Real-time position detection method and device of fan submarine cable and electronic equipment

Abstract

The embodiment of the invention discloses a real-time position detection method and device for a fan submarine cable and electronic equipment. The method comprises the following steps: arranging a plurality of three-way gyroscopes on a central axis of a fan submarine cable to obtain angular velocity data of a plurality of acquisition points, then calculating each angular velocity data based on a quaternion updating method, and then performing interpolation curve fitting on each attitude data, and performing position detection on each unit point to be detected in the real-time position fitting curve based on a Gaussian distribution estimation method to generate detection information. Through the position detection method, the purpose of obtaining the real-time position information of the fan submarine cable is achieved, and through the installed three-way gyroscope and fitting of the real-time position curve of the fan submarine cable, the acquisition precision of obtained data is improved, the automatic detection requirement is met, and the manual inspection frequency and cost are reduced.

Description

Technical Field

[0001] One or more embodiments of this specification relate to the field of instrument measurement and control technology, and in particular, to a method, device, and electronic equipment for real-time position detection of a wind turbine submarine cable. Background Art

[0002] With the rapid development of offshore wind power generation technology, it is necessary to detect the real-time position of the submarine cables at the access end of wind turbines in offshore wind farms to assess the position changes and potential risks of the submarine cables, so as to promptly perform maintenance inspections on wind turbine cables in abnormal positions. Currently, existing monitoring methods often adopt manual scanning methods, using three-dimensional sonar scanning and multi-beam sonar to obtain the location information of the submarine cables. However, traditional manual measurement methods rely on regular monitoring. In extreme weather or sea conditions, inspection work may be forced to be interrupted, and the location information of the submarine cables cannot be obtained in real time, resulting in untimely data updates. In addition, manual measurement inspections are not only affected by multiple factors such as the accuracy of the measuring tools and the experience of the inspectors, resulting in limited data accuracy, but also require a large amount of manpower, material and financial resources, which also increases the operating costs of offshore wind farms. Summary of the Invention

[0003] The embodiments of this specification provide a method, device, and electronic device for real-time position detection of a wind turbine submarine cable, and the technical solutions are as follows:

[0004] In a first aspect, an embodiment of this specification provides a method for detecting the real-time position of a wind turbine submarine cable, the method comprising:

[0005] Acquire angular velocity data of at least two acquisition points in the wind turbine submarine cable based on a three-axis gyroscope, and calculate each of the angular velocity data based on a quaternion update method to obtain attitude data corresponding to each of the acquisition points, wherein each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable;

[0006] Performing interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable;

[0007] Based on the Gaussian distribution estimation method, position detection is performed on each unit point to be tested in the real-time position fitting curve to generate detection information.

[0008] In a second aspect, a real-time position detection device for a wind turbine submarine cable is provided, the device comprising:

[0009] A calculation module is configured to obtain angular velocity data of at least two acquisition points in the wind turbine submarine cable based on a three-axis gyroscope, and calculate each of the angular velocity data based on a quaternion update method to obtain attitude data corresponding to each of the acquisition points, wherein each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable;

[0010] A fitting module, configured to perform interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable;

[0011] The detection module is used to perform position detection on each unit point to be detected in the real-time position fitting curve based on the Gaussian distribution estimation method to generate detection information.

[0012] In a third aspect, an electronic device is provided, including a device processor and a memory;

[0013] The device processor is connected to the memory;

[0014] The memory is used to store executable program code;

[0015] The device processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the steps of the method provided in the first aspect or any possible implementation manner of the first aspect.

[0016] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and the computer-readable storage medium stores instructions. When the instructions are executed on a computer or device processor, the computer or device processor executes the method provided in the first aspect or any possible implementation of the first aspect.

[0017] The beneficial effects of the technical solutions provided by some embodiments of this specification include at least:

[0018] In one or more embodiments of this specification, multiple three-axis gyroscopes are installed on the central axis of the wind turbine submarine cable to obtain angular velocity data from multiple collection points. Each angular velocity data is then calculated based on the quaternion update method, and then an interpolation curve is fitted for each attitude data. The position of each unit point to be measured in the real-time position fitting curve is detected based on the Gaussian distribution estimation method to generate detection information. The above position detection method achieves the purpose of obtaining the real-time position information of the wind turbine submarine cable. Furthermore, by installing and installing the three-axis gyroscope and fitting the real-time position curve of the wind turbine submarine cable, not only is the data acquisition accuracy improved, but it also meets the requirements of automated detection and reduces the frequency and cost of manual inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flow chart of a method for real-time position detection of a wind turbine submarine cable provided in an embodiment of this specification;

[0021] Figure 2 A schematic structural diagram of a real-time position detection device for a wind turbine submarine cable provided in an embodiment of this specification;

[0022] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application.

[0024] Throughout this specification, the claims, and the accompanying drawings, the terms "first," "second," "third," and the like are used to distinguish between different items, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may include other steps or elements inherent to the process, method, product, or apparatus.

[0025] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the functions and arrangements of the elements described without departing from the scope of this specification. Various examples may appropriately omit, replace, or add various processes or components. For example, the described methods may be performed in an order different from the order described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined in other examples.

[0026] See also Figure 1 , Figure 1 The figure shows an overall flow chart of a method for real-time position detection of a wind turbine submarine cable provided in an embodiment of the present specification.

[0027] like Figure 1 As shown, the real-time position detection method of the wind turbine submarine cable may include at least the following steps:

[0028] Step 101: Acquire angular velocity data of at least two acquisition points in a wind turbine submarine cable based on a three-axis gyroscope, and calculate each angular velocity data based on a quaternion update method to obtain attitude data corresponding to each acquisition point.

[0029] Wherein, each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable.

[0030] In the embodiments of this specification, during offshore wind turbine power generation, the exposed section of the wind turbine cable, from the turbine outlet to the seabed entry point, is subject to fluctuations in real-time position due to the influence of sea conditions. When the wind turbine cable's real-time position exceeds a pre-set safety zone, a potential risk exists, requiring timely maintenance and correction. Therefore, to obtain the real-time position of the wind turbine cable, multiple three-dimensional high-precision gyroscopes can be evenly installed along the central axis of the wind turbine cable as detection sensors, for example, one three-dimensional high-precision gyroscope installed every 0.5 meters. Next, each three-dimensional high-precision gyroscope performs real-time data acquisition to obtain angular velocity data at the installation point. Furthermore, since each angular velocity data can only represent individual angular velocity values, to obtain the rotational attitude of each acquisition point in three-dimensional space, the quaternion update method can be used to convert and calculate the angular velocity data to obtain the attitude data corresponding to each acquisition point. The use of the quaternion update method avoids the gimbal lock problem of Euler angles and improves computational efficiency.

[0031] Optionally, a MEMS gyroscope can be selected as the three-axis high-precision gyroscope. The gyroscope sampling frequency is set to 100 Hz, the range is ±2000° / s, and the data is transmitted via the RS-485 bus.

[0032] The quaternion differential equation is:

[0033]

[0034] in, is the quaternion differential, q is the quaternion, ω is the angular velocity vector, is the quaternion multiplication operator.

[0035] The update formula after discretization of the quaternion differential equation is:

[0036]

[0037] Among them, q k The quaternion at the current moment, q k+1 is the quaternion at the next moment, Δt is the time step, and k1, k2, k3, and k4 are the slope calculation values in the Runge-Kutta fourth-order method.

[0038] As an example, assume the angular velocity data of two acquisition points:

[0039] Angular velocity of acquisition point 1 ω1 = [0.1, 0.02, 0.05]

[0040] Angular velocity of acquisition point 2 ω2 = [0.08, 0.03, 0.04]

[0041] If we assume that the initial quaternion q0 = [1, 0, 0, 0] and Δt = 0.1s, we can substitute the initial quaternion q0 and Δt = 0.1s into the calculation after discretization of the quaternion differential equation and obtain:

[0042] The posture of collection point 1 q1 = [0.995, 0.005, 0.001, 0.0025]

[0043] The posture of collection point 2 is q2 = [0.996, 0.004, 0.0015, 0.002].

[0044] In one possible implementation manner, after acquiring angular velocity data of at least two acquisition points in the wind turbine submarine cable based on the three-axis gyroscope, the method includes:

[0045] Performing denoising on the angular velocity data based on a Kalman filter algorithm to obtain standard data;

[0046] Performing time alignment on each of the standard data according to a timestamp synchronization method to obtain synchronized data;

[0047] The quaternion update method is used to calculate each of the angular velocity data to obtain the posture data corresponding to each of the acquisition points, including:

[0048] The synchronization data are calculated based on the quaternion update method to obtain the posture data corresponding to each acquisition point.

[0049] In the embodiments of this specification, in order to eliminate the white noise or temperature drift generated by the three-axis gyroscope during data acquisition, improve the data signal-to-noise ratio, and reduce the integration error, after obtaining the angular velocity data of each acquisition point, the Kalman filter state equation can be used to denoise the angular velocity data to obtain standard data. The Kalman filter state equation is:

[0050] x k =Fx k-1 +w k

[0051] Among them, x k is the system state vector at the current time step k, F is the identity matrix, x k-1 is the system state vector at the previous time step k-1, w k is the process noise.

[0052] The observation equation is:

[0053] z k =Hx k +v k

[0054] Among them, z kis the observation value at the current moment, H is the observation matrix, v k is the observation noise.

[0055] If the original angular velocity ω1 = [0.1, 0.02, 0.05], and determine the unit matrix F, process noise w k , observation matrix H, observation noise V k , and then substitute the obtained system state vector into the observation equation through the Kalman filter state equation. The corresponding standard data after calculation is ω1'=[0.098, 0.021, 0.049].

[0056] Next, since the raw angular velocity data collected by each three-axis gyroscope may correspond to different collection times, in order to align the data timestamps of different collection points and prevent the time error caused by asynchronous sampling, it is necessary to use the timestamp synchronization method to time-align the standard data to obtain synchronized data.

[0057] In one possible implementation, the calculating of each angular velocity data based on the quaternion update method to obtain the posture data corresponding to each acquisition point includes:

[0058] determining the angular velocity change corresponding to each angular velocity data according to an angular velocity integration method;

[0059] The angular velocity changes are calculated based on the quaternion update algorithm to obtain the posture data corresponding to each acquisition point.

[0060] In the embodiments of this specification, since the angular velocity change is generally more convenient for converting non-continuous data than the angular velocity data, and can be applied to different coordinate system processing environments, it becomes the basis for subsequent posture updates. Therefore, when calculating each angular velocity data using the quaternion update method, the angular velocity change corresponding to each angular velocity data can be first determined using the angular velocity integration method, and then the quaternion update formula can be used to calculate each angular velocity change to obtain the posture data corresponding to each acquisition point. As an example, the angular velocity integration formula is as follows:

[0061] Δθ=ω·Δt

[0062] If the sampling point ω1=[0.1,0.02,0.05], Δt=0.1s, then Δθ=[0.01,0.002,0.005]

[0063] Next, use the quaternion conversion method to convert Δθ into a quaternion increment Δq:

[0064]

[0065] Furthermore, the previous quaternion differential equation is discretized and the update formula is used to obtain the posture data q1 = [0.995, 0.005, 0.001, 0.0025].

[0066] Step 102: performing interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0067] In the embodiment of this specification, after obtaining the posture data corresponding to all the collection points, since the posture data is obtained through discrete sampling points, in order to obtain the actual position corresponding to the entire wind turbine cable, the difference curve fitting method can be used to process the limited discrete posture data, fill the blank data positions between the collection points, and obtain the real-time position fitting curve of the wind turbine cable.

[0068] Among them, Lagrange interpolation, linear interpolation or cubic spline interpolation can be used when performing interpolation curve fitting.

[0069] In one possible implementation, before performing interpolation curve fitting on each of the posture data to obtain the real-time position fitting curve of the wind turbine submarine cable, the method further includes:

[0070] Determine the attitude transformation matrix between the gyroscope coordinate system and the global coordinate system;

[0071] Convert each of the posture data based on the posture conversion matrix to obtain global coordinate data;

[0072] The interpolation curve fitting is performed on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable, including:

[0073] Interpolation curve fitting is performed on each of the global coordinate data to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0074] In the embodiments of this specification, in order to facilitate the subsequent interpolation curve fitting of all posture data in the same coordinate system, it is necessary to convert the coordinate system of each posture data. Among them, when converting the coordinate data, it is necessary to first determine the gyroscope coordinate system and the global coordinate system. Usually, each posture data is obtained based on the gyroscope coordinate system, that is, the installation position of the gyroscope is used as the origin, and three mutually perpendicular coordinate axes are defined, while the global coordinate system usually takes the starting point of the submarine cable as the origin, and defines three mutually perpendicular coordinate axes. Then, the gyroscope is calibrated using a calibration device to obtain the posture conversion matrix between each gyroscope coordinate system and the global coordinate system, which is used to describe the rotation and translation relationship between the gyroscope coordinate system and the global coordinate system. Among them, the rotation part is used to describe the rotation angle and direction of the gyroscope coordinate system relative to the global coordinate system, and the translation part is used to describe the position offset of the origin of the gyroscope coordinate system relative to the origin of the global coordinate system. Furthermore, according to the determined attitude conversion matrices, the attitude data collected by the gyroscope is multiplied by the attitude conversion matrix to obtain the global coordinate data in the global coordinate system. Subsequently, it is only necessary to perform interpolation curve fitting on the global coordinate data to obtain the real-time position fitting curve of the wind turbine submarine cable.

[0075] As an example, assuming that the calculated posture conversion matrix R1 = [0.995, 0.005, 0.001, 0.0025] and the posture data is [0, 0, 1], the corresponding global coordinates are [0.002, 0.001, 0.995].

[0076] In one possible implementation, performing interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable includes:

[0077] Performing curve fitting on all the posture data based on the cubic spline interpolation method to obtain an interpolation fitting curve of the wind turbine submarine cable;

[0078] The interpolation fitting curve is physically constrained and checked according to the maximum bending limit of the wind turbine submarine cable to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0079] In the embodiment of the present specification, after obtaining the posture data, a cubic spline interpolation method can be used to first construct a cubic polynomial to approximate the data points, and ensure that the curve smoothly transitions between the data points without inflection points or mutations, so as to obtain the interpolation fitting curve of the wind turbine submarine cable. Then, the cubic spline interpolation method may produce some shapes that do not conform to the actual situation, such as excessive bending or twisting, so it is necessary to perform physical constraint verification to ensure that the shape of the curve conforms to the physical characteristics of the wind turbine submarine cable. The maximum bending limit corresponding to the wind turbine submarine cable can be determined based on the design parameters of the wind turbine submarine cable, and further, each point on the interpolation fitting curve can be checked to ensure that its bending angle or curvature does not exceed the maximum bending limit. If some points on the curve exceed the maximum bending limit, they need to be re-adjusted by difference to ensure that the curvature corresponding to each point on the curve meets the maximum bending limit, and then the real-time position fitting curve of the wind turbine submarine cable is obtained.

[0080] Among them, a cubic polynomial is constructed using the cubic spline interpolation method as follows:

[0081] S(x)=a i +b i (xx i )+c i (xx i ) 2 +d i (xx i ) 3

[0082] Among them, a i 、b i 、c i d i The corresponding spline coefficients when constructing polynomials for each posture data are respectively assumed. Assume that the equation of the difference fitting curve after cubic spline interpolation is y=0.4x-0.1x 2 , and calculated by the curve formula Where S′(x) is the first-order derivative function of S(x), S″(x) is the second-order derivative function of S′(x), and finally the curvature k of the point is calculated to be 0.3. If it is judged to be greater than the maximum curvature limit of 0.2, the difference curve needs to be readjusted.

[0083] Step 103 : Perform position detection on each unit point to be detected in the real-time position fitting curve based on a Gaussian distribution estimation method to generate detection information.

[0084] In an embodiment of the present specification, in order to detect the real-time position of the wind turbine submarine cable, the detection information generated is used to ensure that the entire area where it is located meets the preset conditions. First, each unit point to be measured can be set in the real-time position fitting curve, and then the position data corresponding to each unit point to be measured can be detected by the Gaussian distribution estimation method to obtain the detection information.

[0085] Optionally, when using the Gaussian distribution estimation method, a Gaussian distribution estimation model can be constructed, and then the real-time position detection and judgment of each position data can be performed using the constructed Gaussian distribution estimation model. Alternatively, the Gaussian distribution estimation method can be used to directly compare the real-time position data distribution results corresponding to each unit point to be tested with the position data distribution results under historical normal conditions, and the detection information of each unit point to be tested can be determined based on the comparison results.

[0086] In one possible implementation, performing position detection on each unit point to be measured in the real-time position fitting curve based on a Gaussian distribution estimation method to generate detection information includes:

[0087] Determining the position data corresponding to each unit point to be tested in the real-time position fitting curve according to a preset unit interval to be tested;

[0088] A Gaussian distribution estimation model is constructed, and position detection is performed on each of the position data according to the Gaussian distribution estimation model to generate detection information.

[0089] In the embodiments of this specification, a preset interval of units to be tested can be first determined according to the actual user detection needs. Then, the preset interval of units to be tested is evenly matched to the real-time position fitting curve to determine each unit point to be tested and its corresponding position data. In general, the number of units to be tested far exceeds the number of sampling points, so it is necessary to infer the position data corresponding to a large number of unit points to be tested through the real-time position fitting curve determined by a limited number of sampling points. Furthermore, a Gaussian distribution estimation model is constructed through a large amount of historical submarine cable position data under normal conditions, and the position data corresponding to each unit point to be tested is detected separately according to the Gaussian distribution estimation model. Based on the preset position condition analysis, it is judged whether each position data is abnormal, and all the judgment results are statistically integrated to obtain the detection information of the real-time position of the wind turbine submarine cable.

[0090] Among them, the mean vector μ in the Gaussian distribution estimation model is:

[0091]

[0092] Among them, (x i , g i , z i ) The position data corresponding to each unit point to be tested

[0093] The covariance matrix is Σ:

[0094]

[0095] Assume that based on historical data:

[0096]

[0097] For the unit point X to be tested, the Mahalanobis distance or probability density value corresponding to the Gaussian distribution estimation model calculator can be determined, and then the position can be judged to determine whether it is abnormal.

[0098] In one possible implementation manner, performing position detection on each of the position data according to the Gaussian distribution estimation model to generate detection information includes:

[0099] Calculating the probability density value corresponding to each of the position data according to the Gaussian distribution estimation model;

[0100] Each probability density value is compared with the abnormal threshold value, and the detection information corresponding to each unit point to be tested is determined based on each comparison result.

[0101] In the embodiment of this specification, since the Gaussian distribution estimation model is a probability density function, the probability distribution of the submarine cable position data under the Gaussian distribution is described. The model is defined by two parameters: mean μ and variance ∑.

[0102] Next, the probability density value corresponding to the position data of each unit point to be tested can be calculated through the Gaussian distribution estimation model. Furthermore, each calculated probability density value can be compared with the abnormal threshold, where the abnormal threshold is a preset value and can be adjusted according to the actual application scenario and data distribution. If the comparison result indicates that a certain calculated probability density value is lower than the abnormal threshold, the unit point to be tested can be considered an abnormal point, and the position information corresponding to the point is fed back as abnormal. Finally, the judgment results of all the unit points to be tested are counted to obtain the detection information of the real-time position of the wind turbine submarine cable.

[0103] As an example, we can first calculate the Mahalanobis distance D corresponding to the unit point X to be measured. M :

[0104]

[0105] Next, calculate its probability density value p(x):

[0106]

[0107] If it is assumed that the abnormal threshold ε is set to 3, and the calculated p(x)=2.8<3, the position information corresponding to the point is determined to be abnormal.

[0108] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0109] See next Figure 2 , Figure 2 The following is a schematic diagram showing the structure of a real-time position detection device for a wind turbine submarine cable provided in an embodiment of this specification. Figure 2 The real-time position detection device of the wind turbine submarine cable shown is used to implement the present application Figure 1 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figure 1 The embodiment shown.

[0110] like Figure 2 As shown, the real-time position detection device of the wind turbine submarine cable may at least include:

[0111] A calculation module 201 is configured to obtain angular velocity data of at least two acquisition points in the wind turbine submarine cable based on a three-axis gyroscope, and calculate each of the angular velocity data based on a quaternion update method to obtain attitude data corresponding to each of the acquisition points, wherein each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable;

[0112] A fitting module 202 is configured to perform interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable;

[0113] The detection module 203 is configured to perform position detection on each unit point to be detected in the real-time position fitting curve based on a Gaussian distribution estimation method to generate detection information.

[0114] In one embodiment, the acquisition module 201 is specifically configured to:

[0115] Performing denoising on the angular velocity data based on a Kalman filter algorithm to obtain standard data;

[0116] Performing time alignment on each of the standard data according to a timestamp synchronization method to obtain synchronized data;

[0117] The quaternion update method is used to calculate each of the angular velocity data to obtain the posture data corresponding to each of the acquisition points, including:

[0118] The synchronization data are calculated based on the quaternion update method to obtain the posture data corresponding to each acquisition point.

[0119] In one embodiment, the acquisition module 201 is further configured to:

[0120] determining the angular velocity change corresponding to each angular velocity data according to an angular velocity integration method;

[0121] The angular velocity changes are calculated based on the quaternion update algorithm to obtain the posture data corresponding to each acquisition point.

[0122] In one embodiment, the fitting module 202 is specifically configured to:

[0123] Determine the attitude transformation matrix between the gyroscope coordinate system and the global coordinate system;

[0124] Convert each of the posture data based on the posture conversion matrix to obtain global coordinate data;

[0125] The interpolation curve fitting is performed on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable, including:

[0126] Interpolation curve fitting is performed on each of the global coordinate data to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0127] In one embodiment, the fitting module 202 is further configured to:

[0128] Performing curve fitting on all the posture data based on the cubic spline interpolation method to obtain an interpolation fitting curve of the wind turbine submarine cable;

[0129] The interpolation fitting curve is physically constrained and checked according to the maximum bending limit of the wind turbine submarine cable to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0130] In one embodiment, the detection module 203 is specifically configured to:

[0131] Determining the position data corresponding to each unit point to be tested in the real-time position fitting curve according to a preset unit interval to be tested;

[0132] A Gaussian distribution estimation model is constructed, and position detection is performed on each of the position data according to the Gaussian distribution estimation model to generate detection information.

[0133] In one embodiment, the detection module 203 is further configured to:

[0134] Calculating the probability density value corresponding to each of the position data according to the Gaussian distribution estimation model;

[0135] Each probability density value is compared with the abnormal threshold value, and the detection information corresponding to each unit point to be tested is determined based on each comparison result.

[0136] Those skilled in the art will clearly understand that the technical solutions of the embodiments of the present application can be implemented with the help of software and / or hardware. "Unit" and "module" in this specification refer to software and / or hardware that can independently perform or cooperate with other components to perform specific functions, where the hardware can be, for example, a field programmable gate array (FPGA), an integrated circuit (IC), etc.

[0137] Each processing unit and / or module in the embodiments of the present application may be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or may be implemented by software that executes the functions described in the embodiments of the present application.

[0138] See next Figure 3 , Figure 3 A schematic structural diagram of an electronic device provided in an embodiment of this specification is shown.

[0139] like Figure 3 As shown, the electronic device 300 may include: at least one device processor 301 , at least one network interface 303 , a user interface 303 , a memory 305 and at least one communication bus 302 .

[0140] The communication bus 302 may be used to implement the connection and communication between the above components.

[0141] The user interface 303 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0142] The network interface 304 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, and the like.

[0143] Among them, the device processor 301 may include one or more processing cores. The device processor 301 uses various interfaces and lines to connect the various parts of the entire electronic device 300, and executes various functions of the electronic device 300 and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the device processor 301 can be implemented in at least one hardware form of DSP, FPGA, PLA. The device processor 301 can integrate one or a combination of CPU, GPU and modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to handle wireless communications. It is understandable that the above-mentioned modem may not be integrated into the device processor 301, but may be implemented separately through a chip.

[0144] Among them, the memory 305 may include RAM and ROM. Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also be optionally at least one storage device located away from the aforementioned device processor 301. As Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and program instructions.

[0145] Specifically, the device processor 301 may be used to call the real-time position detection application for the wind turbine submarine cable stored in the memory 305 and specifically perform the following operations:

[0146] Acquire angular velocity data of at least two acquisition points in the wind turbine submarine cable based on a three-axis gyroscope, and calculate each of the angular velocity data based on a quaternion update method to obtain attitude data corresponding to each of the acquisition points, wherein each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable;

[0147] Performing interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable;

[0148] Based on the Gaussian distribution estimation method, position detection is performed on each unit point to be tested in the real-time position fitting curve to generate detection information.

[0149] As an optional embodiment of this specification, after obtaining angular velocity data of at least two collection points in the wind turbine submarine cable based on the three-axis gyroscope, the method includes:

[0150] Performing denoising on the angular velocity data based on a Kalman filter algorithm to obtain standard data;

[0151] Performing time alignment on each of the standard data according to a timestamp synchronization method to obtain synchronized data;

[0152] The quaternion update method is used to calculate each of the angular velocity data to obtain the posture data corresponding to each of the acquisition points, including:

[0153] The synchronization data are calculated based on the quaternion update method to obtain the posture data corresponding to each acquisition point.

[0154] As an optional embodiment of this specification, the quaternion update method is used to calculate each of the angular velocity data to obtain the posture data corresponding to each of the acquisition points, including:

[0155] determining the angular velocity change corresponding to each angular velocity data according to an angular velocity integration method;

[0156] The angular velocity changes are calculated based on the quaternion update algorithm to obtain the posture data corresponding to each acquisition point.

[0157] As an optional embodiment of this specification, before performing interpolation curve fitting on each of the posture data to obtain the real-time position fitting curve of the wind turbine submarine cable, the method further includes:

[0158] Determine the attitude transformation matrix between the gyroscope coordinate system and the global coordinate system;

[0159] Convert each of the posture data based on the posture conversion matrix to obtain global coordinate data;

[0160] The interpolation curve fitting is performed on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable, including:

[0161] Interpolation curve fitting is performed on each of the global coordinate data to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0162] As an optional embodiment of this specification, performing interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable includes:

[0163] Performing curve fitting on all the posture data based on the cubic spline interpolation method to obtain an interpolation fitting curve of the wind turbine submarine cable;

[0164] The interpolation fitting curve is physically constrained and checked according to the maximum bending limit of the wind turbine submarine cable to obtain a real-time position fitting curve of the wind turbine submarine cable.

[0165] As an optional embodiment of this specification, the performing position detection on each unit point to be measured in the real-time position fitting curve based on the Gaussian distribution estimation method to generate detection information includes:

[0166] Determining the position data corresponding to each unit point to be tested in the real-time position fitting curve according to a preset unit interval to be tested;

[0167] A Gaussian distribution estimation model is constructed, and position detection is performed on each of the position data according to the Gaussian distribution estimation model to generate detection information.

[0168] As an optional embodiment of this specification, performing position detection on each position data according to the Gaussian distribution estimation model to generate detection information includes:

[0169] Calculating the probability density value corresponding to each of the position data according to the Gaussian distribution estimation model;

[0170] Each probability density value is compared with the abnormal threshold value, and the detection information corresponding to each unit point to be tested is determined based on each comparison result.

[0171] The embodiments of this specification also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above method. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive, a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic or optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0172] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0173] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0174] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0175] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0176] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0177] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0178] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0179] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for real-time position detection of a wind turbine submarine cable, characterized in that: The method comprises: Acquire angular velocity data of at least two acquisition points in the wind turbine submarine cable based on a three-axis gyroscope, and calculate each of the angular velocity data based on a quaternion update method to obtain attitude data corresponding to each of the acquisition points, wherein each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable; Performing interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable; Based on the Gaussian distribution estimation method, position detection is performed on each unit point to be tested in the real-time position fitting curve to generate detection information.

2. The method according to claim 1, characterized in that After obtaining angular velocity data of at least two acquisition points in the wind turbine submarine cable based on the three-axis gyroscope, the method includes: Performing denoising on the angular velocity data based on a Kalman filter algorithm to obtain standard data; Performing time alignment on each of the standard data according to a timestamp synchronization method to obtain synchronized data; The quaternion update method is used to calculate each of the angular velocity data to obtain the posture data corresponding to each of the acquisition points, including: The synchronization data are calculated based on the quaternion update method to obtain the posture data corresponding to each acquisition point.

3. The method according to claim 1, characterized in that The quaternion update method is used to calculate each of the angular velocity data to obtain the posture data corresponding to each of the acquisition points, including: determining the angular velocity change corresponding to each angular velocity data according to an angular velocity integration method; The angular velocity changes are calculated based on the quaternion update algorithm to obtain the posture data corresponding to each acquisition point.

4. The method according to claim 1, wherein Before performing interpolation curve fitting on each of the posture data to obtain the real-time position fitting curve of the wind turbine submarine cable, the method further includes: Determine the attitude transformation matrix between the gyroscope coordinate system and the global coordinate system; Convert each of the posture data based on the posture conversion matrix to obtain global coordinate data; The interpolation curve fitting is performed on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable, including: Interpolation curve fitting is performed on each of the global coordinate data to obtain a real-time position fitting curve of the wind turbine submarine cable.

5. The method according to claim 1, wherein The interpolation curve fitting is performed on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable, including: Performing curve fitting on all the posture data based on the cubic spline interpolation method to obtain an interpolation fitting curve of the wind turbine submarine cable; The interpolation fitting curve is physically constrained and checked according to the maximum bending limit of the wind turbine submarine cable to obtain a real-time position fitting curve of the wind turbine submarine cable.

6. The method according to claim 1, characterized in that The performing position detection on each unit point to be measured in the real-time position fitting curve based on the Gaussian distribution estimation method to generate detection information includes: Determining the position data corresponding to each unit point to be tested in the real-time position fitting curve according to a preset unit interval to be tested; A Gaussian distribution estimation model is constructed, and position detection is performed on each of the position data according to the Gaussian distribution estimation model to generate detection information.

7. The method according to claim 6, characterized in that The performing position detection on each of the position data according to the Gaussian distribution estimation model to generate detection information includes: Calculating the probability density value corresponding to each of the position data according to the Gaussian distribution estimation model; Each probability density value is compared with the abnormal threshold value, and the detection information corresponding to each unit point to be tested is determined based on each comparison result.

8. A real-time position detection device for a wind turbine submarine cable, characterized in that: The device comprises: A calculation module is configured to obtain angular velocity data of at least two acquisition points in the wind turbine submarine cable based on a three-axis gyroscope, and calculate each of the angular velocity data based on a quaternion update method to obtain attitude data corresponding to each of the acquisition points, wherein each of the three-axis gyroscopes is evenly distributed on the central axis of the wind turbine submarine cable; A fitting module, configured to perform interpolation curve fitting on each of the posture data to obtain a real-time position fitting curve of the wind turbine submarine cable; The detection module is used to perform position detection on each unit point to be detected in the real-time position fitting curve based on the Gaussian distribution estimation method to generate detection information.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer-readable storage medium stores instructions, which, when the instructions are executed on a computer or a processor, cause the computer or processor to execute the steps of the method according to any one of claims 1 to 7.

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