Processing method and system for super-high-voltage transmission tower in overseas high-altitude extremely cold area

Abstract

The application discloses an overseas high-altitude extremely cold area super-high voltage power transmission tower processing method and system, which comprises the following steps: dividing the tower processing process into multiple processing monitoring links with structural form changes as boundaries, obtaining an assembly structure qualification rate through a connection quality control real-time data supervision computer platform to form a quality control determining factor; based on the factor, evaluating whether there is a processing process deviation defect working condition in each link, and then performing deviation tracing and jig positioning precision collection to obtain flow time and welding error; through analysis of whether the test and assembly parameters meet the standards, process optimization is realized; combined with a seasonal autoregressive integrated moving average model, the low temperature resistance and corrosion resistance are evaluated, and the cutting and forming deviation points are positioned, and deviation adjustment and system optimization under man-machine interaction are completed. The application effectively guarantees the production efficiency and finished product quality of the high-reliability power transmission tower in the extremely cold area.

Description

Technical Field

[0001] This invention relates to the field of ultra-high voltage transmission tower processing, and in particular to a method and system for processing ultra-high voltage transmission towers in high-altitude and extremely cold regions overseas. Background Technology

[0002] The manufacturing of ultra-high-voltage transmission towers in high-altitude, extremely cold regions overseas faces severe challenges. These areas are characterized by extreme climates such as low temperatures, strong winds, and low oxygen levels year-round. This results in poor operational stability of processing equipment, welding quality that is easily affected by temperature fluctuations, and difficulty in ensuring the precision of component dimensional control, leading to high quality risks in the overall structure of the transmission towers. Furthermore, the manufacturing process involves the coordinated operation of multiple pieces of equipment and numerous procedures. The interplay of variables such as equipment operating status, process execution precision, and worker skill levels increases the uncertainty and probability of defects during manufacturing. Traditional processing methods lack the ability to accurately identify and dynamically adjust complex processes, making it difficult to meet the high-reliability manufacturing quality requirements of transmission towers in extremely cold overseas environments.

[0003] Current technologies mostly rely on fixed parameter settings and manual monitoring for quality control, which suffers from poor real-time performance, delayed data response, and weak defect tracing capabilities. Once process deviations or equipment malfunctions occur, it is difficult to promptly identify and accurately pinpoint their source, often relying on experience-based adjustments or post-processing rework, severely impacting production efficiency and quality stability. Furthermore, the lack of dynamic modeling and analysis capabilities for environmental factors makes it impossible to assess adaptability to external conditions such as extreme cold and strong corrosion. In addition, insufficient analytical capabilities regarding the collaborative relationships between equipment and the logical dependencies between processing steps can easily lead to the phenomenon of "local deviations accumulating into global defects" in systemic processing flows.

[0004] Therefore, there is an urgent need to propose a processing method and system for ultra-high voltage transmission towers suitable for high-altitude and extremely cold regions overseas, in order to achieve dynamic monitoring and intelligent control of the entire complex processing technology. This method and system should be able to fully adapt to environmental changes under extreme climatic conditions, overcome the technical bottlenecks of existing technologies in parameter fluctuation control, process deviation identification, equipment collaborative management, and quality traceability, and ensure the structural stability and operational reliability of the towers in harsh environments. By integrating multi-source data acquisition, intelligent algorithm evaluation, and human-computer interaction mechanisms, the processing efficiency and product quality of ultra-high voltage transmission towers in special areas such as extremely cold plateaus can be effectively improved, meeting the urgent needs of modern power transmission projects for high-performance tower equipment. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and system for processing ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions.

[0006] On the one hand, a method for manufacturing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions, the method comprising:

[0007] Step S1: Divide the ultra-high voltage transmission tower into different processing monitoring links with the changes in the tower processing form as the dividing point, and connect the different processing monitoring links to the real-time quality control data monitoring computer platform to obtain the pass rate of the tower assembly structure, and obtain the quality control determinant factors of the overseas high-altitude and extremely cold region transmission towers in different processing monitoring links.

[0008] Step S2: Based on the quality control determination factors of the power transmission towers in the high-altitude and extremely cold regions overseas, assess and decide whether the different processing monitoring links are in the process deviation defect condition.

[0009] Step S3: For all different processing monitoring links in the ultra-high voltage transmission tower that are in the process deviation defect condition, trace the source of the processing monitoring link deviation, and collect and process the fixture positioning accuracy of each different processing monitoring link in the process deviation defect condition to obtain the flow time and welding error between different processing monitoring links in the process deviation defect condition.

[0010] Step S4: Based on the flow time and welding error, assess and decide whether the test and assembly parameters do not meet the standard limit value in different processing monitoring links under the processing process deviation defect condition;

[0011] Step S5: Based on the assessment and decision results of whether the test and assembly parameters do not meet the standard limit, optimize the corresponding processing monitoring links in different processing monitoring links that are in the processing process deviation defect condition.

[0012] Step S6: Using a seasonal autoregressive integral moving average model, analyze and evaluate the processing low-temperature resistance and corrosion resistance of the test and assembly parameters that do not meet the standard limit values, and obtain the quality influencing factors from the real-time quality control data monitoring computer platform included in the test and assembly parameters that do not meet the standard limit values.

[0013] Step S7: Locate and investigate the quality influencing factors to determine the cutting and forming deviations that do not fall within the acceptable limits for the testing and assembly parameters; after tracing the source of the deviations in the processing monitoring process, adjust the visualization interface of the real-time quality control data monitoring computer platform and conduct human-computer interaction with the engineer.

[0014] Further, step S1 includes:

[0015] The processing time periods of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in ultra-high voltage transmission towers are obtained. Based on the processing time periods, the ultra-high voltage transmission towers are divided into different processing monitoring links with changes in the tower's processing shape as the dividing point. Furthermore, the working error control of the submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring links is carried out to determine the cutting and forming deviations of the ultra-high voltage transmission towers formed during the operation of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems.

[0016] The pass rate of the tower assembly structure is obtained by connecting the real-time data monitoring computer platform for quality control at different processing monitoring links. All welding current / voltage parameters, welding wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data in the welding link are obtained from the real-time data monitoring computer platform for quality control and are used as the quality control determinant of the power transmission tower in the overseas high-altitude and extremely cold region.

[0017] Further, step S2 includes:

[0018] Time series analysis algorithms were used to locate and investigate all welding current / voltage parameters and all wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data to determine the fluctuation ranges of welding current / voltage parameters and wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data at different processing monitoring stages under safe operating temperatures.

[0019] If the fluctuation range of the welding current / voltage parameters or the fluctuation range of the welding wire / electrode diameter, shielding gas flow rate, welding process adaptation parameters, and welding speed data exceeds the preset safety boundary value, then the different processing monitoring links are assessed and decided to be in a processing process deviation defect condition; if they do not exceed the preset safety boundary value, then the different processing monitoring links are assessed and decided not to be in a processing process deviation defect condition.

[0020] Further, step S3 includes:

[0021] By utilizing the historical processing defect risk nodes of ultra-high voltage transmission towers, the Bat Algorithm is used to trace the source of deviations in different processing monitoring links under the condition of processing deviation defects.

[0022] Based on the health status of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems at different processing monitoring stages where processing deviations and defects occur, all such systems are inspected and repaired. Engineers at different processing monitoring stages locate the causes of processing deviations and defects. The health status is monitored by the working status of these systems. When the working status of these systems fails to meet standards, product defects occur. The assessment and decision-making process includes the material handling efficiency, production resource scheduling optimization, assembly quality and efficiency, and facility allocation dynamics of these systems.

[0023] For each processing monitoring link under the processing process deviation defect condition, the fixture positioning accuracy is collected and processed to obtain the process coordination error and equipment coordination efficiency fluctuation range between different submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment and CNC automated machining systems within the different processing monitoring links under the processing process deviation defect condition. These are used as weighting factors for the flow time and welding error.

[0024] Further, step S4 includes:

[0025] Analyze the coordination errors of the processes to determine whether the processing load index of different submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems working together includes the risk of equipment structural abnormalities.

[0026] The fluctuation range of equipment synergy efficiency is located and investigated to determine whether all processing load indicators with structural anomalies have the same fluctuation range of equipment synergy efficiency in the ultra-high voltage transmission tower processing stage; if it exceeds the range, the assessment and decision-making test and assembly parameters are not within the compliance limit; if they do not exceed the range, the assessment and decision-making test and assembly parameters are within the compliance limit.

[0027] Further, step S5 includes:

[0028] When the test and assembly parameters are within the acceptable limits, then based on the health status of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring stages under processing process deviation and defect conditions, all such submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems will continue to be processed and produced.

[0029] When the test and assembly parameters do not meet the standard limits, manual equipment adjustments are made to all the processes involving submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in different processing monitoring stages under processing process deviation and defect conditions.

[0030] Further, step S6 includes:

[0031] Based on the cutting and forming deviations monitored by the real-time data monitoring computer platform for quality control, which are not included in the standard limit values ​​for testing and assembly parameters, a deviation size measurement signal is sent to the supervising engineer. Based on the deviation size measurement results, the quality influencing factors are fed back to the seasonal autoregressive integral moving average model, and the influence coefficient of the model is calculated.

[0032] Further, step S7 includes:

[0033] By calculating the size of the elements in the matrix of quality influencing factors, the specific time points at which the segmentation and shaping of quality influencing factors occur in the real-time quality control data monitoring computer platform are obtained.

[0034] The specific time points of the cutting and forming are located and investigated to determine whether there are process coordination errors at these specific time points. If process coordination errors exist, the corresponding real-time quality control data monitoring computer platform is identified as a cutting and forming deviation point. Furthermore, the cutting and forming deviations of the test and assembly parameters that do not belong to the compliance limit values ​​are identified, as well as the cutting and forming deviations of the real-time quality control data monitoring computer platform that do not belong to the cutting and forming deviation points.

[0035] Furthermore, step S7 also includes:

[0036] Based on the cutting and forming deviations of the real-time data monitoring computer platform for quality control that do not fall within the standard limit values ​​for the test and assembly parameters, the cutting and forming time nodes of the real-time data monitoring computer platform for quality control that do not fall within the cutting and forming deviation points are calibrated.

[0037] Based on the cutting and forming deviations of all cutting and forming deviation points that do not fall within the acceptable limits according to the test and assembly parameters, determine the cutting and forming deviations of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems connected to all cutting and forming deviation points. Then, inspect and repair all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems connected to all cutting and forming deviation points, thereby tracing the source of deviations in the processing monitoring process for all cutting and forming deviation points. Finally, adjust the visualization interface of the real-time quality control data monitoring computer platform and enable human-computer interaction with engineers.

[0038] On the other hand, a processing system for ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions includes:

[0039] The module for obtaining the quality control determinant of power transmission towers is used to divide ultra-high voltage power transmission towers into different processing and monitoring stages based on changes in the tower processing form. It connects to a real-time quality control data monitoring computer platform for different processing and monitoring stages to obtain the pass rate of the tower assembly structure and obtain the quality control determinant of power transmission towers in high-altitude and extremely cold regions overseas for different processing and monitoring stages.

[0040] The process deviation and defect assessment and decision-making module is used to assess and decide whether the different processing monitoring links are in the process deviation and defect condition based on the quality control determination factors of the overseas high-altitude and extremely cold region power transmission towers.

[0041] The turnaround time and welding error module is used to trace the source of deviations in the processing monitoring links of all processing monitoring links in the ultra-high voltage transmission tower that are in the processing process deviation defect condition, and to collect and process the fixture positioning accuracy of each processing monitoring link in the processing process deviation defect condition to obtain the turnaround time and welding error between the different processing monitoring links in the processing process deviation defect condition.

[0042] The testing and assembly parameter evaluation and decision module is used to evaluate and decide whether the testing and assembly parameters do not meet the standard limit value in different processing monitoring stages under the processing process deviation and defect conditions, based on the flow time and welding error.

[0043] The processing low-temperature resistance and corrosion resistance assessment and decision-making module is used to optimize the processing monitoring links in different processing monitoring links under the processing process deviation defect conditions based on the assessment and decision results of whether the test and assembly parameters do not belong to the compliance limit values; and to analyze and evaluate the processing low-temperature resistance and corrosion resistance of the test and assembly parameters not belonging to the compliance limit values ​​through a seasonal autoregressive integral moving average model, and obtain the quality influencing factors from the real-time quality control data monitoring computer platform included in the test and assembly parameters not belonging to the compliance limit values.

[0044] The cutting and forming deviation point assessment and decision-making module is used to locate and investigate the quality influencing factors and determine the cutting and forming deviation points where the test and assembly parameters do not meet the standard limit values.

[0045] The processing monitoring deviation traceability module is used to trace the deviations in the cutting and forming process, adjust the visualization interface of the real-time quality control data monitoring computer platform, and enable human-computer interaction with engineers.

[0046] The beneficial effects of this invention are:

[0047] This invention provides a method and system for processing ultra-high voltage transmission towers suitable for high-altitude and extremely cold regions overseas. It offers advantages such as full-process monitoring, intelligent decision-making, and high environmental adaptability, overcoming problems such as weak process control under extreme climatic conditions, limited quality traceability methods, inaccurate equipment operation status assessment, and low efficiency in deviation location and correction in existing technologies. By dividing the processing flow into multi-stage monitoring units and acquiring assembly structure pass rate and welding parameter data based on a real-time quality control data monitoring platform, the system utilizes time series analysis algorithms to intelligently identify and provide deviation warnings for fluctuation ranges in welding current, voltage, and welding material parameters, effectively identifying process deviation defects. The system introduces a bat algorithm to trace the source of abnormal operating conditions, combining equipment health status detection and process coordination error analysis to ensure the coordinated and stable operation of various processing equipment in low-temperature, high-wind, and high-altitude environments. Furthermore, the system employs a seasonal autoregressive integral moving average model to model and analyze low-temperature anti-interference capabilities and corrosion resistance, improving the overall intelligence level of quality control. Ultimately, by precisely locating the deviation points in cutting and forming, and supplementing it with visual interface control and human-computer interaction, the production efficiency and finished product quality of high-reliability power transmission towers in extremely cold regions are ensured. Attached Figure Description

[0048] Figure 1 A flowchart of a method for processing ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions provided by this invention;

[0049] Figure 2This invention provides a modular block diagram of a processing system for ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] like Figure 1 As shown, a method for manufacturing ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions includes the following steps:

[0052] Step S1: Divide the ultra-high voltage transmission tower into different processing monitoring links with the changes in the tower processing form as the dividing point, and connect the different processing monitoring links to the real-time quality control data monitoring computer platform to obtain the pass rate of the tower assembly structure, and obtain the quality control determinant factors of the overseas high-altitude and extremely cold region transmission towers in different processing monitoring links.

[0053] Specifically, in the initial stage of ultra-high voltage transmission tower manufacturing in high-altitude, extremely cold regions overseas, the entire manufacturing process needs to be meticulously divided into multiple different monitoring stages based on the changes in the tower's form. For example, the stages from the manufacturing of basic components to the assembly of components and the formation of the overall structure serve as the basis for this division. Each monitoring stage is connected to a real-time quality control data monitoring computer platform. This platform collects various key parameters, such as the dimensional accuracy of components (with an allowable error range of ±0.5 mm) and welding quality, measured by indicators such as weld strength and the number of pores. The strength must meet certain standards, and the number of pores must not exceed three per square centimeter. The platform calculates the pass rate of the assembled tower structure based on these parameters. The pass rate of different monitoring stages constitutes a decisive factor in the quality control of transmission towers in high-altitude, extremely cold regions overseas. It plays a crucial foundational role in subsequent evaluations of the quality status of each manufacturing stage, directly reflecting the performance of each stage in the overall quality control.

[0054] Step S2: Based on the quality control determinants of the power transmission tower in the high-altitude and extremely cold region overseas, assess and decide whether the different processing monitoring links are in a processing process deviation defect condition.

[0055] Specifically, based on the quality control determinants of the transmission towers obtained in step S1, in-depth evaluation and decision-making are conducted. The pass rate of each processing monitoring link is compared with the pre-set standard value. Assuming the standard pass rate is 95%, if the pass rate of a certain processing monitoring link is lower than this standard, it is determined that the link is in a processing deviation defect condition. At the same time, various parameters affecting the pass rate are analyzed. For example, excessive deviation in component dimensions may indicate a problem with the precision of the processing equipment; insufficient welding strength may indicate improper setting of welding process parameters. This step is of great significance because it can promptly identify links with potential quality problems in the processing, so that targeted measures can be taken to prevent the further production of unqualified products and ensure the safety and stability of the transmission towers in harsh environments.

[0056] Step S3: Trace the source of deviations in all different processing monitoring links in the ultra-high voltage transmission tower that are in the process deviation defect condition, and collect and process the fixture positioning accuracy of each different processing monitoring link in the process deviation defect condition to obtain the flow time and welding error between different processing monitoring links in the process deviation defect condition.

[0057] Specifically, once it is determined that different processing monitoring stages are experiencing defects due to process deviations, it is necessary to trace the source of these deviations to find the root causes, such as equipment failure or human error. Simultaneously, the fixture positioning accuracy of each problematic stage must be collected and processed. Fixture positioning accuracy is crucial; for example, its positioning deviation must be controlled within ±0.2 mm. Actual positioning data is obtained using professional measuring tools and compared with standard values ​​to calculate the deviation. Based on this data, the turnaround time between different processing stages—the interval between the completion of one stage and the start of the next—is further calculated. This reflects the smoothness of the processing flow; ideally, the turnaround time should be controlled within a short range, such as no more than 30 minutes. Welding errors, including weld size and shape deviations, are also considered, as these directly affect the structural strength of the tower. This data provides crucial information for subsequent evaluation of the overall performance of the processing stages.

[0058] Step S4: Based on the flow time and welding error, assess and decide whether the test and assembly parameters do not meet the standard limit value in different processing monitoring links under the processing process deviation defect condition;

[0059] Specifically, based on the turnaround time and welding error obtained in step S3, evaluation and decision-making are carried out. The turnaround time is compared with the preset standard turnaround time, assuming the standard turnaround time is 25 minutes. If the actual turnaround time exceeds this range, it indicates that there may be unreasonable aspects to the processing flow. For welding error, it is compared with the maximum allowable welding error standard, such as an allowable deviation of ±1 mm for weld width and ±0.5 mm for height. If the welding error exceeds the standard, or the turnaround time is too long, it is determined that the testing and assembly parameters in this processing monitoring link do not meet the standard limits. This step can identify the specific parameters in the processing link that do not meet the standards, providing accurate direction for subsequent optimization and ensuring that the processed transmission towers meet the stringent usage requirements of high-altitude and extremely cold regions.

[0060] Step S5: Based on the assessment and decision results regarding whether the test and assembly parameters do not fall within the acceptable limits, optimize the corresponding processing monitoring links in different processing monitoring links that are in the process deviation defect condition.

[0061] Specifically, based on the assessment and decision results regarding whether the testing and assembly parameters meet the standards in step S4, optimization is carried out on different processing monitoring links that are experiencing processing deviation defects. If processing accuracy issues are found to be caused by equipment aging, equipment repair or replacement can be arranged; if errors are caused by personnel's lack of proficiency, targeted training is organized. For links with excessively long turnaround times, bottlenecks in the process are analyzed, which may be due to untimely material delivery. In such cases, the material supply process is optimized to ensure that materials arrive at the processing link on time. Through these optimization measures, the quality and efficiency of the processing monitoring links are improved, resulting in more precise transmission tower components and smoother overall assembly, thereby improving product quality, reducing costs, and enhancing applicability in high-altitude and extremely cold regions overseas.

[0062] Step S6: Using a seasonal autoregressive integral moving average model, analyze and evaluate the processing low-temperature resistance and corrosion resistance of the test and assembly parameters that do not meet the standard limit value, and obtain the quality influencing factors from the real-time quality control data monitoring computer platform included in the test and assembly parameters that do not meet the standard limit value.

[0063] Specifically, a seasonal autoregressive integral moving average model is used to conduct in-depth analysis of situations where test and assembly parameters do not meet the acceptable limits. This model fully considers the seasonality, trend, and randomness of time-series data. Taking low-temperature resistance as an example, performance data of tower components under simulated low-temperature environments are collected over different time periods, such as measuring the strength change of components every hour in an environment of -30℃. The model analyzes this data to assess the impact of low temperatures on processing quality. For corrosion resistance, tower components are placed in a simulated corrosion environment, and their corrosion degree is periodically tested, such as by measuring the corrosion rate. Based on this data, the model assesses the quality influencing factors in the real-time quality control data monitoring computer platform related to non-compliance of test and assembly parameters, identifying which factors, such as material composition and processing technology, lead to problems in low-temperature resistance and corrosion resistance, providing a scientific basis for subsequent improvements.

[0064] Step S7: Locate and investigate the quality influencing factors to determine the cutting and forming deviations that do not fall within the acceptable limits for the test and assembly parameters; after tracing the source of the deviations in the processing monitoring process, adjust the visualization interface of the real-time data monitoring computer platform for quality control and conduct human-computer interaction with engineers.

[0065] Specifically, the quality influencing factors identified in step S6 are precisely located and comprehensively investigated. When investigating cutting and forming deviations, the wear of the cutting equipment's tools is carefully checked. If the tool wear exceeds a certain limit, it may lead to dimensional deviations in the cutting. The pressure and temperature parameters in the forming process are checked to ensure they meet standards; for example, the forming pressure needs to be maintained between 10-15 MPa, and the temperature between 200-250℃. After identifying the deviation points, the deviation source is traced again during the processing monitoring process to determine whether the deviation occurred in the equipment, process, or human error stages. Subsequently, the visualization interface of the real-time quality control data monitoring computer platform is adjusted to visually display the identified problems to engineers, facilitating their understanding of the overall issue. Simultaneously, human-computer interaction is implemented, allowing engineers to adjust and optimize the processing technology and equipment parameters based on the displayed information, ensuring that similar cutting and forming deviations do not recur in subsequent processing, thus guaranteeing the processing quality of the transmission towers.

[0066] The beneficial effects of the above technical solution are as follows: This method and system for processing ultra-high voltage transmission towers in extremely cold high-altitude overseas regions divides the ultra-high voltage transmission tower into different processing monitoring stages, with changes in the tower's processing form as the dividing point. Different forms of sampling are applied to these different processing monitoring stages to assess and determine whether they are in a processing technology deviation defect condition or whether the test and assembly parameters do not meet the acceptable limits. Processing monitoring stages in a processing technology deviation defect condition and those with test and assembly parameters not meeting the acceptable limits are monitored to prevent cutting and shaping of other different processing monitoring stages. Furthermore, a seasonal autoregressive integral moving average model is used to analyze the test and assembly parameters. Each cutting and forming deviation point that does not fall within the acceptable limits is investigated to identify the existing cutting and forming deviation points. These deviation points are then monitored separately, along with all other different processing monitoring points in the ultra-high voltage transmission tower awaiting construction. By dividing the ultra-high voltage transmission tower into different processing monitoring points and using zoned sampling inspections, the corresponding real-time quality control data monitoring computer platform can be quickly and accurately located. This promptly prevents cutting and forming deviation points from affecting the normal operation of other real-time quality control data monitoring computer platforms in the ultra-high voltage transmission tower, improving the efficiency and accuracy of ultra-high voltage transmission tower inspections and ensuring the overall safety and stability of the ultra-high voltage transmission tower operation.

[0067] Preferably, the real-time quality control data monitoring computer platform typically uses a variety of sensors to achieve real-time monitoring and data acquisition of the ultra-high voltage transmission tower manufacturing process, including but not limited to the following sensors and implementation methods:

[0068] Displacement sensors are used to measure parameters such as displacement and deformation of components during the manufacturing process of iron towers. For example, they monitor the relative positional changes of components during tower assembly to ensure assembly accuracy. Implementation methods include laser displacement sensors and inductive displacement sensors. Laser displacement sensors calculate the displacement of an object by emitting a laser beam and measuring the time it takes for the reflected light to pass through. Inductive displacement sensors are based on the principle of electromagnetic induction; when the measured object moves, it causes a change in the inductance within the sensor, thus measuring the displacement.

[0069] Pressure sensors are used to monitor pressure parameters during manufacturing processes. For example, during the welding of tower components, they monitor welding pressure to ensure welding quality; when using clamps to fix components, they monitor the clamping force to prevent deformation due to uneven stress. Implementation: Strain gauge pressure sensors are typically used. When subjected to pressure, the resistance of the strain gauge changes. The pressure is calculated by measuring this resistance change and then converted into an electrical signal, which is transmitted to a computer platform.

[0070] Temperature sensors are used to monitor the ambient temperature and the temperature of components during processing, especially in extremely cold, high-altitude regions overseas where temperature significantly impacts the manufacturing process. For example, during welding, they monitor the temperature at the welding point to prevent defects caused by excessively low or high temperatures; in the corrosion protection of iron towers, they monitor the temperature during coating drying to ensure coating quality. Implementation methods commonly use thermocouples or resistance temperature detectors (RTDs). Thermocouples measure temperature by utilizing the thermoelectric potential difference between two different metals at different temperatures; RTDs measure temperature based on the change in resistance of a metal material with temperature, converting the temperature signal into an electrical signal and transmitting it to a computer platform.

[0071] A vision sensor is used to acquire image information of steel tower components, inspecting their appearance, dimensions, and seam gaps. For example, it detects surface defects such as cracks and pores on steel tower components and measures the seam gap dimensions to ensure they meet requirements. Implementation: It typically consists of an industrial camera and an image acquisition card. The industrial camera captures images of the components, and the image acquisition card converts the analog image signals into digital signals, transmitting them to a computer platform. The computer platform then analyzes and processes the images using image recognition algorithms to obtain relevant inspection information.

[0072] These sensors are distributed throughout various stages of tower manufacturing. A data acquisition system converts the analog signals collected by the sensors into digital signals, which are then transmitted to a real-time quality control data monitoring computer platform according to a specific communication protocol. The computer platform analyzes, processes, and stores this data in real time. Using pre-set algorithms and models, it assesses and judges the quality of tower manufacturing. If abnormal parameters or quality problems are detected, it promptly issues early warning signals, allowing engineers to take appropriate measures for adjustment and improvement. This achieves comprehensive quality control over the entire ultra-high voltage transmission tower manufacturing process.

[0073] Preferably, in step S1, the ultra-high voltage transmission tower is divided into different processing monitoring stages based on changes in the tower's processing form. The quality control real-time data monitoring computer platform is connected to each processing monitoring stage to obtain the tower assembly structure qualification rate, thus obtaining the quality control determinants for overseas high-altitude and extremely cold region transmission towers at different processing monitoring stages, including:

[0074] The processing time periods of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in ultra-high voltage transmission towers are obtained. Based on these processing time periods, the ultra-high voltage transmission tower is divided into different processing monitoring links with changes in the tower's processing shape as the dividing point. Furthermore, the working error control of the submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring links is carried out to determine the cutting and forming deviations of the ultra-high voltage transmission tower formed by all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems during their operation.

[0075] The pass rate of the tower assembly structure was obtained by connecting the real-time data monitoring computer platform for quality control at different processing monitoring stages. All welding current / voltage parameters, welding wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data in the welding stage were obtained from the real-time data monitoring computer platform for quality control. These data were used as the determining factors for the quality control of the power transmission tower in this overseas high-altitude and extremely cold region.

[0076] The beneficial effects of the above technical solution are as follows: Ultra-high voltage (UHV) transmission towers include several submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, CNC automated machining systems, and several real-time quality control data monitoring computer platforms. These platforms are connected to the corresponding submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems, collectively forming the corresponding UHV transmission tower structure. Based on the operational connection structure of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems within the UHV transmission tower, the UHV transmission tower is divided into sections, resulting in different processing monitoring links separated by changes in the tower's processing morphology. This allows for subsequent sampling of different processing monitoring links as separate UHV transmission tower sections, improving the sampling reliability for different processing monitoring links. Some submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems are shared to connect different processing monitoring links. This allows for error control of each shared submerged arc welding machine, plasma cutting machine, CNC lathe, X-ray non-destructive testing equipment, and CNC automated machining system. It also determines the cutting and forming deviations of each shared submerged arc welding machine, plasma cutting machine, CNC lathe, X-ray non-destructive testing equipment, and CNC automated machining system during operation. This facilitates subsequent switching between standby and running states of the shared submerged arc welding machine, plasma cutting machine, CNC lathe, X-ray non-destructive testing equipment, and CNC automated machining system, using them as a benchmark, and quickly achieving traceability of deviations in different processing monitoring links.

[0077] Preferably, in step S2, based on the quality control determinant factors of the overseas high-altitude and extremely cold region transmission tower, an assessment and decision are made as to whether the different processing monitoring links are in a processing deviation defect condition, including:

[0078] Time series analysis algorithms were used to locate and investigate all welding current / voltage parameters and all wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data to determine the fluctuation ranges of welding current / voltage parameters and wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data at different processing monitoring stages under safe operating temperatures.

[0079] If the fluctuation range of the welding current / voltage parameter or the fluctuation range of the welding wire / electrode diameter, shielding gas flow rate, welding process adaptation parameters, and welding speed data exceeds the preset safety boundary value, then the assessment and decision of the different processing monitoring links is that they are in a processing process deviation defect condition; if they do not exceed the preset safety boundary value, the assessment and decision of the different processing monitoring links is that they are not in a processing process deviation defect condition.

[0080] The beneficial effects of the above technical solution are as follows: When the data fluctuation of the real-time quality control data monitoring computer platform increases suddenly in a short period of time, it indicates that there may be operational defects in the real-time quality control data monitoring computer platform. By sampling all welding current / voltage parameters and all welding wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data of the real-time quality control data monitoring computer platform included in different processing monitoring links, time series analysis algorithms are used to locate and investigate these data. This yields the fluctuation range of welding current / voltage / welding wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data of different processing monitoring links under safe operating temperatures. This allows for the assessment and decision-making regarding whether there are defects in the data flow of different processing monitoring links that do not meet the standard limits, thus achieving accurate differentiation and identification of defects in different processing monitoring links.

[0081] Preferably, in step S3, the source of deviation in the processing monitoring links of the ultra-high voltage transmission tower under processing process deviation defect conditions is traced, and the fixture positioning accuracy of each processing monitoring link under processing process deviation defect conditions is collected and processed to obtain the flow time and welding error between the different processing monitoring links under processing process deviation defect conditions, including:

[0082] Based on the health status of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring stages under processing process deviation and defect conditions, all such machines are inspected and repaired. Engineers at different processing monitoring stages locate the cause of the processing process deviation and defect conditions. The health status can be detected by the working status of the submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems. When the working status of the submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems does not meet the standards, product defects occur. The assessment and decision-making content includes the material handling efficiency, production resource scheduling optimization degree, assembly quality and efficiency, and facility allocation dynamics of the submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems.

[0083] For each processing monitoring link under the processing process deviation defect condition, the fixture positioning accuracy is collected and processed to obtain the process coordination error and equipment coordination efficiency fluctuation range between different submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment and CNC automated machining systems within the different processing monitoring links under the processing process deviation defect condition. These are used as weighting factors for the flow time and welding error.

[0084] The beneficial effects of the above technical solution are as follows: By identifying the cutting and forming deviations of all related submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in different processing monitoring stages under processing deviation defect conditions, the cutting and forming deviations can be used as a benchmark to inspect all related shared submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems. This enables monitoring of different processing monitoring stages under processing deviation defect conditions, avoiding data interaction between these stages and other different processing monitoring stages. Furthermore, separate fixture positioning accuracy data acquisition and processing can be performed on different processing monitoring stages under processing deviation defect conditions, effectively reducing the workload of fixture positioning accuracy data acquisition and processing and ensuring the reliability of data sampling for fixture positioning accuracy data acquisition and processing.

[0085] Preferably, in step S4, based on the flow time and welding error, an assessment and decision are made regarding whether test and assembly parameters at different processing monitoring stages under processing deviation defect conditions fall outside the acceptable limits, including:

[0086] The process coordination error of this coordination is analyzed to determine whether the processing load index of different submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems working together includes the risk of equipment structural abnormalities.

[0087] The equipment's synergistic performance fluctuation range was located and investigated to determine whether all processing load indicators with structural anomalies risked by the equipment had the same equipment synergistic performance fluctuation range in the ultra-high voltage transmission tower processing stage. If the fluctuation range was exceeded, the assessment and decision-making test and assembly parameters were not within the acceptable limits; if the fluctuation range was not exceeded, the assessment and decision-making test and assembly parameters were within the acceptable limits.

[0088] The beneficial effects of the above technical solution are as follows: By using the above method, the processing load index obtained from the collection and processing of fixture positioning accuracy is analyzed to assess and decide whether the processing load index contains equipment structural anomaly risks; wherein, equipment structural anomaly risks may be, but are not limited to, features corresponding to predetermined types of cutting and forming; and the equipment collaborative efficiency fluctuation range of the processing load index is identified to determine whether the equipment collaborative efficiency fluctuation range of all processing load indices with equipment structural anomaly risks is the same, thereby reliably identifying, assessing and deciding whether the test and assembly parameters in different current processing monitoring links do not meet the standard limits.

[0089] Preferably, in step S5, based on the assessment and decision results regarding whether the test and assembly parameters do not fall within the acceptable limits, the corresponding processing monitoring links in different processing monitoring links under the processing process deviation defect condition are optimized, specifically including:

[0090] When the test and assembly parameters are within the acceptable limits, then based on the health status of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring stages under processing process deviation and defect conditions, all such submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems will continue to be processed and produced.

[0091] When the test and assembly parameters do not meet the standard limits, manual equipment adjustments are made to all the processes involving submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in different processing monitoring stages under processing process deviation and defect conditions.

[0092] The beneficial effects of the above technical solution are as follows: By performing manual equipment debugging on all links involving submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems, and by continuing to process and produce all shared submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems associated with different processing monitoring links whose non-testing and assembly parameters do not meet the standard limits, the scope of investigation for different processing monitoring links in ultra-high voltage transmission towers can be further narrowed, thereby reducing the workload of subsequent sampling and ensuring that other different processing monitoring links whose non-testing and assembly parameters do not meet the standard limits are connected to the network in a timely manner, thus ensuring the normal operation of ultra-high voltage transmission towers.

[0093] Preferably, in step S6, a seasonal autoregressive integral moving average model is used to analyze and evaluate the processing low-temperature resistance and corrosion resistance of the test and assembly parameters that do not fall within the compliance limit values. This yields the quality influencing factors from the real-time quality control data monitoring computer platform that include these factors, specifically:

[0094] Based on the cutting and forming deviations monitored by the real-time data monitoring computer platform, which is not included in the standard limit values ​​for testing and assembly parameters, a deviation size measurement signal is sent to the supervising engineer. Based on the deviation size measurement results, the quality influencing factors are fed back to the seasonal autoregressive integral moving average model, and the influence coefficient of the model is calculated.

[0095] The beneficial effects of the above technical solution are as follows: By means of the above method, the cutting and forming deviation of the quality control real-time data monitoring computer platform is calibrated for the test and assembly parameters that are not included in the compliance limit value. By setting a seasonal autoregressive integral moving average model, the quality control real-time data monitoring computer platform is induced to interact with the seasonal autoregressive integral moving average model, which facilitates further identification of whether the quality control real-time data monitoring computer platform belongs to the cutting and forming deviation point.

[0096] Preferably, in step S7, the quality influencing factors are located and investigated to determine the cutting and forming deviations where the test and assembly parameters do not fall within the acceptable limits. This specifically includes:

[0097] By calculating the size of the elements in the matrix of the quality influencing factors, the specific time points at which the segmentation and shaping of the quality influencing factors occur in the real-time quality control data monitoring computer platform are obtained.

[0098] The specific time point of the cutting and forming process is located and investigated to determine whether there is a process coordination error at that specific time point. If a process coordination error exists, the corresponding real-time quality control data monitoring computer platform is identified as a cutting and forming deviation point. Furthermore, the cutting and forming deviations that do not belong to any of the standard limit values ​​for the test and assembly parameters, as well as the cutting and forming deviations of the real-time quality control data monitoring computer platform that do not belong to any of the cutting and forming deviation points, are identified.

[0099] The beneficial effects of the above technical solution are as follows: by feeding back quality influencing factors from the real-time quality control data monitoring computer platform and calculating the influence coefficients of the model, the size of the elements in the matrix is ​​calculated and the specific time nodes of cutting and forming are identified. This can accurately identify the cutting and forming deviation points that do not belong to the standard limit values ​​in the test and assembly parameters. The identification of cutting and forming deviation points facilitates the subsequent accurate monitoring of the processing of cutting and forming deviation points and the calibration of cutting and forming time nodes.

[0100] Preferably, in step S7, after tracing the source of deviations in the processing monitoring of the cutting and forming deviation points, the visualization interface of the real-time quality control data monitoring computer platform is adjusted, and human-computer interaction with engineers is conducted, specifically including:

[0101] Based on the testing and assembly parameters, which are not among the acceptable limits and do not fall under the cutting and forming deviation points of the real-time data monitoring computer platform for quality control, the cutting and forming time nodes of the real-time data monitoring computer platform that do not fall under the cutting and forming deviation points are calibrated.

[0102] Based on the testing and assembly parameters, the cutting and forming deviations of all cutting and forming deviation points that do not fall within the acceptable limits are determined. This involves identifying the cutting and forming deviations of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems connected to these deviation points. This allows for the inspection and repair of all these systems, enabling the traceability of deviations in the processing monitoring process. Furthermore, the visualization interface of the real-time quality control data monitoring computer platform is adjusted, and human-computer interaction with engineers is implemented.

[0103] The beneficial effects of the above technical solution are as follows: By using the above method, all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems connected to all cutting and forming deviation points can be inspected and repaired. This allows for targeted monitoring of the processing links and calibration of cutting and forming time nodes for the cutting and forming deviation points. As a result, the cutting and forming source can be quickly and accurately located even when there is no need to work on the ultra-high voltage transmission tower.

[0104] like Figure 2 As shown, a processing system for ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions includes:

[0105] The module for obtaining the quality control determinant of power transmission towers is used to divide ultra-high voltage power transmission towers into different processing and monitoring stages based on changes in the tower processing form. It connects to a real-time quality control data monitoring computer platform for different processing and monitoring stages to obtain the pass rate of the tower assembly structure and obtain the quality control determinant of power transmission towers in high-altitude and extremely cold regions overseas for different processing and monitoring stages.

[0106] The process deviation and defect assessment and decision-making module is used to assess and decide whether different processing monitoring links are in a process deviation and defect condition based on the quality control determination factors of the power transmission tower in the overseas high-altitude and extremely cold region.

[0107] The turnaround time and welding error module is used to trace the source of deviations in the processing monitoring links of all processing monitoring links under the processing process deviation defect conditions in the ultra-high voltage transmission tower, and to collect and process the fixture positioning accuracy of each processing monitoring link under the processing process deviation defect conditions to obtain the turnaround time and welding error between the different processing monitoring links under the processing process deviation defect conditions.

[0108] The testing and assembly parameter evaluation and decision module is used to evaluate and decide whether the testing and assembly parameters do not meet the standard limit value in different processing monitoring stages under the processing process deviation and defect conditions, based on the flow time and welding error.

[0109] The processing low-temperature resistance and corrosion resistance assessment and decision-making module is used to optimize the processing monitoring links in different processing monitoring links under the processing process deviation defect conditions based on the assessment and decision results of whether the test and assembly parameters do not fall within the standard limit value; the processing low-temperature resistance and corrosion resistance are analyzed and evaluated by using a seasonal autoregressive integral moving average model when the test and assembly parameters do not fall within the standard limit value, and the quality influencing factors from the real-time quality control data monitoring computer platform included in the test and assembly parameters not falling within the standard limit value are obtained;

[0110] The Cutting and Forming Deviation Point Assessment and Decision Module is used to locate and investigate the quality influencing factors, and to determine the cutting and forming deviation points where the test and assembly parameters do not meet the standard limits.

[0111] The process monitoring deviation traceability module is used to trace the deviation of the cutting and forming deviation points in the process monitoring process, adjust the visualization interface of the real-time quality control data monitoring computer platform, and enable human-computer interaction with engineers.

[0112] As can be seen from the above embodiments, this method and system for processing ultra-high voltage transmission towers in extremely cold high-altitude overseas regions divides the ultra-high voltage transmission tower into different processing monitoring stages, with changes in the tower's processing form as the dividing point. Different forms of sampling are performed on these different processing monitoring stages to assess and determine whether they are in a processing technology deviation defect condition or whether the test and assembly parameters do not meet the acceptable limits. Processing monitoring stages in a processing technology deviation defect condition and those with test and assembly parameters not meeting the acceptable limits are monitored to prevent cutting and shaping of other different processing monitoring stages. Furthermore, seasonal autoregressive integral sliding flattening is utilized. The model investigates each cutting and forming deviation point that does not fall within the acceptable limits for testing and assembly parameters, identifies the existing cutting and forming deviation points, and performs separate processing monitoring for these deviation points, as well as monitoring of all other different processing monitoring points in the ultra-high voltage transmission tower awaiting construction. By dividing the ultra-high voltage transmission tower into different processing monitoring points and conducting zonal sampling inspections, it quickly and accurately locates the corresponding real-time quality control data monitoring computer platform, promptly preventing cutting and forming deviation points from affecting the normal operation of other real-time quality control data monitoring computer platforms in the ultra-high voltage transmission tower, thereby improving the efficiency and accuracy of ultra-high voltage transmission tower inspections.

[0113] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for processing ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions, characterized in that... The method includes: Step S1: Divide the ultra-high voltage transmission tower into different processing monitoring links with the changes in the tower processing form as the dividing point, and connect the different processing monitoring links to the real-time quality control data monitoring computer platform to obtain the pass rate of the tower assembly structure, and obtain the quality control determinant factors of the overseas high-altitude and extremely cold region transmission towers in different processing monitoring links. Step S2: Based on the quality control determination factors of the power transmission towers in the high-altitude and extremely cold regions overseas, assess and decide whether the different processing monitoring links are in the process deviation defect condition. Step S3: For all different processing monitoring links in the ultra-high voltage transmission tower that are in the process deviation defect condition, trace the source of the processing monitoring link deviation, and collect and process the fixture positioning accuracy of each different processing monitoring link in the process deviation defect condition to obtain the flow time and welding error between different processing monitoring links in the process deviation defect condition. Step S4: Based on the flow time and welding error, assess and decide whether the test and assembly parameters do not meet the standard limit value in different processing monitoring links under the processing process deviation defect condition; Step S5: Based on the assessment and decision results of whether the test and assembly parameters do not meet the standard limit, optimize the corresponding processing monitoring links in different processing monitoring links that are in the processing process deviation defect condition. Step S6: Using a seasonal autoregressive integral moving average model, analyze and evaluate the processing low-temperature resistance and corrosion resistance of the test and assembly parameters that do not meet the standard limit values, and obtain the quality influencing factors from the real-time quality control data monitoring computer platform included in the test and assembly parameters that do not meet the standard limit values. Step S7: Locate and investigate the quality influencing factors to determine the cutting and forming deviations that do not fall within the standard limit values ​​for the testing and assembly parameters; after tracing the source of the deviations in the processing monitoring process, adjust the visualization interface of the real-time quality control data monitoring computer platform and conduct human-computer interaction with the engineer. Step S1 includes: The processing time periods of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in ultra-high voltage transmission towers are obtained. Based on the processing time periods, the ultra-high voltage transmission towers are divided into different processing monitoring links with changes in the tower's processing shape as the dividing point. Furthermore, the working error control of the submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring links is carried out to determine the cutting and forming deviations of the ultra-high voltage transmission towers formed during the operation of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems. The pass rate of the tower assembly structure is obtained by connecting the real-time data monitoring computer platform for quality control at different processing monitoring links. All welding current / voltage parameters, all welding wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data in the welding link are obtained from the real-time data monitoring computer platform for quality control and are used as the quality control determinant of the power transmission tower in the overseas high-altitude and extremely cold region. Step S2 includes: Time series analysis algorithms were used to locate and investigate all welding current / voltage parameters and all wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data to determine the fluctuation ranges of welding current / voltage parameters and wire / electrode diameters, shielding gas flow rates, welding process adaptation parameters, and welding speed data at different processing monitoring stages under safe operating temperatures. If the fluctuation range of the welding current / voltage parameters or the fluctuation range of the welding wire / electrode diameter, shielding gas flow rate, welding process adaptation parameters, and welding speed data exceeds the preset safety boundary value, then the different processing monitoring links are assessed and decided to be in a processing process deviation defect condition; if they do not exceed the preset safety boundary value, then the different processing monitoring links are assessed and decided not to be in a processing process deviation defect condition. Step S3 includes: By utilizing the historical processing defect risk nodes of ultra-high voltage transmission towers, the Bat Algorithm is used to trace the source of deviations in different processing monitoring links under the condition of processing deviation defects. Based on the health status of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring stages that are experiencing processing process deviation defects, all of these systems will be inspected and repaired. Engineers at different processing monitoring stages will then locate the cause of the processing process deviation defects. The health status is monitored through the working status of submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems. When the working status of these systems fails to meet standards, product defects occur. The assessment and decision-making process includes the material handling efficiency, production resource scheduling optimization, assembly quality and efficiency, and facility allocation dynamics of these systems. For each processing monitoring link under the processing process deviation defect condition, the fixture positioning accuracy is collected and processed to obtain the process coordination error and equipment coordination efficiency fluctuation range between different submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment and CNC automated machining systems within the different processing monitoring links under the processing process deviation defect condition. These are used as weighting factors for the flow time and welding error.

2. The method for processing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions as described in claim 1, characterized in that: Step S4 includes: Analyze the coordination errors of the processes to determine whether the processing load index of different submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems working together includes the risk of equipment structural abnormalities. The fluctuation range of equipment synergy efficiency is located and investigated to determine whether all processing load indicators with structural anomalies have the same fluctuation range of equipment synergy efficiency in the ultra-high voltage transmission tower processing stage. If the fluctuation range is exceeded, the assessment and decision-making test and assembly parameters are not within the compliance limit; if the fluctuation range is not exceeded, the assessment and decision-making test and assembly parameters are within the compliance limit.

3. The method for processing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions as described in claim 1, characterized in that: Step S5 includes: When the test and assembly parameters are within the acceptable limits, then based on the health status of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems involved in different processing monitoring stages under processing process deviation and defect conditions, all such submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems will continue to be processed and produced. When the test and assembly parameters do not meet the standard limits, manual equipment adjustments are made to all the processes involving submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems in different processing monitoring stages under processing process deviation and defect conditions.

4. The method for processing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions as described in claim 1, characterized in that: Step S6 includes: Based on the cutting and forming deviations monitored by the real-time data monitoring computer platform for quality control, which are not included in the standard limit values ​​for testing and assembly parameters, a deviation size measurement signal is sent to the supervising engineer. Based on the deviation size measurement results, the quality influencing factors are fed back to the seasonal autoregressive integral moving average model, and the influence coefficient of the model is calculated.

5. The method for processing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions as described in claim 1, characterized in that: Step S7 includes: By calculating the size of the elements in the matrix of quality influencing factors, the specific time points at which the segmentation and shaping of quality influencing factors occur in the real-time quality control data monitoring computer platform are obtained. The specific time points of the cutting and forming are located and investigated to determine whether there are process coordination errors at these specific time points. If process coordination errors exist, the corresponding quality control real-time data monitoring computer platform is identified as a cutting and forming deviation point. Furthermore, the cutting and forming deviations of the test and assembly parameters that do not belong to the compliance limit values ​​are identified, as well as the cutting and forming deviations of the quality control real-time data monitoring computer platform that do not belong to the cutting and forming deviation points.

6. The method for processing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions as described in claim 5, characterized in that: Step S7 further includes: Based on the cutting and forming deviations of the real-time data monitoring computer platform for quality control that do not fall within the standard limit values ​​for the test and assembly parameters, the cutting and forming time nodes of the real-time data monitoring computer platform for quality control that do not fall within the cutting and forming deviation points are calibrated. Based on the cutting and forming deviations of all cutting and forming deviation points that do not fall within the acceptable limits according to the test and assembly parameters, determine the cutting and forming deviations of all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems connected to all cutting and forming deviation points. Then, inspect and repair all submerged arc welding machines, plasma cutting machines, CNC lathes, X-ray non-destructive testing equipment, and CNC automated machining systems connected to all cutting and forming deviation points, thereby tracing the source of deviations in the processing monitoring process for all cutting and forming deviation points. Finally, adjust the visualization interface of the real-time quality control data monitoring computer platform and enable human-computer interaction with engineers.

7. A processing system for ultra-high voltage power transmission towers in extremely cold, high-altitude overseas regions, characterized in that, This system is applied to a method for processing ultra-high voltage transmission towers in extremely cold, high-altitude overseas regions, as described in claim 1, comprising: The module for obtaining the quality control determinant of power transmission towers is used to divide ultra-high voltage power transmission towers into different processing and monitoring stages based on changes in the tower processing form. It connects to a real-time quality control data monitoring computer platform for different processing and monitoring stages to obtain the pass rate of the tower assembly structure and obtain the quality control determinant of power transmission towers in high-altitude and extremely cold regions overseas for different processing and monitoring stages. The process deviation and defect assessment and decision-making module is used to assess and decide whether the different processing monitoring links are in the process deviation and defect condition based on the quality control determination factors of the overseas high-altitude and extremely cold region power transmission towers. The turnaround time and welding error module is used to trace the source of deviations in the processing monitoring links of all processing monitoring links in the ultra-high voltage transmission tower that are in the processing process deviation defect condition, and to collect and process the fixture positioning accuracy of each processing monitoring link in the processing process deviation defect condition to obtain the turnaround time and welding error between the different processing monitoring links in the processing process deviation defect condition. The testing and assembly parameter evaluation and decision module is used to evaluate and decide whether the testing and assembly parameters do not meet the standard limit value in different processing monitoring stages under the processing process deviation and defect conditions, based on the flow time and welding error. The processing low-temperature resistance and corrosion resistance assessment and decision-making module is used to optimize the processing monitoring links in different processing monitoring links under the processing process deviation defect conditions based on the assessment and decision results of whether the test and assembly parameters do not belong to the compliance limit values; and to analyze and evaluate the processing low-temperature resistance and corrosion resistance of the test and assembly parameters not belonging to the compliance limit values ​​through a seasonal autoregressive integral moving average model, and obtain the quality influencing factors from the real-time quality control data monitoring computer platform included in the test and assembly parameters not belonging to the compliance limit values. The cutting and forming deviation point assessment and decision-making module is used to locate and investigate the quality influencing factors and determine the cutting and forming deviation points where the test and assembly parameters do not belong to the standard limit values. The processing monitoring deviation traceability module is used to trace the deviations in the cutting and forming process, adjust the visualization interface of the real-time quality control data monitoring computer platform, and enable human-computer interaction with engineers.

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