Method and system for evaluating channel stability of power line communication dual-mode signal

Abstract

The invention relates to the technical field of communication, in particular to a channel stability evaluation method and system for a power line communication dual-mode signal. The method comprises the following steps: acquiring an electromagnetic disturbance information set of a biogas power plant, and analyzing signal-to-noise ratio fluctuation of broadband and micropower wireless carrier communication signals under the grid-connected harmonic action of a biogas generator based on the electromagnetic disturbance information set to obtain a communication channel dynamic information set; based on the communication channel dynamic information set, analyzing the influence of biogas fermentation on power generation efficiency, and further causing dynamic evolution information of communication channel link bit error rate increase and carrier communication channel switching failure, so as to obtain a communication channel reliability map; and dynamically generating communication guarantee plans for different production stages based on the communication channel reliability map, and outputting a channel stability evaluation log. Accurate equipment data transmission and efficient control instruction execution are ensured, and the safe operation level and the power generation efficiency of a power plant are improved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method and system for evaluating the channel stability of dual-mode power line communication signals. Background Technology

[0002] In biogas power plants, power line communication (PLC) is often used for power generation data acquisition, equipment monitoring and grid connection coordination. During biogas power generation, the composition of fermentation feedstock, gas production and engine load will change dynamically, causing grid harmonics and electromagnetic environment disturbances, which in turn affect the quality of broadband and low-power wireless carrier communication that transmits data over the same power line.

[0003] Currently, the evaluation of power line communication channels is mostly based on static or short-term tests, which do not fully consider the fluctuations in power generation efficiency caused by biogas fermentation and its continuous impact on communication links. Existing evaluation methods often fail to accurately reflect communication reliability under complex dynamic scenarios such as grid-connected harmonic changes, increased channel bit error rate, and dual-mode switching failures. This leads to communication interruptions or data loss during critical stages of power generation, affecting the efficiency of remote monitoring and dispatching of power plants, and thus threatening the stable operation of the power generation system. Summary of the Invention

[0004] This application provides a method and system for evaluating the channel stability of dual-mode power line communication signals to solve the above-mentioned problems.

[0005] In a first aspect, this application provides a method for evaluating the channel stability of dual-mode power line communication signals. The method includes: acquiring an electromagnetic disturbance information set of a biogas power plant; based on the electromagnetic disturbance information set, analyzing the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the influence of grid-connected harmonics of the biogas generator to obtain a dynamic information set of the communication channel; based on the dynamic information set of the communication channel, analyzing the impact of biogas fermentation on power generation efficiency, thereby leading to the dynamic evolution information of increased communication channel link bit error rate and carrier communication channel switching failure, to obtain a communication channel reliability map; based on the communication channel reliability map, dynamically generating communication assurance plans for different production stages, and outputting a channel stability evaluation log.

[0006] Through the above technical solutions, targeting the power line communication scenario of biogas power plants, by accurately capturing electromagnetic disturbance information and analyzing the impact of grid-connected harmonics on dual-mode signals, a comprehensive understanding of channel dynamic changes and fault evolution patterns is achieved. The dynamically generated phased communication assurance plans can accurately adapt to the channel requirements of different production stages, effectively reduce link error rates and channel switching failure risks, ensure stable and reliable communication, and provide data support for system optimization through the output evaluation logs. This ensures accurate data transmission and efficient execution of control commands, while also improving the safety level and power generation efficiency of the power plant, thus building a solid communication guarantee for the large-scale and stable operation of biogas power plants.

[0007] Optionally, the electromagnetic disturbance information set includes a biogas generator harmonic information set and a fermentation tank equipment interference information set; based on the biogas generator harmonic information set, the spectral distribution and energy intensity of the harmonic current generated by the generator grid connection in the broadband and low-power wireless carrier communication frequency bands are analyzed to obtain a carrier signal frequency domain information set; based on the fermentation tank equipment interference information set, the impact of pulse and oscillation interference generated by equipment start-up, shutdown and operation on the time domain of the communication frame is analyzed to obtain a communication frame time domain disturbance information set; according to the carrier signal frequency domain information set and the communication frame time domain disturbance information set, a correlation relationship is established between harmonic background noise and the time domain impact in terms of occurrence time and impact intensity; based on the correlation relationship, sensitive frequency bands and sensitive time periods that cause signal-to-noise ratio fluctuations and communication failures are identified to obtain the communication channel dynamic information set.

[0008] Optionally, based on the biogas generator harmonic information set, the energy values ​​of harmonic currents at different time points within the biogas power generation efficiency variation cycle are synchronously analyzed at various frequency points in the broadband and low-power wireless frequency bands, respectively, to obtain broadband frequency band energy fluctuation sequences and low-power wireless frequency band energy fluctuation sequences. The energy values ​​at corresponding time points in the broadband frequency band energy fluctuation sequences and the low-power wireless frequency band energy fluctuation sequences are compared to identify frequency points and corresponding time periods where the energy values ​​exceed a preset interference threshold. All identified frequency points and corresponding time periods are integrated according to the communication frequency band and time sequence to obtain the carrier signal frequency domain information set. The carrier signal frequency domain information set is used to characterize the time-frequency distribution characteristics of harmonic interference to the communication frequency band.

[0009] Optionally, based on the interference information set of the fermentation tank equipment, the start time, duration, and intensity changes of pulse interference and oscillation interference generated during the equipment start-up and shutdown phases and operation process are analyzed to obtain an interference time-domain feature set; based on the interference time-domain feature set, the coverage information caused by the sudden timing of the pulse interference and the duration of the oscillation interference on the communication frame transmission window of the communication channel is analyzed to obtain communication frame coverage disturbance information; based on the communication frame coverage disturbance information, the impact damage of the pulse interference on key fields of the communication frame and the continuous degradation of the overall signal of the communication frame by the oscillation interference during the affected period are analyzed to obtain the communication frame time-domain disturbance information set.

[0010] Optionally, based on the frequency point, the corresponding time period, and combined with the start time and the duration, the overlap information of the frequency domain interference period of the harmonic background noise and the time period affected by the time domain impact of the equipment operation on the time axis is analyzed to obtain a spatiotemporally overlapping interference time period set; based on the spatiotemporally overlapping interference time period set, according to the energy value of the corresponding frequency point in the carrier signal frequency domain information set and the interference intensity of the corresponding time period in the communication frame time domain disturbance information set, the coordinated change trend between the energy fluctuation of the harmonic background noise and the change of the equipment impact intensity in the overlapping time period is analyzed to obtain an interference intensity coupling feature set; based on the interference intensity coupling feature set, the interaction between the harmonic background noise aggravating the time domain impact on the communication frame damage and the abnormal rise of harmonic energy during the time domain impact is identified to obtain the correlation relationship; the interaction is manifested as a bidirectional coupling positive feedback formed between the harmonic background noise aggravating the communication frame damage and the abnormal rise of harmonic energy during the time domain impact; the correlation relationship is used to characterize the dynamic coupling information of continuous harmonic interference and sudden equipment impact jointly causing communication channel degradation in the electromagnetic environment of the biogas power plant during the production stage.

[0011] Optionally, based on the sensitive frequency band and the sensitive time period, the variation information of power generation efficiency under different gas production and load conditions is analyzed to obtain the fermentation process-power generation efficiency mapping relationship; based on the fermentation process-power generation efficiency mapping relationship and the correlation relationship, the variation trend of signal-to-noise ratio of broadband and low-power wireless carrier communication channels under the variation amplitude of power generation efficiency is analyzed to obtain the stage characteristics of channel performance evolution with power generation efficiency; based on the stage characteristics of channel performance evolution with power generation efficiency, the rise amplitude and rise rate of data transmission bit error rate in each period of the stage characteristics are analyzed to obtain link bit error rate dynamic evolution information; based on the link bit error rate dynamic evolution information, the shadowing effect of the cross change of broadband and low-power wireless channel performance on the channel switching decision condition within a preset floating time interval centered on the switching point of each period of the stage characteristics is analyzed to obtain communication channel switching dynamic information; combining the link bit error rate dynamic evolution information and the communication channel switching dynamic information, with the power generation efficiency change cycle as the time series framework, the mapping relationship and the stage characteristics are integrated to draw the communication channel reliability map reflecting the dynamic change of communication channel reliability.

[0012] Optionally, based on the sensitive frequency band and the sensitive time period, the fluctuation information of the biogas generator output power under the communication interference environment during the sensitive time period is analyzed to obtain the interference power generation baseline; based on the interference power generation baseline, according to the collected gas production data, the impact of gas production growth on increasing power generation, and the boundary effect of increased generator load on approaching the power upper limit and lowering efficiency are analyzed to obtain power-efficiency dynamic coupling information; based on the power-efficiency dynamic coupling information, the trajectory of power generation efficiency increasing with the increase of gas production data, but whose lower limit is constrained by the load conditions and the power generation baseline, is depicted to obtain the fermentation process-power generation efficiency mapping relationship.

[0013] Optionally, based on the fermentation process-power generation efficiency mapping relationship, the overall change of the electromagnetic environment constituted by the harmonic information set of the biogas generator and the interference information set of the fermentation tank equipment driven by the power generation efficiency change is analyzed to obtain the interference environment evolution characteristics; based on the interference environment evolution characteristics, combined with the correlation relationship, the effects of the spectral distribution change of the harmonic background noise and the intensity change of the time-domain impact on the signal-to-noise ratio fluctuation of the broadband carrier communication channel and the low-power wireless carrier communication channel are analyzed in different value ranges of the power generation efficiency change, respectively, to obtain the dual-mode channel performance response characteristics; based on the dual-mode channel performance response characteristics, the power generation efficiency change amplitude is used as a reference axis to correlate and map the complete law of the signal-to-noise ratio fluctuation tendency of the broadband and low-power wireless carrier communication channels from the beginning, development to transformation, to obtain the stage characteristics.

[0014] Optionally, based on the stage characteristics mapped in the communication channel reliability map, the channel performance risk level corresponding to different power generation efficiency intervals in the fermentation process-power generation efficiency mapping relationship is analyzed to obtain production stage risk classification information; based on the production stage risk classification information, according to the preset carrier communication mode priority list and channel parameter configuration library, the optimal mode switching timing and parameter adjustment strategy to ensure communication continuity under each level of risk production stage are analyzed to obtain a set of communication guarantee plans; according to the execution process of the set of communication guarantee plans, the improvement effect of the dynamic evolution information of the link bit error rate and the dynamic information of the communication channel switching after the plan is triggered within the power generation efficiency change cycle is analyzed, and combined with the gas production data and the power generation efficiency change amplitude, the channel stability assessment log is generated.

[0015] Secondly, this application provides a channel stability assessment system for dual-mode power line communication signals. The system includes: a fluctuation analysis module, used to acquire an electromagnetic disturbance information set of a biogas power plant, and based on the electromagnetic disturbance information set, analyze the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the action of grid-connected harmonics of the biogas generator to obtain a communication channel dynamic information set; a dynamic evolution module, used to analyze the impact of biogas fermentation on power generation efficiency based on the communication channel dynamic information set, thereby leading to the dynamic evolution information of increased communication channel link bit error rate and carrier communication channel switching failure, to obtain a communication channel reliability map; and a communication assessment module, used to dynamically generate communication assurance plans for different production stages based on the communication channel reliability map, and output a channel stability assessment log. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of an application scenario provided in an embodiment of this application;

[0018] Figure 2 A flowchart illustrating a method for evaluating the channel stability of dual-mode power line communication signals, provided as an embodiment of this application; Figure 3 This is a schematic diagram of a channel stability evaluation system for dual-mode power line communication signals provided in an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0020] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0021] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0022] Current power line communication channel assessments mostly rely on static or short-term tests, failing to fully consider the continuous impact of power generation efficiency fluctuations caused by biogas fermentation on communication links. Existing methods are unable to accurately characterize communication reliability under complex dynamic scenarios such as grid-connected harmonic fluctuations, increased channel bit error rate, and dual-mode switching failures. This can easily lead to communication interruptions and data loss during critical power generation stages, affecting the efficiency of remote monitoring and dispatching of power plants and threatening the stable operation of power generation systems.

[0023] Based on this, this application provides a method and system for evaluating the channel stability of dual-mode power line communication signals. By capturing electromagnetic disturbances and analyzing the effects of grid-connected harmonics on dual-mode signals, the system grasps the dynamics of the channel and the evolution of faults, dynamically generates phased communication assurance schemes, adapts to the channel requirements of different production stages, reduces the risk of link errors and channel switching failures, ensures communication stability, and provides data support for system optimization through the output evaluation logs. This ensures accurate data transmission of equipment and efficient execution of control commands, while improving the safety level and power generation efficiency of power plants, and laying a solid communication foundation for large-scale stable operation.

[0024] Figure 1 This application provides an application scenario diagram. In the process of dual-mode communication of power lines in a biogas power plant, the method provided in this application is applied to capture electromagnetic disturbances, analyze the effect of grid-connected harmonics on dual-mode signals, understand the channel dynamics and fault evolution characteristics, dynamically formulate communication assurance strategies adapted to each production stage, reduce link errors and switching failure probability, ensure communication reliability, and build a solid communication support for the safe, efficient and large-scale operation of the power plant.

[0025] Specifically, the method provided in this application can be applied to any server. The server interacts with the electromagnetic spectrum analyzer to obtain the electromagnetic disturbance information set provided by the electromagnetic spectrum analyzer, fully grasp the dynamic changes and fault evolution of the channel, and output the channel stability assessment log to the communication operation and maintenance personnel. This ensures accurate data transmission and efficient execution of control commands, while also improving the safety level and power generation efficiency of the power plant.

[0026] For specific implementation details, please refer to the following examples.

[0027] Figure 2 This is a flowchart illustrating a method for evaluating the channel stability of dual-mode power line communication signals according to an embodiment of this application. The method of this embodiment can be applied to servers in the above-described scenarios. Figure 2 As shown, the method includes: S201. Obtain the electromagnetic disturbance information set of the biogas power plant. Based on the electromagnetic disturbance information set, analyze the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the action of grid-connected harmonics of the biogas generator, and obtain the dynamic information set of the communication channel.

[0028] The electromagnetic disturbance information set can be a parameter set of the electromagnetic environment disturbance state of a biogas power plant, with an electromagnetic spectrum analyzer deployed at the biogas power plant as the data source. A biogas power plant can be a site that generates electricity using biogas as an energy source, and its operation involves key stages such as biogas fermentation and grid-connected power generation. Grid-connected harmonics from biogas generators can be voltage or current signals with frequencies that are integer multiples of the fundamental frequency generated when the biogas generator is connected to the grid, due to the nonlinear characteristics of the electromagnetic conversion process inside the generator. These harmonics can interfere with power line communication signals transmitted through the grid. Broadband carrier communication signals can be power line communication signals with a wide carrier frequency range. Low-power wireless carrier communication signals can be wireless communication methods that use low transmission power to transmit data in license-free frequency bands. Signal-to-noise ratio fluctuation can be the ratio of signal power to noise power of broadband and low-power wireless carrier communication signals. The communication channel dynamic information set can be a set of information on the dynamic characteristics of the signal-to-noise ratio fluctuation amplitude, fluctuation frequency, and fluctuation triggering conditions of broadband and low-power wireless carrier communication signals.

[0029] Specifically, in the power line communication process of biogas power plants, acquiring electromagnetic disturbance information sets from the biogas power plant and analyzing the signal-to-noise ratio (SNR) fluctuations of dual-mode signals under grid-connected harmonics is a fundamental prerequisite for channel stability assessment. In biogas power plants, generator grid-connected harmonics are the core interference source for communication signals, and existing assessments often neglect their dynamic impact, resulting in the inability to capture real-time SNR fluctuations. Without this step, subsequent assessments will lack accurate data support, fail to reflect the true state of the channel, and consequently lead to distorted assessment results, failing to provide an effective reference for communication stability.

[0030] S202. Based on the dynamic information set of the communication channel, analyze the impact of biogas fermentation on power generation efficiency, and the dynamic evolution information of the increase in the bit error rate of the communication channel link and the failure of carrier communication channel switching, and obtain the communication channel reliability map.

[0031] Biogas fermentation can be considered a biochemical reaction process in which microorganisms decompose biogas feedstock into biogas. Power generation efficiency can be defined as the conversion efficiency of a biogas power plant in converting the chemical energy of biogas into electrical energy. Communication channel link bit error rate (BER) can be defined as the ratio of the number of erroneous data bits received by the receiver to the total number of data bits transmitted during communication channel transmission; an increase in BER indicates that this ratio increases under the influence of external factors. Carrier communication channel handover failure can be defined as the failure of a communication system to successfully switch to a backup channel due to channel mismatch, signal synchronization failure, or other reasons. Dynamic evolution information can be defined as the gradual increase in the communication channel link BER from a normal level, and the change in the probability of carrier communication channel handover failure from low to high. A communication channel reliability map can be a visual representation (such as a line graph or heatmap) showing the reliability status and changing patterns of a communication channel.

[0032] Specifically, in the process of power line communication in biogas power plants, the dynamics of biogas fermentation are directly related to power generation efficiency, which in turn leads to an increase in channel error rate and handover failure. Existing technologies have not established a three-way linkage analysis mechanism. If this step is omitted, it will be impossible to grasp the evolution of channel faults, make it difficult to accurately judge channel reliability, and result in a lack of targeted contingency plans and an inability to avoid communication risks in advance.

[0033] S203. Based on the communication channel reliability map, dynamically generate communication assurance plans for different production stages and output channel stability assessment logs.

[0034] Different production stages can refer to the different operational characteristics of a biogas power plant throughout its entire process from raw material input to power output. Communication assurance plans are response strategies developed to address the communication channel characteristics and potential risks at different production stages of the biogas power plant. Channel stability assessment logs are documents that meticulously record the entire process of stability assessment for dual-mode power line communication channels.

[0035] Specifically, in the process of power line communication in biogas power plants, generating communication assurance plans for different production stages based on reliability maps and outputting assessment logs are key guarantees for the implementation of assessments. The channel characteristics of each production stage in a biogas power plant are significantly different, and existing fixed solutions cannot adapt to dynamic needs and lack complete assessment records. Without this step, channel stability lacks targeted protection, and there is no traceability basis after a failure, which can lead to problems such as communication interruption and equipment coordination failure. The assessment logs can also provide data support for subsequent optimizations.

[0036] The method provided in this embodiment addresses the power line communication scenario in biogas power plants by accurately capturing electromagnetic disturbance information, analyzing the impact of grid-connected harmonics on dual-mode signals, comprehensively understanding the dynamic changes and fault evolution patterns of the channel, and dynamically generating phased communication assurance plans. These plans can accurately adapt to the channel requirements of different production stages, effectively reduce link error rates and channel switching failure risks, ensure stable and reliable communication, and provide data support for system optimization through the output evaluation logs. This ensures accurate data transmission and efficient execution of control commands, while also improving the safety and power generation efficiency of the power plant, thus building a solid communication guarantee for the large-scale and stable operation of biogas power plants.

[0037] In some embodiments, the electromagnetic disturbance information set includes a biogas generator harmonic information set and a fermentation tank equipment interference information set. Based on the biogas generator harmonic information set, the spectral distribution and energy intensity of the harmonic current generated by the generator grid connection in the broadband and low-power wireless carrier communication frequency bands are analyzed to obtain the carrier signal frequency domain information set. Based on the fermentation tank equipment interference information set, the impact of pulse and oscillation interference generated by the equipment start-up, shutdown and operation on the time domain of the communication frame is analyzed to obtain the communication frame time domain disturbance information set. According to the carrier signal frequency domain information set and the communication frame time domain disturbance information set, the correlation between harmonic background noise and time domain impact on the occurrence time and impact intensity is established. Based on the correlation, the sensitive frequency bands and sensitive time periods that cause signal-to-noise ratio fluctuations and communication failures are identified to obtain the communication channel dynamic information set.

[0038] The biogas generator harmonic information set can be a collection of harmonic-related data generated by the biogas generator during grid-connected operation. The fermentation tank equipment interference information set can be a collection of data related to electromagnetic interference generated by fermentation tank auxiliary equipment (such as stirring equipment, pumps, etc.) during start-up, shutdown, and operation. Harmonic current can be the current components of the output current of the biogas generator other than the fundamental frequency. Spectral distribution can be the distribution of harmonic current at different frequency points within the broadband and low-power wireless carrier communication frequency bands. Energy intensity can be the signal energy magnitude of the harmonic current at each frequency point. The carrier signal frequency domain information set can be a data set characterizing the time-frequency distribution features of harmonic interference on the broadband and low-power wireless carrier communication frequency bands. A communication frame can be the basic unit used for data transmission in carrier communication. Time-domain impact can be the impact of pulse and oscillation interference on communication frame transmission in the time dimension. The communication frame time-domain disturbance information set can be a data set recording the impact of pulse and oscillation interference on communication frames in the time domain. Correlation can be the correspondence between the frequency domain interference of harmonic background noise and the time-domain impact of equipment operation in terms of occurrence time and intensity. Sensitive frequency bands can be specific frequency ranges that significantly affect the signal-to-noise ratio of carrier communication signals and are prone to causing a decline in communication quality. Sensitive time periods can be specific time intervals with high interference intensity and significant impairment to communication frame transmission.

[0039] Specifically, in the dual-mode communication process of biogas power plant power lines, if the signal-to-noise ratio fluctuation is not analyzed based on the electromagnetic disturbance information set, the time-frequency influence and coupling relationship of harmonics and equipment interference will be missed, leading to the distortion of dynamic information of the communication channel. This, in turn, causes inaccurate subsequent bit error rate assessment and channel switching analysis, ultimately resulting in a lack of specificity in the communication assurance plan and seriously affecting the communication stability of power plant production monitoring and equipment scheduling. To address the above problems, an electromagnetic spectrum analyzer deployed at the biogas generator grid connection point is used to simultaneously capture the three-phase current and voltage waveforms of the generator. Through real-time Fourier transform and other spectrum analysis methods, combined with spectral characteristic parameters such as kurtosis and spectral flatness, the signal-to-noise ratio fluctuation is calculated. The calculation extracts the spectral distribution and energy intensity of each harmonic in the broadband (e.g., 2-30MHz) and low-power wireless (e.g., 9-500kHz) frequency bands of power line communication, forming a time-varying "carrier signal frequency domain information set". By calculating the spectral energy difference and comparing it with a benchmark threshold, for example, the analysis may reveal that during the peak gas production period in the afternoon, the energy of the 17th harmonic (e.g., the corresponding carrier center frequency) will significantly increase (e.g., rise by several decibels from the benchmark value). Simultaneously, using high-bandwidth current sensors and data acquisition devices, the power supply circuits of key equipment in the fermentation tank are monitored. Time-domain waveform analysis and feature extraction methods are employed to accurately capture the pulse rising edge and width generated by equipment start-up and shutdown events. The signal-noise sensitivity (SNS) metric is introduced to assess the frequency, amplitude, and oscillation frequency and amplitude during operation. This is achieved through calculations of the overlap between pulse parameters and the communication frame timing window, analysis of the ratio of interference amplitude to the frame signal threshold, and analysis of the coverage of these interferences on the transmission window of the standard communication frame structure (such as preamble and frame header). This quantifies the degree of impact damage to the frame structure, thereby constructing a "communication frame time-domain interference information set." For example, it is recorded that each start-up of a mixer generates a pulse group lasting tens of milliseconds with an amplitude of tens of amperes, completely covering the transmission time slots of several consecutive communication frames. Furthermore, a timestamp alignment and correlation analysis algorithm is used to correlate the aforementioned frequency-domain energy fluctuation sequence with the time-domain interference. By comparing event sequences, a "correlation relationship" can be established. For example, correlation analysis may identify that whenever the mixer starts with a pulse, if the energy of a specific low-power wireless frequency point (such as around 315MHz) in the harmonic spectrum is also at a periodic peak phase, the signal-to-noise ratio of that frequency band will drop sharply during that period. The two exhibit a high degree of temporal synchronicity and strong positive correlation. Finally, based on this correlation model, by setting a threshold (such as the signal-to-noise ratio dropping by more than a certain percentage) and scanning all historical and real-time data, the "sensitive frequency bands" and "sensitive time periods" dominated by coupling interference can be automatically identified and output, forming a "dynamic information set of communication channels" for in-depth analysis.

[0040] The method provided in this embodiment enables multi-dimensional interference analysis and correlation mining, accurately identifying key interference factors and spatiotemporal characteristics affecting communication. This provides comprehensive and accurate data support for the dynamic information set of the communication channel, effectively avoiding the limitations of single-dimensional analysis, improving the accuracy and comprehensiveness of channel state perception, laying a solid foundation for subsequent reliability map construction and contingency plan generation, and ensuring stable transmission of dual-mode communication in complex electromagnetic environments.

[0041] In some embodiments, based on the harmonic information set of a biogas generator, the energy values ​​of harmonic currents at different time points within the carrier communication band of broadband and low-power wireless at different time points during the biogas power generation efficiency variation cycle are analyzed synchronously to obtain the broadband frequency band energy fluctuation sequence and the low-power wireless frequency band energy fluctuation sequence, respectively. The energy values ​​at corresponding time points in the broadband frequency band energy fluctuation sequence and the low-power wireless frequency band energy fluctuation sequence are compared to identify the frequency points and corresponding time periods where the energy values ​​exceed a preset interference threshold. All identified frequency points and corresponding time periods are integrated according to the communication frequency band and time sequence to obtain the carrier signal frequency domain information set. The carrier signal frequency domain information set is used to characterize the time-frequency distribution characteristics of harmonic interference to the communication frequency band.

[0042] A broadband frequency band energy fluctuation sequence can be a dataset recording the changes in harmonic current energy values ​​at various frequency points in chronological order within a broadband carrier communication frequency band. A low-power wireless frequency band energy fluctuation sequence can be a dataset recording the changes in harmonic current energy values ​​at various frequency points in chronological order within a low-power wireless carrier communication frequency band. A preset interference threshold can be a critical value set based on the energy tolerance range of normal carrier communication signal transmission. A frequency point can be a specific frequency location within the broadband or low-power wireless carrier communication frequency band. A corresponding time period can be a specific time interval during which the harmonic current energy value exceeds the preset interference threshold.

[0043] Specifically, in the stability assessment of the dual-mode signal channel of the power line communication in a biogas power plant, if a time-domain disturbance information set of communication frames is not constructed, it will be impossible to clarify the time-domain impact law of pulse and oscillation interference from the fermentation tank equipment on the communication frames. This will make it difficult to establish the correlation between harmonic background noise and time-domain impact, and will make it impossible to accurately identify the core causes of signal-to-noise ratio fluctuations. Consequently, the dynamic information set of the communication channel will be distorted, ultimately leading to deviations in the channel stability assessment results and affecting the pertinence and effectiveness of the communication guarantee plan. To address the aforementioned issues, the approach begins with in-depth time-frequency analysis of the acquired biogas generator harmonic information set. Using spectral analysis techniques (such as short-time Fourier transform or wavelet transform), the energy value of the harmonic current at each discrete frequency point within the entire broadband carrier communication band (such as 2-30MHz) and the low-power wireless carrier communication band (such as 9-500kHz) is simultaneously analyzed within a complete cycle of biogas production and power generation efficiency changes (such as from low load in the early morning to high load at noon). This value is obtained by calculating the average power spectral density within a preset bandwidth near that frequency point. This process generates two time series: a broadband frequency band energy fluctuation series (recording the energy of each frequency point within the broadband frequency band at each time point) and a low-power wireless frequency band energy fluctuation series (recording the energy of each frequency point within the low-power wireless frequency band at each time point). Then, using a threshold comparison method, the energy values ​​of corresponding frequencies in the two series at the same time point are compared in real time with a preset interference threshold (e.g., -75dBm) pre-set according to the communication receiver's noise threshold and bit error rate performance requirements. This allows for the accurate identification of all specific frequencies whose energy values ​​exceed this threshold. The data points (e.g., at 14:00, both the 3.5MHz broadband frequency and the 150kHz low-power wireless frequency simultaneously exceed the limit) and their corresponding time periods (e.g., the exceedance lasted for 30 minutes from 13:45 to 14:15) are identified. Finally, using data integration and structuring methods, all identified frequency points and their corresponding time periods are first classified according to their respective communication frequency bands (broadband or low-power wireless), and then arranged and archived within each category according to the chronological order of occurrence. This ultimately constructs a structured carrier signal frequency domain information set. This information set is essentially a multidimensional data table that clearly characterizes the time-frequency distribution features of harmonic energy at specific frequencies and within specific time windows that significantly interfere with communication, providing a precise "interference map" for subsequent analysis.

[0044] The method provided in this embodiment can sort out the temporal characteristics of equipment interference and the damage mechanism to communication frames, providing accurate temporal data support for subsequent correlation analysis. It can clearly present the specific impact of interference on communication frame transmission, help accurately locate sensitive periods and key interference sources, make the dynamic information set of communication channels more reliable, lay a solid foundation for channel reliability mapping, ensure that subsequent communication protection plans can accurately respond to temporal interference, and improve the scientificity and accuracy of channel stability assessment.

[0045] In some embodiments, based on the interference information set of the fermentation tank equipment, the start time, duration, and intensity changes of pulse interference and oscillation interference generated during the equipment start-up and shutdown phases and operation process are analyzed to obtain the interference time-domain feature set; based on the interference time-domain feature set, the coverage information caused by the sudden moment of pulse interference and the duration of oscillation interference on the communication frame transmission window of the communication channel is analyzed to obtain the communication frame coverage disturbance information; based on the communication frame coverage disturbance information, the impact damage of pulse interference on key fields of the communication frame and the continuous degradation of the overall signal of the communication frame by oscillation interference during the affected period are analyzed to obtain the communication frame time-domain disturbance information set.

[0046] Impulse interference can be a transient, high-amplitude interference signal generated during equipment start-up / shutdown or sudden malfunction. Oscillating interference can be a continuous, periodic interference signal generated during stable equipment operation due to mechanical vibration, electromagnetic coupling, etc. The start time can be the specific point in time when the interference signal begins to act on the communication channel. The duration can be the length of time the interference signal continuously affects the communication channel. The intensity change can be the change over time of parameters characterizing the interference level, such as amplitude and power. The interference time-domain feature set can be a set of features formed after extracting and organizing the time-domain attributes such as the start time, duration, and intensity change of impulse and oscillating interference. The communication frame transmission window can be a fixed time interval in the communication channel used to transmit a single communication frame. Communication frame coverage disturbance information can be the overlap relationship and coverage degree information between the period of interference signal action and the communication frame transmission window on the time axis. The communication frame key fields can be fields in the communication frame that play a crucial role in the effectiveness of data transmission. Impulsive damage can be sudden signal distortion, loss, or other damage caused by transient interference such as impulse interference to the key fields of the communication frame. Persistent degradation can be a long-term, gradual deterioration of parameters such as amplitude, phase, and signal-to-noise ratio of the overall signal of a communication frame caused by periodic interference such as oscillation interference.

[0047] Specifically, in the process of power line communication in biogas power plants, the lack of correlation construction steps will make it impossible to clarify the coupling effect of harmonics and equipment impacts, resulting in the distortion of sensitive frequency bands and time periods, the incomplete dynamic information set of communication channels, and the failure of communication protection plans, causing the link error rate to soar and the channel switching failure to seriously affect the transmission of production data. To address the aforementioned issues: First, time-domain waveform analysis and feature extraction techniques are employed to process the raw current or voltage waveforms captured by the sensors. For example, edge detection algorithms can accurately locate a device startup event and extract the starting time of the resulting pulse interference (e.g., recorded as a time point accurate to milliseconds). Its duration may be extremely short (e.g., a few milliseconds), while the intensity change manifests as the amplitude suddenly increasing to several times (e.g., 5 times) the normal value within a very short time (e.g., within 2 milliseconds). Simultaneously, using spectrum analysis and envelope detection techniques, oscillation interference caused by mechanical vibration or load fluctuations can be identified from the steady-state operating data of the equipment. Its oscillation frequency may be within a typical range (e.g., tens to hundreds of hertz) and may last for a relatively long time (e.g., tens of seconds). All extracted features are structured into a time-domain feature set of interference. Then, high-precision timestamp alignment and window coverage analysis techniques are applied. The time period of each interference event in the feature set is mapped and compared with the periodically repeating communication frame transmission window (each window occupies a fixed time length, such as 2 milliseconds) defined at the bottom layer of the communication protocol stack on the same high-precision time axis. By calculating the intersection of time intervals, communication frame coverage interference information is generated, and specific coverage relationships such as "a certain pulse completely covers the header area of ​​frame number N" or "an oscillating interference lasting several seconds continuously affects the entire transmission process of several subsequent data frames" are accurately quantified. Finally, based on the above accurate coverage relationships, communication signal impairment modeling and assessment are applied. The technology conducts in-depth analysis. For frames covered by pulses, it simulates the signal distortion of key fields (such as frame start delimiters) under high-voltage pulse impact to assess the probability of impact damage, such as bit errors or even complete failure. For frames continuously covered by oscillations, it analyzes the amplitude and phase modulation model of the carrier signal caused by periodic interference to assess the degree of continuous degradation that leads to a systematic decrease in the signal-to-noise ratio of the entire frame. Finally, it summarizes and structures the specific damage assessment results at all frame levels to form a complete set of communication frame time-domain disturbance information that can directly reflect "when, which frame, and what kind of damage" is suffered.

[0048] By utilizing the method provided in this embodiment, the bidirectional coupling positive feedback relationship between harmonic background noise and equipment time-domain impact is explored, accurately capturing the dynamic coupling mechanism of communication channel degradation. This provides a core basis for the accurate identification of sensitive frequency bands and sensitive time periods, making the dynamic information set of the communication channel more complete and targeted. Based on this, subsequent reliability mapping and contingency plan formulation are more in line with the actual electromagnetic environment, effectively reducing the bit error rate and the risk of switching failure, and providing key support for the stable dual-mode communication of biogas power plants.

[0049] In some embodiments, based on frequency points and corresponding time periods, combined with start time and duration, the overlap information of the frequency domain interference period of harmonic background noise and the time period of equipment operation domain impact on the time axis is analyzed to obtain a spatiotemporally overlapping interference period set; based on the spatiotemporally overlapping interference period set, according to the energy value of the corresponding frequency point in the carrier signal frequency domain information set and the interference intensity of the corresponding time period in the communication frame time domain disturbance information set, the coordinated change trend between the energy fluctuation of harmonic background noise and the change of equipment impact intensity in the overlapping period is analyzed to obtain an interference intensity coupling feature set; based on the interference intensity coupling feature set, the interaction between harmonic background noise aggravating time domain impact on communication frame damage and the abnormal rise of harmonic energy during time domain impact is identified to obtain a correlation relationship; the interaction is manifested as a bidirectional coupling positive feedback formed between harmonic background noise aggravating communication frame damage and the abnormal rise of harmonic energy during time domain impact; the correlation relationship is used to characterize the dynamic coupling information of continuous harmonic interference and sudden equipment impact jointly causing communication channel degradation during the production stage in the electromagnetic environment of biogas power plant.

[0050] The corresponding time period can be the specific time range within which a frequency point is affected by harmonic interference. Harmonic background noise can be the continuous spectral interference signal generated during the grid-connected operation of a biogas generator. The frequency domain interference period can be the time range within which harmonic background noise interferes with the communication frequency band. The spatiotemporally overlapping interference period set can be the specific set of time periods on the time axis where the harmonic frequency domain interference period and the equipment time domain impact period overlap. The interference intensity coupling feature set can be the set of coordinated change patterns between the energy fluctuations of harmonic background noise and the changes in equipment impact intensity within the overlapping period. The interaction can be the bidirectional promoting relationship formed between the amplification of communication frame damage by harmonic background noise and the abnormal rise of harmonic energy during the time domain impact. The bidirectional coupling positive feedback can be the mechanism by which enhanced harmonic interference further amplifies the damage to communication frames caused by equipment impact, while the occurrence of equipment impact leads to an abnormal increase in harmonic energy, forming a cyclical reinforcement mechanism. Continuous harmonic interference can be the continuous and stable spectral interference generated during the grid-connected operation of a biogas generator. Sudden equipment impact can be the pulse and oscillation interference with high intensity that suddenly occurs during the start-up, shutdown, or operation of the fermentation tank equipment. Dynamic coupling information can be the dynamic data of the correlation and mutual influence between the two types of interference in time and intensity.

[0051] Specifically, in the power line communication process of a biogas power plant, if the combined effect of harmonic background noise and time-domain impact is ignored, it will be impossible to accurately locate the core causes of signal-to-noise ratio fluctuations and communication failures. This leads to persistently high bit error rates in the communication link and frequent carrier channel switching failures, thereby affecting the power plant's production scheduling and safe operation, causing serious production delays and safety hazards. To address these issues: First, time-frequency correlation alignment technology is used to centrally label each sensitive frequency point (e.g., the 433MHz center frequency within the low-power wireless communication band) and its associated frequency domain information. The corresponding time period identified as being disturbed (e.g., a 30-minute time window from 10:00 AM to 10:30 AM) is compared with the precise start time (e.g., a mixer starts at 10:05 AM) and duration (e.g., the oscillation interference it generates lasts for 25 minutes) of each device interference event recorded in the time-domain disturbance information set of the communication frame. This comparison is performed at the millisecond level on the same high-precision time axis. Simultaneously, core evaluation indicators of SNS (Social Network Analysis) (node ​​degree, clustering coefficient, shortest path length) are introduced to quantify the correlation between frequency points and device events. This process identifies and extracts all overlapping time intervals, forming a set of spatiotemporally overlapping interference periods (e.g., explicitly identifying the 25 minutes from 10:05 to 10:30 as the critical overlap period). Simultaneously, based on the ITU-T P.530 standard, signal interference levels are classified (levels 1-5, level 1 being no interference and level 5 being severe interference), and the signal level of each overlapping period is labeled. Then, for these overlapping periods, a coupling strength co-quantitative analysis method is used to process the synchronized time-series data: on the one hand, the harmonics at specific frequency points (such as 150kHz mentioned above) within the overlapping period are extracted. The energy sampling value sequence (whose value may fluctuate from -50dBm to -45dBm) is used to calculate the energy spectral features of wavelet packets. By decomposing 3-5 layers of wavelet packets, 12 spectral feature parameters such as energy entropy, spectral kurtosis, and spectral flatness of each frequency band are obtained, and the energy fluctuation curve is plotted. On the other hand, the key indicator sequence reflecting the impact intensity of the equipment is extracted from the communication channel monitored at the same time (such as the bit error rate increasing sharply from 1.0E-5 to 1.0E-3, or the impulse noise voltage amplitude climbing from 200mV to 500mV), and the impact intensity change curve is plotted. By calculating the sliding window cross-correlation coefficient and time-delay mutual information between the two curves, and establishing a regression model such as "harmonic energy increment - impact intensity increment", the coordinated change trend and quantitative dependence of the two "rising and falling together" are quantitatively characterized, thereby modeling and generating an interference intensity coupling feature set.Finally, based on this feature set, causal inference was performed using a bidirectional feedback mechanism identification algorithm. For example, the algorithm not only identified the phenomenon that the peak harmonic energy and the peak impact intensity occurred simultaneously at 10:15, but also, through backtracking analysis of production and communication data links over longer periods (such as several hours), it found that whenever large power equipment (such as a biogas compressor with a rated power of 500kW) starts up (time-domain impact), the total harmonic distortion (THD) of the bus voltage increases by about 2 percentage points, and the amplitude of specific harmonics (such as the 11th harmonic, corresponding to about 550Hz) increases particularly significantly. Conversely, analysis of historical data shows that during periods when the amplitude of background harmonics (such as the 7th harmonic) is consistently higher than the threshold (e.g., 0.5%), the interference tolerance of the communication receiver to equipment pulses of equal intensity (e.g., 300mV) decreases by about 40%, and the frame error rate surges accordingly. This series of analyses ultimately reveals a two-way coupled positive feedback mechanism: "Harmonic background noise degrades the channel noise floor, thereby exacerbating the actual damage to communication frames caused by equipment impacts; at the same time, the drastic load changes caused by equipment impacts in turn excite the generator set to generate stronger harmonic emissions," thus completing the construction of the correlation.

[0052] The method provided in this embodiment accurately captures the synergistic effect and mutual reinforcement mechanism of the two types of interference, breaking through the limitations of existing single interference analysis. It provides accurate dynamic coupling data for the mapping of communication channel reliability, making subsequent communication protection plans more targeted, effectively improving the accuracy and scientific nature of channel stability assessment, ensuring stable transmission of dual-mode signals, and reducing the risk of communication failure.

[0053] In some embodiments, based on sensitive frequency bands and sensitive time periods, the variation information of power generation efficiency under different gas production and load conditions is analyzed to obtain the fermentation process-power generation efficiency mapping relationship; based on the fermentation process-power generation efficiency mapping relationship and combined with the correlation relationship, the variation trend of signal-to-noise ratio of broadband and low-power wireless carrier communication channels under the variation of power generation efficiency is analyzed to obtain the stage characteristics of channel performance evolution with power generation efficiency; based on the stage characteristics of channel performance evolution with power generation efficiency, the rise magnitude and rise rate of data transmission bit error rate in each period of the stage characteristics are analyzed to obtain link bit error rate dynamic evolution information; based on the link bit error rate dynamic evolution information, the shadowing effect of the cross change of broadband and low-power wireless channel performance on the channel switching decision conditions centered on the switching point of each period of the stage characteristics is analyzed to obtain communication channel switching dynamic information; combining the link bit error rate dynamic evolution information and the communication channel switching dynamic information, with the power generation efficiency change cycle as the time series framework, the mapping relationship and stage characteristics are integrated to draw a communication channel reliability map reflecting the dynamic changes of communication channel reliability.

[0054] The fermentation process-power generation efficiency mapping relationship can be a quantitative correlation model between the change in biogas production and the output efficiency of the biogas generator during biogas fermentation. The stage characteristics of channel performance evolution with power generation efficiency can be the signal-to-noise ratio fluctuation law of broadband and low-power wireless carrier communication channels, exhibiting divisible stage characteristics as power generation efficiency changes. Link bit error rate dynamic evolution information can be a dynamic description of the magnitude and speed of the increase in data transmission bit error rate at each stage of power generation efficiency change. Communication channel switching dynamic information can be the ambiguity or obscuring effect caused by the relative superiority or inferiority of broadband and low-power wireless channel performance on preset switching decision conditions near critical switching points of power generation efficiency change.

[0055] Specifically, in the dual-mode communication process of biogas power lines, if the impact of biogas fermentation on power generation efficiency and the dynamic evolution of the communication channel are not analyzed, the chain relationship of "fermentation-efficiency-electromagnetic environment-communication performance" will be ignored. This will lead to an inability to predict the trend of increasing bit error rate under different gas production and load conditions, and it will also be difficult to identify the risk of channel switching conditions causing obstruction. Consequently, communication protection plans will lack specificity, leading to hazards such as interruption of critical business communication and failure of dispatch command transmission. To address the above problems: First, by deploying methane concentration sensors and generator power meters, continuous data on gas production (e.g., daily cubic meters) and output power are collected. Within the identified "sensitive periods," combined with baseline power fluctuations, a multivariate regression analysis method is used to construct a quantitative mapping model in which power generation efficiency increases with increasing gas production, but is constrained by real-time load (e.g., grid-connected power demand). Subsequently, using this model as input, the spectral data recorded by the harmonic analyzer is analyzed in different ranges of power generation efficiency change (e.g., the ramp-up stage from 65% to 80% efficiency). The study investigates the energy shift towards communication frequency bands (e.g., extracting harmonic component distribution near low-power wireless carrier frequency bands using Fast Fourier Transform) and how start-up and shutdown events become more frequent in equipment monitoring logs. Furthermore, using signal processing techniques, the study calculates the signal-to-noise ratio (SNR) fluctuation curves of broadband and low-power wireless channels within these evolution intervals. Channel performance stages are then defined based on dynamic SNR thresholds (e.g., setting SNR>20dB as a "stable period," 10-20dB as a "transition period," and <10dB as a "high-risk period"). Subsequently, frame calibration records from communication units for the corresponding periods are retrieved. The sequence is verified, and statistical and trend fitting algorithms are used to quantify the magnitude and rate of bit error rate (BER) increase (e.g., exponential fitting is used to describe the BER increase trend over time during the "transition period"). Simultaneously, channel handover decision conditions are set (e.g., requiring the broadband signal-to-noise ratio to be consistently better than low-power wireless for a certain threshold, such as 4 dB, for a certain duration). Monte Carlo simulation is used to simulate the cross-fluctuation of dual-mode signal-to-noise ratio at the inflection point of power generation efficiency. The frequency of handover conditions being frequently triggered and broken is statistically analyzed to identify high-risk periods of handover failure. Finally, the above dynamic information is... By integrating the data into a unified timeline, a comprehensive reliability map is drawn using data visualization methods. This map uses the power generation efficiency curve as a background and overlays contour lines of the bit error rate and hot zones of the handover failure probability. The map features are calculated jointly using time-frequency domain indicators, such as introducing the signal stability index (SSI) and signal-to-noise ratio fluctuation variance to comprehensively evaluate the signal level. Communication reliability is divided into three levels—"high," "medium," and "low"—based on a weighted score of three indicators: bit error rate, signal-to-noise ratio, and handover success rate (the weights can be set to 4:3:3). This reveals the evolution of communication performance and the distribution of risks during the power generation efficiency ramp-up process.

[0056] The method provided in this embodiment accurately captures the dynamic patterns of bit error rate increases and channel switching failures, generating a reliability map of the entire production cycle. This not only fills the gap in the linkage analysis of production process and communication performance, providing a core basis for the subsequent accurate formulation of contingency plans, but also improves the dynamic adaptability of channel stability assessment, effectively avoids the risk of communication interruption, and ensures the continuous stability of key services such as power generation equipment monitoring and dispatch command transmission.

[0057] In some embodiments, based on sensitive frequency bands and sensitive time periods, the fluctuation information of biogas generator output power under communication interference during sensitive time periods is analyzed to obtain the interference power baseline; based on the interference power baseline, according to the collected gas production data, the impact of gas production growth on increasing power generation, and the boundary effect of increased generator load on approaching the power upper limit and lowering efficiency are analyzed to obtain power-efficiency dynamic coupling information; based on the power-efficiency dynamic coupling information, the trajectory of power generation efficiency increasing with the increase of gas production data, but whose lower limit is constrained by the load conditions and the power generation baseline, is depicted to obtain the fermentation process-power generation efficiency mapping relationship.

[0058] The baseline for interfered power generation can be the reference value for the fluctuation of biogas generator output power under communication interference conditions during sensitive periods. Gas production data can be the total gas production of the fermentation tanks in the biogas power plant. Power-efficiency dynamic coupling information can be the information on the mutual influence between power generation and power generation efficiency.

[0059] Specifically, in the channel stability assessment system for dual-mode power line communication signals, the absence of this mapping makes it impossible to accurately correlate the dynamic changes in gas production, load, and power generation efficiency. This leads to an inability to predict the evolution trend of the electromagnetic environment, resulting in inaccurate channel performance stage characteristic analysis, communication assurance plans becoming detached from actual production scenarios, and ultimately causing a surge in link bit error rate and frequent channel switching failures, severely damaging communication stability. To address these issues: First, three key time-series data items are synchronously acquired from the power plant monitoring system via a data interface: time tags based on identified "sensitive periods," a three-phase active power sampling sequence of the biogas generator within the corresponding period (e.g., one point per second, sourced from the power transmitter), and "gas production data" (e.g., cubic meters per minute) reported by the gas flow meter in the fermentation tank. Then, a sliding window averaging combined with Butterworth bandpass filtering is used to process the power sequence, filtering out grid dispatch step components and retaining periodic and sudden fluctuations to form a " The system establishes a baseline for the interfered power generation and simultaneously assesses signal quality, calculating the signal-to-noise ratio (SNR) and harmonic distortion rate (THD). Based on the IEC 61000-4-30 standard, signal levels are categorized (Level A: SNR ≥ 35 dB, THD ≤ 3%; Level B: SNR ≥ 25 dB, THD ≤ 5%; Level C: others). Next, a time-frequency domain spectral feature extraction method is introduced to calculate the spectral kurtosis and envelope peak factor of the power sequence during sensitive periods, in order to identify impulsive and harmonic vibrations. The process involves, for example, calculating the average increase in power generation for each unit increase in gas production (e.g., 10 cubic meters per hour) over multiple past production cycles. It also analyzes the decay pattern of this increase across different load ranges (e.g., light load range below 60%, high-efficiency range between 60% and 85%, and high-load range above 85%), thereby quantifying the "power-efficiency dynamic coupling information." This clarifies the driving effect of gas production and the boundary constraint effect of load. Finally, based on this coupling information, the efficiency value calculated from the baseline of disturbed power generation is used as the dynamic lower limit. Using the efficiency-gas production regression curves under different load ranges as a segmented framework, nonlinear curve fitting techniques (e.g., using an exponential decay model or a polynomial model) are employed to fit the trajectory on the two-dimensional plane of gas production and power generation efficiency. This generates a continuous curve that clearly shows efficiency increasing with gas production, but with the upward slope suppressed by load and always above the dynamic lower limit. This curve is the final, precisely quantified "fermentation process-power generation efficiency mapping relationship," providing the core basis for predicting the stage of power generation efficiency under any gas production state.

[0060] The method provided in this embodiment accurately captures the intrinsic relationship between fermentation and power generation efficiency, clearly defines the efficiency change pattern under different gas production and loads, provides reliable data support for subsequent channel performance analysis, makes the analysis of bit error rate evolution and channel switching more in line with actual production, makes the communication guarantee plan more targeted, effectively improves the scientific nature of channel stability assessment, helps to avoid communication risks in advance, and ensures continuous and stable communication in the complex electromagnetic environment of biogas power plants.

[0061] In some embodiments, based on the mapping relationship between fermentation process and power generation efficiency, the overall changes in the electromagnetic environment constituted by the harmonic information set of the biogas generator and the interference information set of the fermentation tank equipment driven by the change in power generation efficiency are analyzed to obtain the evolution characteristics of the interference environment. Based on the evolution characteristics of the interference environment and combined with the correlation, the effects of the spectral distribution change of harmonic background noise and the intensity change of time-domain impact on the signal-to-noise ratio fluctuation of the broadband carrier communication channel and the low-power wireless carrier communication channel are analyzed in different value ranges of the change in power generation efficiency, respectively, to obtain the dual-mode channel performance response characteristics. Based on the dual-mode channel performance response characteristics, the change in power generation efficiency is used as a reference axis to correlate and map the complete law of the signal-to-noise ratio fluctuation tendency of the broadband and low-power wireless carrier communication channels from the beginning, development to transformation, to obtain the stage characteristics.

[0062] The electromagnetic environment can be defined as the environmental system affecting communication channel performance, comprised of the harmonic information set of the biogas generator and the interference information set of the fermentation tank equipment. Spectral distribution variation can be the frequency distribution variation of harmonic background noise within different power generation efficiency ranges in the broadband and low-power wireless carrier communication frequency bands. Intensity variation can be the variation of interference intensity of time-domain impacts within different power generation efficiency ranges. Dual-mode channel performance response characteristics can be the response patterns and performance characteristics of broadband and low-power wireless carrier communication channels to signal-to-noise ratio (SNR) fluctuations under different interference environments. The reference axis can be an analytical baseline used to correlate and map the SNR fluctuation patterns of dual-mode channels, with the power generation efficiency variation amplitude as a benchmark. The SNR fluctuation tendency can be the complete trend of SNR variation in broadband and low-power wireless carrier communication channels from the initial state, development process, to the transition node. Stage characteristics can be the complete set of laws governing the evolution of channel performance with power generation efficiency, formed by integrating the dual-mode channel performance response characteristics with the power generation efficiency variation amplitude as a reference.

[0063] Specifically, during power line communication in biogas power plants, changes in power generation efficiency can cause changes in the electromagnetic environment, which may lead to misjudgment of channel performance, resulting in problems such as a sudden increase in bit error rate and improper channel switching timing. This can cause interruption of production data transmission, waste of communication resources, and seriously affect the normal operation of equipment scheduling and monitoring services in biogas power plants.To address the aforementioned issues: Based on the established "fermentation process-power generation efficiency mapping relationship," the power generation efficiency gradient threshold method (e.g., setting the efficiency change rate ±5% as the interval boundary) is used to determine the current power generation efficiency change range (e.g., identifying that efficiency is transitioning from the "high-efficiency stable zone" to the "fluctuating and declining zone"). Utilizing the "biogas generator harmonic information set" collected in real-time by a power quality analyzer deployed at the biogas generator grid connection point, spectral feature extraction methods such as power spectral density (PSD) calculation, total harmonic distortion (THD), and characteristic harmonic amplitude proportion analysis are employed to analyze the spectral distribution changes of harmonic current within this efficiency range. For example, it is found that the energy of the 5th and 7th harmonics significantly increases and spreads to the high-frequency bands used by broadband PLCs (e.g., above 10MHz). The harmonic spread coefficient (high-frequency harmonic energy proportion ≥30%) is used to further analyze the results. (Judging as significant spread) This trend is quantified by combining the "fermentation tank equipment interference information set" collected by the transient recorder on the power circuit of the fermentation tank equipment. The time-domain impact intensity is quantified by indicators such as pulse peak factor (peak / effective value), pulse duration variance, and impact energy integral. The "time-domain impact intensity change" of equipment start-up and shutdown is analyzed. For example, it is found that in the same efficiency range, the number of start-ups and shutdowns of the agitator per hour increases due to process adjustments, resulting in pulse interference with higher amplitude and wider pulse width. Then, the above dynamic "harmonic background noise spectrum distribution change" and "time-domain impact intensity change" information are input into the established "correlation relationship" model that reveals the coupling mechanism between the two to analyze their combined effect on the dual-mode channel. Through comparison of simulation and measured data, it is found that in the efficiency decline range, the enhancement of high-frequency harmonic energy will significantly worsen the "signal-to-noise ratio fluctuation" of the "broadband carrier communication channel" that depends on this frequency band, making it The average value decreases (e.g., by 3dB); while low-power wireless channels, operating at lower frequencies (e.g., below 100kHz), are relatively insensitive to the aforementioned harmonics, but the strong pulse interference generated by the frequent start-stop of the stirrer can cause serious instantaneous bit errors. This difference in impact constitutes the "dual-mode channel performance response characteristics". Ultimately, the change in power generation efficiency is used as a substitute axis for time or production process, and the channel performance response patterns obtained from the above analysis (e.g., "the broadband signal-to-noise ratio continues to decline, and the low-power wireless anti-pulse interference capability is strained") are correlated and mapped to it, thereby depicting "stage characteristics" with clear starting, development, and transition nodes. For example, it is clear that "the middle stage of efficiency fluctuation and decline" is the key stage in which the broadband channel deteriorates rapidly and the low-power wireless channel faces the risk of impact. The whole process relies on the fusion analysis of multi-source monitoring data, the dynamic calling of the interference coupling model, and the differential evaluation technology of dual-mode channel performance.

[0064] The method provided in this embodiment accurately maps the correlation between power generation efficiency and dual-mode channel performance, providing a scientific basis for subsequent bit error rate prediction and channel switching. It can predict channel risks at different production stages in advance, optimize communication strategies accordingly, reduce the probability of bit error rate increases and switching failures, ensure the continuity and accuracy of data transmission, improve the stability of power line communication dual-mode signals in complex electromagnetic environments, and build a solid communication support for the efficient operation of biogas power plants.

[0065] In some embodiments, based on the stage characteristics mapped in the communication channel reliability map, the channel performance risk level corresponding to different power generation efficiency intervals in the fermentation process-power generation efficiency mapping relationship is analyzed to obtain production stage risk classification information; based on the production stage risk classification information, according to the preset carrier communication mode priority list and channel parameter configuration library, the optimal mode switching timing and parameter adjustment strategy to ensure communication continuity under each level of risk production stage are analyzed to obtain a set of communication guarantee plans; according to the execution process of the set of communication guarantee plans, the improvement effect of the dynamic evolution information of link bit error rate and the dynamic information of communication channel switching after the plan is triggered within the power generation efficiency change cycle is analyzed, and combined with gas production data and power generation efficiency change amplitude, a channel stability assessment log is generated.

[0066] The risk classification information for the production stage can be a communication risk level identifier for the production stages of a biogas power plant, based on the correlation between different power generation efficiency ranges and channel performance. The preset carrier communication mode priority list can be a set of pre-defined rules to guide the selection order of carrier communication modes under different risk scenarios. The channel parameter configuration library can be a database storing parameters such as communication frequency, power, and encoding methods suitable for different risk levels and production stages. The communication assurance contingency plan set can be a collection of executable solutions, including optimal mode switching timing and parameter adjustment strategies, for each level of production stage risk.

[0067] Specifically, at different production stages of a biogas power plant, fluctuations in power generation efficiency cause dynamic changes in the electromagnetic environment. Continuous harmonics coupled with sudden equipment impacts lead to fluctuations in channel signal-to-noise ratio, increased bit error rate, and even switching failures. In this scenario, the lack of targeted communication guarantees can cause interruptions in production monitoring data transmission and distortion of equipment scheduling instructions. This can result in uncontrolled production parameters or, in severe cases, equipment malfunctions, affecting power generation efficiency and even inducing safety hazards, seriously restricting the stable operation of the power plant. To address the aforementioned issues: First, using graph feature extraction and correlation analysis techniques, the critical power generation efficiency thresholds that cause channel performance inflection points are identified from the "stage feature" curves mapped from the graph. These thresholds are then correlated with specific production intervals defined by the "fermentation process-power generation efficiency mapping relationship" (e.g., the high power generation efficiency and high interference interval corresponding to peak gas production, and the low power generation efficiency and relatively stable interval corresponding to trough gas production). This automatically outputs a "production stage risk classification information," directly quantifying the production status into different levels (e.g., high risk, medium risk, low risk) of communication guarantee requirements. Subsequently, a preset "carrier communication mode priority list" (e.g., specifying priority switching to a low-power wireless mode with stronger anti-pulse interference capability under extreme interference) and a "channel parameter configuration library" (e.g., containing a set of error correction coding schemes for different signal-to-noise ratio levels) are invoked. Using a rule engine and strategy matching algorithm, the "optimal mode switching timing" and "parameter adjustment strategy" to ensure communication continuity are dynamically calculated for each identified risk level. For example, when it is determined that an imminent risk level is about to be reached... When entering the "high-risk" phase, the algorithm will issue a command to switch the main communication channel from broadband to low-power wireless before the power generation efficiency reaches a certain threshold (such as efficiency dropping to a specific value, such as 75% of the rated value). At the same time, the modulation method will be adjusted to a standard with stronger noise resistance, and the redundancy of forward error correction coding will be increased. This series of operations is encapsulated into a complete "communication guarantee plan". After the plan is executed, the changes in "link bit error rate dynamic evolution information" and "communication channel switching dynamic information" are continuously tracked through real-time data stream monitoring and comparative analysis technology to evaluate the actual "improvement effect" of the plan. For example, it is observed whether the bit error rate curve is effectively suppressed below the allowable threshold. Finally, using log structure synthesis technology, the conditions for triggering the plan, the specific actions executed, the observed key performance indicator improvement data, and the production context information such as "gas production data" and "power generation efficiency change range" during the period are integrated to generate a detailed and traceable "channel stability assessment log", completing the closed loop from risk perception, strategy generation, execution to effect evaluation.

[0068] The method provided in this embodiment dynamically adapts to the risks of different production stages, effectively resists electromagnetic interference by accurately matching communication modes and parameters, ensures communication continuity and data transmission accuracy, and at the same time, the generated evaluation logs provide data support for subsequent strategy optimization and equipment maintenance, significantly reducing the probability of communication interruption and switching failure, ensuring the smooth operation of key businesses such as production monitoring and equipment scheduling, helping power plants achieve intelligent and refined management, and improving overall operational stability and efficiency.

[0069] Figure 3 A schematic diagram of a channel stability evaluation system for dual-mode power line communication signals provided in an embodiment of this application is shown below. Figure 3 As shown, the channel stability evaluation system 300 for dual-mode power line communication signals in this embodiment includes: a fluctuation analysis module 301, a dynamic evolution module 302, and a communication evaluation module 303.

[0070] The fluctuation analysis module 301 is used to acquire the electromagnetic disturbance information set of the biogas power plant, and based on the electromagnetic disturbance information set, analyze the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the action of grid-connected harmonics of the biogas generator to obtain the communication channel dynamic information set; the dynamic evolution module 302 is used to analyze the impact of biogas fermentation on power generation efficiency based on the communication channel dynamic information set, and the dynamic evolution information of the resulting increase in communication channel link bit error rate and carrier communication channel switching failure, to obtain the communication channel reliability map; the communication evaluation module 303 is used to dynamically generate communication guarantee plans for different production stages based on the communication channel reliability map, and output the channel stability evaluation log.

[0071] Optionally, when the fluctuation analysis module 301 analyzes the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the influence of harmonics from the biogas generator grid connection based on the electromagnetic disturbance information set, and obtains the communication channel dynamic information set, it is specifically used for: the electromagnetic disturbance information set including the biogas generator harmonic information set and the fermentation tank equipment interference information set; based on the biogas generator harmonic information set, analyzing the spectral distribution and energy intensity of the harmonic current generated by the generator grid connection in the broadband and low-power wireless carrier communication frequency bands, and obtaining the carrier signal frequency domain information set; based on the fermentation tank equipment interference information set, analyzing the impact of pulse and oscillation interference generated by the equipment start-up, shutdown and operation on the time domain of the communication frame, and obtaining the communication frame time domain disturbance information set; establishing the correlation between the harmonic background noise and the time domain impact in terms of occurrence time and impact intensity according to the carrier signal frequency domain information set and the communication frame time domain disturbance information set; and identifying the sensitive frequency bands and sensitive time periods that cause signal-to-noise ratio fluctuations and communication failures based on the correlation, and obtaining the communication channel dynamic information set.

[0072] Optionally, during the construction of the carrier signal frequency domain information set, the fluctuation analysis module 301 is specifically used to: based on the biogas generator harmonic information set, synchronously analyze the energy values ​​of harmonic currents at different time points within the biogas power generation efficiency change cycle at each frequency point in the broadband and the low-power wireless frequency band, respectively obtaining the broadband frequency band energy fluctuation sequence and the low-power wireless frequency band energy fluctuation sequence; compare the energy values ​​at corresponding time points in the broadband frequency band energy fluctuation sequence and the low-power wireless frequency band energy fluctuation sequence to identify the frequency points and corresponding time periods where the energy values ​​exceed a preset interference threshold; integrate all the identified frequency points and corresponding time periods according to the communication frequency band and time sequence to obtain the carrier signal frequency domain information set; the carrier signal frequency domain information set is used to characterize the time-frequency distribution characteristics of harmonic interference to the communication frequency band.

[0073] Optionally, the fluctuation analysis module 301, during the construction of the communication frame time-domain disturbance information set, is specifically used for: based on the interference information set of the fermentation tank equipment, analyzing the start time, duration, and intensity changes of pulse interference and oscillation interference generated during the equipment start-up and shutdown phases and operation process to obtain an interference time-domain feature set; based on the interference time-domain feature set, analyzing the coverage information caused by the sudden moment of the pulse interference and the duration of the oscillation interference on the communication frame transmission window of the communication channel to obtain communication frame coverage disturbance information; based on the communication frame coverage disturbance information, analyzing the impact damage of the pulse interference on key fields of the communication frame and the continuous degradation of the overall signal of the communication frame by the oscillation interference during the affected period to obtain the communication frame time-domain disturbance information set.

[0074] Optionally, during the process of constructing the correlation relationship, the fluctuation analysis module 301 is specifically used to: based on the frequency point, the corresponding time period, and combined with the start time and the duration period, analyze the overlap information on the time axis between the frequency domain interference period of the harmonic background noise and the time period affected by the time domain impact of the equipment operation, to obtain a set of spatiotemporally overlapping interference time periods; based on the set of spatiotemporally overlapping interference time periods, analyze the energy fluctuation of the harmonic background noise and the impact strength of the equipment during the overlapping time periods according to the energy value of the corresponding frequency point in the carrier signal frequency domain information set and the interference intensity of the corresponding time period in the communication frame time domain disturbance information set. The coordinated change trend between degree changes yields an interference intensity coupling feature set; based on the interference intensity coupling feature set, the interaction between harmonic background noise aggravating time-domain impact on communication frame damage and the abnormal rise of harmonic energy during time-domain impact is identified, yielding the correlation relationship; the interaction is manifested as a bidirectional coupled positive feedback between the harmonic background noise aggravating communication frame damage and the abnormal rise of harmonic energy during time-domain impact; the correlation relationship is used to characterize the dynamic coupling information of continuous harmonic interference and sudden equipment impact jointly causing communication channel degradation during the production stage in the electromagnetic environment of biogas power plants.

[0075] Optionally, when the dynamic evolution module 302 analyzes the impact of biogas fermentation on power generation efficiency based on the communication channel dynamic information set, leading to an increase in the communication channel link bit error rate and failure of carrier communication channel switching, and obtains a communication channel reliability map, it is specifically used to: analyze the changes in power generation efficiency under different gas production and load conditions based on the sensitive frequency band and the sensitive time period, and obtain the fermentation process-power generation efficiency mapping relationship; based on the fermentation process-power generation efficiency mapping relationship and the correlation relationship, analyze the changing trend of the signal-to-noise ratio of broadband and low-power wireless carrier communication channels under the change in power generation efficiency, and obtain the stage characteristics of channel performance evolution with power generation efficiency; based on The stage characteristics of channel performance evolution with power generation efficiency are analyzed. The magnitude and rate of increase of data transmission bit error rate in each stage characteristic period are analyzed to obtain dynamic evolution information of link bit error rate. Based on the dynamic evolution information of link bit error rate, the shadowing effect of the cross change of broadband and low-power wireless channel performance on the channel switching decision conditions within a preset floating time interval centered on the switching point of each stage characteristic period is analyzed to obtain communication channel switching dynamic information. Combining the dynamic evolution information of link bit error rate and the dynamic information of communication channel switching, with the power generation efficiency change cycle as the time series framework, the mapping relationship and the stage characteristics are integrated to draw the communication channel reliability map reflecting the dynamic changes of communication channel reliability.

[0076] Optionally, the dynamic evolution module 302, in the process of constructing the fermentation process-power generation efficiency mapping relationship, is specifically used for: based on the sensitive frequency band and combined with the sensitive time period, analyzing the fluctuation information of the biogas generator output power under the communication interference environment during the sensitive time period, and obtaining the interference power generation power baseline; based on the interference power generation power baseline, according to the collected gas production data, analyzing the impact of gas production growth on increasing power generation, and the boundary effect of increased generator load on approaching the power upper limit and lowering efficiency, and obtaining power-efficiency dynamic coupling information; based on the power-efficiency dynamic coupling information, depicting the trajectory of power generation efficiency increasing with the increase of gas production data, but its lower limit being constrained by the load conditions and the power generation power baseline, and obtaining the fermentation process-power generation efficiency mapping relationship.

[0077] Optionally, the dynamic evolution module 302, during the construction of the stage characteristics, is specifically used for: analyzing the overall change in the electromagnetic environment constituted by the biogas generator harmonic information set and the fermentation tank equipment interference information set, based on the fermentation process-power generation efficiency mapping relationship, to obtain the interference environment evolution characteristics; based on the interference environment evolution characteristics, combined with the correlation relationship, analyzing the effects of the spectral distribution change of the harmonic background noise and the intensity change of the time-domain impact on the signal-to-noise ratio fluctuation of the broadband carrier communication channel and the low-power wireless carrier communication channel, respectively, within different value ranges of the power generation efficiency change range, to obtain the dual-mode channel performance response characteristics; based on the dual-mode channel performance response characteristics, using the power generation efficiency change range as a reference axis, correlating and mapping out the complete law of the signal-to-noise ratio fluctuation tendency of the broadband and low-power wireless carrier communication channels from the beginning, development to transformation, to obtain the stage characteristics.

[0078] Optionally, when the communication evaluation module 303 dynamically generates communication assurance plans for different production stages based on the communication channel reliability map and outputs channel stability evaluation logs, it is specifically used to: analyze the channel performance risk level corresponding to different power generation efficiency intervals in the fermentation process-power generation efficiency mapping relationship based on the stage characteristics mapped in the communication channel reliability map, and obtain production stage risk classification information; based on the production stage risk classification information, analyze the optimal mode switching timing and parameter adjustment strategy to ensure communication continuity under each level of risk production stage according to the preset carrier communication mode priority list and channel parameter configuration library, and obtain a set of communication assurance plans; according to the execution process of the set of communication assurance plans, analyze the improvement effect of the dynamic evolution information of the link bit error rate and the dynamic information of the communication channel switching after the plan is triggered within the power generation efficiency change cycle, and generate the channel stability evaluation log by combining the gas production data and the power generation efficiency change amplitude.

[0079] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A method for evaluating the channel stability of dual-mode power line communication signals, characterized in that, include: The electromagnetic disturbance information set of the biogas power plant is obtained. Based on the electromagnetic disturbance information set, the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the action of grid-connected harmonics of biogas generators is analyzed to obtain the dynamic information set of communication channels. Based on the dynamic information set of the communication channel, the impact of biogas fermentation on power generation efficiency is analyzed, which in turn leads to the dynamic evolution information of increased communication channel link bit error rate and carrier communication channel switching failure, and a communication channel reliability map is obtained. Based on the communication channel reliability map, communication assurance plans for different production stages are dynamically generated, and channel stability assessment logs are output.

2. The method according to claim 1, characterized in that, Based on the electromagnetic disturbance information set, the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the influence of grid-connected harmonics from biogas generators is analyzed to obtain a dynamic information set of the communication channel, including: The electromagnetic disturbance information set includes the biogas generator harmonic information set and the fermentation tank equipment interference information set. Based on the biogas generator harmonic information set, the spectrum distribution and energy intensity of the harmonic current generated by the generator grid connection in the broadband and low-power wireless carrier communication frequency bands are analyzed to obtain the carrier signal frequency domain information set. Based on the interference information set of the fermentation tank equipment, the impact of pulse and oscillation interference generated by the start-up, shutdown and operation of the equipment on the time domain of communication frames is analyzed, and the time domain disturbance information set of communication frames is obtained. Based on the carrier signal frequency domain information set and the communication frame time domain disturbance information set, establish the correlation between harmonic background noise and the time domain impact in terms of occurrence time and impact intensity. Based on the aforementioned correlation, sensitive frequency bands and sensitive time periods that cause signal-to-noise ratio fluctuations and communication failures are identified, thus obtaining the dynamic information set of the communication channel.

3. The method according to claim 2, characterized in that, The process of constructing the carrier signal frequency domain information set includes: Based on the biogas generator harmonic information set, the energy values ​​of harmonic current at different time points within the biogas power generation efficiency change cycle are analyzed synchronously at each frequency point in the broadband and the low-power wireless frequency band, respectively, to obtain the broadband frequency band energy fluctuation sequence and the low-power wireless frequency band energy fluctuation sequence. The energy values ​​at corresponding time points in the broadband frequency band energy fluctuation sequence and the low-power wireless frequency band energy fluctuation sequence are compared to identify the frequency points and corresponding time periods where the energy values ​​exceed the preset interference threshold. All the identified frequency points and corresponding time periods are integrated according to the communication frequency band and time order to obtain the carrier signal frequency domain information set; The carrier signal frequency domain information set is used to characterize the time-frequency distribution characteristics of harmonic interference to the communication frequency band.

4. The method according to claim 3, characterized in that, The process of constructing the time-domain disturbance information set of the communication frame includes: Based on the interference information set of the fermentation tank equipment, the starting time, duration and intensity changes of pulse interference and oscillation interference generated during the equipment start-up and shutdown phases and operation process are analyzed to obtain the interference time domain feature set. Based on the interference time-domain feature set, the coverage information caused by the sudden moment of the pulse interference and the duration of the oscillation interference on the communication frame transmission window of the communication channel is analyzed to obtain the communication frame coverage disturbance information. Based on the communication frame coverage disturbance information, the impact damage of the pulse interference on the key fields of the communication frame during the affected period and the continuous degradation of the overall signal of the communication frame by the oscillation interference are analyzed to obtain the communication frame time-domain disturbance information set.

5. The method according to claim 4, characterized in that, The process of constructing the association includes: Based on the frequency point and the corresponding time period, combined with the start time and the duration, the overlap information of the frequency domain interference time period of the harmonic background noise and the time period of the time domain impact of the equipment operation on the time axis is analyzed to obtain the spatiotemporal overlapping interference time period set. Based on the spatiotemporal overlapping interference time period set, according to the energy value of the corresponding frequency point in the carrier signal frequency domain information set and the interference intensity of the corresponding time period in the communication frame time domain interference information set, the coordinated change trend between the harmonic background noise energy fluctuation and the equipment impact intensity change in the overlapping time period is analyzed to obtain the interference intensity coupling feature set. Based on the interference intensity coupling feature set, the interaction between the aggravated time-domain impact of harmonic background noise on communication frame damage and the abnormal rise of harmonic energy during the time-domain impact is identified, and the correlation is obtained. The interaction is manifested as a bidirectional positive feedback between the harmonic background noise that exacerbates communication frame damage and the abnormal rise of harmonic energy during the time-domain impact. The correlation is used to characterize the dynamic coupling information of continuous harmonic interference and sudden equipment impact in the electromagnetic environment of a biogas power plant, which together cause communication channel degradation during the production stage.

6. The method according to claim 5, characterized in that, Based on the dynamic information set of the communication channel, the impact of biogas fermentation on power generation efficiency is analyzed, leading to the dynamic evolution information of increased communication channel link bit error rate and carrier communication channel switching failure, resulting in a communication channel reliability map, including: Based on the sensitive frequency band and the sensitive time period, the variation information of power generation efficiency under different gas production and load conditions is analyzed to obtain the mapping relationship between fermentation process and power generation efficiency. Based on the aforementioned fermentation process-power generation efficiency mapping relationship, and combined with the aforementioned correlation, the changing trend of signal-to-noise ratio of broadband and low-power wireless carrier communication channels under the change in power generation efficiency is analyzed, and the stage characteristics of channel performance evolution with power generation efficiency are obtained. Based on the stage characteristics of the evolution of channel performance with power generation efficiency, the increase magnitude and rate of increase of data transmission bit error rate in each period of the stage characteristics are analyzed to obtain dynamic evolution information of link bit error rate. Based on the dynamic evolution information of the link bit error rate, the masking effect of the cross-change of broadband and low-power wireless channel performance on the channel switching decision conditions is analyzed within a preset floating time interval centered on the switching point of each period of the stage characteristics, so as to obtain the dynamic information of communication channel switching. By combining the dynamic evolution information of the link bit error rate and the dynamic information of the communication channel switching, and using the power generation efficiency change cycle as a time-series framework, the mapping relationship and the stage characteristics are integrated to draw a communication channel reliability map that reflects the dynamic changes in communication channel reliability.

7. The method according to claim 6, characterized in that, The process of constructing the fermentation process-power generation efficiency mapping relationship includes: Based on the sensitive frequency band and the sensitive time period, the fluctuation information of the biogas generator output power under the communication interference environment during the sensitive time period is analyzed to obtain the baseline of the interfered power generation. Based on the baseline of the disturbed power generation, and according to the collected gas production data, the impact of the increase in gas production on the increase in power generation, as well as the boundary effect of the increase in generator load on approaching the power limit and reducing efficiency, are analyzed to obtain dynamic coupling information of power and efficiency. Based on the power-efficiency dynamic coupling information, the trajectory of power generation efficiency increasing with the increase of gas production data, but whose lower limit is limited by the change of load conditions and power generation baseline, is depicted, thus obtaining the fermentation process-power generation efficiency mapping relationship.

8. The method according to claim 7, characterized in that, The process of constructing the stage features includes: Based on the aforementioned fermentation process-power generation efficiency mapping relationship, the overall change of the electromagnetic environment constituted by the biogas generator harmonic information set and the fermentation tank equipment interference information set driven by the change in power generation efficiency is analyzed, and the evolution characteristics of the interference environment are obtained. Based on the aforementioned interference environment evolution characteristics and the aforementioned correlation, the effects of the spectral distribution changes of the harmonic background noise and the intensity changes of the time-domain impact on the signal-to-noise ratio fluctuations of the broadband carrier communication channel and the low-power wireless carrier communication channel are analyzed within different ranges of the power generation efficiency variation amplitude, respectively, to obtain the dual-mode channel performance response characteristics. Based on the dual-mode channel performance response characteristics, the power generation efficiency variation amplitude is used as a reference axis to correlate and map the complete law of the signal-to-noise ratio fluctuation tendency of broadband and low-power wireless carrier communication channels from the beginning, development to transformation, and thus obtain the stage characteristics.

9. The method according to claim 8, characterized in that, Based on the communication channel reliability map, the system dynamically generates communication assurance plans for different production stages and outputs channel stability assessment logs, including: Based on the stage characteristics mapped in the communication channel reliability map, the channel performance risk level corresponding to different power generation efficiency intervals in the fermentation process-power generation efficiency mapping relationship is analyzed to obtain production stage risk classification information. Based on the risk classification information of the production stage, and according to the preset carrier communication mode priority list and channel parameter configuration library, the optimal mode switching timing and parameter adjustment strategy to ensure communication continuity under each level of risk production stage are analyzed, and a set of communication guarantee plans is obtained. Based on the execution process of the communication assurance plan set, the improvement effect of the dynamic evolution information of the link bit error rate and the dynamic information of the communication channel switching after the plan is triggered during the power generation efficiency change cycle is analyzed, and the channel stability assessment log is generated by combining the gas production data and the power generation efficiency change range.

10. A channel stability evaluation system for dual-mode power line communication signals, characterized in that, The method applied to any one of claims 1-9 includes: The fluctuation analysis module is used to acquire the electromagnetic disturbance information set of the biogas power plant. Based on the electromagnetic disturbance information set, the signal-to-noise ratio fluctuation of broadband and low-power wireless carrier communication signals under the action of grid-connected harmonics of biogas generators is analyzed to obtain the dynamic information set of communication channels. The dynamic evolution module is used to analyze the impact of biogas fermentation on power generation efficiency based on the dynamic information set of the communication channel, thereby leading to the dynamic evolution information of the increase in the bit error rate of the communication channel link and the failure of carrier communication channel switching, and to obtain the communication channel reliability map. The communication assessment module is used to dynamically generate communication assurance plans for different production stages based on the communication channel reliability map, and output channel stability assessment logs.

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