Transformer polarity detection data transmission method, system and device

Abstract

The application relates to a mutual inductor polarity detection data transmission method, system and device, relates to the technical field of power data transmission, and can improve the stability of polarity detection data transmission. The method comprises the following steps: obtaining polarity detection data to be transmitted and an electromagnetic interference signal of a transmission environment of a mutual inductor; extracting an interference feature parameter set from the electromagnetic interference signal, matching the interference feature parameter set with a preset parameter matching library, determining transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters suitable for the transmission environment; configuring a radio frequency working frequency band based on the transmission frequency band parameters, generating a pseudo-random spread spectrum code corresponding to the spread spectrum sequence parameters, and determining convolution coding configuration based on the convolution constraint parameters; directly performing spread spectrum and convolution coding fusion modulation on the polarity detection data based on the pseudo-random spread spectrum code and the convolution coding configuration to generate a to-be-transmitted signal; and transmitting the to-be-transmitted signal through the radio frequency working frequency band.

Description

Technical Field

[0001] This application relates to the field of power data processing technology, and in particular to a method, system, device, computer equipment, computer-readable storage medium, and computer program product for transmitting data for transformer polarity detection. Background Technology

[0002] With the development of smart grids, the power system's requirements for the real-time and accuracy of equipment status monitoring within substations are increasing. In the routine operation and calibration of current and voltage transformers, polarity detection data is typically collected and transmitted remotely via wireless communication. However, substations are equipped with numerous high-voltage devices and power electronic devices, which generate strong and dynamically changing electromagnetic interference during operation.

[0003] Traditional technologies for wireless transmission of polarity detection data often rely on factory-preset fixed transmission channels and conventional, fixed modulation and coding rules. However, due to the highly complex and unpredictable electromagnetic environment within substations, this fixed transmission link configuration is completely detached from the actual channel conditions on-site. When sudden environmental noise frequencies overlap with fixed transmission frequencies or interference intensity increases dramatically, the communication link quality can easily deteriorate drastically. Therefore, addressing the problem of transmission parameters failing to adapt to on-site interference in complex electromagnetic environments, and the inherent error and packet loss issues caused by fixed configurations, resulting in substandard transmission stability and anti-interference capabilities, has become a pressing technical challenge in this field. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, system, device, computer equipment, computer-readable storage medium, and computer program product for transmitting data for mutual inductor polarity detection, in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a method for transmitting data for mutual inductor polarity detection, including:

[0006] Acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located;

[0007] The set of interference feature parameters is extracted from the electromagnetic interference signal, and the set of interference feature parameters is matched with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment.

[0008] Configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters;

[0009] Based on the pseudo-random spreading code and the convolutional coding configuration, the polarity detection data is fused and modulated by direct sequence spreading and convolutional coding to generate a signal to be transmitted.

[0010] The signal to be transmitted is transmitted through the radio frequency band.

[0011] In one embodiment, extracting the set of interference feature parameters from the electromagnetic interference signal includes:

[0012] The electromagnetic interference signal is filtered to obtain an effective interference signal;

[0013] The effective interference signal is divided into multiple interference data clusters by a clustering algorithm, and the target interference data cluster is selected from the multiple interference data clusters according to a preset sample number threshold.

[0014] Extract the feature parameter set corresponding to the target interference data cluster, and match the feature parameter set with a preset interference type standard feature database. Based on the matching result, determine the target interference type of the electromagnetic interference signal.

[0015] The set of interference feature parameters is determined based on the target interference type.

[0016] In one embodiment, determining the set of interference feature parameters based on the target interference type includes:

[0017] Standard interference signal samples are determined based on the statistical values ​​of characteristic parameters obtained from the target interference data cluster corresponding to the target interference type.

[0018] Spectral analysis is performed on the standard interference signal samples to obtain frequency band distribution characteristic parameters, and time series analysis is performed on the standard interference signal samples to obtain time series duration characteristic parameters.

[0019] When the standard interference signal sample is injected into a preset test link, the mechanism characteristic parameters are determined based on the transmission parameters of the test link obtained.

[0020] The set of interference characteristic parameters is determined based on the frequency band distribution characteristic parameters, the timing persistence characteristic parameters, and the mechanism characteristic parameters.

[0021] In one embodiment, the step of matching the set of interference feature parameters with a preset parameter matching library to determine the transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters suitable for the transmission environment includes:

[0022] The frequency band distribution characteristic parameters in the interference characteristic parameter set are matched with a preset frequency band matching library to determine the transmission frequency band parameters that are suitable for the transmission environment.

[0023] The target interference type in the interference feature parameter set is matched with a preset spread spectrum sequence matching library to determine the spread spectrum sequence parameters that are suitable for the transmission environment.

[0024] The mechanism feature parameters in the interference feature parameter set are matched with a preset convolution constraint matching library to determine the convolution constraint parameters that are suitable for the transmission environment.

[0025] In one embodiment, before performing direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolutional coding configuration, the method further includes:

[0026] Obtain the preset initial chaos key and chaos control parameters;

[0027] Based on the polarity detection data, the initial chaotic key, and the chaotic control parameters, a chaotic iterative operation is performed to obtain the chaotic encryption key;

[0028] The polarity detection data is superimposed with the chaotic encryption key to obtain an encrypted data sequence;

[0029] The step of performing direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolutional coding configuration includes:

[0030] The encrypted data sequence is fused and modulated using the pseudo-random spreading code and the convolutional coding configuration.

[0031] In one embodiment, the method further includes:

[0032] When the preset interference monitoring update cycle is reached, or when a feedback instruction corresponding to the signal to be transmitted is received, the step of obtaining the electromagnetic interference signal of the transmission environment where the transformer is located is re-executed to update the transmission frequency band parameters, the spread spectrum sequence parameters, and the convolution constraint parameters.

[0033] Secondly, this application also provides a data transmission system for mutual inductor polarity detection, the system comprising: a transmitter, a repeater, and a receiver;

[0034] The sending end is used to execute any of the methods described in the above embodiments;

[0035] The repeater is used to receive the signal to be transmitted sent by the transmitting end and forward the signal to be transmitted.

[0036] The receiving end is used to receive the signal to be transmitted forwarded by the repeater, and demodulate the signal to be transmitted based on the transmission frequency band parameters, spreading sequence parameters and convolution constraint parameters corresponding to the transmitting end, to obtain the demodulation result, and restore the polarity detection data of the mutual inductor according to the demodulation result.

[0037] In one embodiment, the receiving end is further configured to, if the demodulation result is an encrypted data sequence determined based on a preset chaotic initial key and chaotic control parameters, decrypt the encrypted data sequence using the preset chaotic initial key and chaotic control parameters to restore the polarity detection data of the mutual inductor.

[0038] In one embodiment, the system further includes: a transmission status monitoring module, configured to acquire data frames exchanged between the transmitter, the repeater, and the receiver, and determine multiple transmission indicators based on the data frames; when the transmission indicators indicate abnormal transmission, a corresponding feedback instruction is generated and sent to the transmitter;

[0039] The transmitting end is further configured to update the transmission frequency band parameters, the spreading sequence parameters, and the convolution constraint parameters in response to the feedback instruction, and generate a parameter synchronization instruction frame based on the updated transmission frequency band parameters, the spreading sequence parameters, and the convolution constraint parameters, and send the parameter synchronization instruction frame to the receiving end.

[0040] The receiving end is also used to receive the parameter synchronization instruction frame sent by the sending end, and parse it to obtain the transmission frequency band parameters, the spreading sequence parameters, and the convolution constraint parameters to complete parameter synchronization.

[0041] Thirdly, this application also provides a current transformer polarity detection data transmission device, comprising:

[0042] The data acquisition module is used to acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located.

[0043] The interference feature parameter acquisition module is used to extract a set of interference feature parameters from the electromagnetic interference signal, and match the set of interference feature parameters with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment.

[0044] The interference feature parameter configuration module is used to configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters.

[0045] The signal modulation module is used to perform direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolutional coding configuration to generate a signal to be transmitted.

[0046] A signal transmission module is used to transmit the signal to be transmitted via the radio frequency band.

[0047] Fourthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0048] Acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located;

[0049] The set of interference feature parameters is extracted from the electromagnetic interference signal, and the set of interference feature parameters is matched with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment.

[0050] Configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters;

[0051] Based on the pseudo-random spreading code and the convolutional coding configuration, the polarity detection data is fused and modulated by direct sequence spreading and convolutional coding to generate a signal to be transmitted.

[0052] The signal to be transmitted is transmitted through the radio frequency band.

[0053] Fifthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0054] Acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located;

[0055] The set of interference feature parameters is extracted from the electromagnetic interference signal, and the set of interference feature parameters is matched with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment.

[0056] Configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters;

[0057] Based on the pseudo-random spreading code and the convolutional coding configuration, the polarity detection data is fused and modulated by direct sequence spreading and convolutional coding to generate a signal to be transmitted.

[0058] The signal to be transmitted is transmitted through the radio frequency band.

[0059] Sixthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0060] Acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located;

[0061] The set of interference feature parameters is extracted from the electromagnetic interference signal, and the set of interference feature parameters is matched with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment.

[0062] Configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters;

[0063] Based on the pseudo-random spreading code and the convolutional coding configuration, the polarity detection data is fused and modulated by direct sequence spreading and convolutional coding to generate a signal to be transmitted.

[0064] The signal to be transmitted is transmitted through the radio frequency band.

[0065] The aforementioned method, system, device, computer equipment, computer-readable storage medium, and computer program product for transmitting polarity detection data of current transformers acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located; extract a set of interference feature parameters from the electromagnetic interference signal, and match the set of interference feature parameters with a preset parameter matching library to determine the transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters suitable for the transmission environment; configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolution coding configuration based on the convolution constraint parameters; perform direct sequence spreading and convolution coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolution coding configuration to generate the signal to be transmitted; and transmit the signal to be transmitted through the radio frequency operating frequency band. In this application, by actively collecting electromagnetic interference signals from the transmission environment of the instrument transformer and extracting interference feature sets, the traditional blind transmission mode of equipment is changed. Furthermore, by using this feature set to dynamically determine the transmission frequency band, spreading sequence, and convolution constraint parameters adapted to the current environment in a preset matching library, and by performing fusion modulation of direct sequence spreading and convolutional coding on the service data sequence based on these adaptive parameters, it is possible to specifically avoid the congested interference frequency bands in the field and improve the error correction and penetration capabilities of the signal. This effectively reduces the bit error rate and packet loss rate of polarity detection data during transmission in complex electromagnetic environments, and ensures the stability of instrument transformer polarity detection data transmission. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a flowchart illustrating a method for transmitting data to detect the polarity of a current transformer in one embodiment.

[0068] Figure 2 This is a flowchart illustrating the data transmission method for mutual inductor polarity detection in another embodiment;

[0069] Figure 3 This is a structural block diagram of a current transformer polarity detection data transmission device in one embodiment;

[0070] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0072] The instrument transformer polarity detection data method provided in this application can be applied to technical fields such as power system automation, intelligent substation construction, and high-voltage power grid operation and maintenance. It is particularly suitable for the safe, stable, adaptive transmission and intelligent monitoring of current and voltage instrument transformer polarity detection data in complex electromagnetic interference environments at substations. In actual power field operations, the electromagnetic environment of the instrument transformer deployment area and wireless transmission path is often extremely complex and variable due to the interplay of strong electric and magnetic fields. The critical data generated by polarity detection needs to be transmitted efficiently, continuously, and securely to the main control room or remote control center via wireless or wired networks, so that maintenance personnel or power automation management systems can accurately monitor and manage the polarity status of power equipment.

[0073] The network topology to which this method is applicable can be composed of an interactive data acquisition and transmission side, a signal relay side, a data receiving side, and a full-process status monitoring side. For example, this application environment can physically or logically include a transmitter, a repeater, a receiver, and an integrated transmission status monitoring module. The transmitting end can be deployed or integrated at the transformer polarity detection site to sense radio electromagnetic interference in the substation and perform anti-interference and link configuration processing on the polarity detection data to be transmitted. The repeater can be flexibly deployed on the spatial communication path between the transmitting and receiving ends to verify, correct, and relay the transmitted encrypted or modulated signals to overcome multipath fading and extend signal coverage in complex environments. The receiving end is usually deployed in the control room, mobile maintenance terminal, or remote management server to demodulate and restore the polarity detection data. The integrated transmission status monitoring module can operate independently as a monitoring server or be integrated as a software component into the background maintenance terminal or cloud power management platform. It maintains full-process data index capture and interaction with the transmitting end, repeater, and receiving end to provide closed-loop optimization and control support without manual intervention.

[0074] It should be noted that the communication methods and network standards between the aforementioned transmitter, repeater, receiver, and transmission status monitoring module are not strictly limited. Data connections can be established using various wireless communication technologies (such as cellular mobile networks, Wi-Fi, dedicated wireless data transmission radios, etc.) or wired communication methods (such as fiber optic communication, power line carrier communication, etc.). Furthermore, the components in the aforementioned application environment can be physically independent single devices, or, depending on the actual needs of power field integration, logical fusion and software integration of some functional modules can be implemented (for example, the functions or algorithms of the monitoring module can be directly embedded in the receiver, repeater, or backend maintenance terminal). This application does not impose specific limitations in this regard; any system, device internal structure, or network operating environment that can provide similar communication links, multi-terminal interaction, and closed-loop feedback control architecture falls within the scope of this application's technical solution.

[0075] In one exemplary embodiment, such as Figure 1 As shown, a method for transmitting data to detect the polarity of a current transformer is provided. Taking the application of this method to the transmitting end in the above embodiment as an example, the method includes the following steps S101 to S105. Wherein:

[0076] S101, acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment where the transformer is located.

[0077] Among them, the polarity detection data to be transmitted can be the routine electrical test results of current and voltage transformers during daily inspections or equipment commissioning, which reflect their polarity status. It is mainly used to provide data basis for the background to evaluate the operating status of the power system. It can be directly output from the on-site polarity detection equipment and preliminarily sorted to form a data sequence in a unified format.

[0078] Electromagnetic interference signals can be various spatial electromagnetic waves and radio frequency background noise that exist in complex electrical environments such as substations and may cause fading or noise injection into wireless channels. They are mainly used to characterize the interference situation faced by the current wireless transmission path. They can be environmental waveforms collected by sensing units arranged around the transformer.

[0079] Specifically, when the data transmission process is initiated, the polarity detection data to be transmitted is acquired. At the same time, the electromagnetic interference signal of the transmission environment where the current transformer is located is acquired through the corresponding radio frequency antenna or signal acquisition unit, which serves as the input source for subsequent anti-interference transmission strategies.

[0080] Optionally, during the process of acquiring polarity detection data to be transmitted, the original detection file transmitted by the external detection device can be received, and its protocol parsing and formatting can be performed to remove redundant fields and form a standardized original data sequence with a unified format, so as to facilitate subsequent unified encoding and encryption processing. When acquiring electromagnetic interference signals in the transmission environment where the instrument transformer is located, a full-band broadband scan or a periodic monitoring method for a specific operating frequency band can be used to collect spatial electromagnetic interference waveforms in the instrument transformer deployment area and the expected wireless transmission path within the substation. The basic parameters such as the amplitude and frequency range of these signals can be recorded, and they can be summarized into an electromagnetic interference original signal dataset.

[0081] S102, extract the set of interference feature parameters from the electromagnetic interference signal, and match the set of interference feature parameters with the preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters suitable for the transmission environment.

[0082] Among them, the set of interference characteristic parameters can be a set of data obtained after multi-dimensional abstraction and analysis of the original complex waveform. It is mainly used to characterize the physical properties and behavior patterns of the current interference source. It can be formed by extracting electromagnetic interference signals based on mathematical transformation or related analysis algorithms, and may include specific values ​​such as interference center frequency, pulse duty cycle or energy envelope.

[0083] The preset parameter matching library can be a pre-built and stored set of mapping relationship data, mainly used to provide corresponding anti-interference strategies for different types of interference features. It can be formed based on a large amount of historical operation data and field test experience, such as a correspondence table between feature range and communication configuration recorded in the form of a decision matrix.

[0084] Transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters can be communication configuration instructions for anti-interference of wireless communication links. They are mainly used to guide the radio frequency and baseband processing to reconstruct the signal transmission pattern. Among them, the transmission frequency band parameters can be the specified carrier center frequency, the spreading sequence parameters can be the pseudo-random sequence code pattern or code length used to broaden the signal, and the convolution constraint parameters can be the constraint length or coding rate used for forward error correction coding, etc.

[0085] Specifically, after acquiring the electromagnetic interference signal in the environment, the inherent interference characteristics of the signal are extracted to generate a set of interference feature parameters that can characterize the strength and pattern of interference in the current transmission space. Subsequently, a pre-configured parameter matching library is retrieved, and the extracted set of interference feature parameters is used as the search input condition to compare and search in the matching library, thereby determining a set of anti-interference parameters suitable for the current transmission environment, that is, obtaining the transmission frequency band parameters, spread spectrum sequence parameters, and convolution constraint parameters adapted to the transmission environment.

[0086] Optionally, when extracting the set of interference feature parameters, a pre-trained lightweight machine learning model can be used to directly map the feature vectors of the electromagnetic interference signal sequence within a sliding window period, outputting a feature tensor with representational capabilities as the parameter set. Alternatively, wavelet packet decomposition can be used to extract the energy ratio of each frequency band as the feature input. When performing parameter matching, in order to replace the traditional table lookup matching method, a rule engine-based judgment algorithm can be introduced. For example, when an interference feature is detected to cover the current working channel and its energy is greater than a preset judgment value, the new frequency band parameters to avoid the frequency band, the spreading sequence parameters corresponding to the interference intensity, and the convolution constraint parameters can be directly derived and output according to the preset logical rules or decision tree model, so as to further improve the response speed of parameter configuration and the flexibility of dynamic environmental adaptation.

[0087] S103, configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters.

[0088] The radio frequency operating frequency band can be the specific physical spectrum range occupied when transmitting signals. It is mainly used to carry the polarity detection data after modulation and broadening. It can be determined by setting the voltage-controlled oscillator of the internal radio frequency transceiver based on the transmission frequency band parameters, such as a specific microwave band or a specified channel center frequency.

[0089] Pseudo-random spreading codes can be binary sequences that have statistical properties similar to white noise but are actually deterministic and reproducible. They are mainly used to broaden the spectrum of data signals to reduce power spectral density and improve resistance to multipath interference. They can be generated based on spreading sequence parameters (such as a given generator polynomial or initial seed) through algorithms such as linear feedback shift registers, for example, Gold codes or m-sequences with excellent autocorrelation.

[0090] Convolutional coding configuration can be used to set the working mode of forward error correction coding logic. It is mainly used to introduce controlled redundancy check information into the data stream to be sent so as to correct random bit errors when the signal-to-noise ratio is poor. It can be directly determined based on convolutional constraint parameters, such as specific coding constraint length and generator polynomial vector settings.

[0091] Specifically, after determining the anti-interference parameters suitable for the transmission environment, the operating frequency band of the internal wireless communication RF front-end is configured based on the obtained transmission frequency band parameters, so that subsequent signal transmissions accurately fall within the target frequency band range of the anti-interference plan. At the same time, the determined spreading sequence parameters are extracted, and a pseudo-random sequence generation algorithm is activated to generate a pseudo-random spreading code that matches the spreading sequence parameters, in preparation for subsequent code domain widening. In addition, based on the determined convolution constraint parameters, the convolutional coding configuration of the underlying convolutional coding logic is set, and the coding rate and shift register level configuration of the convolutional coding module are completed.

[0092] S104, based on pseudo-random spreading code and convolutional coding configuration, performs direct sequence spreading and convolutional coding fusion modulation on polarity detection data to generate the signal to be transmitted.

[0093] Direct sequence spread spectrum and convolutional coding fusion modulation can be a baseband signal processing mechanism that combines error correction coding technology with spectrum stretching technology. It is mainly used to inject redundant verification information and pseudo noise features into the original service bit stream at the same time. It can be implemented based on a pre-set underlying digital signal processing algorithm or application-specific integrated circuit architecture.

[0094] The signal to be transmitted can be a baseband complex frequency domain waveform that conforms to the physical layer specification of a specific interface after being fused and modulated by direct sequence spread spectrum and convolutional coding. It is mainly used to carry polarity state information after anti-interference hardening, and can be an orthogonal amplitude modulation or phase shift keying analog signal sequence that has been loaded onto a specific carrier frequency.

[0095] Specifically, after the assembly of the anti-interference underlying parameters is completed, based on the generated pseudo-random spreading code and the determined convolutional coding configuration, the polarity detection data to be transmitted is subjected to baseband-level direct sequence spreading and convolutional coding fusion modulation processing to complete the conversion from the original service data to a physical layer waveform with anti-interference capability, and finally generate a signal to be transmitted that can be directly transmitted through the radio frequency antenna.

[0096] Optionally, in the process of fusing direct sequence spread spectrum and convolutional coding modulation, a serial processing architecture can be adopted. First, forward error correction coding is performed on the polarity detection data to be transmitted according to the convolutional coding configuration, and a data stream with parity bits is output. Then, the data stream is subjected to high-rate bit-by-bit XOR widening processing using pseudo-random spreading codes. Alternatively, in order to further reduce the latency of baseband processing, a parallel mapping modulation scheme can be adopted, which maps the chip sequence of direct sequence spread spectrum with the grid state of convolutional coding to a joint constellation diagram, and directly generates the fused modulation symbols on the complex plane. In addition, before generating the signal to be transmitted, additional pulse shaping filtering processing (e.g., using a root-raised cosine filter) can be applied to the fused modulation baseband chip sequence to smooth the signal trajectory, compress out-of-band radiation, and reduce inter-symbol interference, thereby further improving the spectral utilization efficiency and transmission quality of the signal to be transmitted.

[0097] S105 transmits the signal to be transmitted via the radio frequency operating band.

[0098] Specifically, after completing various fusion modulation operations and generating the signal to be transmitted, the enable control of the underlying radio frequency transmission link is triggered. Through the radio frequency operating frequency band that has been adaptively configured, the signal to be transmitted is sent out in the form of spatial electromagnetic waves, so that it officially enters the wireless space channel at the substation site for propagation.

[0099] Optionally, in order to further optimize transmission performance during the transmission of the signal to be transmitted through the radio frequency operating band, an adaptive transmit power control mechanism can be combined. Before transmission, the fading degree of the current radio frequency operating band can be estimated based on historical interaction records, and the output gain of the radio frequency power amplifier can be dynamically adjusted to ensure that the signal is radiated at the most reasonable power level while meeting the signal-to-noise ratio requirements. Alternatively, multi-antenna transmit diversity technology (such as radio frequency beamforming or space-time group transmission) can be used. Multiple physical antenna arrays distributed outside the equipment can be used to jointly transmit the signal to be transmitted on the same designated radio frequency operating band with different phases or time delays. This can further enhance the signal's ability to resist multipath fading in the field without increasing additional spectrum resource consumption, by utilizing spatial multiplexing and diversity gain.

[0100] In this embodiment, by actively collecting electromagnetic interference signals from the transmission environment of the instrument transformer and extracting interference feature sets, the traditional blind transmission mode of equipment is changed. Furthermore, the feature sets are used to dynamically determine the transmission frequency band, spreading sequence, and convolution constraint parameters suitable for the current environment in a preset matching library. Based on these adaptive parameters, the service data sequence is fused and modulated with direct sequence spreading and convolutional coding. This can specifically avoid the congested interference frequency bands in the field and improve the error correction and penetration capabilities of the signal, thereby effectively reducing the bit error rate and packet loss rate of polarity detection data during transmission in complex electromagnetic environments and ensuring the stability of instrument transformer polarity detection data transmission.

[0101] In one embodiment, the set of interference feature parameters is extracted from the electromagnetic interference signal, including:

[0102] The electromagnetic interference signal is filtered to obtain an effective interference signal. The effective interference signal is then divided into multiple interference data clusters using a clustering algorithm. The target interference data cluster is selected from these clusters based on a preset sample size threshold. The feature parameter set corresponding to the target interference data cluster is extracted and matched with a preset interference type standard feature database. The target interference type of the electromagnetic interference signal is determined based on the matching results. Finally, the set of interference feature parameters is determined based on the target interference type.

[0103] Among them, the effective interference signal can be a set of electromagnetic waveforms with certain regularity and interference threat remaining after filtering out conventional environmental white noise and occasional burst noise. It is mainly used as a high-quality input sample for subsequent cluster analysis. It can be obtained by processing the original collected electromagnetic interference signal based on bandpass filter or digital denoising algorithm.

[0104] Interference data clusters can be groups of electromagnetic signal samples with similar physical behavior and feature distribution in a multidimensional feature space. They are mainly used to structurally classify and compress chaotic field interference. They can be divided based on the distance calculation between a large number of effective interference signal feature vectors using unsupervised learning algorithms.

[0105] The target interference data cluster can be a set of data representing typical interference categories that are persistent and dominant in the current substation site, with an internal sample size that meets a predetermined standard. It can be obtained by determining and filtering multiple initial interference data clusters based on a preset sample size threshold.

[0106] The target interference type can be the specific electromagnetic interference category that has the most significant impact on the wireless link in the current transmission environment. It is mainly used to provide a clear directional index for subsequent retrieval of the corresponding anti-interference strategy. It can be determined based on the similarity comparison between the feature parameter set extracted on site and the preset interference type standard feature database.

[0107] Specifically, the system first receives the acquired electromagnetic interference signal as input data and performs filtering on it. By filtering out useless or abnormal waveform components, it outputs a cleaned, effective interference signal. Then, the effective interference signal is input into a clustering processing logic. A clustering algorithm is used to calculate the distance or similarity between signal data, grouping similar data together and outputting multiple independent interference data clusters. To eliminate interference from sporadic data, the number of samples in each interference data cluster is compared with a preset sample quantity threshold. Clusters that reach or exceed this threshold are selected and retained, thus outputting the core target interference data cluster. Next, corresponding feature data is extracted from the target interference data cluster to generate a structured feature parameter set. This feature parameter set is used as a retrieval input and compared and matched in a preset interference type standard feature database. Based on the matching result (such as the highest matching degree), the target interference type of the current electromagnetic interference signal is determined. Finally, using the target interference type as a mapping basis, the set of interference feature parameters used to characterize the current environmental situation is retrieved and determined.

[0108] For example, in a practical application of processing electromagnetic interference signals at a substation site to identify the main interference types, the raw electromagnetic interference signal dataset collected and summarized across the entire area is preprocessed with filtering to obtain a clean and effective interference signal dataset. Next, the K-means clustering algorithm is used to cluster the effective interference signals, extracting interference feature parameters to construct a sample set, and iteratively optimizing the cluster centers to complete the clustering process, resulting in several different interference data clusters. Subsequently, based on a set sample size threshold, these clusters are size-determined, and discrete clusters that are occasional are removed to obtain the main interference data clusters (i.e., target interference data clusters). The core feature parameters of the interference signals within these clusters are extracted and integrated to form the corresponding feature parameter set. Finally, each feature parameter set is matched with a preset interference type standard feature database for similarity, and the corresponding interference type is determined based on the matching results. All interference types are then summarized to form a set of main interference types at the substation site.

[0109] In this embodiment, by filtering the electromagnetic interference signal, using clustering algorithms to divide and screen it, and matching it with a standard feature database to determine the target interference type, the system effectively cleans up the complex background noise in a complex electromagnetic environment and accurately transfers and locks the internal data of the dominant interference source. This lays a solid and reliable data foundation for the subsequent generation of highly adaptable and targeted low-level anti-interference transmission parameters.

[0110] In one embodiment, a set of interference characteristic parameters is determined based on the target interference type, including:

[0111] Based on the statistical values ​​of characteristic parameters obtained from the target interference data cluster corresponding to the target interference type, standard interference signal samples are determined; spectral analysis is performed on the standard interference signal samples to obtain frequency band distribution characteristic parameters, and time series analysis is performed on the standard interference signal samples to obtain time series persistence characteristic parameters; when the standard interference signal samples are injected into a preset test link, the mechanism characteristic parameters are determined based on the transmission parameters of the obtained test link; based on the frequency band distribution characteristic parameters, time series persistence characteristic parameters, and mechanism characteristic parameters, the set of interference characteristic parameters is determined.

[0112] Among them, the statistical value of the feature parameter can be the central expectation value obtained by performing mathematical statistics on the feature values ​​of a certain type of interference group in multiple physical dimensions. It is mainly used to smooth out extreme noise deviations in individual samples to accurately characterize the most typical state of this type of interference. It can be obtained by performing an arithmetic mean calculation on all core data elements in the target interference data cluster.

[0113] Standard interference signal samples can be representative signal sequences extracted manually or by algorithms that can reconstruct the patterns of real interference waveforms. They can be determined by waveform reconstruction or sample mapping based on the aforementioned characteristic parameter mean.

[0114] Frequency band distribution characteristic parameters can be data indicators that quantitatively describe the distribution range of interference energy in the frequency domain.

[0115] The timing persistence characteristic parameter can be a data index that describes the fluctuation pattern of the interference signal on the time axis, pulse width, or duty cycle.

[0116] Mechanism characteristic parameters can be quantitative indicators that reflect the actual degree of damage or coupling mode caused by different types of interference to the communication link.

[0117] Specifically, the system receives the determined target interference type and its mapped target interference data cluster as input data. Statistical operations are performed on all characteristic parameters contained within the target interference data cluster to calculate and output the mean value of the characteristic parameters. Subsequently, using this mean value as the basis for reconstruction, a standard interference signal sample representing the target interference type is determined. Next, this standard interference signal sample is input into different analysis logics: on one hand, spectral analysis is performed on the standard interference signal sample to extract its frequency domain energy structure and output frequency band distribution characteristic parameters; on the other hand, time-series analysis is performed on the standard interference signal sample to extract its time domain period or pulse pattern and output time-series persistence characteristic parameters. Furthermore, the standard interference signal sample is used as a simulated interference source and injected into a preset test link logic. By monitoring the operating status of the test link under this interference condition, corresponding transmission parameters are obtained, and based on these transmission parameters, the mechanism characteristic parameters are logically derived and output. Finally, the frequency band distribution characteristic parameters, time-series persistence characteristic parameters, and mechanism characteristic parameters calculated above are summarized and integrated to establish and output a complete set of interference characteristic parameters.

[0118] For example, in practical applications of extracting interference features and constructing a global feature parameter set, the following steps are taken: First, the mean values ​​of core parameters are extracted from the main interference data clusters corresponding to various types of interference, and standard interference signal samples are generated based on these. Next, spectral analysis is performed on the standard interference signal samples to form a subset of frequency band distribution feature parameters. Simultaneously, time-series analysis is performed on the standard interference signal samples to form a subset of time-series persistence feature parameters. In addition, a test link consistent with the actual transmission parameters of the substation is built, and standard interference signal samples are injected into the link and their actual transmission parameters (such as the degree of signal-to-noise ratio degradation, bit error rate increment, etc.) are collected to form a subset of mechanism feature parameters. Finally, the above three types of feature parameter subsets are integrated to form a complete feature parameter set for a single type of interference, and the complete feature parameter sets for all types of interference are further summarized to construct a global feature parameter set for the main interference types in the substation.

[0119] In this embodiment, standard interference signal samples are determined based on the mean value of feature parameters. Spectrum analysis, time-series analysis, and transmission parameters are obtained from the test link to determine the feature parameters in three dimensions. This effectively avoids blind spots in anti-interference strategies that may result from single-dimensional feature extraction, and provides comprehensive and reliable data support for subsequent accurate matching of transmission frequency bands, spread spectrum sequences, and convolution constraint parameters to suit the actual conditions of the substation.

[0120] In one embodiment, the set of interference feature parameters is matched with a preset parameter matching library to determine the transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters suitable for the transmission environment, including:

[0121] The frequency band distribution feature parameters in the interference feature parameter set are matched with a preset frequency band matching library to determine the transmission frequency band parameters suitable for the transmission environment; the target interference type in the interference feature parameter set is matched with a preset spread spectrum sequence matching library to determine the spread spectrum sequence parameters suitable for the transmission environment; and the action mechanism feature parameters in the interference feature parameter set are matched with a preset convolution constraint matching library to determine the convolution constraint parameters suitable for the transmission environment.

[0122] Among them, the frequency band matching library can be a pre-built, structured collection of data that stores the mapping relationship between known interference frequency ranges and optimal wireless communication channels. It can be formed by integrating historical anti-interference communication test data and spectrum occupancy statistical analysis.

[0123] Spread spectrum sequence matching library can be a data set that records the association rules between various electromagnetic interference modes and different pseudo-random sequences (such as code length and code pattern). It can be derived from a large number of simulation experimental results on resistance to multipath fading and burst noise.

[0124] The convolution constraint matching library can be a set of configurations that maps the correspondence between the physical impairment of the link and the forward error correction coding parameters. It can be established based on the theoretical deduction of channel capacity and coding gain in information theory and the measured bit error correction.

[0125] Specifically, frequency band distribution feature parameters contained in the interference feature parameter set are extracted as retrieval inputs. Data comparison and association retrieval operations are performed in a preset frequency band matching library. Based on the mapping relationship recorded in the library, transmission frequency band parameters suitable for the current transmission environment are filtered and output. Simultaneously or subsequently, target interference type data in the interference feature parameter set are extracted and input into a preset spread spectrum sequence matching library for table lookup or rule comparison logic processing. Spread spectrum sequence parameters that can effectively cope with the interference type and are suitable for the transmission environment are output. In addition, mechanism feature parameters in the interference feature parameter set are obtained. The parameters are quantitatively evaluated and their corresponding relationships are retrieved using a preset convolution constraint matching library. Convolution constraint parameters that meet the current link error correction requirements and are suitable for the transmission environment are calculated and output.

[0126] For example, in the practical application of generating a complete set of basic anti-interference parameters, it is first necessary to build an interference frequency band-transmission frequency band matching database. After obtaining the interference characteristic parameters, the database is matched and filtered according to the main interference frequency band combinations on site to obtain the appropriate transmission frequency band parameters to avoid the current interference frequency band. Next, an interference type set-spreading sequence matching database is built. According to the main interference type combinations identified on site, rule matching is performed in the database to obtain spread spectrum sequence parameters that are suitable for the current interference mode and intensity. In addition, an interference feature-convolution operation constraint parameter matching database is built. According to the interference mechanism feature combination extracted on site, deep matching calculation is performed to obtain convolution constraint parameters that are suitable for the current channel impairment level. Finally, the transmission frequency band parameters, spread spectrum sequence parameters, and convolution constraint parameters obtained by matching and filtering are summarized and integrated to form a complete set of basic anti-interference parameters that can comprehensively adapt to the main interference types on the substation site.

[0127] In this embodiment, by performing targeted matching calculations between frequency band distribution characteristic parameters, target interference type, and mechanism characteristic parameters and corresponding preset frequency band matching libraries, spread spectrum sequence matching libraries, and convolution constraint matching libraries, the accurate translation and mapping of multi-dimensional abstract physical interference characteristics to underlying specific communication configuration parameters is realized, thereby improving the dynamic adaptability and overall stability of polarity detection data transmission links in complex electromagnetic environments such as substations.

[0128] In one embodiment, before performing direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and convolutional coding configuration, the method further includes:

[0129] Obtain the preset initial chaotic key and chaotic control parameters; perform chaotic iterative calculations based on polarity detection data, the initial chaotic key, and the chaotic control parameters to obtain the chaotic encryption key; superimpose the polarity detection data and the chaotic encryption key to obtain the encrypted data sequence.

[0130] Based on pseudo-random spreading codes and convolutional coding configurations, polarity detection data is fused and modulated using direct sequence spreading and convolutional coding, including:

[0131] By using pseudo-random spreading codes and convolutional coding configurations, the encrypted data sequence is fused and modulated using direct sequence spreading and convolutional coding.

[0132] The initial chaotic key can be a data sequence used as an initial value for a nonlinear dynamic system, which is pre-set during the establishment of a secure communication connection. It can be generated based on a secure negotiation mechanism or key management protocol between the sender and receiver.

[0133] Chaotic control parameters can be coefficient indices used to regulate the evolutionary behavior and branching characteristics of nonlinear dynamic equations. They are mainly used to determine the ergodicity and distribution boundary of the generated random sequence, and can also be established based on negotiation synchronization.

[0134] Chaotic encryption keys can be cryptographic sequences generated after the aforementioned nonlinear evolution and quantization extraction to mask real business data. They are mainly used to obfuscate and scramble the core information to be transmitted at the physical level. They can be represented as binary encoded streams with a specific length and random distribution.

[0135] Encrypted data sequences can be masked bit streams that have been mixed and masked and no longer have their original physical meaning at the data link layer. They are mainly used to replace plaintext data (polarity detection data) as a secure input carrier for subsequent modulation.

[0136] Specifically, before performing direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and convolutional coding configuration, a preset chaotic initial key and chaotic control parameters are first obtained as control inputs for the encryption process. Subsequently, the polarity detection data to be transmitted, the obtained chaotic initial key, and the chaotic control parameters are input into the computational logic. Based on these inputs, chaotic iterative operations are performed. After multiple rounds of mathematical mapping and evolution, a chaotic encryption key with high pseudo-randomness is derived and output. Next, the polarity detection data and the generated chaotic encryption key are sent to the data processing module for superposition processing. Through specific merging logic, the feature arrangement of the original data is changed, and the mixed encrypted data sequence is output. Finally, when performing low-level anti-interference modulation, the polarity detection data to be sent is replaced with the masked encrypted data sequence. That is, the direct sequence spreading and convolutional coding fusion modulation processing is performed on the encrypted data sequence using the pseudo-random spreading code and convolutional coding configuration determined in the previous steps.

[0137] For example, in a practical application of encrypting the polarity detection data of substation instrument transformers to form a low-level encrypted data sequence, the process begins by taking the standardized original data sequence (i.e., the processed polarity detection data) and the chaotic initial key and chaotic control parameters pre-negotiated by the multi-link management module at both ends as inputs. Discrete chaotic iterative operations are then performed within the internal encryption chip. This iterative operation continues until a continuous chaotic floating-point sequence matching the length of the standardized original data sequence is generated. Next, the generated chaotic floating-point sequence is converted into a discrete decimal number according to a preset quantization rule, and this decimal number is... The sequence is further converted into a fixed-bit binary code, which is then concatenated and truncated in an iterative order to form a binary chaotic encryption key sequence. Subsequently, using a standard bitwise XOR reversible operation, the standardized original data sequence is superimposed and encrypted bit by bit with the aforementioned binary chaotic encryption key sequence. This bit-by-bit encryption operation masks the entire sequence, ultimately generating the underlying encrypted data sequence. Finally, using this underlying encrypted data sequence and the generated pseudo-random spreading code as input, direct sequence spreading and convolutional coding fusion modulation are performed to generate the encrypted signal to be transmitted and input it into the repeater.

[0138] In this embodiment, a chaotic encryption key is generated by performing chaotic iterative calculations on a preset chaotic initial key and chaotic control parameters. The polarity detection data is then superimposed with the key to form an encrypted data sequence, which is then fused and modulated. This achieves the goal of effectively preventing the illegal theft, tampering, or forgery of polarity detection sensitive data in the open and complex wireless space channel of a substation without disrupting the physical layer spread spectrum communication timing. Furthermore, the chaotic encryption protection of the data link layer and the spread spectrum error correction and anti-interference mechanism of the physical layer are deeply integrated, constructing a dual high-reliability guarantee system that balances data security defense and channel transmission stability.

[0139] In one embodiment, the method further includes:

[0140] When the preset interference monitoring update cycle is reached, or when a feedback instruction corresponding to the signal to be transmitted is received, the step of obtaining the electromagnetic interference signal of the transmission environment where the transformer is located is re-executed in order to update the transmission frequency band parameters, spread spectrum sequence parameters, and convolution constraint parameters.

[0141] The preset interference monitoring update cycle can be a time interval indicator set in advance to deal with the slow time-varying characteristics of wireless communication links. It is a time trigger condition for actively initiating a reassessment of the current transmission environment status. It can be flexibly configured based on the historical fluctuation pattern of the electromagnetic situation at the substation site or the timeliness requirements of the business, such as being set as a cyclic timer for several minutes or several hours.

[0142] Feedback instructions can be control data packets carrying the current transmission link quality assessment results or abnormal warning information. They are mainly used to provide passive parameter reconstruction control signals when communication is blocked due to sudden strong interference. They can be generated based on connectivity statistics or error determination of the underlying interactive data frames.

[0143] Specifically, during continuous data transmission, timing and status monitoring logic are simultaneously activated. When the current running time reaches the preset interference monitoring update cycle, or when a feedback instruction is received for the signal to be transmitted, the parameter reconstruction and environmental reassessment process is triggered. In response to this triggering condition, the step of acquiring the electromagnetic interference signal of the transmission environment where the current transformer is located is re-executed, and the latest acquired field electromagnetic waveform is used as the new environmental input basis. Subsequently, the relevant feature extraction and matching calculation process is executed sequentially. Based on the latest acquired electromagnetic interference signal, the transmission frequency band parameters, spread spectrum sequence parameters, and convolution constraint parameters are recalculated and updated, and the latest underlying anti-interference configuration adapted to the current environmental situation is output.

[0144] For example, on the one hand, an adaptive interference monitoring update cycle can be preset. When the preset cycle is reached, the entire process of substation interference signal acquisition, main interference type determination, interference feature extraction, and parameter matching is automatically restarted, thereby synchronously updating the complete set of anti-interference adaptation parameters. On the other hand, if the monitoring module determines that there is a link synchronization anomaly, transmission quality anomaly, or anti-interference parameter synchronization failure based on the comparison results of each transmission index with the corresponding threshold, it will feed back these anomaly determination results to the interference parameter configuration module. After receiving the above feedback information, the module will also immediately restart the interference acquisition and anti-interference parameter matching process to complete the parameter update of the entire link.

[0145] In this embodiment, by reacquiring electromagnetic interference signals to update various anti-interference parameters when the preset interference monitoring update cycle is reached or when a feedback instruction is received, the parameter refresh combining active periodic detection and passive abnormal response is realized. This gives the transmission link the ability to adapt and evolve, effectively avoiding communication paralysis caused by long-term fixed parameters, and providing a reliable system-level guarantee for the long-term, stable and continuous transmission of polarity detection data of current and voltage transformers.

[0146] In one embodiment, this application also provides a current transformer polarity detection data transmission system, the system comprising: a transmitter, a repeater, and a receiver;

[0147] The transmitting end is used to execute the method in any one or more of the above embodiments; the repeater is used to receive the signal to be transmitted sent by the transmitting end and forward the signal to be transmitted; the receiving end is used to receive the signal to be transmitted forwarded by the repeater, and demodulate the signal to be transmitted based on the transmission frequency band parameters, spreading sequence parameters and convolution constraint parameters corresponding to the transmitting end, to obtain the demodulation result, and to restore the polarity detection data of the mutual inductor based on the demodulation result.

[0148] The transmitting end can be a communication node installed at the current and voltage transformer test site, mainly used to collect polarity data and adaptively sense the environment to generate customized anti-interference radio frequency waveforms.

[0149] A repeater can be a wireless relay device installed in the middle of the transmission path. It is mainly used to compensate for the limited single-hop communication distance or to avoid large metal obstructions on site. It can be implemented based on a space radio frequency transceiver antenna and signal amplification circuit.

[0150] The receiving end can be a data aggregation node located at a remote master station, mainly used to capture space electromagnetic waves and reverse-parse out readable service plaintext. It can be built based on high-performance baseband signal processing devices.

[0151] Specifically, in the overall operation logic of the current transformer polarity detection data transmission system, the transmitting end, as the source node, first executes the aforementioned complete data acquisition, environmental perception, parameter matching, and anti-interference fusion modulation process, encapsulating the original polarity information and converting it into a radio frequency layer signal to be transmitted and radiating it into the spatial channel. Subsequently, the repeater deployed in the middle of the link captures and receives the signal to be transmitted from the transmitting end within its coverage area, and relays the signal to be transmitted without changing the core service carrying intent of the signal, and forwards it to the target area again. Finally, the receiving end receives the signal to be transmitted forwarded by the repeater on a predetermined frequency band, and strictly performs reverse demodulation processing on the signal to be transmitted in the internal baseband processor based on the transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters established or agreed upon with the transmitting end. The output is a demodulation result stripped of the anti-interference physical layer mask, and further reconstructs the format according to the demodulation result to restore the original polarity detection data of the current transformer.

[0152] In this embodiment, a complete closed-loop communication architecture is achieved through method execution at the transmitting end, relay forwarding by the repeater, and collaborative demodulation processing based on alignment parameters at the receiving end. This architecture enables high-fidelity, cross-obstacle transmission of underlying sensing data even under complex electromagnetic interference and spatial fading conditions in substations. Furthermore, it overcomes the shortcomings of traditional single-point direct-connection communication, such as poor resilience and large coverage blind spots, at the system level, providing a solid and highly robust transmission foundation for remote polarity status monitoring of current and voltage transformers.

[0153] In one embodiment, the receiver is further configured to, if the demodulation result is an encrypted data sequence determined based on the chaotic initial key and the chaotic control parameters, decrypt the encrypted data sequence using the preset chaotic initial key and the chaotic control parameters to restore the polarity detection data of the mutual inductor.

[0154] Specifically, in the data aggregation stage of the current transformer polarity detection data transmission system, after completing the baseband decoding at the physical layer, the receiving end obtains the demodulation processing result as the input verification object of the data link layer. When the state of the data is analyzed, if it is determined that the demodulation processing result is an encrypted data sequence determined based on the chaotic initial key and chaotic control parameters, the internal reverse restoration logic is triggered. Subsequently, the receiving end extracts the locally preset chaotic initial key and chaotic control parameters that are synchronized with the sending end, performs reverse decryption processing on the encrypted data sequence forwarded by the repeater, and finally outputs and restores the initial polarity detection data of the current transformer by stripping off the outer chaotic confusion features.

[0155] For example, in the specific practical application of decrypting and restoring the standardized original data sequence at the system receiving end, since the transmitting end uses discrete chaotic iteration and bitwise XOR encryption, after the receiving end demodulates the underlying encrypted data sequence, its internal chip will first perform discrete chaotic iterative operation based on the same chaotic initial key and chaotic control parameters previously negotiated and confirmed by the multi-link management module, continuously iterating and generating a binary chaotic encryption key sequence that is completely consistent with the transmitting end; then, by making full use of the reversible operation characteristics of the standard bitwise XOR operation, the receiving end only needs to perform a bitwise superposition operation on the obtained underlying encrypted data sequence and the locally synchronously generated binary chaotic encryption key sequence to cancel the chaotic garbled code injected in the transmitting stage, decrypt and restore the standardized original data sequence with a unified format, that is, the real current and voltage transformer polarity detection data.

[0156] By using a preset chaotic initial key and chaotic control parameters to decrypt the data when the receiving end confirms that the demodulation result is an encrypted data sequence, the high efficiency of reverse conversion and cleaning of the underlying masking information at the end of the communication link is achieved. This achieves the goal of forming a complete data security closed loop with the nonlinear chaotic encryption mechanism of the source node, thereby ensuring that the core detection data can still be safely and accurately restored after passing through the complex and easily eavesdropped wireless space channel of the substation, effectively guaranteeing the absolute confidentiality and authenticity of the end-to-end data of the power Internet of Things business.

[0157] In one embodiment, the system further includes: a transmission status monitoring module, used to acquire data frames exchanged between the transmitter, repeater and receiver, and determine multiple transmission indicators based on the data frames; when the transmission indicators indicate that transmission is not normal, a corresponding feedback instruction is generated and sent to the transmitter;

[0158] The transmitting end is also used to update the transmission frequency band parameters, spreading sequence parameters and convolution constraint parameters in response to the feedback command, and generate a parameter synchronization command frame based on the updated transmission frequency band parameters, spreading sequence parameters and convolution constraint parameters, and send the parameter synchronization command frame to the receiving end.

[0159] The receiver is also used to receive parameter synchronization instruction frames sent by the transmitter, and parse them to obtain transmission frequency band parameters, spread spectrum sequence parameters, and convolution constraint parameters to complete parameter synchronization.

[0160] The transmission status monitoring module can be a hardware and software co-processing unit deployed in the system architecture to coordinate the quality of link communication. It is mainly used to capture and analyze the underlying interaction status between various nodes in real time.

[0161] A data frame can be a standardized data encapsulation format for logical interaction and status confirmation between various communication nodes above the physical layer. It is mainly used to carry handshake signals, synchronization flags or parameter configuration information between nodes. It can be represented as a structured bit stream containing a frame header, payload and checksum.

[0162] Transmission metrics can be statistical characteristic values ​​that quantitatively assess the current wireless link communication health and the effectiveness of anti-interference strategies. They are mainly used to provide objective data for decision-making regarding whether the system needs to reconstruct underlying communication parameters. Feedback commands can be alarm and reconfiguration control signaling sent by the monitoring unit to the upstream source node when link degradation or parameter out-of-synchronization is detected. They are mainly used to trigger the system's adaptive closed-loop optimization mechanism. Parameter synchronization command frames can be specific control messages used by the transmitting end to notify the remote receiving node of the latest link configuration after completing the anti-interference parameter update. They are mainly used to force both ends of the link to re-achieve consistency in the underlying frequency domain, code domain, and error correction domain.

[0163] Specifically, during continuous system operation, the transmission status monitoring module acquires various data frames exchanged between the transmitter, repeater, and receiver in the channel in real time. Subsequently, the module extracts the interaction records and status characteristics within each data frame, and calculates and determines multiple transmission indicators characterizing the current link quality based on these extracted data frames. Next, it performs status analysis on these multiple transmission indicators. When the value or logical state of a transmission indicator indicates that the system is not transmitting normally, the transmission status monitoring module generates a corresponding feedback instruction and sends this feedback instruction to the transmitter to trigger exception handling. Upon receiving the feedback instruction, the transmitter, in response to the instruction's indication, restarts the process. The process involves matching environmental parameters and adjusting strategies, refreshing and updating existing transmission frequency band parameters, spreading sequence parameters, and convolutional constraint parameters. Following this, the transmitting end, based on the updated transmission frequency band parameters, spreading sequence parameters, and convolutional constraint parameters, packages and generates a parameter synchronization command frame containing the latest configuration information, and sends this command frame to the remote receiving end via the wireless link. Finally, the receiving end receives the parameter synchronization command frame sent by the transmitting end, performs a parsing operation on it, parses out the latest transmission frequency band parameters, spreading sequence parameters, and convolutional constraint parameters carried within, and applies them to its local demodulation logic, thereby completing parameter synchronization between the transmitting and receiving ends. For example, in practical applications that achieve integrated monitoring of transmission status and closed-loop optimization of the entire link, the transmission status monitoring module will capture the standard handshake frames, link synchronization frames, and parameter synchronization command frames (i.e., the actual data frames) of the interaction between the sender, receiver, and repeater in real time, and record the transmission and reception times and response status of various frames. After the receiver completes decryption, it will also retrieve the original standardized data sequence and the decrypted and restored data sequence to count the number of bit errors. Based on these statistical data, specific transmission indicators such as link synchronization frame loss rate, encryption / decryption verification matching rate, parameter synchronization success rate, and signal transmission bit error rate will be calculated. When a certain indicator (such as the signal transmission bit error rate) exceeds a preset state judgment threshold, it is determined that the transmission quality is abnormal (not transmitting normally). The system will generate an anomaly judgment result and send it as a feedback instruction to the interference parameter configuration module at the transmitting end. After receiving the instruction, the transmitting end immediately restarts the entire process of substation interference signal acquisition, clustering, feature extraction and matching, thereby generating a completely new set of transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters to complete the end-to-end parameter update. After the update is completed, the transmitting end sends a parameter synchronization instruction frame carrying a verification field and synchronization identifier to the receiving end via the wireless link. After receiving the instruction frame, the receiving end verifies the parameters and parses the new parameters according to the verification field and synchronization identifier, ensuring that the end-to-end anti-interference parameters are consistent in real time, and finally completely completes the parameter synchronization update and the closed-loop self-healing of the entire process.

[0164] In this embodiment, the transmission status monitoring module acquires interactive data frames and determines transmission indicators. When transmission is abnormal, the sending end is triggered to update parameters and send parameter synchronization instruction frames to the receiving end to complete parameter synchronization. This achieves global dynamic insight into the complex wireless link status of the substation and autonomous discovery of communication anomalies. It achieves the goal of quickly restoring communication connection without manual intervention when encountering sudden strong electromagnetic interference or link loss of synchronization, thus improving the system's long-term unattended operation stability and resilience under harsh conditions.

[0165] To enable those skilled in the art to better understand the above steps, the following example illustrates the embodiments of this application, but it should be understood that the embodiments of this application are not limited thereto.

[0166] This embodiment provides a monitoring system for encrypted transmission of current transformer polarity detection data. The system mainly includes a transmitter, a repeater, a receiver, and an integrated monitoring module for transmission status.

[0167] In terms of internal component structure and connectivity, the transmitting end, acting as the source hub for data initiation, further integrates a multi-link management module, an interference parameter configuration module, and an encryption spread spectrum fusion module. Specifically:

[0168] In the initial stage of communication, the multi-link management module establishes a two-way handshake connection with the external receiver through the wireless link to realize the synchronization of the transmitting and receiving ends, link allocation, and advance negotiation of security parameters.

[0169] The input of the interference parameter configuration module is logically connected to the field environment detection unit to sense external electromagnetic waveforms. Its output is connected to the internal encrypted spread spectrum fusion module to provide underlying anti-interference physical parameters, and to the external radio frequency transmission link to send parameter synchronization command frames unidirectionally to the receiver.

[0170] The encryption spread spectrum fusion module receives parameters and data from the preceding module, and its output is directly connected to the radio frequency antenna of the transmitting end, radiating the processed encrypted signal outward through the wireless space physical channel.

[0171] Regarding cross-node data transmission relationships: the RF antenna of the transmitting end establishes a spatial wireless connection with the repeater erected in the middle of the link; the repeater, as an amplification and error correction relay node, has its output connected to the remote receiving end again through the spatial wireless link; in addition, the integrated transmission status monitoring module, as the global monitoring center, maintains a logical connection with the wireless interaction link between the transmitting end, repeater, and receiving end through network bypass monitoring, and is used to collect handshake and verification data frames between each node in real time. Furthermore, the control output of this monitoring module is connected to the interference parameter configuration module and the encryption spread spectrum fusion module inside the transmitting end through feedback links, thereby constructing a complete system-level physical and logical connection topology.

[0172] Based on the above system architecture, the most detailed execution process of this system for encrypting and monitoring polarity detection data transmission is as follows: Figure 2 As shown:

[0173] The transmitting end performs link negotiation and synchronization using the multi-link management module. At the start of system transmission, the multi-link management module within the transmitting end establishes basic communication with the receiving end via a wireless channel, performing synchronization and link allocation between the two ends. During this process, both parties interact through a security protocol to negotiate and establish the initial chaotic key and chaotic control parameters for subsequent encryption calculations, as well as the pseudo-random generation seed for spread spectrum, thereby completing parameter negotiation and link allocation and laying the foundation for stable parallel transmission across multiple nodes.

[0174] The transmitting end executes the interference parameter configuration module for interference acquisition and parameter generation. This module works in two ways: firstly, it formats and preprocesses the raw business data of the instrument transformers to form unified polarity detection data; secondly, it initiates full-domain environmental perception, acquires electromagnetic interference waveforms at the substation site, and performs filtering processing to obtain clean and effective interference signals. Subsequently, a clustering algorithm is used to classify the effective interference signals based on similarity, and target interference data clusters that meet the standard size are selected and retained according to a preset sample size threshold. Their feature parameter sets are extracted and compared with a standard library to identify the target interference type in the current environment. Further, the mean value of feature parameters is extracted from the target interference data clusters to reconstruct standard interference signal samples. These samples are then sent to different analysis logics: spectrum analysis is performed to extract frequency band distribution feature parameters, and time series analysis is performed to extract time series persistence feature parameters. These are then injected into a preset test link to obtain mechanism feature parameters. These three types of parameters are summarized and integrated to construct a full-domain interference feature parameter set. Finally, the set is input into the preset frequency band matching library, spread spectrum sequence matching library and convolution constraint matching library respectively to perform rule matching, calculate and generate transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters adapted to the current harsh transmission environment, so as to form a complete set of anti-interference basic parameters.

[0175] The transmitting end performs anti-interference parameter synchronization of the interference parameter configuration module. After generating the latest parameters, the transmitting end encapsulates the determined transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters to generate a parameter synchronization command frame carrying a check field and a synchronization identifier, and sends it to the receiving end via the wireless link. The receiving end parses the frame based on the check field and forces the underlying anti-interference configuration to align with the transmitting end, thus achieving parameter synchronization across the entire link.

[0176] The transmitting end executes data encryption and spread spectrum modulation using the encryption-spread spectrum fusion module. Taking the polarity detection data to be transmitted, along with the previously negotiated chaotic initial key and chaotic control parameters, as inputs, it internally performs discrete chaotic iterative operations to quantize and output a highly pseudo-random chaotic encryption key. Next, using reversible superposition logic, the polarity detection data and the key are merged bit-by-bit to generate an encrypted data sequence that conceals underlying service characteristics. Subsequently, the radio frequency working band is configured according to the synchronized transmission frequency band parameters, a corresponding pseudo-random spreading code is generated based on the spreading sequence parameters, and the convolutional coding configuration is set according to the convolutional constraint parameters. Finally, the encrypted data sequence is fused and modulated using the spreading code and convolutional configuration to generate the signal to be transmitted and transmitted via the radio frequency antenna.

[0177] Repeaters perform signal verification and forwarding. A repeater deployed in the physical environment captures the signal to be transmitted within its coverage area, performs necessary verification and forward error correction at the physical layer, then transparently amplifies and forwards it to the receiving end in the target area.

[0178] The receiving end performs data decryption and restoration. After receiving the signal to be transmitted, the receiving end performs demodulation processing strictly based on the synchronized communication parameters, extracting the demodulation result after stripping the physical layer mask. When the result is confirmed to be a low-level encrypted sequence, the corresponding decryption mask is synchronously derived using the locally stored chaotic initial key and chaotic control parameters. The demodulation result is then decrypted in reverse to restore the original polarity detection data of the current transformer without loss, and the response data of the link interaction is sent back to the monitoring module.

[0179] The integrated transmission status monitoring module performs transmission monitoring, anomaly detection, and closed-loop optimization throughout the entire process. It continuously captures various data frames exchanged between the transmitter, repeater, and receiver, accurately calculating core transmission indicators such as link synchronization frame loss rate, encryption / decryption verification matching rate, parameter synchronization success rate, and signal transmission error rate. These indicators are then compared with preset thresholds. If all transmission indicators are within healthy thresholds, the system is considered to be without anomalies. Following the flowchart logic, the system directly loops back to the transmitter: the encryption and spread spectrum fusion module performs data encryption and spread spectrum modulation, continuing to use the current parameters to modulate and transmit subsequent polarity detection data. If any transmission indicator exceeds the limit, the system is deemed not to be transmitting normally, and a feedback command is immediately generated to trigger closed-loop optimization: parameter reconfiguration and key calibration. If there is an anomaly in link synchronization, transmission quality, or parameter synchronization, the feedback command is directed to the interference parameter configuration module, triggering the module to restart the entire interference acquisition and parameter matching process. If there is an anomaly in encryption / decryption operations, the feedback command is directed to the encryption and spread spectrum fusion module, triggering a new request to the multi-link management module to negotiate and update chaotic parameters and calibrate the spread spectrum code.

[0180] Once the above-mentioned reconfiguration or calibration optimization operations are completed, the process will jump back to the transmitting end to perform the interference parameter configuration module anti-interference parameter synchronization step. By re-issuing the parameter synchronization command frame, the refreshed anti-interference link parameters will be forcibly synchronized to the receiving end again, thereby completing the grand closed loop from anomaly detection to full-link self-healing.

[0181] In this embodiment, the encrypted transmission monitoring system for current and voltage transformer polarity detection data performs full-domain acquisition and filtering of electromagnetic interference signals at the substation through an interference parameter configuration module. It employs a clustering algorithm to identify the main interference types at the site, constructing interference characteristics from three dimensions: frequency band distribution, temporal duration, and mechanism of action. This generates suitable transmission frequency bands, spread spectrum sequences, and convolution constraint parameters. The system can also restart the interference acquisition and parameter matching process at preset intervals and synchronize the parameters to the entire link. This allows the transmission configuration to closely match the actual interference situation at the substation, reducing the impact of complex electromagnetic environments on data transmission, decreasing bit errors and packet loss during data transmission, and improving the stability of transformer polarity detection data transmission. Furthermore, this encrypted transmission monitoring system combines chaotic encryption with spread spectrum transmission through an encryption spread spectrum fusion module, based on a cooperative... The chaotic parameters of the transformer are used to generate a key for data encryption, which is then combined with anti-interference parameters to complete the link configuration. This reduces the possibility of the detection data being stolen or tampered with during transmission, ensuring data transmission security, and also improves the signal transmission capability in complex environments, achieving dual protection of data transmission security and stability. This current and voltage transformer polarity detection data encryption transmission monitoring system monitors the link synchronization frame loss rate, encryption / decryption verification matching rate, and signal transmission error rate through an integrated transmission status monitoring module. Based on the monitoring results, it determines transmission anomalies and feeds back the anomaly information to the corresponding functional module, automatically re-performing the anti-interference parameter matching work, or renegotiating the chaotic initial key and calibrating the pseudo-random spreading code. The system can complete the repair of transmission anomalies without manual operation, simplifying the system operation and maintenance process, maintaining the stable operation of the system, and ensuring the continuity of transformer polarity detection data transmission.

[0182] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0183] Based on the same inventive concept, this application also provides a current transformer polarity detection data transmission device for implementing the aforementioned current transformer polarity detection data transmission method. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations of one or more current transformer polarity detection data transmission device embodiments provided below can be found in the limitations of the current transformer polarity detection data transmission method described above, and will not be repeated here.

[0184] In one exemplary embodiment, such as Figure 3 As shown, a current transformer polarity detection data transmission device is provided, comprising: a data acquisition module 310, an interference characteristic parameter acquisition module 320, an interference characteristic parameter configuration module 330, a signal modulation module 340, and a signal transmission module 350, wherein:

[0185] The data acquisition module 310 is used to acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located.

[0186] The interference feature parameter acquisition module 320 is used to extract the interference feature parameter set from the electromagnetic interference signal and match the interference feature parameter set with the preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters suitable for the transmission environment.

[0187] The interference feature parameter configuration module 330 is used to configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters.

[0188] The signal modulation module 340 is used to perform direct sequence spread spectrum and convolutional coding fusion modulation on polarity detection data based on pseudo-random spreading code and convolutional coding configuration to generate a signal to be transmitted.

[0189] The signal transmission module 350 is used to transmit the signal to be transmitted via the radio frequency operating band.

[0190] In one embodiment, the data acquisition module 310 is further configured to:

[0191] When the preset interference monitoring update cycle is reached, or when a feedback instruction corresponding to the signal to be transmitted is received, the step of obtaining the electromagnetic interference signal of the transmission environment where the transformer is located is re-executed in order to update the transmission frequency band parameters, spread spectrum sequence parameters, and convolution constraint parameters.

[0192] In one embodiment, the interference feature parameter acquisition module 320 is further configured to:

[0193] The electromagnetic interference signal is filtered to obtain an effective interference signal. The effective interference signal is then divided into multiple interference data clusters using a clustering algorithm. The target interference data cluster is selected from these clusters based on a preset sample size threshold. The feature parameter set corresponding to the target interference data cluster is extracted and matched with a preset interference type standard feature database. The target interference type of the electromagnetic interference signal is determined based on the matching results. Finally, the set of interference feature parameters is determined based on the target interference type.

[0194] In one embodiment, the interference feature parameter acquisition module 320 is further configured to:

[0195] Based on the statistical values ​​of characteristic parameters obtained from the target interference data cluster corresponding to the target interference type, standard interference signal samples are determined; spectral analysis is performed on the standard interference signal samples to obtain frequency band distribution characteristic parameters, and time series analysis is performed on the standard interference signal samples to obtain time series persistence characteristic parameters; when the standard interference signal samples are injected into a preset test link, the mechanism characteristic parameters are determined based on the transmission parameters of the obtained test link; based on the frequency band distribution characteristic parameters, time series persistence characteristic parameters, and mechanism characteristic parameters, the set of interference characteristic parameters is determined.

[0196] In one embodiment, the interference feature parameter acquisition module 320 is further configured to:

[0197] The frequency band distribution feature parameters in the interference feature parameter set are matched with a preset frequency band matching library to determine the transmission frequency band parameters suitable for the transmission environment; the target interference type in the interference feature parameter set is matched with a preset spread spectrum sequence matching library to determine the spread spectrum sequence parameters suitable for the transmission environment; and the action mechanism feature parameters in the interference feature parameter set are matched with a preset convolution constraint matching library to determine the convolution constraint parameters suitable for the transmission environment.

[0198] In one embodiment, the signal modulation module 340 is further configured to:

[0199] Before performing direct sequence spread spectrum and convolutional coding fusion modulation on the polarity detection data, a preset chaotic initial key and chaotic control parameters are obtained; based on the polarity detection data, chaotic initial key and chaotic control parameters, chaotic iterative calculation is performed to obtain a chaotic encryption key; the polarity detection data and chaotic encryption key are superimposed to obtain an encrypted data sequence; using pseudo-random spreading code and convolutional coding configuration, the encrypted data sequence is subjected to direct sequence spread spectrum and convolutional coding fusion modulation.

[0200] Each module in the aforementioned transformer polarity detection data transmission device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0201] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media to run. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for data transmission of current transformer polarity detection.

[0202] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0203] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0204] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0205] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0206] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0207] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0208] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0209] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for transmitting data for polarity detection of a current transformer, characterized in that, The method includes: Acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located; The set of interference feature parameters is extracted from the electromagnetic interference signal, and the set of interference feature parameters is matched with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment. Configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters; Based on the pseudo-random spreading code and the convolutional coding configuration, the polarity detection data is fused and modulated by direct sequence spreading and convolutional coding to generate a signal to be transmitted. The signal to be transmitted is transmitted through the radio frequency band.

2. The method according to claim 1, characterized in that, The extraction of the set of interference feature parameters from the electromagnetic interference signal includes: The electromagnetic interference signal is filtered to obtain an effective interference signal; The effective interference signal is divided into multiple interference data clusters by a clustering algorithm, and the target interference data cluster is selected from the multiple interference data clusters according to a preset sample number threshold. Extract the feature parameter set corresponding to the target interference data cluster, and match the feature parameter set with a preset interference type standard feature database. Based on the matching result, determine the target interference type of the electromagnetic interference signal. The set of interference feature parameters is determined based on the target interference type.

3. The method according to claim 2, characterized in that, Determining the set of interference feature parameters based on the target interference type includes: Standard interference signal samples are determined based on the statistical values ​​of characteristic parameters obtained from the target interference data cluster corresponding to the target interference type. Spectral analysis is performed on the standard interference signal samples to obtain frequency band distribution characteristic parameters, and time series analysis is performed on the standard interference signal samples to obtain time series duration characteristic parameters. When the standard interference signal sample is injected into a preset test link, the mechanism characteristic parameters are determined based on the transmission parameters of the test link obtained. The set of interference characteristic parameters is determined based on the frequency band distribution characteristic parameters, the timing persistence characteristic parameters, and the mechanism characteristic parameters.

4. The method according to claim 3, characterized in that, The step of matching the set of interference feature parameters with a preset parameter matching library to determine the transmission frequency band parameters, spreading sequence parameters, and convolution constraint parameters suitable for the transmission environment includes: The frequency band distribution feature parameters in the interference feature parameter set are matched with a preset frequency band matching library to determine the transmission frequency band parameters that are suitable for the transmission environment. The target interference type in the interference feature parameter set is matched with a preset spread spectrum sequence matching library to determine the spread spectrum sequence parameters that are suitable for the transmission environment. The mechanism feature parameters in the interference feature parameter set are matched with a preset convolution constraint matching library to determine the convolution constraint parameters that are suitable for the transmission environment.

5. The method according to claim 1, characterized in that, Before performing direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolutional coding configuration, the method further includes: Obtain the preset initial chaos key and chaos control parameters; Based on the polarity detection data, the initial chaotic key, and the chaotic control parameters, a chaotic iterative operation is performed to obtain the chaotic encryption key; The polarity detection data is superimposed with the chaotic encryption key to obtain an encrypted data sequence; The step of performing direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolutional coding configuration includes: The encrypted data sequence is fused and modulated using the pseudo-random spreading code and the convolutional coding configuration.

6. The method according to claim 1, characterized in that, The method further includes: When the preset interference monitoring update cycle is reached, or when a feedback instruction corresponding to the signal to be transmitted is received, the step of obtaining the electromagnetic interference signal of the transmission environment where the transformer is located is re-executed to update the transmission frequency band parameters, the spread spectrum sequence parameters, and the convolution constraint parameters.

7. A current transformer polarity detection data transmission system, characterized in that, The system includes: a transmitter, a repeater, and a receiver; The transmitting end is configured to perform the method according to any one of claims 1 to 6; The repeater is used to receive the signal to be transmitted sent by the transmitting end and forward the signal to be transmitted. The receiving end is used to receive the signal to be transmitted forwarded by the repeater, and demodulate the signal to be transmitted based on the transmission frequency band parameters, spreading sequence parameters and convolution constraint parameters corresponding to the transmitting end, to obtain the demodulation result, and restore the polarity detection data of the mutual inductor according to the demodulation result.

8. The system according to claim 7, characterized in that, The receiving end is further configured to, if the demodulation result is an encrypted data sequence determined based on a preset chaotic initial key and chaotic control parameters, decrypt the encrypted data sequence using the preset chaotic initial key and chaotic control parameters to restore the polarity detection data of the mutual inductor.

9. The system according to claim 7, characterized in that, The system further includes: a transmission status monitoring module, used to acquire data frames exchanged between the sending end, the repeater and the receiving end, and determine multiple transmission indicators based on the data frames; when the transmission indicators indicate that transmission is not normal, a corresponding feedback instruction is generated and sent to the sending end; The transmitting end is further configured to update the transmission frequency band parameters, the spreading sequence parameters, and the convolution constraint parameters in response to the feedback instruction, and generate a parameter synchronization instruction frame based on the updated transmission frequency band parameters, the spreading sequence parameters, and the convolution constraint parameters, and send the parameter synchronization instruction frame to the receiving end. The receiving end is also used to receive the parameter synchronization instruction frame sent by the sending end, and parse it to obtain the transmission frequency band parameters, the spreading sequence parameters, and the convolution constraint parameters to complete parameter synchronization.

10. A data transmission device for detecting the polarity of a current transformer, characterized in that, The device includes: The data acquisition module is used to acquire the polarity detection data to be transmitted, as well as the electromagnetic interference signal of the transmission environment in which the current transformer is located. The interference feature parameter acquisition module is used to extract a set of interference feature parameters from the electromagnetic interference signal, and match the set of interference feature parameters with a preset parameter matching library to determine the transmission frequency band parameters, spread spectrum sequence parameters and convolution constraint parameters that are suitable for the transmission environment. The interference feature parameter configuration module is used to configure the radio frequency operating frequency band based on the transmission frequency band parameters, generate a pseudo-random spreading code corresponding to the spreading sequence parameters, and determine the convolutional coding configuration based on the convolutional constraint parameters. The signal modulation module is used to perform direct sequence spreading and convolutional coding fusion modulation on the polarity detection data based on the pseudo-random spreading code and the convolutional coding configuration to generate a signal to be transmitted. A signal transmission module is used to transmit the signal to be transmitted via the radio frequency band.

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