Offshore hoisting operation time prediction method and system

Abstract

The invention relates to an offshore hoisting operation time prediction method and system, and the method comprises the steps: calculating the motion state of a floating type sea surface hoisting platform and the stable state of a shield tunneling machine part hoisted on a hoisting support arm under meteorological prediction data based on the meteorological prediction data outputted by a meteorological prediction model; if the fluctuating motion amplitude, the fluctuating motion frequency and the horizontal stable state of the floating type sea surface hoisting platform are normal within one or more future time points, and shield tunneling machine parts hoisted on the hoisting support arms are not influenced by sea wind and are kept stable, the future time points are used as target time points. The target time point constitutes a job prediction time period in which the job can be normally performed. Based on the meteorological prediction data, the time for safe operation can be effectively predicted, and it is ensured that the shield tunneling machine can be accurately and stably hoisted in place.

Description

Technical Field

[0001] This invention relates to the field of marine operation support technology, specifically a method and system for predicting the time of marine lifting operations. Background Technology

[0002] As a modern underground engineering construction machine, the tunnel boring machine (TBM) plays an irreplaceable role in subway construction. As an essential part of TBM construction, the dismantling of the TBM after completing its tunneling task is characterized by high specialization, high risk, and numerous limiting factors. Due to the limited size of the tunnel shaft opening and the large size and weight of the TBM, the conventional dismantling procedure involves the TBM entering the station shaft opening, dismantling the four main components—the cutterhead, front shield, middle shield, and tail shield—and then directly hoisting them out of the shaft.

[0003] The most prominent characteristic of offshore tunnel boring machine (TBM) hoisting operations is the high winds and waves, which directly impact the stability and safety of the operation. Wind and waves can cause the hoisting equipment (e.g., cranes, slings, etc.) to sway and shift, increasing operational difficulty and risk. Changes in ocean currents and tides can affect the positioning accuracy and stability of the hoisting operation. Therefore, the impact of tidal variations on the hoisting height and angle must be fully considered during the hoisting process.

[0004] Therefore, there is a need to provide a method for predicting the time of offshore lifting operations, in order to determine the appropriate time for offshore tunnel boring machine (TBM) lifting operations and improve the safety of offshore TBM lifting. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method and system for predicting the time of offshore lifting operations, so as to solve the problems in the background art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The present invention provides a method for predicting the time of offshore lifting operations, comprising the following steps:

[0008] Obtain meteorological forecast data for sea level, wherein the meteorological forecast data includes wind speed, wind direction, wave height, wave period, ocean current speed, and ocean current direction at multiple future time points;

[0009] Based on the meteorological forecast data, the motion state of the floating sea surface hoisting platform and the stability state of the shield machine parts hoisted on the hoisting boom at multiple future time points are calculated. The motion state of the floating sea surface hoisting platform includes the maximum amplitude of the undulation motion, the frequency of the undulation motion, and the horizontal stability state of the sea surface hoisting platform.

[0010] The future time point that simultaneously meets the target conditions is taken as the target time point. The target conditions include: the maximum amplitude of the undulation motion of the sea surface hoisting platform is less than a preset amplitude threshold, the motion frequency of the sea surface hoisting platform is less than a preset frequency threshold, the sea surface hoisting platform is in a stable state in the horizontal direction, and the shield machine parts are in a stable state.

[0011] The predicted time period for the task is constructed based on the target time point.

[0012] In one embodiment of this application, calculating the maximum amplitude of the undulation motion of a floating sea-based hoisting platform at multiple future time points based on the meteorological forecast data includes:

[0013] The wave height and wave period are input into a pre-built prediction model to obtain the maximum amplitude of the undulation motion of the floating sea surface hoisting platform at multiple future time points. The prediction model represents the correspondence between the wave parameters and the maximum amplitude of the undulation motion of the floating sea surface hoisting platform. The wave parameters include wave height and wave period.

[0014] In one embodiment of this application, the method for constructing the prediction model includes:

[0015] Acquire historical wave heights, historical wave periods, and the historical maximum amplitude of motion of the floating offshore hoisting platform at multiple historical time points;

[0016] Construct a binary regression equation, wherein the mathematical expression of the binary regression equation is:

[0017] Y max =β1×H+β2×T+α

[0018] In the formula, Y max The historical maximum amplitude of the movement is represented by H, the historical wave height is represented by T, the historical wave period is represented by β1, the wave height coefficient is represented by β2, and the period coefficient is represented by α, which is the error term.

[0019] Based on the historical wave height, historical wave period, and historical maximum amplitude of the floating sea-surface hoisting platform at multiple historical time points, and by fitting the data using the least squares method, a prediction model is obtained.

[0020] In one embodiment of this application, the undulating motion frequency of the sea surface hoisting platform is the wave frequency ω, where ω = T / 2π, and T is the wave period.

[0021] In one embodiment of this application, calculating the horizontal stability state of a sea-based hoisting platform at multiple future time points based on the meteorological forecast data includes:

[0022] The equivalent frontal area S1 and windward area S2 of the floating sea-surface hoisting platform are determined based on the ocean current direction and wind direction. Among them, S i Let θ be the area of ​​the i-th frontal surface. i Let S be the angle between the i-th upstream face and the ocean current, and n be the number of upstream faces. j Let θ be the area of ​​the j-th windward side. j Let m be the angle between the j-th windward side and the wind direction, and m be the number of windward sides.

[0023] Calculate the first horizontal force F1 exerted by the ocean current on the floating sea-surface hoisting platform and the second horizontal force F2 exerted by the sea wind on the floating sea-surface hoisting platform. The mathematical expressions for the first horizontal force F1 and the second horizontal force F2 are as follows:

[0024]

[0025] In the formula, ρ1 is the density of seawater, C d Where ρ is the seawater drag coefficient, v1 is the ocean current velocity, ρ2 is the air density, and C is the air pressure coefficient. w v1 is the drag coefficient, v2 is the wind speed;

[0026] The resultant force is calculated based on the first horizontal force F1, the second horizontal force F2, and the angle between the first horizontal force F1 and the second horizontal force F2, and the total horizontal force F is obtained.

[0027] Obtain the maximum resistance force F of the floating sea surface hoisting platform. a Wherein, the maximum resisting force F a Provided by a drive unit installed on the side of the floating sea-surface lifting platform;

[0028] Will satisfy F>F a The horizontally stable state at future time points of ×γ is marked as unstable, and F≤F a The horizontally stable state at a future time point of ×γ is marked as stable, where γ is a stability coefficient less than 1.

[0029] In one embodiment of this application, calculating the stable state of tunnel boring machine components at multiple future time points based on the meteorological forecast data includes:

[0030] Map wind speed and direction at multiple future time points to a one-dimensional coordinate system;

[0031] Construct a sliding window with a width equal to the construction time required, and perform sliding with a preset step size based on the sliding window. During each sliding, calculate the average wind speed, wind speed variance, and wind direction variance for all future time points within the sliding window.

[0032] When the average wind speed within the target sliding window is less than a preset wind speed threshold, the wind speed variance is less than a preset first variance threshold, and the wind direction variance is less than a preset second variance threshold, the stable state of the tunnel boring machine component at the future time point corresponding to the target sliding window is marked as a stable state.

[0033] In one embodiment of this application, constructing a job prediction time period based on the target time point includes:

[0034] When multiple target time points are consecutive, and these consecutive target time points are greater than or equal to the minimum operation duration, the consecutive target time points are used as the operation prediction time period.

[0035] In one embodiment of this application, the meteorological forecast data is a plurality of future time points within a preset time period after the current time point, and the meteorological forecast data is generated based on a meteorological forecast model.

[0036] In one embodiment of this application, it further includes:

[0037] Obtain the predicted rainfall for the specified time period;

[0038] When the predicted rainfall is greater than a preset rainfall threshold, the predicted time period for the operation is removed; when the predicted rainfall is less than or equal to the preset rainfall threshold, the predicted time period for the operation is retained.

[0039] This application also provides a system for predicting the time of offshore lifting operations, including:

[0040] The acquisition module is used to acquire meteorological forecast data of sea level, wherein the meteorological forecast data includes wind speed, wind direction, wave height, wave period, ocean current speed and ocean current direction at multiple future time points;

[0041] The calculation module is used to calculate the motion state of the floating sea surface hoisting platform and the stability state of the shield machine parts hoisted on the hoisting boom at multiple future time points based on the meteorological forecast data. The motion state of the floating sea surface hoisting platform includes the maximum amplitude of the undulation motion, the frequency of the undulation motion, and the horizontal stability state of the sea surface hoisting platform.

[0042] The filtering module is used to select future time points that simultaneously meet target conditions as target time points. The target conditions include: the maximum amplitude of the undulation motion of the sea surface hoisting platform is less than a preset amplitude threshold, the motion frequency of the sea surface hoisting platform is less than a preset frequency threshold, the sea surface hoisting platform is in a stable state in the horizontal direction, and the shield machine parts are in a stable state.

[0043] The prediction module is used to construct a predicted time period for the operation based on the target time point.

[0044] The beneficial effects of this invention are as follows: The method and system for predicting offshore lifting operation time, based on meteorological forecast data output from a meteorological forecast model, calculates the motion state of the floating offshore lifting platform and the stability state of the tunnel boring machine (TBM) components hoisted on the lifting boom under the given meteorological forecast data. If, at one or more future time points, the amplitude and frequency of the floating offshore lifting platform's undulating motion and its horizontal stability are normal, and the TBM components hoisted on the lifting boom remain stable without being affected by sea winds, then these future time points are taken as target time points. These target time points constitute the predicted operation period during which operations can proceed normally. Based on meteorological forecast data, this application can effectively predict the safe operating time, ensuring that the TBM can be accurately and smoothly hoisted into place. Attached Figure Description

[0045] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0046] Figure 1 This is an application scenario diagram of a method for predicting the time of offshore hoisting operations, as shown in one embodiment of this application;

[0047] Figure 2 This is a flowchart illustrating a method for predicting the time of offshore lifting operations in one embodiment of this application;

[0048] Figure 3 This is a schematic diagram of the horizontal force analysis of a floating work platform in one embodiment of this application;

[0049] Figure 4 This is a structural diagram of a marine lifting operation time prediction system shown in one embodiment of this application; Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the embodiments of this application is shown;

[0050] The attached diagram is labeled as follows: 110-Conversion shaft cofferdam, 120-Tunnel, 130-Floating sea-based lifting platform, 140-Lifting boom, 150-Shield machine parts; 501-CPU, 502-ROM, 503-RAM, 504-Bus, 505-I / O interface, 506-Input section, 507-Output section, 508-Storage section, 509-Communication section, 510-Driver, 511-Removable media. Detailed Implementation

[0051] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0052] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the layers related to the present invention and are not drawn according to the actual number, shape and size of the layers in the actual implementation. In the actual implementation, the form, number and proportion of each layer can be arbitrarily changed, and the layer layout may also be more complex.

[0053] Numerous details are explored in the following description to provide a more thorough explanation of embodiments of the invention; however, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details.

[0054] Figure 1 This is an application scenario diagram of a method for predicting the time of offshore lifting operations, as shown in one embodiment of this application. Figure 1 As shown, during the excavation of the undersea tunnel, a conversion shaft cofferdam 110 needs to be constructed on the seabed. The conversion shaft cofferdam 110 is connected to the undersea tunnel 120. The opening of the conversion shaft cofferdam 110 is on the sea surface. One side of the conversion shaft cofferdam 110 is a floating sea surface hoisting platform 130. The floating sea surface hoisting platform 130 is equipped with a hoisting arm 140. The end of the hoisting arm 140 is hoisted with a steel cable to lift the shield machine parts 150, thereby hoisting the shield machine parts 150 into the conversion shaft cofferdam 110 to provide them to the shield machine inside the undersea tunnel.

[0055] Specifically, the maximum operating radius of the tunnel boring machine (TBM) during hoisting is 38m, and the maximum weight of the cutterhead being lifted is 140t. The large size of the equipment and the long operating radius are the key challenges and difficulties of this project's hoisting. Offshore hoisting differs from land hoisting; the impact of wind and waves must be considered in advance to select an appropriate time while ensuring a certain safety factor. Anchoring of the floating crane and barges must also be carried out to ensure hoisting stability. Therefore, this application provides the following scheme to predict the operation time to ensure the stability and safety of the hoisting.

[0056] Figure 2 This is a flowchart illustrating a method for predicting the time of offshore lifting operations in one embodiment of this application, as shown below. Figure 2 As shown: A method for predicting the time of offshore lifting operations in this embodiment may include steps S210 to S240:

[0057] S210, acquire meteorological forecast data of sea level, wherein the meteorological forecast data includes wind speed, wind direction, wave height, wave period, ocean current speed and ocean current direction at multiple future time points;

[0058] The meteorological forecast data in this application is generated based on existing meteorological forecast models and can be provided by local weather stations or partner organizations. The meteorological forecast data in this application is for 3-5 days after the current time. Since specific forecast operation times are required, the time granularity of the forecast model is between 1-2 hours.

[0059] The weather forecasting model in this application can be a statistical model, a numerical model, a machine learning model, etc.

[0060] Among them, wind speed and wind direction are used to judge the stability of the shield machine parts suspended on the steel cable at the end of the lifting arm. Since the shield machine parts in this application are similar to pendulums, they are highly susceptible to the influence of sea winds.

[0061] Wave height and wave period are used to assess the stability of the undulating motion of a floating offshore lifting platform. This application employs a suspended platform for operational convenience, making it highly susceptible to wave influence. These waves include those generated by tides, sea breezes, and ocean currents.

[0062] The velocity and direction of ocean currents are used to determine the horizontal stability of floating sea-based lifting platforms. Suspended operating platforms are also easily affected by horizontal ocean currents (in reality, the direction is more complex, but this application simplifies it to the horizontal direction).

[0063] The above data, for the context of this application, is used to conduct stability analysis on the stability of the tunnel boring machine parts, the undulating motion of the floating sea-based hoisting platform, and the horizontal stability of the floating sea-based hoisting platform, assuming that they will be used in the future and during the operation.

[0064] S220, based on the meteorological forecast data, calculate the motion state of the floating sea surface hoisting platform and the stability state of the shield machine parts hoisted on the hoisting boom at multiple future time points, wherein the motion state of the floating sea surface hoisting platform includes the maximum amplitude of the undulation motion of the sea surface hoisting platform, the frequency of the undulation motion, and the horizontal stability state.

[0065] The specific analysis process is as follows:

[0066] (a) Maximum amplitude of undulation motion of offshore lifting platform

[0067] This application uses a binary regression model to determine the motion state of a floating sea-surface lifting platform at multiple future time points. According to linear wave theory and the Morrison equation, the main factors affecting a platform floating on the sea surface are wave height and period. In other words, the amplitude of the floating platform's periodic undulation motion under wave influence is affected by wave height and period. However, since linear wave theory and the Morrison equation involve numerous parameters that need to be measured, this application uses a binary regression model to find the correspondence between the motion amplitude of the floating sea-surface lifting platform and wave height and period in order to simplify the measurement workload. This establishes a predictive model. Therefore, the process of determining the maximum amplitude of the floating sea-surface lifting platform's undulation motion at multiple future time points based on the predictive model includes:

[0068] The wave height and wave period are input into a pre-built prediction model to obtain the maximum amplitude of the undulation motion of the floating sea surface hoisting platform at multiple future time points. The prediction model represents the correspondence between the wave parameters and the maximum amplitude of the undulation motion of the floating sea surface hoisting platform. The wave parameters include wave height and wave period.

[0069] The process of building a predictive model includes:

[0070] (1) Obtain the historical wave height, historical wave period, and historical maximum amplitude of the floating sea-based hoisting platform at multiple historical time points; wherein, the historical wave height and historical wave period at multiple historical time points are independent variables, and the historical maximum amplitude of the motion is the dependent variable. Therefore, the model in this application can be regarded as a binary regression model.

[0071] (2) Construct a binary regression equation, wherein the mathematical expression of the binary regression equation is:

[0072] Y max =β1×H+β2×T+α

[0073] In the formula, Y max The historical maximum amplitude of the movement is represented by H, the historical wave height is represented by T, the historical wave period is represented by β1, the wave height coefficient is represented by β2, and the period coefficient is represented by α, which is the error term.

[0074] (3) Based on the historical wave height, historical wave period and historical maximum amplitude of the floating sea surface hoisting platform at the multiple historical time points, and combined with the least squares method, a prediction model is obtained.

[0075] Specifically, this application treats the above model as a linear regression model, and therefore uses the least squares method for fitting to obtain the specific values ​​of the wave height coefficient β1, the period coefficient β2, and the error term α. However, in some cases, if the number of data samples is sufficient, it can also be regarded as a nonlinear regression model, and iterative optimization algorithms (such as gradient descent, Newton's method, etc.) can be used to find the optimal parameters.

[0076] Furthermore, after fitting, the model needs to be validated. This can be done using various statistical metrics (such as R-squared). 2 The model's fit can be evaluated using metrics such as scores, mean squared error (MSE), and root mean squared error (RMSE). Graphical tools such as residual plots can also be used to check whether the model's assumptions are met and to identify outliers or heteroscedasticity.

[0077] (ii) Frequency of undulating motion of offshore lifting platforms

[0078] In this application, the undulating motion frequency of the offshore lifting platform is the same as the wave frequency ω; where ω = T / 2π, and T is the wave period. Therefore, the undulating motion frequency of the offshore lifting platform can be obtained by simply converting the wave period.

[0079] (III) Horizontal Steady State

[0080] The horizontal forces acting on a floating work platform are highly complex, including wave horizontal components, sea wind forces, and ocean current forces. In this application, to simplify the analysis, the effects of ocean currents and sea winds are primarily considered. Specifically, this includes:

[0081] (1) Determine the equivalent frontal area S1 and windward area S2 of the floating sea surface hoisting platform based on the ocean current direction and wind direction. Among them, S i Let θ be the area of ​​the i-th frontal surface. i Let S be the angle between the i-th upstream face and the ocean current, and n be the number of upstream faces. j Let θ be the area of ​​the j-th windward side. j Let m be the angle between the j-th windward side and the wind direction, and m be the number of windward sides.

[0082] Figure 3 This is a schematic diagram of the horizontal force analysis of a floating work platform in one embodiment of this application, as shown below. Figure 3As shown, since this application only considers the horizontal forces exerted by ocean currents and winds on the floating platform, and the directions of ocean currents and winds may differ, this application first calculates the equivalent frontal area S1 and windward area S2 separately, and then calculates the corresponding forces. This application uses the angles between the wind direction and ocean current direction and multiple sides to calculate the equivalent area perpendicular to the direction. Assuming the shape of the floating platform projected onto the sea surface is approximately rectangular, there are 1-2 frontal and windward surfaces. The equivalent area can be obtained through simple trigonometric function conversion relationships.

[0083] (2) Calculate the first horizontal force F1 exerted by the ocean current on the floating sea-surface hoisting platform and the second horizontal force F2 exerted by the sea wind on the floating sea-surface hoisting platform. The mathematical expressions for the first horizontal force F1 and the second horizontal force F2 are as follows:

[0084]

[0085] In the formula, ρ1 is the density of seawater, C d Where ρ is the seawater drag coefficient, v1 is the ocean current velocity, ρ2 is the air density, and C is the air pressure coefficient. w v1 is the drag coefficient, v2 is the wind speed;

[0086] Where ρ1 is the density of seawater, C d Where ρ is the seawater drag coefficient, ρ2 is the air density, and C is the air density. w The drag coefficient can be obtained by consulting relevant materials.

[0087] (3) Calculate the resultant force based on the first horizontal force F1, the second horizontal force F2 and the angle between the first horizontal force F1 and the second horizontal force F2 to obtain the total horizontal force F;

[0088] The calculated directions of the first horizontal force F1 and the second horizontal force F2 may differ, therefore they cannot be directly added. This application determines the angle between the first horizontal force F1 and the second horizontal force F2 (i.e., the angle between the direction of the sea breeze and the direction of the ocean current), and then calculates their resultant force. The formula for the resultant force is: θ is the angle between the first horizontal force F1 and the second horizontal force F2.

[0089] (4) Obtain the maximum resistance force F of the floating sea surface hoisting platform. a Wherein, the maximum resisting force F a Provided by a drive unit installed on the side of the floating sea-surface lifting platform;

[0090] The floating sea-based lifting platform of this application is equipped with a drive unit on its side, which provides horizontal counterforce by driving propeller blades. The maximum counterforce F in this application... a It was obtained through preliminary experiments.

[0091] (5) satisfying F>F a The horizontally stable state at future time points of ×γ is marked as unstable, and F≤F a The horizontally stable state at a future time point of ×γ is marked as stable, where γ is a stability coefficient less than 1.

[0092] If the combined force of the sea breeze and ocean current is less than F a This indicates that the floating sea-level lifting platform can resist the combined forces of sea winds and currents, remaining stationary on the sea surface. However, in some cases, full-power operation of the drive unit can cause instability in the platform (e.g., vibration, inability to maintain power). Therefore, this application adds a stability coefficient less than 1 as a stabilizing counterforce F. a ×γ.

[0093] (iv) Stability of Tunnel Boring Machine Components

[0094] The stability of tunnel boring machine (TBM) components is primarily affected by sea breezes. Strong sea breezes or frequent changes in wind speed and direction can disrupt hoisting operations. Therefore, this application determines the stability of TBM components by analyzing future sea breeze speeds and their variations, specifically including:

[0095] (1) Map the wind speed and direction at multiple future time points to a one-dimensional coordinate system;

[0096] (2) Construct a sliding window with a width equal to the construction time required, and perform sliding with a preset step size based on the sliding window. During each sliding, calculate the average wind speed, wind speed variance, and wind direction variance for all future time points within the sliding window.

[0097] Since the stability of tunnel boring machine (TBM) components cannot be obtained by analyzing wind speed and direction changes at multiple time points (since it's impossible to directly obtain the changes at a single time point), this application constructs a sliding window to perform the sliding operation. Each window represents a time period that can meet the minimum construction time requirement. Stability analysis is performed within this window to obtain a relatively stable time period. In this application, stability is represented by wind speed variance and wind direction variance, while wind speed magnitude is represented by the average wind speed.

[0098] (3) When the average wind speed within the target sliding window is less than the preset wind speed threshold, the wind speed variance is less than the preset first variance threshold, and the wind direction variance is less than the preset second variance threshold, the stable state of the tunnel boring machine component at the future time point corresponding to the target sliding window is marked as a stable state.

[0099] When the average wind speed is less than the preset wind speed threshold, the wind speed variance is less than the preset first variance threshold, and the wind direction variance is less than the preset second variance threshold, it indicates that the overall wind speed in the corresponding time period is relatively low, and the wind speed and wind direction are relatively stable, which is suitable for hoisting operations.

[0100] S230, the future time point that simultaneously satisfies the target conditions is taken as the target time point, wherein the target conditions include:

[0101] (1) The maximum amplitude of the undulation motion of the offshore hoisting platform is less than the preset amplitude threshold.

[0102] (2) The movement frequency of the sea-surface hoisting platform is less than a preset frequency threshold;

[0103] (3) The offshore hoisting platform is in a stable state in the horizontal direction;

[0104] (3) The components of the tunnel boring machine meet the stability requirements;

[0105] In this application, if all four conditions mentioned above are met simultaneously, it can be concluded that the offshore lifting platform can stably and safely perform lifting operations at the target time point. Therefore, this is considered the target time point where construction can proceed.

[0106] S240, construct a job prediction time period based on the target time points. Specifically, when multiple target time points are consecutive, and these consecutive target time points are greater than or equal to the minimum job duration, the consecutive target time points are used as the job prediction time period.

[0107] In one embodiment of this application, rainfall is also incorporated. If there is significant rainfall at sea, it may still be unsuitable for hoisting operations. Therefore, after obtaining the predicted operation period, this application also needs to perform the following:

[0108] Predicted rainfall for the operational forecast period is obtained through meteorological forecasting models;

[0109] When the predicted rainfall is greater than a preset rainfall threshold, the predicted time period for the operation is removed; when the predicted rainfall is less than or equal to the preset rainfall threshold, the predicted time period for the operation is retained.

[0110] This invention discloses a method for predicting the time of offshore hoisting operations. Based on meteorological forecast data output from a weather forecast model, it calculates the motion state of a floating offshore hoisting platform and the stability state of the tunnel boring machine (TBM) components hoisted on the hoisting boom under the given meteorological forecast data. If, at one or more future time points, the amplitude and frequency of the floating offshore hoisting platform's undulating motion and its horizontal stability are normal, and the TBM components hoisted on the hoisting boom remain stable without being affected by sea winds, then these future time points are taken as target time points. The target time points constitute the predicted time period during which operations can proceed normally. This application, based on meteorological forecast data, can effectively predict the safe operating time, ensuring that the TBM can be accurately and smoothly hoisted into place.

[0111] like Figure 4 As shown, this application also provides a marine lifting operation time prediction system, including:

[0112] The acquisition module is used to acquire meteorological forecast data of sea level, wherein the meteorological forecast data includes wind speed, wind direction, wave height, wave period, ocean current speed and ocean current direction at multiple future time points;

[0113] The calculation module is used to calculate the motion state of the floating sea surface hoisting platform and the stability state of the shield machine parts hoisted on the hoisting boom at multiple future time points based on the meteorological forecast data. The motion state of the floating sea surface hoisting platform includes the maximum amplitude of the undulation motion, the frequency of the undulation motion, and the horizontal stability state of the sea surface hoisting platform.

[0114] The filtering module is used to select future time points that simultaneously meet target conditions as target time points. The target conditions include: the maximum amplitude of the undulation motion of the sea surface hoisting platform is less than a preset amplitude threshold, the motion frequency of the sea surface hoisting platform is less than a preset frequency threshold, the sea surface hoisting platform is in a stable state in the horizontal direction, and the shield machine parts are in a stable state.

[0115] The prediction module is used to construct a predicted time period for the operation based on the target time point.

[0116] This invention discloses a marine lifting operation time prediction system. Based on meteorological forecast data output from a meteorological forecast model, it calculates the motion state of a floating marine lifting platform and the stability state of the tunnel boring machine (TBM) components hoisted on the lifting boom under the given meteorological forecast data. If, at one or more future time points, the amplitude and frequency of the floating marine lifting platform's undulating motion and its horizontal stability are normal, and the TBM components hoisted on the lifting boom remain stable without being affected by sea winds, then these future time points are taken as target time points. These target time points constitute the predicted operation period during which operations can proceed normally. Based on meteorological forecast data, this application can effectively predict the safe operating time, ensuring that the TBM can be accurately and smoothly hoisted into place.

[0117] Figure 5 A schematic diagram of a computer system suitable for implementing embodiments of the present invention is shown. It should be noted that... Figure 5 The computer system of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0118] like Figure 5 As shown, the computer system includes a CPU 501 (Central Processing Unit), which can perform various appropriate actions and processes based on programs stored in ROM 502 (Read-Only Memory) or programs loaded from storage portion 508 into RAM 503 (Random Access Memory), such as executing the methods in the above embodiments. RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via bus 504. I / O interface 505 is also connected to bus 504.

[0119] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0120] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by CPU 501, it performs various functions defined in the system of the present invention.

[0121] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0123] The units described in the embodiments of the present invention can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0124] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer's processor, causes the computer to perform the method as described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0125] Another aspect of the present invention provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various embodiments described above.

[0126] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

Claims

1. A method of predicting a sea hoisting operation time, characterized by, The method comprises the steps of: obtaining weather forecast data of a sea surface, wherein the weather forecast data comprises wind speed, wind direction, wave height, wave period, current speed and current direction at multiple future time points; calculating motion states of a floating sea surface hoisting platform and stability states of shield machine parts hoisted on a hoisting branch arm at the multiple future time points based on the weather forecast data, wherein the motion states of the floating sea surface hoisting platform comprise maximum amplitude of heave motion, heave motion frequency and horizontal stability state of the sea surface hoisting platform; taking a future time point that meets target conditions as a target time point, wherein the target conditions comprise that the maximum amplitude of heave motion of the sea surface hoisting platform is less than a preset amplitude threshold, the motion frequency of the sea surface hoisting platform is less than a preset frequency threshold, the sea surface hoisting platform meets the stability state in the horizontal direction, and the shield machine parts meet the stability state; constructing a work prediction time period based on the target time point.

2. The offshore hoisting operation time prediction method according to claim 1, characterized in that, calculating the maximum amplitude of heave motion of the floating sea surface hoisting platform at the multiple future time points based on the weather forecast data comprises: inputting the wave height and the wave period into a prediction model constructed in advance to obtain the maximum amplitude of heave motion of the floating sea surface hoisting platform at the multiple future time points, wherein the prediction model represents a corresponding relationship between wave parameters and the maximum amplitude of heave motion of the floating sea surface hoisting platform, and the wave parameters comprise the wave height and the wave period.

3. A method of predicting the time of a marine lifting operation according to claim 2, characterized in that, The method for constructing the prediction model comprises: obtaining historical wave height, historical wave period and historical maximum amplitude of motion of the floating sea surface hoisting platform at multiple historical time points; constructing a binary regression equation, wherein the mathematical expression of the binary regression equation is: Y max = β1 x H + β2 x T + α where Y max represents the maximum amplitude of historical motion, H is the historical wave height, T is the historical wave period, β1 is the wave height coefficient, β2 is the period coefficient, and α is the error term. fitting the historical wave height, the historical wave period and the historical maximum amplitude of motion of the floating sea surface hoisting platform at the multiple historical time points based on the least square method to obtain the prediction model.

4. The offshore hoisting operation time prediction method of claim 1, wherein The heave motion frequency of the sea surface hoisting platform is a wave frequency ω, ω = T / 2π, wherein T is a wave period.

5. The offshore hoisting operation time prediction method of claim 1, wherein, calculating the horizontal stability state of the sea surface hoisting platform at the multiple future time points based on the weather forecast data comprises: determining a reduced up-current area S1 and a windward area S2 of the floating offshore lifting platform based on the current direction and the wind direction, wherein S i is an area of the i-th up-current surface, θ i is an angle between the i-th up-current surface and the current, n is a number of the up-current surfaces, S j is an area of the j-th windward surface, θ j is an angle between the j-th windward surface and the wind direction, and m is a number of the windward surfaces. calculating a first horizontal force F1 applied to the floating sea surface hoisting platform by a current and a second horizontal force F2 applied to the floating sea surface hoisting platform by a sea wind, and the mathematical expressions of the first horizontal force F1 and the second horizontal force F2 are: wherein ρ1 is the density of seawater, C d is the drag coefficient of seawater, v1 is the flow velocity of seawater, ρ2 is the density of air, C w is the drag coefficient of air, and v2 is the wind speed. calculating a resultant force based on the first horizontal force F1, the second horizontal force F2 and an included angle between the first horizontal force F1 and the second horizontal force F2 to obtain a total horizontal force F; acquiring the maximum resisting force F of the floating offshore lifting platform a wherein the maximum resisting force F a is provided by a driving device installed on the side of the floating offshore lifting platform a future time point satisfying F > F a is marked as unstable, and a horizontal steady state of a future time point satisfying F ≤ F a is marked as stable, where γ is a stability coefficient less than 1.

6. The offshore hoisting operation time prediction method of claim 1, wherein calculating the stability state of the shield machine parts at the multiple future time points based on the weather forecast data comprises: mapping the wind speed and the wind direction at the multiple future time points to a one-dimensional coordinate system; constructing a sliding window with a width of a construction required time, and performing sliding with a preset step length based on the sliding window, and calculating, at each time of sliding, a wind speed average value, a wind speed variance and a wind direction variance of all future time points in the sliding window; When the average value of the wind speed in the target sliding window is less than a preset wind speed threshold, a wind speed variance is less than a preset first variance threshold, and a wind direction variance is less than a preset second variance threshold, the stable state of the TBM part at a future time point corresponding to the target sliding window is marked as a stable state.

7. The offshore hoisting operation time prediction method of claim 1, wherein, The target time point is used to construct a work prediction time period, including: When a plurality of target time points are continuous, and the continuous plurality of target time points are greater than or equal to a minimum work duration, the continuous plurality of target time points are used as a work prediction time period.

8. The offshore hoisting operation time prediction method of claim 1, wherein, The weather prediction data is for a plurality of future time points in a preset time period after a current time point, and the weather prediction data is generated based on a weather prediction model.

9. The offshore hoisting operation time prediction method of claim 7, wherein, Further comprising: Obtaining a predicted rainfall in the work prediction time period; When the predicted rainfall is greater than a preset rainfall threshold, the work prediction time period is removed; When the predicted rainfall is less than or equal to the preset rainfall threshold, the work prediction time period is retained.

10. A marine lifting operation time prediction system, characterized by, Including: An obtaining module is configured to obtain weather prediction data of a sea surface, wherein the weather prediction data includes wind speed, wind direction, wave height, sea wave period, sea current speed, and sea current direction of a plurality of future time points; A calculating module is configured to calculate, based on the weather prediction data, a motion state of a floating sea surface hoisting platform and a stable state of a TBM part hoisted on a hoisting branch arm at the plurality of future time points, wherein the motion state of the floating sea surface hoisting platform includes a maximum amplitude of heave motion, a heave motion frequency, and a horizontal stable state of the sea surface hoisting platform; A screening module is configured to use a future time point that meets a target condition as a target time point, wherein the target condition includes that a maximum amplitude of heave motion of the sea surface hoisting platform is less than a preset amplitude threshold, a motion frequency of the sea surface hoisting platform is less than a preset frequency threshold, the sea surface hoisting platform meets a stable state in a horizontal direction, and a TBM part meets a stable state; A prediction module is configured to use the target time point to construct a work prediction time period.

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