Offshore wind power parameter interpretation system

Abstract

The present disclosure relates to the technical field of offshore wind power, and provides an offshore wind power parameter interpretation system. The system comprises: a seabed geotechnical stratification module, which is used for determining a soil behavior classification index of each soil layer according to in-situ test data of a plurality of fixed-thickness soil layers in a sea area to be analyzed, and determining a soil type corresponding to each soil layer based on a variation of the soil behavior classification index of adjacent soil layers; a pile foundation bearing layer matching degree marking module, which is used for determining a pile foundation bearing layer matching degree grade of each fixed-thickness soil layer according to a measured geological parameter of each fixed-thickness soil layer and a standard geological parameter of a pile foundation bearing layer; and a shear strength index calculation module, which is used for determining a target shear strength index calculation method for each fixed-thickness soil layer according to the soil type corresponding to the soil layer, and determining a shear strength index value of the soil layer based on the target shear strength index calculation method. The present scheme can improve the interpretation efficiency of offshore wind power parameters.

Description

Technical Field

[0001] This disclosure relates to the field of offshore wind power technology, and more specifically, to an offshore wind power parameter interpretation system. Background Technology

[0002] Offshore wind power projects involve numerous parameters. By interpreting the collected marine geological parameters or offshore wind power parameters obtained from indoor experiments, offshore wind power projects can be evaluated or designed to better implement or maintain them.

[0003] However, there is currently a lack of technology to automatically interpret offshore wind power parameters according to project requirements, resulting in low efficiency in parameter interpretation for offshore wind power projects.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this disclosure is to provide an offshore wind power parameter interpretation system, thereby improving the efficiency of offshore wind power parameter interpretation to at least a certain extent.

[0006] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part from practice of this disclosure.

[0007] According to embodiments of this disclosure, an offshore wind power parameter interpretation system is provided, comprising: a seabed geological soil stratification module, used to determine the soil behavior classification index of each soil layer based on in-situ test data of multiple soil layers of fixed thickness in the sea area to be analyzed, and to determine the soil type corresponding to each soil layer based on a first change in the soil behavior classification index of adjacent soil layers and a second change in a first geological parameter of adjacent soil layers, so as to obtain the soil stratification result of the sea area to be analyzed; and a pile foundation bearing layer matching degree marking module, used to determine the soil type of each soil layer based on the measured geological parameters of each fixed thickness soil layer and the standard geological parameters of the pile foundation bearing layer. The system calculates the matching degree of the pile foundation bearing layer and displays the matching degree of the pile foundation bearing layer for each soil layer in the visualized soil stratification results. The matching degree of the pile foundation bearing layer is used to indicate the suitability of the soil layer of a fixed thickness as the bearing layer of the pile foundation. The shear strength index calculation module is used to determine the target shear strength index calculation method from multiple candidate shear strength index calculation methods for each soil layer of a fixed thickness, based on the soil type corresponding to the soil layer and the parameter type of the input geological parameters of the soil layer, and to determine the shear strength index value of the soil layer based on the target shear strength index calculation method.

[0008] As can be seen from the above technical solution, the wind power parameter interpretation system in the exemplary embodiment of this disclosure has at least the following advantages and positive effects:

[0009] In the technical solutions provided by some embodiments of this disclosure, on the one hand, by processing in-situ test data of multiple soil layers of fixed thickness, soil stratification results can be automatically output, improving the efficiency of soil stratification; on the other hand, by quantifying and visually displaying the matching degree of the pile foundation bearing layer for each soil layer, relevant personnel can intuitively determine whether each soil layer can be used as a bearing layer, avoiding the risk of misjudgment due to experience, and improving the efficiency and accuracy of pile foundation bearing layer judgment; furthermore, by adapting the shear strength index calculation method to soil type and parameter type, the accuracy of shear strength index value calculation can be improved.

[0010] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0011] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0012] Figure 1 A schematic diagram of the structure of an offshore wind power parameter interpretation system according to an exemplary embodiment of the present disclosure is shown.

[0013] Figure 2 A flowchart illustrating a method for determining soil type according to an exemplary embodiment of this disclosure is shown.

[0014] Figure 3 A graph showing a soil behavior classification index versus formation depth in an exemplary embodiment of this disclosure is shown.

[0015] Figure 4 A schematic diagram of the structure of an electronic device in an exemplary embodiment of this disclosure is shown. Detailed Implementation

[0016] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0017] The terms “a,” “an,” “the,” and “the” are used in this specification to indicate the presence of one or more elements / components / etc.; the terms “including” and “having” are used to indicate an open-ended inclusion and to mean that there may be other elements / components / etc. in addition to the listed elements / components / etc.; the terms “first” and “second” are used only as markings and are not a limitation on the number of objects.

[0018] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0019] Offshore wind power parameter interpretation can be understood as the process of transforming raw data related to offshore wind power development (such as geological and geotechnical data obtained through in-situ testing) into structured information that can directly support engineering design, construction, and operation and maintenance decisions. The core is to "translate" scattered and complex raw parameter data into representative engineering conclusion data. Interpreting offshore wind power parameters can solve the problem of "abundant raw data but limited usable information" in offshore wind power development.

[0020] In related technologies, there is a lack of a system for automatically interpreting offshore wind power parameters, resulting in low interpretation efficiency and affecting the implementation progress of offshore wind power projects.

[0021] To address the aforementioned issues, this disclosure provides an offshore wind power parameter interpretation system, with reference to... Figure 1The system may include: a seabed geological soil stratification module 110, used to determine the soil behavior classification index of each soil layer based on in-situ test data of multiple soil layers of fixed thickness in the sea area to be analyzed, and to determine the soil type corresponding to each soil layer based on the first change in the soil behavior classification index of adjacent soil layers and the second change in the first geological parameter of adjacent soil layers, so as to obtain the soil stratification result of the sea area to be analyzed; and a pile foundation bearing layer matching degree marking module 120, used to determine the pile foundation bearing layer matching degree of each soil layer based on the measured geological parameters of each fixed thickness soil layer and the standard geological parameters of the pile foundation bearing layer. The system classifies and displays the matching degree of each soil layer to the pile foundation bearing layer in the visualized soil stratification results. The matching degree of the pile foundation bearing layer is used to indicate the suitability of the soil layer of a fixed thickness as the pile foundation bearing layer. The shear strength index calculation module 130 is used to determine the target shear strength index calculation method from multiple candidate shear strength index calculation methods for each soil layer of a fixed thickness, based on the soil type corresponding to the soil layer and the parameter type of the input geological parameters of the soil layer, and to determine the shear strength index value of the soil layer based on the target shear strength index calculation method.

[0022] exist Figure 1 In the technical solution provided by the illustrated embodiment, on the one hand, by processing the in-situ test data of multiple soil layers of fixed thickness, the soil stratification results can be automatically output, improving the efficiency of soil stratification; on the other hand, by quantifying and visually displaying the matching degree of the pile foundation bearing layer for each soil layer, relevant personnel can intuitively determine whether each soil layer can be used as a bearing layer, avoiding the risk of misjudgment due to experience, and improving the efficiency and accuracy of pile foundation bearing layer judgment; furthermore, by adapting the shear strength index calculation method to soil type and parameter type, the calculation accuracy of shear strength index value can be improved.

[0023] Next, a detailed description will be given of the specific implementation method of "the seabed geological soil and rock stratification module 110, which is used to determine the soil behavior classification index of each soil layer based on the in-situ test data of multiple soil layers of fixed thickness in the sea area to be analyzed, and to determine the soil type corresponding to each soil layer based on the first change of the soil behavior classification index of the adjacent soil layers and the second change of the first geological parameter of the adjacent soil layers, so as to obtain the soil stratification result of the sea area to be analyzed".

[0024] In one exemplary embodiment, multiple fixed thicknesses increase arithmetically. For example, the seabed geology and soil of the sea area to be analyzed can be divided into layers at preset thicknesses, such as 0.02 meters per layer, thereby obtaining multiple soil layers of fixed thickness, such as the first soil layer being 0.02 meters thick, the second soil layer being 0.04 meters thick, the third soil layer being 0.06 meters thick, and so on.

[0025] For example, in-situ static cone penetration tests can be conducted at preset thicknesses on the seabed geology and soil of the sea area to be analyzed, thereby obtaining in-situ static cone penetration test data of seabed pore pressure corresponding to multiple soil layers of fixed thickness in the sea area to be analyzed.

[0026] For example, in-situ test data may include one or more of cone tip resistance, side friction resistance, and pore water pressure.

[0027] For example, based on the Robertson Soil Behavior Classification System, the soil behavior classification index for each soil layer can be calculated using tip resistance, side friction, and pore water pressure. For instance, users can upload files corresponding to tip resistance, side friction, and pore water pressure for each soil layer to the offshore wind power parameter interpretation system's interface. They can then input correction coefficients, such as the tip resistance normalization correction coefficient, the kPa value corresponding to standard atmospheric pressure (atmKpa), and regional empirical correction coefficients. After inputting these coefficients and clicking the confirmation button, the system can automatically calculate the soil behavior classification index for each soil layer using the built-in algorithm based on the Robertson Soil Behavior Classification System with SBT (Soil Behavior Type) parameters.

[0028] After obtaining the soil behavior classification index, the soil type of each soil layer can be determined based on the soil behavior classification index.

[0029] For example, if the first change between the current soil layer and the previous soil layer is less than or equal to a first threshold and the second change is less than or equal to a second threshold, the soil type of the current soil layer is determined based on the cumulative value of the first change and the cumulative value of the second change corresponding to a preset number of consecutive soil layers adjacent to the current soil layer; if the first change between the current soil layer and the previous soil layer is greater than the first threshold or the second change is greater than the second threshold, the soil type of the current soil layer is determined based on the soil behavior classification index and the first geological parameter of the current soil layer.

[0030] For example, if the first change between the current soil layer and the previous soil layer is less than or equal to a first threshold and the second change is less than or equal to a second threshold, it can be determined whether the cumulative value of the first change among a predetermined number of consecutive soil layers adjacent to the current soil layer is greater than a third threshold and whether the cumulative value of the second change is greater than a fourth threshold. If the cumulative value of the first change among a predetermined number of consecutive soil layers adjacent to the current soil layer is greater than the third threshold or the cumulative value of the second change is greater than the fourth threshold, the soil type of the current soil layer is determined based on the soil behavior classification index and the first geological parameter. If the cumulative value of the first change among a predetermined number of consecutive soil layers adjacent to the current soil layer is less than or equal to the third threshold and the cumulative value of the second change is less than or equal to the fourth threshold, the soil type of the previous soil layer is determined as the soil type of the current soil layer.

[0031] For example, Figure 2 A flowchart illustrating a method for determining soil type according to an exemplary embodiment of this disclosure is shown. (Reference) Figure 2 The method may include steps S210 to S270. Wherein:

[0032] In step S210, the soil type of the first soil layer is determined based on the soil behavior classification index and the first geological parameters of the first soil layer.

[0033] In one exemplary embodiment, the first geological parameter includes one or more of soil physical property parameters, soil mechanical property parameters, and in-situ soil testing parameters. That is, the first geological parameter may include geological parameters that can be used for soil type classification.

[0034] Among them, soil physical property parameters can include soil particle size distribution, natural water content, density, etc. Soil mechanical property parameters can be obtained through mechanical experiments, which can include data such as soil internal friction angle and compression modulus. Soil in-situ test parameters can include the aforementioned cone tip resistance, side friction resistance, etc.

[0035] For example, a soil classification model can be trained using historical data of the first geological parameter. The specific data of the first geological parameter of the first soil layer are then input into the trained soil type model. Based on the output of the soil classification model, the first candidate soil type for the first soil layer is obtained. Through the mapping relationship between the soil behavior classification index and the soil type, the second candidate soil type for the first soil layer is obtained based on the soil behavior classification index. For instance, if the mapping relationship indicates that the soil is type A when the soil behavior classification index is less than 0.2, and the soil behavior classification index of the first soil layer is 0.18, then the second candidate soil type for the first soil layer is type A.

[0036] For example, the offshore wind power parameter interpretation system in this disclosure further includes: an empirical parameter library construction module, used to generate an empirical mapping relationship between soil behavior classification index and soil type corresponding to different sea area types based on historical offshore wind power parameter data of different sea area types.

[0037] Based on this, for example, the offshore wind power parameter interpretation system in this disclosure further includes: an empirical parameter library query module, used to query the empirical mapping relationship between the soil behavior classification index and soil type corresponding to the input sea area type in the empirical parameter library, so as to determine the soil type corresponding to each fixed thickness of soil layer according to the empirical mapping relationship and the first geological parameter.

[0038] For example, the mapping relationship between soil behavior classification indices and soil types may differ in different sea areas. By constructing a mapping relationship between soil behavior classification indices and soil types for different sea area types, a more suitable and accurate mapping relationship can be selected based on the sea area type to be analyzed, thereby improving the accuracy of soil type determination.

[0039] For example, a database can be established based on marine area divisions. Based on historical survey data of different marine areas, an empirical mapping relationship between soil behavior classification indices and soil types can be established for different marine areas. When interpreting parameters, users can provide the target marine area identifier for the marine area to be analyzed, and then query the empirical mapping relationship corresponding to the target marine area identifier in the empirical database. The empirical mapping relationship found can replace the general mapping relationship, thereby improving the accuracy of soil classification.

[0040] For example, users can also upload new survey data, and the empirical mapping relationships in the empirical parameter library can be updated based on the new survey data uploaded by the user.

[0041] For example, if the first candidate soil type and the second candidate soil type are the same, then either the first candidate soil type or the second candidate soil type is directly determined as the soil type of the first soil layer; if the first candidate soil type and the second candidate soil type are different, then the soil type of the first soil layer is determined as pending. Simultaneously, after the soil types of all soil layers are determined, a prompt message for all soil layers with pending soil types is returned to the user's logged-in terminal, such as "Unable to determine the soil type of the 0.48m and 0.56m soil layers, please verify if the data is correct." This prompts the user to check if the input data is correct. If it is, the data is reclassified after the user corrects it. If the user confirms that the input data is correct, the expert experience database is invoked. The first soil behavior classification index and the first geological parameter are concatenated as a single data point, and a similarity calculation is performed with the data in the expert experience database. The soil type corresponding to the data with the highest similarity in the expert experience database is determined as the soil type of the first soil layer.

[0042] In step S220, the next soil layer is traversed.

[0043] For example, after determining the soil type of the first soil layer, you can continue to traverse the next soil layer.

[0044] In step S230, it is determined whether the first change between the current soil layer and the previous soil layer is greater than the first threshold or whether the second change is greater than the second threshold. If yes, proceed to step S240; otherwise, proceed to step S250.

[0045] For example, for the currently traversed soil layer, a first change can be calculated between the soil behavior classification index of the currently traversed soil layer and the soil behavior classification index of the previous soil layer, and a second change can be calculated between the first geological parameter of the currently traversed soil layer and the first geological parameter of the previous soil layer.

[0046] In step S240, the soil type of the current soil layer is determined based on the soil behavior classification index and the first geological parameter.

[0047] For example, if the first change is greater than the first threshold or the second change of any first geological parameter is greater than its corresponding second threshold, it indicates that there is a significant difference in the soil properties between the current soil layer and the previous soil layer, and the soil type of the current soil layer needs to be re-determined.

[0048] For example, the specific implementation of step S240 can be referred to the specific implementation of step S210 described above, and will not be repeated here.

[0049] In step S250, it is determined whether the cumulative value of the first change between the current layer and a number of adjacent consecutive soil layers is greater than the third threshold or whether the cumulative value of the second change is greater than the fourth threshold. If so, proceed to step S260; otherwise, proceed to step S270.

[0050] In step S260, the soil type of the current soil layer is determined based on the soil behavior classification index and the first geological parameter.

[0051] For example, the specific implementation of step S260 can be referred to the specific implementation of step S210 described above, and will not be repeated here.

[0052] In step S270, the soil type of the previous soil layer is determined as the soil type of the current soil layer.

[0053] For example, if the first change is less than or equal to the first threshold and the second change of each first geological parameter is less than its corresponding second threshold, it indicates that the soil properties of adjacent soil layers are consistent. However, considering that the change of two adjacent layers may be less than the corresponding threshold (e.g., if the current layer is layer 10, the changes of layers 10 and 9 may be less than the corresponding threshold, but the sum of the changes of layers 10 and 9 and the changes of layers 9 and 8 may exceed the corresponding threshold, i.e., there is a cumulative effect of error, leading to inaccurate classification results), if the change of the current layer and the layer before it is less than the corresponding threshold, it can continue to be compared with the current layer. To determine if the cumulative change between multiple consecutive adjacent soil layers is less than the corresponding threshold, for example, if the preset quantity is 2 and the current layer is the 10th layer, the absolute values ​​of the changes between the 8th and 9th layers, and the absolute values ​​of the changes between the 9th and 10th layers can be calculated. Then, these two values ​​can be added together to obtain the cumulative value of the change. If the cumulative value of the change is still less than the corresponding threshold, it indicates that the soil properties have not changed significantly. In this case, the soil type of the previous layer can be used as the soil type of the current layer. Otherwise, the soil type of the current layer is re-determined based on the data of the current layer, and then the process continues to traverse the next soil layer until all soil layers have been traversed.

[0054] In one exemplary embodiment, if the soil type of the preceding soil layer is undetermined, the soil type of the current soil layer can be directly determined based on the soil behavior classification index and the first geological parameter. In other words, if the soil type of the preceding soil layer is not undetermined, steps S230 to S270 described above are performed.

[0055] Through steps S210 to S270, for soil layers with insignificant changes in soil properties, the soil type of the current soil layer can be directly determined based on the soil type of the preceding soil layer, improving the efficiency of soil type identification. Simultaneously, by judging the changes in multiple adjacent soil layers, cumulative error verification can be performed, improving the accuracy of soil type identification. Furthermore, the mutual verification between the soil behavior classification index and the soil type model using the first geological parameter as input data improves the reliability of soil type identification.

[0056] For example, the seabed geological soil and rock stratification module 110 is also used to divide each soil layer of fixed thickness into multiple sub-soil layers. If the first change amount corresponding to the current sub-soil layer and the previous sub-soil layer is greater than a fifth threshold or the second change amount is greater than a sixth threshold, the soil type of the current sub-soil layer is re-determined according to the soil behavior classification index and the first geological parameter of the current sub-soil layer, and the current sub-soil layer is identified as the target sub-soil layer to be marked, so as to provide a second prompt display for the target sub-soil layer in the visualized soil stratification results.

[0057] For example, the thickness of each sub-soil layer is less than the fixed thickness of each soil layer. For instance, a 20-centimeter-thick soil layer can be further divided into four equal parts, resulting in four 5-centimeter-thick sub-soil layers. Then, for adjacent sub-soil layers, if there is a significant difference between the first change in the soil behavior classification index and the second change in the first geological parameter, it indicates that a thin interlayer with a soil type inconsistent with the current soil layer may exist within that fixed-thickness soil layer. This provides a secondary indication of the thin interlayer. The identification and labeling of thin interlayers can assist relevant personnel in making more accurate decisions regarding offshore wind power construction.

[0058] In one exemplary implementation, after calculating the soil behavior classification index for each soil layer, the index can be visualized in the form of a chart, or a curve showing the relationship between the soil behavior classification index and the soil layer thickness can be plotted, such as... Figure 3 As shown, in Figure 3 In the middle, the orange lines are layering reference lines.

[0059] Next, a detailed description will be given of the specific implementation of the "pile foundation bearing layer matching degree marking module 120, which is used to determine the pile foundation bearing layer matching degree level of each soil layer based on the measured geological parameters of each soil layer of fixed thickness and the standard geological parameters of the pile foundation bearing layer, and to display the first prompt of the pile foundation bearing layer matching degree level of each soil layer in the visualized soil stratification results".

[0060] For example, determining the pile bearing layer matching degree level for each soil layer based on the measured geological parameters of each fixed-thickness soil layer and the standard geological parameters of the pile bearing layer includes: for each fixed-thickness soil layer, calculating the ratio between the measured geological parameters of the soil layer and the standard geological parameters of the pile bearing layer; if the ratio is greater than a seventh threshold, determining the pile bearing layer matching degree level of the soil layer as a first level; if the ratio is less than or equal to the seventh threshold and greater than an eighth threshold, determining the pile bearing layer matching degree level of the soil layer as a second level; and if the ratio is less than or equal to the eighth threshold, determining the pile bearing layer matching degree level of the soil layer as a third level.

[0061] For example, the bearing layer refers to the soil layer that directly bears the load of the superstructure (such as the weight of the wind turbine and tower) transmitted from the offshore wind power pile foundation. It is the core soil layer that determines the bearing capacity and stability of the pile foundation.

[0062] For example, standard geological parameters of the bearing stratum for offshore wind turbine pile foundations can be determined according to existing technical specifications. For instance, a certain specification might define the standard geological parameters as follows: for sandy soil, the corrected cone tip resistance is greater than A1 and the relative density is greater than B1; for cohesive soil, the undrained shear strength is greater than C1 and the compression modulus is greater than D1. Then, for a soil layer of cohesive soil type, the ratio of the measured corrected cone tip resistance A2 to the standard value A1 (1), and the ratio of the measured relative density B2 to the standard value B1 (2), can be calculated. The minimum value between ratio 1 and ratio 2 is taken. If the minimum value is greater than 0.9, it is determined to be of the first grade; if the minimum value is less than or equal to 0.9 but greater than 0.6, it is determined to be of the second grade; and if the minimum value is less than or equal to 0.6, it is determined to be of the third grade. That is, the first grade has the highest matching degree, the second grade has the second highest matching degree, and the third grade has the lowest matching degree.

[0063] In one exemplary embodiment, the pile bearing stratum matching degree grade is used to indicate the suitability of the soil layer of fixed thickness as a pile bearing stratum. That is, the first grade soil layer is suitable as a pile bearing stratum, the second grade may need to be verified to confirm its suitability as a pile bearing stratum, and the third grade is not suitable as a pile bearing stratum.

[0064] For example, the way the first prompt is displayed can be customized according to the needs, such as directly marking the pile bearing layer matching degree level of each soil layer, or marking the first level as a green dot, the second level as a yellow dot, and the third level as a red dot, etc.

[0065] It should be noted that all thresholds in this disclosure can be customized according to needs or experience, and this exemplary implementation does not impose any special limitations on them.

[0066] Next, a detailed description will be given of the specific implementation of the "shear strength index calculation module 130, which is used to determine the target shear strength index calculation method from multiple candidate shear strength index calculation methods for each soil layer of fixed thickness, based on the soil type corresponding to the soil layer and the parameter type of the input geological parameters of the soil layer, and to determine the shear strength index value of the soil layer based on the target shear strength index calculation method".

[0067] In one exemplary implementation, the parameter type for input geological parameters may include in-situ test data types and laboratory experiment data types.

[0068] For example, a pre-established association between different soil types and their corresponding candidate shear strength index calculation methods can be created, while binding the parameter types of the geological parameters upon which each candidate shear strength index calculation method depends. For each soil layer, candidate shear strength index calculation methods can first be determined from the association based on the soil type. Then, the parameter types of the currently input geological parameters are queried, and the queried parameter types are matched with the parameter types bound to the candidate shear strength index calculation methods. The successfully matched candidate shear strength index calculation methods are then determined as the target shear strength index calculation methods.

[0069] For example, there may be multiple methods for calculating shear strength indices. Each method may be applicable to different types of soil and subject to different constraints, such as requiring different geological parameter data for calculation. For instance, the internal friction angle of soil type 1 can be calculated using methods E and F. Method E only requires in-situ test data, while method F requires both in-situ test data and laboratory experimental data. If the currently input geological parameters lack laboratory experimental data, then method E will be used as the target shear strength index calculation method for soil type 1.

[0070] For example, the offshore wind power parameter interpretation system in this disclosure further includes: a shear wave velocity calculation module, used to calculate the shear modulus corresponding to the soil layer based on the modified cone tip resistance, natural soil self-weight stress, and soil behavior classification index corresponding to each soil layer of fixed thickness, and to calculate the shear wave velocity corresponding to the soil layer based on the shear modulus.

[0071] For example, there is an empirical relationship between shear modulus and shear wave velocity. Similarly, there is an empirical relationship between the modified cone tip resistance, natural soil self-weight stress, and soil behavior classification index and the shear modulus. Therefore, the shear modulus can be calculated first using the modified cone tip resistance, natural soil self-weight stress, and soil behavior classification index, and then the shear wave velocity can be determined using the empirical relationship between the shear modulus and shear wave velocity. In this way, the shear wave velocity can be estimated using in-situ test data, eliminating the need for laboratory experiments and improving the efficiency of shear wave velocity estimation. Furthermore, pore water pressure static cone penetration testing is a continuous penetration test that can obtain continuous parameters such as the modified cone tip resistance, thereby allowing for the calculation of a continuous shear wave velocity distribution. This provides a more detailed description of the mechanical properties of the soil, thus helping to improve the accuracy of construction assessments for offshore wind power projects.

[0072] For example, the offshore wind power parameter interpretation system in this disclosure further includes: a data denoising module, used to denoise the input in-situ test data and visually display the change curve of the input in-situ test data and the change curve of the denoised in-situ test data.

[0073] For example, noise reduction can be applied to in-situ test data input by users to improve data validity and thus help improve the accuracy of interpretation results. By visually comparing the data change curves before and after noise reduction, the noise reduction effect can be displayed more intuitively, making it easier for users to identify problems.

[0074] Furthermore, it should be noted that the above figures are merely illustrative representations of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0075] The specific details of each part of the above-mentioned device have been described in detail in the method section of the implementation plan. For any undisclosed details, please refer to the implementation plan of the method section, and therefore will not be repeated here.

[0076] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0077] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0078] Exemplary embodiments of this disclosure also provide a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the above-described... Figure 2 Methods for determining soil type.

[0079] In one implementation, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing a computer program, such as read-only memory, NAND flash memory, etc.

[0080] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0081] Computer program code can be written in one or more programming languages. Examples of programming languages ​​include C, Java, C++, and Python. Program code can execute entirely on the user's computing device, partially on the user's computing device, or as a standalone software package. It can also execute partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, such as a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via an internet connection provided by a mobile network operator).

[0082] Computer programs can be carried or transmitted via signals such as electricity, magnetism, light, electromagnetic radiation, and infrared radiation. Electronic devices can convert signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, to execute by the processor of the electronic device) the method steps of various exemplary embodiments of this disclosure, such as the method for determining soil type described above.

[0083] Exemplary embodiments of this disclosure also provide an electronic device, which may include a processor and a memory. The memory stores executable instructions of the processor, such as a computer program. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of this disclosure. Furthermore, the electronic device may also include a display for displaying a graphical user interface.

[0084] The following is for reference. Figure 4 The electronic device is illustrated by way of a general-purpose computing device. It should be understood that... Figure 4The electronic device 400 shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0085] like Figure 4 As shown, the electronic device 400 may include: a processor 410, a memory 420, a bus 430, an I / O (input / output) interface 440, a network adapter 450, and a display 460.

[0086] Memory 420 may include volatile memory, such as RAM 421 and cache unit 422, and may also include non-volatile memory, such as ROM 423. Memory 420 may also include one or more program modules 424, including but not limited to: operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, program module 424 may include the modules in the above-described apparatus.

[0087] The processor 410 may include one or more processing units, such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit).

[0088] The processor 410 can be used to execute executable instructions stored in the memory 420, such as the method described above for determining the soil type.

[0089] Bus 430 is used to connect different components of electronic device 400 and may include a data bus, an address bus and a control bus.

[0090] Electronic device 400 can communicate with one or more external devices 500 (such as keyboard, mouse, external controller, etc.) through I / O interface 440.

[0091] Electronic device 400 can communicate with one or more networks via network adapter 450. For example, network adapter 450 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. Network adapter 450 can communicate with other modules of electronic device 400 via bus 430.

[0092] The electronic device 400 can display a graphical user interface via a display 460, such as an interface that displays visualized soil stratification results.

[0093] although Figure 4 Other hardware and / or software modules, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, may also be configured in the electronic device 400.

[0094] Those skilled in the art will understand that various aspects of this disclosure can be implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be referred to as “circuit,” “module,” or “system,” respectively.

[0095] It should be understood that this disclosure is not limited to the specific methods, steps, or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily conceive of other embodiments based on the specific implementations provided in this disclosure. Therefore, the specific implementations provided in this disclosure are merely exemplary, and the scope and spirit of this disclosure are indicated by the claims, and should cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary technical means in the art not disclosed in this disclosure.

Claims

1. An offshore wind power parameter interpretation system, characterized by, The method comprises the following steps: a seabed geotechnical stratification module is used to determine a soil behavior classification index of each soil layer according to in-situ test data of a plurality of fixed-thickness soil layers in a sea area to be analyzed, and determine a soil type corresponding to each soil layer based on a first variation of the soil behavior classification index of an adjacent soil layer and a second variation of a first geological parameter of the adjacent soil layer, so as to obtain a soil stratification result of the sea area to be analyzed; a pile foundation bearing stratum matching degree marking module is used to determine a pile foundation bearing stratum matching degree grade of each soil layer according to a measured geological parameter of each fixed-thickness soil layer and a standard geological parameter of a pile foundation bearing stratum, and perform a first prompt display of the pile foundation bearing stratum matching degree grade of each soil layer in a visual soil stratification result, wherein the pile foundation bearing stratum matching degree grade is used to indicate an adaptation degree of the fixed-thickness soil layer as a pile foundation bearing stratum; a shear strength index calculation module is used to determine a target shear strength index calculation method from a plurality of candidate shear strength index calculation methods according to a parameter type of an input geological parameter of each fixed-thickness soil layer and a soil type corresponding to the soil layer, and determine a shear strength index value of the soil layer based on the target shear strength index calculation method.

2. The offshore wind power parameter interpretation system according to claim 1, characterized in that, The plurality of fixed thicknesses are in equal-difference increments, and the determination of the soil type corresponding to each soil layer based on the first variation of the soil behavior classification index of the adjacent soil layer and the second variation of the first geological parameter of the adjacent soil layer comprises: in a case where the first variation between the current soil layer and the previous soil layer is less than or equal to a first threshold value and the second variation is less than or equal to a second threshold value, determining the soil type of the current soil layer according to accumulated values of the first variation and the second variation between a preset number of continuous soil layers adjacent to the current soil layer; in a case where the first variation corresponding to the current soil layer and the previous soil layer is greater than the first threshold value or the second variation is greater than the second threshold value, determining the soil type of the current soil layer according to the soil behavior classification index and the first geological parameter of the current soil layer.

3. The offshore wind power parameter interpretation system according to claim 2, characterized in that, The determination of the soil type of the current soil layer according to the accumulated values of the first variation and the second variation between the preset number of continuous soil layers adjacent to the current soil layer comprises: in a case where the accumulated value of the first variation between the preset number of continuous soil layers adjacent to the current soil layer is greater than a third threshold value or the accumulated value of the second variation is greater than a fourth threshold value, determining the soil type of the current soil layer according to the soil behavior classification index and the first geological parameter of the current soil layer; in a case where the accumulated value of the first variation between the preset number of continuous soil layers adjacent to the current soil layer is less than or equal to the third threshold value and the accumulated value of the second variation is less than or equal to the fourth threshold value, determining the soil type of the previous soil layer of the current soil layer as the soil type of the current soil layer.

4. The offshore wind power parameter interpretation system according to claim 2, characterized in that, The seabed geotechnical stratification module is further configured to, for each soil layer of a fixed thickness, divide the soil layer into a plurality of sub-soil layers, and in a case where a first variation corresponding to a current sub-soil layer and a previous sub-soil layer of the current sub-soil layer is greater than a fifth threshold value or a second variation is greater than a sixth threshold value, re-determine a soil type of the current sub-soil layer according to a soil behavior classification index and a first geological parameter of the current sub-soil layer, and determine the current sub-soil layer as a target sub-soil layer to be marked, so as to perform a second prompt display on the target sub-soil layer to be marked in a visual soil stratification result.

5. The offshore wind power parameter interpretation system according to claim 1, characterized in that, The first geological parameter includes one or more of a soil physical property parameter, a soil mechanical property parameter, and a soil in-situ test parameter.

6. The offshore wind power parameter interpretation system according to claim 1, characterized in that, The determination of the pile bearing stratum matching degree level of each soil layer according to the measured geological parameter of each soil layer of a fixed thickness and the standard geological parameter of the pile bearing stratum includes: For each soil layer of a fixed thickness, a ratio between the measured geological parameter of the soil layer and the standard geological parameter of the pile bearing stratum is calculated; In a case where the ratio is greater than a seventh threshold value, the pile bearing stratum matching degree level of the soil layer is determined as a first level, in a case where the ratio is less than or equal to the seventh threshold value and greater than an eighth threshold value, the pile bearing stratum matching degree level of the soil layer is determined as a second level, and in a case where the ratio is less than or equal to the eighth threshold value, the pile bearing stratum matching degree level of the soil layer is determined as a third level.

7. The offshore wind power parameter interpretation system according to claim 1, characterized in that, The system further includes: A shear wave velocity calculation module configured to calculate a shear modulus corresponding to each soil layer of a fixed thickness according to a corrected cone tip resistance, a natural soil self-weight stress, and a soil behavior classification index corresponding to the soil layer, and calculate a shear wave velocity corresponding to the soil layer according to the shear modulus.

8. The offshore wind power parameter interpretation system according to claim 1, characterized in that, The system further includes: A data denoising module configured to perform denoising processing on input in-situ test data, and visually display a change curve of the input in-situ test data and a change curve of the denoised in-situ test data.

9. The offshore wind power parameter interpretation system according to claim 1, characterized in that, The system further includes: An empirical parameter library construction module configured to generate an empirical mapping relationship between a soil behavior classification index and a soil type corresponding to different sea area types according to historical offshore wind power parameter data of the different sea area types.

10. The offshore wind power parameter interpretation system according to claim 9, characterized in that, The system further includes: An empirical parameter library query module configured to query an empirical mapping relationship between a soil behavior classification index and a soil type corresponding to an input sea area type in an empirical parameter library, so as to determine a soil type corresponding to each soil layer of a fixed thickness according to the empirical mapping relationship and the first geological parameter.

Images