Large-arrangement laying design method for geotextile laying ship

Abstract

The invention discloses a large-arrangement laying design method for a laying ship, and relates to the technical field of ship operation. The problems that the influence of multiple factors is not comprehensively considered, the operation of the geotextile laying ship is prone to exceeding the capacity range, resource waste is caused, the quality progress is affected, risks are increased, and problems are difficult to find in advance and laying is difficult to scientifically guide are solved. According to the method, parameters such as the ship speed, the tension and the laying angle are accurately configured and dynamically adjusted by integrating multiple factors, efficient and stable operation of the geotextile laying ship is ensured, the laying efficiency and quality are improved, actually monitored key target items are compared with a preset large-layout laying characteristic database, unconventional items are marked, effective prediction of the laying problem is achieved, and the laying efficiency and quality are improved. Coping strategies with clear priorities are formulated according to different risk levels, potential problems can be solved in advance, operation risks can be reduced, after laying is completed, multi-source feedback data are obtained, laying results are analyzed, an unconventional item weight distribution strategy is established, and subsequent laying operation can be continuously optimized by continuously improving a mechanism.

Description

Technical Field

[0001] The invention relates to the technical field of ship operation, and in particular to a large-scale laying design method of a laying ship. Background Art

[0002] In the fields of water conservancy engineering, marine engineering, etc., large-scale laying operations by laying vessels are a vital basic work. The Chinese patent application with publication number CN102979060A discloses a method for soft laying construction. The patent realizes real-time positioning of the laying body during the soft laying construction process by introducing underwater beacons and transmitters and receivers, and then provides real-time and accurate feedback and control of the construction process.

[0003] However, although the above patent provides an economical, environmentally friendly, fast and accurate soft material laying method, the following problems still exist: The laying operation is affected by many factors, such as the geographical location of the laying area, the storage location of the large laying, the size parameters of the laying ship itself, etc., which will jointly affect the operating efficiency and quality of the laying ship, resulting in the laying ship being unable to operate in the best state, causing resource waste or poor laying effect, making the laying ship face situations beyond its capacity during the operation, increasing the operation risk, and even affecting the laying quality and progress; There is also a lack of comprehensive capture and analysis of key target items in the large-scale laying process, which makes it difficult to discover possible problems in the laying process in advance, and thus it is impossible to take effective countermeasures in time, which increases the laying risk. There is also no systematic collection and integration of the characteristics of different types of large-scale arrangements and the corresponding laying environment, which is not conducive to scientific guidance and optimization of the laying process. Summary of the invention

[0004] The purpose of the present invention is to provide a large-scale laying design method for a laying vessel. By reasonably configuring the operating parameters and dynamically adjusting the operating parameters, it is ensured that the laying vessel is always in the best operating state, and potential problems can be discovered and solved in advance, laying risks can be reduced, and smooth operations can be ensured. The laying efficiency and quality are improved to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: The design method of large-scale laying of laying vessels includes: Collecting operation preparation data, including the geographical location of the laying area, the geographical location of the large-scale layout storage location, the size parameters of the laying vessel, the laying pipeline diameter and the laying depth, and determining the laying environment and large-scale layout type based on the operation preparation data, and determining the laying vessel's operating capacity and operating span range; Based on the data collection results of the operation preparation, combined with the preset large-layout laying characteristics database, the conventional operation parameter range under similar laying environments and large-layout types is retrieved, and the operation parameters of the laying ship are configured in combination with the operation capacity and operation span of the laying ship; Acquire the monitoring data fed back by each monitoring device during the operation of the laying ship in real time, and capture the key target items in the large-scale laying process, including: large-scale laying speed, large-scale laying direction, large-scale laying depth difference, pause points and pause time during the laying process; Compare the key target items in the currently captured large-scale laying process with the large-scale laying characteristic database, mark the unconventional items in the captured key target items of the large-scale laying, and determine them as abnormal laying conditions; Based on the retrieved historical data, the identified laying abnormalities are predicted and risk assessed, and the corresponding solutions are matched based on the prediction results to generate laying risk response strategies, take different response measures in different abnormal situations, and make dynamic adjustments based on the actual situation; According to the prediction results and the laying risk response strategy, the configured laying ship operation parameters are adjusted, including the ship speed adjustment value, the tension adjustment value and the laying angle adjustment value; Obtain feedback data after the paving is completed, analyze the paving results, analyze the impact of unconventional items that occurred during this paving operation on the paving results, and determine whether the unconventional items should be included in the key target items for subsequent paving references.

[0006] Further, the operation parameters of the laying ship are configured, including: Obtain the operating capacity range of the laying vessel; Use geographic information monitoring equipment to obtain the operating span range formed between the laying area and the large layout storage location; Based on the large-scale laying characteristic database, obtaining a parameter range for a conventional laying operation; According to the operating capacity range of the laying vessel and the parameter range of conventional laying operations, the operating parameters of the laying vessel are configured within the operating span.

[0007] Furthermore, the preset large-scale layout paving characteristic database specifically includes: Determine the large arrangement classification mark based on the characteristics of the large arrangement, input it into a preset neural network for learning, determine the classification expression of the large arrangement classification mark, and construct a large arrangement classification model based on the classification expression; Input the obtained work preparation data into the large-scale arrangement classification model for classification, determine the large-scale arrangement type, obtain the environmental parameters of the paving area based on the paving environment characteristics, and predict the paving effects of different large-scale arrangement types in the paving area; Based on the monitoring equipment, the status information of the large-scale laying process is captured in real time, the laying characteristics are extracted, and the laying characteristics under different conditions are identified based on the extraction results, and possible abnormal conditions are identified; The large-scale arrangement type, laying environment and corresponding laying characteristics are integrated, and the integrated data are mapped into a vector space of fixed dimension based on the large-scale arrangement type to generate a large-scale arrangement laying characteristic database.

[0008] Furthermore, the key objectives in the large-scale laying process also include: The displacement volume of the laying ship is calculated based on the size parameters of the laying ship, the displacement of the laying ship is determined, and the effective load of the laying ship is calculated according to the displacement and the empty ship weight of the laying ship; Calculate the weight per unit length of the pipeline on the laying vessel based on the diameter of the pipeline and the laying depth; calculate the length of the pipeline that can be laid by the laying vessel based on the effective load of the laying vessel and the weight per unit length of the pipeline; Determine the starting and ending coordinates of the paving area according to the geographical location of the paving area, determine the center line of the paving area based on the starting and ending coordinates, and determine the navigation route of the paving ship based on the center line and the large-scale paving direction; Calculate the number of voyages of the laying ship according to the sailing route and pipeline length, and calculate the number of laying ships to be deployed according to the number of voyages and the working efficiency of the laying ship. , where N represents the number of laying vessels, N c Indicates the number of voyages, E f Indicates the working efficiency of the laying ship; The layout spacing of the laying ship is determined according to the navigation route and the number of laying ships, and the layout position of the laying ship is determined according to the layout spacing and the size parameters of the laying ship.

[0009] Furthermore, the unconventional items in the key target items of the large layout are marked and captured, including: Determine the large-scale laying speed and large-scale laying depth difference as conventional target items, and obtain the range value of each conventional target item based on historical data and industry standards; The pause points, large-scale laying directions and pause times in the laying process are determined as change target items, and the monitoring values ​​of each change target item are obtained through real-time monitoring equipment, and each change target item monitoring value is used as a marking value of an abnormal item; Based on the range values ​​of conventional target items, the monitored unconventional items are compared and analyzed to identify abnormal situations in large-scale laying.

[0010] Furthermore, generating a laying risk response strategy also includes: establishing a risk assessment matrix for different abnormal situations and predicted laying problems, dividing the risk levels based on the risk assessment matrix, and determining the priority of the response items in each laying risk response strategy based on each risk level.

[0011] Furthermore, a risk assessment matrix is ​​established for different abnormal situations and predicted laying problems, and risk levels are divided based on the risk assessment matrix, including: Retrieve the probability of occurrence of each abnormal situation during the large-scale laying process; Retrieve the predicted probability of occurrence of each laying problem; Retrieve the large-scale laying delay rate and economic loss rate corresponding to abnormal situations and laying problems; Obtaining an abnormal coefficient corresponding to the abnormal situation and the laying problem using the large-scale laying delay rate and economic loss rate corresponding to the abnormal situation and the laying problem; The abnormal coefficient corresponding to the abnormal situation is obtained by the following formula:

[0012] Among them, R 01 represents the abnormal coefficient corresponding to the abnormal situation; T and J represent the large-scale laying delay rate and economic loss rate corresponding to the abnormal situation; T c and J c Indicates the reference value of the large-scale laying delay rate and the reference value of the economic loss rate corresponding to the preset abnormal situation; k 01 represents a first adjustment coefficient, which is obtained through experiments according to actual application scenarios and is used to adjust the relative importance between the large-scale laying delay rate and the economic loss rate when abnormal situations occur, and the value range of the adjustment coefficient is 0.35-0.72; In addition, the abnormal coefficient corresponding to the laying problem is obtained by the following formula:

[0013] Among them, R 02 represents the abnormal coefficient corresponding to the laying problem; G and H represent the large-scale laying delay rate and economic loss rate corresponding to the laying problem; k 02 represents a second adjustment coefficient, which is obtained through experiments according to actual application scenarios and is used to adjust the relative importance between the large-scale laying delay rate and the economic loss rate when laying problems occur, and the value range of the adjustment coefficient is 0.21-0.74; A risk assessment matrix is ​​established using the abnormal conditions and abnormal coefficients corresponding to the laying problems, and risk levels are divided.

[0014] Furthermore, a risk assessment matrix is ​​established using the abnormal conditions and abnormal coefficients corresponding to the laying problems, and risk levels are divided, including: When the abnormal coefficient exceeds the first abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of high severity; when the abnormal coefficient does not exceed the first abnormal coefficient threshold, but exceeds the second abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of medium severity; when the abnormal coefficient does not exceed the second abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of general severity; Extracting a severity level parameter corresponding to each abnormal situation, wherein the severity level includes a high severity, a medium severity, and a general severity, and the severity level parameter corresponding to the high severity is 0.8, the severity level parameter corresponding to the medium severity is 0.6, and the severity level parameter corresponding to the general severity is 0.4; Extracting the severity level parameter corresponding to each paving problem, wherein the severity level includes a high severity, a medium severity and a general severity, and the severity level parameter corresponding to the high severity is 1, the severity level parameter corresponding to the medium severity is 0.8, and the severity level parameter corresponding to the general severity is 0.5; Establishing a risk assessment matrix using the occurrence probability corresponding to each abnormal situation and the severity level parameter corresponding to each abnormal situation in combination with the occurrence probability corresponding to each laying problem and the severity level parameter corresponding to each laying problem; The structure of the risk assessment matrix is ​​as follows:

[0015] Where A represents the risk assessment matrix; Y 1 , Y 2 ...Y n They represent the occurrence probabilities of n abnormal situations respectively; S y1 , S y2 ……S yn They represent the severity level parameters corresponding to n abnormal situations; W 1 , W 2 ...W m They represent the occurrence probabilities of m laying problems respectively; S w1 , S w2 ……S wm They represent the severity level parameters corresponding to m laying problems respectively; when m≠n, the vacant elements in the matrix are filled with the occurrence probability 0 and the severity level parameter 0.

[0016] Acquiring a norm of the risk assessment matrix according to the structure of the risk assessment matrix; Comparing the norm of the risk assessment matrix with a preset norm threshold; When the norm of the risk assessment matrix is ​​lower than a preset first norm threshold, the risk level is determined to be low; When the norm of the risk assessment matrix is ​​not lower than the preset first norm threshold but lower than the second norm threshold, the risk level is determined to be medium; When the norm of the risk assessment matrix is ​​not lower than a preset second norm threshold, the risk level is determined to be high.

[0017] Further, adjust the operation parameters of the laying ship, including: According to the predicted laying problems and the formulated response strategies, determine the types of laying ship operating parameters that need to be adjusted, and determine the adjustment direction and goals of each laying ship operating parameter; According to the risk level of laying problems and the priority of the response items in the laying risk response strategy, combined with the operation parameters of the laying ship, the large-scale layout characteristics and the laying environment, the ship speed adjustment value, the tension adjustment value and the laying angle adjustment value are calculated; The corresponding operating parameters of the laying vessel are adjusted according to the calculated adjustment values, and the adjusted operating parameters are compared and evaluated to determine whether the adjustment effect meets the expectations.

[0018] Furthermore, feedback data is obtained after the laying is completed, including the actual topographic data of the laying area, the actual laying position and status data of the large-scale laying, the operation data of the laying ship during the entire operation process, and the laying quality inspection data.

[0019] Compared with the prior art, the present invention has the following beneficial effects: Accurately configure and dynamically adjust ship speed, tension, laying angle and other parameters based on multiple factors to ensure efficient and stable operation of the laying vessel, improve laying efficiency and quality, and compare the key target items actually monitored with the preset large-scale laying characteristic database, mark unconventional items, and achieve effective prediction of laying problems. Formulate response strategies with clear priorities for different risk levels, which can solve potential problems in advance and reduce operational risks. After laying is completed, obtain multi-source feedback data, analyze laying results, establish a weight distribution strategy for unconventional items, and determine whether to include them in subsequent references. The continuous improvement mechanism can continuously optimize subsequent laying operations, accumulate experience, make the entire laying process more scientific and reliable, and provide strong guarantees for related projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The present invention is a flow chart of the large-scale laying design method of the laying ship. DETAILED DESCRIPTION

[0021] 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.

[0022] In order to solve the technical problems that the laying is not comprehensively considered to be affected by multiple factors such as regional location and hull parameters, which may easily cause the laying ship to operate beyond its capacity, resulting in resource waste, affecting quality progress and increasing risks, lack of comprehensive monitoring and analysis of key laying targets and systematic integration of large-scale layout characteristics and environmental data, making it difficult to discover problems in advance and scientifically guide laying, please refer to Figure 1 , this embodiment provides the following technical solutions: The design method of large-scale laying of laying vessels includes: Collecting operation preparation data, i.e. basic information and relevant scope related to the laying operation, including obtaining the geographical location of the laying area (clarifying its latitude and longitude range, topographical features, etc.), the geographical location of the large-scale layout storage location (planning the transportation route), the size parameters of the laying ship (such as ship length, ship width, ship height and draft), laying pipeline diameter and laying depth, and determining the laying environment and large-scale layout type based on the operation preparation data, and determining the laying ship's operating capacity and operating span range; Based on the data collection results of the operation preparation, combined with the preset large-layout laying characteristics database, the conventional operation parameter range under similar laying environments and large-layout types is retrieved, and the operation parameters of the laying ship are configured in combination with the operation capacity and operation span of the laying ship; Acquire the monitoring data fed back by each monitoring device during the operation of the laying ship in real time, and capture the key target items in the large-scale laying process. The key target items include: the laying speed of the large-scale laying, which is the average speed of the large-scale laying in the laying area; the laying direction of the large-scale laying, which is the angle formed by the laying path of the large-scale laying and the axes of different directions after the spatial rectangular coordinate system is established in the laying area; the laying depth difference of the large-scale laying, which refers to the difference in the laying depth of the large-scale laying captured at two monitoring time points; the pause point in the laying process, that is, the target position point where the large-scale laying stops in the laying area during the laying process; the pause time, which is the time consumed by the large-scale laying at the target position point in the laying area; Compare the key target items in the currently captured large-scale laying process with the large-scale laying characteristic database, mark the unconventional items in the captured key target items of the large-scale laying, and determine them as abnormal laying conditions; Based on the retrieved historical data, the identified laying abnormalities are predicted and risk assessed, and corresponding solutions are matched based on the prediction results, such as adjusting the operating parameters of the laying vessel, adjusting the type of large-scale laying, adjusting the laying method, performing equipment maintenance, etc., to generate laying risk response strategies, take different response measures in different abnormal situations, and make dynamic adjustments based on actual conditions; In this embodiment, it also includes: establishing a risk assessment matrix for different abnormal situations and predicted laying problems, dividing the risk levels based on the risk assessment matrix, and determining the priority of the response items in each laying risk response strategy based on each risk level. For high-risk laying problems, the most direct and effective response measures are taken first, such as immediately stopping the laying operation and conducting a comprehensive inspection and debugging of the equipment; for medium-risk problems, the operation parameters can be gradually adjusted during the laying process, while paying close attention to the development trend of the problem; for low-risk problems, the parameters can be appropriately optimized in the subsequent laying plan for prevention and control; According to the prediction results and the laying risk response strategy, the configured laying ship operation parameters are adjusted, including the ship speed adjustment value, the tension adjustment value and the laying angle adjustment value; Obtain feedback data after the completion of laying, including the actual topographic data of the laying area (obtained through high-precision measuring equipment), the actual laying position and status data of the large-scale layout (obtained by non-destructive testing technology and on-site investigation), the operation data of the laying ship during the entire operation process (extracted from the equipment log and monitoring system) and the laying quality inspection data (such as the inspection results of indicators such as laying flatness and density), and analyze the laying results, analyze the impact of unconventional items that appeared in this laying operation on the laying results, establish an unconventional item weight allocation strategy, and determine whether the unconventional items should be included in the key target items for subsequent laying references.

[0023] In this embodiment, the operation parameters are configured by comprehensively acquiring various information to ensure that the operation is carried out within the capabilities of the ship, thereby reducing resource waste and operation risks, capturing key target items in the large-scale laying process, and a preset large-scale laying characteristic database. The two are compared and unconventional items are marked, which can effectively discover problems that may arise in the laying process in advance. At the same time, a risk assessment matrix is ​​established to divide risk levels, determine the priority of response projects, and generate a dynamic laying risk response strategy. Targeted measures can be taken in time to reduce laying risks. The laying ship operation parameters can be dynamically adjusted to adapt to changes in the laying process, thereby improving the flexibility and adaptability of laying. Multi-source feedback data after the laying is completed is obtained and the laying results are analyzed. A weight allocation strategy for unconventional items is established to determine whether to include them in subsequent references. This is conducive to summarizing experience and lessons, continuously improving laying methods, and achieving scientific guidance for laying operations.

[0024] Specifically, for different abnormal situations and predicted laying problems, a risk assessment matrix is ​​established, and risk levels are divided based on the risk assessment matrix, including: Retrieve the probability of occurrence of each abnormal situation during the large-scale laying process; Retrieve the predicted probability of occurrence of each laying problem; Retrieve the large-scale laying delay rate and economic loss rate corresponding to abnormal situations and laying problems; Obtaining an abnormal coefficient corresponding to the abnormal situation and the laying problem using the large-scale laying delay rate and economic loss rate corresponding to the abnormal situation and the laying problem; The abnormal coefficient corresponding to the abnormal situation is obtained by the following formula:

[0025] Among them, R 01 represents the abnormal coefficient corresponding to the abnormal situation; T and J represent the large-scale laying delay rate and economic loss rate corresponding to the abnormal situation; T c and J c Indicates the reference value of the large-scale laying delay rate and the reference value of the economic loss rate corresponding to the preset abnormal situation; k 01 represents a first adjustment coefficient, which is obtained through experiments according to actual application scenarios and is used to adjust the relative importance between the large-scale laying delay rate and the economic loss rate when abnormal situations occur, and the value range of the adjustment coefficient is 0.35-0.72; In addition, the abnormal coefficient corresponding to the laying problem is obtained by the following formula:

[0026] Among them, R 02 represents the abnormal coefficient corresponding to the laying problem; G and H represent the large-scale laying delay rate and economic loss rate corresponding to the laying problem; k 02 It represents the second adjustment coefficient, which is obtained through experiments according to actual application scenarios, and is used to adjust the relative importance between the large-scale laying delay rate and the economic loss rate when laying problems occur. The value range of the adjustment coefficient is 0.21-0.74.

[0027] The technical effect of the above technical solution is as follows: the solution comprehensively considers various abnormal situations and predicted laying problems that may occur during the large-scale laying process, and establishes a comprehensive and systematic risk assessment system by retrieving their corresponding probability of occurrence, delay rate and economic loss rate. This helps to comprehensively identify and manage potential risks and ensure the smooth progress of the project. The solution quantitatively evaluates the risks of abnormal situations and laying problems by introducing abnormal coefficients. This quantitative method makes the severity of risks more intuitive and easy to understand, provides decision makers with accurate risk information, and helps to make more scientific and reasonable decisions. The adjustment coefficients (k01 and k02) in the solution can be obtained through experiments according to actual application scenarios, which increases the flexibility and applicability of the solution. Different projects or application scenarios may require different risk assessment standards. By adjusting the adjustment coefficients, it can be ensured that the risk assessment results are more in line with the actual situation. The solution provides a structured risk management method that helps organizations form a continuous risk management culture. By continuously accumulating experience and data, the setting of risk assessment matrix and adjustment coefficient can be further improved, thereby improving the accuracy and efficiency of risk management.

[0028] In summary, this technical solution provides strong support for the smooth progress of the project and risk management through its technical effects in comprehensively and systematically identifying and managing potential risks, quantitatively assessing the severity of risks, providing flexible and applicable risk assessment standards, clearly dividing risk levels, building an intuitive risk assessment matrix, and promoting continuous improvement of risk management.

[0029] Specifically, a risk assessment matrix is ​​established using the abnormal conditions and abnormal coefficients corresponding to the laying problems, and risk levels are divided, including: When the abnormal coefficient exceeds the first abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of high severity; when the abnormal coefficient does not exceed the first abnormal coefficient threshold, but exceeds the second abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of medium severity; when the abnormal coefficient does not exceed the second abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of general severity; Extracting a severity level parameter corresponding to each abnormal situation, wherein the severity level includes a high severity, a medium severity, and a general severity, and the severity level parameter corresponding to the high severity is 0.8, the severity level parameter corresponding to the medium severity is 0.6, and the severity level parameter corresponding to the general severity is 0.4; Extracting the severity level parameter corresponding to each paving problem, wherein the severity level includes a high severity, a medium severity and a general severity, and the severity level parameter corresponding to the high severity is 1, the severity level parameter corresponding to the medium severity is 0.8, and the severity level parameter corresponding to the general severity is 0.5; Establishing a risk assessment matrix using the occurrence probability corresponding to each abnormal situation and the severity level parameter corresponding to each abnormal situation in combination with the occurrence probability corresponding to each laying problem and the severity level parameter corresponding to each laying problem; The structure of the risk assessment matrix is ​​as follows:

[0030] Where A represents the risk assessment matrix; Y 1 , Y 2 ...Y n They represent the occurrence probabilities of n abnormal situations respectively; S y1 , S y2 ……S yn They represent the severity level parameters corresponding to n abnormal situations; W 1 , W 2 ...W m They represent the occurrence probabilities of m laying problems respectively; S w1 , S w2 ……S wm They represent the severity level parameters corresponding to m laying problems respectively; when m≠n, the vacant elements in the matrix are filled with the occurrence probability 0 and the severity level parameter 0.

[0031] Acquiring a norm of the risk assessment matrix according to the structure of the risk assessment matrix; Comparing the norm of the risk assessment matrix with a preset norm threshold; When the norm of the risk assessment matrix is ​​lower than a preset first norm threshold, the risk level is determined to be low; When the norm of the risk assessment matrix is ​​not lower than the preset first norm threshold but lower than the second norm threshold, the risk level is determined to be medium; When the norm of the risk assessment matrix is ​​not lower than a preset second norm threshold, the risk level is determined to be high.

[0032] The technical effect of the above technical scheme is: the scheme divides the severity levels of abnormal situations and laying problems into three levels of greater severity, medium severity and general severity by setting the first abnormal coefficient threshold and the second abnormal coefficient threshold. This clear division helps to prioritize different risks, so as to reasonably allocate resources and formulate countermeasures. The scheme constructs a risk assessment matrix using the probability of occurrence, severity level parameters of abnormal situations and the probability of occurrence, severity level parameters of laying problems. This matrix intuitively shows the risk level and probability of occurrence of various risks and problems, providing strong support for risk management and decision-making. When the number of abnormal situations is not equal to the number of laying problems, the scheme fills the vacant elements in the matrix with the probability of occurrence 0 and the severity level parameter 0. This processing method ensures the integrity and consistency of the risk assessment matrix and avoids the deviation of the assessment results caused by missing data. At the same time, by setting different abnormal coefficient thresholds, the severity levels of abnormal situations and laying problems are subdivided into three levels of greater severity, medium severity and general severity. This subdivision makes risk management more refined, and different countermeasures can be taken for risks of different levels, thereby improving the pertinence and effectiveness of risk management. Specific severity level parameters are assigned to each severity level, which reflect the severity of different levels of risk. When establishing the risk assessment matrix, the probability and severity level parameters of abnormal situations, as well as the probability and severity level parameters of laying problems, are combined. This enables decision makers to more intuitively understand the overall situation and priority of risks, providing strong support for the formulation of scientific and reasonable response measures. The solution comprehensively considers multiple factors such as the probability of occurrence of abnormal situations and laying problems, delay rate and economic loss rate, and quantifies risks by calculating abnormal coefficients. At the same time, the risk assessment matrix is ​​used to integrate multiple risk factors to form a comprehensive and accurate risk assessment system. This helps to comprehensively identify and manage potential risks and improve the accuracy and reliability of risk assessment. By establishing a risk assessment matrix, organizations can regularly review and update risk data and continuously optimize risk assessment models. With the accumulation of experience and the enrichment of data, risks can be assessed more accurately and the efficiency and effectiveness of risk management can be improved. At the same time, this also helps to form a continuous risk management culture and promote the continuous progress of organizations in risk management.

[0033] At the same time, the scheme provides a standardized framework for risk assessment by calling the preset risk assessment matrix. This ensures the consistency and repeatability of the assessment process and reduces the assessment bias caused by human factors. By calculating the norm of the risk assessment matrix and comparing it with the preset norm threshold, the scheme can quantitatively divide the risk level. This quantitative method makes the determination of risk level more objective and accurate, which is convenient for subsequent risk management and the formulation of countermeasures. Using the risk assessment matrix and the norm comparison method, the risk level can be quickly determined without complex analysis and calculation. This greatly improves the efficiency of risk assessment, especially in emergency situations that require rapid response. Clear risk level division can provide strong support for decision makers. Different levels of risk correspond to different countermeasures and resource inputs, which helps decision makers make reasonable decisions based on risk levels and optimize resource allocation. The preset norm threshold in the scheme can be adjusted and optimized according to actual conditions. With the deepening of risk management practice and the accumulation of experience, the risk assessment matrix and norm threshold can be continuously improved to improve the accuracy and effectiveness of risk management. Through clear risk level division and corresponding countermeasures, the scheme helps to enhance the awareness and attention to risks within the organization. This can promote the formation of a positive risk management culture in the organization and improve the overall risk management level.

[0034] In summary, this technical solution achieves standardization, quantification, efficiency and decision support of risk assessment by dividing risk levels based on the risk assessment matrix, which helps organizations improve their risk management capabilities and levels.

[0035] In this embodiment, the configuration of the laying ship operation parameters specifically includes: Obtain the operating capacity range of the laying vessel; Use geographic information monitoring equipment to obtain the operating span range formed between the laying area and the large layout storage location; Based on the large-scale laying characteristic database, obtaining a parameter range for a conventional laying operation; According to the operating capacity range of the laying ship and the parameter range of conventional laying operations, the operating parameters of the laying ship are configured within the operating span to ensure the normal operation of the laying ship.

[0036] In this embodiment, combined with the parameter range of conventional laying operations, the laying vessel can operate efficiently and safely within the operating span between the laying area and the large layout storage location, avoiding waste of resources, low operating efficiency and potential safety risks caused by improper configuration of operating parameters, improving the overall planning and execution capabilities of the laying operation, and ensuring the smooth progress of the laying operation and high-quality laying results.

[0037] In this embodiment, the key objectives in the large-scale laying process also include: The displacement volume of the laying ship is calculated based on the size parameters of the laying ship, the displacement of the laying ship is determined, and the effective load of the laying ship is calculated according to the displacement and the empty ship weight of the laying ship; Calculate the weight per unit length of the pipeline on the laying vessel based on the diameter of the pipeline and the laying depth; calculate the length of the pipeline that can be laid by the laying vessel based on the effective load of the laying vessel and the weight per unit length of the pipeline; Determine the starting and ending coordinates of the paving area according to the geographical location of the paving area, determine the center line of the paving area based on the starting and ending coordinates, and determine the navigation route of the paving ship based on the center line and the large-scale paving direction; Calculate the number of voyages of the laying ship according to the sailing route and pipeline length, and calculate the number of laying ships to be deployed according to the number of voyages and the working efficiency of the laying ship. , where N represents the number of laying vessels, N c Indicates the number of voyages, E f Indicates the working efficiency of the laying ship; The layout spacing of the laying ship is determined according to the sailing route and the number of laying ships, and the layout position of the laying ship is determined according to the layout spacing and the size parameters of the laying ship (ship length and ship width).

[0038] In this embodiment, the effective load, the weight per unit length of the pipeline and the layable length are determined through parameters such as the size of the laying vessel, the load-bearing and operating range is accurately grasped, safety is ensured, and resource utilization is improved. The navigation route is determined in combination with the location of the laying area, the spacing and position are clarified, the operation path and layout are scientifically planned, the operation efficiency is improved, and the quality and uniformity of large-scale laying are guaranteed.

[0039] In this embodiment, the preset large-scale layout paving characteristic database specifically includes: Determine the large arrangement classification mark based on the characteristics of the large arrangement, input it into a preset neural network for learning, determine the classification expression of the large arrangement classification mark, and construct a large arrangement classification model based on the classification expression; Input the obtained operation preparation data into the large-scale arrangement classification model for classification, determine the large-scale arrangement type, obtain the geological conditions, water flow velocity and other environmental parameters of the paving area based on the paving environment characteristics, and predict the paving effects of different large-scale arrangement types in the paving area; Based on the monitoring equipment, the status information of the large-scale laying process is captured in real time, and the laying characteristics are extracted, such as settlement speed, laying depth, tension change, deformation degree, etc. Based on the extraction results, the laying characteristics under different conditions are identified, such as uneven settlement, severe deformation, excessive tension, etc., and possible abnormal conditions are identified, such as equipment failure, data error, etc. The large-scale arrangement type, laying environment and corresponding laying characteristics are integrated, and the integrated data are mapped into a vector space of fixed dimension based on the large-scale arrangement type to generate a large-scale arrangement laying characteristic database.

[0040] In this embodiment, the expression of the large-scale layout classification mark is determined by learning through a preset neural network, and a classification model is constructed. The large-scale layout can be accurately classified, and the laying effects of different types of large-scale layouts can be predicted in advance based on the laying environment parameters. The laying status information can be captured in real time, the characteristic features can be extracted and the anomalies can be identified. Potential problems can be discovered in time, and a database can be integrated to provide a comprehensive and accurate reference basis for subsequent large-scale layout laying operations, thereby improving the laying efficiency and quality.

[0041] In this embodiment, the unconventional items in the key target items of the large-scale layout paving captured by marking specifically include: Determine the large-scale laying speed and the large-scale laying depth difference as conventional target items, and obtain the range value of each conventional target item based on historical data and industry standards, such as the optimal laying speed range and laying depth variation range of different types of large-scale laying; The pause point, large-scale laying direction and pause time in the laying process are determined as change target items, and the monitoring value of each change target item is obtained through real-time monitoring equipment, and each change target item monitoring value is used as a marking value of an unconventional item, such as the position of the pause point, the change range of the laying direction, the length of the pause time, etc.; Compare and analyze the monitored unconventional items based on the range values ​​of conventional target items to identify abnormal conditions in large-scale laying, such as laying speed that is too fast or too slow, deviation from the laying direction, and long pause time, and then predict possible laying problems; In this embodiment, the pause point in the laying process, that is, the point where the large arrangement stops at the target object position in the laying area during the laying process, and its specific position (the position of the pause point) is used as the marking value of the abnormal item; for example, if the large arrangement frequently pauses at a specific obstacle, this position is a marking point of the abnormal situation; Large-scale laying direction: after the spatial rectangular coordinate system is established in the laying area, the angle formed by the large-scale laying path and the axes of different directions. The variation range (variation range of laying direction) is used as the marking value of the unconventional item; for example, if the laying direction deviates greatly from the preset direction, it is an unconventional situation; Pause time: the time that the large layout stays at the target object position in the layout area. Its length (the length of the pause time) is used as the marking value of the abnormal item; if the pause time is too long and exceeds the normal range, it is regarded as an abnormal situation.

[0042] In this embodiment, conventional target items and their range values ​​are clarified to provide a reference standard for judging abnormalities. Pause points, laying directions, pause times, etc. are determined as variable target items. Their monitoring values ​​are used as marking values. Dynamic abnormalities in laying can be accurately captured. By comparing and analyzing with the range values ​​of conventional target items, abnormal situations such as abnormal speed, deviation in direction, and excessive pauses can be quickly identified, and possible laying problems can be predicted, which helps to take measures in advance to avoid problems from worsening, improve laying quality and efficiency, and reduce operational risks.

[0043] In this embodiment, the operation parameters of the laying ship are adjusted, specifically including: According to the predicted laying problems and the formulated coping strategies, the types of laying ship operating parameters that need to be adjusted are determined, including ship speed, tension and laying angle, etc., and the adjustment direction and target of each laying ship operating parameter are determined. For example, if it is predicted that the laying speed of the large-scale laying is too fast, resulting in uneven laying, then the goal of the ship speed adjustment value is to reduce the ship speed to reach the appropriate laying speed range; if it is found that the tension is too high during the laying process, affecting the laying quality of the large-scale laying, then the direction of the tension adjustment value is to reduce the tension; According to the risk level of the laying problem and the priority of the response items in the laying risk response strategy, combined with the operating parameters of the laying ship, the large-scale layout characteristics and the laying environment, the ship speed adjustment value, the tension adjustment value and the laying angle adjustment value are calculated. For example, according to the power system characteristics of the laying ship, the current ship speed and the required adjustment target, the ship speed adjustment value is calculated using the dynamic formula; according to the material, structure and stress conditions of the large-scale layout, combined with the data of the tension sensor, the tension adjustment value is calculated using the principle of mechanics; according to the topography of the laying area, the direction of water flow and the preset laying path, the laying angle adjustment value is calculated by mathematical methods such as trigonometric functions; Adjust the corresponding operating parameters of the laying ship according to the calculated adjustment values, and compare and evaluate the adjusted operating parameters to determine whether the adjustment effect meets the expectations. When adjusting the ship speed, increase or decrease the ship speed by a small amount each time, and observe the navigation stability of the ship and the laying conditions of the large layout; when adjusting the tension, monitor the data of the tension sensor in real time to make it gradually approach the adjusted target value.

[0044] In this embodiment, the type, direction and target of the operating parameters to be adjusted are clarified based on the predicted problems and response strategies to make the adjustment targeted. The adjustment value is calculated in combination with the risk level, ship and cloth characteristics and the environment. The operation is performed according to the adjustment value and the effect is evaluated. Small adjustments are made and monitored in real time to ensure that the adjustment process is smooth and the adjustment effect meets the expectations, thereby improving the quality and efficiency of large-scale laying.

[0045] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A large-scale laying design method for laying vessels, characterized in that: include: Determine the laying environment and large-scale layout type based on the collected operation preparation data, determine the laying ship's operating capacity and operating span range, and based on the operation preparation data collection results, retrieve the conventional operating parameter range under similar laying environments and large-scale layout types in combination with the preset large-scale layout laying characteristic database, and configure the laying ship's operating parameters in combination with the laying ship's operating capacity and operating span range; Acquire the monitoring data fed back by each monitoring device during the operation of the laying ship in real time, capture the key target items in the large-scale laying process, compare the key target items in the large-scale laying process currently captured with the large-scale laying characteristic database, mark the unconventional items in the captured key target items of the large-scale laying, and determine them as abnormal laying conditions; Based on the retrieved historical data, the identified laying anomalies are predicted and risk assessed, and the configured laying vessel operation parameters are adjusted; Obtain feedback data after the laying is completed, analyze the impact of unconventional items in this laying operation on the laying results, and determine whether unconventional items should be included in the key target items for subsequent laying references; The key objectives in the large-scale laying process also include: The displacement volume of the laying ship is calculated based on the size parameters of the laying ship, the displacement of the laying ship is determined, and the effective load of the laying ship is calculated according to the displacement and the empty ship weight of the laying ship; Calculate the weight per unit length of the pipeline on the laying vessel based on the diameter of the pipeline and the laying depth; calculate the length of the pipeline that can be laid by the laying vessel based on the effective load of the laying vessel and the weight per unit length of the pipeline; Determine the starting and ending coordinates of the paving area according to the geographical location of the paving area, determine the center line of the paving area based on the starting and ending coordinates, and determine the navigation route of the paving ship based on the center line and the large-scale paving direction; Calculate the number of voyages of the laying ship according to the sailing route and pipeline length, and calculate the number of laying ships to be deployed according to the number of voyages and the working efficiency of the laying ship. , where N represents the number of laying vessels, N c Indicates the number of voyages, E f Indicates the working efficiency of the laying ship; The layout spacing of the laying ships is determined according to the navigation route and the number of laying ships, and the layout position of the laying ships is determined according to the layout spacing and the size parameters of the laying ships.

2. The large-scale laying design method for laying vessels according to claim 1 is characterized in that: The configuration of the laying ship operation parameters specifically includes: Obtain the operating capacity range of the laying vessel; Use geographic information monitoring equipment to obtain the operating span formed between the laying area and the large layout storage location; Based on the large-scale laying characteristic database, obtaining a parameter range for a conventional laying operation; According to the operating capacity range of the laying vessel and the parameter range of conventional laying operations, the operating parameters of the laying vessel are configured within the operating span.

3. The large-scale laying design method for laying vessels according to claim 2 is characterized in that: The preset large-scale laying characteristics database includes: Determine the large arrangement classification mark based on the characteristics of the large arrangement, input it into a preset neural network for learning, determine the classification expression of the large arrangement classification mark, and construct a large arrangement classification model based on the classification expression; Input the obtained work preparation data into the large-scale arrangement classification model for classification, determine the large-scale arrangement type, obtain the environmental parameters of the paving area based on the paving environment characteristics, and predict the paving effects of different large-scale arrangement types in the paving area; Based on the monitoring equipment, the status information of the large-scale laying process is captured in real time, the laying characteristics are extracted, and the laying characteristics under different conditions are identified based on the extraction results, and possible abnormal conditions are identified; The large-scale arrangement type, laying environment and corresponding laying characteristics are integrated, and the integrated data are mapped into a vector space of fixed dimension based on the large-scale arrangement type to generate a large-scale arrangement laying characteristic database.

4. The large-scale laying design method for laying vessels according to claim 1, characterized in that: Mark and capture the unconventional items in the key target items of large-scale layout laying, including: Determine the large-scale laying speed and large-scale laying depth difference as conventional target items, and obtain the range value of each conventional target item based on historical data and industry standards; The pause points, large-scale laying directions and pause times in the laying process are determined as change target items, and the monitoring values ​​of each change target item are obtained through real-time monitoring equipment, and each change target item monitoring value is used as a marking value of an abnormal item; Based on the range values ​​of conventional target items, the monitored unconventional items are compared and analyzed to identify abnormal situations in large-scale laying.

5. The large-scale laying design method for laying vessels according to claim 1, characterized in that: Generating a laying risk response strategy also includes: establishing a risk assessment matrix for different abnormal situations and predicted laying problems, dividing the risk levels based on the risk assessment matrix, and determining the priority of the response items in each laying risk response strategy based on each risk level.

6. The large-scale laying design method for laying vessels according to claim 5, characterized in that: According to different abnormal situations and predicted laying problems, a risk assessment matrix is ​​established, and risk levels are divided based on the risk assessment matrix, including: Retrieve the probability of occurrence of each abnormal situation during the large-scale laying process; Retrieve the predicted probability of occurrence of each laying problem; Retrieve the large-scale laying delay rate and economic loss rate corresponding to abnormal situations and laying problems; Obtaining an abnormal coefficient corresponding to the abnormal situation and the laying problem by using the large-scale laying delay rate and economic loss rate corresponding to the abnormal situation and the laying problem; The abnormal coefficient corresponding to the abnormal situation is obtained by the following formula: ； Among them, R 01 represents the abnormal coefficient corresponding to the abnormal situation; T and J represent the large-scale laying delay rate and economic loss rate corresponding to the abnormal situation; T c and J c Indicates the reference value of the large-scale laying delay rate and the reference value of the economic loss rate corresponding to the preset abnormal situation; k 01 represents a first adjustment coefficient, which is used to adjust the relative importance between the large-scale laying delay rate and the economic loss rate when abnormal conditions occur, and the value range of the adjustment coefficient is 0.35-0.72; In addition, the abnormal coefficient corresponding to the laying problem is obtained by the following formula: ； Among them, R 02 represents the abnormal coefficient corresponding to the laying problem; G and H represent the large-scale laying delay rate and economic loss rate corresponding to the laying problem; k 02 represents a second adjustment coefficient, which is used to adjust the relative importance between the large-scale laying delay rate and the economic loss rate when laying problems occur, and the value range of the adjustment coefficient is 0.21-0.74; A risk assessment matrix is ​​established using the abnormal conditions and abnormal coefficients corresponding to the laying problems, and risk levels are divided.

7. The large-scale laying design method for laying vessels according to claim 6, characterized in that: A risk assessment matrix is ​​established using the abnormal conditions and abnormal coefficients corresponding to the laying problems, and risk levels are divided, including: When the abnormal coefficient exceeds the first abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of high severity; when the abnormal coefficient does not exceed the first abnormal coefficient threshold, but exceeds the second abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of medium severity; when the abnormal coefficient does not exceed the second abnormal coefficient threshold, the severity level corresponding to the abnormal situation and the laying problem is determined to be of general severity; Extracting a severity level parameter corresponding to each abnormal situation, wherein the severity level includes a high severity, a medium severity, and a general severity, and the severity level parameter corresponding to the high severity is 0.8, the severity level parameter corresponding to the medium severity is 0.6, and the severity level parameter corresponding to the general severity is 0.4; Extracting the severity level parameter corresponding to each paving problem, wherein the severity level includes a high severity, a medium severity and a general severity, and the severity level parameter corresponding to the high severity is 1, the severity level parameter corresponding to the medium severity is 0.8, and the severity level parameter corresponding to the general severity is 0.5; Establishing a risk assessment matrix using the occurrence probability corresponding to each abnormal situation and the severity level parameter corresponding to each abnormal situation in combination with the occurrence probability corresponding to each laying problem and the severity level parameter corresponding to each laying problem; Acquiring a norm of the risk assessment matrix according to the structure of the risk assessment matrix; Comparing the norm of the risk assessment matrix with a preset norm threshold; When the norm of the risk assessment matrix is ​​lower than a preset first norm threshold, the risk level is determined to be low; When the norm of the risk assessment matrix is ​​not lower than the preset first norm threshold but lower than the second norm threshold, the risk level is determined to be medium; When the norm of the risk assessment matrix is ​​not lower than a preset second norm threshold, the risk level is determined to be high.

8. The large-scale laying design method for laying vessels according to claim 1, characterized in that: The operation parameters of the laying ship include the ship speed adjustment value, tension adjustment value and laying angle adjustment value. Adjusting the operation parameters of the laying ship includes: According to the predicted laying problems and the formulated response strategies, determine the types of laying ship operating parameters that need to be adjusted, and determine the adjustment direction and goals of each laying ship operating parameter; According to the risk level of laying problems and the priority of the response items in the laying risk response strategy, combined with the operation parameters of the laying ship, the large-scale layout characteristics and the laying environment, the ship speed adjustment value, the tension adjustment value and the laying angle adjustment value are calculated; The corresponding operating parameters of the laying vessel are adjusted according to the calculated adjustment values, and the adjusted operating parameters are compared and evaluated to determine whether the adjustment effect meets the expectations.

9. The large-scale laying design method for laying vessels according to claim 8, characterized in that: Obtain feedback data after the laying is completed, including the actual topographic data of the laying area, the actual laying position and status data of the large-scale laying, the operation data of the laying ship during the entire operation process, and the laying quality inspection data.

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