A 10kV strong power carrier communication method and device based on pulse modulation

Abstract

The application relates to the technical field of carrier communication, and discloses a 10kV strong power frequency carrier communication method and device based on pulse modulation, which comprises the following steps: the application is aimed at a 10kV distribution network, noise distribution is obtained through real-time power frequency signal spectrum analysis, and an initial coding sequence is generated through discrete pulse modulation. When the sequence packet loss rate exceeds a threshold value, the pulse duty cycle is adjusted to form an optimized code. Meanwhile, the power grid load fluctuation trend is analyzed, and the transmission frequency range is dynamically determined. If the frequency range and the optimized code synchronization error exceed the limit, the synchronization pulse is adaptively and iteratively generated in combination with a feedback signal. The stable data stream is synthesized through subcarrier modulation, IFFT transformation and orthogonalization. After the packet loss rate reaches the standard, the signal energy is adjusted and injected into the communication channel. The scheme combines noise analysis, dynamic frequency adjustment and channel optimization, significantly reduces the packet loss rate, and improves the communication stability and reliability of the distribution network.

Description

Technical Field

[0001] This invention relates to the field of carrier communication technology, and in particular to a 10kV high-power frequency carrier communication method and apparatus based on pulse modulation. Background Technology

[0002] Currently, power communication is a pillar technology for modern power grid operation and is crucial to ensuring the stability and intelligence of the power system. In particular, in the 10kV distribution network, communication reliability directly affects the efficiency of power dispatch and fault response.

[0003] In one existing technology, discrete pulse position modulation or differential pulse width modulation is used as the core encoding method. Specifically, a time window with a typical width of 0.5ms-1ms is opened near the zero-crossing point of the power frequency voltage, i.e., the interval with the lowest voltage amplitude, and an extremely narrow pulse signal is transmitted within this window. This existing technology suffers from pulse waveform tailing distortion caused by distributed capacitance effect, with a rising edge delay of 0.3ms and a falling edge tail of more than 2ms. When the pulse interval is less than 1.5ms, inter-symbol interference occurs, requiring RS error correction coding compensation. However, this results in a real-time service packet loss rate exceeding 10%.

[0004] Existing power line carrier communication methods often face signal attenuation and interference problems in complex power grid environments, especially in strong power frequency environments, where traditional modulation methods are difficult to effectively embed communication data, resulting in insufficient data transmission reliability. Summary of the Invention

[0005] This invention provides a 10kV high-power frequency carrier communication method and apparatus based on pulse modulation to achieve stable data transmission in a 10kV high-power frequency environment.

[0006] In a first aspect, to solve the above-mentioned technical problems, the present invention provides a 10kV high-power frequency carrier communication method based on pulse modulation, comprising:

[0007] Acquire real-time power frequency signals, grid load fluctuation data, and feedback signals from the 10kV distribution network;

[0008] The noise spectrum distribution is obtained by performing spectral characteristic analysis on the real-time power frequency signal.

[0009] Based on the noise spectrum distribution, discrete pulse modulation is performed to obtain an initial pulse coding sequence, and the structure of the coded signal is determined by analyzing the initial pulse coding sequence.

[0010] When the packet loss rate of the encoded signal structure is higher than the preset packet loss threshold, the pulse duty cycle is adjusted to obtain an optimized encoded sequence.

[0011] The load fluctuation data of the power grid is analyzed to obtain the load change trend, and the final dynamic transmission frequency range is determined by combining the load change trend;

[0012] When the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, adaptive iterative control is performed in conjunction with the feedback signal to obtain a synchronization pulse signal.

[0013] The modulation data stream is obtained by subcarrier allocation and modulation based on the synchronization pulse signal, and the modulation data stream is then subjected to inverse fast Fourier transform and combined with orthogonal subcarriers to obtain the initial transmission signal.

[0014] Based on the initial transmission signal, signal orthogonalization and signal synthesis are performed to obtain a stable transmission data stream;

[0015] When the packet loss rate of the stable data stream is lower than the preset packet loss threshold, the signal energy distribution is adjusted and injected into the 10kV distribution network communication channel to complete the data transmission.

[0016] In one optional implementation, the step of performing spectral characteristic analysis on the real-time power frequency signal to obtain the noise spectrum distribution includes:

[0017] The original signal is obtained by analog-to-digital conversion based on the real-time power frequency signal;

[0018] The original signal is filtered to obtain a preprocessed signal;

[0019] Background noise components are extracted from the preprocessed signal to obtain background noise data;

[0020] The background noise data is subjected to a fast Fourier transform to obtain the noise spectrum distribution curve;

[0021] When the spectral value in the noise spectrum distribution curve exceeds the preset spectral threshold, it is marked as an abnormal frequency point to obtain the noise spectrum distribution.

[0022] In one optional implementation, the step of obtaining an initial pulse coding sequence by performing discrete pulse modulation based on the noise spectrum distribution, and analyzing the initial pulse coding sequence to determine the coded signal structure, includes:

[0023] Spectral distribution data is obtained by performing spectral analysis based on the noise spectral distribution.

[0024] When the noise energy in the spectral distribution data exceeds a preset energy threshold, noise suppression processing is performed on the spectral distribution data to obtain a denoised signal.

[0025] The denoised signal is subjected to discrete pulse modulation coding to obtain an initial pulse coding sequence;

[0026] The initial pulse coding sequence is subjected to Huffman coding compression to obtain the coded signal structure.

[0027] In one optional implementation, when the data packet loss rate of the encoded signal structure is higher than a preset packet loss threshold, adjusting the pulse duty cycle to obtain an optimized encoded sequence includes:

[0028] An initial data packet loss rate is obtained by monitoring the data packet loss rate of the encoded signal structure. The average loss rate is then calculated using a sliding window based on the initial data packet loss rate to obtain the first data packet loss rate value.

[0029] When the first data packet loss rate exceeds the preset packet loss threshold, the pulse duty cycle increment ΔD is calculated to obtain the first pulse duty cycle value.

[0030] Based on the first pulse duty cycle value, the structure of the encoded signal is reconfigured to obtain a first optimized encoded sequence;

[0031] Signal transmission quality parameters are extracted from the first optimized coding sequence to obtain the optimized coding sequence.

[0032] In one optional implementation, the step of analyzing the power grid load fluctuation data to obtain the load change trend, and combining the load change trend to determine the final dynamic transmission frequency range, includes:

[0033] The periodic features are extracted from the power grid load fluctuation data to obtain the first load fluctuation sequence;

[0034] The load change rate is obtained by performing a sliding window calculation on the first load fluctuation sequence. When the load change rate exceeds a preset change rate threshold, a first change trend curve is generated, and the load change trend is determined by combining the first change trend curve.

[0035] The load change trend is linearly fitted to obtain the trend slope, and the frequency increment ΔF is adjusted according to the trend slope to obtain the first dynamic transmission frequency value;

[0036] The transmission frequency is reconfigured based on the first dynamic transmission frequency value to obtain the final dynamic transmission frequency range.

[0037] In one optional implementation, when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, adaptive iterative control is performed in conjunction with the feedback signal to obtain a synchronization pulse signal, including:

[0038] When the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds the error threshold, the time deviation value is calculated through error detection.

[0039] The final dynamic transmission frequency range is adjusted according to the time deviation value, and the feedback signal is segmented based on the final dynamic transmission frequency range to obtain the adjusted frequency value.

[0040] Based on the adjusted frequency value and the feedback signal, an adaptive iteration is performed to obtain a synchronization pulse signal.

[0041] In one optional implementation, the step of allocating and modulating subcarriers according to the synchronization pulse signal to obtain a modulated data stream, performing an inverse fast Fourier transform on the modulated data stream and combining it with orthogonal subcarriers to obtain an initial transmission signal includes:

[0042] The channel quality index value is obtained by performing a fast Fourier transform on the spectral distribution of the synchronization pulse signal.

[0043] The subcarriers are dynamically allocated based on the channel quality index values ​​to obtain a subcarrier allocation scheme.

[0044] If the subcarrier allocation scheme meets the preset channel quality threshold, then QAM modulation is performed on the subcarrier data; if the subcarrier allocation scheme does not meet the preset channel quality threshold, then PSK modulation is performed on the subcarrier data to obtain the modulated data stream.

[0045] The modulated data stream is subjected to inverse fast Fourier transform and combined with orthogonal subcarriers to obtain the initial transmission signal.

[0046] In one optional implementation, the step of performing signal orthogonalization processing and signal synthesis based on the initial transmitted signal to obtain a stable transmitted data stream includes:

[0047] By monitoring the attenuation of the initial transmitted signal, channel state data is obtained. The amplitude and phase of the initial transmitted signal are then adjusted based on the channel state data to obtain a compensated first signal.

[0048] The compensated first signal is decomposed into orthogonal subcarriers, and the interference value between the subcarriers is obtained based on the orthogonal subcarriers. The subcarrier phase is adjusted in combination with the obtained interference value between the subcarriers to obtain the orthogonalized second signal.

[0049] The second signal is bandpass filtered to extract the target frequency band signal, resulting in a third signal with interference suppression.

[0050] The third signal is integrated with other subcarrier signals to obtain a stable transmission data stream.

[0051] In one optional implementation, when the packet loss rate of the stable data stream is lower than a preset packet loss threshold, adjusting the signal energy distribution and injecting it into the 10kV distribution network communication channel to complete data transmission includes:

[0052] When the packet loss rate of the stable transmission data stream is lower than the preset packet loss threshold, the energy distribution data of the stable transmission data stream is decomposed and the target frequency band energy component is extracted to obtain the energy distribution characteristics.

[0053] The signal modulation parameters are adjusted according to the energy distribution characteristics to obtain the modulated first signal.

[0054] Channel state monitoring is performed on the modulated first signal to obtain real-time channel state data. The channel capacity allocation scheme is determined by combining the real-time channel state data to obtain optimized channel allocation parameters.

[0055] The first signal is injected into the power distribution network communication channel, and the channel allocation parameters are integrated with the first signal to complete data transmission.

[0056] Secondly, the present invention provides a 10kV high-power frequency carrier communication device based on pulse modulation, comprising:

[0057] The signal acquisition module is used to acquire real-time power frequency signals, power grid load fluctuation data, and feedback signals of the 10kV distribution network.

[0058] The spectrum analysis module is used to perform spectrum characteristic analysis on the real-time power frequency signal to obtain the noise spectrum distribution;

[0059] The coding and modulation module is used to perform discrete pulse modulation based on the noise spectrum distribution to obtain an initial pulse coding sequence, and to analyze the initial pulse coding sequence to determine the structure of the coded signal.

[0060] The pulse adjustment module is used to adjust the pulse duty cycle to obtain an optimized encoding sequence when the data packet loss rate of the encoded signal structure is higher than a preset packet loss threshold.

[0061] The frequency confirmation module is used to analyze the power grid load fluctuation data to obtain the load change trend, and combine the load change trend to confirm the final dynamic transmission frequency range;

[0062] An iterative control module is used to perform adaptive iterative control in conjunction with the feedback signal to obtain a synchronization pulse signal when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold.

[0063] The signal synthesis module is used to allocate and modulate subcarriers according to the synchronization pulse signal to obtain a modulated data stream, perform inverse fast Fourier transform on the modulated data stream and combine it with orthogonal subcarriers to obtain an initial transmission signal;

[0064] The signal adjustment module is used to perform signal orthogonalization processing and signal synthesis based on the initial transmission signal to obtain a stable transmission data stream.

[0065] The data transmission module is used to adjust the signal energy distribution and inject it into the 10kV distribution network communication channel to complete data transmission when the data packet loss rate of the stable data transmission stream is lower than a preset packet loss threshold.

[0066] Thirdly, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the 10kV high-power frequency carrier communication method based on pulse modulation as described in any one of the above.

[0067] Fourthly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the 10kV high-power frequency carrier communication method based on pulse modulation as described above.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] (1) This invention constructs a closed-loop adaptive communication system to achieve reliable transmission through environmental perception and dynamic adjustment. First, real-time power frequency signals, grid load fluctuation data, and feedback signals are collected, and spectral feature analysis is performed to lock the noise distribution characteristics. Based on the analysis results, a discrete pulse coding sequence is generated, and the transmission quality is dynamically evaluated to trigger parameter optimization: when the communication reliability does not meet the requirements, the pulse timing characteristics are automatically adjusted; load trend prediction is carried out simultaneously, and the optimal transmission frequency band range is dynamically determined in combination with the grid state evolution model. For timing synchronization deviations, the feedback signal is fused for iterative control to generate a precise synchronization signal. Based on this, subcarrier dynamic allocation and joint modulation are implemented, and spectral interference is eliminated through multiple orthogonal processing to form a transmission signal stream that meets the stability requirements, and finally, channel adaptation injection is completed.

[0070] (2) Based on noise analysis, this invention reveals the differences in signal transmission capabilities of different frequency bands and guides the intelligent allocation of signal energy; the pulse adjustment mechanism automatically tends to the optimal state under power grid interference; the physical characteristics of the power line determine the correspondence between load changes and the optimal frequency band; the feedback system achieves precise synchronization through continuous adjustment; the principle of anti-overlapping of multiple signals eliminates interference between channels in essence.

[0071] (3) This invention enhances communication immunity and fundamentally improves signal quality through adaptive noise suppression technology, ensuring stable communication reliability to meet industrial-grade requirements; the system environment adaptability has made significant progress, and load fluctuation tracking technology enables intelligent following of communication parameters, effectively overcoming transmission degradation caused by drastic changes in power grid conditions; communication efficiency has been comprehensively enhanced, and orthogonal architecture solves the problem of spectrum resource conflict, maintaining efficient and stable transmission under complex power grid topology and harsh operating conditions. Attached Figure Description

[0072] Figure 1 This is a schematic diagram of the 10kV high-power frequency carrier communication method based on pulse modulation provided in the first embodiment of the present invention;

[0073] Figure 2 This is a schematic diagram of the structure of a 10kV high-power frequency carrier communication device based on pulse modulation provided in the second embodiment of the present invention. Detailed Implementation

[0074] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0075] Reference Figure 1 The first embodiment of the present invention provides a 10kV high-power frequency carrier communication method based on pulse modulation, comprising the following steps:

[0076] S11, acquire real-time power frequency signals, grid load fluctuation data, and feedback signals of the 10kV distribution network;

[0077] S12, Perform spectral characteristic analysis on the real-time power frequency signal to obtain the noise spectrum distribution;

[0078] S13, perform discrete pulse modulation based on the noise spectrum distribution to obtain an initial pulse coding sequence, and analyze the initial pulse coding sequence to determine the coding signal structure;

[0079] S14, when the data packet loss rate of the encoded signal structure is higher than the preset packet loss threshold, the pulse duty cycle is adjusted to obtain an optimized encoding sequence;

[0080] S15, Analyze the power grid load fluctuation data to obtain the load change trend, and combine the load change trend to confirm the final dynamic transmission frequency range;

[0081] S16, when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, adaptive iterative control is performed in conjunction with the feedback signal to obtain a synchronization pulse signal;

[0082] S17, Subcarrier allocation and modulation are performed according to the synchronization pulse signal to obtain a modulated data stream, and the modulated data stream is subjected to inverse fast Fourier transform and combined with orthogonal subcarriers to obtain an initial transmission signal;

[0083] S18, perform signal orthogonalization and signal synthesis based on the initial transmission signal to obtain a stable transmission data stream;

[0084] S19, when the packet loss rate of the stable transmission data stream is lower than the preset packet loss threshold, the signal energy distribution is adjusted and injected into the 10kV distribution network communication channel to complete the data transmission.

[0085] In step S11, it is necessary to acquire the real-time power frequency signal, power grid load fluctuation data, and feedback signal of the 10kV distribution network.

[0086] It should be noted that the real-time power frequency signal refers to the voltage or current waveform of the 50Hz fundamental and harmonic components in the 10kV distribution network, which is obtained through electromagnetic induction voltage transformers or Rogowski coil sensors and reflects the instantaneous operating status of the power grid.

[0087] Among them, the power grid load fluctuation data represents the dynamic changes in the power of distribution transformers, distributed power sources and electrical equipment. It is collected in real time by smart meters, power transmitters and SCADA systems and transmitted to the communication controller via the data bus.

[0088] The feedback signal refers to the communication quality assessment parameters generated after demodulation at the receiving end, including bit error rate, latency, and signal strength, which are transmitted back to the transmitting end through a dedicated reverse channel or time slot multiplexing. The three data sources are acquired synchronously using multi-threaded parallel acquisition technology, providing complete environmental awareness for subsequent adaptive control.

[0089] In step S12, the spectral characteristic analysis of the real-time power frequency signal to obtain the noise spectrum distribution includes:

[0090] The original signal is obtained by analog-to-digital conversion based on the real-time power frequency signal;

[0091] The original signal is filtered to obtain a preprocessed signal;

[0092] Background noise components are extracted from the preprocessed signal to obtain background noise data;

[0093] The background noise data is subjected to a fast Fourier transform to obtain the noise spectrum distribution curve;

[0094] When the spectral value in the noise spectrum distribution curve exceeds the preset spectral threshold, it is marked as an abnormal frequency point to obtain the noise spectrum distribution.

[0095] First, the real-time power frequency signal is converted into a digital signal using an analog-to-digital converter (ADC) to obtain the original signal. The voltage signal of the 10kV line is sampled to generate raw signal data containing power frequency components, noise, and interference. This step ensures high-fidelity digitization of the analog signal, laying the foundation for subsequent processing. The selection of the ADC must consider high sampling rate and accuracy, such as 16-bit resolution, to capture signal details.

[0096] Subsequently, the original signal is filtered using wavelet transform, which effectively removes high-frequency interference and baseline drift. The signal is decomposed into four levels using the Daubechies wavelet basis to filter out high-frequency noise above 1kHz, while simultaneously eliminating baseline drift caused by temperature changes or equipment aging, resulting in a smooth pre-processed signal. This method is more suitable for processing non-stationary signals than traditional filters, preserving the characteristics of power frequency signals and reducing the risk of misjudgment.

[0097] Next, an adaptive filter is used to extract the power frequency background noise component from the preprocessed signal data. For example, by comparing it with a preset 50Hz power frequency model, the adaptive filter can dynamically adjust its parameters to separate the background noise data. Suppose that the preprocessed signal of a certain line contains a 50Hz power frequency component and 100Hz harmonic interference, the adaptive filter, through iterative learning, identifies the 100Hz component as noise and outputs clean background noise data. This method can adapt to signal fluctuations caused by load changes during power grid operation, improving the accuracy of noise extraction.

[0098] Then, a Fast Fourier Transform (FFT) is performed on the background noise data to obtain the spectral distribution curve. After converting the background noise data to the frequency domain, a spectrum graph is generated, showing 50Hz as the dominant frequency, accompanied by several harmonic components. Finally, the noise spectral distribution curve is analyzed to obtain the corresponding spectral values. Assuming a preset spectral threshold of 0.5V, when the spectral value reaches 0.7V at 200Hz, it is identified as an abnormal frequency point, thus obtaining the abnormal noise distribution. This method can intuitively reflect abnormal frequencies caused by electromagnetic interference or equipment failure in the power grid, helping to quickly locate problems. Furthermore, the abnormal noise distribution can further assist in fault diagnosis.

[0099] For example, the spectrum diagram of a 10kV line shows an abnormal peak at 300Hz, which may indicate partial discharge in the transformer. By combining historical data with on-site inspection, the cause of the fault can be identified and maintenance measures can be taken. The advantage of this method is its high sensitivity and rapid response, which can significantly improve the operational reliability of the distribution network.

[0100] In one possible implementation, the aforementioned technologies can be integrated into an intelligent monitoring terminal. The terminal acquires signals in real time, processes them through analog-to-digital conversion, wavelet transform, adaptive filtering, and fast Fourier transform, outputs abnormal noise distribution results, and pushes them to maintenance personnel via a cloud platform. This end-to-end processing flow not only improves fault detection efficiency but also reduces manual inspection costs, providing technical support for intelligent management of power distribution networks.

[0101] In step S13, the step of obtaining an initial pulse coding sequence by performing discrete pulse modulation based on the noise spectrum distribution, and analyzing the initial pulse coding sequence to determine the structure of the coded signal, includes:

[0102] Spectral distribution data is obtained by performing spectral analysis based on the noise spectral distribution.

[0103] When the noise energy in the spectral distribution data exceeds a preset energy threshold, noise suppression processing is performed on the spectral distribution data to obtain a denoised signal.

[0104] The denoised signal is subjected to discrete pulse modulation coding to obtain an initial pulse coding sequence;

[0105] The initial pulse coding sequence is subjected to Huffman coding compression to obtain the coded signal structure.

[0106] First, the Fast Fourier Transform (FFT) decomposes the noise spectrum distribution into different frequency components, calculates the energy distribution in the signal frequency domain, and obtains the spectral distribution data. Assuming the input signal of a 10kV line contains a 50Hz power frequency component and various noises, after processing with the FFT, spectral distribution data can be generated, showing the dominant frequency peak at 50Hz, accompanied by harmonic components such as 100Hz and 200Hz, and intuitively reflecting the intensity of each frequency component; for example, the energy at 50Hz is 10W, and at 100Hz it is 2W.

[0107] Subsequently, if the preset noise energy threshold is 1.5W, the frequency component at 100Hz is marked as noise, and the adaptive filter suppresses signals whose noise energy exceeds the threshold. Assuming the detected noise energy at 100Hz is 2W, exceeding the 1.5W threshold, the adaptive filter dynamically adjusts its filtering parameters to identify and weaken the 100Hz component. In implementation, the filter can use a minimum mean square error algorithm to compare the signal with a 50Hz reference model in real time to obtain the denoised signal. This process ensures the integrity of the power frequency signal is preserved while reducing noise interference. For example, in the signal processing of a substation, 100Hz noise is effectively suppressed, and the 50Hz component of the output signal is cleaner.

[0108] Next, the denoised signal is encoded using discrete pulse modulation (DPCM) to obtain an initial pulse-coded sequence. DPCM converts the signal into a pulse sequence, facilitating subsequent transmission and storage. The uniform quantization method determines the pulse amplitude range and the length of the encoded sequence.

[0109] For example, with a signal amplitude range of -5V to 5V, quantization is divided into 16 levels, each level being 0.625V, and the encoding sequence length is set to 8 bits, which can generate a high-precision initial pulse code sequence. This quantization method, through a fixed step size, ensures that signal details are accurately captured. In the signal processing terminal of a 10kV line, the quantized pulse sequence can efficiently represent voltage fluctuation characteristics.

[0110] Finally, the initial pulse-coded sequence is compressed using Huffman coding to obtain the coded signal structure. Huffman coding assigns different code lengths based on the frequency of symbols in the pulse sequence; high-frequency symbols use short codes, and low-frequency symbols use long codes. For example, if the 0V amplitude appears most frequently in a pulse sequence, it is assigned a 2-bit code, while the 5V amplitude is less frequent and is assigned a 4-bit code, the compressed coded signal structure is generated. In a power distribution network monitoring system, the compressed signal data volume is reduced by 30%, facilitating transmission and storage on the cloud platform. This method improves the efficiency of signal processing and transmission by reducing redundant data.

[0111] In one possible implementation, the aforementioned technologies can be integrated into intelligent monitoring equipment. The equipment forms a complete process from signal acquisition to spectrum analysis, noise suppression, signal encoding, and compression. In a monitoring terminal for a 10kV line, the signal undergoes Fast Fourier Transform to generate a spectrum distribution, an adaptive filter removes noise, and discrete pulse modulation and Huffman coding generate a highly efficient coded signal, which is then uploaded to a cloud platform in real time. This end-to-end processing method, through efficient data processing and compression, optimizes the performance of distribution network signal analysis, providing reliable data support for subsequent fault diagnosis and maintenance.

[0112] In step S14, when the data packet loss rate of the encoded signal structure is higher than a preset packet loss threshold, the pulse duty cycle is adjusted to obtain an optimized encoding sequence, including:

[0113] An initial data packet loss rate is obtained by monitoring the data packet loss rate of the encoded signal structure. The average loss rate is then calculated using a sliding window based on the initial data packet loss rate to obtain the first data packet loss rate value.

[0114] When the first data packet loss rate exceeds the preset packet loss threshold, the pulse duty cycle increment ΔD is calculated to obtain the first pulse duty cycle value.

[0115] Based on the first pulse duty cycle value, the structure of the encoded signal is reconfigured to obtain a first optimized encoded sequence;

[0116] Signal transmission quality parameters are extracted from the first optimized coding sequence to obtain the optimized coding sequence.

[0117] First, the structure of the encoded signal in the power frequency environment is monitored in real time to analyze the data packet loss situation. Then, the average loss rate per unit time is calculated using a sliding window to obtain the first data packet loss rate value.

[0118] For example, in the signal transmission system of a 10kV substation, the monitoring equipment collects 1000 data packets per second, records their reception status, and generates loss rate statistics. With a window size set to 10 seconds, the monitoring system counts the number of data packets lost per second. Assuming that the number of data packets lost within a certain window is 5, 3, 6, 4, 2, 3, 5, 7, 4, and 3 respectively, the average loss rate is calculated to be 4.2%.

[0119] Subsequently, with a preset packet loss threshold of 3%, this 4.2% first data packet loss rate indicates impaired transmission quality, necessitating adjustment of the pulse duty cycle based on environmental noise characteristics. An adaptive adjustment algorithm analyzes the noise spectrum and dynamically calculates the duty cycle increment ΔD. If high interference energy is detected at 100Hz, the algorithm sets ΔD to 5% to enhance signal anti-interference capability, resulting in a first pulse duty cycle value of 30%.

[0120] Next, the coded signal structure is uniformly pulse-modulated based on the adjusted first pulse duty cycle to obtain the first pulse sequence. For example, if the signal amplitude range is -10V to 10V, 8-level quantization is used, with each level at 2.5V, combined with a 30% duty cycle to generate a pulse sequence. This sequence represents the signal characteristics through pulse amplitude at fixed time intervals, ensuring transmission stability. In the generated sequence, the pulse width and amplitude are combined to obtain the first optimized coded sequence.

[0121] Finally, signal transmission quality parameters are extracted from the first optimized coding sequence, and signal amplitude integrity and pulse interval consistency are ensured. The bit error rate (BER) of the first optimized coding sequence is then tested to verify signal integrity, ultimately yielding the optimized coding sequence. The monitoring system calculates the BER by comparing the received sequence with a reference sequence. If the BER in a 10kV line transmission is 0.5%, which is lower than the preset threshold of 1%, it indicates good signal integrity.

[0122] For example, in a practical application, a power distribution network monitoring terminal optimizes signal encoding using the above method. After real-time monitoring detects that the data packet loss rate exceeds the standard, the duty cycle is adjusted and the pulse sequence is regenerated. Bit error rate detection confirms signal integrity. This process ensures efficient signal transmission even in noisy environments, providing reliable support for subsequent data analysis.

[0123] In step S15, analyzing the power grid load fluctuation data to obtain the load change trend, and combining the load change trend to confirm the final dynamic transmission frequency range, includes:

[0124] The periodic features are extracted from the power grid load fluctuation data to obtain the first load fluctuation sequence;

[0125] The load change rate is obtained by performing a sliding window calculation on the first load fluctuation sequence. When the load change rate exceeds a preset change rate threshold, a first change trend curve is generated, and the load change trend is determined by combining the first change trend curve.

[0126] The load change trend is linearly fitted to obtain the trend slope, and the frequency increment ΔF is adjusted according to the trend slope to obtain the first dynamic transmission frequency value;

[0127] The transmission frequency is reconfigured based on the first dynamic transmission frequency value to obtain the final dynamic transmission frequency range.

[0128] First, a Fast Fourier Transform (FFT) is performed on the power grid load fluctuation data to convert the time-domain signal into the frequency domain, obtaining the frequency components of the signal. Assuming the acquired feedback signal is a periodic pulse signal with a sampling rate of 1000Hz, the FFT can identify the dominant frequency component, such as 200Hz, to obtain the first load fluctuation sequence.

[0129] Subsequently, in the sliding window calculation step, the window size is set to 0.2 seconds and the sliding step size to 0.02 seconds. For the first load fluctuation sequence, the load change rate within each window is calculated in real time. It is assumed that when the load change rate within a window exceeds a preset threshold of ±15% / second, a trend analysis mechanism is triggered. For example, if a significant change in load value is observed within the time interval t=1.58 seconds to 1.78 seconds, the calculated instantaneous change rate is +15.3% / second, exceeding the preset change rate threshold of +15% / second. The system extracts the window data that continuously exceeds the threshold, such as the interval from 1.58 seconds to 2.18 seconds, obtains the first change trend curve through polynomial fitting, and analyzes the first change trend curve to obtain the load change trend.

[0130] Next, based on the load change trend, the system obtains the trend slope by linearly fitting the load change trend. For example, the fitted slope value is +18% / second. According to the preset dynamic adjustment rule—when the slope is greater than +10% / second, the frequency increment ΔF is adjusted to +12Hz—the system determines ΔF = +12Hz and calculates the first dynamic transmission frequency value. Finally, the transmission range is reconfigured based on the first dynamic transmission frequency value. Considering the transient tolerance capability of the equipment and the system stability requirements, the allowable offset is set to ±5Hz, resulting in the final dynamic transmission frequency range.

[0131] This range is only effective during periods of severe load fluctuations. For example, if the load change rate is below ±3% / second for 2 seconds, the system will automatically reset to the reference frequency range.

[0132] In step S16, when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, the adaptive iterative control combined with the feedback signal to obtain a synchronization pulse signal includes:

[0133] When the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds the error threshold, the time deviation value is calculated through error detection.

[0134] The final dynamic transmission frequency range is adjusted according to the time deviation value, and the feedback signal is segmented based on the final dynamic transmission frequency range to obtain the adjusted frequency value.

[0135] Adaptive iterative control is performed based on the adjusted frequency value and the feedback signal to obtain a synchronization pulse signal.

[0136] First, if the synchronization error between the final dynamic transmission frequency range and the optimized coded sequence exceeds a threshold—for example, if the error threshold is set to 5Hz but the actual error is 8Hz—then an error detection algorithm is needed to calculate the time deviation. This algorithm can analyze the phase difference of the signal, comparing the arrival times of the signals at the transmitting and receiving ends to obtain a time deviation value, such as 0.02 seconds. This time deviation reflects the degree of signal synchronization offset, providing a basis for frequency adjustment.

[0137] Subsequently, the final dynamic transmission frequency range is adjusted based on the time deviation value using a step-size control algorithm. For example, if the time deviation is 0.02 seconds, the algorithm can gradually increase or decrease the frequency step size, such as adjusting by 2Hz each time, to approach the target frequency. The adjusted frequency value may change from 200Hz to 198Hz, thereby reducing synchronization error. This method can dynamically optimize the frequency and ensure the stability of signal transmission.

[0138] Next, by combining time windowing, the feedback signal is divided into multiple time segments, each 0.1 seconds in length. By performing Fast Fourier Transform analysis on each segment individually, the dynamic changes of the signal can be captured more accurately, yielding a more precise adjusted frequency value, such as 197.5 Hz. This segmented processing effectively addresses the non-stationary characteristics of the signal and improves synchronization accuracy.

[0139] Finally, the adaptive iterative algorithm generates a synchronization pulse signal based on the adjusted frequency value and the real-time feedback signal. For example, the algorithm dynamically updates the trigger time of the pulse signal by comparing the deviation between the real-time signal and the adjusted frequency value, ultimately obtaining a synchronization pulse signal with a period of 0.005 seconds. This adaptive method can correct frequency drift in real time, ensuring precise synchronization between the transmitter and receiver.

[0140] It should be noted that the combination of the above methods can significantly improve the synchronization performance of wireless communication systems. For example, through Fast Fourier Transform and time windowing, the system can quickly respond to signal changes; step size control and adaptive iterative algorithms ensure the flexibility and accuracy of frequency adjustment. These technologies work together to enable the communication system to maintain efficient and stable data transmission even in complex environments, reducing the bit error rate and improving signal quality.

[0141] In step S17, the process of allocating and modulating subcarriers according to the synchronization pulse signal to obtain a modulated data stream, performing an inverse fast Fourier transform on the modulated data stream and combining it with orthogonal subcarriers to obtain an initial transmission signal includes:

[0142] The channel quality index value is obtained by performing a fast Fourier transform on the spectral distribution of the synchronization pulse signal.

[0143] The subcarriers are dynamically allocated based on the channel quality index values ​​to obtain a subcarrier allocation scheme.

[0144] If the subcarrier allocation scheme meets the preset channel quality threshold, then QAM modulation is performed on the subcarrier data; if the subcarrier allocation scheme does not meet the preset channel quality threshold, then PSK modulation is performed on the subcarrier data to obtain the modulated data stream.

[0145] The modulated data stream is subjected to inverse fast Fourier transform and combined with orthogonal subcarriers to obtain the initial transmission signal.

[0146] First, channel state data of the synchronization pulse signal is acquired in real time to provide a basis for subcarrier allocation and data modulation. Channel state data typically includes information such as signal-to-noise ratio and fading characteristics. Fast Fourier Transform (FFT) is used to convert this time-domain data into the frequency domain, generating a spectral distribution. For example, assuming the channel monitoring module acquires data at a sampling rate of 2000Hz, FFT analysis shows that the dominant frequency components are concentrated around 300Hz, from which a channel quality index of 80dB can be calculated.

[0147] Subsequently, based on channel quality metrics, subcarriers are dynamically allocated and prioritized, with higher-priority services receiving the best subcarriers. For example, video streams have higher priority than text transmissions. Assuming the system has 16 subcarriers, and channel quality metrics show that the signal-to-noise ratio (SNR) of 8 subcarriers is higher than a preset threshold of 60 dB, the algorithm prioritizes allocating these 8 subcarriers to the video stream, and the remaining subcarriers to text transmission. This allocation method ensures that high-priority services receive better transmission quality.

[0148] Next, if the subcarrier allocation scheme meets the channel quality threshold, for example, the signal-to-noise ratio (SNR) of all subcarriers is higher than 60 dB, then QAM modulation is used; if the SNR of some subcarriers is lower than the channel quality threshold, for example, only 50 dB, then PSK modulation is used to obtain the modulated data stream. QAM modulation carries more data through a combination of amplitude and phase. PSK modulation only adjusts the phase, resulting in stronger noise immunity. Specifically, 16-QAM modulation, where each symbol can transmit 4 bits of data, is suitable for high SNR scenarios. 8-PSK modulation, where each symbol transmits 3 bits of data, is suitable for scenarios with poor channel quality.

[0149] Finally, the modulated data stream is combined with orthogonal subcarriers using an IFFT transform to obtain the initial transmitted signal. The IFFT transform converts the frequency domain data back to the time domain, ensuring orthogonality between subcarriers. Assuming the system uses 64 orthogonal subcarriers, the IFFT transform maps the modulated data stream onto these subcarriers, generating a time-domain transmitted signal with a period of 0.01 seconds. This method guarantees efficient signal transmission and interference-free characteristics between subcarriers.

[0150] It should be noted that the above technologies are closely integrated with channel state data, forming a complete signal processing chain from spectrum analysis to subcarrier allocation, modulation, and signal generation. The implementation of each step relies on data support from the previous step. Channel quality indicators directly affect the subcarrier allocation strategy, and the allocation result determines the choice of modulation scheme. This logical progression ensures the rigor and efficiency of the solution.

[0151] In step S18, the process of performing signal orthogonalization and signal synthesis based on the initial transmission signal to obtain a stable transmission data stream includes:

[0152] By monitoring the attenuation of the initial transmitted signal, channel state data is obtained. The amplitude and phase of the initial transmitted signal are then adjusted based on the channel state data to obtain a compensated first signal.

[0153] The compensated first signal is decomposed into orthogonal subcarriers, and the interference value between the subcarriers is obtained based on the orthogonal subcarriers. The subcarrier phase is adjusted in combination with the obtained interference value between the subcarriers to obtain the orthogonalized second signal.

[0154] The second signal is bandpass filtered to extract the target frequency band signal, resulting in a third signal with interference suppression.

[0155] The third signal is integrated with other subcarrier signals to obtain a stable transmission data stream.

[0156] First, a channel state monitoring module deployed at the receiving end can monitor the attenuation of the initial transmitted signal in real time, acquiring channel state data including amplitude attenuation and phase shift during transmission. Assuming a 5G communication system, the monitoring module detects a signal amplitude attenuation of 3dB and a phase shift of 15 degrees on a certain channel. The monitoring module extracts the amplitude and phase information from the time-domain waveform of the sampled signal and transmits the data to the processing unit in real time. This method relies on high-precision sampling equipment to ensure that the data accurately reflects the channel state, providing a reliable basis for subsequent processing. For example, using time-domain analysis to calculate signal amplitude and phase, a digital signal processor can be used to analyze the acquired time-domain signal. For instance, in the signal received by the base station, through fast time-domain sampling, the peak amplitude of the signal is calculated to be 0.8 times the original signal, and the phase shift is 20 degrees. The analysis process decomposes the time-domain signal into frequency components using Fourier transform, extracting key features. This method can accurately capture the dynamic changes of the signal, providing a basis for adaptive equalization.

[0157] Subsequently, when the adaptive equalizer adjusts the signal amplitude and phase, it can employ a gradient descent-based equalization algorithm. For example, in the equalizer, for a detected 3dB attenuation, the algorithm automatically increases the gain compensation to near the original amplitude, while simultaneously correcting a 15-degree phase shift, resulting in the compensated first signal. This compensation ensures that the signal maintains high integrity in subsequent processing, reducing data distortion caused by channel attenuation.

[0158] Next, based on the orthogonal component characteristics of the first signal, the orthogonal frequency division multiplexing method is used to decompose the signal into multiple orthogonal subcarriers through fast Fourier transform. Assume the signal is decomposed into 64 subcarriers, where the interference value of a certain subcarrier is 0.2. The system identifies the source of interference by analyzing the amplitude differences between the subcarriers. This method utilizes the frequency division characteristics of orthogonal subcarriers to ensure efficient signal separation in the frequency domain.

[0159] Then, when adjusting the subcarrier phase using the minimum mean square error algorithm, adjustments can be made specifically for subcarriers with high interference values. For subcarriers with an interference value of 0.2, the algorithm iteratively adjusts the phase angle to reduce the interference to below 0.05, resulting in an orthogonalized second signal. This optimization effectively improves the independence between subcarriers and enhances the signal's anti-interference capability.

[0160] Next, when processing the third signal, a bandpass filter with a center frequency of 2.4 GHz and a bandwidth of 20 MHz can be designed to extract the target frequency band signal using a digital filter. This filter removes interference frequencies below 1 GHz and above 3 GHz, retaining only the target signal, thus obtaining a third signal with interference suppression. This method, through precise frequency selection, significantly reduces inter-carrier interference and improves signal purity.

[0161] Finally, the third signal can be combined with other subcarrier signals through weighted averaging. Assuming there are four subcarrier signals, the system assigns weights to each signal based on channel quality, such as 0.4, 0.3, 0.2, and 0.1. After weighted averaging, a stable transmitted data stream is obtained. This method balances the contributions of each signal through linear combination, ensuring the stability of the final data stream in complex channel environments.

[0162] In one possible implementation, the above scheme can be extended to multi-antenna systems. For example, in a MIMO system, the monitoring module simultaneously acquires attenuation and phase data from multiple signals, the equalizer compensates for each signal individually, and then, through orthogonal frequency division multiplexing and digital filtering, a stable multi-channel data stream is finally obtained. This extended scheme improves the overall throughput and reliability of the system through multi-channel coordination.

[0163] In step S19, when the packet loss rate of the stable transmission data stream is lower than a preset packet loss threshold, the signal energy distribution is adjusted and injected into the 10kV distribution network communication channel to complete data transmission, including:

[0164] When the packet loss rate of the stable transmission data stream is lower than the preset packet loss threshold, the energy distribution data of the stable transmission data stream is decomposed and the target frequency band energy component is extracted to obtain the energy distribution characteristics.

[0165] The signal modulation parameters are adjusted according to the energy distribution characteristics to obtain the modulated first signal.

[0166] Channel state monitoring is performed on the modulated first signal to obtain real-time channel state data. The channel capacity allocation scheme is determined by combining the real-time channel state data to obtain optimized channel allocation parameters.

[0167] The first signal is injected into the power distribution network communication channel, and the channel allocation parameters are integrated with the first signal to complete data transmission.

[0168] First, when the packet loss rate is below a preset threshold, signal energy distribution data can be obtained through time-domain analysis. An energy detection module is deployed at the receiving end to collect the signal's time-domain waveform in real time and analyze it to obtain energy distribution data for the stable transmitted data stream. Assuming a power distribution network scenario, the detection module finds that the signal energy is mainly concentrated in the 0.5 to 2 MHz frequency band, with peak energy accounting for 80% of the original signal. This analysis captures the signal's time-domain changes through sampling equipment, providing a reliable data foundation for subsequent processing.

[0169] Subsequently, the energy distribution data of the stable transmission data stream is decomposed using Fast Fourier Transform (FFT) to extract the energy components of the target frequency band and obtain the energy distribution characteristics. For example, in the aforementioned distribution network scenario, the system decomposes the signal into multiple frequency bands, extracts the energy components of the 1MHz band, and finds that it accounts for 60% of the total energy. This method, through frequency domain analysis, accurately separates the characteristics of the target frequency band, providing a basis for adjusting modulation parameters.

[0170] Next, the adaptive modulation method adjusts the signal modulation parameters according to the energy distribution characteristics. For example, for the energy components in the 1MHz band, the system selects 16-QAM modulation, increasing the modulation order to improve data transmission efficiency. The sine wave generator generates the modulated signal based on the adjusted parameters, obtaining the modulated first signal. This modulation method can dynamically adapt to the channel conditions, ensuring high efficiency in signal transmission.

[0171] Then, the system acquires real-time data on the channel status of the first signal through the monitoring module of the power distribution network communication channel, obtaining real-time channel status data, such as a signal-to-noise ratio of 20dB and a channel attenuation of 2dB. The support vector machine algorithm uses this data to determine a channel capacity allocation scheme and obtain optimized allocation parameters. Specifically, the algorithm allocates more bandwidth, such as 30MHz, to high signal-to-noise ratio channels to improve transmission efficiency. This method optimizes resource allocation through machine learning, enhancing the adaptability of the communication system.

[0172] Finally, during multi-signal synthesis, the system injects the first signal into the distribution network communication channel and integrates the channel optimization allocation parameters using a weighted averaging algorithm. Assuming there are three signals, the system assigns weights of 0.5, 0.3, and 0.2 based on channel quality. After weighted averaging, a stable data stream is obtained. This method balances the contributions of multiple signals through signal integration, ensuring the stability of the data stream in complex distribution network environments.

[0173] In summary, this invention discloses a 10kV high-power frequency carrier communication method based on pulse modulation, comprising: acquiring real-time power frequency signals, power grid load fluctuation data, and feedback signals of a 10kV distribution network; performing spectral characteristic analysis on the real-time power frequency signals to obtain a noise spectrum distribution; performing discrete pulse modulation based on the noise spectrum distribution to obtain an initial pulse coding sequence; analyzing the initial pulse coding sequence to determine the coding signal structure; when the data packet loss rate of the coding signal structure is higher than a preset packet loss threshold, adjusting the pulse duty cycle to obtain an optimized coding sequence; analyzing the power grid load fluctuation data to obtain a load change trend, and combining the load change trend to confirm the final dynamic transmission frequency. The synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold. Adaptive iterative control is then performed using the feedback signal to obtain a synchronization pulse signal. Subcarrier allocation and modulation are performed based on the synchronization pulse signal to obtain a modulated data stream. The modulated data stream undergoes an inverse fast Fourier transform and is combined with orthogonal subcarriers to obtain an initial transmission signal. Signal orthogonalization and signal synthesis are performed based on the initial transmission signal to obtain a stable transmission data stream. When the packet loss rate of the stable transmission data stream is lower than a preset packet loss threshold, the signal energy distribution is adjusted and injected into the 10kV distribution network communication channel to complete data transmission.

[0174] This invention achieves a significant reduction in data packet loss rate and improves the stability and reliability of 10kV distribution network communication by seamlessly integrating noise analysis, dynamic frequency adjustment, and channel optimization, providing an innovative solution for efficient data transmission in complex power grid environments.

[0175] Reference Figure 2 The second embodiment of the present invention provides a 10kV high-power frequency carrier communication device based on pulse modulation, comprising:

[0176] The signal acquisition module is used to acquire real-time power frequency signals, power grid load fluctuation data, and feedback signals of the 10kV distribution network.

[0177] The spectrum analysis module is used to perform spectrum characteristic analysis on the real-time power frequency signal to obtain the noise spectrum distribution;

[0178] The coding and modulation module is used to perform discrete pulse modulation based on the noise spectrum distribution to obtain an initial pulse coding sequence, and to analyze the initial pulse coding sequence to determine the structure of the coded signal.

[0179] The pulse adjustment module is used to adjust the pulse duty cycle to obtain an optimized encoding sequence when the data packet loss rate of the encoded signal structure is higher than a preset packet loss threshold.

[0180] The frequency confirmation module is used to analyze the power grid load fluctuation data to obtain the load change trend, and combine the load change trend to confirm the final dynamic transmission frequency range;

[0181] An iterative control module is used to perform adaptive iterative control in conjunction with the feedback signal to obtain a synchronization pulse signal when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold.

[0182] The signal synthesis module is used to allocate and modulate subcarriers according to the synchronization pulse signal to obtain a modulated data stream, perform inverse fast Fourier transform on the modulated data stream and combine it with orthogonal subcarriers to obtain an initial transmission signal;

[0183] The signal adjustment module is used to perform signal orthogonalization processing and signal synthesis based on the initial transmission signal to obtain a stable transmission data stream.

[0184] The data transmission module is used to adjust the signal energy distribution and inject it into the 10kV distribution network communication channel to complete data transmission when the data packet loss rate of the stable data transmission stream is lower than a preset packet loss threshold.

[0185] It should be noted that the 10kV high-power frequency carrier communication device based on pulse modulation provided in this embodiment of the invention is used to execute all the process steps of the 10kV high-power frequency carrier communication method based on pulse modulation in the above embodiment. The working principle and beneficial effects of the two are one-to-one, so they will not be described again.

[0186] This invention also provides an electronic device. The electronic device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a spectral characteristic analysis program. When the processor executes the computer program, it implements the steps described in the various embodiments of the 10kV strong power frequency carrier communication method based on pulse modulation, for example... Figure 1 The step S11 shown. Alternatively, when the processor executes the computer program, it implements the functions of each module in the above-described device embodiments, such as the information acquisition module.

[0187] For example, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0188] The electronic device may be a desktop computer, laptop, handheld computer, or smart tablet, etc. The electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. It may include more or fewer components than described above, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0189] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the electronic device, connecting all parts of the electronic device via various interfaces and lines.

[0190] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0191] Wherein, if the modules / units integrated in the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0192] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0193] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A 10kV high-power frequency carrier communication method based on pulse modulation, characterized in that, include: Acquire real-time power frequency signals, grid load fluctuation data, and feedback signals from the 10kV distribution network; The noise spectrum distribution is obtained by performing spectral characteristic analysis on the real-time power frequency signal. Based on the noise spectrum distribution, discrete pulse modulation is performed to obtain an initial pulse coding sequence, and the structure of the coded signal is determined by analyzing the initial pulse coding sequence. When the packet loss rate of the encoded signal structure is higher than the preset packet loss threshold, the pulse duty cycle is adjusted to obtain an optimized encoded sequence. The load fluctuation data of the power grid is analyzed to obtain the load change trend, and the final dynamic transmission frequency range is determined by combining the load change trend; When the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, adaptive iterative control is performed in conjunction with the feedback signal to obtain a synchronization pulse signal. The modulation data stream is obtained by subcarrier allocation and modulation based on the synchronization pulse signal, and the modulation data stream is then subjected to inverse fast Fourier transform and combined with orthogonal subcarriers to obtain the initial transmission signal. Based on the initial transmission signal, signal orthogonalization and signal synthesis are performed to obtain a stable transmission data stream; When the packet loss rate of the stable data stream is lower than the preset packet loss threshold, the signal energy distribution is adjusted and injected into the 10kV distribution network communication channel to complete the data transmission. Wherein, when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, adaptive iterative control is performed in conjunction with the feedback signal to obtain a synchronization pulse signal, including: When the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds the error threshold, the time deviation value is calculated through error detection. The final dynamic transmission frequency range is adjusted according to the time deviation value, and the feedback signal is segmented based on the final dynamic transmission frequency range to obtain the adjusted frequency value. By comparing the deviation between the real-time feedback signal and the adjusted frequency value, the trigger time of the pulse signal is dynamically updated, and finally a synchronous pulse signal with a period of 0.005 seconds is obtained.

2. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, The step of performing spectral characteristic analysis on the real-time power frequency signal to obtain the noise spectrum distribution includes: The original signal is obtained by analog-to-digital conversion based on the real-time power frequency signal; The original signal is filtered to obtain a preprocessed signal; Background noise components are extracted from the preprocessed signal to obtain background noise data; The background noise data is subjected to a fast Fourier transform to obtain the noise spectrum distribution curve; When the spectral value in the noise spectrum distribution curve exceeds the preset spectral threshold, it is marked as an abnormal frequency point to obtain the noise spectrum distribution.

3. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, The step of obtaining an initial pulse coding sequence by performing discrete pulse modulation based on the noise spectrum distribution, and analyzing the initial pulse coding sequence to determine the structure of the coded signal, includes: Spectral distribution data is obtained by performing spectral analysis based on the noise spectral distribution. When the noise energy in the spectral distribution data exceeds a preset energy threshold, noise suppression processing is performed on the spectral distribution data to obtain a denoised signal. The denoised signal is subjected to discrete pulse modulation coding to obtain an initial pulse coding sequence; The initial pulse coding sequence is subjected to Huffman coding compression to obtain the coded signal structure.

4. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, When the data packet loss rate of the encoded signal structure is higher than a preset packet loss threshold, the pulse duty cycle is adjusted to obtain an optimized encoded sequence, including: An initial data packet loss rate is obtained by monitoring the data packet loss rate of the encoded signal structure. The average loss rate is then calculated using a sliding window based on the initial data packet loss rate to obtain the first data packet loss rate value. When the first data packet loss rate exceeds the preset packet loss threshold, the pulse duty cycle increment ΔD is calculated to obtain the first pulse duty cycle value. Based on the first pulse duty cycle value, the structure of the encoded signal is reconfigured to obtain a first optimized encoded sequence; Signal transmission quality parameters are extracted from the first optimized coding sequence to obtain the optimized coding sequence.

5. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, The analysis of the power grid load fluctuation data to obtain the load change trend, and the determination of the final dynamic transmission frequency range based on the load change trend, includes: The periodic features are extracted from the power grid load fluctuation data to obtain the first load fluctuation sequence; The load change rate is obtained by performing a sliding window calculation on the first load fluctuation sequence. When the load change rate exceeds a preset change rate threshold, a first change trend curve is generated, and the load change trend is determined by combining the first change trend curve. The load change trend is linearly fitted to obtain the trend slope, and the frequency increment ΔF is adjusted according to the trend slope to obtain the first dynamic transmission frequency value; The transmission frequency is reconfigured based on the first dynamic transmission frequency value to obtain the final dynamic transmission frequency range.

6. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, The process of allocating and modulating subcarriers according to the synchronization pulse signal to obtain a modulated data stream, performing an inverse fast Fourier transform on the modulated data stream and combining it with orthogonal subcarriers to obtain an initial transmission signal includes: The channel quality index value is obtained by performing a fast Fourier transform on the spectral distribution of the synchronization pulse signal. The subcarriers are dynamically allocated based on the channel quality index values ​​to obtain a subcarrier allocation scheme. If the subcarrier allocation scheme meets the preset channel quality threshold, then QAM modulation is performed on the subcarrier data; if the subcarrier allocation scheme does not meet the preset channel quality threshold, then PSK modulation is performed on the subcarrier data to obtain the modulated data stream. The modulated data stream is subjected to inverse fast Fourier transform and combined with orthogonal subcarriers to obtain the initial transmission signal.

7. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, The step of performing signal orthogonalization processing and signal synthesis based on the initial transmitted signal to obtain a stable transmitted data stream includes: By monitoring the attenuation of the initial transmitted signal, channel state data is obtained. The amplitude and phase of the initial transmitted signal are then adjusted based on the channel state data to obtain a compensated first signal. The compensated first signal is decomposed into orthogonal subcarriers, and the interference value between the subcarriers is obtained based on the orthogonal subcarriers. The subcarrier phase is adjusted in combination with the obtained interference value between the subcarriers to obtain the orthogonalized second signal. The second signal is bandpass filtered to extract the target frequency band signal, resulting in a third signal with interference suppression. The third signal is integrated with other subcarrier signals to obtain a stable transmission data stream.

8. The 10kV high-power frequency carrier communication method based on pulse modulation according to claim 1, characterized in that, When the packet loss rate of the stable data stream is lower than a preset packet loss threshold, the signal energy distribution is adjusted and injected into the 10kV distribution network communication channel to complete data transmission, including: When the packet loss rate of the stable transmission data stream is lower than the preset packet loss threshold, the energy distribution data of the stable transmission data stream is decomposed and the target frequency band energy component is extracted to obtain the energy distribution characteristics. The signal modulation parameters are adjusted according to the energy distribution characteristics to obtain the modulated first signal. Channel state monitoring is performed on the modulated first signal to obtain real-time channel state data. The channel capacity allocation scheme is determined by combining the real-time channel state data to obtain optimized channel allocation parameters. The first signal is injected into the power distribution network communication channel, and the channel allocation parameters are integrated with the first signal to complete data transmission.

9. A 10kV high-power frequency carrier communication device based on pulse modulation, characterized in that, include: The signal acquisition module is used to acquire real-time power frequency signals, power grid load fluctuation data, and feedback signals of the 10kV distribution network. The spectrum analysis module is used to perform spectrum characteristic analysis on the real-time power frequency signal to obtain the noise spectrum distribution; The coding and modulation module is used to perform discrete pulse modulation based on the noise spectrum distribution to obtain an initial pulse coding sequence, and to analyze the initial pulse coding sequence to determine the structure of the coded signal. The pulse adjustment module is used to adjust the pulse duty cycle to obtain an optimized encoding sequence when the data packet loss rate of the encoded signal structure is higher than a preset packet loss threshold. The frequency confirmation module is used to analyze the power grid load fluctuation data to obtain the load change trend, and combine the load change trend to confirm the final dynamic transmission frequency range; An iterative control module is used to perform adaptive iterative control in conjunction with the feedback signal to obtain a synchronization pulse signal when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold. The signal synthesis module is used to allocate and modulate subcarriers according to the synchronization pulse signal to obtain a modulated data stream, perform inverse fast Fourier transform on the modulated data stream and combine it with orthogonal subcarriers to obtain an initial transmission signal; The signal adjustment module is used to perform signal orthogonalization processing and signal synthesis based on the initial transmission signal to obtain a stable transmission data stream. The data transmission module is used to adjust the signal energy distribution and inject it into the 10kV distribution network communication channel to complete data transmission when the data packet loss rate of the stable data transmission stream is lower than a preset packet loss threshold. Wherein, when the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds a preset error threshold, adaptive iterative control is performed in conjunction with the feedback signal to obtain a synchronization pulse signal, including: When the synchronization error between the final dynamic transmission frequency range and the optimized coding sequence exceeds the error threshold, the time deviation value is calculated through error detection. The final dynamic transmission frequency range is adjusted according to the time deviation value, and the feedback signal is segmented based on the final dynamic transmission frequency range to obtain the adjusted frequency value. By comparing the deviation between the real-time feedback signal and the adjusted frequency value, the trigger time of the pulse signal is dynamically updated, and finally a synchronous pulse signal with a period of 0.005 seconds is obtained.

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