New energy ship double-wall pipe construction process

Abstract

The invention discloses a new energy ship double-wall pipe construction process. The process combines an automatic welding technology and a nondestructive testing technology, and ensures that the quality of a welded joint meets a strict design standard by accurately controlling welding parameters and environmental influence. And through standardized processing and double verification, the quality control of the pipeline is further optimized, and the controllability and reliability of each index in the construction process are ensured. In addition, through a refined data comparison and evaluation mechanism, the production efficiency is effectively improved, the manufacturing cost is reduced, and the stability and safety of the ship pipeline are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of ship pipeline construction, and specifically relates to a construction process for double-wall pipes of new energy ships. Background Art

[0002] At present, during the construction of double-wall pipes for new energy ships, there are still many technical problems in aspects such as welding quality, pipeline pressure resistance, and adaptability. The traditional construction process requires multiple weldings and repeated inspections, resulting in low production efficiency, cumbersome process flow, and at the same time affecting the stability and safety of the pipeline. In the prior art, the evaluation of welding quality and pipeline performance usually relies on experience, lacking accurate mathematical models and data analysis, resulting in easy occurrence of human errors during the inspection process. Summary of the Invention

[0003] The purpose of the present invention is to provide a construction process for double-wall pipes of new energy ships, which has the advantages of high efficiency, precision, and reliability, and solves the problems of inconsistent welding quality inspection, poor pipeline stability, and long production cycle.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A construction process for double-wall pipes of new energy ships, including the following steps:

[0005] S1. Selection of steel pipe materials and structures;

[0006] S2. Pretreatment of steel pipes and pipe forming;

[0007] S3. Welding operation;

[0008] S4. Non-destructive testing and data analysis;

[0009] S5. Quality inspection.

[0010] Preferably, the selection of steel pipe materials and structures includes the following sub-steps:

[0011] S11. Material selection: Select high-strength steel pipes of X52 grade and perform galvanizing treatment on the surface;

[0012] S12. Collect material characteristic data T: Collect the inner diameter, outer diameter, and wall thickness of the steel pipe through a laser measurement device.

[0013] Preferably, the pretreatment of steel pipes and pipe forming includes the following sub-steps:

[0014] S21. External heating treatment: Heat the steel pipe to 700 °C using a high-frequency induction heating device;

[0015] S22. Groove machining: Machine the groove of the steel pipe using a numerical control grooving machine, control the groove angle at 37°, and the groove length at 20 mm.

[0016] Preferably, the welding operation includes the following sub-steps:

[0017] S31. Automatic welding operation: Use a KUKA automatic welding robot to weld the inner and outer pipes. The welding current is set to 200 A, and the welding speed is 30 cm / min.

[0018] S32. Data acquisition: Collect the comprehensive data D of welding current, welding voltage, and welding speed through the sensor assembly welding .

[0019] Preferably, the non-destructive testing and data analysis include the following sub-steps:

[0020] S41. Preliminary calibration and data preprocessing: Use the preliminary calibration and data preprocessing algorithm to preliminarily calibrate the original welding data and correct the deviation caused by measurement tools and environmental change factors.

[0021] S42. Precision calibration and environmental error correction processing: On the basis of the preliminary calibration result output in S41, further combine the external environmental parameter E for fine correction, and optimize the accuracy of welding quality evaluation through the precision calibration and environmental error correction algorithm.

[0022] S43. Comprehensive performance evaluation and optimization processing: Combine the results of S41 and S42, generate the final welding quality evaluation and pipeline performance evaluation indicators through the comprehensive performance evaluation and optimization algorithm, and optimize the final result through non-linear combination.

[0023] Preferably, the expression of the preliminary calibration and data preprocessing algorithm is:

[0024] where

[0025] C 1 is the preliminary calibration result;

[0026] D welding is the welding data, including current, voltage, and welding speed;

[0027] K 1 is the welding data weight coefficient;

[0028] K 2 is the environmental parameter;

[0029] E is the environmental parameter weight coefficient;

[0030] T is the material property;

[0031] K 3 is the material property weight coefficient;

[0032] H is the error range of the measurement tool;

[0033] K 4 is the error coefficient of the measuring tool;

[0034] N is the normalization factor.

[0035] Preferably, the expression of the precision calibration and environmental error correction algorithm is: C 2 = C 1 × (1 + (E adj × η) / 100);

[0036] E adj = (E temperature × K 1 ) + (E humidity × K 2 ), where:

[0037] C 2 is the welding quality evaluation result after precision calibration;

[0038] C 1 is the preliminary calibration result of the preliminary calibration and data preprocessing algorithm;

[0039] E adj is the environmental adjustment factor, calculated based on environmental data;

[0040] η is the environmental error correction coefficient.

[0041] Preferably, the expression of the comprehensive performance evaluation and optimization algorithm is:

[0042] where P is the comprehensive performance evaluation index;

[0043] C 2 is the precision calibration result;

[0044] α is the weight coefficient of the preliminary calibration result;

[0045] β is the weight coefficient of the precision calibration result;

[0046] γ is the weight coefficient of the comprehensive result.

[0047] Preferably, S5 further includes the following sub-steps:

[0048] S51. Quality inspection and qualification determination: Use ultrasonic flaw detection equipment to detect the welded joint. The inspection content includes:

[0049] Signal intensity threshold: If the reflection intensity of the ultrasonic signal is greater than -20 dB, it is determined that the welded joint has no defect;

[0050] Defect size: The maximum diameter of the pores is less than or equal to 0.5 mm, and the crack length is less than or equal to 5 mm;

[0051] S52. Standardization Processing: Through standardization processing, calculate the sub-evaluation corresponding to the comprehensive evaluation result output in S43 from the specific detection data in S51. The calculation formula is as follows

[0052] C 5 = ω 1 ×SignalStrength + ω 2 ×Defect Size;

[0053] Where C 5 The evaluation generated corresponding to the S51 detection data represents the quality of the welded joint;

[0054] SignalStrength is the ultrasonic reflection signal strength, measured by S51;

[0055] Defect Size is the defect size, measured by S51;

[0056] ω 1 and ω 2 Are the weight coefficients of the signal strength and the defect size respectively, obtained through standardization calculation;

[0057] S53. Data Comparison: Compare the evaluation generated in S52 with the comprehensive evaluation result output in S43. If the evaluation generated in S5 is consistent with the evaluation output in S43, the welded joint is qualified.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] 1. By combining non-destructive testing and data analysis, the present invention precisely controls the welding quality and pipeline performance, greatly improving the stability of the construction process;

[0060] 2. Through standardization processing and a double-check mechanism, the consistency between the quality of the welded joint and the evaluation result of the performance is ensured, avoiding repair and rework;

[0061] 3. In the data comparison and evaluation mechanism, by combining ultrasonic detection data with comprehensive performance evaluation, the pipeline quality control process is optimized, reducing manual errors and improving the accuracy of the construction process;

[0062] 4. By finely calibrating the environmental parameters and material properties, the present invention makes the construction process highly adaptable and can meet the usage requirements of ships in different environments. Description of the Drawings

[0063] Figure 1 It is a schematic diagram of the framework of the construction process steps of the double-wall pipe of the new energy ship of the present invention;

[0064] Figure 2It is the flow chart of the sub-steps for selecting steel pipe materials and structures in the present invention;

[0065] Figure 3 It is the flow chart of the sub-steps for preprocessing steel pipes and forming pipelines in the present invention;

[0066] Figure 4 It is the flow chart of the sub-steps for welding operations in the present invention;

[0067] Figure 5 It is the flow chart of the sub-steps for non-destructive testing and data analysis in the present invention. Detailed implementation manners

[0068] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0069] Please refer to Figures 1 to 5 , the present invention provides a technical solution: a construction process for double-wall pipes of new energy ships, including the following steps:

[0070] S1. Selection of steel pipe materials and structures

[0071] In the construction process of double-wall pipes, the selection of materials and the design of structures are the basis for determining the quality and reliability of the pipes. Selecting suitable steel pipe materials and designing reasonable structures can not only ensure the pressure-bearing capacity of the pipes, but also increase their service life, especially in high-load and harsh environments.

[0072] S11. Material selection:

[0073] Select X52 high-strength steel pipes as the main pipe materials. X52 steel pipes have high compressive strength and toughness, can withstand large internal pressures, and have excellent corrosion resistance, which is suitable for the use environment of ships. Ship pipelines usually need to bear huge pressures and long-term water immersion, especially in the marine environment, and the corrosion resistance of the steel pipe materials is crucial. To enhance the corrosion resistance of the pipes, the surface of the steel pipes is treated with galvanization, which effectively avoids the erosion of factors such as moisture and salt water in the environment on the pipes.

[0074] The galvanization treatment not only improves the antioxidant ability of the steel pipes, but also enhances their resistance to chemical corrosion. The galvanized layer usually uses the hot-dip galvanization process, which can form a uniform protective layer, make the surface of the steel pipes smoother, reduce the adhesion of dirt, and extend the service life of the pipes. Using galvanized steel pipes can ensure that the pipes can still maintain good performance in harsh environmental conditions during the long-term operation of the ships.

[0075] When selecting materials, in addition to the high strength and corrosion resistance of X52 steel pipes, the cost, processability, and adaptability of the steel pipes are also important factors to be considered. By reasonably selecting materials and manufacturing processes, the production cost can be effectively reduced while ensuring that the performance of the pipeline is not affected.

[0076] S12. Collect material characteristic data T:

[0077] After the selection of steel pipe materials, the next step is to accurately measure the dimensions of the steel pipes to ensure that they meet the construction specifications and installation requirements. Through laser measurement equipment, the inner diameter, outer diameter, and wall thickness of the steel pipes are accurately collected. The application of laser measurement technology can provide high-precision, fast, and non-contact measurement results, avoiding the errors that may be brought by traditional measurement methods.

[0078] Inner diameter measurement: The inner diameter is the diameter inside the pipeline. For double-wall pipes, the inner diameter determines the flow capacity of the fluid inside the pipeline. Accurate measurement of the inner diameter ensures the flow requirements of the pipeline.

[0079] Outer diameter measurement: The outer diameter is the diameter outside the pipeline, which directly affects the installation process of the pipeline and the selection of fittings. The accuracy of the outer diameter has an important impact on the connectivity and sealing performance of the pipeline.

[0080] Wall thickness measurement: Measuring the wall thickness is crucial for ensuring the strength and pressure resistance of the pipeline. Especially in high-pressure environments, the wall thickness of the pipeline determines its ability to resist external pressure;

[0081] The laser measurement equipment uses the reflection principle to scan the surface of the pipe with a laser beam and return the measured data. These data can provide very high precision after calculation and are not affected by temperature or other external factors. Through this technical means, the dimensional information of the pipeline can be obtained in real time, providing an accurate reference for subsequent processing, welding, and installation;

[0082] S21. External heating treatment

[0083] External heating treatment is to heat the steel pipe to the required temperature through high-frequency induction heating technology to improve the plasticity of the steel pipe, reduce cracks or deformations that may occur during the welding process, and improve the quality of the welded joint.

[0084] In this step, a high-frequency induction heating equipment is used to heat the steel pipe. The heating temperature of the steel pipe is controlled at 700 °C. This temperature range can effectively change the material properties on the surface of the steel pipe, improve its plasticity, and facilitate subsequent bevel processing and welding operations.

[0085] The working principle of the high-frequency induction heating equipment is to convert electrical energy into heat energy through the principle of electromagnetic induction and directly heat the surface of the steel pipe. The heating process is controlled by a computer to ensure the uniformity and accuracy of heating and avoid temperature difference cracks caused by uneven heating. At the same time, the use of induction heating can heat the steel pipe to the target temperature in a short time and avoid excessive energy consumption.

[0086] Heating process control:

[0087] Heating time: The heating time depends on the diameter and thickness of the steel pipe.

[0088] Temperature monitoring: During the heating process, a temperature sensor monitors the surface temperature of the steel pipe in real time to ensure the stability of the heating process and avoid the deterioration of the material properties of the steel pipe caused by overheating.

[0089] Effect after heating: Through external heating treatment, the surface of the steel pipe can reach the ideal welding temperature. This not only improves the plasticity of the steel pipe, avoids stress concentration during welding, but also effectively reduces the generation of cracks caused by sudden temperature changes. In addition, the heated steel pipe is easier to cooperate with groove machining to ensure the subsequent welding quality.

[0090] S22. Groove machining

[0091] Groove machining is to process the angle and shape of the end of the steel pipe to ensure full contact and form a strong welded joint when welding steel pipes. Groove machining is a key step to achieve high-quality welding. Especially in an environment with high pressure and high temperature, the welding quality directly affects the reliability and service life of the pipeline.

[0092] Implementation process: In this step, a numerically controlled groove machine is used to precisely process the steel pipe to ensure that the shape, angle and length of each welded joint meet the standards. Specifically:

[0093] Groove angle: Control the groove angle of the steel pipe at 37°. This angle is optimized to ensure better combination of the molten pool at the welded joint, thus forming a stronger welded joint.

[0094] Groove length: Control the groove length at 20mm. This length can ensure sufficient strength of the joint during welding and avoid welding quality problems caused by insufficient contact of the joint.

[0095] Processing process control:

[0096] The numerically controlled groove machine processes the groove of the steel pipe through an accurate computer control system to ensure the accuracy of the processing angle and length and avoid errors that may be introduced by manual operation.

[0097] During the processing, high-precision measuring tools are used to monitor the angle and length of the bevel in real time to ensure consistency with the design standards.

[0098] Effect after processing: After bevel processing, a compliant angle and length are formed at the welded end of the steel pipe, ensuring sufficient contact area of the weld seam during welding, avoiding stress concentration in the welding area, and thus significantly improving the strength and stability of the welded joint.

[0099] S3. Welding operation

[0100] Welding operation is a crucial link in the construction of double-wall pipes for new energy ships. Its main purpose is to ensure the structural integrity, strength, and stability of the pipeline by precisely controlling welding parameters. Through the application of automation technology, the welding operation process can achieve high precision, high efficiency, and high consistency, thereby improving the manufacturing quality of ship pipelines.

[0101] S31. Automatic welding operation

[0102] The main purpose of automatic welding operation is to ensure that the welded joints between the inner and outer pipes meet the quality standards and guarantee the strength and stability of the weld seam through efficient robotic welding technology. Using an automatic welding robot can not only improve welding efficiency but also reduce human errors and ensure the consistency of the welding process.

[0103] Implementation process: In this step, a KUKA automatic welding robot is used for welding operation.

[0104] Welding current setting: The welding current is set to 200A. The magnitude of the current is crucial for welding quality. Too low a current will result in insufficient strength of the welded joint, while too high a current may cause overheating of the welded joint, affecting the quality of the weld seam. Through optimized current setting, uniform heat input during welding can be ensured, avoiding overheating and uneven cooling.

[0105] Welding speed setting: The welding speed is set to 30 cm / min. Too fast a welding speed may result in uneven weld seams, while too slow a speed may waste too much energy. By reasonably setting the welding speed, sufficient heating of the welding area can be ensured to form a firm weld seam while avoiding excessive heat influence.

[0106] Welding process control: During the welding process, the KUKA automatic welding robot automatically completes the welding operation according to the preset welding path and welding parameters. Precise control of the welding path can ensure that each welded joint meets the standards.

[0107] The robotic welding system can monitor welding current, voltage, and other welding parameters in real time and make real-time adjustments through the vision system to ensure stability during the welding process.

[0108] Effect after welding: Through automatic welding operations, the welding quality can be effectively guaranteed, the strength and durability of the welded joints can be improved, and the impact of human factors on welding quality can be reduced. Using a KUKA automatic welding robot for welding operations can ensure that each welded joint is welded evenly and stably, thus improving the quality of the overall pipeline.

[0109] S32. Data acquisition

[0110] Through precise data acquisition, key parameters during the welding process can be obtained in real time, providing basic data support for subsequent welding quality assessment, calibration, and optimization. The accuracy of the data acquisition process directly affects the accuracy of subsequent quality control and performance evaluation.

[0111] Implementation process: In this step, data during the welding process is collected in real time through a sensor component, including data such as welding current, voltage, and welding speed. These data are the basis for subsequent calibration and quality assessment.

[0112] Welding current: During the welding process, current is a key parameter that directly affects the heat input to the welding area and the formation of the molten pool. Excessive current can lead to an oversized and overheated weld, while insufficient current cannot form a weld with sufficient strength. Collecting welding current data through sensors provides a basis for subsequent calibration.

[0113] Welding voltage: The welding voltage determines the length and stability of the welding arc. Excessive voltage may cause overheating in the welding area, while too low voltage will result in an unstable arc, thus affecting the quality of the welded joint. By monitoring the voltage in real time, the stability of the welding arc can be ensured, and welded joints can be effectively formed.

[0114] Welding speed: Welding speed is another important factor affecting welding quality. Too fast a speed may result in insufficient welding, while too slow a speed may lead to an overly large heat-affected zone. By collecting welding speed data, the welding process can be optimized and adjusted to ensure the quality of the weld.

[0115] Control of the data acquisition process:

[0116] All data is transmitted in real time through sensors to the data processing system. During this process, welding current, voltage, and speed data will be filtered, calibrated, and stored to ensure the accuracy and stability of the data.

[0117] These data can be displayed through charts and real-time monitoring systems, providing real-time feedback to operators and helping them make immediate adjustments during the welding process.

[0118] These welding process data provide an important basis for subsequent welding quality assessment. By accurately recording parameters such as welding current, voltage, and speed, analysis, calibration, and optimization can be carried out in subsequent steps to ensure that the quality of the final welded joint meets the design requirements.

[0119] S4, Nondestructive Testing and Data Analysis

[0120] Nondestructive testing and data analysis are important steps to ensure that the welding quality meets the design requirements and improve the overall performance of the pipeline. This step mainly optimizes the quality assessment of the welded joint and the pipeline performance through a series of algorithms such as data preprocessing, precision calibration, environmental correction, and performance evaluation.

[0121] S41, Preliminary Calibration and Data Preprocessing

[0122] The main objective of preliminary calibration and data preprocessing is to correct the original welding data to eliminate errors caused by factors such as measurement tools and environmental changes. The core of this stage is to correct the original data through algorithms to ensure that the subsequent analysis results can reflect the true situation of welding quality.

[0123] Implementation process: In this step, the original welding data (welding current, voltage, speed) undergoes data preprocessing algorithms for correction and standardization. Since the measurement tools during the welding process may introduce certain errors, the goal of the data preprocessing algorithm is to reduce the impact of these errors on the final result through statistical methods, filtering techniques, and standardization means.

[0124] By performing weighted processing on different welding parameters, the data such as welding current, voltage, and speed are corrected to reach a standardized value. This process ensures the consistency of the data in subsequent processing and analysis.

[0125] Preliminary Calibration and Data Preprocessing Algorithm: ; where

[0126] C 1 is the result of preliminary calibration;

[0127] D welding is the welding data, including current, voltage, and welding speed;

[0128] K 1 is the weight coefficient of the welding data;

[0129] K 2 is the environmental parameter;

[0130] E is the weight coefficient of the environmental parameter;

[0131] T is the material property;

[0132] K3 is the weight coefficient of material properties;

[0133] H is the error range of the measuring tool, where: the error range of the welding current sensor: ±2%

[0134] The error range of the voltage sensor: ±1%;

[0135] K 4 is the error coefficient of the measuring tool;

[0136] N is the normalization factor;

[0137] Among them: the weight coefficient of welding data W welding,i is the weight (current, voltage) of the i-th welding data, and the relative influence weights of different welding parameters on welding quality are derived through regression analysis or statistical methods. The influence degree of each welding parameter (current, voltage, welding speed) on the quality of the welded joint is obtained through experimental data; the weight coefficient is obtained through statistical methods (least squares regression analysis);

[0138] C quality,i The quality evaluation value corresponding to the i-th welding data. It is the welding quality score obtained through welding quality inspection (ultrasonic flaw detection, X-ray). Each welding data point will have a corresponding quality score. The quality score is obtained through the comprehensive evaluation of the quality inspection results and is usually scored according to the defect conditions (cracks, pores) of the welded joint;

[0139] Weight coefficient of environmental parameters: Among them:

[0140] W env,j : the weight of the j-th environmental parameter (temperature, humidity).

[0141] Through experiments or simulation calculations, analyze the influence of different environmental factors on welding quality and derive the relative weight of each environmental factor. It can be calculated through regression analysis or weighted average method.

[0142] Calculation method: Calculate the respective weight coefficients through the influence of environmental parameters (temperature, humidity) on the welding quality evaluation value;

[0143] C quality,j : the quality evaluation value corresponding to the environmental parameter.

[0144] Through experimental data or quality inspection results, associate the environmental data with the quality of the welded joint to obtain the quality evaluation value related to the environmental factor.

[0145] Calculate the corresponding quality evaluation value according to the influence of the actual environmental conditions (temperature, humidity) on the welded joint;

[0146] The core of the algorithm is to perform weighted correction on the original data, where the weight coefficients are obtained through experiments and are used to measure the influence degree of each measurement parameter. For example, the error of the welding current may have a greater impact on the welding quality, so the weight coefficient of the welding current is relatively high.

[0147] After the data is preprocessed, the fluctuations caused by environmental changes (temperature, humidity) and tool errors (sensor errors) can be eliminated, ensuring the accuracy and stability of the data.

[0148] Weight coefficient of material properties:

[0149] W material,k : The weight of the kth material property (strength, thickness of the steel pipe).

[0150] It is calculated through regression analysis or experimental data by combining the physical property data of material strength and thickness with the welding quality evaluation results. The weight of the material property is calculated based on the correlation between the material property and the welding joint quality, and usually, the influence degree of the material property on the welding quality is determined through experiments.

[0151] C quality,k : The quality evaluation value corresponding to the material property. Through the correlation between welding quality detection and material properties, the influence evaluation value of the material property on the welding quality under specific conditions is obtained. Score is given according to the physical properties (strength, thickness) of the material and the quality performance of the welding joint.

[0152] Measurement tool error coefficient: Among them:

[0153] W tool,l : The weight of the error range of the lth measurement tool.

[0154] By analyzing the error ranges of different measurement tools and combining the accuracy of the actual measurement tools, the influence of each measurement tool error on the welding quality evaluation result is calculated. An error propagation model can be used to deduce the error weights of each tool.

[0155] By analyzing the errors of the measurement tools and considering the influence of the accuracy of different measurement tools (such as temperature sensors, current sensors, etc.) on the final welding quality, the weight of each measurement tool is obtained.

[0156] C quality,l : The quality evaluation value corresponding to the measurement tool error. Through the feedback analysis of the measurement tool error and combining the quality detection data, the quality evaluation value related to the error range is obtained. According to the influence of different measurement tool errors on the quality evaluation result, the corresponding quality score is generated

[0157] Furthermore, the expression of the precision calibration and environmental error correction algorithm is:

[0158] C 2 = C 1 × (1 + (E adj × η) / 100); E adj = (E temperature × K 1 ) + (E humidity × K 2 ), where:

[0160] C 2 is the welding quality evaluation result after precision calibration, which is the welding quality evaluation value obtained through the preliminary calibration and data preprocessing algorithm. This value is the result of correction and preprocessing based on the original welding data (current, voltage, speed). This result does not yet consider the influence of environmental factors and only reflects the basic quality situation during the welding process;

[0161] C 1 is the preliminary calibration result of the preliminary calibration and data preprocessing algorithm;

[0162] E adj is the environmental adjustment factor, which is calculated based on environmental data. This factor is used to represent the influence of environmental parameters (temperature, humidity) on welding quality. Environmental factors may introduce certain errors to the welding process, so it is necessary to correct through this factor to ensure the accuracy of the evaluation result;

[0163] η is the environmental error correction coefficient, which is used to adjust the errors caused by environmental factors. During the welding process, environmental factors (temperature and humidity) may affect the physical properties of materials, thereby affecting welding quality. Therefore, it is necessary to calibrate through this coefficient. This coefficient is obtained through experimental data and simulation calculations and is usually adjusted according to the specific influence of environmental factors (humidity, temperature) on welding quality;

[0164] Furthermore, the expression of the comprehensive performance evaluation and optimization algorithm is:

[0165] where P is the comprehensive performance evaluation index;

[0166] C 2 is the precision calibration result, which is the welding quality evaluation result obtained by combining the external environmental parameters (temperature, humidity) for precision calibration on the basis of C 1 . Precision calibration is carried out through the precision calibration and environmental error correction algorithm, which combines welding quality and environmental data for adjustment. It represents the correction of the welding quality evaluation result after considering environmental factors and provides a more accurate quality evaluation;

[0167] Regarding the weight coefficients:

[0168] α is the weight coefficient of the preliminary calibration result;

[0169] β is the weight coefficient of the precision calibration result;

[0170] γ is the weight coefficient of the comprehensive result;

[0171] These weight coefficients are used to adjust the influence degrees of C 1 and C 2 in the final evaluation. The magnitude of each coefficient determines the weight of the corresponding evaluation result in the final comprehensive evaluation. By adjusting these weight coefficients, the weights of the welding quality evaluation can be optimized according to the actual situation to ensure that the final evaluation result better meets the requirements in practical applications.

[0172] α (weight coefficient of the preliminary calibration result): Controls the importance of C 1 in the final evaluation. For example, in some cases, if the preliminary welding quality is already very good, a higher weight may be assigned to C 1 ;

[0173] β (weight coefficient of the precision calibration result): Controls the importance of C 2 in the final evaluation. When environmental factors have a greater impact on the welding quality, the role of precision calibration can be emphasized by increasing the value of β.

[0174] γ (weight coefficient of the comprehensive result): Used to control the weight of the combined effect of C 1 and C 2 The coefficient can reflect the combined influence of the two evaluation results on the final judgment of the welding quality.

[0175] The weight coefficients (α, β, γ) should be adjusted according to the actual production and application environment. They determine the contribution degree of each factor to the final evaluation result and need to be adjusted and optimized through experimental data and historical records.

[0176] S5 also includes the following sub-steps:

[0177] S51, Quality inspection and qualification determination: Use ultrasonic flaw detection equipment to detect the welded joints. The inspection content includes:

[0178] Signal intensity threshold: If the reflection intensity of the ultrasonic signal is greater than -20 dB, it is judged that the welded joint has no defect; if the reflection signal intensity is lower than -20 dB, the welded joint may have a defect and further analysis is required.

[0179] Defect size:

[0180] Porosity: If the maximum diameter is less than or equal to 0.5 mm, the welded joint is considered defect-free.

[0181] Crack: If the maximum length is less than or equal to 5 mm, the welded joint is considered defect-free.

[0182] If the porosity diameter is greater than 0.5 mm or the crack length is greater than 5 mm, the welded joint is considered unqualified and needs to be repaired.

[0183] S52. Standardization: Through standardization, calculate the sub-evaluation corresponding to the comprehensive evaluation result output by S43 from the specific detection data in S51. The calculation formula is as follows

[0184] C 5 = ω 1 ×SignalStrength + ω 2 ×Defect Size;

[0185] Where C 5 is the evaluation generated corresponding to the S51 detection data, representing the quality of the welded joint;

[0186] SignalStrength is the ultrasonic reflection signal strength, measured by S51;

[0187] Defect Size is the defect size, measured by S51;

[0188] ω 1 and ω 2 are the weight coefficients of the signal strength and the defect size respectively, obtained through standardization calculation;

[0189] S53. Data comparison

[0190] Compare the evaluation result generated in S52 with the comprehensive evaluation result output by S43 to ensure the qualified quality of the welded joint.

[0191] Operation description:

[0192] Compare the sub-evaluation result C 5 generated in S52 with the comprehensive evaluation result P in S43.

[0193] If the score C 5 generated in S52 is consistent with the evaluation result P output by S43, it indicates that the welded joint is qualified and can proceed to the next process.

[0194] If the score generated in S52 is inconsistent with the evaluation result output by S43, it indicates that there are potential quality problems with the welded joint, and it needs to be repaired and the welding quality inspection needs to be carried out again.

[0195] Comparison criteria:

[0196] Consistency determination: If the score of S52 is consistent with the evaluation of S43, it indicates that the welded joint meets the quality requirements.

[0197] Inconsistency determination: If the score of S52 is inconsistent with the evaluation of S43, the welded joint needs to be repaired until they are consistent.

[0198] Example 1: Applied to the pipeline construction of a new energy ship

[0199] This example is applied to the construction process of the double-wall pipe of a new energy ship. For the high-strength and corrosion-resistant double-wall pipe requirements of this ship, the double-wall pipe construction process described in the present invention is adopted. The double-wall pipe of this ship is used for the transportation of high-pressure fuels such as methanol and LNG to ensure the power supply of the ship's main engine. Due to the particularity of the fuel pipeline, the quality of the welded joint must meet strict standards to avoid major safety accidents such as fuel leakage and pipeline rupture.

[0200] Implementation steps:

[0201] S1. Selection of steel pipe materials and structures: X52 grade high-strength steel pipes are selected and galvanized on the surface to improve corrosion resistance and compressive strength. Laser measurement equipment is used to accurately collect size data such as the inner diameter, outer diameter, and wall thickness of the steel pipe to ensure the accuracy of the pipeline.

[0202] S2. Pretreatment of steel pipe and pipe forming: The steel pipe is heated to 700 °C using high-frequency induction heating equipment to improve the plasticity of the steel pipe and avoid cracks or deformation during subsequent welding. Groove machining is performed on the steel pipe, and the groove angle is controlled at 37° to ensure that the pipeline connection part can withstand greater pressure.

[0203] S3. Welding operation: A KUKA automatic welding robot is used for welding the inner and outer pipes. The welding current is set at 200 A and the welding speed is 30 cm / min to ensure the stability and uniformity of the welding process.

[0204] During the welding process, data such as welding current, voltage, and welding speed are collected through sensors to provide support for subsequent data analysis and quality evaluation.

[0205] S4. Nondestructive testing and data analysis: The preliminary calibration and data preprocessing algorithm are used to preliminarily correct the original welding data to ensure the accuracy of the data. According to environmental factors (such as temperature, humidity, etc.), the accuracy of the preliminary calibration results is further corrected to ensure a high-precision evaluation of the welding quality.

[0206] S5. Quality inspection: An ultrasonic flaw detection device is used to detect the welded joint, and the welding quality is verified by quantifying the detection data.

[0207] The data such as ultrasonic signal intensity and defect size are converted into sub-ratings through standardization processing, and compared with the comprehensive evaluation results to confirm whether the welded joint is qualified.

[0208] Comparative experiment:

[0209] Purpose of the experiment:

[0210] Through comparative experiments with existing technologies, the superiority of the present invention is verified, especially its advantages in welding quality control and pipeline performance evaluation.

[0211] Experimental process:

[0212] Control group: Welding is carried out using traditional welding techniques, and quality inspection is performed through manual inspection and conventional welding quality evaluation methods.

[0213] Experimental group: Welding is carried out using the new energy ship double-wall pipe construction process of the present invention, and quality inspection is performed using ultrasonic flaw detection equipment, precision calibration and environmental error correction algorithms, and a double verification mechanism.

[0214] Experimental data:

[0215]

[0216]

[0217] Analysis of experimental results:

[0218] Qualified rate of welded joints: After the experimental group adopted the process of the present invention, the qualified rate of welded joints increased by 13%, greatly reducing the occurrence of welding defects.

[0219] Average defect size of welded joints: Through ultrasonic flaw detection equipment and quality evaluation algorithms, the defect size of welded joints in the experimental group was significantly reduced, reducing the quality problems of welded joints, and the defect size was reduced by 75%.

[0220] Welding quality evaluation score: Through comprehensive performance evaluation and optimization algorithms, the welding quality of the experimental group has been significantly improved, and the score has increased by 18.75% compared with the control group.

[0221] Temperature distribution uniformity of welded joints: Due to precise temperature control and automated welding equipment, the temperature distribution of welded joints in the experimental group is more uniform, improving the stability of welding, and the temperature distribution uniformity has increased by 20%.

[0222] Production cycle: Due to precise quality inspection and optimized welding operations, the production cycle of the experimental group has been reduced by 25%, significantly improving production efficiency.

[0223] Rework rate: The rework rate of the experimental group is only 3%, which is 75% less than that of the control group, indicating that the present invention can significantly reduce welding defects and improve process stability.

[0224] Welding strength: Due to the improvement of welding quality, the welding strength of the experimental group is 28.57% higher than that of the control group, increasing the compressive capacity of the pipeline.

[0225] Welding defect detection time: Through efficient data collection and analysis, the welding defect detection time of the experimental group is greatly shortened, and the detection time is reduced by 60%, effectively improving production efficiency.

[0226] Summary: Through 8 groups of comparative experiments, the new energy ship double-wall pipe construction process provided by the present invention shows significant superiority in terms of welding quality control, pipeline performance evaluation, production efficiency and safety. The quality of the welded joints is effectively improved, the production cycle is greatly shortened, the rework rate is significantly reduced, and the welding strength is greatly improved, ultimately improving the safety and reliability of the ship pipeline system and having broad application prospects.

[0227] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A double-walled pipe construction process for new energy ships, characterized by: The following steps are involved: S1. Steel pipe material and structure selection; S2, steel pipe pretreatment and pipe forming; S3, welding operation; S4, nondestructive testing and data analysis; S5. Quality inspection.

2. A new energy ship double-walled pipe construction process according to claim 1, characterized in that: The steel pipe material and structure selection includes the following sub-steps: S11. Material selection: Use X52 grade high-strength steel pipe with galvanized surface; S12. Collect material property data T: collect the inner diameter, outer diameter and wall thickness of the steel pipe through laser measuring equipment.

3. A new energy ship double-walled pipe construction process according to claim 1, characterized in that: The steel pipe pretreatment and pipe forming comprises the following sub-steps: S21, external heating treatment: use high frequency induction heating equipment to heat the steel pipe to 700℃; S22. Beveling: Use a CNC beveling machine to bevel the steel pipe. The bevel angle is controlled at 37° and the bevel length is 20mm.

4. A new energy ship double-walled pipe construction process according to claim 1, characterized in that: The welding operation includes the following sub-steps: S31, automatic welding operation: KUKA automatic welding robot is used for inner and outer pipe welding, the welding current is set to 200A, and the welding speed is 30cm / min; S32, Data acquisition: Collect comprehensive data of welding current, welding voltage and welding speed through sensor components welding .

5. The double-walled pipe construction process for new energy ships according to claim 1 is characterized in that: The non-destructive testing and data analysis includes the following sub-steps: S41, preliminary calibration and data preprocessing: use preliminary calibration and data preprocessing algorithms to perform preliminary calibration on the original welding data to correct the deviation caused by measurement tools and environmental changes; S42, precision calibration and environmental error correction processing: Based on the preliminary calibration result output in S41, further fine correction is performed in combination with the external environmental parameter E, and the accuracy of welding quality assessment is optimized through precision calibration and environmental error correction algorithm; S43, comprehensive performance evaluation and optimization processing: Based on the results of S41 and S42, the final welding quality evaluation and pipeline performance evaluation indicators are generated through comprehensive performance evaluation and optimization algorithms, and the final results are optimized through nonlinear combination.

6. A new energy ship double-walled pipe construction process according to claim 5, characterized in that: The expression of the preliminary calibration and data preprocessing algorithm is: in C1 is the preliminary calibration result; D welding Welding data, including current, voltage, and welding speed; K1 is the welding data weight coefficient; K2 is the environmental parameter; E is the environmental parameter weight coefficient; T is the material property; K3 is the material property weight coefficient; H is the error range of the measuring tool; K4 is the error coefficient of the measuring tool; N is the normalization factor.

7. A new energy ship double-walled pipe construction process according to claim 5, characterized in that: The expression of the precision calibration and environmental error correction algorithm is: C2 = C1 × (1 + (E adj ×η) / 100); E adj = (E temperature ×K1) + (E humidity ×K2), among which: C2 is the welding quality evaluation result after precision calibration; C1 is the preliminary calibration result of the preliminary calibration and data preprocessing algorithm; E adj is the environmental adjustment factor, which is calculated based on environmental data; η is the environmental error correction coefficient.

8. A new energy ship double-walled pipe construction process according to claim 5, characterized in that: The comprehensive performance evaluation and optimization algorithm expression is: Where P is the comprehensive performance evaluation index; C2 is the accuracy calibration result; α is the weight coefficient of the preliminary calibration result; β is the weight coefficient of the accuracy calibration result; γ is the comprehensive result weight coefficient.

9. A new energy ship double-walled pipe construction process according to claim 1, characterized in that: S5 also includes the following sub-steps: S51. Quality inspection and qualification judgment: Use ultrasonic flaw detection equipment to inspect the welded joints. The inspection contents include: Signal strength threshold: If the ultrasonic signal reflection intensity is greater than -20dB, the weld joint is judged to be free of defects; Defect size: The maximum diameter of the pore is less than or equal to 0.5mm, and the length of the crack is less than or equal to 5mm; S52, standardization processing: Through standardization processing, the specific detection data in S51 is calculated into a sub-evaluation corresponding to the comprehensive evaluation result output by S43. The calculation formula is as follows C5=ω1×SignalStrength+ω2×Defect Size; Among them, C5 is the evaluation generated according to the S51 test data, which indicates the quality of the welded joint; SignalStrength is the ultrasonic reflection signal strength, measured by S51; Defect Size is the defect size, measured by S51; ω1 and ω2 are the weight coefficients of signal intensity and defect size, respectively, which are calculated by standardization; S53, data comparison: compare the evaluation generated in S52 with the comprehensive evaluation result output by S43. If the evaluation generated in S5 is consistent with the evaluation output by S43, the weld joint is qualified.

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