Double-row immersed pipeline connection quality monitoring management system

Abstract

The invention discloses a double-row immersed pipeline connection quality monitoring and management system, which belongs to the technical field of pipeline monitoring and management, and comprises a joint butt joint monitoring module for obtaining butt joint parameter information in a butt joint process; the welding monitoring module is used for acquiring welding parameter information in the welding process; the underwater trench excavation monitoring module is used for acquiring excavation parameter information in a trench excavation process; and the analysis processing module is used for analyzing the acquired various parameter information so as to detect whether the working process of each monitoring module is abnormal or not and correspondingly processing the abnormal condition. Advanced automatic detection, intelligent monitoring and data analysis technologies are integrated, welding parameter information obtained by the welding monitoring module is transmitted to the analysis processing module, then through analysis processing of the analysis processing module, the welding quality in the welding process can be monitored in real time, and the welding quality and normal welding are guaranteed.

Description

Technical Field

[0001] The invention belongs to the technical field of pipeline monitoring and management, and in particular relates to a double-row immersed tube pipeline connection quality monitoring and management system. Background Art

[0002] In the field of underwater pipeline engineering, immersed tube construction has always been the focus and difficulty in infrastructure construction due to its unique operating environment and technical difficulty. With the acceleration of urbanization and the growth of demand for water development, higher requirements are placed on the quality of immersed tube construction. On the one hand, the construction of urban water supply, drainage, energy transmission and other infrastructure requires immersed tubes to have higher safety and durability to support the sustainable development of the city. On the other hand, large-scale engineering projects such as oil and gas transportation and cross-sea channel construction in the marine environment pose severe challenges to the accuracy and efficiency of immersed tube construction.

[0003] The traditional immersed tube construction method relies on a lot of manual work and experience judgment, which is not only inefficient but also difficult to ensure the construction quality. Especially for the complex structure of double-row pipes, the welding quality, the precise docking between pipe sections and the accuracy of underwater operations are directly related to the stability and service life of the entire pipeline system. Summary of the invention

[0004] The object of the present invention is to provide a double-row immersed tube pipeline connection quality monitoring and management system to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A double-row immersed tube pipeline connection quality monitoring and management system, the monitoring and management system comprising:

[0007] A joint docking monitoring module, which is used to obtain docking parameter information of the docking process and transmit it to the analysis and processing module;

[0008] A welding monitoring module, which is used to obtain welding parameter information of the welding process and transmit it to the analysis and processing module;

[0009] An underwater trench excavation monitoring module, which is used to obtain excavation parameter information during the trench excavation process and transmit it to the analysis and processing module;

[0010] The analysis and processing module is used to analyze the acquired parameter information, thereby detecting whether the working process of each monitoring module is abnormal, and performing corresponding processing on the abnormal situation.

[0011] Furthermore, the method in which the analysis and processing module detects the welding monitoring module is:

[0012] According to the welding requirements, set the corresponding welding parameters and set the corresponding sensors to obtain the welding parameters in real time, including the welding current I, voltage U, welding speed V and line energy T;

[0013] By formula Obtain abnormal warning value B;

[0014] The obtained abnormal warning value B is compared with the preset abnormal warning threshold B th To compare:

[0015] When B>B th When , an abnormal signal is generated;

[0016] Among them, I0 is the standard welding current set during welding, U0 is the standard welding voltage set during welding, V0 is the standard welding speed set during welding, T0 is the standard line energy set during welding, ΔI is the welding current reference value, ΔU is the welding voltage reference value, ΔV is the welding speed reference value, and ΔT is the line energy reference value.

[0017] Furthermore, the method in which the analysis and processing module detects the welding monitoring module also includes:

[0018] When generating abnormal signals, a high-precision camera is used to obtain the weld image after welding, and after grayscale processing, the edge recognition technology is used to obtain the weld contour and the current weld width L. N ;

[0019] Thus, through the formula R = |L N -L0|get the error value R;

[0020] When R∈[0, R1), each set welding parameter is automatically fine-tuned;

[0021] When R∈[R1, +∞), a reminder warning is generated and the welding operation is stopped;

[0022] Among them, R1 is the error threshold set by the system.

[0023] Furthermore, the method in which the analysis and processing module detects the welding monitoring module also includes:

[0024] When no abnormal signal is generated, the temperature variation curve T during welding is obtained every detection cycle. e (t) and the welding stress variation curve F(t) during welding;

[0025] By formula Obtain the potential risk value Q;

[0026] Compare the obtained potential risk value Q with the potential risk threshold interval [Q1, Q2] preset in the system:

[0027] When Q∈[Q1, Q2], the current welding speed is maintained;

[0028] when When , an adjustment instruction is generated to fine-tune the current welding speed;

[0029] Among them, t1 is the start time of the detection cycle, and t2 is the end time of the detection cycle. is the standard welding temperature variation curve set by the system, F0(t) is the standard welding stress variation curve set by the system, T e F is the corresponding difference value of welding temperature stress, γ1, γ2 and γ3 are preset coefficients, and Q1 and Q2 are potential risk thresholds set by the system.

[0030] Furthermore, the method for obtaining the corresponding difference value of the welding temperature stress is:

[0031] By formula Get the corresponding difference value T of welding temperature stress e F;

[0032] Among them, k is the welding temperature versus welding stress function preset by the system, and Y is the standard comparison ratio preset by the system.

[0033] Furthermore, the adjustment instruction includes an increase instruction and a decrease instruction:

[0034] When Q>Q2, an increase instruction is generated, and the welding speed is adjusted to V1 through the formula V1=V0+σ*(Q-Q2);

[0035] When Q<Q1, a reduction instruction is generated, and the welding speed is adjusted to V2 by the formula V2=V0-σ*(Q1-Q);

[0036] Among them, V0 is the current welding speed, V1 is the welding speed after adjustment, V2 is the welding speed after adjustment, and σ is the speed conversion coefficient.

[0037] Furthermore, the method in which the analysis and processing module detects the joint docking monitoring module is:

[0038] High-precision displacement sensors are arranged on and around the Haff joint. When a position change on the displacement sensor is detected, a warning is generated.

[0039] At the same time, underwater sonar or laser scanning technology can be used to accurately locate the relative position of the end of the immersed tube and the Haff joint. When the relative position changes, a reminder warning is generated.

[0040] Furthermore, the method in which the analysis and processing module detects the underwater trench excavation monitoring module is:

[0041] According to the construction plan, determine the depth, width, slope and bottom flatness of the excavation trench, set the excavation route, and drive the excavation equipment to excavate along the set route;

[0042] The position of the excavation equipment is obtained in real time to determine whether the excavation equipment is within the set line position range. When it exceeds the set line position range, the position of the grooving equipment is adjusted in time.

[0043] Beneficial effects of the present invention:

[0044] The present invention integrates advanced automatic detection, intelligent monitoring and data analysis technologies, and transmits the docking parameter information obtained by the joint docking monitoring module, the welding parameter information obtained by the welding monitoring module, and the excavation parameter information obtained by the underwater trench excavation monitoring module to the analysis and processing module. Through the analysis and processing of the analysis and processing module, the welding quality in the welding process can be monitored in real time to ensure normal welding; at the same time, the position of the excavation trench equipment can be monitored in real time during the trench excavation process to ensure the accuracy of the excavation, and the position of the pipeline can be monitored in real time during the half joint docking installation process to ensure the accuracy of the pipeline connection during the docking process, thereby ensuring the sealing and structural strength of the pipeline connection, reducing errors caused by human factors, and comprehensively improving the overall quality and safety of the immersed tube construction.

[0045] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0047] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In one embodiment, a double-row immersed tube pipeline connection quality monitoring and management system is disclosed, such as Figure 1 As shown, the monitoring and management system includes:

[0050] A joint docking monitoring module, which is used to obtain docking parameter information during the docking process and transmit it to the analysis and processing module;

[0051] A welding monitoring module, which is used to obtain welding parameter information of the welding process and transmit it to the analysis and processing module;

[0052] An underwater trench excavation monitoring module is used to obtain excavation parameter information during the trench excavation process and transmit it to the analysis and processing module;

[0053] The analysis and processing module is used to analyze the acquired parameter information, so as to detect whether the working process of each monitoring module is abnormal, and to handle the abnormal situation accordingly.

[0054] Through the above-mentioned technical scheme, this application integrates advanced automatic detection, intelligent monitoring and data analysis technologies, and transmits the docking parameter information obtained by the joint docking monitoring module, the welding parameter information obtained by the welding monitoring module, and the excavation parameter information obtained by the underwater trench excavation monitoring module to the analysis and processing module. Then, through the analysis and processing of the analysis and processing module, the welding quality during the welding process can be monitored in real time to ensure normal welding; at the same time, the position of the excavation trench equipment can be monitored in real time during the trench excavation process to ensure the accuracy of the excavation, and the position of the pipeline can be monitored in real time during the half joint docking installation process to ensure the accuracy of the pipeline connection during the docking process, thereby ensuring the sealing and structural strength of the pipeline connection, reducing errors caused by human factors, and comprehensively improving the overall quality and safety of immersed tube construction.

[0055] As an embodiment of the present invention, the method for the analysis and processing module to detect the welding monitoring module is:

[0056] According to the welding requirements, set the corresponding welding parameters and set the corresponding sensors to obtain the welding parameters in real time, including the welding current I, voltage U, welding speed V and line energy T;

[0057] By formula Obtain abnormal warning value B;

[0058] The obtained abnormal warning value B is compared with the preset abnormal warning threshold B th To compare:

[0059] When B>B th When , an abnormal signal is generated;

[0060] Among them, I0 is the standard welding current size set during welding, U0 is the standard welding voltage size set during welding, V0 is the standard welding speed size set during welding, T0 is the standard line energy size set during welding, ΔI is the welding current reference value, ΔU is the welding voltage reference value, ΔV is the welding speed reference value, and ΔT is the line energy reference value;

[0061] When generating abnormal signals, a high-precision camera is used to obtain the weld image after welding, and after grayscale processing, the edge recognition technology is used to obtain the weld contour and the current weld width L. N ;

[0062] Thus, through the formula R = |L N -L0|get the error value R;

[0063] When R∈[0, R1), each set welding parameter is automatically fine-tuned;

[0064] When R∈[R1, +∞), a reminder warning is generated and the welding operation is stopped;

[0065] Among them, R1 is the error threshold set by the system.

[0066] Through the above technical solution, this embodiment provides a method for the analysis and processing module to detect the welding monitoring module. First, according to the welding requirements, the corresponding welding parameters are set, such as welding current, voltage, welding speed, welding line energy, etc., and then the corresponding sensors are set during welding to obtain these parameter information during welding, and the formula is used to calculate the welding parameters. The abnormal warning value B is obtained. Generally speaking, the better the welding quality, the smaller the fluctuation of the current, voltage, welding speed and welding line energy. Therefore, the obtained welding current, voltage, welding speed and welding line energy are compared with their respective preset standard values ​​to obtain the difference change. If only one parameter is compared, it is easy to be affected by accidental factors and cause errors. Therefore, the formula is used Comprehensive analysis is performed to obtain the abnormal warning value B. Obviously, it can be seen from the formula that the larger the value of the abnormal warning value, the greater the possibility of welding abnormality. Therefore, after obtaining the abnormal warning value, the obtained abnormal warning value B is compared with the preset abnormal warning threshold B.th Compare: When B>B th When the welding is abnormal, it means that the welding may be abnormal, and an abnormal signal is generated. When an abnormal signal is generated, a high-precision camera is used to obtain the weld image after welding, and after grayscale processing, the edge recognition technology is used to obtain the outline of the weld and the current weld width L is obtained. N , so through the formula R=|L N -L0|gets the error value R, and compares the error value R with the error threshold R1 set by the system. When R∈[0, R1), it means that although an abnormal signal appears at this time, it has not affected the quality of the weld or has little impact on the quality of the weld. At this time, the set welding parameters are automatically fine-tuned, and the parameters are slowly adjusted to the vicinity of the standard value, so as to ensure the subsequent welding quality; when R∈[R1, +∞), it means that the quality of the weld has been greatly affected at this time, and the defects in the weld are large, then a reminder warning is generated to remind the operation management personnel, and the welding operation is stopped, and the parameters are reset to ensure the qualified welding quality. In this way, it is possible to first judge whether the welding is abnormal according to the changes in the set welding parameters, and then judge the severity of the welding abnormality according to the weld condition after welding. When the weld defect is small, the set parameters can be automatically corrected. When the weld defect is large, a warning is generated to remind the operator to reset it, so as to ensure the welding quality of the entire welding process.

[0067] In the above technical solution, the standard welding current size I0 set during welding, the standard welding voltage size U0 set during welding, the standard welding speed size V0 set during welding, and the standard line energy size T0 set during welding can all be determined according to the welding standard during the actual welding operation, and the welding current reference value ΔI, the welding voltage reference value ΔU, the welding speed reference value ΔV, the line energy reference value ΔT, the preset abnormal warning threshold value B th The error threshold R1 set by the system can be selected and determined based on historical experience data, which will not be described in detail here.

[0068] As an embodiment of the present invention, the method for the analysis and processing module to detect the welding monitoring module also includes:

[0069] When no abnormal signal is generated, the temperature variation curve T during welding is obtained every detection cycle. e (t) and the welding stress variation curve F(t) during welding;

[0070] By formula Obtain the potential risk value Q;

[0071] Compare the obtained potential risk value Q with the potential risk threshold interval [Q1, Q2] preset in the system:

[0072] When Q∈[Q1, Q2], the current welding speed is maintained;

[0073] when When , an adjustment instruction is generated to fine-tune the current welding speed;

[0074] Among them, t1 is the start time of the detection cycle, and t2 is the end time of the detection cycle. is the standard welding temperature variation curve set by the system, F0(t) is the standard welding stress variation curve set by the system, T e F is the difference value corresponding to the welding temperature stress, γ1, γ2 and γ3 are the preset coefficients, and Q1 and Q2 are the potential risk thresholds set by the system;

[0075] The method for obtaining the corresponding difference value of welding temperature stress is: Get the corresponding difference value T of welding temperature stress e F;

[0076] Among them, k is the welding temperature versus welding stress function preset by the system, and Y is the standard comparison ratio preset by the system.

[0077] Through the above technical solution, this embodiment provides another method for the analysis and processing module to detect the welding monitoring module. Since when an abnormality is detected, the abnormality has already occurred, so it is impossible to judge the potential abnormal risk. Therefore, when no abnormal signal is generated, every detection cycle, the detection cycle can be manually determined to obtain the temperature change curve T during welding. e (t) and the welding stress variation curve F(t) during welding, and then through the formula The potential risk value Q is obtained, and then the potential risk is judged according to the size of the potential risk value and the corresponding treatment is carried out; in the formula It indicates the difference between the current welding temperature change and the standard welding temperature change. The larger the difference, the more the welding temperature exceeds the standard temperature, and the greater the possibility of potential risk. It indicates the difference between the current welding stress change and the standard welding stress change. The larger the difference, the greater the welding stress exceeds the standard welding stress, and the greater the possibility of potential risk. The welding temperature and welding stress will also have a corresponding impact. In order to make the test results more accurate, the formula Get the corresponding difference value T of welding temperature stress e F, from the formula It can reflect the ratio of the actual welding temperature change to the actual welding stress change during the test cycle and the standard welding temperature to the welding stress change. The ratio is compared with the preset standard control ratio to obtain the corresponding difference value of welding temperature stress. Obviously, the larger the value, the greater the risk of welding abnormality. Therefore, the formula A comprehensive analysis is performed to obtain the potential risk value Q, and the obtained potential risk value Q is compared with the potential risk threshold interval [Q1, Q2] preset in the system. When Q∈[Q1, Q2], it means that the potential risk value is within the normal risk threshold interval, and it is considered that there is no potential abnormal risk, and there is no need to adjust the welding speed. Just keep the current welding speed. It indicates that there is a potential abnormal risk at this time. In order to avoid the occurrence of abnormal risks, it is necessary to generate adjustment instructions and fine-tune the current welding speed to avoid subsequent welding abnormalities and ensure welding quality.

[0078] In the above technical solution, the standard welding temperature curve set by the system changes with time , the system-set standard welding stress change with time curve F0(t), the system-preset welding temperature control welding stress function k can be determined based on the relevant historical data in the big data combined with the empirical data, and the preset coefficients γ1, γ2 and γ3, and the system-set potential risk thresholds Q1 and Q2 can be determined based on experience, and the system-preset standard control ratio Y can be selectively set according to the ratio's empirical numerical range, which will not be described in detail here.

[0079] As an implementation mode of the present invention, the adjustment instruction includes an increase instruction and a decrease instruction:

[0080] When Q>Q2, an increase instruction is generated, and the welding speed is adjusted to V1 through the formula V1=V0+σ*(Q-Q2);

[0081] When Q<Q1, a reduction instruction is generated, and the welding speed is adjusted to V2 by the formula V2=V0-σ*(Q1-Q);

[0082] Among them, V0 is the current welding speed, V1 is the welding speed after adjustment, V2 is the welding speed after adjustment, and σ is the speed conversion coefficient.

[0083] Through the above technical solution, this embodiment provides a specific adjustment method for the adjustment instruction. When Q>Q2, it means that the Q value is large at this time, that is, the temperature is high or the welding stress is large. When the temperature is high or the welding stress is large, it means that too much heat is taken in. In order to ensure the normal weld, it is necessary to slightly increase the welding speed to reduce the heat retention. Therefore, an increase instruction is generated. At this time, the welding speed is adjusted to V1 through the formula V1=V0+σ*(Q-Q2). It can be seen from the formula that the larger the Q value, the more the speed needs to be increased; similarly, when Q<Q1, it means that the Q value is small at this time. That is to say, if the temperature is low or the welding stress is small, it means that the heat intake is small. Therefore, in order to ensure normal welding, it is necessary to slightly reduce the welding speed and increase the heat residence time, then a reduction instruction is generated. At this time, the welding speed is adjusted to V2 through the formula V2=V0-σ*(Q1-Q); in this way, when no abnormal signal is generated, the potential abnormal risk can be judged according to the temperature change and welding stress change during welding. When the potential abnormal risk is found, the welding speed can be adjusted in time, which can avoid the occurrence of abnormal risks and ensure the welding quality.

[0084] It should be noted that the speed conversion coefficient σ is determined based on empirical data.

[0085] As an embodiment of the present invention, the method for the analysis and processing module to detect the joint docking monitoring module is:

[0086] High-precision displacement sensors are arranged on and around the Haff joint. When a position change on the displacement sensor is detected, a warning is generated.

[0087] At the same time, underwater sonar or laser scanning technology can be used to accurately locate the relative position of the end of the immersed tube and the Haff joint. When the relative position changes, a reminder warning is generated.

[0088] Through the above technical scheme, this embodiment provides a method for the analysis and processing module to detect the joint docking monitoring module. In order to ensure the accuracy of the Haff joint during docking, before the installation of the Haff joint, a high-precision displacement sensor array is arranged on the Haff joint and its surroundings according to the pipeline specifications and docking requirements to ensure that all key monitoring points are covered. After the sensor is calibrated, the position change on the displacement sensor is monitored. When the position change on the displacement sensor is detected, a reminder warning is generated to remind the operator to adjust the joint; at the same time, the relative position of the end of the immersed tube and the Haff joint is accurately located through underwater sonar or laser scanning technology. When the relative position changes, a reminder warning is generated to remind the operator to adjust the joint; in this way, the docking process can be monitored in real time to ensure the accuracy of the docking.

[0089] As an embodiment of the present invention, the method for the analysis and processing module to detect the underwater trench excavation monitoring module is:

[0090] According to the construction plan, determine the depth, width, slope and bottom flatness of the excavation trench, set the excavation route, and drive the excavation equipment to excavate along the set route;

[0091] The position of the excavation equipment is obtained in real time to determine whether the excavation equipment is within the set line position range. When it exceeds the set line position range, the position of the grooving equipment is adjusted in time.

[0092] Through the above technical solution, this embodiment provides a method for the analysis and processing module to detect the underwater trench excavation monitoring module. According to the construction plan, the depth, width, slope and bottom flatness of the excavation groove are determined, and the excavation route is set. Each excavation route has a corresponding coordinate, and the excavation equipment is driven to excavate along the set route. The position of the excavation equipment is obtained in real time, and it is determined whether the excavation equipment is within the set line position coordinate range. When it exceeds the set line position coordinate range, the position of the trenching equipment is adjusted in time. In this way, when a deviation is found, the automatic control system adjusts the position of the excavation equipment, or sends a real-time correction instruction to the operator to adjust the position, angle, etc. to ensure the accuracy of the excavation.

[0093] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A double-row immersed tube connection quality monitoring and management system, characterized in that: The monitoring and management system comprises: A joint docking monitoring module, which is used to obtain docking parameter information of the docking process and transmit it to the analysis and processing module; A welding monitoring module, which is used to obtain welding parameter information of the welding process and transmit it to the analysis and processing module; An underwater trench excavation monitoring module, which is used to obtain excavation parameter information during the trench excavation process and transmit it to the analysis and processing module; The analysis and processing module is used to analyze the acquired parameter information, thereby detecting whether the working process of each monitoring module is abnormal, and performing corresponding processing on the abnormal situation.

2. A double-row immersed tube connection quality monitoring and management system according to claim 1, characterized in that: The method by which the analysis and processing module detects the welding monitoring module is: According to the welding requirements, set the corresponding welding parameters and set the corresponding sensors to obtain the welding parameters in real time, including the welding current I, voltage U, welding speed V and line energy T; By formula Obtain abnormal warning value B; The obtained abnormal warning value B is compared with the preset abnormal warning threshold B th To compare: When B>B th When , an abnormal signal is generated; Among them, I0 is the standard welding current set during welding, U0 is the standard welding voltage set during welding, V0 is the standard welding speed set during welding, T0 is the standard line energy set during welding, ΔI is the welding current reference value, ΔU is the welding voltage reference value, ΔV is the welding speed reference value, and ΔT is the line energy reference value.

3. A double-row immersed tube connection quality monitoring and management system according to claim 2, characterized in that: The method in which the analysis and processing module detects the welding monitoring module also includes: When generating abnormal signals, a high-precision camera is used to obtain the weld image after welding, and after grayscale processing, the edge recognition technology is used to obtain the weld contour and the current weld width L. N ; Thus, through the formula R = |L N -L0|get the error value R; When R∈[0, R1), each set welding parameter is automatically fine-tuned; When R∈[R1, +∞), a reminder warning is generated and the welding operation is stopped; Among them, R1 is the error threshold set by the system.

4. A double-row immersed tube connection quality monitoring and management system according to claim 3, characterized in that: The method in which the analysis and processing module detects the welding monitoring module also includes: When no abnormal signal is generated, the temperature variation curve T during welding is obtained every detection cycle. e (t) and the welding stress variation curve F(t) during welding; By formula Obtain the potential risk value Q; Compare the obtained potential risk value Q with the potential risk threshold interval [Q1, Q2] preset in the system: When Q∈[Q1, Q2], the current welding speed is maintained; when When , an adjustment instruction is generated to fine-tune the current welding speed; Among them, t1 is the start time of the detection cycle, and t2 is the end time of the detection cycle. is the standard welding temperature variation curve set by the system, F0(t) is the standard welding stress variation curve set by the system, T e F is the corresponding difference value of welding temperature stress, γ1, γ2 and γ3 are preset coefficients, and Q1 and Q2 are potential risk thresholds set by the system.

5. A double-row immersed tube connection quality monitoring and management system according to claim 4, characterized in that: The method for obtaining the corresponding difference value of welding temperature stress is: By formula Get the corresponding difference value T of welding temperature stress e F; Among them, k is the welding temperature versus welding stress function preset by the system, and Y is the standard comparison ratio preset by the system.

6. A double-row immersed tube connection quality monitoring and management system according to claim 5, characterized in that: The adjustment instructions include increase instructions and decrease instructions: When Q>Q2, an increase instruction is generated, and the welding speed is adjusted to V1 through the formula V1=V0+σ*(Q-Q2); When Q<Q1, a reduction instruction is generated, and the welding speed is adjusted to V2 by the formula V2=V0-σ*(Q1-Q); Among them, V0 is the current welding speed, V1 is the welding speed after adjustment, V2 is the welding speed after adjustment, and σ is the speed conversion coefficient.

7. A double-row immersed tube connection quality monitoring and management system according to claim 1, characterized in that: The method for the analysis and processing module to detect the joint docking monitoring module is: High-precision displacement sensors are arranged on and around the Haff joint. When a position change on the displacement sensor is detected, a warning is generated. At the same time, underwater sonar or laser scanning technology can be used to accurately locate the relative position of the end of the immersed tube and the Haff joint. When the relative position changes, a reminder warning is generated.

8. The double-row immersed tube connection quality monitoring and management system according to claim 1 is characterized in that: The method by which the analysis and processing module detects the underwater trench excavation monitoring module is: According to the construction plan, determine the depth, width, slope and bottom flatness of the excavation trench, set the excavation route, and drive the excavation equipment to excavate along the set route; The position of the excavation equipment is obtained in real time to determine whether the excavation equipment is within the set line position range. When it exceeds the set line position range, the position of the grooving equipment is adjusted in time.

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