Monitoring data determination method, simulation device, simulation device testing method, electronic device, and storage medium

Abstract

The application provides a monitoring data determination method, a simulation device, a simulation device test method, an electronic device and a storage medium, relates to the field of data processing, is applied to a simulation device, the simulation device comprises a displacement device, a plurality of target anchor chains and sensors corresponding to the target anchor chains, the monitoring data determination method comprises: acquiring a displacement parameter of the displacement device; controlling the displacement device to displace in a preset space range at a preset speed, the preset space range being determined based on the displacement parameter; collecting a top end tension data set of the corresponding target anchor chain through the sensor, the top end tension data set comprising a top end tension of the target anchor chain in a plurality of different target states, the target state comprising at least one of a normal state, an anchor walking state and an anchor breaking state; and storing the top end tension data set, the top end tension data set being used for monitoring the target anchor chain in an actual environment.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method for determining monitoring data, a simulation device, a method for testing the simulation device, an electronic device, and a storage medium. Background Technology

[0002] Wind energy, as a green energy source, is largely found on the ocean surface. With the vigorous development of wind power generation, the focus is shifting from fixed wind turbines in near-shore and shallow waters to floating wind turbines in deep-sea areas. Wind power generation systems generally consist of wind turbine generators, blades, towers, foundations, and mooring systems. Online monitoring, as an effective means of ensuring the safe operation and reliability of wind turbines, is increasingly being applied throughout the entire lifecycle of wind turbine safety operation and maintenance. Floating wind turbine foundations and mooring systems, operating in the marine environment for extended periods, are subjected to environmental loads such as wind, waves, and currents, resulting in corrosion, wear, and other forms of damage. Mooring chains also experience issues like anchor dragging and breakage, severely impacting the normal operation of wind turbines. Currently, there are limited technologies for monitoring floating wind turbine foundations and mooring systems. Data is typically collected by sensors placed on the blades or towers, and then manually monitored, resulting in low monitoring efficiency and a high rate of misjudgments. Summary of the Invention

[0003] This application provides a method for determining monitoring data, a simulation device, a method for testing the simulation device, an electronic device, and a storage medium.

[0004] One embodiment of this application provides a monitoring data determination method applied to a simulation device, the simulation device including a displacement device, multiple target anchor chains, and sensors corresponding to the target anchor chains, the method comprising:

[0005] Obtain the displacement parameters of the displacement device;

[0006] The displacement device is controlled to move at a preset speed within a preset spatial range, the preset spatial range being determined based on the displacement parameters;

[0007] The sensor collects a dataset of tip tension of the target anchor chain. The dataset includes the tip tension of the target anchor chain under multiple different target states, including at least one of the following: normal state, anchor dragging state, and anchor breakage state.

[0008] The top tension dataset is stored and used to monitor the target anchor chain in a real-world environment.

[0009] The damage levels of the multiple target anchor chains vary, and the data collection of the tip tension of the target anchor chains includes:

[0010] The tip tension of each target anchor chain under multiple different target states is collected to obtain the tip tension dataset, which includes the tip tension of multiple target anchor chains with different degrees of damage under multiple different target states.

[0011] The method further includes:

[0012] Acquire the dimensional data and displacement parameters of the object to be measured, and the dimensional data of the simulation device;

[0013] The size factor is determined based on the size data of the object to be measured and the size data of the simulation device;

[0014] The displacement coefficients between the object under test and the simulation device are determined based on the size coefficients.

[0015] The displacement parameters of the simulation device are determined based on the displacement parameters of the object under test and the displacement coefficient.

[0016] After obtaining the displacement parameters of the displacement device, the method further includes:

[0017] Obtain the positioning data of the simulation device;

[0018] The preset spatial range is determined based on the displacement parameters and the positioning data.

[0019] The method further includes:

[0020] Obtain the load parameters of the object under test and the rated load of the simulation device;

[0021] The load parameters of the simulation device are determined based on the load parameters of the object to be tested, the rated load of the simulation device, and the size factor. The load parameters of the simulation device are used to set the load of the simulation device.

[0022] Another embodiment of this application provides a simulation device, which includes: a displacement device, a plurality of target anchor chains, and sensors corresponding to the target anchor chains;

[0023] The top end of the target anchor chain is connected to the displacement device;

[0024] The sensor is positioned at the top of the target anchor chain.

[0025] The displacement device further includes: an upper platform, a lower platform, and multiple electric cylinders;

[0026] The top end of the target anchor chain is connected to the upper platform;

[0027] The plurality of electric cylinders are connected to the upper platform and the lower platform.

[0028] Another aspect of this application provides a method for testing a simulation device, the method comprising:

[0029] The displacement device is controlled to move the target distance;

[0030] Obtain the actual distance of the displacement device;

[0031] The distance deviation is determined based on the target distance and the actual distance, and the distance deviation characterizes the performance of the displacement device.

[0032] Another aspect of this application provides an electronic device, comprising:

[0033] Processor; memory for storing processor-executable instructions;

[0034] The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the monitoring data determination method.

[0035] In another aspect, this application provides a computer-readable storage medium storing a computer program for executing the monitoring data determination method described above.

[0036] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0037] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. Several embodiments of this application are illustrated in the drawings by way of example and not limitation, in which:

[0038] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0039] Figure 1 A flowchart of a monitoring data determination method according to an embodiment of this application is shown;

[0040] Figure 2 A flowchart of a monitoring data determination method according to another embodiment of this application is shown;

[0041] Figure 3 A flowchart of a monitoring data determination method according to another embodiment of this application is shown;

[0042] Figure 4 A flowchart of a monitoring data determination method according to another embodiment of this application is shown;

[0043] Figure 5 A schematic diagram of the structure of a simulation device according to an embodiment of this application is shown;

[0044] Figure 6 A flowchart of a simulation device testing method according to an embodiment of this application is shown;

[0045] Figure 7 A schematic diagram of a simulated curve of a target anchor chain according to an embodiment of this application is shown;

[0046] Figure 8 A schematic diagram of the composition structure of an electronic device according to an embodiment of this application is shown. Detailed Implementation

[0047] To make the objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] To improve the monitoring efficiency of floating wind turbine mooring systems and reduce misjudgments, one embodiment of this application provides a monitoring data determination method applied to a simulation device. The simulation device includes a displacement device, multiple target anchor chains, and sensors corresponding to the target anchor chains. Figure 1 As shown, the method includes:

[0049] Step 101: Obtain the displacement parameters of the displacement device.

[0050] The simulation device includes a displacement device and multiple target anchor chains connected to the displacement device, as well as a sensor corresponding to each target anchor chain. The effect of ocean current velocity on the anchor chains is simulated by controlling the displacement of the displacement device, and the tension at the tip of the target anchor chains is then collected by the sensors.

[0051] The displacement parameters include at least the angular range of attitude angles such as pitch, roll, and yaw, as well as the distance range in the three axes of lateral, longitudinal, and vertical directions. For example, as shown in Table 1, the displacement parameters of a certain displacement device include: pitch angle... Roll angle is Yaw angle is Horizontal distance is Longitudinal distance is Vertical distance is .

[0052] Table 1

[0053]

[0054] The displacement parameters of the displacement device can be obtained directly by the user through the human-computer dialogue interface in the simulation device or the electronic device (such as a computer, tablet, etc.) connected to the simulation device, or they can be calculated based on the size data and displacement parameters of the object to be measured input by the user.

[0055] Step 102: Control the displacement device to move at a preset speed within a preset spatial range, wherein the preset spatial range is determined based on the displacement parameters.

[0056] The preset spatial range is the motion boundary of the displacement device determined by the displacement parameters.

[0057] The preset speed is set by the user through the human-computer interface, including the movement speed and acceleration of the displacement device. For example, as shown in Table 2, in a certain simulation test, the user set the preset speed of the displacement device through the human-computer interface, including: pitch angular velocity of... , roll angular velocity is yaw rate is Pitch angle acceleration is The roll angle acceleration is Yaw angular acceleration is Horizontal velocity is Longitudinal velocity is Vertical velocity is lateral acceleration is Longitudinal acceleration is Vertical acceleration is .

[0058] Table 2

[0059]

[0060] Sending commands to the displacement device drives it to move at a preset speed within a preset spatial range, so that the tension generated by the displacement device on the target anchor chain during its movement can simulate the effect of ocean current speed on the anchor chain.

[0061] Step 103: Collect the top tension dataset of the corresponding target anchor chain through the sensor. The top tension dataset includes the top tension of the target anchor chain in multiple different target states. The target states include at least one of the normal state, the anchor dragging state, and the anchor breakage state.

[0062] While the displacement device moves at a preset speed within a preset spatial range, sensors continuously collect tip tension data of the target anchor chains. Multiple target anchor chains are in different target states, including at least one of the following: normal state, anchor dragging state, and anchor breakage state. Tip tension data is collected for the target anchor chains in different target states to obtain a tip tension dataset.

[0063] For example, as shown in Table 3, the simulation device was set with six target anchor chains: target anchor chain A, target anchor chain B, target anchor chain C, target anchor chain D, target anchor chain E, and target anchor chain F. Target anchor chains A and B were in normal condition, target anchor chains C and D were in a dragging state, and target anchor chains E and F were in a broken state. At 50ms, when the control displacement device was moving at a preset speed within a preset spatial range, the top tension of target anchor chain A was measured to be 128N, the top tension of target anchor chain B was 125N, the top tension of target anchor chain C was 205N, the top tension of target anchor chain D was 215N, the top tension of target anchor chain E was 452N, and the top tension of target anchor chain F was 455N. At 100ms, when the displacement device is moving at a preset speed within a preset spatial range, the top tension of target anchor chain A is collected as follows: 132N; top tension of target anchor chain B: 130N; top tension of target anchor chain C: 208N; top tension of target anchor chain D: 205N; top tension of target anchor chain E: 460N; and top tension of target anchor chain F: 463N. This yields the top tension dataset.

[0064] Table 3

[0065]

[0066] Step 104: Store the top tension dataset, which is used to monitor the target anchor chain in the actual environment.

[0067] The top tension dataset is stored for monitoring target anchor chains in real-world environments.

[0068] It should be noted that due to the differences between the actual environment and the environment of the target anchor chain in the simulation, including the fact that the target anchor chain is connected to a ship or floating wind turbine in the actual environment, the top tension dataset needs to be converted into a dataset for monitoring in the actual environment according to the scale.

[0069] For example, as shown in Table 4, the top tension dataset is obtained by converting the top tension dataset shown in Table 3 by a factor of 10. Target anchor chains A, C, and E are anchor chains of the same specification. The top tension dataset shown in Table 4 is used to monitor target anchor chains of the same specification as target anchor chain A in a real-world environment. The risk of target anchor chains dragging or breaking can be monitored using the top tension data of target anchor chain A in a normal state, target anchor chain C in a dragging state, and target anchor chain E in a broken state.

[0070] Table 4

[0071]

[0072] In the above scheme, a simulation device including a displacement device, multiple target anchor chains, and corresponding sensors is used. First, displacement parameters covering the pitch, roll, and yaw angles, as well as the distances in the lateral, longitudinal, and vertical directions, are acquired. Then, a preset spatial range is determined based on these displacement parameters. The displacement device is controlled to move within the preset spatial range at a preset speed and acceleration to simulate the influence of ocean currents on the anchor chains. During the displacement process, sensors continuously collect tip tension data of multiple target anchor chains in normal, dragged, and broken anchor states, forming and storing a tip tension dataset. This dataset can then be proportionally converted into a monitoring dataset adapted to the actual environment for monitoring target anchor chains in real-world conditions. This effectively fills the gap in current floating wind turbine mooring system monitoring technology, overcomes the limitations of relying solely on sensors mounted on blades or towers, abandons traditional manual monitoring methods, and significantly improves the monitoring efficiency of floating wind turbine mooring systems. Meanwhile, by acquiring benchmark data on the top tension of the anchor chain under different target conditions and applying it to actual monitoring, the phenomenon of misjudgment during the monitoring process is effectively reduced. This provides reliable data support for timely identification of situations such as anchor dragging and anchor breakage that may occur in the long-term operation of the floating wind turbine mooring system in the marine environment, thereby ensuring the normal operation of floating wind turbine power generation.

[0073] In one example of this application, a method for determining monitoring data is also provided, wherein the damage degrees of the multiple target anchor chains are different, and the method for collecting the tip tension dataset of the target anchor chains includes:

[0074] The tip tension of each target anchor chain under multiple different target states is collected to obtain the tip tension dataset, which includes the tip tension of multiple target anchor chains with different degrees of damage under multiple different target states.

[0075] The simulation device contains multiple target anchor chains, each with different target states and varying degrees of damage. Damage can be caused by corrosion or abrasion.

[0076] For example, in the top tension dataset shown in Table 3, target anchor chains A, B, C, D, E, and F are all of the same specification. Target anchor chains A, C, and E are all new, undamaged anchor chains, while target anchor chains B, D, and F all have corrosion damage of the same degree. When the displacement device moves at a preset speed within a preset spatial range, the top tension of these six target anchor chains is collected, resulting in top tensions corresponding to multiple target anchor chains with different degrees of damage under multiple different target conditions.

[0077] In the above scheme, for multiple target anchor chains in the simulation device, in addition to setting different target states such as normal state, anchor dragging state, and anchor breakage state, different damage degrees caused by corrosion or wear are also set. Then, the tip tension of each target anchor chain with different damage degrees is collected under multiple different target states, forming a tip tension dataset containing multiple damage degree differences. This ensures that the obtained tip tension dataset not only covers the tip tension data of anchor chains under different states, but also supplements the tip tension data of anchor chains with different damage degrees, further expanding the coverage of the monitoring data. This allows for a more comprehensive matching of target anchor chains that may have different corrosion or wear conditions in actual environments when the dataset is subsequently converted proportionally for use in actual environmental monitoring. It provides more sufficient data support for accurately identifying the tension change characteristics of anchor chains with different damage degrees under various states, effectively avoiding the problem of incomplete actual monitoring due to a lack of damage degree-related data. Therefore, the monitoring of target anchor chains in actual environments is more closely aligned with their real-world usage conditions.

[0078] This application also provides a method for determining monitoring data in one example, such as Figure 2 As shown, the method further includes:

[0079] Step 201: Obtain the size data and displacement parameters of the object to be measured and the size data of the simulation device.

[0080] The object to be tested can be a ship or a floating wind turbine, or any other object that needs to operate in a marine environment.

[0081] Obtain the dimensional data of the actual object under test, as well as the displacement parameters of the object when it is stationary in the actual environment due to factors such as ocean waves. Obtain the dimensional data of the simulation device. The dimensional data of the simulation device can be determined based on the size of the test environment.

[0082] For example, if the object under test is a floating wind turbine, the dimensions of the floating wind turbine include: platform length 20 meters, width 20 meters, height 8 meters, and anchor chain length 500 meters. The displacement parameters of the floating wind turbine in the actual marine environment include: lateral displacement ±5200 mm, longitudinal displacement ±5200 mm, and vertical displacement ±2600 mm. The dimensions of the simulation device include: platform length 1 meter, width 1 meter, height 0.4 meters, and anchor chain length 25 meters.

[0083] Step 202: Determine the size coefficient based on the size data of the object to be measured and the size data of the simulation device.

[0084] The size factor is determined based on the size data of the object under test and the size data of the simulation device, which is the scaling factor of the object under test and the simulation device in the size dimension.

[0085] Step 203: Determine the displacement coefficients between the object under test and the simulation device based on the size coefficient.

[0086] Based on similarity theory, and considering the uncertainty of the characteristic relationships of similar structures, it is necessary to assume that the main parameters affecting the forces acting on a physical system are external loads. Elastic modulus Dimension L, stress Displacement The target parameters are set as two physical quantities: stress and displacement. These two physical quantities are then expressed as functions of the remaining physical quantities.

[0087]

[0088]

[0089] We can obtain:

[0090]

[0091]

[0092] Furthermore, using force F and dimension L as the fundamental physical quantities, the remaining physical quantities can be expressed in terms of dimensions as follows:

[0093]

[0094]

[0095]

[0096]

[0097] Based on the principle of uniform dimensions, both sides of the equation have equal dimensions. Therefore, by setting up a system of equations, we can obtain:

[0098]

[0099] Substituting the system of equations into formulas (1) and (2), and then rearranging the terms, we can obtain:

[0100]

[0101]

[0102] According to formula (4), the displacement y is the same as the dimension L, that is, the displacement coefficient and the dimension coefficient are the same. Therefore, the corresponding displacement coefficient can be determined by the dimension coefficients of the object to be measured and the simulation device.

[0103] Continuing with the above example, the size factor of the object under test and the simulation device is: The corresponding displacement coefficient is also .

[0104] Step 204: Determine the displacement parameters of the simulation device based on the displacement parameters of the object to be measured and the displacement coefficient.

[0105] Continuing with the above example, the displacement parameters of the object to be measured include: lateral displacement ±5200mm, longitudinal displacement ±5200mm, and vertical displacement ±2600mm. Based on the displacement coefficient... The displacement parameters of the simulation device were determined to be: lateral displacement ±260mm, longitudinal displacement ±260mm, and vertical displacement ±130mm.

[0106] It should be noted that the attitude angle data in the displacement parameters does not need to be adjusted using displacement coefficients. The attitude angle data of the simulation device can directly use the attitude angle data of the object under test. It can also be connected to the monitoring system of the object under test, which collects the real-time displacement parameters of the object under test, converts them into displacement parameters for the simulation device using displacement coefficients, and sends them to the simulation device for simulation, achieving real-time monitoring. Furthermore, it can be connected to a deep learning model, inputting the collected real-time displacement parameters of the object under test and the environmental data of the sea area where the object is located into the deep learning model to predict the displacement parameters of the object under test over a future period, thereby predicting the tip tension that the target anchor chain will bear in the future.

[0107] In the above scheme, the dimensional data and displacement parameters of the object under test (AUT), as well as the dimensional data of the simulation device, are first obtained. Then, the dimensional coefficient is determined based on the dimensional data of AUT and the simulation device. Subsequently, using similarity theory and dimensional analysis, the displacement coefficient is found to be the same as the dimensional coefficient. Finally, the displacement parameters of the simulation device are determined using the displacement parameters of AUT and the displacement coefficient. This effectively establishes a parameter correlation between AUT and the simulation device, allowing the displacement parameters of the simulation device to accurately match the motion characteristics of AUT in the actual environment. This avoids the problem of the simulation device parameter settings being out of sync with the actual AUT, and simplifies the steps for determining the displacement parameters of the simulation device. It ensures that the motion state simulated by the simulation device is more closely related to the actual situation of AUT, thus making the subsequent top tension dataset collected by the simulation device more consistent with actual monitoring needs and providing more accurate data support for monitoring the mooring system of AUT in actual environments.

[0108] This application also provides a method for determining monitoring data in one example, such as Figure 3 As shown, after obtaining the displacement parameters of the simulation device, the method further includes:

[0109] Step 301: Obtain the positioning data of the simulation device.

[0110] In this embodiment, the positioning data of the simulation device is obtained by sensors to acquire the initial reference position coordinates of its displacement device. For example, the initial positioning data of the displacement device in the three-dimensional coordinate system is (0mm, 0mm, 0mm), where the x-axis represents the horizontal direction, the y-axis represents the vertical direction, and the z-axis represents the vertical direction. The three-dimensional coordinate system has the center of the displacement device as the origin.

[0111] Step 302: Determine the preset spatial range based on the displacement parameters and the positioning data.

[0112] Following the example above, the displacement parameters of the simulation device include: lateral displacement ±260mm, longitudinal displacement ±260mm, and vertical displacement ±130mm. Using the positioning data of the simulation device as the center, and combining the displacement parameters, the preset spatial range is determined to include: lateral -260mm~260mm, longitudinal -260mm~260mm, and vertical -130mm~130mm.

[0113] In the above scheme, after acquiring the displacement parameters of the simulation device, the initial reference position coordinates of the displacement device are first obtained using sensors as positioning data. Then, based on this positioning data and the displacement parameters, a preset spatial range is determined. This accurately defines the motion boundary of the displacement device, avoiding the problem of ambiguous spatial range definition due to the lack of a reference. It ensures that the subsequent displacement of the displacement device within the preset spatial range more closely matches the motion scenario of the object under test in the actual environment. Consequently, the tension data at the top of the target anchor chain collected by the sensors better matches the actual monitoring requirements, providing a more accurate foundation for subsequent monitoring of the target anchor chain in the actual environment based on this dataset.

[0114] This application also provides a method for determining monitoring data in one example, such as Figure 4 As shown, the method further includes:

[0115] Step 401: Obtain the load parameters of the object to be tested and the rated load of the simulation device.

[0116] The load parameter is the actual self-weight of the object under test. The rated load of the simulation device is the maximum load that the simulation device can withstand.

[0117] For example, the object under test is a floating wind turbine, and its load parameter is obtained as 3000kN. The rated load of the simulation device is obtained as 50kN.

[0118] Step 402: Determine the load parameters of the simulation device based on the load parameters of the object to be tested, the rated load of the simulation device, and the size factor. The load parameters of the simulation device are used to set the load of the simulation device.

[0119] According to formula (3), when the stress data of the object under test is equal to the stress data of the simulation device, the load factor between the object under test and the simulation device is directly proportional to the square of the size factor. Therefore, in this embodiment, the material of the simulation device is selected to be the same as that of the object under test, so that the stress data of the two are also the same. Then, the load parameters of the simulation device that do not exceed the rated load are determined by the load factor and the load parameters of the object under test.

[0120] Continuing with the above example, the dimensional factor between the object under test and the simulation device is... The corresponding load factor is proportional to the square of the size factor, i.e. The load parameter of the object under test is 4000kN, and the rated load of the simulation device is 50kN. When the load factor... When the load factor is 1, the load parameter of the simulation device is 10kN, which does not exceed the rated load of the simulation device. When the load factor is twice that of the device, the load parameter of the simulation device is 20kN, which does not exceed the rated load of the simulation device. When the load factor is... When the load factor is three times that of the simulation device, the load parameter is 30kN, which does not exceed the rated load of the simulation device. When the load factor is... When the load factor is four times that of the simulation device, the load parameter is 40kN, which does not exceed the rated load of the simulation device. When the load factor... When the load factor is 5 times the rated load, the load parameter of the simulation device is 50kN, which does not exceed the rated load of the simulation device. When the load is 6 times the rated load, the simulation device's load parameter is 60kN, exceeding the device's rated load. Therefore, the simulation device's load parameters are {10kN, 20kN, 30kN, 40kN, 50kN}. The simulation device's load can be set based on these load parameters.

[0121] In the above scheme, the load parameters of the object under test and the rated load of the simulation device are first obtained. Then, by selecting the same material as the object under test to make the stress data of the two equal, and combining the relationship that the load factor is proportional to the square of the size factor, the load parameters of the simulation device that do not exceed the rated load are determined and used to set the load of the simulation device. This avoids damage to the simulation device due to the load exceeding the rated load, and also ensures that the load of the simulation device and the load of the object under test maintain a reasonable correspondence. This ensures that the stress state of the simulation device during subsequent operation closely matches the actual stress condition of the object under test. As a result, the target anchor chain tip tension dataset collected by the sensor can better reflect the actual working conditions, providing a more reliable basis for subsequent monitoring of the target anchor chain in the actual environment based on this dataset.

[0122] This application provides an example of a simulation device, such as... Figure 5 As shown, the simulation device 500 includes: a displacement device 501, a plurality of target anchor chains 502, and a sensor 503 corresponding to the target anchor chains 502;

[0123] The top end of the target anchor chain 502 is connected to the displacement device 501; the sensor 503 is disposed at the top end of the target anchor chain 502.

[0124] The top end of the target anchor chain 502 is connected to the displacement device 501. When the displacement device 501 moves within a preset displacement range, it pulls the target anchor chain 502 to simulate the state of the target anchor chain under the force of waves and other forces in the actual marine environment. A sensor 503 is placed at the top end of the target anchor chain 502 to accurately collect the tension at the top of the target anchor chain 502.

[0125] This application also provides an example of a simulation device, such as... Figure 5 As shown, the displacement device 501 further includes: an upper platform 5011, a lower platform 5012, and multiple electric cylinders 5013;

[0126] The top end of the target anchor chain 502 is connected to the upper platform 5011; the plurality of electric cylinders 5013 are connected to the upper platform 5011 and the lower platform 5012.

[0127] The top of each target anchor chain 502 is connected to the edge of the upper platform 5011. Multiple electric cylinders 5013 connect the upper platform 5011 and the lower platform 5012.

[0128] Multiple electric cylinders 5013 are used to receive control commands and move according to the control commands, driving the upper platform 5011 to move within the preset displacement range indicated by the control commands. The upper platform 5011 moves within the preset displacement range, pulling the target anchor chain 502, so that the target anchor chain 502 bears the tension, in order to simulate the influence of factors such as ocean waves on the target anchor chain 502 in the real marine environment.

[0129] It should be noted that when conducting simulation tests on the simulation device, the simulation device needs to be set on a plane. The bottom end of the target anchor chain can be connected to the same plane as the simulation device, or to a plane that is lower than the plane where the simulation device is located, such as 30-50 cm lower, depending on the actual situation or requirements.

[0130] This application also provides a simulation device testing method in one example, such as Figure 6 As shown, the method includes:

[0131] Step 601: Control the displacement device to move the target distance.

[0132] By sending control commands to the displacement device, the displacement device can be controlled to move the target distance.

[0133] For example, a control command is sent to the displacement device, instructing the displacement device to move laterally by 200 mm.

[0134] Step 602: Obtain the actual distance of the displacement device.

[0135] After the displacement device moves according to the control command, the actual distance of the displacement device after the displacement is obtained.

[0136] Following the example above, after receiving the control command, the displacement device actually moved laterally by 190mm.

[0137] Step 603: Determine the distance deviation based on the target distance and the actual distance, wherein the distance deviation characterizes the performance of the displacement device.

[0138] Continuing with the example above, the distance deviation between the target distance and the actual distance of the displacement device is 20mm. This can characterize the performance of the displacement device.

[0139] It should be noted that the smaller the distance deviation, the better the performance of the control system of the displacement characterizing device.

[0140] In the above scheme, control commands are first sent to the displacement device to control its target displacement distance. After the displacement device completes the displacement operation, its actual displacement distance is obtained. Then, the distance deviation is calculated based on the target distance and the actual distance, and this distance deviation is used to characterize the performance of the displacement device. It is clear that the smaller the distance deviation, the better the performance of the displacement device's control system. This allows for a direct and accurate understanding of the displacement device's operating performance, avoiding insufficient displacement accuracy in subsequent simulations due to poor device performance. It ensures that the displacement device can accurately reproduce the motion of the object under test in the actual environment, thereby guaranteeing the accuracy of the target anchor chain top tension dataset collected by sensors. This provides more reliable support for subsequent monitoring of the target anchor chain in the actual environment based on this dataset.

[0141] In one example of this application, a method for testing a simulation device is also provided, the method comprising:

[0142] First, construct a simulation curve based on the position and length of the target anchor chain in the actual environment. Divide the simulation curve into n equally straight segments, and take the center point of each segment to obtain n-1 target points.

[0143] like Figure 7 As shown, Figure 7 The simulation curve of a constructed target anchor chain is shown, where, (kN) represents the tip tension of the target anchor chain, which can be decomposed into a horizontal component. (kN) and along the vertical direction (kN), The depth is in meters (m). The bottoming point of the target anchor chain. The length (m) of the target anchor chain. The total length of the target anchor chain is projected horizontally as a distance (m). The angle between the top of the target anchor chain and the horizontal direction.

[0144] After constructing the simulation curve, the tip tension of the target anchor chain, neglecting the influence of wave and current loads, is calculated using the following formula. :

[0145]

[0146] in, The target anchor chain has a unit length mass (kN / m) in seawater.

[0147] Calculate according to the following formula :

[0148]

[0149] in, The target anchor chain has a unit length mass (kN / m) in seawater.

[0150] As ocean current velocity increases, the wave and current load on the target anchor chain gradually increases. The components of the drag force and inertial force along the tangential direction of the target anchor chain affect the actual tip tension. Therefore, after calculating the tip tension of the target anchor chain without considering the wave and current load, it is also necessary to calculate the drag force and inertial force of the target anchor chain affected by the wave and current load. Environmental data of the sea area to be measured are collected, and the drag force and inertial force of the target anchor chain affected by the wave and current load are calculated based on the environmental data.

[0151] Calculate the drag force of each segment of the simulated curve using the following formula. :

[0152]

[0153] in, The preset drag force coefficient, The density of the seawater in the area to be tested. The projected area of ​​each curve segment in the horizontal direction (which can be determined by the segment of the actual target anchor chain corresponding to the curve). This represents the horizontal velocity of the ocean current.

[0154] Calculate the inertial force of each segment of the simulated curve using the following formula. :

[0155]

[0156] in, The preset inertial force coefficient, The density of the seawater in the area to be tested. The volume of each curve segment (which can be determined by the segment of the actual target anchor chain corresponding to the curve). This represents the horizontal acceleration of the ocean current.

[0157] After determining the drag force and inertial force corresponding to each curve segment, the drag forces corresponding to all curves are summed to obtain the drag force of the target anchor chain. Summing the inertial forces corresponding to all curves yields the inertial force of the target anchor chain. .

[0158] The tip tension of the target anchor chain is calculated according to the following formula. :

[0159]

[0160] The tension at the tip of the target anchor chain This can be used to verify the reliability of the top tension dataset of the target anchor chain determined by the simulation device. If the deviation is small, the top tension dataset is reliable. If the deviation is large, the top tension dataset is unreliable, and the parameters of the simulation device need to be further adjusted until the top tension dataset is reliable.

[0161] In the above scheme, a simulated curve is first constructed based on the position and length of the target anchor chain in the actual environment. This curve is divided into multiple straight segments, and the target point is obtained by taking the center point of each segment. Next, the tip tension of the target anchor chain, without considering the influence of wave and current loads, is calculated. Then, environmental data of the sea area to be measured is collected. Based on the environmental data, the drag force and inertial force of each segment in the simulated curve are calculated. The drag force and inertial force of all curves are summed to obtain the total drag force and total inertial force of the target anchor chain. Finally, the actual tip tension of the target anchor chain is calculated by combining the tip tension without considering wave and current loads. This actual tip tension is used to verify the reliability of the tip tension dataset determined by the simulation device. If the deviation is small, the dataset is reliable; if the deviation is large, the simulation device parameters are adjusted until the dataset is reliable. This method can effectively determine whether the tip tension dataset collected by the simulation device matches the actual situation, avoiding deviations in the monitoring of the target anchor chain in the actual environment due to the use of unreliable datasets. Furthermore, when the dataset is unreliable, adjustments can be made to ensure that subsequent actual monitoring work based on this dataset is more reliable.

[0162] In one example of this application, a motor testing method is also provided, the method comprising:

[0163] In this embodiment, the motor of the electric cylinder in the simulation device can be tested.

[0164] An electric motor converts electrical energy into mechanical energy by generating force in a magnetic field through the flow of current or by inducing electromotive force through its motion cutting magnetic field lines. Motor testing refers to the maximum load a motor can withstand. Under normal operating conditions, a higher load capacity results in better stability under load changes and a shorter response time.

[0165] The specific process involves controlling the motor in a steady-state state under no-load (load) conditions at 0.5 times its rated speed, then suddenly applying 0.5 times its rated load. After the motor stabilizes again, the load is suddenly unloaded, and the change curve of the motor speed during this process is recorded. If the motor recovers its original speed within a given sampling period, it indicates that the motor's ability to resist load disturbances meets the actual operating requirements of the engineering project.

[0166] In the above scheme, specific tests are conducted on the motor of the electric cylinder in the simulation device. First, the motor is controlled to operate in a steady-state state under no-load conditions at 0.5 times its rated speed. Then, a load of 0.5 times the rated speed is suddenly applied. After the motor stabilizes again, it is suddenly unloaded, and the motor speed change curve is recorded. If the motor can recover its original speed within a given sampling period, it indicates that its load disturbance resistance meets the actual engineering operation requirements. This test effectively verifies the motor's load-bearing capacity and operational stability, ensuring that the motor has both good stability and rapid response when the load changes. As a key component of the drive displacement device, the reliable performance of the motor ensures that the displacement device accurately moves according to requirements, thereby making the target anchor chain top tension data collected by sensors more accurate, providing a more reliable guarantee for monitoring the target anchor chain in actual environments.

[0167] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0168] Figure 8 A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0169] like Figure 8 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. The RAM 703 may also store various programs and data required for the operation of the electronic device 700. The computing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0170] Multiple components in electronic device 700 are connected to I / O interface 705, including: input unit 706, such as keyboard, mouse, etc.; output unit 707, such as various types of displays, speakers, etc.; storage unit 708, such as disk, optical disk, etc.; and communication unit 709, such as network card, modem, wireless transceiver, etc. Communication unit 709 allows electronic device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0171] The computing unit 701 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as the monitoring data determination method. For example, in some embodiments, the monitoring data determination method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by the computing unit 701, one or more steps of the monitoring data determination method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the monitoring data determination method by any other suitable means (e.g., by means of firmware).

[0172] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0173] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0174] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0175] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0176] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0177] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0178] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0179] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0180] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method of monitoring data determination, characterized by, The method is applied to a simulation device, which includes a displacement device, multiple target anchor chains, and sensors corresponding to the target anchor chains. The displacement device includes an upper platform, a lower platform, and multiple electric cylinders connecting the upper platform and the lower platform. The multiple electric cylinders are used to receive control commands and move according to the control commands, driving the upper platform to move within a preset displacement range indicated by the control commands. Obtain the displacement parameters of the displacement device; The displacement device is controlled to move at a preset speed within a preset spatial range, the preset spatial range being determined based on the displacement parameters; The sensor collects a dataset of tip tension of the target anchor chain. The dataset includes the tip tension of the target anchor chain under multiple different target states, including at least one of the following: normal state, anchor dragging state, and anchor breakage state. The top tension dataset is stored and used to monitor the target anchor chain in a real-world environment. The multiple target anchor chains have different degrees of damage, and the top tension dataset of the target anchor chains is collected, including: The tip tension of each target anchor chain under multiple different target states is collected to obtain the tip tension dataset, which includes the tip tension of multiple target anchor chains with different damage levels under multiple different target states. A simulation curve is constructed based on the position and length of the target anchor chain in the actual environment; The component of the top end tension of the target anchor along the horizontal direction is calculated according to the following formula : wherein, is the unit length mass of the target chain in seawater, is the water depth, is the length of the target chain; The target top tension of the anchor chain without considering the influence of wave current load is calculated according to the following formula : ； The drag force for each segment of the simulated curve is calculated according to the following equation : wherein, is a preset drag coefficient, is the seawater density of the sea area to be measured, is the projection area of each curve in the horizontal direction, is the flow velocity of the sea current in the horizontal direction; The inertial force for each segment of the simulated curve is calculated according to the following formula : wherein, is a preset inertial force coefficient, is the seawater density of the sea area to be measured, is the volume of each curve, is the acceleration of the sea current in the horizontal direction; Summing up the drag force of all curves, the target anchor chain drag force is obtained ; Summing up the inertia forces corresponding to all the curves, the inertia force of the target anchor is obtained ; The top end tension of the target anchor chain is calculated according to the following formula : ； Top end tension of target anchor chain A method for verifying whether a top end tension data set of a target anchor chain determined by a simulation device is trustworthy.

2. The method of claim 1, wherein, The method further includes: Acquire the dimensional data and displacement parameters of the object to be measured, and the dimensional data of the simulation device; The size factor is determined based on the size data of the object to be measured and the size data of the simulation device; The displacement coefficients between the object under test and the simulation device are determined based on the size coefficients. The displacement parameters of the simulation device are determined based on the displacement parameters of the object under test and the displacement coefficient.

3. The method of claim 1, wherein, After obtaining the displacement parameters of the displacement device, the method further includes: Obtain the positioning data of the simulation device; The preset spatial range is determined based on the displacement parameters and the positioning data.

4. The method of claim 2, wherein, The method further includes: Obtain the load parameters of the object under test and the rated load of the simulation device; The load parameters of the simulation device are determined based on the load parameters of the object to be tested, the rated load of the simulation device, and the size factor. The load parameters of the simulation device are used to set the load of the simulation device.

5. The method of claim 1, wherein, The method includes: The displacement device is controlled to move the target distance; Obtain the actual distance of the displacement device; The distance deviation is determined based on the target distance and the actual distance, and the distance deviation characterizes the performance of the displacement device.

6. An electronic device, comprising: include: Processor; memory for storing processor-executable instructions; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the monitoring data determination method according to any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for executing the monitoring data determination method according to any one of claims 1-5.

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