Method and system for monitoring synchronization of long distance transmission of power communication

Abstract

The present application relates to the technical field of power communication, and particularly relates to a power communication long-distance transmission synchronization monitoring method and system, comprising: a plurality of monitoring units are arranged along the optical communication system power optical cable; a software defined network controller acquires real-time synchronization parameters of each monitoring unit, determines a key monitoring area according to a phase deviation slope, and issues an interference protection strategy containing a high-frequency sampling frequency to the monitoring units in the area; the monitoring unit acquires an analog-digital conversion sampling signal collected by an electric field induction coil, determines an external alternating current phase and an alternating electromagnetic field zero point period through a preset algorithm, and sends a compact pulse message containing only a time stamp to a target monitoring unit based on the zero point period through a medium access control layer in a strong electromagnetic interference state, so as to perform phase calibration sampling and time delay compensation. The method globally identifies a key monitoring area and issues a high-frequency sampling strategy, realizes on-demand scheduling of network resources, and greatly improves the survival rate of data packets under strong electromagnetic transient impact.

Description

Technical Field

[0001] This specification relates to the field of power communication technology, and in particular to a method and system for synchronous monitoring of long-distance power communication transmission. Background Technology

[0002] Power communication systems are a crucial supporting infrastructure for smart grids, carrying critical services such as relay protection, dispatch automation, and synchronization measurements by miniature phasor measurement units (PMUs). With the expansion of power grids and the increase in transmission distance, power communication systems widely adopt fiber optic communication technology, using specialized power optical cables such as fiber-optic composite overhead ground wires (OPGW) and all-dielectric self-supporting optical cables (ADSS) to achieve cross-regional, long-distance communication transmission. In these long-distance transmission scenarios, high-precision time synchronization is the core foundation for ensuring the normal operation of power services. Currently, power optical communication systems typically employ synchronization technologies such as the IEEE 1588 Precise Time Protocol (PTP) or Synchronous Digital Hierarchy (SDH), achieving clock synchronization between communication nodes through the periodic exchange of time synchronization messages. These synchronization methods can meet the synchronization accuracy requirements of power systems under normal electromagnetic environments. However, power optical cables are usually erected on the same towers or in composite laying with high-voltage transmission lines, and are exposed to complex, strong electromagnetic environments for extended periods. When transient events occur in the power system, such as lightning strikes, short-circuit faults, or circuit breaker trips, transient strong electromagnetic pulses are generated, which can cause serious interference to optical communication equipment and synchronization systems along the line.

[0003] Therefore, this specification provides a method and system for synchronous monitoring of long-distance power communication transmission, which can achieve low-cost, highly reliable, and predictable nanosecond-level time synchronization monitoring in environments with strong electromagnetic interference, especially in scenarios involving long-distance transmission along power optical cables. Summary of the Invention

[0004] One embodiment of this specification provides a method for synchronous monitoring of long-distance power communication transmission. The method is applied to a long-distance power communication transmission synchronous monitoring system, which includes a software-defined network controller (SDN) and multiple monitoring units deployed along the power optical cable of an optical communication system. The method includes: acquiring real-time synchronization parameters of the optical communication system from the multiple monitoring units; determining one or more key monitoring areas based on the real-time synchronization parameters; and issuing interference protection strategies to one or more monitoring units within the one or more key monitoring areas. The interference protection strategies include a high-frequency sampling frequency, and the real-time synchronization parameters include the phase deviation slope of each monitoring unit; acquiring analog-to-digital conversion (ADC) sampling signals collected by an electric field induction coil; inputting the ADC sampling signals into a preset algorithm for processing to determine the external AC phase; determining the zero-point time period corresponding to the AC electromagnetic field based on the external AC phase; and when a strong electromagnetic interference state is determined, sending a compact pulse message containing only a timestamp to the target monitoring unit based on the zero-point time period via a medium access control layer, for phase calibration sampling and delay compensation based on the high-frequency sampling frequency.

[0005] One embodiment of this specification provides a long-distance synchronous monitoring system for power communication transmission. The system includes a software-defined network (SDN) controller and multiple monitoring units deployed along the power optical cable of the optical communication system. The SDN controller is configured to: acquire real-time synchronization parameters of the optical communication system from the multiple monitoring units; determine one or more key monitoring areas based on the real-time synchronization parameters; and issue interference protection strategies to one or more monitoring units within the one or more key monitoring areas. The interference protection strategies include a high-frequency sampling frequency, and the real-time synchronization parameters include the phase deviation slope of each monitoring unit. Each monitoring unit is configured to: acquire analog-to-digital conversion (ADC) sampling signals collected by an electric field induction coil; input the ADC sampling signals into a preset algorithm for processing to determine the external AC phase; determine the zero-point time period corresponding to the AC electromagnetic field based on the external AC phase; and when a strong electromagnetic interference state is determined, based on the zero-point time period, trigger a compact pulse message containing only a timestamp to the target monitoring unit via a medium access control layer, for phase calibration sampling and delay compensation based on the high-frequency sampling frequency.

[0006] One embodiment of this specification provides a power communication long-distance transmission synchronization monitoring device, including a processor, which is used to execute the power communication long-distance transmission synchronization monitoring method.

[0007] One embodiment of this specification provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes the long-distance power communication transmission synchronization monitoring method.

[0008] The beneficial effects of the embodiments in this specification include, but are not limited to: by introducing a software-defined network controller to globally identify key monitoring areas and issue high-frequency sampling strategies, on-demand scheduling of network resources is achieved. Simultaneously, by directly sensing the phase of the power frequency AC current through the monitoring unit, the physical gaps during the "zero-point period" when electromagnetic radiation is minimal during the alternation of positive and negative half-cycles of a strong electric field are accurately captured. Under strong interference, the traditional cumbersome software protocol stack synchronization mechanism is abandoned, and high-frequency sampling and interaction are performed by directly triggering extremely lightweight, compact pulse messages using the media access control layer. This greatly improves the survival rate of data packets under strong electromagnetic transient impacts and avoids the problem of broken links and gaps in clock synchronization protocols. Attached Figure Description

[0009] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0010] Figure 1 This is an exemplary structural diagram of a long-distance synchronous monitoring system for power communication transmission, as shown in some embodiments of this specification. Figure 2 This is an exemplary flowchart of a method for synchronous monitoring of long-distance power communication transmission according to some embodiments of this specification; Figure 3 This is an exemplary schematic diagram illustrating the determination of the phase deviation slope according to some embodiments of this specification; Figure 4 This is an exemplary schematic diagram illustrating sampling performed at a high-frequency sampling frequency according to some embodiments of this specification. Detailed Implementation

[0011] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0012] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0013] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0014] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0015] Figure 1 This is an exemplary structural diagram of a long-distance synchronous monitoring system for power communication transmission, illustrated in some embodiments of this specification. Long-distance transmission refers to the transmission of optical communication signals over a relatively long physical span within a power optical cable. For example, when the length of the optical cable between two communication devices is greater than or equal to 10 kilometers, it can be considered a long-distance transmission scenario. Figure 1 As shown, the long-distance power communication transmission synchronous monitoring system 100 includes a software-defined network controller 110 and a monitoring unit 120.

[0016] The software-defined network controller 110 refers to the logical control center that centrally acquires, uniformly analyzes, and issues synchronization control policies for the status of network nodes.

[0017] Monitoring unit 120 refers to a hardware module or subsystem with signal acquisition, protocol processing, and synchronization calibration functions. The long-distance power communication transmission synchronization monitoring system 100 includes one or more monitoring units, which can be distributed along the power optical cable of the optical communication system. Here, optical communication system refers to a communication system that uses optical signals as information carriers and transmits them through optical fiber media.

[0018] For example, a transmission network built on power optical cables can be considered an optical communication system. Power optical cables refer to optical fiber cables installed in power system-related facilities to carry optical communication services, such as OPGW, ADSS, or other special optical cables erected on the same poles as transmission lines. In some embodiments, monitoring units can be laid along transmission lines, poles, or substations.

[0019] In some embodiments, the software-defined network controller 110 and the monitoring unit 120 can establish a TCP connection via an Ethernet / IP network or a logical connection via a power data communication network.

[0020] In some embodiments, the software-defined network controller 110 can obtain real-time synchronization parameters of the optical communication system from multiple monitoring units 120, determine one or more key monitoring areas based on the real-time synchronization parameters, and issue interference protection strategies to one or more monitoring units within the one or more key monitoring areas.

[0021] In some embodiments, the monitoring unit 120 can acquire the analog-to-digital conversion sampling signal collected by the electric field induction coil; input the analog-to-digital conversion sampling signal into a preset algorithm for processing to determine the external AC phase; determine the zero-point time period corresponding to the AC electromagnetic field based on the external AC phase; when it is determined that it is in a strong electromagnetic interference state, based on the zero-point time period, trigger the sending of a compact pulse message containing only a timestamp to the target monitoring unit through the medium access control layer, for phase calibration sampling and time delay compensation based on the high-frequency sampling frequency.

[0022] For a detailed explanation of the above content, please refer to [link / reference]. Figure 2 content.

[0023] Through the above structure, this system realizes a complete synchronous monitoring closed loop from global monitoring to local collaboration, and from passive response to active protection, which can maintain high-precision time synchronization of the power optical communication system in a strong electromagnetic interference environment.

[0024] Figure 2 This is an exemplary flowchart of synchronous monitoring for long-distance power communication transmission, as shown in some embodiments of this specification. Figure 2 As shown, process 200 includes steps 210-250. In some embodiments, step 210 may be performed by a software-defined network controller (e.g., software-defined network controller 110), and steps 220-250 may be performed by a monitoring unit (e.g., monitoring unit 120).

[0025] Step 210: Obtain real-time synchronization parameters of the optical communication system from multiple monitoring units, determine one or more key monitoring areas based on the real-time synchronization parameters, and issue interference protection strategies to one or more monitoring units within the one or more key monitoring areas.

[0026] Real-time synchronization parameters refer to a set of quantitative indicators reflecting the consistency of time, phase, and frequency among communication nodes. In some embodiments, real-time synchronization parameters may include the phase deviation slope of each monitoring unit. The phase deviation slope refers to the rate of change of the phase error of the monitoring unit's local clock per unit time. The local clock refers to the clock generated by the device's internal clock source and used for maintaining the device's time reference.

[0027] In some embodiments, the monitoring unit can acquire the polarization angle abrupt change and Verdet constant of the received optical signal; input the polarization angle abrupt change and Verdet constant into an electromagnetic calculation model for reverse calculation to determine the transient electromagnetic intensity acting on the monitoring unit; and substitute the transient electromagnetic intensity into the drift compensation polynomial for calculation to determine the phase deviation slope. For more details, please refer to... Figure 3 And its related descriptions.

[0028] In some embodiments, the real-time synchronization parameters may further include the clock offset of each monitoring unit, the round-trip time jitter of the time synchronization packet, and the frequency accuracy deviation.

[0029] Clock offset refers to the absolute time difference between the monitoring unit's local clock and the global reference clock. Round-trip time jitter refers to the variance or range of the physical time required for the monitoring unit to send a time synchronization packet and receive a reply packet from the other end over multiple interactions. Frequency accuracy deviation refers to the relative deviation rate between the actual output frequency of the monitoring unit's local crystal oscillator and the standard nominal frequency.

[0030] In some embodiments, the software-defined network controller can periodically acquire real-time synchronization parameters from multiple monitoring units. See also the description of the optical communication system. Figure 1 Related content.

[0031] Key monitoring areas refer to communication link segments where link quality has deteriorated or where electromagnetic shocks are imminent. For example, fiber optic cable segments with abnormal link quality or link segments near electromagnetic shock sources can be designated as key monitoring areas.

[0032] In some embodiments, the software-defined network controller normalizes the data in the real-time synchronization parameters, assigns preset weight coefficients to the indicators of each normalized data point, and then performs a linear weighted summation to obtain the link degradation index of the corresponding link segment. The preset weight coefficients can be manually configured based on experience. For example, round-trip time jitter can directly reflect the degree of interference to the communication link and can be set with the highest weight.

[0033] If the link degradation index exceeds a preset degradation threshold, the link segment containing the monitoring unit is designated as a key monitoring area. The software-defined network controller then issues interference protection strategies to the monitoring units within this key monitoring area. The degradation threshold can be determined based on empirical presets or experimental calibration.

[0034] In some embodiments, the software-defined network controller can also jointly determine the link degradation index based on the time and spatial dimensions of real-time synchronization parameter sequences at multiple consecutive time points. For example, the software-defined network controller can calculate the changing trend of the link degradation index within multiple consecutive time windows, the degradation consistency of corresponding link segments of adjacent monitoring units, and the duration of anomalies; when the link degradation index of multiple adjacent link segments continuously exceeds a preset degradation judgment threshold within the same time window, the software-defined network controller identifies the corresponding link segment as a key monitoring area.

[0035] Interference protection strategies refer to a set of rules that constrain or configure the sampling, transmission, and synchronization compensation behavior of monitoring units in environments with strong interference. Interference protection strategies may include high-frequency sampling frequencies or sampling and compensation flow tables.

[0036] High-frequency sampling refers to a higher signal acquisition or processing frequency compared to the system's normal operating state under a specific intervention mode. For example, a high-frequency sampling frequency can be between 250Hz and 500Hz. A specific intervention mode refers to a defensive operating state that the optical communication system switches to when it detects or predicts that it will face a strong electromagnetic interference impact.

[0037] In some embodiments, under a specific intervention mode, the monitoring unit suspends the conventional synchronization mechanism and instead performs sampling and message exchange only at a higher frequency during the zero-crossing period of the power frequency AC electromagnetic field. For example, when a link segment is identified as a key monitoring area, the monitoring units within that area enter a specific intervention mode, sending compact pulse messages to adjacent monitoring units only at the zero-crossing moment of each power frequency cycle for high-frequency calibration.

[0038] Here, a compact pulse message refers to a pulsed data message with concise fields and a light payload. In this specification, a compact pulse message is preferably a message containing only a timestamp. For example, a data packet carrying only a hardware timestamp field can be considered a compact pulse message. For more information on compact pulse messages and timestamps, see the relevant content in step 250. For specific explanations on sampling and compensation flow tables, see [link to relevant documentation]. Figure 4 Related content.

[0039] In some embodiments, the software-defined network controller can generate interference protection policy instructions that include high-frequency sampling frequencies. The interference protection policy instructions may include a list of key monitoring areas and interference protection policies that include high-frequency sampling frequencies for each key monitoring area, and then issue the corresponding interference protection policies to one or more monitoring units within the key monitoring areas.

[0040] The software-defined network controller obtains the following input parameters: zero-point time window width (ΔT) zero ), phase deviation slope (K) slope ) and target synchronization accuracy (σ target The zero-point window width is calculated by the monitoring unit based on the external AC phase, representing the duration during which the electromagnetic radiation intensity is less than a preset threshold when the positive and negative half-cycles of the power frequency AC electromagnetic field alternate. The preset threshold can be obtained empirically. For example, if the electromagnetic radiation intensity is less than the preset threshold for 2ms before and after each zero-crossing of the power frequency cycle, the total zero-point window width is 4ms. The phase deviation slope is calculated by the monitoring unit based on the transient electromagnetic intensity using a drift compensation polynomial, representing the drift rate of the local clock crystal oscillator after electromagnetic interference. The faster the drift rate, the higher the required sampling frequency. For the calculation method of the phase deviation slope, see [link to relevant documentation]. Figure 3 Related notes: The target synchronization accuracy is the system's preset nanosecond-level time synchronization accuracy threshold.

[0041] The software-defined network controller inputs the above parameters into its internal high-frequency sampling frequency calculation module and performs the following determination steps: First, based on a variant of Shannon's sampling theorem, it calculates the minimum sampling step size, ensuring that the sampling interval is much smaller than the time required for the crystal oscillator to experience a minimum precision unit drift, thereby suppressing transient drift; Second, it calculates the number of compact pulse packets that can be accommodated within a single zero-point time window, using the formula N=ΔT. zero / (T packet +T guard ), where T packet The message transmission time can be obtained through factory calibration or actual measurement, T. guard The hardware protection interval can be determined based on empirical presets; finally, an adaptive frequency adjustment function F is established. h =f(K slope ,ΔT zero As the phase deviation slope increases, the software-defined network controller linearly increases the high-frequency sampling frequency F. h This continues until the hardware processing limit of the monitoring unit is reached or the zero-hour time window is filled.

[0042] For example, if the system’s normal sampling frequency is 1 time / second, the high-frequency sampling frequency can be set to continuously send 3 to 5 probe pulses at the zero-crossing instant in each power frequency cycle (20ms), with the equivalent instantaneous frequency reaching hundreds of hertz or even kilohertz levels.

[0043] The software-defined network controller ultimately outputs a list of key monitoring areas and interference protection strategies for each key monitoring area, forming interference protection strategy instructions to control the monitoring units to begin sending compact pulse messages to the target monitoring units at a high-frequency sampling rate. For more information on the zero-point time period, compact pulse messages, and target monitoring units, please see the following content.

[0044] In some embodiments, the software-defined network controller may use different normalization rules, weighting coefficients or degradation judgment thresholds to determine key monitoring areas for different line types, link lengths or historical interference levels. However, each implementation still uses the link degradation index calculated based on multiple real-time synchronization parameters as the basis for area division.

[0045] Step 220: Acquire the analog-to-digital conversion sampling signal collected by the electric field induction coil.

[0046] An electric field induction coil is a sensing component used to detect external alternating electromagnetic fields and output corresponding electrical signals. For example, it can be placed near a power line to detect the alternating electromagnetic field around the power line. The analog-to-digital conversion sampling signal refers to the digital electrical signal output in discrete form by the electric field induction coil after detecting the transient electromagnetic field around the power line, via an analog-to-digital converter.

[0047] In some embodiments, the monitoring unit uses an electric field induction coil to sense an external AC electromagnetic field, which is then isolated at the front end, voltage conditioned, amplified, and filtered against anti-aliasing to complete the analog-to-digital conversion and obtain an analog-to-digital conversion sampling signal.

[0048] Step 230: Input the analog-to-digital conversion sampling signal into a preset algorithm for processing to determine the phase of the external AC power.

[0049] A preset algorithm refers to a digital signal processing algorithm that uses a closed-loop control mechanism to automatically track and synchronize the locally generated signal with the input signal in terms of frequency and phase. For example, a preset algorithm can be a phase-locked loop (PLL) algorithm.

[0050] External AC phase refers to the instantaneous phase angle of the transient AC electromagnetic field at power line frequency that causes the current strong electromagnetic interference. For example, the power line AC electromagnetic field corresponds to different external AC phases during the positive half-cycle, negative half-cycle, and zero-crossing position.

[0051] In some embodiments, the monitoring unit inputs the analog-to-digital conversion sampled signal into a preset algorithm for processing, including: first performing bandpass filtering on the analog-to-digital conversion sampled signal to extract the fundamental frequency component, and then tracking the fundamental phase through a digital phase-locked loop. The output of the digital phase-locked loop is the external AC phase.

[0052] Taking the PLL algorithm as an example, the monitoring unit inputs the analog-to-digital conversion sampling signal into a digital phase detector (PD) to calculate the phase difference between the analog-to-digital conversion sampling signal and the feedback signal of the locally numerically controlled oscillator (NCO). The phase difference signal is then input into a digital loop filter LF to filter out high-frequency noise components and extract the DC control level E. ctrl The frequency and phase of the local numerically controlled oscillator (NCO) are then adjusted using the DC control level until the feedback signal locks the fundamental frequency of the analog-to-digital conversion sampling signal. In the locked state, the monitoring unit can directly extract the current instantaneous phase angle from the internal status register of the NCO as the external AC phase. Specifically, the monitoring unit can use ΔFCW=E ctrl ×K nco Calculate the frequency fine-tuning word and apply it according to POW=E. ctrl ×K p Calculate the phase offset word, where K nco K represents the frequency mapping coefficients. p The phase mapping coefficients can be obtained through factory calibration; let the fundamental frequency control word corresponding to the nominal output frequency of the NCO (e.g., the preset 50Hz power frequency) be FCW. base Then the actual frequency control word can be updated to FCW. actual =FCW base +ΔFCW. When the external power frequency increases, E ctrl When ΔFCW is positive, the accumulation step size of the NCO phase accumulator increases, and the output frequency increases accordingly; when the external power frequency decreases, E ctrl When the value is negative, ΔFCW is negative, the accumulation step size decreases, and the output frequency slows down accordingly. Based on this, a phase offset word is used to gradually align the local signal phase curve with the external AC phase.

[0053] In some embodiments, the long-distance synchronous monitoring system for power communication inputs the analog-to-digital conversion sampled signal into a preset algorithm for processing, and may further include: performing discrete Fourier transform or quadrature demodulation on the analog-to-digital conversion sampled signal to obtain the fundamental quadrature component and the in-phase component, and then determining the external AC phase based on the arctangent operation.

[0054] In some embodiments, the external AC phase can also be determined in other ways. For example, a long-distance power communication transmission synchronization monitoring system fits the analog-to-digital conversion sampled signal into a sinusoidal model and obtains the model phase parameters based on the least squares method; however, it is not limited to this.

[0055] Step 240: Determine the zero-point time period corresponding to the AC electromagnetic field based on the external AC phase.

[0056] The zero-point period refers to the time interval during which the alternating electromagnetic field is near the alternation of positive and negative half-cycles and the electromagnetic radiation intensity is below a preset threshold. For example, the short window corresponding to when the phase of the alternating current is close to the zero-crossing position can be regarded as the zero-point period, i.e., the zero-point period window.

[0057] In some embodiments, the monitoring unit can read the external AC phase in real time. When it detects that the external AC phase crosses the zero-crossing interval corresponding to an integer multiple of 0 degrees or 180 degrees, it maps the zero-crossing interval to an alternating node where the electric field radiation intensity crosses zero. It also intercepts the time period before and after the zero-crossing interval where the absolute intensity of electromagnetic radiation is less than a preset intensity threshold, as the zero-point time period.

[0058] The preset intensity threshold can be determined empirically, where the absolute intensity B of electromagnetic radiation is... abs According to B abs =V adc Calculate V using / (G·N·A·ω). adc The amplitude corresponding to the analog-to-digital conversion sampling signal can be obtained through actual measurement. N is the number of coil turns, A is the effective cross-sectional area, and G is the hardware gain coefficient. N, A, and G can be obtained through factory calibration. ω is the external AC angular frequency, which can be obtained based on the external AC phase.

[0059] In some embodiments, the determination of zero-point time periods based on the external AC phase in the long-distance power communication transmission synchronization monitoring system may further include: first estimating the current power frequency cycle based on phase changes, then predicting one or more subsequent zero-crossing moments, and generating corresponding lists of zero-point time periods. Based on this, the long-distance power communication transmission synchronization monitoring system can schedule subsequent media access control layer transmission timings in advance.

[0060] In some embodiments, the zero-point time period can also be determined in other ways. For example, in a long-distance power communication transmission synchronization monitoring system, the sign changes of adjacent sampling points are detected and the zero-crossing time is interpolated, and the width of the zero-point time period can be adjusted according to the on-site interference intensity; however, it is not limited to this.

[0061] Step 250: When it is determined that the system is in a state of strong electromagnetic interference, based on the zero-point period, a compact pulse message containing only a timestamp is sent to the target monitoring unit through the medium access control layer for phase calibration sampling and time delay compensation based on the high-frequency sampling frequency.

[0062] A strong electromagnetic interference (EMI) state refers to a condition where the instantaneous amplitude or energy density of external electromagnetic radiation exceeds a preset interference threshold. The preset interference threshold can be determined empirically. For example, a high-intensity electromagnetic shock generated during a lightning strike or short-circuit transient can correspond to an EMI state.

[0063] The Media Access Control (MAC) layer is a sublayer within the data link layer that directly controls the transmission media access control, and is used to control the transmission and access of data frames. For example, the MAC layer can directly trigger the transmission of compact pulse messages. A timestamp is time data used to identify an event, message, or sampling time. For example, both the transmission and reception timestamps of a message can be used as timestamps.

[0064] A target monitoring unit refers to a network node located in the same key monitoring area and adjacent to the monitoring unit sending the message, used for synchronization calibration with that monitoring unit. Phase calibration sampling refers to the sampling operation performed to correct the phase relationship between different monitoring units or between the local clock and a reference clock. For example, phase calibration sampling can be performed based on the timing information of received compact pulse messages. Delay compensation refers to the process of correcting time delay deviations generated during signal transmission, processing, or interaction. For example, it can compensate for synchronization errors caused by link propagation delay or node processing delay.

[0065] In some embodiments, the monitoring unit determines that it is in a strong electromagnetic interference state by: comparing the amplitude of the analog-to-digital conversion sampling signal with a preset interference amplitude threshold; if the amplitude exceeds the preset interference amplitude threshold, then setting the interference state flag to determine that it has entered a strong electromagnetic interference state.

[0066] The preset interference amplitude threshold can be preset based on experience. When the determination result is a strong electromagnetic interference state, the current monitoring unit acts as the transmitting monitoring unit. Before the arrival of the most recent zero point period, it sends a compact pulse message containing only a timestamp to the target monitoring unit located in the same key monitoring area and adjacent to it on the optical cable topology through the medium access control layer. The target monitoring unit can be the previous monitoring unit or the next monitoring unit.

[0067] The target monitoring unit records the local arrival timestamp of the compact pulse message at a high-frequency sampling frequency and compares it with the transmission timestamp carried by the compact pulse message to obtain the estimated one-way transmission delay and the current instantaneous phase deviation. Based on this, the target monitoring unit generates the delay compensation amount and the phase calibration amount, and writes the delay compensation amount into the local clock calibration register or the link delay compensation parameter table to complete the phase calibration sampling and delay compensation.

[0068] In some embodiments, under strong electromagnetic interference conditions, the monitoring unit shields the software timer synchronization trigger path of the conventional Transmission Control Protocol / Internet Protocol (TCP / IP) protocol stack. When the local system time enters the determined zero-point period, the hardware transmitting circuit pushes the predefined compact pulse message frame into the transmission queue through Direct Memory Access (DMA) according to the issued high-frequency sampling frequency. The payload of the compact pulse message only includes the hardware timestamp field. The necessary frame delimitation and address fields required for transmission are retained during the encapsulation of the media access control layer, thereby directly transmitting the compact pulse message through the physical fiber optic link.

[0069] In some embodiments, the determination of a strong electromagnetic interference state by the long-distance power communication transmission synchronization monitoring system may further include: making a judgment based on at least one of the synchronization message bit error rate, timestamp jitter, and clock lockout count. When the judgment result meets the strong electromagnetic interference condition, the long-distance power communication transmission synchronization monitoring system enables contention-free transmission time slots or temporary priority scheduling through the media access control layer, so that compact pulse messages are transmitted during the zero-point period. Since compact pulse messages only contain timestamps and have a short message length, the long-distance power communication transmission synchronization monitoring system can reduce the probability of messages being disturbed in a strong interference environment and enable the target monitoring unit to estimate the link transmission delay and processing delay more accurately based on the high-frequency sampling frequency.

[0070] In some embodiments, the transmission triggered by the media access control layer can also be implemented in other ways. For example, a long-distance power communication transmission synchronization monitoring system sets a protection interval and suspends the transmission of non-critical services during the zero-point period to ensure that compact pulse messages containing only timestamps are sent on time; but it is not limited to this.

[0071] In some embodiments, when the current monitoring unit sends a compact pulse message to a target monitoring unit within a key monitoring area based on a zero-point time period via the media access control layer, the current monitoring unit inputs the external AC phase into a preset filtering algorithm for processing to determine one or more predicted zero-point time periods in the future; obtains the historical one-way link transmission delay corresponding to the target monitoring unit; determines the transmission advance for the corresponding target monitoring unit based on the historical one-way link transmission delay; and sends a compact pulse message at the time point determined based on the transmission advance before one or more predicted zero-point time periods arrive, so that the compact pulse message arrives at the adjacent monitoring unit during the corresponding zero-point time period.

[0072] In some embodiments, the current monitoring unit processes the external AC phase input into a preset filtering algorithm to determine one or more predicted zero-point time periods for future periods.

[0073] A pre-defined filtering algorithm is a mathematical algorithm used for state estimation of nonlinear systems. It linearizes the nonlinear function using Taylor expansion and recursively derives the optimal state of the system from noisy observation data. For example, a pre-defined filtering algorithm could be a Kalman filter.

[0074] The predicted zero-point period refers to the time interval during which the predicted future power frequency AC electromagnetic field alternates between positive and negative values ​​and its intensity is less than a preset intensity threshold. For example, several short windows near zero crossings in the future can be used as the predicted zero-point period.

[0075] In some embodiments, the current monitoring unit can use the instantaneous phase output by the phase-locked loop as an observation value to construct a state vector X. k =[θ k ,ω k ,α k ] T Where k represents the k-th time in the discrete time series, θ k Let Rad, ω be the instantaneous phase at time k. k Let α be the angular velocity at time k, denoted by Rad / s, corresponding to the power frequency. k Let Rad / s² be the angular acceleration at time k, representing the frequency micro-drift rate caused by grid load fluctuations, and T denote the matrix transpose. The current monitoring unit performs prediction, observation, and update steps based on the Kalman filter algorithm to obtain optimal state estimates of phase, angular velocity, and angular acceleration.

[0076] In some embodiments, the prediction step, observation step, and update step based on the Kalman filter algorithm may include: using the optimal state estimate from the previous time step. The prior state estimate at the current time is extrapolated using the state transition matrix F. And calculate the prior covariance. Where Q is the process noise covariance, reflecting the uncertainty caused by power grid load fluctuations (such as sudden increases or decreases in load), and can be preset based on experience; the instantaneous phase of the phase-locked loop output is used as the observed value Z. k Based on the observation equation Z k =H·X k +V calculation Where H=[1,0,0]; V is the observation noise, which can be preset based on experience; during innovative calculations, the phase error is unwrapped to keep the error within the range of [-π,π]; then the Kalman gain is calculated based on the prediction covariance and the observation noise. Where R is the covariance matrix of the observation noise, determined by the ADC sampling accuracy and PLL lock-in fluctuations, and this Kalman gain is used to complete the state update. When the grid load changes abruptly, the observed phase Z... kAn offset occurs, Kalman gain K k The offset can be allocated to the corresponding state variables of angular velocity ω and angular acceleration α according to the noise ratio, so as to dynamically correct the estimate of grid frequency drift.

[0077] In some embodiments, after each round of Kalman filtering and obtaining the optimal state estimate, the current monitoring unit then... The solution determines the future zero-crossing time, where Δt represents the time interval from the current time to the future zero-crossing time, n is an integer and dimensionless, and nπ (e.g., 0°, 180°) corresponds to the phase angle at different zero-crossing times. The current monitoring unit can extrapolate N power frequency half-cycles backward (e.g., N=10, corresponding to predicting all zero points within the next 100ms), thereby generating one or more timestamp sequences for the predicted zero-point periods.

[0078] In some embodiments, the current monitoring unit acquires historical one-way link transmission latency.

[0079] Historical one-way link transmission delay refers to the time parameter required for a signal to travel along a one-way link from one monitoring unit to another, based on historical measurement results. For example, the average one-way propagation time of optical signals between adjacent monitoring units can be used as the historical one-way link transmission delay.

[0080] An adjacent monitoring unit refers to another monitoring unit that is directly adjacent to or directly connected to the current monitoring unit in the physical optical cable topology. For example, the next node located upstream or downstream of the current monitoring unit can be an adjacent monitoring unit.

[0081] Historical one-way link transmission delay includes the average flight time of the optical signal on the spatial physical link between the current monitoring unit and the adjacent monitoring unit.

[0082] A space physical link refers to a physical transmission path in actual space that connects two communication nodes and carries signals. For example, a fiber optic link between adjacent monitoring units can be considered a space physical link.

[0083] Average time of flight (ATF) refers to the average time a signal takes to propagate through a physical link. For example, the average time it takes for an optical signal to propagate between two adjacent monitoring units can be considered the ATF.

[0084] In some embodiments, the current monitoring unit obtains the historical one-way link transmission delay by: reading the sending timestamp and receiving timestamp of the historical interaction message, calculating the one-way propagation time within multiple historical periods; and taking the average of the multiple one-way propagation times to obtain the historical one-way link transmission delay.

[0085] In some embodiments, the process of the current monitoring unit obtaining historical one-way link transmission delay may further include: first obtaining the round-trip measurement results between the current monitoring unit and the adjacent monitoring unit, and then calculating the one-way propagation time by combining the uplink and downlink asymmetry compensation values ​​of the link; the current monitoring unit performs average or moving average processing on the multiple one-way propagation times obtained by the calculation to obtain the historical one-way link transmission delay.

[0086] In some embodiments, historical one-way link transmission delay can also be obtained in other ways. For example, it can be calculated by the current monitoring unit based on link length records, fiber refractive index, and interface fixed delay calibration values; but it is not limited to this.

[0087] In some embodiments, the current monitoring unit determines the transmission lead based on historical one-way link transmission delay.

[0088] Transmission lead time refers to the advance value reserved in advance to ensure that the message arrives at the target time. For example, a compact pulse message can be sent in advance according to the transmission lead time before the predicted midnight time period.

[0089] In some embodiments, the current monitoring unit determines the transmission lead time by: recording the historical one-way link transmission delay as Delay. avg The local media access control layer encapsulation delay and the inherent hard delay of photoelectric conversion are denoted as Tphy_delay, which can be obtained based on the factory calibration; the current monitoring unit follows T... advance =Delay avg +Tphy_delay calculates the lead time for transmission.

[0090] In some embodiments, the current monitoring unit's determination of the transmission lead may further include: calculating link jitter based on historical one-way link transmission delays and extracting the hardware protection interval value T. guard As a protection margin; the current monitoring unit follows T advance =Delay avg +Tphy_delay+T guard Calculate the transmission lead time to increase the probability that the message falls within the predicted midnight time period.

[0091] In some embodiments, the current monitoring unit sends a compact pulse message at a time point determined based on the transmission lead time before one or more predicted zero-point periods arrive, so that the compact pulse message arrives at the corresponding zero-point period when it reaches the adjacent monitoring unit.

[0092] In some embodiments, the current monitoring unit sending a compact pulse message includes: selecting the nearest target time period start point from the predicted zero-point time period timestamp sequence, subtracting the transmission advance from the start point to obtain the target transmission trigger time; the current monitoring unit starts a high-precision timer or hardware countdown timer, and sends an interrupt signal to the media access control layer when the local time reaches the target transmission trigger time; the current monitoring unit then injects and sends a compact pulse message to the physical port corresponding to the adjacent monitoring unit through the media access control layer.

[0093] By introducing a Kalman filter algorithm to predict the phase evolution of the nonlinear AC electromagnetic field and combining this with the inherent time delay of the physical link to set a transmission lead, this design cleverly solves the "peak shaving" problem caused by the flight time of optical signals in long-distance transmission. This ensures that compact pulse messages, after traversing tens or even hundreds of kilometers of optical fiber, fall precisely into the "physical zero-point time gap" of the target receiving environment, avoiding the risk of messages being directly erased by strong electromagnetic pulses at the receiving end and guaranteeing the delivery rate of synchronization information.

[0094] In some embodiments, after sending a compact pulse message, the monitoring unit pauses external network message transmission requests and performs internal high-frequency correction on the local clock before the next predicted zero-point period arrives. The internal high-frequency correction includes: acquiring the real-time ambient temperature of the local crystal oscillator; determining the weight allocation coefficients of the drift prediction model based on one or more predicted zero-point periods and the real-time ambient temperature; determining local compensation word parameters based on the historical deviation regression term and random noise compensation term using the drift prediction model; and performing local closed-loop frequency modulation at a frequency not lower than a preset frequency based on the local compensation word parameters.

[0095] In some embodiments, the monitoring unit suspends external network packet transmission requests based on the already transmitted compact pulse messages and the next predicted zero-point period, and performs internal high-frequency correction on the local clock.

[0096] An external network message transmission request refers to a request initiated by the local protocol stack or upper-layer application to send service messages to an external network. For example, a command to send ordinary service data can be considered an external network message transmission request.

[0097] Internal high-frequency correction refers to the process of intensive fine-tuning of the crystal oscillator control register solely based on locally calculated data during closed periods without external network interaction. For example, internal high-frequency correction can be performed between two adjacent prediction zero-point periods.

[0098] In some embodiments, the monitoring unit may select the time period that is temporally closest to but later than the current time from one or more predicted zero-point time periods as the next predicted zero-point time period, and designate the time interval from the current time to the start of that time period as a closed period. During this closed period, the monitoring unit suspends the interruption of message transmission from the media access control plane to the external network, retains only clock measurement and compensation control tasks, and initiates internal high-frequency correction for the local clock.

[0099] In some embodiments, the monitoring unit can also pause external network packet transmission requests on the protocol stack transmission queue side. Specifically, the monitoring unit marks service packet transmission requests with a waiting flag and temporarily stores them in a local buffer, resuming queue transmission only when the predicted midnight period arrives or after internal correction is completed.

[0100] In some embodiments, suspending external network packet transmission requests can also be achieved in other ways. For example, the monitoring unit freezes the outbound queue based on a transmission gating flag and restores it uniformly after the predicted midnight period; however, it is not limited to this.

[0101] In some embodiments, the monitoring unit acquires the real-time ambient temperature of the local crystal oscillator.

[0102] A local crystal oscillator refers to a crystal oscillator that serves as the local clock source for a device. For example, the crystal oscillator used to provide a reference frequency within a monitoring unit can be a local crystal oscillator.

[0103] Real-time ambient temperature refers to the ambient temperature value currently measured at a location associated with the local clock device. For example, the current temperature collected by a temperature sensor near the crystal oscillator can be used as the real-time ambient temperature.

[0104] In some embodiments, the monitoring unit acquires the current temperature value through a temperature sensor installed close to the local crystal oscillator, and uses this temperature value as the real-time ambient temperature input to the subsequent drift prediction process. This acquisition process can be implemented using existing temperature sampling circuits.

[0105] In some embodiments, the monitoring unit can also read the output value of the temperature detection unit built into the local crystal oscillator package, and obtain the real-time ambient temperature after analog-to-digital conversion or register reading.

[0106] In some embodiments, the monitoring unit determines the weighting coefficients of the drift prediction model based on one or more predicted zero-point periods and real-time ambient temperature.

[0107] A drift prediction model is a model used to predict the drift trend of a local clock based on historical deviation information and relevant disturbance factors. For example, a drift prediction model can be an Autoregressive Moving Average (ARMA) model.

[0108] Weighting coefficients are parameters used to adjust the proportion of different predictive factors or model components in the final result. For example, they can be used to adjust the influence ratio of temperature factors and historical bias factors in drift prediction.

[0109] In some embodiments, the monitoring unit uses the actual time interval between the current predicted zero-point period and the previous predicted zero-point period as a sparsity characterization parameter and determines whether the time interval exceeds a preset interval threshold. When the time interval exceeds the preset interval threshold, the monitoring unit determines the weight increment corresponding to the temperature mapping deviation value through a mapping table based on the absolute value of the temperature difference between the real-time ambient temperature and the local crystal oscillator calibration zero-drift temperature, and updates the weight allocation coefficients of the drift prediction model accordingly. When the time interval does not exceed the preset interval threshold, the monitoring unit maintains the default weight allocation coefficients. The preset interval threshold can be determined based on experience.

[0110] In some embodiments, the monitoring unit may also use a piecewise function to determine the weight allocation coefficients. Specifically, the monitoring unit first determines the interference level based on the predicted zero-point time interval, and then determines the temperature weight interval based on the temperature zone to which the real-time ambient temperature belongs, so that the weights of the temperature influence factor, the historical deviation regression term, and the random noise compensation term are adjusted in a predetermined manner.

[0111] In some embodiments, the weighting coefficients can also be determined in other ways. For example, the monitoring unit can perform a two-dimensional lookup table based on the predicted zero-point time interval and the absolute value of the temperature difference, and directly output the corresponding weight combination; but it is not limited to this.

[0112] In some embodiments, the monitoring unit determines the local compensation word parameters based on the historical deviation regression term and the random noise compensation term using a drift prediction model.

[0113] Historical deviation regression term refers to the regression component that characterizes the continuity of clock deviation based on historical clock deviation sequences. For example, an autoregressive term formed by multiple historical phase deviation samples can be considered a historical deviation regression term.

[0114] Random noise compensation term refers to the error correction component used to characterize and compensate for the historical impact of random disturbances. For example, the moving average compensation term formed by historical random error sequences can be classified as random noise compensation term.

[0115] Local compensation word parameters are digital control parameters used to write into the local oscillator control unit to achieve frequency fine-tuning. For example, digital code values ​​that can be written into the digitally controlled oscillator (DCO), direct digital synthesizer (DDS), or crystal oscillator control register can be local compensation word parameters.

[0116] In some embodiments, the monitoring unit acquires a phase deviation slope sequence of multiple consecutive cycles during a closed period before the predicted zero-point time, and inputs the phase deviation slope sequence and weight allocation coefficients into the drift prediction model. The drift prediction model calculates the historical deviation regression term reflecting inertial drift and the random noise compensation term reflecting short-term random jitter, and then performs weighted fusion with the temperature mapping deviation value to obtain the local compensation word parameters.

[0117] For example, it can be pressed C total =WAR·PAR+WMA·PMA+W Temp ·P Temp Generate local compensation word parameters, where C total For the final generated local compensation word parameters, PAR represents the historical bias regression term, WAR is the weighting coefficient assigned to the historical bias regression term, PMA represents the random noise compensation term, WMA is the weighting coefficient assigned to the random noise compensation term, and P... Temp W represents the temperature mapping deviation value. Temp These are the weighting coefficients assigned to the temperature mapping deviation values.

[0118] In some embodiments, after obtaining the weighted fusion result, the monitoring unit can also perform quantization, limiting, and code value mapping on the result to generate local compensation word parameters adapted to the crystal oscillator digital-to-analog converter controller, DCO, or DDS register format. This method is applicable to different types of local oscillator control interfaces.

[0119] In some embodiments, the local compensation word parameters can also be determined in other ways. For example, the monitoring unit obtains the autoregressive predicted value and the noise mean correction value based on the deviation sequence of the most recent multiple periods, and then generates a digital control code through table lookup quantization; but it is not limited to this.

[0120] In some embodiments, the monitoring unit performs local closed-loop frequency modulation at a frequency not lower than a preset frequency based on local compensation word parameters.

[0121] The preset frequency refers to the minimum refresh rate limit pre-set for the local closed-loop frequency modulation process. The preset frequency can be set according to the local crystal oscillator type, the time interval between predicted zero-point periods, the target synchronization accuracy, and the temperature drift range. For example, when the predicted zero-point period interval increases or the target synchronization accuracy improves, the refresh frequency of the local compensation word parameters can be increased accordingly; when using a voltage-controlled temperature-compensated crystal oscillator, the preset frequency can be set to a refresh frequency higher than the local crystal oscillator's thermal inertia response frequency while meeting the current compensation accuracy requirements.

[0122] Local closed-loop frequency modulation refers to a closed-loop control process within the device that continuously adjusts the local clock frequency based on feedback results. For example, the local crystal oscillator can be continuously frequency-modulated based on local compensation word parameters.

[0123] In some embodiments, the monitoring unit, driven by a hardware frequency modulation clock, cyclically writes the local compensation word parameters into the control register of the voltage-controlled temperature-compensated crystal oscillator at a refresh rate not lower than a preset frequency, and updates the compensation value for the next refresh cycle based on the local frequency deviation or phase deviation slope after each write, thereby forming a local closed-loop frequency modulation.

[0124] In some embodiments, the monitoring unit can also write local compensation word parameters into the control register of the digitally controlled oscillator or the direct digital frequency synthesizer, and read the internal counting feedback result in each refresh cycle, and fine-tune the subsequent written code value according to the feedback result to achieve closed-loop frequency biasing and recovery.

[0125] In some embodiments, local closed-loop frequency modulation can also be implemented in other ways. For example, the monitoring unit periodically outputs compensation codes at a preset frequency and performs incremental or decremental adjustments based on the frequency deviation direction measured by the local counter; however, it is not limited to this.

[0126] During the communication dead zone between two "zero-hour period" interaction windows, external network packets are automatically paused to avoid resource preemption and underlying conflicts. The weight parameters of the ARMA model are dynamically adjusted using the time interval sparsity caused by ambient temperature and interference. This allows the monitoring unit to accurately "blindly push" clock drift using its internal independent high-frequency closed-loop algorithm, even when network communication is blocked for extended periods due to strong magnetic pulses. This reduces the cumulative timekeeping error during long periods of lockout and ensures seamless alignment when the next zero-hour period arrives.

[0127] Some embodiments in this specification achieve on-demand scheduling of network resources by introducing a software-defined network controller to globally identify key monitoring areas and issue high-frequency sampling strategies. Simultaneously, by directly sensing the phase of the power frequency AC current through the monitoring unit, it accurately captures physical gaps during the "zero-point period" when electromagnetic radiation is minimal, coinciding with the alternation of positive and negative half-cycles of a strong electric field. Under strong interference, it abandons the traditional cumbersome software protocol stack synchronization mechanism, utilizing the media access control layer to directly trigger extremely lightweight, compact pulse messages for high-frequency sampling and interaction. This significantly improves the survival rate of data packets under strong electromagnetic transient impacts and avoids the problem of broken links and gaps in clock synchronization protocols.

[0128] Figure 3 This is an exemplary schematic diagram illustrating the determination of the phase deviation slope according to some embodiments of this specification.

[0129] In some embodiments, the monitoring unit acquires the polarization angle abrupt change and Verdet constant of the received optical signal; inputs the polarization angle abrupt change and Verdet constant into the electromagnetic calculation model for reverse calculation to determine the transient electromagnetic intensity acting on the monitoring unit; and substitutes the transient electromagnetic intensity into the drift compensation polynomial for calculation to determine the phase deviation slope.

[0130] In some embodiments, the monitoring unit acquires the polarization angle abrupt change and the Verdet constant of the received optical signal.

[0131] The received optical signal refers to the optical signal carrying an optical communication carrier transmitted via a power optical cable connected to the monitoring unit. The polarization angle abrupt change refers to the angle value of the instantaneous rotation of the optical polarization state caused by the Faraday magneto-optical effect resulting from the instantaneous penetration of a strong external electromagnetic field during transmission within the optical fiber. The Verdet constant is a physical constant characterizing the strength of the magneto-optical polarization rotation capability of a specific optical cable medium material under the influence of a magnetic field.

[0132] In some embodiments, the monitoring unit can continuously sample the polarization state of the received optical signal to obtain the polarization angles corresponding to multiple sampling times; perform differential calculation on the polarization angles of adjacent times or adjacent time windows, and expand the angle jump to obtain the polarization angle change amount.

[0133] In some embodiments, the monitoring unit can calculate the polarization angle based on the Stokes parameters output by the polarization detector, and compare the current polarization angle with the moving average polarization angle or the unperturbed reference polarization angle to obtain the polarization angle abrupt change. In some embodiments, the polarization angle abrupt change can also be obtained based on the difference between the continuous sampling sequence and the reference polarization angle, but is not limited thereto.

[0134] In some embodiments, the monitoring unit can read the corresponding Verdet constant from a pre-established calibration table based on the fiber material, operating wavelength, and current temperature. In some embodiments, the monitoring unit can be magnetically calibrated during the installation and commissioning phase to establish a set of Verdet constant parameters corresponding to the monitoring unit and environmental conditions, and the corresponding parameters can be called according to the current scenario during runtime. In some embodiments, the Verdet constant can also be obtained from locally stored parameters or remotely transmitted parameters; however, it is not limited to these methods.

[0135] In some embodiments, the monitoring unit acquires the Stokes vector output by the polarization state analyzer; performs frequency domain filtering on the Stokes vector to separate the low-frequency drift component and the high-frequency abrupt change component; determines the polarization angle abrupt change based on the high-frequency abrupt change component; and corrects the Verdet constant based on the low-frequency drift component.

[0136] In some embodiments, the monitoring unit acquires the Stokes vector output by the polarization state analyzer.

[0137] A polarization state analyzer is an optical detection hardware device that is bypassed or connected in series with the front end of the optical receiving module of the monitoring unit to measure the polarization characteristics of the input beam in real time. The Stokes vector is a mathematical vector consisting of four real-valued parameters (e.g., S0, S1, S2, S3) that completely and uniquely describes the total light intensity of the received optical signal and the distribution ratio of various polarization states.

[0138] In some embodiments, the monitoring unit can read the Stokes parameters corresponding to the sampling time from the digital output interface of the polarization state analyzer and construct a Stokes vector sequence in chronological order. For example, the Stokes vector may include multiple components characterizing the polarization state of the optical signal for subsequent frequency domain decomposition and polarization angle analysis.

[0139] In some embodiments, the monitoring unit performs frequency domain filtering based on Stokes vectors to obtain low-frequency drift components and high-frequency abrupt change components.

[0140] Frequency domain filtering refers to digital signal processing techniques that convert discrete-time series signals to the frequency domain and then block or allow specific frequency components by setting a cutoff frequency. Low-frequency drift components characterize the slowly varying polarization state changes caused by changes in ambient temperature and optical cable mechanical stress; for example, frequencies less than 10 Hz. High-frequency abrupt changes refer to the Faraday magneto-optical polarization state rotation caused by strong electromagnetic transient pulses; for example, frequencies greater than 300 Hz.

[0141] In some embodiments, the monitoring unit may first perform time alignment and discrete Fourier transform on the Stokes vector, and then divide the spectrum into low-frequency and high-frequency intervals according to a preset cutoff frequency; retain the low-frequency interval to obtain the low-frequency drift component, retain the high-frequency interval to obtain the high-frequency abrupt component, and then recover the corresponding component through inverse transform.

[0142] The preset cutoff frequency can be configured based on the fiber optic link length, sampling rate, and environmental disturbance frequency band. The preset cutoff frequency may include a first low-pass cutoff frequency and a second high-pass cutoff frequency. In some embodiments, the first low-pass cutoff frequency can be determined based on the range of mechanical vibration frequencies of the power optical cable in a light wind environment from historical data, specifically the upper limit of that range. The second high-pass cutoff frequency can be set higher than the upper limit of the energy distribution area of ​​the steady-state power frequency and its low-order harmonics of the power system, for example, higher than 400Hz, to suppress power frequency and low-order harmonic components and retain high-frequency abrupt changes caused by strong electromagnetic transient pulses. The monitoring unit can divide the spectrum below the first low-pass cutoff frequency into a low-frequency range, extract spectral lines below the first low-pass cutoff frequency using a digital low-pass filter, and perform an inverse Fourier transform to obtain the low-frequency drift component; and divide the spectrum above the second high-pass cutoff frequency into a high-frequency range, extract spectral lines above the second high-pass cutoff frequency using a digital high-pass filter, and perform an inverse Fourier transform to obtain the high-frequency abrupt change component.

[0143] In some embodiments, the monitoring unit performs a determination process based on the high-frequency abrupt change component to obtain the polarization angle abrupt change amount.

[0144] In some embodiments, the monitoring unit can map the high-frequency abrupt change component to the Poincaré spherical coordinate system, extract the difference in its trajectory change, and calculate the instantaneous polarization rotation angle according to arctan(S2_high / S1_high) / 2. This rotation angle is determined as the polarization angle abrupt change, where S1_high and S2_high represent the Stokes components corresponding to the high-frequency abrupt change component, respectively.

[0145] In some embodiments, the monitoring unit can calculate the polarization azimuth angle difference between adjacent sampling times based on the polarization state change trajectory corresponding to the high-frequency abrupt change component, and determine the angle change exceeding the noise threshold as the polarization angle abrupt change. For example, the monitoring unit can perform unwinding processing on continuous angle sequences to avoid misjudgments caused by angle spanning periods.

[0146] In some embodiments, the monitoring unit may first calculate the amplitude envelope or energy index of the high-frequency mutation component, and then determine the polarization angle mutation amount by combining the polarization angle mapping relationship. This embodiment is suitable for identifying disturbance events with short mutation duration and high amplitude.

[0147] In some embodiments, the polarization angle abrupt change can also be determined in other ways. For example, the monitoring unit can use a lookup table to map the peak value of the high-frequency abrupt change component to the polarization angle change based on a preset angle response model; however, it is not limited to this.

[0148] In some embodiments, the monitoring unit can estimate the equivalent environmental temperature drift and equivalent slow stress of the optical cable based on the arc length of the long-period motion trajectory of the low-frequency drift component on the Poincaré sphere. For example, the arc length of the long-period motion trajectory can be subjected to low-frequency filtering to obtain the low-frequency component L. total,trend and the high-frequency part L total,periodic And according to ΔT=L total,periodic / (KT·d), Δε=L total,trend The equivalent environmental temperature drift ΔT and the equivalent slow stress Δε are calculated using / (Kε·d), where KT and Kε are the temperature and stress sensitivity coefficients, respectively, and d is the conversion scale factor. Then, the stress / temperature-Verdet constant sensitivity coefficient is matched by looking up ΔT and Δε to obtain the physical offset margin of the Verdet constant. This physical offset margin is then added to the current Verdet constant to update the Verdet constant used for subsequent model calculations in real time.

[0149] In some embodiments, the monitoring unit performs correction processing based on the low-frequency drift component to update the Verdet constant.

[0150] In some embodiments, the monitoring unit can jointly analyze the slowly changing polarization rotation trend characterized by the low-frequency drift component with the current temperature, magnetic field background value, or link historical calibration value to calculate the compensation amount of the Verdet constant, and correct the Verdet constant based on the compensation amount. Exemplarily, the compensation amount can be obtained through a linear fitting relationship or a piecewise fitting relationship.

[0151] In some embodiments, the monitoring unit can also input the low-frequency drift component into a pre-established drift compensation model and output a corrected Verdet constant. This drift compensation model can be established based on historical calibration data, with inputs including low-frequency drift characteristics and outputs including the corresponding Verdet constant correction value.

[0152] In some embodiments, the Verdet constant can also be corrected in other ways. For example, the monitoring unit can perform table lookup compensation based on the low-frequency drift component and the temperature calibration curve to obtain the corrected Verdet constant; but it is not limited to this.

[0153] Some embodiments in this specification decouple transient polarization changes from slowly varying parameter calibration by separating high-frequency abrupt changes from low-frequency drift, thereby extracting polarization angle abrupt changes more accurately and improving the accuracy of Verdet constant correction.

[0154] In some embodiments, the monitoring unit performs a reverse calculation based on the polarization angle abrupt change and the Verdet constant to obtain the transient electromagnetic intensity acting on the monitoring unit.

[0155] In some embodiments, the monitoring unit will measure the abrupt change in polarization angle θ. F Verdet constant V Verdet And the equivalent integral length constant L is input into the electromagnetic calculation model, based on Faraday's rotation law θ F =V Verdet Solve in reverse order using B·L, according to B=θ F / (V Verdet The real-time magnetic flux density is calculated using L, which is then used as the transient electromagnetic intensity acting on the monitoring unit.

[0156] In some embodiments, transient electromagnetic intensity can also be determined in other ways. For example, the monitoring unit may perform a mapping based on a pre-calibrated polarization angle abrupt change—Verdet constant—electromagnetic intensity lookup table; but it is not limited to this.

[0157] In some embodiments, the monitoring unit performs drift compensation polynomial calculations based on transient electromagnetic intensity to obtain the phase deviation slope.

[0158] The monitoring unit substitutes the transient electromagnetic intensity as the independent variable x into the pre-calibrated drift compensation polynomial y = a0 + a1·x + a2·x 2 +a3·x 3 +…, calculate the phase drift rate caused by the stimulated deterioration of the crystal oscillator frequency, and output it as the phase deviation slope; where the polynomial coefficients a0 to a… n It is obtained by calibrating the clock crystal in a strong magnetic environment laboratory at the time of manufacture.

[0159] In some embodiments, the order and coefficients of the drift compensation polynomial can be adjusted based on the field calibration results; for example, the monitoring unit can update the drift compensation polynomial based on the fitting parameters after periodic recalibration; but it is not limited to this.

[0160] Some embodiments in this specification reuse existing power optical cables and optical communication carriers themselves as "distributed electromagnetic sensors" to extract polarization angle abrupt changes caused by the Faraday magneto-optical effect and infer external transient electromagnetic intensity. This eliminates the cost of laying expensive electromagnetic detection equipment along the entire line. Simultaneously, the calculated transient electromagnetic intensity is used to predict the phase deviation slope of the local crystal oscillator, allowing for the acquisition of valuable equipment degradation trend indicators before strong interference completely disrupts communication. This provides data support for subsequent early network intervention and synchronous correction.

[0161] Figure 4 This is an exemplary flowchart illustrating sampling at a high-frequency sampling rate according to some embodiments of this specification. Flow 400 can be executed by a software-defined network controller (software-defined network controller 110).

[0162] In some embodiments, the interference protection strategy includes a sampling and compensation flow table, which includes a high-frequency sampling frequency.

[0163] The sampling and compensation flow table (hereinafter referred to as the flow table) refers to the match-action rule entries used to instruct the monitoring unit to perform network sampling and packet capture, service packet isolation and discarding, and internal clock compensation operations at a specific frequency (i.e., high-frequency sampling frequency) that exceeds the normal cycle.

[0164] Flow tables can include flow table status, high-frequency sampling frequency, etc. Flow table status includes dormant state and active state. Dormant state refers to a suspended state in which the flow table resides in the forwarding table space of the monitoring unit but has not yet been enabled for data flow matching. It is used to deploy flow tables in advance but not to start high-frequency sampling. Active state refers to a running state in which matching, forwarding, and interception actions are immediately started on the passing underlying physical data after the trigger condition is met. It is used to start high-frequency sampling and retain the sampling segments required for synchronization compensation.

[0165] Triggering conditions may include the physical layer detecting a message misalignment event or the current time being a predicted strong interference moment. The physical layer detecting a message misalignment event refers to the underlying physical chip (PHY) of the monitoring unit detecting a low-level hard fault phenomenon caused by external strong electric field interference, such as loss of preamble, frame delimiter distortion, or synchronization header alignment failure in the received serial bit stream.

[0166] The predicted time of severe interference refers to the absolute system time (i.e., the predicted time of severe interference) at a specific optical cable location (i.e., the predicted area of ​​severe interference), calculated by the interference prediction model. For further explanation of the triggering conditions, please see below.

[0167] In some embodiments, the software-defined network controller can generate sampling and compensation flow tables for different key monitoring areas, or it can generate a shared template flow table for multiple monitoring units, and then instantiate and configure it according to the area identifier or monitoring unit identifier. The high-frequency sampling frequency can be higher than the regular inspection sampling frequency and adjusted according to the area's interference level. For further explanation regarding the high-frequency sampling frequency, see [link to relevant documentation]. Figure 2 Related content.

[0168] like Figure 4 As shown, process 400 includes the following steps.

[0169] Step 410: Receive power load data and power flow change data transmitted by one or more micro phasor measurement units in key monitoring areas.

[0170] Power load data refers to a set of parameters that reflect the baseline state of steady-state operation of the power grid. Power load data can include real-time voltage and current phasors of transmission lines.

[0171] Power flow transient data refers to the set of alarm parameters reflecting drastic transient changes and faults in the power grid's operating conditions. Power flow transient data can include high-power circuit breaker operating status signals and short-circuit transient current peak values. Circuit breakers with a rated voltage of 110kV and above or a rated breaking current of 40kA and above can be classified as high-power circuit breakers. High-power circuit breaker operating status signals can include closing / opening position status, operating timestamp, reclosing operation identifier, and operation type (e.g., planned switching operation, relay protection tripping, surge arrester breakdown operation). Short-circuit transient current peak values ​​include the instantaneous maximum current and current change rate.

[0172] In some embodiments, the software-defined network controller can establish a data channel with the micro phasor measurement unit through a dedicated power communication network, and receive periodically reported power load data and event-triggered power flow change data according to a unified timestamp.

[0173] In some embodiments, the software-defined network controller can first receive data packets that have been synchronized and cached from the edge aggregation node of the key monitoring area, and then parse them to obtain the power load data and power flow change data corresponding to each micro phasor measurement unit.

[0174] Step 420: Based on power load data and power flow change data, determine one or more predicted strong interference times and corresponding predicted strong interference areas in the future period through the interference prediction model.

[0175] In some embodiments, the application layer of the software-defined network controller uses a circuit breaker action signal or a current change rate exceeding a preset threshold as a trigger source. This preset threshold can be based on empirical estimation. When a trigger source is detected, the software-defined network controller uses the instantaneous maximum current in the short-circuit transient current peak as the initial value of the electromagnetic impulse intensity and constructs an interference prediction model based on the transmission line topology and the spatial location of the optical cable.

[0176] The interference prediction model calculates the predicted absolute time and impact range of the shock wave reaching each communication node by estimating the propagation delay of the electromagnetic pulse traveling wave along the overhead line and combining this with the timestamp of the source node's action. These timestamps serve as one or more predicted strong interference moments and corresponding predicted strong interference regions. For further explanation of the specific construction of the interference prediction model and the determination of the predicted strong interference moments and corresponding predicted strong interference regions, please refer to the relevant embodiments below.

[0177] In some embodiments, the software-defined network controller (SDB) constructs a two-layer graph mapping model that includes the physical topology of the power grid and the physical topology of the communication network. The SDB extracts the initial energy and source node location of transient electromagnetic waves from power flow change data and obtains a high-precision timestamp when the source node fault occurs. Based on the initial energy, source node location, traveling wave propagation velocity, and attenuation constant, the SDB calculates the absolute time difference and predicted interference intensity of the electromagnetic surge arriving at one or more monitoring units in the two-layer graph mapping model. Based on the absolute time difference and predicted interference intensity, the SDB determines the predicted strong interference region. The high-precision timestamp is added to the absolute time difference corresponding to each monitoring unit to obtain the predicted strong interference time for each monitoring unit, and a sampling and compensation flow table containing the predicted strong interference time is generated for each monitoring unit within the predicted strong interference region.

[0178] In some embodiments, the two-layer graph mapping model includes a power grid mapping model and a communication network mapping model; the power grid mapping model includes power grid nodes, power grid edges and corresponding features, and the communication network mapping model includes communication nodes, communication edges and corresponding features.

[0179] The physical topology of a power grid refers to the actual physical connection structure of various power nodes and their connecting lines in a power system. For example, the connection relationships between substations, power poles, and transmission lines constitute the physical topology of a power grid.

[0180] The physical topology of a communication network refers to the actual physical connection structure of each communication node and its transmission links in the communication network. For example, the connection relationship between optical transmission equipment, monitoring units, and power optical cables can constitute the physical topology of a communication network.

[0181] The two-layer graph mapping model refers to a data structure model that is jointly constructed by a directed graph of power topology (upper layer) representing interference sources and a directed graph of communication topology (lower layer) representing interference entities under a unified coordinate system, through geospatial constraints.

[0182] The power grid mapping model is a graph theory model that reflects the relationship between the transmission of high-voltage power and the distributed physical network.

[0183] A power grid node is a node entity in a power grid mapping model, representing a specific facility or location within a power system. Power grid nodes include substations, power poles, and generator sets. A power system is a system for the production and transmission of electrical energy, consisting of power generation, transmission, transformation, distribution, and related operating facilities. A substation is a power facility used for voltage transformation, power distribution, line connection, and operational control; examples include step-up substations, step-down substations, or hub substations. A power pole is a vertical support structure used to support overhead conductors, ground wires, or related communication cables; examples include transmission towers or power poles. A generator set is a combination of power generation equipment used to convert other forms of energy into electrical energy; examples include thermal power units, hydropower units, or wind power units.

[0184] Power grid node characteristics refer to the set of information used to describe the physical or operational attributes of power grid nodes. Power grid node characteristics include the geographic coordinates and operating voltage level of the power grid node. Geographic coordinates refer to coordinate information used to represent the spatial location of an object, such as longitude, latitude, and elevation. Operating voltage level refers to the voltage level to which a power facility or line belongs during operation, such as 110kV, 220kV, or 500kV.

[0185] A power grid edge is an edge element in a power grid mapping model used to connect two power grid nodes. A power grid edge can be a transmission line connecting two substations. A transmission line is a line facility used to transmit electrical energy in a power system, such as an overhead transmission line or a cable transmission line. A power grid edge is considered to exist between two power grid nodes when there is an actual transmission line connection between them.

[0186] Grid edge characteristics include line length and conductor spatial arrangement parameters. Line length refers to the spatial length of a line, such as the actual length of a transmission line laid between two adjacent grid nodes. Conductor spatial arrangement parameters describe the geometric arrangement of conductors in space, such as conductor spacing, phase sequence arrangement, and height above ground.

[0187] The communication network mapping model is a graph theory model that reflects the relationship between weak current information transmission and clock synchronization.

[0188] A communication node is a node entity in a communication network mapping model, representing equipment that undertakes optical communication transmission, processing, or monitoring functions. Communication nodes include optical transmission equipment and monitoring units. Optical transmission equipment refers to devices used to send, receive, forward, or process optical communication signals, such as optical transceivers, optical repeaters, or optical switches.

[0189] Communication node characteristics refer to attribute information used to describe the processing or clocking capabilities of a communication node. These characteristics include hardware processing latency and local clock accuracy. Hardware processing latency refers to the time consumed for a signal to complete operations such as reception, processing, forwarding, or encapsulation within the device hardware; for example, chip-level transceiver processing time. Local clock accuracy is a parameter characterizing how closely the local clock output approximates a reference time or frequency; for example, nanosecond-level timekeeping accuracy or frequency stability indicators.

[0190] A communication edge is an edge element in a communication network mapping model used to connect two communication nodes. A communication edge can be a power fiber optic link connecting two communication nodes. A communication edge is considered to exist between two communication nodes when there is an actual power fiber optic link connecting them.

[0191] Communication characteristics include the fiber optic cable span length and the medium signal attenuation coefficient. The fiber optic cable span length refers to the physical length of the fiber optic cable between adjacent support points or adjacent connection nodes; for example, the length of the cable segment between adjacent towers. The medium signal attenuation coefficient is a parameter used to characterize the degree to which a signal weakens as the propagation distance increases in the transmission medium; for example, the optical signal attenuation coefficient in optical fiber.

[0192] In some embodiments, the software-defined network controller constructs a two-layer graph mapping model by: importing coordinate information, voltage levels, transmission line ledgers, and conductor layout ledgers of substations, towers, and generator sets from a GIS system to initialize a power grid mapping model; importing optical transmission equipment, monitoring units, and power optical cable laying ledgers from a communication network management system to initialize a communication network mapping model; and then establishing cross-layer mapping relationships based on latitude and longitude overlap relationships, accompanying direction relationships, or shared tower installation relationships under a unified coordinate system to obtain a two-layer graph mapping model.

[0193] In some embodiments, the software-defined network controller extracts the initial energy and source node location of transient electromagnetic waves from power flow change data.

[0194] Transient electromagnetic waves are short-duration electromagnetic fluctuations generated by faults, switching actions, or other transient events. For example, the electromagnetic pulse generated by a short-circuit fault can be classified as a transient electromagnetic wave.

[0195] Initial energy refers to the initial energy value of a transient electromagnetic wave when it is released at its source. For example, the initial electromagnetic shock energy released at the moment of action of a fault point can be used as the initial energy. In some embodiments, the software-defined network controller can filter nodes whose current change rate exceeds a preset change threshold from power flow change data, determine the physical reporting location of the node as the source node location, extract the corresponding short-circuit transient current peak value, and combine it with the line equivalent impedance Z and duration Δτ, according to E=I 2 The initial energy is calculated as ×Z×Δτ, where I is the peak current, Z is the corresponding grid node impedance, and Δτ is the extremely short-term window.

[0196] The location of the source node refers to the spatial location of the source node in the model that causes a sudden power flow change or electromagnetic shock. For example, the location of a tower or substation where a short-circuit fault occurs can be used as the location of the source node.

[0197] In some embodiments, the software-defined network controller calculates the absolute time difference of electromagnetic surges arriving at one or more monitoring units and predicts the interference intensity based on initial energy, source node location, traveling wave propagation speed, and attenuation constant in a two-layer graph mapping model.

[0198] The propagation velocity of a traveling wave refers to the speed parameter of a transient traveling wave as it propagates along a line or in space; for example, the speed at which an electromagnetic pulse propagates along a transmission line. The attenuation constant is a parameter used to characterize how quickly the energy or amplitude of an electromagnetic wave decays during propagation. For example, the attenuation constant can be used to describe the degree of energy loss of an electromagnetic surge along its propagation path.

[0199] In some embodiments, the traveling wave propagation velocity and attenuation constant can be determined based on the line type, conductor spatial arrangement parameters, medium environment, and historical calibration data. For example, the software-defined network controller can look up the basic propagation velocity and basic attenuation constant according to tables for overhead lines, optical cable sections on the same tower, or free-space radiation sections, and then correct them by combining the operating voltage level corresponding to the current power load data, line length, and historical event playback results; when the propagation path contains multiple different segments, values ​​can be taken separately for each segment of the path and accumulated.

[0200] Electromagnetic surges refer to transient electromagnetic impacts that are sudden and have high energy. For example, pulsed electromagnetic disturbances caused by circuit breaker operation or short-circuit faults can be classified as electromagnetic surges.

[0201] The absolute time difference refers to the precise time required for an electromagnetic traveling wave to travel through space and radiate from its source node to a specific communication node. For example, the propagation time of an electromagnetic surge from a fault point to a monitoring unit.

[0202] Predicted interference intensity refers to the calculated expected intensity value of the interference at the target location, such as the residual field strength when an electromagnetic surge arrives at a monitoring unit.

[0203] In some embodiments, the interference prediction model may employ a two-layer graph mapping model. In some embodiments, the software-defined network controller takes the location of the source node as the starting point and uses the shortest path algorithm in the power grid mapping model to calculate the propagation distance D1 of the electromagnetic traveling wave along the transmission line to the high-voltage tower closest to the spatial projection of the target monitoring unit; then it calculates the vertical free space distance D2 from the high-voltage tower to the target monitoring unit; the absolute time difference is calculated according to Time_diff=(D1+D2) / traveling wave propagation speed, and the predicted interference intensity is calculated according to Intensity=initial energy×exp(-attenuation constant×(D1+D2)).

[0204] In some embodiments, the software-defined network controller may further include the following steps in calculating the absolute time difference and predicting the interference intensity: configuring each edge in the two-layer graph mapping model as a weighted edge with propagation speed and attenuation parameters, accumulating the propagation distance and path attenuation from the source node to the target monitoring unit segment by segment; calculating the total propagation delay based on the distance and wave velocity of each segment, and calculating the predicted interference intensity of the target monitoring unit based on the attenuation product or logarithmic attenuation of each segment.

[0205] In some embodiments, the software-defined network controller determines the predicted strong interference area based on the absolute time difference and the predicted interference intensity.

[0206] In some embodiments, the software-defined network controller compares the predicted interference intensity of each monitoring unit with a security intensity threshold, identifies the set of monitoring units exceeding the security intensity threshold as the predicted strong interference region, and uses the location range or coverage link range of the corresponding monitoring unit as the spatial boundary of the region. The security intensity threshold can be preset.

[0207] In some embodiments, the software-defined network controller generates a sampling and compensation flow table containing the predicted strong interference time for each monitoring unit within the predicted strong interference area based on the absolute time difference.

[0208] In some embodiments, the software-defined network controller can add the high-precision timestamp of the source fault action to the absolute time difference of each monitoring unit to obtain the predicted strong interference time for each monitoring unit.

[0209] This specification describes several embodiments that establish a two-layer spatial mapping model between the power grid (interference generation layer) and the communication network (victim-bearing layer). By accurately simulating the composite path of "traveling wave propagation" and "spatial radiation" of fault pulses in the physical world, it achieves precise calculation of the arrival time and intensity of interference pulses. Through spatial geometric transformation to extract the absolute time difference of each node, it can generate individually customized, precise nanosecond-level protection activation schedules for monitoring units scattered along the optical cable over hundreds of kilometers, improving the efficiency of computing resource scheduling and the precision of collaborative anti-interference.

[0210] Step 430: Distribute the dormant sampling and compensation flow meter to one or more monitoring units within one or more key monitoring areas.

[0211] In some embodiments, the software-defined network controller can send flow table entries to the target monitoring unit one by one through the control channel. After receiving the entries, the monitoring unit writes the flow table to the local cache or configuration register and marks the flow table status as dormant.

[0212] In some embodiments, the software-defined network controller may also first send the sampling and compensation flow table to the regional agent node, and then the regional agent node multicasts or broadcasts it to each monitoring unit.

[0213] Step 440: When one or more monitoring units detect a message misalignment event at the physical layer or when the current time is a predicted strong interference time, switch the sampling and compensation flow table to the active state to perform sampling according to the high-frequency sampling frequency.

[0214] In some embodiments, the monitoring unit maintains a local polling and hardware monitoring mechanism. On the one hand, it compares the local system time with the predicted strong interference time bound to the sampling and compensation flow table matching domain in real time. On the other hand, it monitors the hardware interrupt pin of the PHY chip. When the local time comparison hits the predicted strong interference time, or when the PHY chip detects a message misalignment event caused by a sudden interference and triggers an interrupt, the processor inside the monitoring unit immediately changes the status flag bit of the corresponding sampling and compensation flow table in the TCAM area from "0" to "1" to switch the flow table from a dormant state to an active state.

[0215] In some embodiments, after the sampling and compensation flow table is locally activated, the underlying network processor immediately executes the interception of regular service packets, initiates high-frequency sampling, and calls the compact pulse packet transmission logic according to the activated flow table. The sampled data can be accompanied by a high-precision time stamp and used for subsequent synchronization compensation or anomaly location.

[0216] Some embodiments in this specification, through circuit breaker operation and transient current source prediction, enable the software-defined network controller to preemptively issue defensive flow tables and remain dormant. This avoids the fatal flaw of communication link disruptions during strong electromagnetic interference outbreaks, which prevent control commands from being issued. When the interference actually arrives or the underlying physical layer collapses first, the dormant flow table can be instantly activated into a "hard-shell" protective state through local triggering, maximizing the preservation of core synchronization data sampling and recovery.

[0217] This specification also provides an embodiment of a power communication long-distance transmission synchronization monitoring device. The device includes a processor for executing the power communication long-distance transmission synchronization monitoring method described in any embodiment of this specification.

[0218] This specification also provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions from the storage medium, the computer executes the power communication long-distance transmission synchronous monitoring method described in any embodiment of this specification.

[0219] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0220] Some embodiments of this specification also provide a computer-readable storage medium that, when a computer reads computer instructions from the storage medium, enables the computer to execute at least a portion of the following program modules: a real-time synchronization parameter acquisition module, an external AC phase determination module, a zero-point time period determination module, a compact pulse message transmission control module, and an interference prediction and sampling compensation flow table processing module, thereby executing the power communication long-distance transmission synchronization monitoring method described in the embodiments of this specification.

[0221] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0222] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0223] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0224] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0225] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0226] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A long-distance synchronous monitoring system for power communication transmission, characterized in that, It includes a software-defined network controller and multiple monitoring units, which are deployed along the power optical cable of the optical communication system; The software-defined network controller is configured as follows: The real-time synchronization parameters of the optical communication system are obtained from multiple monitoring units. Based on the real-time synchronization parameters, one or more key monitoring areas are determined, and interference protection strategies are issued to one or more monitoring units within the one or more key monitoring areas. The interference protection strategies include sampling and compensation flow tables, which include high-frequency sampling frequencies. The real-time synchronization parameters include the phase deviation slope of each monitoring unit. The software-defined network controller is further configured to: Receive power load data and power flow change data transmitted by micro phasor measurement units in one or more key monitoring areas; Based on the power load data and the power flow change data, one or more predicted strong interference moments and corresponding predicted strong interference areas within a future time period are determined through an interference prediction model. The dormant sampling and compensation flow table is sent to one or more monitoring units within the one or more key monitoring areas; When one or more of the monitoring units detect a message misalignment event at the physical layer or when the current time is the predicted strong interference time, the sampling and compensation flow table is switched to the active state to perform sampling according to the high-frequency sampling frequency; The monitoring unit is configured as follows: Acquire the analog-to-digital conversion sampling signal collected by the electric field induction coil; The analog-to-digital conversion sampling signal is input into a preset algorithm for processing to determine the phase of the external AC power. Based on the external AC phase, the zero-point time period corresponding to the AC electromagnetic field is determined; as well as, When it is determined that the system is under strong electromagnetic interference, a compact pulse message containing only a timestamp is sent to the target monitoring unit through the medium access control layer based on the zero-point time period. This message is used for phase calibration sampling and delay compensation based on the high-frequency sampling frequency.

2. The power communication long-distance transmission synchronous monitoring system as described in claim 1, characterized in that, The monitoring unit is further configured to: Obtain the polarization angle abrupt change and Verdet constant of the received optical signal; The polarization angle abrupt change and the Verdet constant are input into the electromagnetic calculation model for reverse calculation to determine the transient electromagnetic intensity acting on the monitoring unit; and, The transient electromagnetic intensity is substituted into the drift compensation polynomial for calculation to determine the phase deviation slope.

3. The long-distance power communication transmission synchronous monitoring system as described in claim 2, characterized in that, The monitoring unit is further configured to: Obtain the Stokes vector output by the polarization state analyzer; Frequency domain filtering is performed on the Stokes vector to separate the low-frequency drift component and the high-frequency abrupt change component; Based on the high-frequency abrupt change component, determine the polarization angle abrupt change amount; and, The Verdet constant is corrected based on the low-frequency drift component.

4. A method for synchronous monitoring of long-distance power communication transmission, characterized in that, An application is made in a long-distance synchronous monitoring system for power communication transmission. The system includes a software-defined network controller and multiple monitoring units, which are deployed along the power optical cable of the optical communication system. The method for long-distance synchronous monitoring of power communication transmission includes: The real-time synchronization parameters of the optical communication system are obtained from multiple monitoring units. Based on the real-time synchronization parameters, one or more key monitoring areas are determined, and interference protection strategies are issued to one or more monitoring units within the one or more key monitoring areas. The interference protection strategies include sampling and compensation flow tables, which include high-frequency sampling frequencies. The real-time synchronization parameters include the phase deviation slope of each monitoring unit. The long-distance power communication transmission synchronization monitoring method further includes: Receive power load data and power flow change data transmitted by micro phasor measurement units in one or more key monitoring areas; Based on the power load data and the power flow change data, one or more predicted strong interference moments and corresponding predicted strong interference areas within a future time period are determined through an interference prediction model. The dormant sampling and compensation flow table is sent to one or more monitoring units within the one or more key monitoring areas; When one or more of the monitoring units detect a message misalignment event at the physical layer or when the current time is the predicted strong interference time, the sampling and compensation flow table is switched to the active state to perform sampling according to the high-frequency sampling frequency; The method for synchronous monitoring of long-distance power communication transmission also includes: Acquire the analog-to-digital conversion sampling signal collected by the electric field induction coil; The analog-to-digital conversion sampling signal is input into a preset algorithm for processing to determine the phase of the external AC power. Based on the external alternating current phase, determine the zero-point time period corresponding to the alternating electromagnetic field; and When it is determined that the system is under strong electromagnetic interference, a compact pulse message containing only a timestamp is sent to the target monitoring unit through the medium access control layer based on the zero-point time period. This message is used for phase calibration sampling and delay compensation based on the high-frequency sampling frequency.

5. The method for synchronous monitoring of long-distance power communication transmission as described in claim 4, characterized in that, The process of obtaining the real-time synchronization parameters of the optical communication system includes: Obtain the polarization angle abrupt change and Verdet constant of the received optical signal; The polarization angle abrupt change and the Verdet constant are input into the electromagnetic calculation model for reverse calculation to determine the transient electromagnetic intensity acting on the monitoring unit; and, The transient electromagnetic intensity is substituted into the drift compensation polynomial for calculation to determine the phase deviation slope.

6. The method for synchronous monitoring of long-distance power communication transmission as described in claim 5, characterized in that, The acquisition of the polarization angle abrupt change and Verdet constant of the received optical signal includes: Obtain the Stokes vector output by the polarization state analyzer; Frequency domain filtering is performed on the Stokes vector to separate the low-frequency drift component and the high-frequency abrupt change component; Based on the high-frequency abrupt change component, determine the polarization angle abrupt change amount; and, The Verdet constant is corrected based on the low-frequency drift component.

7. A long-distance synchronous monitoring device for power communication transmission, characterized in that, Includes a processor, said processor being used to execute the power communication long-distance transmission synchronous monitoring method according to any one of claims 4 to 6.

8. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions from the storage medium, the computer executes the power communication long-distance transmission synchronous monitoring method as described in any one of claims 4 to 6.

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