Small hydropower station data transmission method and system

Abstract

The invention discloses a small hydropower station data transmission method and system, and the method comprises the steps: obtaining first target data, and carrying out the first preprocessing of the first target data, and obtaining second target data; presetting a first signal transmission model, and setting to-be-optimized parameters of the first signal transmission model; optimizing the to-be-optimized parameters of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model; and transmitting the second target data according to the second signal transmission model. Through the combination of an optimization algorithm and a signal transmission model, the stability and efficiency of data transmission are effectively improved, and the method is especially prominent in remote small hydropower stations with complex terrains and weak signals. Signal transmission parameters can be automatically adjusted according to the specific environment and requirements of the small hydropower station, and the reliability of data transmission is ensured. The intelligent management level of the small hydropower station is improved, and powerful technical support is provided for stable operation and operation and maintenance efficiency of the power station.

Description

Technical Field

[0001] The present invention relates to the technical field of small hydropower data transmission, and in particular to a small hydropower data transmission method and system. Background Art

[0002] With the development of the small hydropower industry, the demand for its intelligent management is growing. During the intelligent inspection of small hydropower stations, a large amount of picture and video data needs to be transmitted in real time to timely detect equipment failures and safety hazards and ensure the stable operation of the power station. However, remote small hydropower stations are usually located in areas with complex geographical environments and weak communication infrastructure, facing serious signal problems, which makes it difficult for traditional communication methods to meet the requirements of data transmission.

[0003] Traditional single base station coverage or simple signal enhancement methods are not effective in remote small hydropower areas. Due to factors such as undulating mountain terrain, building obstruction, and long distance from the base station, the signal is prone to attenuation, interruption, and interference, resulting in data transmission delays, interruptions, or serious degradation of image quality. For example, in some small hydropower stations in mountainous areas, relying only on signals from nearby base stations, the high-definition pictures and videos collected by inspection equipment often cannot be smoothly transmitted to the monitoring center, which seriously affects the development of intelligent inspection work and the operation and maintenance efficiency of the power station.

[0004] In addition, some existing data transmission systems lack targeted optimization when dealing with the complex environment of small hydropower. For example, the antenna layout is unreasonable and cannot provide effective coverage based on the characteristics of the small hydropower area; the signal processing technology is single and cannot effectively resist multipath fading and interference; the data cache and transmission control mechanism is imperfect, and data loss is prone to occur when the signal is unstable. These all urgently require a data transmission solution specifically for remote small hydropower to improve the stability, efficiency and reliability of data transmission. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the present invention provides a small hydropower data transmission method and system, which can solve the problems mentioned in the background technology.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides a small hydropower data transmission method, comprising:

[0010] Acquire first target data, and perform first preprocessing on the first target data to obtain second target data;

[0011] Presetting a first signal transmission model, and setting parameters to be optimized of the first signal transmission model;

[0012] Optimizing the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model;

[0013] The second target data is transmitted according to the second signal transmission model.

[0014] As a preferred solution of the small hydropower data transmission method of the present invention, the first signal transmission model includes:

[0015] The first signal transmission model includes a first objective function and a first constraint condition set;

[0016] The first objective function is an arbitrary function used to represent the transmission characteristics of the first signal;

[0017] The first constraint condition set includes at least any constraints on the first signal transmission characteristics.

[0018] As a preferred solution of the small hydropower data transmission method of the present invention, the first optimization algorithm includes:

[0019] The first optimization algorithm is any model that can optimize the parameters to be optimized of the first signal transmission model;

[0020] The parameter to be optimized is any parameter related to the first signal transmission characteristic.

[0021] As a preferred solution of the small hydropower data transmission method described in the present invention, wherein: the first signal transmission characteristics at least include transmission loss, transmission distance and transmission signal strength.

[0022] As a preferred solution of the small hydropower data transmission method described in the present invention, wherein: the first objective function at least includes determining the actual area occupied by the small hydropower station, determining the coverage radius of the antenna in the small hydropower environment, determining the antenna node controller allocation loss, determining the gain of each antenna node and determining the number of antennas.

[0023] As a preferred solution of the small hydropower data transmission method described in the present invention, wherein: the first constraint condition set includes signal coverage constraint and signal strength constraint.

[0024] As a preferred solution of the small hydropower data transmission method of the present invention, wherein: the variable of the first objective function is set to the number of antennas:

[0025] The parameters to be optimized of the first signal transmission model are optimized according to a first optimization algorithm to obtain a second signal transmission model.

[0026] In a second aspect, the present invention provides a small hydropower data transmission system, comprising:

[0027] A data processing module, used for acquiring first target data, and performing first preprocessing on the first target data to obtain second target data;

[0028] A model building module, used to preset a first signal transmission model and set parameters to be optimized of the first signal transmission model;

[0029] A model optimization module, configured to optimize the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model;

[0030] A transmission module is used to transmit the second target data according to the second signal transmission model.

[0031] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0032] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described above when executed by a processor.

[0033] Compared with the prior art, the invention has the following beneficial effects: the invention proposes a small hydropower data transmission method and system, obtains first target data, performs first preprocessing on the first target data, and obtains second target data; presets a first signal transmission model, and sets the parameters to be optimized of the first signal transmission model; optimizes the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model; and transmits the second target data according to the second signal transmission model. By combining the optimization algorithm and the signal transmission model, the stability and efficiency of data transmission are effectively improved, especially in remote small hydropower stations with complex terrain and weak signals. The signal transmission parameters can be automatically adjusted according to the specific environment and needs of the small hydropower station to ensure the reliability of data transmission. Advanced signal processing technology is adopted to effectively resist multipath fading and interference, reduce data loss, and improve transmission quality. Through reasonable antenna layout and optimization of coverage radius, effective coverage of the small hydropower station area is achieved, ensuring that the monitoring center can receive clear pictures and video data. It not only improves the intelligent management level of small hydropower stations, but also provides strong technical support for the stable operation and operation and maintenance efficiency of power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0035] Figure 1 A method flow chart of a small hydropower data transmission method and system provided by an embodiment of the present invention;

[0036] Figure 2 An internal structural diagram of a computer device of a small hydropower data transmission method and system provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0038] Example 1

[0039] Reference Figure 1-Figure 2, which is the first embodiment of the present invention, and provides a small hydropower data transmission method and system, including:

[0040] There are some problems in the existing related technologies. For example, the real-time and accuracy of data transmission are often affected by environmental factors such as weather conditions, equipment aging or failure, etc. In addition, traditional data transmission systems may lack sufficient security measures and are vulnerable to external attacks, resulting in data leakage or tampering.

[0041] This application provides a method that can effectively solve the above-mentioned problems. Next, how to implement the small hydropower data transmission method will be described in detail in combination with multiple embodiments;

[0042] Figure 1 A method flow chart of a small hydropower data transmission method and system is shown, including:

[0043] S101, acquiring first target data, and performing first preprocessing on the first target data to obtain second target data;

[0044] In an optional embodiment, the first target data may be operating parameter data collected after the intelligent inspection equipment of the target small hydropower station is started, according to the preset inspection path planning and time interval setting, such as key indicators such as water level, flow, power generation, equipment temperature, etc.

[0045] In an optional embodiment, the first target data may also be image and video data of equipment, facilities and surrounding environment in the target small hydropower station;

[0046] In an optional embodiment, the second target data is pre-processed data, which may include data format conversion, noise filtering, outlier removal, etc., to ensure the accuracy and reliability of the data.

[0047] In an optional embodiment, the first target data can be realized by setting a data acquisition unit, wherein the data acquisition unit at least includes a high-resolution camera and a video acquisition card;

[0048] In the embodiment of the present application, after the intelligent inspection equipment of the small hydropower station is started, data collection is started according to the preset inspection path planning and time interval setting. It is set to inspect a specific area once every 10 minutes, and each collection time is 5 minutes, and the collection frequency is (f). The high-resolution camera captures the optical image information of the inspection area and converts it into an analog electrical signal.

[0049] In the embodiment of the present application, the analog-to-digital converter (ADC) in the video capture card converts the analog electrical signal from the camera into a digital signal. The conversion process follows the sampling theorem, and the sampling frequency is usually twice the highest frequency of the signal to ensure that the digital signal can accurately restore the information of the analog signal.

[0050] In the embodiment of the present application, a median filtering algorithm is used to process the converted digital signal to improve the data quality. Assume that the signal-to-noise ratio of the signal before processing is (SNR in ), after preliminary processing, the signal-to-noise ratio is improved to (SNR out ), the improvement of signal-to-noise ratio can be calculated by the formula, (SNR improvement =SNR out -SNR in )(unit: decibel).

[0051] It should be noted that obtaining the first target data and performing the first preprocessing on the first target data to obtain the second target data improves the accuracy and reliability of the data, because the preprocessing can remove noise and irrelevant data, ensuring the accuracy of subsequent analysis and processing. Reduce the complexity and amount of calculation of data processing, because the preprocessed data is more concise and convenient for further analysis and processing. Provide convenience for data storage and transmission, because the preprocessed data is usually smaller in size, easy to store and quickly transmit. Provide clearer signals for subsequent data analysis and mining, which helps to improve the quality and efficiency of analysis results.

[0052] S102, presetting a first signal transmission model, and setting parameters to be optimized of the first signal transmission model;

[0053] In an embodiment of the present application, the first signal transmission model includes:

[0054] The first signal transmission model includes a first objective function and a first constraint condition set;

[0055] The first objective function is an arbitrary function used to represent the transmission characteristics of the first signal;

[0056] The first constraint condition set includes at least any constraints on the first signal transmission characteristics.

[0057] In an optional embodiment, the first signal transmission model can be implemented by an algorithm based on machine learning, which can automatically adjust the parameters to be optimized according to historical data to adapt to different signal transmission environments and conditions.

[0058] In another optional embodiment, the first signal transmission model may include a neural network structure that can learn and simulate various characteristics and changes of the signal during the transmission process. Through training, the model can identify the key factors affecting the signal quality and optimize these factors to improve the efficiency and reliability of signal transmission. In addition, the model can also integrate a feedback mechanism to monitor the signal transmission status in real time and dynamically adjust the transmission strategy based on the monitoring results to cope with environmental changes or system performance fluctuations.

[0059] In an optional embodiment, the first signal transmission model can further improve the transmission quality of the signal by integrating advanced signal processing technology. For example, the system can use orthogonal frequency division multiplexing (OFDM) technology to improve spectrum efficiency and reduce interference caused by multipath effects.

[0060] In an optional embodiment, the first signal transmission model may include an adaptive modulation and coding (AMC) mechanism through the system to dynamically select the most appropriate modulation and coding scheme according to channel conditions to optimize data transmission rate and reliability.

[0061] In an optional embodiment, the first signal transmission model can also utilize multiple input multiple output (MIMO) technology through the system to increase the capacity and coverage of data transmission through multiple transmitting and receiving antennas. The combination of these technologies enables the small hydropower data transmission system to adapt to complex environmental changes and ensure the stability and efficiency of data transmission.

[0062] In the embodiment of the present application, a distributed antenna system is used as the first signal transmission model, wherein the first objective function and the first constraint condition set are the objective function and constraint conditions for the distributed antenna system;

[0063] In an optional embodiment, the first objective function can be set to minimize the total power consumption during signal transmission while meeting certain data transmission rate requirements. To achieve this goal, the system can use a power control algorithm to dynamically adjust the transmission power of each distributed antenna unit.

[0064] In an optional embodiment, the first set of constraints may include signal quality standards, spectrum resource restrictions, and device power restrictions, etc., to ensure that the system operates in an optimal or near-optimal state while meeting performance indicators.

[0065] In an optional embodiment, a distributed antenna system is used as a signal transmission model. The distributed antenna system can achieve uniform coverage and enhancement of signals through the coordinated operation of multiple antenna units. Each antenna unit is connected to a signal processing and transmission unit, which is responsible for receiving, processing and forwarding signals. The signal processing and transmission unit uses advanced signal processing algorithms to optimize the transmission quality of the signal, reduce interference, and improve the overall performance of the system.

[0066] In another optional embodiment, the distributed antenna system can also automatically adjust the antenna configuration according to environmental changes to adapt to different transmission conditions, thereby ensuring the continuity and reliability of data transmission.

[0067] In an embodiment of the present application, the first objective function includes at least determining the actual footprint of the small hydropower station, determining the coverage radius of the antenna in the small hydropower environment, determining the antenna node controller allocation loss, determining the gain of each antenna node, and determining the number of antennas.

[0068] In an embodiment of the present application, the first constraint condition set includes a signal coverage constraint and a signal strength constraint.

[0069] In the embodiment of the present application, the variable of the first objective function is set to the number of antennas:

[0070] The parameters to be optimized of the first signal transmission model are optimized according to a first optimization algorithm to obtain a second signal transmission model.

[0071] In the embodiment of the present application, the signal source module of the distributed antenna system establishes a connection with the external communication network to receive a weak original communication signal. The actual architecture of the distributed antenna system may be as follows:

[0072] In an optional embodiment, the input signal can be amplified by a low noise amplifier (LNA), and its gain is set to (G LNA )(unit: decibel), then the amplified signal power Among them (P in ) is the input signal power.

[0073] In an optional embodiment, the amplified signal can be filtered by a filter to remove out-of-band noise and interference. Assume that the attenuation coefficient of the filter outside the passband is (A filter )(unit: decibel), then the signal power after filtering is (In the passband (A filter =0)).

[0074] In an optional embodiment, a power amplifier may be designed to further amplify the filtered signal, and its gain is (GPA )(unit: decibel), the signal power output by the final signal source module The total gain of the signal source module (G s =G LNA +G PA -A filter )(unit: decibel).

[0075] In an optional embodiment, the signal is transmitted through the transmission medium module and first passes through the optical fiber part. Assume that the transmission loss coefficient of the optical fiber is (α f )(unit: decibel / km), length is (L f )(unit: km), then the signal power after optical fiber transmission is

[0076] In an optional embodiment, the signal can enter the coaxial cable part, and the coaxial cable transmission loss coefficient is (α c )(unit: decibel / meter), length is (L c )(unit: meter), the signal power that finally reaches the antenna node module

[0077] In an optional embodiment, the antenna node controller in the antenna node module can be used to process the received signal, including power allocation, filtering and other operations. Assume that the allocation loss of the antenna node controller is (L d )(unit: decibel), the signal power allocated to each antenna The gain of each antenna node is (G a )(unit: decibel), effective radiated power of the antenna

[0078] In an embodiment of the present application, the specific first objective function and the first constraint condition for designing the distributed antenna system can be obtained by accurately measuring the actual area occupied by the small hydropower station through a geographic information system (GIS) measurement tool, including all areas requiring signal coverage, such as substations, dams, office areas and surrounding ancillary areas.

[0079] In an optional embodiment, the coverage radius of the antenna in the small hydropower environment can be calculated and determined. According to the type, gain, transmission power of the antenna, the topography of the small hydropower area, the distribution of buildings and other factors, the free space propagation model is used with appropriate correction factors to estimate. For the ideal free space propagation model, the attenuation formula of the signal power with distance (d) is: Among them (P t ) is the transmission power, (G t ) is the transmitting antenna gain, (G r) is the receiving antenna gain, (λ) is the signal wavelength. In the actual small hydropower environment, due to factors such as terrain obstruction and building reflection, a correction factor (K) needs to be introduced. The actual coverage radius (r) can be obtained by solving the corrected formula We get, where (P min ) is the minimum acceptable received signal power.

[0080] In an optional embodiment, the antenna node controller can allocate the loss (L d ) is determined by the hardware characteristics of the antenna node controller. During the test, a known power (P in ) signal, and measure the power (P out ), and then according to the formula Calculate the distribution loss.

[0081] In an optional embodiment, the gain of each antenna node (G a ) depends on the fact that different types of antennas (such as omnidirectional antennas and directional antennas) have different gains in different directions. The effective gain of the antenna in actual installation and usage scenarios must be considered during calculation.

[0082] In an optional embodiment, the number of antennas can be set to (n), and the antenna procurement cost can be set to (C a ) yuan / piece, the installation cost is (C i ) yuan / unit, and the signal processing and maintenance cost related to the number of antennas is (C m ) yuan / unit, then the total system cost (C(n) = n(C a +C i +C m )). At the same time, consider the signal interference factor (I(n)), which is a function of the number of antennas (n) and reflects the degree of interference between adjacent antennas. It can be expressed by the ratio of the overlapping area of ​​adjacent antenna signals or the ratio of the interference signal strength to the useful signal strength. A comprehensive evaluation function is constructed by using parameters such as the signal strength variance and data transmission bit error rate at multiple test points in the small hydropower station area. The optimization objective function can be expressed as: [O(n) = αC(n) + βI(n) - γP(n)] where (α), (β), and (γ) are weight coefficients, and the importance of each part is determined according to actual needs.

[0083] It should be noted that the above is the step of determining the first objective function;

[0084] In an optional embodiment, a signal coverage constraint (nA≥S) may be imposed, that is, the total coverage area of ​​the antennas must be greater than or equal to the area of ​​the small hydropower station to ensure that the entire area can be covered by the signal.

[0085] In an optional embodiment, the signal strength constraint can be used. At any point in the area of ​​the small hydropower station, the received signal strength (P r ) must be greater than or equal to the minimum acceptable signal strength (P min ). Modified free space propagation model After determining the antenna parameters and minimum signal strength requirements, constraints on the number of antennas (n) can be obtained, because changes in (n) will affect the antenna layout and thus affect the signal strength at each point in the area.

[0086] It should be noted that the above is the step of determining the first constraint condition;

[0087] It should also be noted that by presetting the first signal transmission model and setting the parameters to be optimized of the first signal transmission model, a basic signal coverage and strength prediction framework can be provided for the data transmission system of the small hydropower station. Setting the parameters to be optimized of the first signal transmission model allows the system to be simulated and adjusted before actual deployment to adapt to specific environmental conditions and requirements. Such an optimization process helps to improve the accuracy and efficiency of signal coverage and ensure the stability and reliability of data transmission. In addition, by optimizing the parameters, the workload and cost of on-site debugging can be reduced while improving the performance of the entire system.

[0088] S103, optimizing the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model;

[0089] In an optional embodiment, the first optimization algorithm can be a genetic algorithm. A genetic algorithm is a search optimization algorithm that simulates the principles of natural selection and genetics, and improves candidate solutions through an iterative process. In the present invention, a genetic algorithm is used to optimize the parameters of a signal transmission model to achieve the best signal coverage effect. The performance of each parameter combination is evaluated by defining a fitness function, and then new parameter combinations are generated through operations such as selection, crossover, and mutation, thereby continuously approaching the optimal solution. This method is particularly suitable for handling complex optimization problems, such as signal coverage optimization in a small hydropower station data transmission system, because it can effectively find the global optimal solution or an approximate optimal solution in a broad search space.

[0090] In an optional embodiment, the first optimization algorithm can also be a particle swarm optimization algorithm. Particle swarm optimization (PSO) is an optimization technology based on swarm intelligence, which finds the optimal solution by simulating the foraging behavior of bird flocks. In the present invention, PSO is used to adjust the parameters of the signal transmission model to achieve more efficient signal coverage. Each particle represents a potential solution, and the speed and position of the particle are updated by tracking the individual historical best position and the group historical best position. This method performs well in dealing with continuous space optimization problems and can quickly converge to the optimal solution. It is particularly suitable for the optimization problem of signal coverage in the data transmission system of small hydropower stations.

[0091] In an optional embodiment, the first optimization algorithm may also be an ant colony optimization algorithm. The ant colony algorithm is a heuristic algorithm that simulates the foraging behavior of ants. It finds the shortest path by simulating the release of pheromones by ants in the process of searching for food. In the present invention, the ant colony algorithm is used to optimize the signal transmission path to improve the efficiency and reliability of data transmission. In the algorithm, ants represent different signal transmission paths. Through the accumulation and volatilization mechanism of pheromones, ants gradually tend to choose shorter or better paths. This method has good global search capabilities when solving path optimization problems, can effectively avoid local optimal solutions, and is particularly suitable for complex signal path optimization in small hydropower station data transmission systems. Through the ant colony algorithm, dynamic optimization of signal transmission paths can be achieved, thereby improving the performance of the entire system.

[0092] In an embodiment of the present application, the first optimization algorithm includes:

[0093] The first optimization algorithm is any model that can optimize the parameters to be optimized of the first signal transmission model;

[0094] The parameter to be optimized is any parameter related to the first signal transmission characteristic.

[0095] In an embodiment of the present application, the first optimization algorithm uses a genetic algorithm, and the parameters to be optimized of the first signal transmission model are optimized according to the genetic algorithm to obtain a second signal transmission model.

[0096] In an embodiment of the present application, the first signal transmission characteristic includes at least transmission loss, transmission distance and transmission signal strength.

[0097] Exemplarily, the specific steps of optimizing the parameters to be optimized of the first signal transmission model according to the genetic algorithm to obtain the second signal transmission model may be as follows:

[0098] ① Encode the number of antennas (n), for example, using binary encoding. Determine the length of the encoding (l), based on the estimated range of the number of antennas ([n min ,nmax ]), so that (2 l ≥n max -n min +1).

[0099] ② Initialize the population: Randomly generate a certain number (set to (N)) of initial chromosome individuals, each of which represents a possible number of antennas.

[0100] ③Fitness function calculation: Calculate the fitness value of each individual according to the objective function (O(n)). The fitness value reflects the quality of the antenna quantity solution represented by the individual. The larger the fitness value, the better the solution.

[0101] ④ Selection operation: Use selection strategies such as roulette selection to select a certain number of individuals from the population as parents based on the fitness value of the individuals. Individuals with high fitness values ​​are more likely to be selected, so that excellent genes can be retained (i.e., a better antenna number scheme).

[0102] ⑤ Crossover operation: Perform a crossover operation on the selected parent individuals to generate new offspring individuals. Use single-point crossover or multi-point crossover to exchange some gene fragments in the encoding of two parent individuals, thereby generating a new antenna quantity combination.

[0103] ⑥ Mutation operation: with a certain probability (set as (p m )) Perform mutation operations on the coding of offspring individuals, randomly change the value of a certain gene bit, introduce new genes (antenna number scheme), and prevent the algorithm from falling into a local optimal solution.

[0104] ⑦ Termination condition judgment: judge whether the termination condition is met, such as reaching the maximum number of iterations (T) or the fitness value of the population converges (that is, the fitness value change for several consecutive generations is less than the set threshold). If it is met, the optimal solution is output, that is, the optimal number of antennas (n opt ); otherwise, return to the fitness function calculation step and continue iterative optimization.

[0105] It should be noted that the parameters to be optimized of the first signal transmission model are optimized according to the first optimization algorithm, and the second signal transmission model is obtained to improve the efficiency of signal transmission. The number and layout of antennas are adjusted by the optimization algorithm to make the signal coverage more uniform and reduce blind spots. The stability of the system is enhanced, and the optimized model can adapt to different environmental changes to ensure the continuity and reliability of data transmission. The cost is reduced. Through precise parameter optimization, unnecessary hardware investment can be reduced and the optimal configuration of resources can be achieved. The scalability of the system is improved. The optimized model provides a good foundation for possible future upgrades and expansions, and is easy to maintain and upgrade.

[0106] S104: Transmit the second target data according to the second signal transmission model.

[0107] In an optional embodiment, after obtaining the second signal transmission model, the system will further configure the signal processing and transmission unit. The signal processing and transmission unit is responsible for receiving signals from the distributed antenna system and performing necessary processing, such as amplification, filtering, modulation and demodulation, to ensure signal quality. The processed signal is transmitted through the optimized antenna layout, thereby achieving more efficient signal coverage and data transmission. In addition, the system also includes an intelligent monitoring module for real-time monitoring of signal transmission status and environmental changes to ensure stable operation of the system. When encountering environmental changes or system performance degradation, the intelligent monitoring module can trigger an adaptive adjustment mechanism to automatically optimize the antenna layout and signal processing parameters to adapt to new conditions and ensure the continuity and reliability of data transmission.

[0108] In the embodiment of the present application, the distributed antenna system after the solution transmits the signal, and in the intelligent inspection equipment and other terminals, the signal is transmitted back to the monitoring center through the path. The signal power (P r ) can be calculated according to the Friis transmission formula: Among them (P t ) is the transmission power (ie (ERP)), (G t ) is the transmitting antenna gain, (G r ) is the receiving antenna gain, (λ) is the signal wavelength, and (d) is the transmission distance. In practical applications, due to factors such as multipath fading, the formula needs to be corrected and the Rice fading model can be used for calculation.

[0109] In an optional embodiment, considering Rice fading, the signal power (P r ) requires a correction to the previous calculation based on the Friis transmission formula. According to the Friis transmission formula, the received signal power (P) without fading is calculated. r0 ):

[0110]

[0111] Among them, (P t ) is the transmission power (ie (ERP)), (G t ) is the transmitting antenna gain, (G r ) is the receiving antenna gain, (λ) is the signal wavelength, and (d) is the transmission distance. Introducing the Rice fading factor (K), It indicates the ratio of line-of-sight signal power to multipath scattering signal power. When the (K) value is large, the line-of-sight signal is dominant and the fading is mild; when the (K) value is small, the multipath scattering signal is dominant and the fading is severe.

[0112] In an optional embodiment, the received signal power (P r ):

[0113]

[0114] The formula is a calculation formula based on the correction of the received signal power based on the Rice fading model. It takes into account the combined effects of line-of-sight and multipath fading, making the signal power calculation more accurate in the complex environment of small hydropower.

[0115] It should be noted that, since the received signal power has changed, the coverage radius (r) of the antenna also needs to be re-evaluated.

[0116] Assume that the minimum acceptable received signal power is (P min ), then the corrected received signal power formula is We can get:

[0117]

[0118]

[0119] Will Substituting into the above formula, we can solve the coverage radius (r) after considering Rice fading:

[0120]

[0121] It should be noted that according to the new coverage radius (r), the calculation is re-optimized and the number of antenna nodes (n) is adjusted. In the presence of practical factors such as multipath fading, the Rice fading model is used to more accurately calculate and adjust the signal power, coverage range and number of antenna nodes in the small hydropower data transmission system, which helps to improve the performance and reliability of the system and better meet the needs of small hydropower intelligent inspection data transmission.

[0122] In an optional embodiment, the signal modulation module of the signal processing and transmission unit uses orthogonal frequency division multiplexing (OFDM) modulation technology to modulate the collected digital signal. Assuming the number of subcarriers in the OFDM system is (N), and each subcarrier uses 16QAM, then the number of bits of each subcarrier is (k=log2M).

[0123] In an alternative embodiment, the modulation efficiency Where (T) is the OFDM symbol period. Then the data transmission rate after modulation (Rm = η m × f × D) (unit: bits per second).

[0124] In an optional embodiment, when signal transmission is interrupted or congested, the data cache module starts to work. Let the cache capacity be (C) (unit: bytes), and the amount of cached data be (D c ), when (D c < C), the data is cached normally. When (D c = C), the earliest cached data is discarded according to the first-in, first-out principle. At the same time, the cache module can calculate the cache occupancy rate (unit: none) and the average cache time (T c ) (unit: seconds) so that the monitoring system can understand the cache status and make corresponding adjustments.

[0125] It should be noted that the signal demodulation module demodulates the signal transmitted through the distributed antenna system at the receiving end. OFDM demodulation decomposes the received signal into each subcarrier signal according to the parameters of OFDM modulation (such as the number of subcarriers, subcarrier spacing, etc.); demapping restores the subcarrier signal to the encoded bit stream according to the QAM mapping method used during modulation; decoding uses LDPC decoding corresponding to the encoding algorithm during modulation to restore the encoded bit stream to the original digital signal.

[0126] In an optional embodiment, the monitoring center receives the demodulated original digital signal from the signal processing and transmission unit through the network interface. Let the network transmission rate be (R net ) (unit: bits per second), and the data transmission time be (t) (unit: seconds), then the amount of received data (D recv = R net × t). The received data is stored in the hard disk storage system of the high-performance server, and the storage path and file name can be named according to information such as time and device number for subsequent query and management.

[0127] It should be noted that the data receiving module of the monitoring software converts the received digital signal into the image and video data format, and then the image and video processing module processes it. The intelligent analysis module uses the object detection algorithm based on deep learning to identify and detect the status of the devices in the image. Let the recognition accuracy rate be (P acc ) (unit: none), and the false alarm rate be (P false ) (unit: none). The algorithm is optimized through a large number of sample trainings and tests to improve (P acc ) and reduce (P false ). At the same time, the operating parameters of the devices (such as temperature, pressure, current, voltage, etc.) are analyzed to determine whether they exceed the normal range.

[0128] In an optional embodiment, the operation and maintenance personnel can remotely control the intelligent inspection equipment of the small hydropower station through the remote control module of the monitoring software. Send instructions to adjust the camera's shooting angle, focal length, exposure and other parameters, start or stop the inspection task, etc. Suppose the transmission delay of the remote control instruction is (T d )(unit: seconds), the total time from sending the command to the device responding (T total =T d +T response ), where (T response ) is the response time of the device to execute the command. The monitoring center can d ) and (T response ) to monitor and collect statistics in order to evaluate the performance of remote control and optimize it.

[0129] In summary, the present invention proposes a small hydropower data transmission method, which obtains first target data, performs a first preprocessing on the first target data, and obtains second target data; presets a first signal transmission model, and sets the parameters to be optimized of the first signal transmission model; optimizes the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model; and transmits the second target data according to the second signal transmission model. By combining the optimization algorithm and the signal transmission model, the stability and efficiency of data transmission are effectively improved, especially in remote small hydropower stations with complex terrain and weak signals. The signal transmission parameters can be automatically adjusted according to the specific environment and needs of the small hydropower station to ensure the reliability of data transmission. Advanced signal processing technology is used to effectively resist multipath fading and interference, reduce data loss, and improve transmission quality. Through reasonable antenna layout and optimization of coverage radius, effective coverage of the small hydropower station area is achieved, ensuring that the monitoring center can receive clear pictures and video data. It not only improves the intelligent management level of small hydropower stations, but also provides strong technical support for the stable operation and operation and maintenance efficiency of power stations.

[0130] Example 2

[0131] This embodiment also provides a small hydropower data transmission system, including:

[0132] A data processing module, used for acquiring first target data, and performing first preprocessing on the first target data to obtain second target data;

[0133] A model building module, used to preset a first signal transmission model and set parameters to be optimized of the first signal transmission model;

[0134] A model optimization module, configured to optimize the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model;

[0135] A transmission module is used to transmit the second target data according to the second signal transmission model.

[0136] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0137] This embodiment also provides a computer device, which may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 2 As shown. The computer device includes a processor, a memory, a communication interface, a display screen 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 communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a small hydropower data transmission method 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.

[0138] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0139] Acquire first target data, and perform first preprocessing on the first target data to obtain second target data;

[0140] Presetting a first signal transmission model, and setting parameters to be optimized of the first signal transmission model;

[0141] Optimizing the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model;

[0142] The second target data is transmitted according to the second signal transmission model.

[0143] Example 3

[0144] In a preferred embodiment, a specific system architecture is designed according to Embodiment 2, as follows:

[0145] 1. Design data acquisition unit: The high-resolution camera collects image and video data of the equipment, facilities and surrounding environment in the small hydropower station at a frequency (f) according to the set inspection path and time interval. It converts the optical image information into analog electrical signals, and then the video acquisition card converts the analog electrical signals into digital signal format to form raw data for subsequent processing and transmission. The data volume is (D).

[0146] 1.1 High-resolution camera: It uses a high-pixel image sensor with a pixel count that can meet the requirements of clearly capturing the details of the small hydropower station equipment. The lens assembly has a variety of optical properties, including a variable focal length range to adapt to the shooting objects at different distances, and an adjustable aperture size to control the amount of light entering under different light intensities to ensure image quality. It is equipped with an autofocus and autoexposure control system that can automatically adjust the focus and exposure parameters according to the shooting scene to ensure that the pictures and videos taken are clear, bright and accurate in color.

[0147] 1.2 Video capture card: It is mainly composed of analog-to-digital converter (ADC), data buffer, control logic circuit and interface circuit. ADC is responsible for converting the analog video signal from the camera into a digital signal. Its sampling frequency and accuracy determine the quality of the converted digital signal. The data buffer is used to temporarily store the converted digital data to match the data reading rate of the subsequent signal processing and transmission unit. The control logic circuit coordinates the workflow between the camera, ADC and buffer to ensure the continuity and stability of data acquisition. The interface circuit realizes the connection with the signal processing and transmission unit to transmit the collected digital data at high speed.

[0148] 2. Design distributed antenna systems;

[0149] 2.1 Signal source module: establishes a connection with the external communication network and receives weak original communication signals. The low noise amplifier performs low noise amplification on the signal, improves the signal strength and maintains a low noise level. The filter removes clutter and interference in the signal to make the signal purer. The power amplifier further amplifies the signal to a suitable power level. The signal source controller monitors and adjusts the entire process in real time to ensure that the output signal is stable, reliable and meets the requirements of subsequent transmission. The signal power after processing is Among them (P in ) is the input signal power, (G s ) is the gain of the signal source module (unit: decibel).

[0150] 2.1.1 Low noise amplifier (LNA): A low noise amplifier chip made of gallium arsenide (GaAs) material is selected, which has excellent noise performance and gain characteristics in the high frequency band. When receiving weak external original communication signals, it can reduce the noise introduction of the signal as much as possible, and at the same time, preliminarily amplify the signal to improve the signal-to-noise ratio.

[0151] 2.1.2 Filter: The filter characteristics are designed according to the signal frequency range required for small hydropower data transmission. The center frequency and bandwidth are determined according to the actual communication standard. It is used to filter out clutter and interference signals in the received signal and only allow useful signals within a specific frequency range to pass.

[0152] 2.1.3 Power amplifier: A power amplifier based on silicon LDMOS (laterally diffused metal oxide semiconductor) technology is selected, which can maintain good linearity and stability at higher power output. After the signal is processed by the low noise amplifier and filter, the signal is further amplified to meet the power requirements of subsequent transmission media and antenna nodes.

[0153] 2.1.4 Signal source controller: It is composed of a microprocessor or digital signal processor (DSP) and related peripheral circuits, and is responsible for controlling and coordinating the various components in the signal source module. It can dynamically adjust the operating parameters of the low noise amplifier, filter and power amplifier, such as gain, filter frequency range, etc., according to the strength and quality of the received signal and the overall needs of the system to optimize the performance of the signal source module.

[0154] 2.2 Transmission medium module: The optical fiber part is used as the backbone transmission link, which undertakes the task of long-distance and large-capacity signal transmission. Its transmission loss coefficient is (α f )(unit: decibel / km), length is (L f ) (unit: km). When optical signals are transmitted in optical fibers, certain losses will occur due to absorption and scattering of optical fiber materials. However, compared with other transmission media, optical fibers can still maintain low losses over longer distances, ensuring that the signals can be stably transmitted to the various antenna node controllers distributed in the small hydropower area. The coaxial cable section is used for short-distance, flexible signal distribution and transmission, connecting the antenna node controller with each antenna node. It can provide better signal transmission performance in short-distance transmission, and its shielding performance helps to reduce electromagnetic interference to the signal during transmission, so that the signal can accurately reach each antenna node. The formula for calculating the power of the signal after passing through the transmission medium is (P out =P s ×10 -αfLf-αcLc ).

[0155] 2.2.1 Fiber optic transmission part: It consists of fiber optic cables, fiber optic connectors and optical transceivers. Fiber optic cables use single-mode or multi-mode optical fibers. Single-mode optical fibers have a smaller core diameter and lower transmission loss, and are suitable for long-distance, high-speed data transmission. Multi-mode optical fibers have a larger core diameter and are relatively easier to connect, but the transmission distance and rate are relatively limited. Fiber optic connectors are used to connect different sections of fiber optic cables and the connection between optical fibers and optical transceivers to ensure stable transmission of optical signals. Optical transceivers realize the conversion between electrical signals and optical signals. At the signal source module end, electrical signals are converted into optical signals for transmission in the optical fiber, and at the antenna node controller end, optical signals are converted back into electrical signals. The performance parameters of optical transceivers include optical transmission power, receiving sensitivity, transmission rate, etc., which need to be selected according to the specific requirements of small hydropower data transmission.

[0156] 2.2.2 Coaxial cable transmission part: It consists of coaxial cable, coaxial cable connector and impedance matcher. Coaxial cable consists of inner conductor, insulation layer, outer conductor and sheath. Its structural characteristics give it good shielding performance and can effectively reduce the impact of external electromagnetic interference on the signal. Coaxial cable connectors are used to connect different sections of coaxial cable and the connection between coaxial cable and antenna node or antenna node controller. Impedance matcher is used to ensure impedance matching between coaxial cable and connected equipment, including antenna node, antenna node controller, etc., to reduce signal reflection and improve transmission efficiency. The transmission loss coefficient of coaxial cable is (α c )(unit: decibel / meter), its length is (L c )(unit: meter).

[0157] 2.3 Antenna node module: Multiple distributed antenna nodes are evenly distributed in key locations such as substations, dams, office areas and surrounding areas of small hydropower to realize signal transmission and reception, and ensure the effective propagation and coverage of signals in complex terrain and environments. The antenna node controller processes and distributes the signal transmitted from the transmission medium, and then transmits the signal through the antenna unit so that the signal can cover every corner of the small hydropower area. At the same time, it receives signals from intelligent inspection equipment or other terminals and transmits them back to the signal processing and transmission unit. According to the area (S) of the small hydropower station, the number of antenna nodes should be reasonably determined. in It means rounding up. By rationally arranging antenna nodes, it is ensured that the entire small hydropower area can obtain good signal coverage to meet the needs of intelligent inspection data transmission.

[0158] 2.3.1 Antenna unit: A combination of omnidirectional antenna and directional antenna is used. Omnidirectional antennas are used to provide relatively uniform signal coverage within a certain range, such as in office areas of small hydropower stations and areas with frequent personnel activities, to ensure that devices in all directions can receive signals; directional antennas are used for signal transmission in specific directions or over long distances, such as in areas such as dams of small hydropower stations, to concentrate signals to the areas that need to be covered for transmission or reception, thereby improving signal transmission efficiency and coverage. The structure of the antenna includes a radiator, a reflector, a feeder and other parts. The shape and size of the radiator determine the radiation characteristics of the antenna. The reflector is used to enhance the directivity of the antenna, and the feeder connects the antenna to the subsequent signal processing circuit. The gain of each antenna node is (G a )(unit: decibel), effective radiated power of the antenna Assume that the coverage radius of the antenna is (r) (unit: meter), and its coverage area (A = πr 2 ).

[0159] 2.3.2 Antenna node controller: It consists of a signal distributor, a power amplifier, a low noise amplifier, a filter and a microcontroller. The signal distributor distributes the signal from the transmission medium module (coaxial cable) to each antenna unit to ensure that each antenna unit can receive the appropriate signal. The power amplifier amplifies the signal when the signal is transmitted to increase the transmission power of the antenna; the low noise amplifier amplifies the weak received signal and reduces the noise when the signal is received; the filter is used to filter the transmitted and received signals to remove clutter and interference signals. The microcontroller is responsible for controlling and coordinating the various components in the antenna node controller, automatically adjusting the gain of the power amplifier and the low noise amplifier according to the instructions of the monitoring center or the signal quality, switching the working mode of the filter, and communicating with the monitoring center to feedback the working status information of the antenna node.

[0160] 3. Design signal processing and transmission unit;

[0161] 3.1 Signal modulation module: Use advanced orthogonal frequency division multiplexing (OFDM) modulation technology to efficiently modulate the digital signal from the data acquisition unit. Suppose the modulation efficiency is (η m ), then the modulated data transmission rate (R m =η m×f×D)(unit: bit / s). OFDM modulation technology divides high-speed data streams into multiple low-speed sub-data streams and transmits them in parallel on multiple subcarriers, effectively resisting multipath fading and narrowband interference, and improving the reliability and efficiency of signal transmission. At the same time, through the processing of coding and mapping circuits, the signal's anti-interference ability is further enhanced, so that the modulated signal can better adapt to the transmission characteristics of the distributed antenna system, and achieve stable and high-speed data transmission in the complex small hydropower communication environment.

[0162] 3.1.1 It is built on a digital signal processor (DSP) or an application-specific integrated circuit (ASIC). It contains a coding circuit, a mapping circuit and an OFDM modulator. The coding circuit uses a low-density parity-check code (LDPC) to encode the collected digital signal to improve the signal's anti-interference ability during transmission. The mapping circuit maps the coded signal to the corresponding subcarrier according to the requirements of OFDM modulation, and uses the QAM (quadrature amplitude modulation) mapping method to select the appropriate QAM order according to different transmission rates and signal quality requirements. The OFDM modulator performs OFDM modulation on the mapped signal according to the set subcarrier number, subcarrier spacing and other parameters to generate a signal waveform suitable for transmission in a distributed antenna system.

[0163] 3.2 Data cache module: When signal transmission is interrupted or congested, the data is cached. During the transmission of small hydropower data, signal interruption or decreased transmission rate may occur due to signal instability and other reasons. At this time, the data cache module comes into play. The data from the data acquisition unit or signal modulation module is temporarily stored in a large-capacity RAM, and the transmission is continued after the signal returns to normal to ensure that the data is not lost. Through the management of the cache controller, the cache space can be effectively utilized, data loss caused by cache overflow can be avoided, the integrity and continuity of data transmission can be guaranteed, and a reliable data storage and transmission guarantee mechanism is provided for the entire small hydropower data transmission system.

[0164] 3.2.1 It is mainly composed of a large-capacity random access memory (RAM) and a cache controller. The large-capacity RAM is used as a storage medium for data cache. Its capacity (C) (unit: byte) is determined according to the duration of signal interruptions and the size of data flow that may occur during the transmission of small hydropower data to meet the needs of high-speed data storage and reading. The cache controller is responsible for managing the storage and reading operations of data in the RAM, including address generation circuits, read-write control circuits, and cache status monitoring circuits. The address generation circuit generates the corresponding memory address according to the storage order and reading requirements of the data; the read-write control circuit controls the writing and reading operations of the data to ensure the correct storage and timely reading of the data; the cache status monitoring circuit monitors the usage of the cache in real time, such as the amount of cached data (D c ), when (Dc When <C), the data is cached normally. When (D c = C), the earliest cached data is discarded according to the first-in, first-out principle, and the cache status information is sent to other modules of the signal processing and transmission unit or the monitoring center.

[0165] 3.3 Signal demodulation module: Demodulates the signal transmitted through the distributed antenna system at the receiving end and restores it to the original digital signal. At the receiving end of the small hydropower data transmission, the signal demodulation module receives the signal transmitted from the antenna node module. After a series of processes of the OFDM demodulator, demapping circuit, and decoding circuit, the original digital signal is restored from the modulated complex waveform. This process is the reverse process of signal transmission. It needs to accurately perform the demodulation operation according to the modulation parameters and algorithms of the signal modulation module to ensure the accuracy and integrity of the restored original digital signal, providing a basic guarantee for the correct processing and analysis of the small hydropower intelligent inspection data by the monitoring center.

[0166] 3.3.1 Implemented based on a digital signal processor (DSP) or an application-specific integrated circuit (ASIC). It includes an OFDM demodulator, a demapping circuit, and a decoding circuit. The OFDM demodulator performs OFDM demodulation on the signal transmitted and received through the distributed antenna system, and demodulates the original sub-data stream from multiple subcarriers. The demapping circuit performs a demapping operation on the demodulated signal according to the QAM mapping method used in OFDM modulation to restore the encoded signal. The decoding circuit then uses the decoding algorithm corresponding to the encoding circuit in the signal modulation module to decode the encoded signal and restore it to the original digital signal for subsequent processing and analysis.

[0167] 4. Design the monitoring center: Receive and store the picture and video data from the signal processing and transmission unit, and perform real-time display, analysis, and processing on the data through the monitoring software. It can remotely control the intelligent inspection equipment. The monitoring center is the core management and decision-making unit of the entire small hydropower data transmission system. It comprehensively processes and analyzes the received intelligent inspection data, timely discovers the faults and potential safety hazards of small hydropower equipment, and operates the intelligent inspection equipment through the remote control function to achieve the remote intelligent management of small hydropower stations. At the same time, the monitoring center can also query and statistically analyze historical data, providing data support and decision-making basis for the maintenance, upgrade, and optimization of small hydropower equipment, ensuring the safe, stable operation, and efficient management of small hydropower stations.

[0168] 4.1 High-performance server: equipped with multi-core processors, large-capacity memory and high-speed hard disk storage system. Multi-core processors can quickly process large amounts of image and video data. Large-capacity memory is used to temporarily store data being processed and analyzed to increase data processing speed. High-speed hard disk storage system (such as solid-state hard disk array) is used to store historical data of small hydropower intelligent inspection for long-term storage for subsequent query and analysis. The server is also installed with an operating system and a database management system. The operating system is responsible for managing the server's hardware resources and software operating environment; the database management system is used to store and manage small hydropower equipment information, inspection data, fault records and other data.

[0169] 4.2 Monitoring software: It consists of a data receiving module, an image and video processing module, an intelligent analysis module, a user interface module, and a remote control module. The data receiving module is responsible for establishing a communication connection with the signal processing and transmission unit, receiving the demodulated original digital signal, and converting it into an image and video data format that can be processed by subsequent modules. The image and video processing module performs image enhancement, video decoding, format conversion, and other operations on the received image and video data to improve the quality and display effect of the image and video. The intelligent analysis module uses advanced image recognition, data analysis, and artificial intelligence algorithms to intelligently monitor and analyze the operating status of small hydropower equipment. It uses image recognition algorithms to detect whether the appearance of the equipment is damaged, and uses data analysis algorithms to analyze whether the operating parameters of the equipment are abnormal, and generates analysis reports and alarm information in a timely manner. The user interface module provides a friendly human-computer interaction interface, allowing operation and maintenance personnel to intuitively view real-time images and videos, analysis reports, alarm information, etc. of small hydropower equipment, and can perform related operation settings, such as adjusting inspection parameters, viewing historical data, etc. The remote control module allows operation and maintenance personnel to remotely control the intelligent inspection equipment of small hydropower stations through monitoring software, start or stop inspections, adjust camera parameters, etc.

[0170] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0171] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0172] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0173] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0174] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0175] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0176] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A small hydropower data transmission method, characterized in that: include: Acquire first target data, and perform first preprocessing on the first target data to obtain second target data; Presetting a first signal transmission model, and setting parameters to be optimized of the first signal transmission model; Optimizing the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model; The second target data is transmitted according to the second signal transmission model.

2. The small hydropower data transmission method according to claim 1, characterized in that: The first signal transmission model includes: The first signal transmission model includes a first objective function and a first constraint condition set; The first objective function is an arbitrary function used to represent the transmission characteristics of the first signal; The first constraint condition set includes at least any constraints on the first signal transmission characteristics.

3. The small hydropower data transmission method according to claim 2, characterized in that: The first optimization algorithm comprises: The first optimization algorithm is any model that can optimize the parameters to be optimized of the first signal transmission model; The parameter to be optimized is any parameter related to the first signal transmission characteristic.

4. The small hydropower data transmission method according to claim 3, characterized in that: The first signal transmission characteristics include at least transmission loss, transmission distance and transmission signal strength.

5. The small hydropower data transmission method according to claim 4, characterized in that: The first objective function at least includes determining the actual area occupied by the small hydropower station, determining the coverage radius of the antenna in the small hydropower environment, determining the distribution loss of the antenna node controller, determining the gain of each antenna node and determining the number of antennas.

6. The small hydropower data transmission method according to claim 5, characterized in that: The first constraint condition set includes a signal coverage constraint and a signal strength constraint.

7. The small hydropower data transmission method according to claim 6, characterized in that: The variable of the first objective function is set to the number of antennas: The parameters to be optimized of the first signal transmission model are optimized according to a first optimization algorithm to obtain a second signal transmission model.

8. A small hydropower data transmission system, characterized in that: include: A data processing module, used for acquiring first target data, and performing first preprocessing on the first target data to obtain second target data; A model building module, used to preset a first signal transmission model and set parameters to be optimized of the first signal transmission model; A model optimization module, configured to optimize the parameters to be optimized of the first signal transmission model according to a first optimization algorithm to obtain a second signal transmission model; A transmission module is used to transmit the second target data according to the second signal transmission model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, 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, 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 7 are implemented.

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