BD3 short message transmission method, system, device and medium for power system

Abstract

The present invention provides a BD3 short message transmission method, system, equipment and medium for an electric power system, the method comprising: obtaining an electric power monitoring data signal, and delaying the electric power monitoring data signal to obtain a corresponding monitoring data delay signal; inputting the monitoring data delay signal into an improved LMS filter that optimizes the step size factor by adopting a preset step size factor learning selection algorithm for filtering processing to obtain a corresponding monitoring data noise reduction signal; performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal; according to the Beidou short message protocol, converting the monitoring data digital signal into a corresponding BD3 short message, and transmitting the BD3 short message through Beidou. The present invention can effectively avoid the transmission interference of the complex environment in the electric power system on the message, efficiently and reliably reduce the transmission delay, realize the real-time transmission of the electric power system monitoring data, and thus ensure the safe and stable operation of electric power services such as operation and maintenance control.

Description

Technical Field

[0001] The present invention relates to the technical field of power system data transmission, and in particular to a BD3 short message transmission method, system, computer equipment and storage medium for a power system. Background Art

[0002] With the progress and development of modern society, the power system plays an important role in the development of the national economy, and the safe and stable operation of the power system affects all aspects of people's lives. Among them, the realization of real-time monitoring of power equipment is an effective means to ensure the safe and stable operation of the power system. With the gradual globalization of the Beidou satellite navigation system, the application of Beidou short message communication in the civilian field has been continuously expanded. Short message communication is a unique function of the Beidou satellite navigation system, which can realize point-to-point and multi-point-to-multi-point two-way data transmission, with the advantages of large coverage, no blind spots in communication, and safe and reliable. However, the complex environment in the power system may cause Beidou short message communication to be interfered by noise, resulting in excessive delay in Beidou short message communication information transmission, affecting the real-time transmission of data in the power system, and then affecting the safe and stable operation of power services such as operation and maintenance control.

[0003] At present, most power system communication and data transmission use adaptive filters to eliminate noise interference, but the traditional noise interference suppression method based on the least mean square (LMS) filter cannot simultaneously have a high convergence speed and a small steady-state noise. It cannot really and effectively solve the problem of excessive transmission delay of Beidou short message communication information, and it is difficult to meet the real-time transmission requirements of power system monitoring data.

[0004] Therefore, there is an urgent need for a BD3 short message communication information transmission method for power systems that can effectively avoid the interference of the complex environment within the power system on message transmission, efficiently and reliably reduce transmission delays, and thus effectively ensure the real-time transmission of power system monitoring data. Summary of the invention

[0005] The purpose of the present invention is to provide a BD3 short message transmission method for an electric power system, which delays the electric power monitoring data signal sent by the electric power equipment to Beidou, and then performs efficient and reliable interference noise reduction processing based on the improved LMS filter that optimizes the step factor using the step factor learning selection algorithm, effectively solving the application defects of the existing technology, and can truly realize the real-time transmission of the monitoring data of the electric power system, thereby ensuring the safe and stable operation of electric power services such as operation and maintenance control.

[0006] In order to achieve the above objectives, it is necessary to provide a BD3 short message transmission method, system, computer equipment and storage medium for a power system in response to the above technical problems.

[0007] In a first aspect, an embodiment of the present invention provides a BD3 short message transmission method for a power system, the method comprising the following steps:

[0008] Acquire a power monitoring data signal, and perform delay processing on the power monitoring data signal to obtain a corresponding monitoring data delay signal; the power monitoring data signal includes a power monitoring data modulation signal and a corresponding noise interference signal;

[0009] The monitoring data delay signal is input into the improved LMS filter for filtering to obtain a corresponding monitoring data noise reduction signal; the improved LMS filter is obtained by optimizing the LMS filter step factor by using a preset step factor learning selection algorithm;

[0010] Performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal;

[0011] According to the Beidou short message protocol, the monitoring data digital signal is converted into a corresponding BD3 short message, and the BD3 short message is transmitted through Beidou.

[0012] Furthermore, the step of delaying the power monitoring data signal to obtain a corresponding monitoring data delay signal includes:

[0013] Based on the preset time screening principle, the signal delay time is determined, and according to the signal delay time, the power monitoring data signal is delayed to obtain the monitoring data delay signal; the monitoring data delay signal is expressed as:

[0014] x'(nT)=[x(nT),x(nT-1),...,x(nT-M+1)] T

[0015] x(n)=s(n)+e(n)

[0016] Among them, x(n) and x'(nT) represent the power monitoring data signal and the monitoring data delayed signal at the nth sampling moment respectively; s(n) and e(n) represent the power monitoring data modulation signal and the noise interference signal at the nth sampling moment respectively; T represents the signal delay time; M represents the order of the improved LMS filter.

[0017] Furthermore, the preset time length screening principle is that the power monitoring data modulation signal is uncorrelated and the noise interference signal is strongly correlated.

[0018] Furthermore, the step of inputting the monitoring data delay signal into the improved LMS filter for filtering to obtain the corresponding monitoring data noise reduction signal includes:

[0019] Initializing a weight vector of the improved LMS filter according to a data range of the monitoring data delay signal;

[0020] According to the weight vector and the corresponding monitoring data delay signal, a monitoring data output signal is obtained; the monitoring data output signal is expressed as:

[0021] y(n)=w(n)*x′(nT)

[0022] In the formula,

[0023] w(n)=[w 1 (n),w 2 (n),w 3 (n),...,w M (n)]

[0024] Wherein, x'(nT) represents the delayed signal of the monitoring data at the nth sampling moment; w(n) represents the weight vector at the nth sampling moment; T represents the signal delay time; M represents the order of the improved LMS filter;

[0025] Obtaining a signal error according to the monitoring data output signal and the power monitoring data modulation signal;

[0026] The current optimal step factor of the LMS filter is determined by a preset step factor learning selection algorithm, and the weight vector of the improved LMS filter is updated according to the current optimal step factor and the signal error, and the monitoring data delayed signal is filtered according to the updated weight vector of the improved LMS filter to obtain the monitoring data denoised signal.

[0027] Furthermore, the step of determining the current optimal step size factor of the LMS filter by learning and selecting an algorithm based on a preset step size factor comprises:

[0028] By taking the LMS filter as the decision maker and the LMS filter step factor as the rocker, the step factor optimization MAB problem is determined;

[0029] The LMS filter step factor is evenly divided into a preset number of step factor levels within a preset range, and a reward function for the step factor optimization MAB problem is determined according to the signal error of the LMS filter; the reward function is expressed as:

[0030]

[0031] Where θ(n) represents the reward value of the step factor optimization MAB problem at the nth sampling moment; e(n) represents the signal error of the LMS filter;

[0032] Traversing each step factor level to randomly select a step factor, and obtaining a corresponding initial reward value according to the reward function;

[0033] The preference values ​​of each step factor are calculated according to the initial reward value, and the step factor level with the largest preference value is selected; the preference value is expressed as:

[0034]

[0035] in, represents the preference value of the i-th step size factor; k i represents the number of selections of the i-th step size factor; k represents the total number of selections of all step size factors; is the average reward of the step factor level corresponding to the i-th step factor;

[0036] A step size factor is randomly selected within the step size factor level as the current optimal step size factor of the LMS filter.

[0037] Furthermore, the step of performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal includes:

[0038] According to the Beidou short message RDSS2.1 protocol, the monitoring data noise reduction signal is sampled, held, quantized and encoded by an A / D converter to obtain the monitoring data digital signal.

[0039] Further, the step of converting the monitoring data digital signal into a corresponding BD3 short message according to the Beidou short message protocol, and transmitting the BD3 short message through Beidou includes:

[0040] According to the ASCII code protocol, the monitoring data digital signal is converted into corresponding string data through modelsim software;

[0041] According to the Beidou short message protocol, the string data is integrated into a corresponding BD3 short message;

[0042] The BD3 short message is sent to BeiDou, and data is forwarded through BeiDou.

[0043] In a second aspect, an embodiment of the present invention provides a BD3 short message transmission system for a power system, the system comprising:

[0044] A delay processing module, used to obtain a power monitoring data signal, and perform delay processing on the power monitoring data signal to obtain a corresponding monitoring data delay signal; the power monitoring data signal includes a power monitoring data modulation signal and a corresponding noise interference signal;

[0045] A filtering processing module, used for inputting the monitoring data delay signal into an improved LMS filter for filtering processing to obtain a corresponding monitoring data noise reduction signal; the improved LMS filter is obtained by optimizing the LMS filter step factor by adopting a preset step factor learning selection algorithm;

[0046] A signal conversion module, used for performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal;

[0047] The message generation module is used to convert the monitoring data digital signal into a corresponding BD3 short message according to the Beidou short message protocol, and transmit the BD3 short message through Beidou.

[0048] In a third aspect, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0049] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0050] The above application provides a BD3 short message transmission method, system, computer equipment and storage medium for an electric power system. Through the method, it is realized to obtain the electric power monitoring data signal, delay the electric power monitoring data signal, obtain the corresponding monitoring data delay signal, and input the monitoring data delay signal into the improved LMS filter that optimizes the step factor by adopting the preset step factor learning selection algorithm for filtering processing, and after obtaining the corresponding monitoring data noise reduction signal, the monitoring data noise reduction signal is data processed to obtain the corresponding monitoring data digital signal, and according to the Beidou short message protocol, the monitoring data digital signal is converted into the corresponding BD3 short message, and the BD3 short message is transmitted through Beidou. Technical solution. Compared with the prior art, the BD3 short message transmission method of the electric power system can effectively avoid the interference of the complex environment in the electric power system on the transmission of the message, efficiently and reliably reduce the transmission delay of the short message communication, realize the real-time transmission of the monitoring data of the electric power system, and thus ensure the safe and stable operation of electric power services such as operation and maintenance control. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flow chart of a BD3 short message transmission method of a power system in an embodiment of the present invention;

[0052] Figure 2 1 is a schematic diagram of a filtering process of an improved LMS filter based on a preset step size factor learning selection algorithm in an embodiment of the present invention;

[0053] Figure 3 Schematic diagram of the structure of the BD3 short message transmission system of the power system in an embodiment of the present invention;

[0054] Figure 4 It is a diagram of the internal structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and beneficial effects of the present application clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the embodiments described below are part of the embodiments of the present invention and are only used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The BD3 short message transmission method for the power system provided by the present invention is mainly based on the fact that the existing BD3 short message information transmission method for the power system cannot avoid the interference of the complex environment in the power system on the message, affecting the transmission delay, and the use of the existing LMS filter cannot ensure a high convergence speed and a small steady-state noise while achieving interference elimination, and thus cannot ensure the real-time transmission of the power system monitoring data. A method is proposed for delaying the power monitoring data signal, and then using an LMS filter based on a step factor learning selection algorithm to optimize and improve the filtering process to perform noise reduction filtering on the delayed signal, and a technical solution is generated based on the Beidou short message protocol for Beidou transmission, thereby truly realizing the real-time transmission of the power system monitoring data; the following embodiments will explain in detail the BD3 short message transmission method for the power system of the present invention.

[0057] In one embodiment, Figure 1 As shown, a BD3 short message transmission method for a power system is provided, comprising the following steps:

[0058] S11, obtaining a power monitoring data signal, and delaying the power monitoring data signal to obtain a corresponding monitoring data delay signal; wherein the power monitoring data signal can be understood as a power system monitoring signal that the power equipment needs to send to Beidou for transmission. Considering the interference of the complex environment in the power system on the message, the power system monitoring signal is represented as a data signal including a power monitoring data modulation signal and a corresponding noise interference signal, wherein the power monitoring data modulation signal is a useful signal;

[0059] Delay processing can be understood as a data processing method in which the useful signals (power monitoring data modulation signals) in the power monitoring data signal are uncorrelated with each other and the corresponding noise interference signals have good correlation by selecting a suitable delay time; specifically, the step of delaying the power monitoring data signal to obtain the corresponding monitoring data delay signal includes:

[0060] Based on the preset time length screening principle, the signal delay time length is determined, and according to the signal delay time length, the power monitoring data signal is delayed to obtain the monitoring data delayed signal; wherein, the preset time length screening principle is that the power monitoring data modulation signal is uncorrelated and the noise interference signal is strongly correlated, and the corresponding monitoring data delayed signal is expressed as:

[0061] x'(nT)=[x(nT),x(nT-1),...,x(nT-M+1)] T

[0062] x(n)=s(n)+e(n)

[0063] Wherein, x(n) and x'(nT) represent the power monitoring data signal and the monitoring data delay signal at the nth sampling moment respectively; s(n) and e(n) represent the power monitoring data modulation signal and the noise interference signal at the nth sampling moment respectively; T represents the signal delay time; M represents the order of the improved LMS filter;

[0064] It should be noted that the above-mentioned power monitoring data modulation signal s(n) and noise interference signal e(n) are statistically independent of each other, and according to their respective characteristics, s(n) is a weakly correlated signal and e(n) is an Alpha stable distributed noise; x(nT), x(nT-1) and x(nT-M+1) in the monitoring data delay signal x'(nT) respectively represent the Mth data, M-1th data and 1st data before the nth sampling moment.

[0065] S12, inputting the monitoring data delay signal into the improved LMS filter for filtering processing to obtain the corresponding monitoring data noise reduction signal; the improved LMS filter is obtained by optimizing the LMS filter step factor by adopting a preset step factor learning selection algorithm, which can be understood as the improved LMS filter determines the optimal step factor based on the preset step factor learning selection algorithm to filter and reduce the noise of the input monitoring data delay signal;

[0066] Specifically, the step of inputting the monitoring data delay signal into the improved LMS filter for filtering to obtain the corresponding monitoring data noise reduction signal includes:

[0067] Initialize the weight vector of the improved LMS filter according to the data range of the monitoring data delay signal; wherein the initialization of the weight vector of the improved LMS filter can be understood as averaging the data range of the monitoring data delay signal (i.e., the order of the improved LMS filter), and the corresponding initial weight vector is w(1)=[w 1 (1),w 2 (1),w 3 (1),...,w M (1)], and w i (1) = 1 / M, which will be updated and used later based on the optimal step size factor corresponding to each sampling moment determined by the preset step size factor learning selection algorithm;

[0068] According to the weight vector and the corresponding monitoring data delay signal, a monitoring data output signal is obtained; the monitoring data output signal is expressed as:

[0069] y(n)=w(n)*x′(nT)

[0070] In the formula,

[0071] w(n)=[w 1 (n),w 2 (n),w 3 (n),...,w M (n)]

[0072] Wherein, x'(nT) represents the delayed signal of the monitoring data at the nth sampling moment; w(n) represents the weight vector at the nth sampling moment; T represents the signal delay time; M represents the order of the improved LMS filter;

[0073] According to the monitoring data output signal and the power monitoring data modulation signal, a signal error is obtained; wherein the signal error is expressed as:

[0074] E a (n) = s(n) - y(n)

[0075] Among them, E a (n) represents the signal error; s(n) and y(n) represent the power monitoring data modulation signal and the corresponding monitoring data output signal respectively;

[0076] Determine the current optimal step factor of the LMS filter by a preset step factor learning selection algorithm, and update the weight vector of the improved LMS filter according to the current optimal step factor and the signal error, and filter the monitoring data delay signal according to the updated weight vector of the improved LMS filter to obtain the monitoring data noise reduction signal;

[0077] like Figure 2 As shown, the step of determining the current optimal step factor of the LMS filter by learning and selecting the algorithm through the preset step factor includes:

[0078] By taking the LMS filter as the decision maker and the LMS filter step factor as the rocker, the step factor optimization MAB problem is determined;

[0079] The LMS filter step factor is evenly divided into a preset number of step factor levels within a preset range, and a reward function for the step factor optimization MAB problem is determined according to the signal error of the LMS filter; the reward function is expressed as:

[0080]

[0081] Where θ(n) represents the reward value of the step factor optimization MAB problem at the nth sampling moment; e(n) represents the signal error of the LMS filter;

[0082] Traversing each step factor level to randomly select a step factor, and obtaining a corresponding initial reward value according to the reward function;

[0083] The preference values ​​of each step factor are calculated according to the initial reward value, and the step factor level with the largest preference value is selected; the preference value is expressed as:

[0084]

[0085] in, represents the preference value of the i-th step size factor; k i represents the number of selections of the i-th step size factor; k represents the total number of selections of all step size factors; is the average reward of the step factor level corresponding to the i-th step factor;

[0086] A step factor is randomly selected within the step factor level as the current optimal step factor of the LMS filter:

[0087] It should be noted that the preset range of the step factor of the above-mentioned LMS filter and the corresponding step factor level division can be selected and set according to actual application requirements. In this embodiment, the preset range is preferably determined as [0, 0.2] based on historical experience, and the preset range is evenly divided into 5 levels: the first level is [0, 0.04], the second level is [0.04, 0.08], the third level is [0.08, 0.12], the fourth level is [0.12, 0.16], and the fifth level is [0.16, 0.2]. That is, there are 5 rocker arms. By evenly dividing the step factor into five ranges, local convergence caused by excessive step selection can be avoided, and since the number of step factors at each level is moderate, the calculation speed can be effectively reduced to improve the optimization efficiency.

[0088] The specific process of executing the above-mentioned preset step factor learning selection algorithm can be understood as follows: initialize the number of selections of each step factor to 0, and when the number of selections t<5 (the preset number of selections threshold), traverse and select each step factor level and randomly select a step factor value within the range and obtain the initial reward value according to the defined reward function; after obtaining the initial reward value, calculate the preference value of each step factor, and according to the obtained preference value, select the step factor level with the maximum preference value, and randomly select a value within the range as the optimal step factor used in the current filtering and denoising processing of the improved LMS filter for reducing data transmission delay; update the weight vector of the improved LMS filter according to the obtained current optimal step factor, recalculate the power monitoring data output signal, obtain the required monitoring data denoising signal, and update the signal error, reward value and the number of selections of each rocker arm of the signal at the next moment, and realize the adaptive update of the preference value by balancing the relationship between the reward, the number of selections and the step factor, so as to select the optimal step factor for filtering processing at subsequent moments.

[0089] This embodiment inputs the monitoring data delay signal into a pre-built improved LMS filter to eliminate noise interference, and uses a preset step factor learning selection algorithm to optimize the improved filtering process. While improving its convergence speed, it can also ensure a smaller steady-state noise, thereby achieving efficient and reliable interference elimination of power monitoring data information, effectively reducing the transmission delay of power system monitoring data, and ensuring the real-time transmission of monitoring data.

[0090] S13, performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal; wherein the data processing can be understood as signal conversion processing, and the corresponding monitoring data digital signal contains the power monitoring data to be transmitted in the power system; specifically, the step of performing data processing on the monitoring data noise reduction signal to obtain the corresponding monitoring data digital signal includes:

[0091] According to the Beidou short message RDSS2.1 protocol, the monitoring data noise reduction signal is sampled, held, quantized and encoded by an A / D converter to obtain the monitoring data digital signal.

[0092] S14, according to the Beidou short message protocol, converting the monitoring data digital signal into a corresponding BD3 short message, and transmitting the BD3 short message through Beidou; wherein the generation process of the BD3 short message includes two processing processes of first converting the monitoring data digital signal into a corresponding character string, and then encoding the obtained character string into a corresponding power monitoring data short message based on the Beidou short message protocol. Specifically, according to the Beidou short message protocol, converting the monitoring data digital signal into a corresponding BD3 short message, and transmitting the BD3 short message through Beidou includes:

[0093] According to the ASCII code protocol, the monitoring data digital signal is converted into corresponding string data through modelsim software;

[0094] According to the Beidou short message protocol, the string data is integrated into a corresponding BD3 short message;

[0095] The BD3 short message is sent to BeiDou, and data is forwarded through BeiDou.

[0096] The embodiment of the present application obtains an effective monitoring data noise reduction signal by inputting the monitoring data delay signal obtained by delaying the power monitoring data signal into an improved LMS filter that optimizes the step factor by adopting a preset step factor learning selection algorithm for efficient and reliable filtering processing, and then obtains a corresponding monitoring data digital signal by data processing, and converts the monitoring data digital signal into a corresponding BD3 short message according to the Beidou short message protocol and transmits it through Beidou. The method effectively solves the application defects of the prior art, can not only effectively avoid the interference of the complex environment in the power system on the message transmission, but also can efficiently and reliably reduce the transmission delay of short message communication, truly realize the real-time transmission of power system monitoring data, and thus ensure the safe and stable operation of power services such as operation and maintenance control.

[0097] In one embodiment, Figure 3 As shown, a BD3 short message transmission system of a power system is provided, and the system includes:

[0098] The delay processing module 1 is used to obtain a power monitoring data signal and perform delay processing on the power monitoring data signal to obtain a corresponding monitoring data delay signal; the power monitoring data signal includes a power monitoring data modulation signal and a corresponding noise interference signal;

[0099] Filter processing module 2, used for inputting the monitoring data delay signal into the improved LMS filter for filtering processing to obtain the corresponding monitoring data noise reduction signal; the improved LMS filter is obtained by optimizing the LMS filter step factor by adopting a preset step factor learning selection algorithm;

[0100] The signal conversion module 3 is used to perform data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal;

[0101] The message generation module 4 is used to convert the monitoring data digital signal into a corresponding BD3 short message according to the Beidou short message protocol, and transmit the BD3 short message through Beidou.

[0102] For the specific definition of a BD3 short message transmission system for an electric power system, please refer to the definition of a BD3 short message transmission method for an electric power system mentioned above, which will not be repeated here. Each module in the above-mentioned BD3 short message transmission system for an electric power system can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0103] Figure 4 FIG. 1 shows an internal structure diagram of a computer device in an embodiment, and the computer device may specifically be a terminal or a server. Figure 4 As shown, the computer device includes a processor, a memory, a network interface, a display and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a BD3 short message transmission method for a power system is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0104] It can be understood by those skilled in the art that Figure 4The structure shown in the figure is only a block diagram of a part of the structure related to the present application scheme, and does not constitute a limitation on the computer device to which the present application scheme is applied. The specific computing device may include more or fewer components than shown in the figure, or combine certain components, or have the same component arrangement.

[0105] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the above method are implemented when the processor executes the computer program.

[0106] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0107] In summary, the embodiments of the present invention provide a BD3 short message transmission method, system, computer equipment and storage medium for an electric power system. The BD3 short message transmission method for the electric power system realizes the acquisition of the electric power monitoring data signal, and delays the electric power monitoring data signal to obtain the corresponding monitoring data delay signal, and inputs the monitoring data delay signal into the improved LMS filter that optimizes the step factor by adopting a preset step factor learning selection algorithm for filtering processing, and after obtaining the corresponding monitoring data noise reduction signal, the monitoring data noise reduction signal is data processed to obtain the corresponding monitoring data digital signal, and according to the Beidou short message protocol, the monitoring data digital signal is converted into the corresponding BD3 short message, and the BD3 short message is transmitted through Beidou. The method delays the electric power monitoring data signal, and then performs efficient and reliable interference noise reduction processing based on the improved LMS filter that optimizes the step factor by using a step factor learning selection algorithm. It can not only effectively avoid the interference of the complex environment in the power system on the transmission of the message, but also reduce the transmission delay of the short message communication, truly realize the real-time transmission of the monitoring data of the power system, and thus ensure the safe and stable operation of power services such as operation and maintenance control.

[0108] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0109] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A BD3 short message transmission method for a power system, It is characterized in that The method comprises the following steps: Acquire a power monitoring data signal, and perform delay processing on the power monitoring data signal to obtain a corresponding monitoring data delay signal; the power monitoring data signal includes a power monitoring data modulation signal and a corresponding noise interference signal; The monitoring data delay signal is input into the improved LMS filter for filtering to obtain a corresponding monitoring data noise reduction signal; the improved LMS filter is obtained by optimizing the LMS filter step factor by using a preset step factor learning selection algorithm; Performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal; According to the Beidou short message protocol, the monitoring data digital signal is converted into a corresponding BD3 short message, and the BD3 short message is transmitted through Beidou; The steps of optimizing the LMS filter step factor by using a preset step factor learning selection algorithm include: By taking the LMS filter as the decision maker and the LMS filter step factor as the rocker, the step factor optimization MAB problem is determined; The LMS filter step factor is evenly divided into a preset number of step factor levels within a preset range, and a reward function for the step factor optimization MAB problem is determined according to the signal error of the LMS filter; the reward function is expressed as: Where θ(n) represents the reward value of the step factor optimization MAB problem at the nth sampling moment; e(n) represents the signal error of the LMS filter; Traversing each step factor level to randomly select a step factor, and obtaining a corresponding initial reward value according to the reward function; The preference values ​​of each step factor are calculated according to the initial reward value, and the step factor level with the largest preference value is selected; the preference value is expressed as: in, represents the preference value of the i-th step size factor; k i represents the number of selections of the i-th step size factor; k represents the total number of selections of all step size factors; is the average reward of the step factor level corresponding to the i-th step factor; A step size factor is randomly selected within the step size factor level as the current optimal step size factor of the LMS filter.

2. The BD3 short message transmission method of the power system according to claim 1, It is characterized in that The step of delaying the power monitoring data signal to obtain a corresponding monitoring data delay signal comprises: Based on the preset time screening principle, the signal delay time is determined, and according to the signal delay time, the power monitoring data signal is delayed to obtain the monitoring data delay signal; the monitoring data delay signal is expressed as: x′(n-T)=[x(n-T),x(n-T-1),...,x(n-T-M+1)] T x(n)=s(n)+e(n) Among them, x(n) and x′(nT) represent the power monitoring data signal and the monitoring data delayed signal at the nth sampling moment respectively; s(n) and e(n) represent the power monitoring data modulation signal and the noise interference signal at the nth sampling moment respectively; T represents the signal delay time; M represents the order of the improved LMS filter.

3. The BD3 short message transmission method of the power system according to claim 2, It is characterized in that The preset time length screening principle is that the power monitoring data modulation signal is uncorrelated and the noise interference signal is strongly correlated.

4. The BD3 short message transmission method of the power system according to claim 1, It is characterized in that The step of inputting the monitoring data delay signal into the improved LMS filter for filtering to obtain the corresponding monitoring data noise reduction signal comprises: Initializing a weight vector of the improved LMS filter according to a data range of the monitoring data delay signal; According to the weight vector and the corresponding monitoring data delay signal, a monitoring data output signal is obtained; the monitoring data output signal is expressed as: y(n)=w(n)*x′(nT) In the formula, w(n)=[w 1 (n),w 2 (n),w 3 (n),...,w M (n)] Wherein, x′(nT) represents the delayed signal of the monitoring data at the nth sampling moment; w(n) represents the weight vector at the nth sampling moment; T represents the signal delay time; M represents the order of the improved LMS filter; Obtaining a signal error according to the monitoring data output signal and the power monitoring data modulation signal; The current optimal step factor of the LMS filter is determined by a preset step factor learning selection algorithm, and the weight vector of the improved LMS filter is updated according to the current optimal step factor and the signal error, and the monitoring data delayed signal is filtered according to the updated weight vector of the improved LMS filter to obtain the monitoring data denoised signal.

5. The BD3 short message transmission method of the power system according to claim 1, It is characterized in that The step of performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal comprises: According to the Beidou short message RDSS2.1 protocol, the monitoring data noise reduction signal is sampled, held, quantized and encoded in sequence using an A / D converter to obtain the monitoring data digital signal.

6. The BD3 short message transmission method of the power system according to claim 1, It is characterized in that The step of converting the monitoring data digital signal into a corresponding BD3 short message according to the Beidou short message protocol, and transmitting the BD3 short message through Beidou comprises: According to the ASCII code protocol, the monitoring data digital signal is converted into corresponding string data through modelsim software; According to the Beidou short message protocol, the string data is integrated into a corresponding BD3 short message; The BD3 short message is sent to BeiDou, and data is forwarded through BeiDou.

7. A BD3 short message transmission system for power system, It is characterized in that The BD3 short message transmission method of the power system according to claim 1 is executed, and the system comprises: A delay processing module, used to obtain a power monitoring data signal, and perform delay processing on the power monitoring data signal to obtain a corresponding monitoring data delay signal; the power monitoring data signal includes a power monitoring data modulation signal and a corresponding noise interference signal; A filtering processing module, used for inputting the monitoring data delay signal into an improved LMS filter for filtering processing to obtain a corresponding monitoring data noise reduction signal; the improved LMS filter is obtained by optimizing the LMS filter step factor by adopting a preset step factor learning selection algorithm; A signal conversion module, used for performing data processing on the monitoring data noise reduction signal to obtain a corresponding monitoring data digital signal; The message generation module is used to convert the monitoring data digital signal into a corresponding BD3 short message according to the Beidou short message protocol, and transmit the BD3 short message through Beidou.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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