Pressure Pipeline Inspection System

Abstract

The present invention belongs to the technical field of pipeline detection, and specifically relates to a pressure pipeline detection system, including a detection module, a preprocessing module, a local pipeline analysis module, a superposition effect analysis module and a feedback module; the detection module includes a first monitoring unit, a second monitoring unit and a third monitoring unit; the preprocessing module includes a processing unit and a standardization unit; the local pipeline analysis module includes an inner wall state analysis unit, an influence unit and an early warning unit; the superposition effect analysis module includes a flow classification unit and an effect analysis unit; the feedback module includes a comparison unit and a feedback management unit. The present invention further improves the detection accuracy of the pressure pipeline by comprehensively considering weld defects, flow resistance, flow state and their superposition effects, optimizes pipeline maintenance and management, and thus ensures the safety and efficiency of the system.

Description

Technical Field

[0001] The invention belongs to the technical field of pipeline detection, and in particular relates to a pressure pipeline detection system. Background Art

[0002] Pressure piping system is an important field in industrial piping system, which is mainly used for various fluid transportation and transmission tasks. Pressure piping plays a vital role in many industries such as petrochemical, energy and electricity. In these piping systems, welding joints are the key parts connecting various pipe sections, and their quality directly affects the operating efficiency and safety of the entire piping system.

[0003] At present, the inspection of pressure pipelines mainly relies on traditional inspection methods. Traditional methods can usually detect static defect information, but it is difficult to analyze the dynamic impact of multiple welds on flow resistance in many aspects. In the actual operation of pressure pipelines, the flatness and welding quality of each weld will affect the flow state of the fluid in the pipeline, thereby affecting the flow resistance of the pipeline. When the weld is not flat enough or has defects, it may cause abnormal changes in flow resistance, and these anomalies may be superimposed. Therefore, the analysis of the superposition effect of flow resistance needs to be paid attention to and analyzed, which makes traditional inspection methods have room for further improvement. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a pressure pipeline detection system, which further improves the detection accuracy of the pressure pipeline and optimizes pipeline maintenance and management by comprehensively considering weld defects, flow resistance, flow state and their superposition effects.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a pressure pipeline detection system, including a detection module, a preprocessing module, a local pipeline analysis module, a superposition effect analysis module and a feedback module;

[0006] The detection module is used to preselect a section of a straight pressure pipe and monitor the edge conditions of adjacent parent materials in the section of the straight pressure pipe to record relevant weld connection data information, and monitor relevant pressure state data information and pipe condition data information around each weld to construct a detection data set;

[0007] The preprocessing module is used to preprocess the relevant data information in the detection data set, and standardize the processed relevant data information according to the dimensionless processing technology to unify the units;

[0008] The local pipeline analysis module is used to construct the flatness coefficient Pzxs of the welds at the edges of each adjacent parent material based on the relevant weld connection data information, and extract the flow resistance Lzz from the relevant pressure state data information to analyze the influence of Pzxs on Lzz at the corresponding part, and construct the influence coefficient Yxs. If there is an influence, a troubleshooting instruction is issued;

[0009] The superposition effect analysis module is used to construct the Reynolds number Re based on the pipe condition data information after receiving the troubleshooting instruction, judge the flow state of the fluid in each part, distinguish it, and analyze the difference mean Clz between adjacent flow resistances under the laminar flow state. avg and the mean difference Tlz between adjacent flow resistances in turbulent state avg , and combined with Clz avg and Tlz avg , calculate the comparison value Bdz;

[0010] The feedback module is used to pre-set the evaluation threshold Q and compare and analyze Q with Bdz to determine whether there is a superposition phenomenon in the pressure pipeline.

[0011] Preferably, the detection module includes a first monitoring unit, a second monitoring unit and a third monitoring unit;

[0012] The first monitoring unit is used to monitor the edge conditions of adjacent parent materials in the cut straight pressure pipe section to obtain and record relevant weld connection data information, wherein the relevant weld connection data information includes the residual height value Yg and the undercut depth Ybsd at each adjacent parent material edge weld;

[0013] The second monitoring unit is used to monitor the relevant pressure state data information around each weld in real time, wherein the relevant pressure state data information includes the flow resistance Lz of the rear side of the adjacent parent material edge at each detection time point under the laminar flow state. after , flow resistance Lz at the front part before , and the flow resistance Lzz at the rear side of the adjacent parent material edge at each detection time point under turbulent conditions after , flow resistance Lzz at the front part before ;

[0014] The third monitoring unit is used to monitor and record the pipe condition data information of the pressure pipe in advance, wherein the pipe condition data information includes the fluid density in the pressure pipe. , fluid velocity v, pressure pipe diameter D and fluid viscosity .

[0015] Preferably, the preprocessing module includes a processing unit and a standardization unit;

[0016] The processing unit is used to monitor abnormal values ​​and missing values ​​in relevant weld connection data information, relevant pressure state data information and pipe condition data information, and remove abnormal values ​​and fill in missing values;

[0017] The standardization unit is used to uniformly format the relevant data information in the detection data set using dimensionless processing technology, so that the collected relevant data information can adapt to different statistical and machine learning algorithms.

[0018] Preferably, the local pipeline analysis module includes an inner wall state analysis unit, an impact unit and an early warning unit;

[0019] The inner wall state analysis unit is used to perform dimensionless processing on the excess height value Yg and the undercut depth Ybsd according to the relevant weld connection data information, and map the corresponding data values ​​in the interval [0, 1], and then construct the flatness state coefficient Pzxs of the weld at the edge of each adjacent parent material according to the following formula:

[0020] ;

[0021] Where i=1, 2, 3, ..., n, n represents the number of reinforcements generated at the corresponding weld, j=1, 2, 3, ..., J, J represents the number of undercuts generated at the corresponding weld, represents the i-th reinforced height value at the corresponding weld, represents the mean value of the reinforcement at the corresponding weld. represents the jth undercut depth at the corresponding weld, represents the mean value of the undercut depth at the corresponding weld, α and β are weight values, and C represents the correction constant, where 0<α≤1, 0<β≤1, and α+β=1.

[0022] Preferably, the influence unit is used to analyze the influence of the flatness coefficient Pzxs of the weld at the edge of the adjacent parent material on the flow resistance Lzz of the corresponding part to construct the influence coefficient Yxs, which is specifically obtained in the following manner:

[0023] ;

[0024] Where k=1, 2, 3, ..., K, K represents the number of welding points, represents the flatness coefficient at the edge of the kth adjacent parent material, It represents the average value of the flatness coefficient at the edges of adjacent parent materials in the straight pipe section of the cut-off pressure. represents the flow resistance at the rear side of the kth adjacent parent material edge, It represents the average value of the flow resistance at the rear side of the adjacent parent material edge in the straight pipe section with this cut-off pressure.

[0025] Preferably, the early warning unit is used to determine whether the welding state affects the fluid flow in the pressure pipeline according to the value of the influence coefficient Yxs. The specific analysis content is as follows:

[0026] If the influence coefficient Yxs does not fall within the preset safety threshold range, it is judged that the welding state has an impact on the fluid flow in the pressure pipeline, and an external inspection instruction is issued;

[0027] If the influence coefficient Yxs falls within the preset safety threshold range, it is determined that the welding state has no influence on the fluid flow in the pressure pipeline. At this time, no additional troubleshooting instructions will be issued.

[0028] Preferably, the superposition effect analysis module includes a flow condition classification unit and an effect analysis unit;

[0029] The flow classification unit is used to construct the Reynolds number Re based on the troubleshooting instructions issued by the early warning unit and combined with the pipe condition data information. Re is obtained by the following formula:

[0030] ;

[0031] According to the Re value, the flow state of the fluid in each part is judged. The specific judgment method is as follows:

[0032] If Re < 2000, it means that the current position is in laminar flow state;

[0033] If Re>4000, it means the current position is in a turbulent state;

[0034] If 2000≤Re≤4000, it means that the current position is in a transition state between laminar flow and turbulent flow.

[0035] Preferably, the effect analysis unit is used to analyze the difference mean values ​​Clz between adjacent flow resistances under the laminar flow state after distinguishing the flow state of the fluid. avg and the mean difference Tlz between adjacent flow resistances in turbulent state avg , which can be obtained by:

[0036] ;

[0037] In the formula, m represents, h=1, 2, 3, ..., m, It represents the flow resistance at the rear side of the kth adjacent parent material edge at the hth detection time point under laminar flow conditions. It represents the flow resistance at the front side of the kth adjacent parent material edge at the h-1th detection time point under laminar flow state;

[0038] ;

[0039] In the formula, It represents the flow resistance at the rear side of the kth adjacent parent material edge at the hth detection time point under turbulent conditions, It represents the flow resistance at the front side of the kth adjacent parent material edge at the h-1th detection time point under turbulent state;

[0040] According to Clz avg and Tlz avg , calculate the comparison value Bdz:

[0041] .

[0042] Preferably, the feedback module includes a comparison unit and a feedback management unit;

[0043] The comparison unit is used to compare and analyze the comparison value Bdz with the evaluation threshold Q to determine whether there is a superposition phenomenon in the pressure pipeline. The specific contents are as follows:

[0044] If Bdz exceeds Q, it is determined that there is a superposition phenomenon in the pressure pipeline, and a processing instruction will be issued;

[0045] If Bdz does not exceed Q, it is determined that there is no superposition phenomenon in the pressure pipeline, and no processing instruction is issued at this time.

[0046] Preferably, the feedback management unit is used to use non-destructive testing technology to inspect the adjacent parent material edges at the corresponding position after receiving the processing instructions issued by the comparison unit to confirm the severity of the weld, and after reconfirming the position, size and depth of the gap, use grinding to clean the welding area, and then post-process the welding area, and the post-processing includes heat treatment and deburring.

[0047] The present invention has the following beneficial effects:

[0048] The present invention further ensures the versatility and accuracy of the data by detecting the data set, providing a reliable basis for subsequent analysis; by calculating the flatness coefficient Pzxs of the weld and combining it with the flow resistance Lzz, the influence of the weld flatness on the flow resistance is analyzed. This analysis helps to identify the actual influence of weld defects on the flow resistance, and can effectively discover potential anomalies and problems. The superposition effect analysis module constructs the Reynolds number Re according to the pipe condition data information, judges the flow state of the fluid, and analyzes the mean difference of the flow resistance under laminar and turbulent states respectively. This comprehensive analysis can reveal the superposition effect of flow resistance, which is of great significance for understanding fluid behavior and improving pipeline performance.

[0049] The present invention can intelligently determine whether there is a superposition phenomenon in the pipeline by setting an evaluation threshold Q and comparing it with the comparison value Bdz. This intelligent feedback mechanism ensures that a troubleshooting instruction can be issued in time when an abnormality is detected, helping engineers to take measures quickly and further avoid potential system performance degradation or safety hazards. By comprehensively considering weld defects, flow resistance, flow state and their superposition effects, the detection accuracy of pressure pipelines can be further improved, and pipeline maintenance and management can be optimized, thereby ensuring the safety and efficiency of the system.

[0050] In the specific pressure pipeline inspection process, the present invention pays attention to the status of each weld, such as excess height, undercut and other defects. These defects may lead to increased local flow resistance and affect the flow efficiency of the entire system. Therefore, accurately analyzing the impact of the flatness of the weld on the flow resistance and determining whether there is a superposition effect are the core tasks to further ensure the stability and performance of the pipeline system.

[0051] The present invention helps to identify possible welding defects through accurate evaluation of weld flatness, thereby improving the quality control of pipelines. The influence unit constructs the influence coefficient by analyzing the relationship between the flatness coefficient of the weld and the flow resistance. This analysis method helps to understand how flatness defects affect the flow resistance, thereby providing scientific guidance for maintaining and optimizing the pipeline system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a block diagram flowchart of the present invention. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present invention are described clearly and completely below in conjunction with the accompanying drawings.

[0054] Example 1

[0055] like Figure 1 As shown, the pressure pipeline detection system includes a detection module, a preprocessing module, a local pipeline analysis module, a superposition effect analysis module and a feedback module;

[0056] The detection module is used to preselect a section of a straight pressure pipe and monitor the edge conditions of adjacent parent materials in the section of the straight pressure pipe to record relevant weld connection data information, and monitor relevant pressure state data information and pipe condition data information around each weld to construct a detection data set;

[0057] The preprocessing module is used to preprocess the relevant data information in the detection data set, and standardize the processed relevant data information according to the dimensionless processing technology to unify the units;

[0058] The local pipeline analysis module is used to construct the flatness coefficient Pzxs of the welds at the edges of each adjacent parent material based on the relevant weld connection data information, and extract the flow resistance Lzz from the relevant pressure state data information to analyze the influence of Pzxs on Lzz at the corresponding part, and construct the influence coefficient Yxs. If there is an influence, a troubleshooting instruction is issued;

[0059] The superposition effect analysis module is used to construct the Reynolds number Re based on the pipe condition data information after receiving the troubleshooting instruction, judge the flow state of the fluid in each part, distinguish it, and analyze the difference mean Clz between adjacent flow resistances under the laminar flow state. avg and the mean difference Tlz between adjacent flow resistances in turbulent state avg , and combined with Clz avg and Tlz avg , calculate the comparison value Bdz;

[0060] The feedback module is used to pre-set the evaluation threshold Q and compare and analyze Q with Bdz to determine whether there is a superposition phenomenon in the pressure pipeline.

[0061] During the operation of this system, the detection module conducts detailed monitoring of the straight pressure pipe section. The system can further accurately record the weld connection data information, pressure status data information and pipe condition data information. This comprehensive data collection provides a variety of basic data for subsequent analysis, which helps to accurately evaluate the status of the weld and its impact on pipeline performance. The preprocessing module standardizes the detection data through dimensionless processing technology, unifies the units, and ensures the consistency and comparability of the data. This process eliminates the differences between different data sources, making subsequent analysis more accurate and reliable.

[0062] The local pipeline analysis module constructs the weld flatness coefficient Pzxs based on the weld connection data information and analyzes its impact on the flow resistance. The module can accurately calculate the influence coefficient Yxs and issue troubleshooting instructions in a timely manner to ensure that the detection and treatment of weld defects are more targeted. The superposition effect analysis module determines the fluid flow state based on the Reynolds number Re, and analyzes the difference in flow resistance under laminar and turbulent states respectively. By calculating the comparison value Bdz, the superposition effect of flow resistance can be effectively identified and quantified, thereby more accurately evaluating the actual operating status of the pipeline system. The feedback module automatically determines whether there is a superposition phenomenon by comparing and analyzing the comparison value Bdz with the preset evaluation threshold. This automated feedback mechanism can detect potential problems in a timely manner, reduce the workload of manual inspection, and improve the response speed and processing efficiency of the system.

[0063] Example 2

[0064] like Figure 1As shown, the detection module includes a first monitoring unit, a second monitoring unit and a third monitoring unit;

[0065] The first monitoring unit is used to monitor the edge conditions of adjacent parent materials in the cut straight pressure pipe section to obtain and record relevant weld connection data information, wherein the relevant weld connection data information includes the residual height value Yg and the undercut depth Ybsd at each adjacent parent material edge weld;

[0066] The height value Yg can be measured by a laser rangefinder on the welding area to obtain the height value, while the undercut depth Ybsd can be measured by ultrasonic technology.

[0067] The second monitoring unit is used to monitor the relevant pressure state data information around each weld in real time, wherein the relevant pressure state data information includes the flow resistance Lz of the rear side of the adjacent parent material edge at each detection time point under the laminar flow state. after , flow resistance Lz at the front part before , and the flow resistance Lzz at the rear side of the adjacent parent material edge at each detection time point under turbulent conditions after , flow resistance Lzz at the front part before The differential pressure sensor can be used to measure the pressure difference between the front and rear parts of the pipeline and calculate the flow resistance.

[0068] The third monitoring unit is used to monitor and record the pipe condition data information of the pressure pipe in advance, wherein the pipe condition data information includes the fluid density in the pressure pipe. , fluid velocity v, pressure pipe diameter D and fluid viscosity .

[0069] Fluid density can be measured by the propagation speed of ultrasound in the fluid ; The fluid velocity v is measured by the change of ultrasonic wave velocity; The diameter D of the pressure pipe can be accurately measured by a laser rangefinder; Fluid viscosity The viscosity can be monitored and obtained by a viscometer, wherein the viscometer includes a rotational viscometer and a capillary viscometer, which are used to directly measure the viscosity of the fluid.

[0070] The preprocessing module includes a processing unit and a standardization unit;

[0071] The processing unit is used to monitor abnormal values ​​and missing values ​​in relevant weld connection data information, relevant pressure state data information and pipe condition data information, and remove abnormal values ​​and fill in missing values;

[0072] The standardization unit is used to uniformly format the relevant data information in the detection data set using dimensionless processing technology, so that the collected relevant data information can adapt to different statistical and machine learning algorithms.

[0073] In this embodiment, the design of the detection module includes a first monitoring unit, a second monitoring unit and a third monitoring unit, forming a multi-level monitoring system. The first monitoring unit focuses on obtaining the residual height value and undercut depth of the weld at the edge of the adjacent parent material, ensuring the multi-faceted recording of the quality data of the weld connection. The second monitoring unit monitors the pressure state data around the weld in real time, including the flow resistance under laminar and turbulent conditions, which provides detailed basic data for the dynamic analysis of flow state and resistance changes. The third monitoring unit is responsible for recording pipe condition data, which provides all-round data support for fluid behavior analysis.

[0074] The processing unit of the preprocessing module ensures the accuracy and completeness of the detection data by identifying and processing the outliers and missing values ​​in the data. The outlier removal and missing value filling operations in this process improve the quality of the data and further avoid erroneous analysis caused by incomplete or inaccurate data. The standardization unit uses dimensionless processing technology to uniformly format the data, so that data from different sources can be compatible and applicable to various statistical and machine learning algorithms. This standardized processing not only improves the efficiency of data processing, but also enhances the reliability of the analysis results. The acquisition and processing of comprehensive monitoring data enables the system to provide detailed analysis of weld connection quality, flow resistance status and fluid behavior in the pipeline. This comprehensive data integration and processing capability enables the system to more accurately evaluate the impact of weld defects on flow resistance, discover potential problems in a timely manner, and provide a scientific basis for further maintenance and optimization. This system improves the level of intelligent data processing by combining monitoring data with standardized processing technology, enabling the system to automatically identify and process abnormal situations and provide accurate analysis results. This intelligent processing method not only improves the response speed of the system, but also enhances its adaptability to complex pipeline conditions.

[0075] Example 3

[0076] like Figure 1 As shown, the local pipeline analysis module includes an inner wall state analysis unit, an impact unit and an early warning unit;

[0077] The inner wall state analysis unit is used to perform dimensionless processing on the excess height value Yg and the undercut depth Ybsd according to the relevant weld connection data information, and map the corresponding data values ​​in the interval [0, 1], and then construct the flatness state coefficient Pzxs of the weld at the edge of each adjacent parent material according to the following formula:

[0078] ;

[0079] Where i=1, 2, 3, ..., n, n represents the number of reinforcements generated at the corresponding weld, j=1, 2, 3, ..., J, J represents the number of undercuts generated at the corresponding weld, represents the i-th reinforced height value at the corresponding weld, represents the mean value of the reinforcement at the corresponding weld. represents the jth undercut depth at the corresponding weld, represents the mean value of the undercut depth at the corresponding weld, α and β are weight values, and C represents the correction constant, where 0<α≤1, 0<β≤1, and α+β=1.

[0080] The influence unit is used to analyze the influence of the flatness coefficient Pzxs of the weld at the edge of the adjacent parent material on the flow resistance Lzz of the corresponding part, so as to construct the influence coefficient Yxs, which is obtained in the following way:

[0081] ;

[0082] Where k=1, 2, 3, ..., K, K represents the number of welding points, represents the flatness coefficient at the edge of the kth adjacent parent material, It represents the average value of the flatness coefficient at the edges of adjacent parent materials in the straight pipe section of the cut-off pressure. represents the flow resistance at the rear side of the kth adjacent parent material edge, It represents the average value of the flow resistance at the rear side of the adjacent parent material edge in the straight pipe section with this cut-off pressure.

[0083] The early warning unit is used to determine whether the welding state affects the fluid flow in the pressure pipeline based on the value of the influence coefficient Yxs. The specific analysis content is as follows:

[0084] If the influence coefficient Yxs does not fall within the preset safety threshold range, it is judged that the welding state has an impact on the fluid flow in the pressure pipeline, and an external inspection instruction is issued;

[0085] If the influence coefficient Yxs falls within the preset safety threshold range, it is determined that the welding state has no influence on the fluid flow in the pressure pipeline. At this time, no additional troubleshooting instructions will be issued.

[0086] The preset safety threshold range is set as follows: According to the above-mentioned method for obtaining the influence coefficient Yxs, the influence coefficient Yxs of the flatness coefficient Pzxs of the welds at the edges of the adjacent parent materials on the flow resistance Lzz of the corresponding parts is obtained, and the average influence coefficients are obtained respectively by combining the statistical algorithm. and standard deviation of the influence coefficient ,based on and , set the range of safety threshold: ;

[0087] Among them, g is a constant, usually taking values ​​of 1-3, corresponding to different confidence levels. The specific value is set by the user (according to actual conditions); the setting method of the evaluation threshold Q in the comparison unit in the feedback module is the same as the safety threshold here.

[0088] According to actual needs, the safety threshold range can also be directly set, for example, set to [-0.8, 0.8].

[0089] In this embodiment, the inner wall state analysis unit can further effectively reflect the actual flatness of the weld by constructing the flatness state coefficient Pzxs of the weld. This precise analysis helps to identify and quantify weld defects, thereby ensuring that the weld quality meets the standard; the influence unit constructs the influence coefficient Yxs based on the flatness state coefficient Pzxs and the flow resistance Lzz, which can evaluate the specific impact of the weld flatness on the flow resistance; by calculating the influence coefficient, the system can clarify the actual impact of weld defects on fluid flow. This analysis helps to identify welds that may cause increased flow resistance, thereby providing data support for pipeline maintenance and optimization. The early warning unit determines whether the welding state has an actual impact on the fluid flow in the pressure pipeline based on the value of the influence coefficient Yxs. By setting clear judgment criteria, the system can intelligently issue troubleshooting instructions or temporarily not issue additional troubleshooting instructions. This mechanism ensures that when actual impacts are discovered, quick action can be taken to avoid the impact of potential flow resistance problems on the pipeline system.

[0090] Through accurate weld flatness analysis and flow resistance impact assessment, this system can timely identify and handle possible welding defects and improve the overall reliability of the pipeline system. At the same time, the intelligent early warning mechanism makes maintenance work more efficient, reduces unnecessary inspections and interventions, and optimizes the allocation of pipeline maintenance resources. The system comprehensively utilizes inner wall state analysis, impact assessment and early warning mechanism to provide engineers with detailed data support and decision-making basis. This data-driven approach makes pipeline inspection and maintenance decisions more scientific and accurate, thereby improving the operating efficiency and safety of the pipeline system. In summary, the system provides a comprehensive and accurate pipeline inspection solution through inner wall state analysis, impact assessment and intelligent early warning. The application of the system will significantly improve the inspection accuracy of pressure pipelines, optimize maintenance strategies, and ensure the long-term stable operation of the system.

[0091] Example 4

[0092] like Figure 1 As shown, specifically: the superposition effect analysis module includes a flow classification unit and an effect analysis unit;

[0093] The flow classification unit is used to construct the Reynolds number Re based on the troubleshooting instructions issued by the early warning unit and combined with the pipe condition data information. Re is obtained by the following formula:

[0094] ;

[0095] According to the Re value, the flow state of the fluid in each part is judged. The specific judgment method is as follows:

[0096] If Re < 2000, it means that the current position is in laminar flow state;

[0097] If Re>4000, it means the current position is in a turbulent state;

[0098] If 2000≤Re≤4000, it means that the current position is in a transition state between laminar flow and turbulent flow.

[0099] In this embodiment, this classification method can accurately identify the flow state, thereby providing a scientific basis for subsequent flow resistance analysis and system optimization. Accurate judgment of laminar flow, turbulent flow and transitional state helps to understand the behavior characteristics and flow characteristics of fluids under different conditions. By calculating the Reynolds number Re, the flow classification unit can quantify the changes in the flow state. This quantitative analysis capability makes it possible to accurately correlate the flow state with factors such as flow resistance and the influence of welding defects, providing data support for subsequent effect analysis. Accurate calculation and classification of the Reynolds number Re helps to optimize the design and operation strategy of the pipeline system. According to the judgment results of the flow classification unit, the effect analysis unit can analyze the superposition effect of flow resistance and welding defects under different flow states. This detailed analysis can help identify the impact of different flow states on the pipeline system, formulate targeted repair measures, and further improve the maintenance efficiency and effectiveness of the system.

[0100] By combining the Reynolds number Re with flow state analysis, the system can more comprehensively evaluate the flow of fluid in the pipeline and its impact on pipeline performance. This comprehensive analysis capability improves the understanding of the operating status of the pipeline system, thereby enhancing the reliability and safety of the system, ensuring that the pipeline system can maintain good performance under various flow conditions, helping to reduce potential failures and optimize pipeline operation safety. The superposition effect analysis module can dynamically adjust the evaluation and maintenance strategy of the pipeline system based on real-time monitoring data. This data-driven approach enables the system to respond to changes in flow conditions in real time, thereby achieving dynamic fault prevention and performance optimization.

[0101] Example 5

[0102] like Figure 1 As shown, specifically: the effect analysis unit is used to analyze the difference mean Clz between adjacent flow resistances under the laminar flow state after distinguishing the flow state of the fluid. avg and the mean difference Tlz between adjacent flow resistances in turbulent state avg, which can be obtained by:

[0103] ;

[0104] In the formula, m represents, h=1, 2, 3, ..., m, It represents the flow resistance at the rear side of the kth adjacent parent material edge at the hth detection time point under laminar flow conditions. It represents the flow resistance at the front side of the kth adjacent parent material edge at the h-1th detection time point under laminar flow state;

[0105] ;

[0106] In the formula, It represents the flow resistance at the rear side of the kth adjacent parent material edge at the hth detection time point under turbulent conditions, It represents the flow resistance at the front side of the kth adjacent parent material edge at the h-1th detection time point under turbulent state;

[0107] According to Clz avg and Tlz avg , calculate the comparison value Bdz:

[0108] .

[0109] In this embodiment, the effect analysis unit provides a clear understanding of the resistance difference under different flow states by calculating the mean and difference between adjacent flow resistances under laminar and turbulent states respectively. This analysis helps to evaluate the specific impact of flow state on pipeline performance and ensure the accuracy and reliability of the test results. By calculating the mean of the difference in flow resistance under laminar and turbulent states and further deriving a comparison value, the system can identify abnormal changes in flow resistance. This comprehensive comparison method not only reveals the impact of flow state on flow resistance, but also effectively detects possible abnormal phenomena, providing clear guidance for system maintenance and optimization.

[0110] Analyzing the mean of flow resistance difference under laminar and turbulent conditions can help engineers better understand the flow resistance characteristics under different flow conditions. This understanding can guide the adjustment of pipeline design, welding process and operating conditions, thereby improving the overall flow performance and efficiency of the system. When the comparison value exceeds the preset threshold, the system can quickly issue an early warning and conduct targeted troubleshooting. This early warning mechanism is based on the analysis of resistance differences under different flow conditions, making troubleshooting more efficient and targeted, thereby improving the maintenance efficiency and safety of the system. In short, the effect analysis unit enhances the system's understanding and management capabilities of resistance changes under fluid flow conditions through detailed analysis and comparison of the mean of flow resistance differences under laminar and turbulent conditions. This not only optimizes the detection and analysis process of flow resistance, but also improves the accuracy of fault detection and the maintenance efficiency of the system, providing strong support for the stable operation of the pressure pipeline system.

[0111] Example 6

[0112] like Figure 1 As shown, specifically: the feedback module includes a comparison unit and a feedback management unit;

[0113] The comparison unit is used to compare and analyze the comparison value Bdz with the evaluation threshold Q to determine whether there is a superposition phenomenon in the pressure pipeline. The specific contents are as follows:

[0114] If Bdz exceeds Q, it is determined that there is a superposition phenomenon in the pressure pipeline, and a processing instruction will be issued;

[0115] If Bdz does not exceed Q, it is determined that there is no superposition phenomenon in the pressure pipeline, and no processing instruction is issued at this time.

[0116] The feedback management unit is used to use non-destructive testing (NDT) technology to detect the adjacent parent material edges at the corresponding position after receiving the processing instructions issued by the comparison unit to confirm the severity of the weld, and after re-confirming the position, size and depth of the gap, use grinding to clean the welding area to ensure that the welding edge and the parent material are clean and rust-free, and then post-process the welding area. The post-processing includes heat treatment and deburring to ensure that the weld is flat and uniform; the non-destructive testing (NDT) technology used includes ultrasonic testing (UT), X-ray testing (RT), magnetic particle testing (MT) or penetration testing (PT) to confirm the nature and severity of the gap.

[0117] In this embodiment, the comparison unit can accurately determine whether there is a flow resistance superposition phenomenon by comparing the comparison value Bdz with the set evaluation threshold. This process can effectively identify the abnormal flow resistance caused by welding defects and ensure that the processing instruction is issued only when there is a problem, further avoiding unnecessary intervention. After receiving the processing instruction, the feedback management unit uses non-destructive testing technology to conduct detailed inspections on the weld. Through these technologies, the nature, location, size and depth of the gap can be accurately confirmed, providing a reliable basis for subsequent processing. After confirming the severity of the welding defect, the system will perform post-processing operations such as grinding, heat treatment and deburring on the welding area. These treatment measures can effectively clean the welding area, remove rust on the welding edge and the parent material, ensure the flatness and uniformity of the weld, and further improve the overall performance and reliability of the pipeline. Through methods such as grinding, heat treatment and deburring, the processing of the welding area not only improves the cleanliness of the welding edge and the parent material, but also ensures the flatness and uniformity of the weld. This series of operations can significantly improve the welding quality and reduce the negative impact of welding defects on the flow performance of the pipeline.

[0118] Through precise detection and post-processing, the system can effectively reduce the risk of pipeline failures caused by welding defects, thereby improving the operational safety and reliability of the pipeline. Based on the comparison results of the comparison value Bdz and the evaluation threshold, the system can scientifically issue processing instructions to ensure that maintenance work is concentrated in the areas that really need to be processed. This method reduces interference with normal work and improves the efficiency and pertinence of pipeline maintenance. In short, the system significantly improves the operational safety and reliability of pressure pipelines through precise comparison analysis and efficient welding defect processing.

Claims

1. Pressure pipeline detection system, characterized by: It includes detection module, pre-processing module, local pipeline analysis module, superposition effect analysis module and feedback module; The detection module is used to preselect a section of a straight pressure pipe and monitor the edge conditions of adjacent parent materials in the section of the straight pressure pipe to record relevant weld connection data information, and monitor relevant pressure state data information and pipe condition data information around each weld to construct a detection data set; The preprocessing module is used to preprocess the relevant data information in the detection data set, and standardize the processed relevant data information according to the dimensionless processing technology to unify the units; The local pipeline analysis module is used to construct the flatness coefficient Pzxs of the welds at the edges of each adjacent parent material based on the relevant weld connection data information, and extract the flow resistance Lzz from the relevant pressure state data information to analyze the influence of Pzxs on Lzz at the corresponding part, and construct the influence coefficient Yxs. If there is an influence, a troubleshooting instruction is issued; The superposition effect analysis module is used to construct the Reynolds number Re based on the pipe condition data information after receiving the troubleshooting instruction, judge the flow state of the fluid in each part, distinguish it, and analyze the difference mean Clz between adjacent flow resistances under the laminar flow state. avg and the mean difference Tlz between adjacent flow resistances in turbulent state avg , and combined with Clz avg and Tlz avg , calculate the comparison value Bdz; The feedback module is used to pre-set the evaluation threshold Q and compare and analyze Q with Bdz to determine whether there is a superposition phenomenon in the pressure pipeline; The detection module includes a first monitoring unit, a second monitoring unit and a third monitoring unit; The first monitoring unit is used to monitor the edge conditions of adjacent parent materials in the cut straight pressure pipe section to obtain and record relevant weld connection data information, wherein the relevant weld connection data information includes the residual height value Yg and the undercut depth Ybsd at each adjacent parent material edge weld; The second monitoring unit is used to monitor the relevant pressure state data information around each weld in real time, wherein the relevant pressure state data information includes the flow resistance Lz of the rear side of the adjacent parent material edge at each detection time point under the laminar flow state. after , flow resistance Lz at the front part before , and the flow resistance Lzz at the rear side of the adjacent parent material edge at each detection time point under turbulent conditions after , flow resistance Lzz at the front part before ; The third monitoring unit is used to monitor and record the pipe condition data information of the pressure pipe in advance, wherein the pipe condition data information includes the fluid density in the pressure pipe. , fluid velocity v, pressure pipe diameter D and fluid viscosity ; The local pipeline analysis module includes an inner wall status analysis unit, an impact unit, and an early warning unit; The inner wall state analysis unit is used to perform dimensionless processing on the excess height value Yg and the undercut depth Ybsd according to the relevant weld connection data information, and map the corresponding data values ​​in the interval [0, 1], and then construct the flatness state coefficient Pzxs of the weld at the edge of each adjacent parent material according to the following formula: ； Where i=1, 2, 3, ..., n, n represents the number of reinforcements generated at the corresponding weld, j=1, 2, 3, ..., J, J represents the number of undercuts generated at the corresponding weld, represents the i-th reinforced height value at the corresponding weld, represents the mean value of the reinforcement at the corresponding weld. represents the jth undercut depth at the corresponding weld, represents the mean value of the undercut depth at the corresponding weld, α and β are weight values, C represents the correction constant, where 0<α≤1, 0<β≤1, and α+β=1; The influence unit is used to analyze the influence of the flatness coefficient Pzxs of the weld at the edge of the adjacent parent material on the flow resistance Lzz of the corresponding part, so as to construct the influence coefficient Yxs, which is obtained in the following way: ； Where k=1, 2, 3, ..., K, K represents the number of welding points, represents the flatness coefficient at the edge of the kth adjacent parent material, It represents the average value of the flatness coefficient at the edges of adjacent parent materials in the straight pipe section of the cut-off pressure. represents the flow resistance at the rear side of the kth adjacent parent material edge, It represents the mean value of the flow resistance at the rear side of the adjacent parent material edge in the straight pipe section of the cut-off pressure; The early warning unit is used to determine whether the welding state affects the fluid flow in the pressure pipeline based on the value of the influence coefficient Yxs. The specific analysis content is as follows: If the influence coefficient Yxs does not fall within the preset safety threshold range, it is judged that the welding state has an impact on the fluid flow in the pressure pipeline, and an external inspection instruction is issued; If the influence coefficient Yxs falls within the preset safety threshold range, it is determined that the welding state has no influence on the fluid flow in the pressure pipeline, and no additional troubleshooting instructions are issued at this time; The superposition effect analysis module includes a flow classification unit and an effect analysis unit; The flow classification unit is used to construct the Reynolds number Re based on the troubleshooting instructions issued by the early warning unit and combined with the pipe condition data information. Re is obtained by the following formula: ； According to the Re value, the flow state of the fluid in each part is judged. The specific judgment method is as follows: If Re < 2000, it means that the current position is in laminar flow state; If Re>4000, it means the current position is in a turbulent state; If 2000≤Re≤4000, it means that the current position is in the transition state between laminar flow and turbulent flow; The effect analysis unit is used to analyze the difference between adjacent flow resistances under laminar flow conditions after distinguishing the flow conditions of the fluid. avg and the mean difference Tlz between adjacent flow resistances in turbulent state avg , which can be obtained by: ； In the formula, m represents, h=1, 2, 3, ..., m, It represents the flow resistance at the rear side of the kth adjacent parent material edge at the hth detection time point under laminar flow conditions. It represents the flow resistance at the front side of the kth adjacent parent material edge at the h-1th detection time point under laminar flow state; ； In the formula, It represents the flow resistance at the rear side of the kth adjacent parent material edge at the hth detection time point under turbulent conditions, It represents the flow resistance at the front side of the kth adjacent parent material edge at the h-1th detection time point under turbulent state; According to Clz avg and Tlz avg , calculate the comparison value Bdz: 。 2. The pressure pipeline detection system according to claim 1, characterized in that: The preprocessing module includes a processing unit and a standardization unit; The processing unit is used to monitor abnormal values ​​and missing values ​​in relevant weld connection data information, relevant pressure state data information and pipe condition data information, and remove abnormal values ​​and fill in missing values; The standardization unit is used to uniformly format the relevant data information in the detection data set using dimensionless processing technology, so that the collected relevant data information can adapt to different statistical and machine learning algorithms.

3. The pressure pipeline detection system according to claim 1, characterized in that: The feedback module includes a comparison unit and a feedback management unit; The comparison unit is used to compare and analyze the comparison value Bdz with the evaluation threshold Q to determine whether there is a superposition phenomenon in the pressure pipeline. The specific contents are as follows: If Bdz exceeds Q, it is determined that there is a superposition phenomenon in the pressure pipeline, and a processing instruction will be issued; If Bdz does not exceed Q, it is determined that there is no superposition phenomenon in the pressure pipeline, and no processing instruction is issued at this time.

4. The pressure pipeline detection system according to claim 3, characterized in that: The feedback management unit is used to use non-destructive testing technology to detect the adjacent parent material edges at the corresponding position after receiving the processing instructions issued by the comparison unit to confirm the severity of the weld. After reconfirming the position, size and depth of the gap, the welding area is cleaned by grinding, and then the welding area is post-processed, including heat treatment and deburring.

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