identification. It completely avoids quality fluctuations caused by differences in human skill, worker fatigue, and operational errors. Grinding quality is determined by the equipment's precise algorithms and sensor-collected data, achieving standardized and homogeneous bevel grinding production and completely solving the problem of poor quality consistency in traditional processes. It eliminates uneven grinding and over-grinding defects, significantly improving bevel forming accuracy. Through a multivariate coupled adaptive model, it addresses the 360° all-around bevel grinding process. Differentiated precision grinding is achieved by addressing unevenness and angular deviations at specific points. Excess material is precisely removed from raised areas, while the substrate is precisely protected in recessed areas. Automatic parameter compensation is provided after the grinding tool wears down. This significantly optimizes subsequent welding quality, reduces pipeline operation risks, and ensures uniform weld fusion and full filler material during welding. It completely eliminates welding quality problems such as incomplete fusion, porosity, slag inclusions, and cracks caused by defects in beveling. The tensile strength, impact toughness, and sealing performance of the welded joints are significantly improved, reducing the rework rate of pipeline welding and effectively extending the service life of oil and gas, chemical, and municipal pipelines. This invention addresses safety hazards such as pipe leaks and bursts, and is suitable for the stringent construction standards of high-pressure and long-distance pipelines. It boasts exceptional adaptability and a wide range of applications, adapting to various pipe materials and handling complex unstructured conditions such as pipe cutting deformation, uneven end faces, inconsistent oxide layer thickness, and progressive wear of grinding tools. It eliminates the need for reprogramming and teaching for different pipes and conditions, making its versatility and flexibility far superior to traditional grinding equipment. Furthermore, it significantly improves operational efficiency and safety while reducing production costs. This invention achieves automated operation without human intervention, improving the efficiency of single-pipe beveling compared to manual grinding and surpassing traditional robotic grinding methods. The fixed-track grinding process has also been improved, significantly reducing the intensity of manual labor and labor costs. At the same time, the entire process is unmanned, completely avoiding operational safety risks such as grinding dust, noise, and mechanical injuries, improving the working environment at the construction site, and adapting to the standardized production needs of modern industrial assembly lines. This invention adopts a high-frequency real-time correction mechanism to dynamically monitor the grinding conditions and equipment status throughout the process, continuously optimizing grinding parameters. It can effectively offset the cumulative interference from progressive wear of grinding tools, minor differences in pipeline conditions, and slight errors in equipment operation, ensuring the grinding accuracy and consistency of the equipment during long-term continuous operation, without any operational attenuation issues, and is suitable for batch and routine industrial production.

[0073] It should be recognized that embodiments of the present invention may be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable storage medium.

[0074] The method can be implemented using standard programming techniques, including a non-transitory computer-readable storage medium configured with a computer program in the computer program, wherein the storage medium is configured such that the computer operates in a specific and predefined manner.

[0075] Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system; however, if required, the program can be implemented in assembly or machine language.

[0076] In any case, the language can be a compiled or interpreted language.

[0077] Furthermore, for this purpose, the program can run on a programmed application-specific integrated circuit.

[0078] The processes described herein (or variations and / or combinations thereof) can be executed under the control of one or more computer systems configured with executable instructions, and can be implemented by hardware or a combination thereof as code (e.g., executable instructions, one or more computer programs, or one or more applications) that commonly executes on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.

[0079] Furthermore, the method can be implemented in any suitable computing platform, including but not limited to personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, standalone or integrated computer platforms, or in communication with charged particle tools or other imaging devices.

[0080] Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether portable or integrated into a computing platform, such as a hard disk, optical read and / or write storage medium, RAM, ROM, etc., such that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the processes described herein.

[0081] Furthermore, machine-readable code, or parts thereof, can be transmitted via wired or wireless networks.

[0082] When such media includes instructions or programs that combine with a microprocessor or other data processor to implement the steps described above, the invention described herein includes these and other different types of non-transitory computer-readable storage media.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A robot-based adaptive grinding control method for pipe beveling, characterized in that, include: Step 1: Before grinding the pipe bevel, calibrate the equipment and preset the standard parameters; Step 2: While the grinding robot is grinding the pipe to be ground, perform real-time acquisition of multi-dimensional working parameters; Step 3: The control system performs parameter calculations using a multivariable coupled adaptive grinding control model; Step 4: The control system generates the grinding trajectory of the grinding head for adaptive grinding.

2. The robot-based adaptive grinding control method for pipe beveling according to claim 1, characterized in that, Step 1 specifically includes: before the pipe beveling operation, completing the collaborative calibration of the grinding robot, speed sensor, line laser profile scanner, six-dimensional force sensor and laser rangefinder, that is, connecting the programmable logic controller of the grinding robot with the speed sensor, line laser profile scanner, six-dimensional force sensor and laser rangefinder; according to the specifications of the pipe to be processed, preset the beveling standard parameters in the programmable logic controller of the grinding robot, which is the control system.

3. The robot-based adaptive grinding control method for pipe beveling according to claim 2, characterized in that, In step 1, the preset bevel standard parameters include the standard bevel grinding allowance. Standard bevel angle Reference grinding pressure Reference grinding speed Reference feed rate and initial thickness of the mold .

4. The robot-based adaptive grinding control method for pipe beveling according to claim 3, characterized in that, Step 2 specifically includes: fixing the pipe to be ground to the tooling fixture, the grinding robot driving the grinding head to the starting position of the beveling operation, and starting multiple devices to simultaneously collect multi-dimensional working parameters.

5. The robot-based adaptive grinding control method for pipe beveling according to claim 4, characterized in that, In step 2, the method of simultaneously collecting multi-dimensional working parameters from multiple devices is initiated, specifically including: scanning the entire bevel area with a line laser profile scanner to obtain the actual grinding allowance at each point. and actual bevel angle The data is then transmitted to the control system; the tangential resistance of the grinding head is collected in real time by a six-dimensional force sensor at the end of the grinding robot. The data is then transmitted to the control system; the real-time thickness of the mold is collected in real time by a laser rangefinder. The data is then transmitted to the control system; the real-time feed speed is collected by the speed sensor and the servo encoder of the grinding robot. and the real-time rotation speed of the grinding head And transmit it to the control system.

6. The robot-based adaptive grinding control method for pipe beveling according to claim 5, characterized in that, Step 3 specifically includes: Three sets of coupled calculation formulas are constructed for a multivariable coupled adaptive grinding control model, which are used to solve for the bevel grinding correction coefficient, optimal grinding pressure, optimal feed rate and optimal grinding speed.

7. The robot-based adaptive grinding control method for pipe beveling according to claim 6, characterized in that, In step 3, the three sets of coupled calculation formulas include the comprehensive correction coefficient formula for the bevel condition, which is: ； In this formula, The comprehensive correction coefficient for the bevel condition at the i-th grinding point; This represents the actual amount of material to be polished at the i-th polishing point. Preset grinding allowance as per standard; The actual bevel angle at the i-th grinding point; The standard bevel angle is preset; This represents the real-time thickness of the mold. Let be the initial thickness of the mold, and max() be the MAX function.

8. The robot-based adaptive grinding control method for pipe beveling according to claim 7, characterized in that, In step 3, the three sets of coupled calculation formulas also include an adaptive optimal grinding pressure formula, which is: ； In this formula, To determine the optimal grinding pressure for the grinding head in real time; Use the benchmark grinding pressure; The comprehensive correction coefficient for the bevel condition at the i-th grinding point; To reduce the tangential resistance of the grinding head; The tangential resistance is preset for standard operating conditions.

9. The robot-based adaptive grinding control method for pipe beveling according to claim 8, characterized in that, In step 3, the three sets of coupling calculation formulas also include an adaptive dynamic grinding parameter coupling formula, which is: ； In this formula, The optimal grinding feed speed for the grinding head; β is the base feed rate; β is the feed rate adjustment index; The optimal grinding head speed for grinding; γ is the reference grinding speed; γ is the speed adjustment index.

10. The robot-based adaptive grinding control method for pipe beveling according to claim 9, characterized in that, Step 4 specifically includes: Before grinding the pipe bevel, the control system uses point cloud data of the pipe bevel acquired and transmitted by a line laser profile scanner. It then applies a cubic B-spline curve fitting algorithm to the point cloud data to generate the grinding trajectory of the grinding head. Finally, it combines the calculated real-time optimal grinding pressure at each grinding point along the grinding trajectory. Optimal feed rate and optimal grinding speed The grinding pressure, feed rate, and grinding speed of the grinding head of the grinding robot at a specific grinding point are adjusted in real time to achieve the optimal grinding pressure at that point. Optimal feed rate and optimal grinding speed .

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