A visual positioning and welding forming method and system for subway segment reinforcement cages

Abstract

This invention relates to a visual positioning and welding forming method and system for subway tunnel segment rebar cages, relating to the field of rebar cage manufacturing. The method includes: Step 100: acquiring a material image; Step 101: identifying the material curvature from the material image and retrieving dimensional requirements; Step 102: determining the installation position based on the material curvature and dimensional requirements; Step 103: determining the installation sequence based on the installation position and determining the stacking sequence from the material image based on the installation position; Step 104: generating a retrieval stroke based on the installation sequence and stacking sequence; Step 105: generating and sending a rebar retrieval command based on the retrieval stroke. This application improves the welding efficiency of tunnel segment rebar cages, achieving rapid positioning and stable welding of rebars through visual technology.

Description

Technical Field

[0001] This invention relates to the field of steel cage manufacturing, and in particular to a visual positioning welding forming method and system for subway segment steel cages. Background Technology

[0002] The segment reinforcement cage is the internal steel reinforcement skeleton of precast reinforced concrete shield tunnel segments. It is used to form segments after bonding with concrete and assemble them into the permanent lining structure of the tunnel.

[0003] In existing technologies, segment reinforcement cages are generally welded together from circumferential main bars, longitudinal distribution bars, stirrups, positioning bars, and accessories such as pre-embedded lifting rings and bolt sleeves. The removal and installation of the reinforcement bars mostly rely on manual positioning, and the segment reinforcement cage is generally in the shape of an arc plate.

[0004] The steel bars that make up the segment reinforcement cage are numerous, and the length and curvature deviations of different steel bars are small. This makes it difficult for workers to quickly select the required steel bars from the piled materials, resulting in low welding efficiency of the segment reinforcement cage. Summary of the Invention

[0005] To improve the welding efficiency of subway tunnel segment reinforcement cages and to quickly locate and stabilize the welded reinforcement bars using visual technology, this invention provides a visual positioning welding forming method and system for subway tunnel segment reinforcement cages.

[0006] In a first aspect, the present invention provides a method for visual positioning and welding of steel cages for subway tunnel segments, employing the following technical solution: A method for visual positioning and welding of steel reinforcement cages for subway tunnel segments includes: Step 100: Acquire material images; Step 101: Identify the material curvature from the material image and retrieve the dimensional requirements; Step 102: Determine the installation location based on the material's curvature and dimensional requirements; Step 103: Determine the installation sequence based on the installation location, and determine the stacking sequence from the material image based on the installation location; Step 104: Generate a fetching process by combining the installation sequence and the stacking sequence; Step 105: Generate and send a rebar retrieval instruction based on the retrieval process.

[0007] By adopting the above technical solution, visual technology is used to identify the curvature of materials in material images and combine it with size requirements to accurately determine the installation position, installation sequence and stacking sequence, and generate picking stroke and picking instructions, thereby realizing the automation and precision of steel bar picking, avoiding installation deviations caused by material misalignment and sequence disorder, and improving the welding efficiency of the segment steel cage.

[0008] Optional, also includes: Step 106: Determine the welding points according to the installation sequence and installation location; Step 107: Determine welding parameters based on the welding points; Step 108: Analyze the welding parameters to determine the heat input; Step 109: Determine the welding angle based on the heat input, and identify the welding surface angle from the material image based on the welding point location; Step 110: Determine the welding torch angle by combining the welding angle and the welding surface angle; Step 111: In response to the generation and transmission of the welding torch angle and welding point, a rebar welding command is sent.

[0009] By adopting the above technical solution, the welding point is determined based on the installation sequence and installation position. Then, the heat input is analyzed in conjunction with the welding parameters, and the welding gun angle is determined in conjunction with the welding surface angle before the welding command is issued. This ensures that the welding gun angle is accurately matched with the welding point and heat input, reduces defects such as incomplete fusion and undercut in the weld, and improves the welding quality of the steel cage of the tunnel segment.

[0010] Optional, also includes: Step 112: When the heat input is greater than the preset deformation threshold, the material length is identified from the material image based on the heat input. Step 113: Determine the degree of deformation based on the material length and heat input; Step 114: Determine the clamping force based on the degree of deformation, and determine the clamping number based on the welding point; Step 115: In response to the clamping force and clamping number, generate and send a clamping command for the tire carcass.

[0011] By adopting the above technical solution, when the heat input is too large, the length of the material is visually identified, and the degree of deformation is determined in combination with the heat input. Then, the clamping force of the jig is adjusted. In this way, the deformation risk is predicted in advance and the clamping force is precisely controlled to constrain the thermal expansion of the steel bars. This reduces the deformation of the arc-shaped steel cage due to excessive heat input, such as warping and shrinkage, and improves the welding quality of the segment steel cage.

[0012] Optionally, a real-time welding method may also be included, the real-time welding method comprising: Step 200: Acquire a thermal image in response to the steel bar welding command; Step 201: Determine the actual heat from the thermal image based on the welding point location; Step 202: Calculate the difference between the actual heat and the heat input, and define it as the heat deviation; Step 203: Determine the calibration angle based on the heat deviation; Step 204: Update the welding torch angle in response to the calibration angle.

[0013] By adopting the above technical solution, heat images are collected in real time during welding to determine the actual heat, thereby calculating the heat deviation and selecting a suitable calibration angle to adjust the welding torch angle. This reduces the welding torch angle inaccuracy caused by heat input fluctuations during welding, and improves the welding quality of the segment reinforcement cage.

[0014] Optionally, the real-time welding method further includes: Step 205: Determine the heat range based on actual heat output; Step 206: Determine the range length based on the stated heat range; Step 207: Determine the thermal conductivity according to the length of the range; Step 208: Determine the conduction angle based on the thermal conductivity; Step 209: Update the welding torch angle in response to the transmission angle.

[0015] By adopting the above technical solution, the heat diffusion range can be identified from the thermal image, and the thermal conductivity can be evaluated according to the size of the heat range. Then, the appropriate conduction angle can be selected according to the thermal conductivity to adjust the welding gun angle, thereby reducing the situation of local heat accumulation caused by excessive thermal conductivity and improving the welding quality of the segment reinforcement cage.

[0016] Optionally, the real-time welding method further includes: Step 210: In response to the rebar welding command, acquire the rebar image and generate a rebar reference model by combining the material curvature and material length; Step 211: Identify the steel bar welding model from the steel bar image; Step 212: Compare the aforementioned steel reinforcement reference model and steel reinforcement welding model to determine the deformation distance; Step 213: Determine the deformation center and deformation rate based on the deformation distance; Step 214: Determine the fixed number according to the deformation center, and determine the clamping force according to the deformation rate; Step 215: Update the carcass clamping command based on the fixed number and clamping force.

[0017] By adopting the above technical solution, images of the reinforcing bars are collected during welding to generate a reinforcing bar welding model. Combined with the material curvature and length before welding, a reference model of the reinforcing bars is generated. By comparing the reinforcing bar welding model and the reinforcing bar reference model, the deformation distance of the reinforcing bars under welding is determined. Then, when the deformation distance is too large, the clamping force of the jig is increased, thereby offsetting the welding deformation in real time, reducing the over-standard size of the reinforcing cage caused by deformation accumulation, and improving the welding quality of the segment reinforcing cage.

[0018] Optionally, it also includes an arc control method, the arc control method comprising: Step 300: Acquire welding acoustic signature in response to the rebar welding command; Step 301: Identify the three frequency bands from the welding acoustic waveform; Step 302: Analyze the three frequency bands to determine the energy of the three frequencies; Step 303: Determine the proportion of the three frequencies based on the three-frequency energy; Step 304: Determine the percentage deviation based on the three frequency percentages; Step 305: Select the adjustment current according to the stated percentage deviation; Step 306: In response to the regulation current generation, an arc control command is sent.

[0019] By adopting the above technical solution, welding acoustic patterns are collected, three frequency bands are identified, the energy ratio of the three frequencies is analyzed to determine the deviation, and the current of the welding torch is adjusted. In this way, the degree of penetration of the steel bars can be indirectly monitored through acoustic pattern recognition, reducing weld defects caused by abnormal penetration and improving the welding quality of the steel cage of the tunnel segment.

[0020] Optionally, the arc control method further includes: Step 307: Determine the deviation sound segment based on the stated proportion deviation; Step 308: When the deviation sound segment is consistent with the preset high-frequency sound segment, extract the high-frequency sound pattern from the three-frequency sound segment; Step 309: Determine the high-frequency power spectrum based on the high-frequency acoustic signature; Step 310: Determine the peak power and average power from the high-frequency power spectrum; Step 311: Calculate the quotient of the peak power and the average power, and define it as the peak sharpness; Step 312: Determine the adjustment frequency based on the peak sharpness; Step 313: Update the arc control command in response to the adjusted frequency.

[0021] By adopting the above technical solution, when the energy proportion of the high-frequency sound band is too high, the high-frequency sound pattern is extracted, the power spectrum is analyzed to determine the peak sharpness, and then the frequency of the welding gun current is adjusted. In this way, the stability of the electric arc can be accurately identified through power spectrum analysis, reducing defects such as weld undercut and weld beads caused by high-frequency electric arc instability, and improving the welding quality of the steel cage of the tunnel segment.

[0022] Optionally, the arc control method further includes: Step 314: When the peak sharpness is greater than the preset peak threshold, determine the frequency peak based on the power peak value; Step 315: Extract the voiceprint frequency point from the high-frequency voiceprint in response to the frequency peak; Step 316: Determine the peak energy based on the voiceprint frequency point, and extract the high-frequency energy from the three-frequency energy; Step 317: Calculate the quotient of the peak energy and the high-frequency energy, and define it as the peak percentage; Step 318: Select the swing amplitude according to the peak percentage; Step 319: Update the rebar welding command in response to the swing amplitude.

[0023] By adopting the above technical solution, when the peak sharpness is too large, the peak frequency energy is extracted and compared with the total high-frequency energy to obtain the peak ratio. Based on this, the welding torch oscillation amplitude is selected, thereby quantifying the severity of porosity tendency through energy concentration and promoting bubble escape through graded intervention, thus achieving online suppression of porosity defects and improving the welding quality of the segment reinforcement cage.

[0024] Secondly, this application provides a visual positioning and welding forming system for subway tunnel segment reinforcement cages, which adopts the following technical solution: A visual positioning and welding forming system for subway segment reinforcement cages includes: The acquisition module is used to acquire material images; The memory is used to store the program for any of the above-mentioned methods for visual positioning and welding of subway segment steel cages; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

[0025] By adopting the above technical solution, visual technology is used to identify the curvature of materials in material images and combine it with size requirements to accurately determine the installation position, installation sequence and stacking sequence, and generate picking stroke and picking instructions, thereby realizing the automation and precision of steel bar picking, avoiding installation deviations caused by material misalignment and sequence disorder, and improving the welding efficiency of the segment steel cage.

[0026] In summary, this application includes at least one of the following beneficial technical effects: By using visual technology to identify the curvature of materials in material images and combining it with size requirements, the installation position, installation sequence and stacking sequence are accurately determined, and the picking stroke and picking instructions are generated, thereby realizing the automation and precision of steel bar picking, avoiding installation deviations caused by material misalignment and sequence disorder, and improving the welding efficiency of the steel cage of the tunnel segment. Welding points are determined based on the installation sequence and location. The heat input is analyzed in conjunction with welding parameters, and the welding gun angle is determined in conjunction with the welding surface angle before welding commands are issued. This ensures that the welding gun angle is accurately matched with the welding point and heat input, reducing defects such as incomplete fusion and undercut, and improving the welding quality of the steel cage of the tunnel segment. When the heat input is too large, the length of the material is visually identified and the degree of deformation is determined in combination with the heat input. Then, the clamping force of the jig is adjusted. By predicting the deformation risk in advance and accurately controlling the clamping force, the steel bars are constrained by thermal expansion. This reduces the deformation of the arc-shaped steel cage due to excessive heat input, such as warping and shrinkage, and improves the welding quality of the segment steel cage. Attached Figure Description

[0027] Figure 1 This is a flowchart of a visual positioning and welding method for subway tunnel segment reinforcement cages; Figure 2 This is a flowchart of the real-time welding method; Figure 3 This is a flowchart of the arc control method. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0029] This application discloses a method and system for visual positioning and welding of steel reinforcement cages for subway tunnel segments.

[0030] Reference Figure 1 A method for visual positioning and welding of steel reinforcement cages for subway tunnel segments, comprising: Step 100: Acquire material images.

[0031] Material images refer to panoramic images containing the steel bars (materials) to be retrieved, clearly showing the stacking status, outline, and curvature characteristics of the steel bars. Material images can be acquired through visual sensors, and the acquisition method is selected by the staff according to the actual situation.

[0032] Step 101: Identify the material curvature from the material image and retrieve the size requirements.

[0033] Material curvature refers to the degree of curvature of each steel bar, that is, the curvature value of the steel bar axis deviating from the straight line. Material curvature can be determined by image recognition technology. The method of material curvature identification is common knowledge in the field.

[0034] Size requirements refer to the design dimensions of the steel cage for subway segments, including the length of the main reinforcement bars, the spacing of the stirrups, the curvature of the steel cage, and the inner and outer diameters, which can be preset by the staff according to the requirements.

[0035] Step 102: Determine the installation location based on the material's curvature and size requirements.

[0036] The installation position refers to the pre-set fixed position of the reinforcing bar on the curved support frame, that is, the three-dimensional coordinates that the reinforcing bar needs to achieve after installation. It can be calculated by matching the material curvature and size requirements. The installation position is common knowledge to those in the field.

[0037] Step 103: Determine the installation sequence based on the installation location, and determine the stacking sequence from the material image based on the installation location.

[0038] The installation sequence refers to the order in which the reinforcing bars are installed. It can be determined based on the spatial distribution of the installation location and the assembly logic of the reinforcing cage (e.g., installing the main bars first and then the stirrups, or installing the outer arc reinforcing bars first and then the inner arc reinforcing bars). The method for determining the installation sequence is common knowledge to those skilled in the art.

[0039] The stacking sequence refers to the stacking order of the steel bars to be retrieved in the material storage area. It can be determined by image recognition technology from the number of stacked layers and the distribution of positions of the steel bars in the material image. The method for determining the stacking sequence is common knowledge to those in the field.

[0040] Step 104: Generate a fetching process by combining the installation sequence and the stacking sequence.

[0041] The retrieval stroke refers to the complete movement trajectory of retrieving the target steel bar from the material storage area and then transferring the target steel bar to the installation position according to the installation sequence. The method for determining the retrieval stroke is common knowledge to those skilled in the art.

[0042] Step 105: Generate and send a rebar retrieval instruction based on the retrieval process.

[0043] A rebar retrieval command is a command that controls the robotic arm to sequentially transfer the required rebars to the installation position according to the retrieval stroke. The method for determining the rebar retrieval command is common knowledge to those skilled in the art.

[0044] By using visual technology to identify the curvature of materials in material images and combining it with size requirements, the installation position, installation sequence, and stacking sequence are accurately determined, and the picking stroke and picking instructions are generated. This achieves automation and precision in the picking of steel bars, avoids installation deviations caused by misaligned picking or disordered sequences, and improves the welding efficiency of the steel cage for the tunnel lining segments.

[0045] A method for visual positioning and welding of steel reinforcement cages for subway tunnel segments, further comprising: Step 106: Determine the welding points according to the installation sequence and installation location.

[0046] Welding points refer to the specific locations where reinforcing bars (main bars and stirrups, main bars and reinforcing bars) need to be welded, i.e., the three-dimensional coordinate points of the welding, i.e., the intersections of the reinforcing bars with the reinforcing bars before the installation sequence. For example, when the installation sequence is 3, the welding points are the intersections of reinforcing bar No. 3 with reinforcing bars No. 1 and No. 2 respectively. The method for determining the welding points is selected by the staff according to the actual situation.

[0047] Step 107: Determine welding parameters based on the welding points.

[0048] Welding parameters refer to the core parameters that need to be controlled during the welding process, including welding current, welding voltage, welding speed, etc. They can be determined according to the specifications and materials of the steel bars at the welding point. The method for determining welding parameters is selected by the staff based on the actual situation.

[0049] Step 108: Analyze the welding parameters to determine the heat input.

[0050] Heat input refers to the heat energy input per unit length of weld seam, which can be calculated using the formula: Heat input = (Welding current * Welding voltage) / Welding speed.

[0051] Step 109: Determine the welding angle based on the heat input, and identify the welding surface angle from the material image based on the welding point location.

[0052] The welding angle refers to the angle between the welding torch and the welding surface of the reinforcing bar. The larger the heat input, the smaller the welding angle. The welding angle corresponding to the heat input can be found in the angle correspondence table, which is a data table that records different heat inputs and their corresponding welding angles.

[0053] The welding surface angle refers to the actual surface normal angle of the welded part of the steel bar (such as the intersection of the main bar and the stirrup). It can be obtained by image recognition technology from the contour features of the welding point in the material image. The method of identifying the welding surface angle is common knowledge in the field.

[0054] Step 110: Determine the welding torch angle by combining the welding angle and the welding surface angle.

[0055] The welding torch angle refers to the actual working angle of the welding torch, which is calculated as the sum of the welding angle and the welding surface angle.

[0056] Step 111: In response to the generation and transmission of the welding torch angle and welding point, a rebar welding command is sent.

[0057] The rebar welding command refers to the command that controls the robotic arm to control the welding torch to process the welding points one by one according to the angle of the welding torch. The method of generating the rebar welding command is common knowledge to those in the field.

[0058] The welding points are determined based on the installation sequence and location. The heat input is analyzed in conjunction with the welding parameters, and the welding gun angle is determined in conjunction with the welding surface angle before the welding command is issued. This ensures that the welding gun angle is accurately matched with the welding point and the heat input, reducing defects such as incomplete fusion and undercut in the weld, and improving the welding quality of the steel cage of the tunnel segment.

[0059] A method for visual positioning and welding of steel reinforcement cages for subway tunnel segments, further comprising: Step 112: When the heat input is greater than the preset deformation threshold, the material length is identified from the material image based on the heat input.

[0060] The deformation threshold refers to the critical value of heat input that easily leads to thermal deformation of the reinforcing steel. The deformation threshold is selected by the staff based on the actual situation. If the heat input exceeds the deformation threshold, it means that the risk of thermal deformation of the reinforcing steel is relatively high, and it is necessary to suppress the thermal deformation of the reinforcing steel. The material length refers to the actual length of the reinforcing steel to be welded, which can be calculated by fitting the outline of the reinforcing steel in the material image using image recognition technology. The method for determining the material length is common knowledge in the field.

[0061] Step 113: Determine the degree of deformation by combining the material length and heat input.

[0062] Deformation degree refers to the amount of deformation that may occur in steel bars during welding. The greater the material length and heat input, the greater the deformation degree. The deformation degree corresponding to the material length and heat input can be found in the deformation correspondence table. The deformation correspondence table is a data table that records different material lengths and heat inputs and their corresponding deformation degrees.

[0063] Step 114: Determine the clamping force based on the degree of deformation, and determine the clamping number based on the welding point.

[0064] Clamping force refers to the clamping force of the jig fixture on the steel bar to be welded. The greater the degree of deformation, the greater the clamping force is used. The clamping force corresponding to the degree of deformation can be found in the clamping correspondence table, which is a data table that records different degrees of deformation and their corresponding clamping forces.

[0065] The clamping number is a unique identifier for the clamp closest to the welding point. Multiple clamps are evenly arranged on the jig, and each clamp uses an independent motor to control the clamping force. The clamping number closest to the welding point can be found from the clamping record table. The clamping record table is a data table that records the clamping numbers of different clamps and their corresponding clamping positions.

[0066] Step 115: In response to the clamping force and clamping number, generate and send a clamping command for the tire carcass.

[0067] The jig clamping command refers to the command that controls the motor of the jig corresponding to the clamping number to drive the jig to clamp the steel bar according to the clamping force. The method of generating the jig clamping command is common knowledge to those skilled in the art.

[0068] When the heat input is too large, the length of the material is visually identified and the degree of deformation is determined in combination with the heat input. Then, the clamping force of the jig is adjusted. By predicting the deformation risk in advance and accurately controlling the clamping force, the steel bars are constrained by thermal expansion. This reduces the deformation of the arc-shaped steel cage due to excessive heat input, such as warping and shrinkage, and improves the welding quality of the segment steel cage.

[0069] Reference Figure 2 Real-time welding methods include: Step 200: Acquire thermal images in response to the steel bar welding command.

[0070] Thermal images refer to the thermal distribution images of a steel cage being welded. These images can be acquired using an infrared thermal imaging camera, and the acquisition method is selected by the staff based on the actual situation.

[0071] Step 201: Determine the actual heat from the thermal image based on the welding point.

[0072] Actual heat refers to the actual heat input at the welding point. The heat value at the welding point can be read from the heat image, and the difference between the heat value of the current cycle and the heat value of the previous cycle can be calculated as the actual heat.

[0073] Step 202: Calculate the difference between the actual heat and the heat input, and define it as the heat deviation.

[0074] Heat deviation is a numerical value used to represent the degree of deviation from the predicted heat input.

[0075] Step 203: Determine the calibration angle based on the heat deviation.

[0076] The calibration angle refers to the angle value that the welding torch needs to be adjusted to eliminate heat deviation. The calibration angle corresponding to the heat deviation can be found in the angle correspondence table. Then, the sum of the original welding torch angle and the calibration angle is calculated as the new welding torch angle.

[0077] Step 204: Update the welding torch angle in response to the calibration angle.

[0078] By acquiring heat images in real time during welding to determine the actual heat, the heat deviation can be calculated and a suitable calibration angle can be selected to adjust the welding torch angle. This reduces the welding torch angle inaccuracy caused by fluctuations in heat input during welding, thereby improving the welding quality of the segment reinforcement cage.

[0079] Real-time welding methods also include: Step 205: Determine the heat range based on actual heat.

[0080] The heat range refers to the spatial range of heat diffusion. The heat range can be selected from the range of heat values ​​in the heat image that is between (actual heat - selected range) and (actual heat + selected range). The selected range is used to select the heat deviation of the heat range, and the selected range is selected by the staff according to the actual situation.

[0081] Step 206: Determine the range length based on the heat range.

[0082] The range length refers to the maximum diameter of the heat range, which can be calculated by fitting the contour of the heat range. The method for determining the range length is common knowledge to those in the field.

[0083] Step 207: Determine the thermal conductivity according to the length of the range.

[0084] Thermal conductivity refers to the ability of heat to be transferred through steel bars. The longer the range, the greater the thermal conductivity. The thermal conductivity corresponding to the range length can be found in the conduction correspondence table, which is a data table that records different range lengths and their corresponding thermal conductivity.

[0085] Step 208: Determine the conduction angle based on the thermal conductivity.

[0086] The conduction angle refers to the welding torch angle correction value used to adapt to the thermal conductivity. The higher the thermal conductivity, the more the welding torch needs to be tilted and the larger the conduction angle needs to be. The conduction angle corresponding to the thermal conductivity can be found in the conduction angle table. Then, the sum of the original welding torch angle and the conduction angle is calculated as the new welding torch angle. The conduction angle table is a data table that records different thermal conductivity and their corresponding conduction angles.

[0087] Step 209: Update the welding torch angle in response to the transmission angle.

[0088] The heat diffusion range is identified from the thermal image, and the thermal conductivity is evaluated according to the size of the heat range. Then, the appropriate conduction angle is selected according to the thermal conductivity to adjust the welding torch angle, thereby reducing the situation of local heat accumulation caused by excessive thermal conductivity and improving the welding quality of the segment reinforcement cage.

[0089] Real-time welding methods also include: Step 210: In response to the rebar welding command, acquire the rebar image and generate a rebar reference model by combining the material curvature and material length.

[0090] A rebar image refers to a picture of a rebar cage being welded. Rebar images can be acquired through a visual sensor, and the acquisition method is selected by the staff based on the actual situation.

[0091] A steel reinforcement reference model is a three-dimensional model of the steel reinforcement before welding, established according to the material's curvature and length. The method for generating a steel reinforcement reference model is common knowledge to those in the field.

[0092] Step 211: Identify the steel bar welding model from the steel bar image.

[0093] A steel bar welding model refers to a three-dimensional model of steel bars being welded. Steel bar welding models can be generated through image recognition technology, and the method for generating steel bar welding models is common knowledge to those in the field.

[0094] Step 212: Compare the steel reinforcement reference model and the steel reinforcement welding model to determine the deformation distance.

[0095] Deformation distance refers to the displacement difference between corresponding points after point cloud registration between the welded steel bar model and the steel bar reference model. The calculation method of deformation distance is common knowledge to those in the field.

[0096] Step 213: Determine the deformation center and deformation rate based on the deformation distance.

[0097] The deformation center refers to the core location where the steel bar undergoes deformation, i.e., the location with the largest deformation distance. The deformation rate refers to the speed at which the deformation center undergoes deformation, which is calculated from the deformation distance at different times. The methods for determining the deformation center and deformation rate are selected by the staff based on the actual situation.

[0098] Step 214: Determine the fixed number according to the deformation center and determine the clamping force according to the deformation rate.

[0099] The fixed number refers to the unique identifier of the fixture closest to the deformation center. The fixed number closest to the deformation center can be found in the fixture record table. The clamping force refers to the clamping force required to suppress deformation. The greater the deformation rate, the greater the clamping force is used. The clamping force corresponding to the deformation rate can be found in the clamping correspondence table. Then, the clamping force corresponding to the fixed number is retrieved. Finally, the sum of the clamping force and the clamping force is calculated as the new clamping force. The clamping correspondence table is a data table that records different deformation rates and their corresponding clamping forces.

[0100] Step 215: Update the carcass clamping command based on the fixed number and clamping force.

[0101] Images of the reinforcing bars are captured during welding to generate a welding model. A reference model of the reinforcing bars is generated by combining the material curvature and length before welding. The welding model and the reference model are then compared to determine the deformation distance of the reinforcing bars under welding. If the deformation distance is too large, the clamping force of the jig is increased to offset the welding deformation in real time, reduce the over-standard size of the reinforcing cage caused by deformation accumulation, and improve the welding quality of the segment reinforcing cage.

[0102] Reference Figure 3 Arc control methods include: Step 300: Collect welding acoustic patterns in response to the steel bar welding command.

[0103] Welding acoustic signatures refer to the sound signals generated by the burning of the electric arc and the fluctuation of the molten pool during the welding process. They can be collected by industrial acoustic signature sensors, and the collection method for welding acoustic signatures is selected by the staff according to the actual situation.

[0104] Step 301: Identify the three frequency bands from the welding acoustic waveform.

[0105] The three-frequency sound bands refer to the characteristic frequency bands obtained by wavelet packet decomposition of welding acoustic patterns according to frequency. They are generally divided into three characteristic frequency bands: low frequency band (0-1.5kHz, corresponding to molten pool vibration), mid frequency band (1.5-4.5kHz, corresponding to stable arc combustion), and high frequency band (4.5-10kHz, corresponding to arc micro-explosion and unstable factors). The identification method of the three-frequency sound bands is selected by the staff according to the actual situation.

[0106] Step 302: Analyze the three frequency bands to determine the three frequency energies.

[0107] Three-frequency energy refers to the sound energy of each frequency band in the three-frequency sound range. The power spectrum integral of each frequency band can be calculated as the energy of the corresponding frequency band. The calculation method of three-frequency energy is common knowledge to those in the field.

[0108] Step 303: Determine the proportion of the three frequencies based on the three-frequency energy.

[0109] The tri-band ratio refers to the proportion of tri-band energy in each frequency band to the total tri-band energy. The calculation method for the tri-band ratio is selected by the staff based on the actual situation.

[0110] Step 304: Determine the percentage deviation based on the three frequency percentages.

[0111] The percentage deviation refers to the maximum difference between the actual three-frequency percentage and the standard three-frequency percentage. The standard three-frequency percentage refers to the three-frequency percentage value under normal melting and penetration conditions. The standard three-frequency percentage is preset by the staff according to the actual situation.

[0112] Step 305: Select the adjustment current according to the aforementioned percentage deviation.

[0113] The adjustment current refers to the correction value used to adjust the arc current of the welding torch. The larger the percentage deviation, the larger the adjustment current. The adjustment current corresponding to the percentage deviation can be found in the adjustment correspondence table. Then, the adjustment symbol is selected according to the frequency band of the percentage deviation. For example, if the percentage deviation is in the low frequency band, the current value needs to be reduced, and if the percentage deviation is in the high frequency band, the current value needs to be increased. The adjustment correspondence table is a data table that records different percentage deviations and their corresponding adjustment currents.

[0114] Step 306: In response to the regulation current generation, an arc control command is sent.

[0115] Arc control commands are instructions to adjust the current of the welding torch according to a reference. The method for generating arc control commands is common knowledge to those skilled in the art.

[0116] By collecting welding acoustic patterns, identifying the three frequency bands, analyzing the energy ratio of the three frequencies to determine the deviation, and adjusting the welding torch current, the degree of steel penetration can be indirectly monitored through acoustic pattern recognition, reducing weld defects caused by abnormal penetration and improving the welding quality of the steel cage.

[0117] Arc control methods also include: Step 307: Determine the deviation sound segment based on the stated proportion deviation.

[0118] The deviation range refers to the frequency band in which the deviation occurs, namely the low-frequency band, mid-frequency band, or high-frequency band. The method for determining the deviation range is selected by the staff based on the actual situation.

[0119] Step 308: When the deviation sound segment is consistent with the preset high-frequency sound segment, extract the high-frequency sound pattern from the three-frequency sound segment.

[0120] The high-frequency sound segment refers to the deviation sound segment corresponding to the high-frequency segment. If the deviation sound segment is consistent with the high-frequency sound segment, it means that the proportion of deviation corresponds to the high-frequency segment, that is, the energy of the high-frequency segment is too concentrated. The high-frequency voiceprint refers to the voiceprint information corresponding to the high-frequency segment. The extraction method of the high-frequency voiceprint is selected by the staff according to the actual situation.

[0121] Step 309: Determine the high-frequency power spectrum based on the high-frequency acoustic signature.

[0122] High-frequency power spectrum refers to the estimation of power spectral density of high-frequency acoustic waveforms to obtain the power distribution at each frequency point in the high-frequency band. The calculation method of high-frequency power spectrum is common knowledge to those in the field.

[0123] Step 310: Determine the peak power and average power from the high-frequency power spectrum.

[0124] Peak power refers to the maximum power in the high-frequency power spectrum, reflecting the strongest energy point of the high-frequency voiceprint. Average power refers to the average power of all frequency points in the high-frequency power spectrum, reflecting the average energy level of the high-frequency voiceprint. The methods for determining peak power and average power are common knowledge to those skilled in the art.

[0125] Step 311: Calculate the quotient of the peak power and the average power, and define it as the peak sharpness.

[0126] Peak sharpness refers to the energy concentration of high-frequency acoustic signatures. The higher the peak sharpness, the more concentrated the energy and the less stable the arc.

[0127] Step 312: Determine the adjustment frequency based on the peak sharpness.

[0128] The adjustment frequency refers to the correction value used to adjust the frequency of the arc current. The greater the sharpness of the spectral peak, the smaller the adjustment frequency. The adjustment frequency corresponding to the spectral peak sharpness can be found in the frequency correspondence table, which is a data table that records different spectral peak sharpness and their corresponding adjustment frequencies.

[0129] Step 313: Update the arc control command in response to the adjusted frequency.

[0130] When the energy proportion of the high-frequency sound band is too high, the high-frequency sound pattern is extracted and the power spectrum is analyzed to determine the peak sharpness. Then, the frequency of the welding gun current is adjusted. In this way, the stability of the electric arc can be accurately identified through power spectrum analysis, reducing defects such as weld undercut and weld beads caused by high-frequency electric arc instability, and improving the welding quality of the segment reinforcement cage.

[0131] Arc control methods also include: Step 314: When the peak sharpness is greater than the preset peak threshold, determine the frequency peak based on the power peak value.

[0132] The peak threshold refers to the critical value of spectral peak sharpness that indicates the presence of isolated peaks; 3.5 is generally used as the peak threshold. A peak sharpness greater than the peak threshold indicates the presence of isolated peaks, i.e., a tendency for bubbles. The frequency peak value refers to the frequency value corresponding to the power peak value, which can be read from the high-frequency power spectrum.

[0133] Step 315: Extract the voiceprint frequency point from the high-frequency voiceprint in response to the frequency peak.

[0134] Voiceprint frequency points refer to the number of frequency points that are consistent with the frequency peak value extracted from high-frequency voiceprints. The extraction method of voiceprint frequency points is selected by the staff according to the actual situation.

[0135] Step 316: Determine the peak energy based on the voiceprint frequency point, and extract the high-frequency energy from the three-frequency energy.

[0136] Peak energy refers to the sound energy corresponding to the voiceprint frequency point, which can be calculated as the product of the peak power and the voiceprint frequency point. High-frequency energy refers to the power spectrum integral corresponding to the high-frequency band, and the method for obtaining high-frequency energy is selected by the staff according to the actual situation.

[0137] Step 317: Calculate the quotient of the peak energy and the high-frequency energy, and define it as the peak percentage.

[0138] Peak percentage refers to a value used to quantify the energy concentration of high-frequency sound signatures. The higher the peak percentage, the more concentrated the energy of the high-frequency sound signature is at the peak, and the more severe the porosity tendency.

[0139] Step 318: Select the swing amplitude according to the peak percentage.

[0140] The oscillation amplitude refers to the left and right oscillation distance of the welding torch per unit time during the welding process. The larger the peak percentage, the larger the oscillation amplitude is used to stir the molten pool and promote the escape of bubbles. The oscillation amplitude corresponding to the peak percentage can be found in the oscillation correspondence table, which is a data table that records different peak percentages and their corresponding oscillation amplitudes.

[0141] Step 319: Update the rebar welding command in response to the swing amplitude.

[0142] When the peak sharpness is too high, the peak frequency energy is extracted and compared with the total high-frequency energy to obtain the peak ratio. Based on this, the welding torch oscillation amplitude is selected. In this way, the severity of porosity tendency is quantified by energy concentration, and graded intervention is used to promote bubble escape, thereby achieving online suppression of porosity defects and improving the welding quality of the segment reinforcement cage.

[0143] Based on the same inventive concept, embodiments of the present invention provide a visual positioning and welding forming system for subway segment reinforcement cages, comprising: The acquisition module is used to acquire material images; The memory is used to store the program for any of the above-mentioned methods for visual positioning and welding of subway segment steel cages; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

[0144] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0145] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for visual positioning and welding of steel reinforcement cages for subway tunnel segments, characterized in that, include: Step 100: Acquire material images; Step 101: Identify the material curvature from the material image and retrieve the dimensional requirements; Step 102: Determine the installation location based on the material's curvature and dimensional requirements; Step 103: Determine the installation sequence based on the installation location, and determine the stacking sequence from the material image based on the installation location; Step 104: Generate a fetching process by combining the installation sequence and the stacking sequence; Step 105: Generate and send a rebar retrieval command based on the retrieval stroke; Also includes: Step 106: Determine the welding points according to the installation sequence and installation location; Step 107: Determine welding parameters based on the welding points; Step 108: Analyze the welding parameters to determine the heat input; Step 109: Determine the welding angle based on the heat input, and identify the welding surface angle from the material image based on the welding point location; Step 110: Determine the welding torch angle by combining the welding angle and the welding surface angle; Step 111: In response to the generation and transmission of the welding torch angle and welding point, a rebar welding command is sent.

2. The method for visual positioning and welding of subway tunnel segment reinforcement cages according to claim 1, characterized in that, Also includes: Step 112: When the heat input is greater than the preset deformation threshold, the material length is identified from the material image based on the heat input. Step 113: Determine the degree of deformation based on the material length and heat input; Step 114: Determine the clamping force based on the degree of deformation, and determine the clamping number based on the welding point; Step 115: In response to the clamping force and clamping number, generate and send a clamping command for the tire carcass.

3. The method for visual positioning and welding of subway tunnel segment reinforcement cages according to claim 2, characterized in that, It also includes a real-time welding method, which includes: Step 200: Acquire a thermal image in response to the steel bar welding command; Step 201: Determine the actual heat from the thermal image based on the welding point location; Step 202: Calculate the difference between the actual heat and the heat input, and define it as the heat deviation; Step 203: Determine the calibration angle based on the heat deviation; Step 204: Update the welding torch angle in response to the calibration angle.

4. The method for visual positioning and welding of subway segment reinforcement cages according to claim 3, characterized in that, The real-time welding method further includes: Step 205: Determine the heat range based on actual heat output; Step 206: Determine the range length based on the stated heat range; Step 207: Determine the thermal conductivity according to the length of the range; Step 208: Determine the conduction angle based on the thermal conductivity; Step 209: Update the welding torch angle in response to the transmission angle.

5. The method for visual positioning and welding of rebar cages for subway tunnel segments according to claim 4, characterized in that, The real-time welding method further includes: Step 210: In response to the rebar welding command, acquire the rebar image and generate a rebar reference model by combining the material curvature and material length; Step 211: Identify the steel bar welding model from the steel bar image; Step 212: Compare the aforementioned steel reinforcement reference model and steel reinforcement welding model to determine the deformation distance; Step 213: Determine the deformation center and deformation rate based on the deformation distance; Step 214: Determine the fixed number according to the deformation center, and determine the clamping force according to the deformation rate; Step 215: Update the carcass clamping command based on the fixed number and clamping force.

6. The method for visual positioning and welding of subway segment reinforcement cages according to claim 2, characterized in that, It also includes an arc control method, the arc control method comprising: Step 300: Acquire welding acoustic signature in response to the rebar welding command; Step 301: Identify the three frequency bands from the welding acoustic waveform; Step 302: Analyze the three frequency bands to determine the energy of the three frequencies; Step 303: Determine the proportion of the three frequencies based on the three-frequency energy; Step 304: Determine the percentage deviation based on the three frequency percentages; Step 305: Select the adjustment current according to the stated percentage deviation; Step 306: In response to the regulation current generation, an arc control command is sent.

7. The method for visual positioning and welding of subway tunnel segment reinforcement cages according to claim 6, characterized in that, The arc control method further includes: Step 307: Determine the deviation sound segment based on the stated proportion deviation; Step 308: When the deviation sound segment is consistent with the preset high-frequency sound segment, extract the high-frequency sound pattern from the three-frequency sound segment; Step 309: Determine the high-frequency power spectrum based on the high-frequency acoustic signature; Step 310: Determine the peak power and average power from the high-frequency power spectrum; Step 311: Calculate the quotient of the peak power and the average power, and define it as the peak sharpness; Step 312: Determine the adjustment frequency based on the peak sharpness; Step 313: Update the arc control command in response to the adjusted frequency.

8. The method for visual positioning and welding of subway segment reinforcement cages according to claim 7, characterized in that, The arc control method further includes: Step 314: When the peak sharpness is greater than the preset peak threshold, determine the frequency peak based on the power peak value; Step 315: Extract the voiceprint frequency point from the high-frequency voiceprint in response to the frequency peak; Step 316: Determine the peak energy based on the voiceprint frequency point, and extract the high-frequency energy from the three-frequency energy; Step 317: Calculate the quotient of the peak energy and the high-frequency energy, and define it as the peak percentage; Step 318: Select the swing amplitude according to the peak percentage; Step 319: Update the rebar welding command in response to the swing amplitude.

9. A visual positioning and welding forming system for subway segment reinforcing cages, characterized in that, include: The acquisition module is used to acquire images of materials. A memory for storing a program for a visual positioning and welding forming method for subway segment reinforcement cages as described in any one of claims 1 to 8; The processor is the unit of memory that allows programs to be loaded and executed by the processor.

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