Dehumidifier control method and apparatus for offshore wind turbines

Abstract

The application provides a dehumidifier control method and device for offshore wind turbines, which comprises the following steps: obtaining the indoor humidity of the offshore wind turbine, the sea humidity and the working power of the dehumidifier at multiple time points in a preset time period; arranging the indoor humidity of the offshore wind turbine, the sea humidity and the working power of the dehumidifier according to the time dimension into an indoor humidity input vector, a sea humidity input vector and a power input vector; obtaining a collaborative humidity matrix according to the product of the transposed vector of the indoor humidity input vector and the sea humidity input vector; obtaining a decoding feature matrix according to the collaborative humidity matrix and the power input vector; performing logical regression on the decoding feature matrix to obtain a logical value; and controlling the working power of the dehumidifier based on the logical value. The application adaptively controls the working power of the dehumidifier based on the indoor humidity of the offshore wind turbine and the sea humidity, flexibly adjusts the dehumidification effect, and is more suitable for the actual working environment of various offshore wind turbines.

Description

Technical Field

[0001] This application relates to the field of wind power technology, and in particular to a dehumidifier control method and device for offshore wind turbines. Background Technology

[0002] Offshore wind turbines operate in high-humidity, high-salt environments for extended periods. The internal metal equipment and facilities are highly susceptible to corrosion. Generally, the critical relative humidity for metal corrosion is 45%-50%; exceeding this limit will lead to corrosion. As relative humidity increases, the corrosion rate accelerates, and the corrosion process becomes even more rapid once condensation occurs on the steel. Therefore, dehumidifiers must be installed inside offshore wind turbines to prevent internal corrosion and ensure their normal operation. Summary of the Invention

[0003] This application aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, the first aspect of this application proposes a dehumidifier control method for offshore wind turbines, comprising:

[0005] The system acquires the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period; wherein, the multiple time points include the current time point.

[0006] The indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier are arranged according to the time dimension as indoor humidity input vector, sea surface humidity input vector, and power input vector, respectively.

[0007] The cooperative humidity matrix is ​​obtained by multiplying the transpose of the indoor humidity input vector with the sea surface humidity input vector.

[0008] Based on the cooperative humidity matrix and the power input vector, the decoding feature matrix is ​​obtained;

[0009] Logistic regression is performed on the decoded feature matrix to obtain logical values; wherein, the logical values ​​are used to indicate whether the dehumidifier power value should increase or decrease at the current time point;

[0010] The second aspect of this application discloses a dehumidifier control device for offshore wind turbines, comprising:

[0011] The receiving module is used to acquire the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period; wherein, the multiple time points include the current time point;

[0012] The first processing module is used to arrange the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier according to the time dimension into an indoor humidity input vector, a sea surface humidity input vector, and a power input vector, respectively.

[0013] The second processing module is used to obtain a cooperative humidity matrix based on the product between the transpose of the indoor humidity input vector and the sea surface humidity input vector.

[0014] The third processing module is used to obtain the decoding feature matrix based on the cooperative humidity matrix and the power input vector;

[0015] The logistic regression module is used to perform logistic regression on the decoded feature matrix to obtain a logistic value; wherein the logistic value is used to indicate whether the dehumidifier power value should increase or decrease at the current time point;

[0016] The output module is used to output a dehumidifier power control command based on the logic value.

[0017] A third aspect of this application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the program, it implements the method described in the first aspect above.

[0018] The fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements the method described in the first aspect above.

[0019] According to the dehumidifier control method for offshore wind turbines in the embodiments of this application, considering the different indoor humidity and sea surface humidity of the offshore wind turbines, the humidity change trend characteristics are represented by the synergistic characteristics between the indoor humidity of the offshore wind turbines and the sea surface humidity, thereby adaptively controlling the working power of the dehumidifier, flexibly adjusting the dehumidification effect, making it more suitable for the actual working environment of each offshore wind turbine, improving dehumidification efficiency, and reducing energy waste to a certain extent.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0022] Figure 1 A schematic flowchart illustrating a dehumidifier control method for an offshore wind turbine provided in an embodiment of this application;

[0023] Figure 2 A schematic flowchart illustrating another dehumidifier control method for offshore wind turbines provided in an embodiment of this application;

[0024] Figure 3 A schematic diagram of a dehumidifier control device for an offshore wind turbine provided in an embodiment of this application;

[0025] Figure 4 This is a structural block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0026] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0027] Because the sea surface and the interior of the offshore wind turbine are connected, moisture from the sea surface enters the wind turbine with the sea breeze, increasing the indoor humidity. In related technologies, dehumidifiers in offshore wind turbines mostly operate in a fixed-power mode. However, the humidity levels inside the offshore wind turbine and on the sea surface vary, making fixed-power dehumidification control unsuitable for each wind turbine's operating environment. This can lead to over- or under-dehumidification, resulting in relatively low dehumidification efficiency and unnecessary energy consumption. Therefore, this application proposes a dehumidifier control method and apparatus for offshore wind turbines that adaptively controls the dehumidifier based on both sea surface humidity and indoor humidity within the offshore wind turbine, adjusting the dehumidification effect. Specifically, the following description, with reference to the accompanying drawings, illustrates an embodiment of the dehumidifier control method and apparatus for offshore wind turbines.

[0028] Figure 1 This is a schematic flowchart illustrating a dehumidifier control method for offshore wind turbines provided in an embodiment of this application. Figure 1 As shown, the dehumidifier control method for offshore wind turbines includes the following steps:

[0029] Step 101: Obtain the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period. The multiple time points include the current time point.

[0030] Step 102: Arrange the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier according to the time dimension as indoor humidity input vector, sea surface humidity input vector, and power input vector, respectively.

[0031] Step 103: Obtain the cooperative humidity matrix by multiplying the transpose of the indoor humidity input vector with the sea surface humidity input vector.

[0032] It should be noted that this collaborative humidity matrix is ​​used to represent the characteristics of humidity change trends.

[0033] Step 104: Obtain the decoding feature matrix based on the cooperative humidity matrix and the power input vector.

[0034] One possible implementation is to calculate the transition vector of the cooperative humidity matrix relative to the power input vector, thereby obtaining the decoded feature matrix.

[0035] Step 105: Perform logistic regression on the decoded feature matrix to obtain the logistic value. The logistic value indicates whether the dehumidifier power should increase or decrease at the current time point.

[0036] Step 106: Control the operating power of the dehumidifier based on the logic value.

[0037] According to the dehumidifier control method for offshore wind turbines in the embodiments of this application, considering the different indoor humidity and sea surface humidity of the offshore wind turbines, the humidity change trend characteristics are represented by the synergistic characteristics between the indoor humidity of the offshore wind turbines and the sea surface humidity, thereby adaptively controlling the working power of the dehumidifier, flexibly adjusting the dehumidification effect, making it more suitable for the actual working environment of each offshore wind turbine, improving dehumidification efficiency, and reducing energy waste to a certain extent.

[0038] It should be noted that in some embodiments of this application, matrix inversion operations that are not suitable for logical solutions may be introduced in the process of calculating the transition vector of the cooperative humidity matrix relative to the power input vector. Therefore, in order to avoid this situation as much as possible, this application provides another dehumidifier control method for offshore wind turbines. By using a cooperative constraint method based on switch state control, the transition state between the power input vector and the cooperative operation representation of the indoor humidity of the offshore wind turbine and the sea surface humidity is obtained, thereby improving the accuracy of dehumidifier control. Figure 2 This is a schematic flowchart illustrating another dehumidifier control method for offshore wind turbines provided in an embodiment of this application. Figure 2 As shown, the dehumidifier control method for offshore wind turbines includes the following steps:

[0039] Step 201: Obtain the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period. The multiple time points include the current time point.

[0040] Step 202: Arrange the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier according to the time dimension as indoor humidity input vector, sea surface humidity input vector, and power input vector, respectively.

[0041] Step 203: Obtain the cooperative humidity matrix by multiplying the transpose of the indoor humidity input vector with the sea surface humidity input vector.

[0042] Step 204: Input the cooperative humidity matrix into the switch array to obtain the global cooperative humidity state matrix. The switching control threshold of the switch array is the product of the mean of the indoor humidity input vector at each position and the mean of the sea surface humidity input vector at each position.

[0043] That is, by constructing state transition control lines through hardware circuits (parallel switches), the cooperative humidity matrix is ​​transformed into a global cooperative humidity state matrix with a binary distribution of (0,1). Therefore, by introducing the product of the global time-series average of indoor humidity and sea surface humidity as the switching control threshold of the switch array, the cooperative operation state can be roughly divided into global state and local state.

[0044] Step 205: Input the indoor humidity input vector to the first parallel switch to obtain the indoor humidity state vector. The switching control threshold of the first parallel switch is the average value of the vector values ​​at each position of the indoor humidity input vector.

[0045] The indoor humidity input vector is transformed into an indoor humidity state vector with a binary distribution of (0,1).

[0046] Step 206: Input the sea surface humidity input vector to the second parallel switch to obtain the sea surface humidity state vector. The switching control threshold of the second parallel switch is the average value of the vector values ​​at each position of the sea surface humidity input vector.

[0047] The sea surface humidity input vector is transformed into a (0,1) binary distribution sea surface humidity state vector.

[0048] Step 207: Calculate the positional XOR relationship between the indoor humidity state vector and the sea surface humidity state vector to obtain the local cooperative state matrix.

[0049] Step 208: Calculate the position-based XOR relationship between the global cooperative humidity state matrix and the local cooperative humidity state matrix to obtain the inverse cooperative humidity state matrix.

[0050] Step 209: Perform a dot product between the cooperative humidity matrix and the inverse cooperative humidity state matrix to obtain the inverse cooperative humidity matrix.

[0051] In other words, a switch array is set up with an inverse cooperative humidity state matrix, and the cooperative humidity matrix is ​​passed through the switch array as a constraint condition to constrain each cooperative humidity value in the cooperative humidity matrix. In this way, the inverse cooperative part of indoor humidity and sea surface humidity relative to the global cooperative value is selected from the cooperative humidity matrix to obtain the inverse cooperative humidity matrix.

[0052] Step 210: Obtain the decoding feature matrix based on the inverse cooperative humidity matrix and the power input vector.

[0053] As one possible implementation, the product of the inverse cooperative humidity matrix and the power input vector can be used as the decoding feature matrix.

[0054] Step 211: Perform logistic regression on the decoded feature matrix to obtain logistic values. These logistic values ​​indicate whether the dehumidifier power should increase or decrease at the current time point.

[0055] Step 212: Control the operating power of the dehumidifier based on logic values.

[0056] The dehumidifier control method for offshore wind turbines according to embodiments of this application takes into account the varying indoor humidity and sea surface humidity of the offshore wind turbines. It represents the humidity change trend using the collaborative characteristics between the indoor humidity of the offshore wind turbines and the sea surface humidity. Furthermore, through a collaborative constraint method based on switch-state control, it obtains the transition state between the power input vector and the collaborative operation representation of the indoor humidity of the offshore wind turbines and the sea surface humidity. This allows for adaptive control of the dehumidifier's operating power, flexibly adjusting the dehumidification effect and further improving the accuracy of dehumidifier control. This application is more applicable to the actual working environment of various offshore wind turbines, improving dehumidification efficiency and reducing energy waste to a certain extent.

[0057] Figure 3 This is a schematic diagram of a dehumidifier control device for an offshore wind turbine, provided as an embodiment of this application. The device can be a dedicated programmable controller for the dehumidifier of an offshore wind turbine. Figure 3 As shown, the dehumidifier control device for offshore wind turbines includes: a receiving module 301, a first processing module 302, a second processing module 303, a third processing module 304, a logic regression module 305, and an output module 306. Among them,

[0058] The receiving module 301 is used to acquire the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period. These multiple time points include the current time point. Optionally, the receiving module 301 can be an input interface; after receiving the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier, the input interface can store these data in a memory.

[0059] The first processing module 302 is used to arrange the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier according to the time dimension into an indoor humidity input vector, a sea surface humidity input vector, and a power input vector, respectively.

[0060] The second processing module 303 is used to obtain a cooperative humidity matrix based on the product between the transpose of the indoor humidity input vector and the sea surface humidity input vector.

[0061] The third processing module 304 is used to obtain the decoding feature matrix based on the cooperative humidity matrix and the power input vector.

[0062] In some embodiments of this application, the third processing module 304 is specifically used for: inputting the cooperative humidity matrix into a switch array to obtain a global cooperative humidity state matrix; the switching control threshold of the switch array is the product of the mean value of each position vector of the indoor humidity input vector and the mean value of each position vector of the sea surface humidity input vector; inputting the indoor humidity input vector into a first parallel switch to obtain an indoor humidity state vector; the switching control threshold of the first parallel switch is the mean value of each position vector of the indoor humidity input vector; inputting the sea surface humidity input vector into a second parallel switch to obtain a sea surface humidity state vector; the switching control threshold of the second parallel switch is the mean value of each position vector of the sea surface humidity input vector; and obtaining a decoding feature matrix based on the indoor humidity state vector, the sea surface humidity state vector, the global cooperative humidity state matrix, and the power input vector.

[0063] In some embodiments of this application, the third processing module 304 is further configured to: calculate the positional XOR relationship between the indoor humidity state vector and the sea surface humidity state vector to obtain a local cooperative state matrix; calculate the positional XOR relationship between the global cooperative humidity state matrix and the local cooperative state matrix to obtain an inverse cooperative humidity state matrix; perform a dot product between the cooperative humidity matrix and the inverse cooperative humidity state matrix to obtain an inverse cooperative humidity matrix; and obtain a decoding feature matrix based on the inverse cooperative humidity matrix and the power input vector.

[0064] In some embodiments of this application, the third processing module 304 is further configured to: multiply the inverse cooperative humidity matrix and the power input vector as the decoding feature matrix.

[0065] The logistic regression module 305 is used to perform logistic regression on the decoded feature matrix to obtain logistic values. These logistic values ​​indicate whether the dehumidifier power should increase or decrease at the current time point.

[0066] Optionally, the first processing module 302, the second processing module 303, the third processing module 304, and the logistic regression module 305 can be modules in a central processing unit to process the data received by the receiving module 301.

[0067] Output module 306 is used to output dehumidifier power control commands based on logic values. Optionally, output module 306 can be an output interface.

[0068] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0069] According to the embodiments of this application, the dehumidifier control device for offshore wind turbines takes into account the different indoor humidity and sea surface humidity of the offshore wind turbines. It uses the synergistic characteristics between the indoor humidity of the offshore wind turbines and the sea surface humidity to represent the humidity change trend characteristics, thereby adaptively controlling the dehumidifier's operating power, flexibly adjusting the dehumidification effect, making it more suitable for the actual working environment of various offshore wind turbines, improving dehumidification efficiency, and reducing energy waste to a certain extent.

[0070] To implement the above embodiments, this application also provides a computer device. Figure 4 This is a structural block diagram of a computer device provided in an embodiment of this application. Figure 4 As shown, the computer device 400 may include a memory 401, a processor 402, and a computer program 403 stored in the memory 401 and executable on the processor 402. When the processor 402 executes the computer program 403, it executes the dehumidifier control method for offshore wind turbines described in any of the above embodiments of this application.

[0071] To implement the above embodiments, this application also proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the dehumidifier control method for offshore wind turbines described in any of the above embodiments of this application.

[0072] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0073] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0074] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0075] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0076] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0077] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A dehumidifier control method for offshore wind turbines, characterized in that, Includes the following steps: The system acquires the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period; wherein, the multiple time points include the current time point. The indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier are arranged according to the time dimension as indoor humidity input vector, sea surface humidity input vector, and power input vector, respectively. The cooperative humidity matrix is ​​obtained by multiplying the transpose of the indoor humidity input vector with the sea surface humidity input vector. Based on the cooperative humidity matrix and the power input vector, the decoding feature matrix is ​​obtained; Logistic regression is performed on the decoded feature matrix to obtain logical values; wherein, the logical values ​​are used to indicate whether the dehumidifier power value should increase or decrease at the current time point; The operating power of the dehumidifier is controlled based on the logic value. The step of obtaining the decoding feature matrix based on the cooperative humidity matrix and the power input vector includes: The cooperative humidity matrix is ​​input to the switch array to obtain the global cooperative humidity state matrix; the switching control threshold of the switch array is the product of the mean of the vector values ​​at each position of the indoor humidity input vector and the mean of the vector values ​​at each position of the sea surface humidity input vector. The indoor humidity input vector is input to the first parallel switch to obtain the indoor humidity state vector; the switching control threshold of the first parallel switch is the average value of the vector values ​​at each position of the indoor humidity input vector. The sea surface humidity input vector is input to a second parallel switch to obtain a sea surface humidity state vector; the switching control threshold of the second parallel switch is the average value of the vector values ​​at each position of the sea surface humidity input vector. The decoding feature matrix is ​​obtained based on the indoor humidity state vector, the sea surface humidity state vector, the global cooperative humidity state matrix, and the power input vector. The step of obtaining the decoding feature matrix based on the indoor humidity state vector, the sea surface humidity state vector, the global cooperative humidity state matrix, and the power input vector includes: Calculate the positional XOR relationship between the indoor humidity state vector and the sea surface humidity state vector to obtain a local cooperative state matrix; Calculate the position-wise XOR relationship between the global cooperative humidity state matrix and the local cooperative humidity state matrix to obtain the inverse cooperative humidity state matrix; The inverse cooperative humidity matrix is ​​obtained by multiplying the cooperative humidity matrix by the inverse cooperative humidity state matrix. The decoding feature matrix is ​​obtained based on the inverse cooperative humidity matrix and the power input vector; The step of obtaining the decoding feature matrix based on the inverse cooperative humidity matrix and the power input vector includes: The product of the inverse cooperative humidity matrix and the power input vector is used as the decoding feature matrix.

2. A dehumidifier control device for offshore wind turbines, characterized in that, include: The receiving module is used to acquire the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier at multiple time points within a preset time period; wherein, the multiple time points include the current time point; The first processing module is used to arrange the indoor humidity of the offshore wind turbine, the sea surface humidity, and the operating power of the dehumidifier according to the time dimension into an indoor humidity input vector, a sea surface humidity input vector, and a power input vector, respectively. The second processing module is used to obtain a cooperative humidity matrix based on the product between the transpose of the indoor humidity input vector and the sea surface humidity input vector. The third processing module is used to obtain the decoding feature matrix based on the cooperative humidity matrix and the power input vector; The logistic regression module is used to perform logistic regression on the decoded feature matrix to obtain a logistic value; wherein the logistic value is used to indicate whether the dehumidifier power value should increase or decrease at the current time point; The output module is used to output a dehumidifier power control command based on the logic value; The third processing module is specifically used for: The cooperative humidity matrix is ​​input to the switch array to obtain the global cooperative humidity state matrix; the switching control threshold of the switch array is the product of the mean of the vector values ​​at each position of the indoor humidity input vector and the mean of the vector values ​​at each position of the sea surface humidity input vector. The indoor humidity input vector is input to the first parallel switch to obtain the indoor humidity state vector; the switching control threshold of the first parallel switch is the average value of the vector values ​​at each position of the indoor humidity input vector. The sea surface humidity input vector is input to a second parallel switch to obtain a sea surface humidity state vector; the switching control threshold of the second parallel switch is the average value of the vector values ​​at each position of the sea surface humidity input vector. The decoding feature matrix is ​​obtained based on the indoor humidity state vector, the sea surface humidity state vector, the global cooperative humidity state matrix, and the power input vector. The third processing module is also used for: Calculate the positional XOR relationship between the indoor humidity state vector and the sea surface humidity state vector to obtain a local cooperative state matrix; Calculate the position-wise XOR relationship between the global cooperative humidity state matrix and the local cooperative humidity state matrix to obtain the inverse cooperative humidity state matrix; The inverse cooperative humidity matrix is ​​obtained by multiplying the cooperative humidity matrix by the inverse cooperative humidity state matrix. The decoding feature matrix is ​​obtained based on the inverse cooperative humidity matrix and the power input vector; The third processing module is also used for: The product of the inverse cooperative humidity matrix and the power input vector is used as the decoding feature matrix.

3. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in claim 1.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in claim 1.

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