A monitoring method, system and emi protection device for a filter

Abstract

The application relates to a monitoring method and system for a filter and an electromagnetic pulse prevention device, and belongs to the technical field of filter monitoring. The method comprises the following steps: periodically acquiring initial power working condition data; determining whether an abnormal working condition exists according to the initial power working condition data to obtain a first determination result; if the first determination result is that there is an abnormal working condition risk, triggering a retention observation mechanism to obtain a second determination result; when the first determination result or the second determination result is that there is an abnormal working condition, determining abnormal working condition data, and acquiring output power working condition data in real time; based on the output power working condition data and the abnormal working condition data, the filtering effect of the electromagnetic pulse prevention filter is evaluated in quality to obtain an evaluation result; and the initial filtering parameter is adaptively adjusted according to the evaluation result. Through the closed-loop measures of monitoring, judging, evaluating and feedback adjusting, the application is helpful to improving the reliability and stability of the power supply system by finding problems in time.

Description

Technical Field

[0001] This application relates to the field of filter monitoring technology, and in particular to a method, system and electromagnetic pulse protection device for monitoring filters. Background Technology

[0002] As a key component for signal frequency selection in electronic systems, filters are widely used in fields such as communication, radar, and measurement and control. The stability of their performance directly affects the overall signal quality of the system. Among them, electromagnetic pulse (EMP) filters mainly reduce the harmonic content in the power supply by absorbing or reflecting electromagnetic pulse interference and combining it with LC filter circuits, thereby providing a stable power supply environment for the equipment.

[0003] Currently, the function of traditional electromagnetic pulse (EMP) filters is limited to passive filtering. Their operation depends entirely on the static characteristics of the hardware itself, and their performance relies on periodic manual inspection or passive troubleshooting after a fault occurs. However, in actual operation, the real-time operating conditions of the power supply are uncertain. The intensity and frequency of voltage amplitude, harmonic components, and electromagnetic pulse interference may change randomly and uncontrollably. When the filter is subjected to the impact of a transient electromagnetic pulse or voltage transient, it may still maintain the appearance of normal operation in the short term without exposing potential hidden dangers. For example, when the power supply causes voltage transients due to transient overvoltage, current surge, or harmonic distortion, although traditional filters can temporarily suppress interference, they cannot record or report such abnormal events. At the same time, the performance degradation of its internal components (such as inductor windings and capacitor dielectrics) is difficult to detect in a timely manner through conventional means.

[0004] Therefore, when traditional filters are in undetected abnormal operating conditions for a long time, the core components of the filter (such as varistors and capacitors) may gradually deteriorate due to repeated overload stress, or even fail suddenly due to cumulative damage, which greatly reduces the operational reliability of the equipment. It may also cause a chain of failures in sensitive downstream electronic equipment due to the implicit decline in filtering performance, resulting in production interruption or high maintenance costs. Summary of the Invention

[0005] To address the issue that traditional filters are prone to performance degradation due to unexpected events, leading to low operational reliability, this application provides a monitoring method, system, and electromagnetic pulse protection device for filters.

[0006] Firstly, this application provides a monitoring method for a filter, employing the following technical solution: A method for monitoring a filter, comprising: Periodically acquire initial power condition data at the input of the electromagnetic pulse protection device; Based on the initial power condition data, determine whether there is an abnormal condition and obtain a first determination result; If the first judgment result indicates that there is a risk of abnormal working conditions, the observation and detention mechanism is triggered to obtain the second judgment result; When the first judgment result or the second judgment result indicates the existence of an abnormal operating condition, the abnormal operating condition data is determined, and the output power condition data of the output terminal of the anti-electromagnetic pulse device is acquired in real time. The filtering effect of the electromagnetic pulse filter is evaluated based on the output power supply operating condition data and the abnormal operating condition data, and the evaluation results are obtained. The optimization parameters are obtained based on the evaluation results; The preset initial filtering parameters in the electromagnetic pulse protection filter are adaptively adjusted according to the optimization parameters to obtain the optimal filtering parameters.

[0007] By adopting the above technical solution, the initial power condition data of the input terminal of the electromagnetic pulse protection device is acquired periodically. Based on the initial power condition data, it is determined whether there is an abnormal condition and a first judgment result is obtained. This can effectively identify various abnormal conditions, such as voltage surges and drops, current overload, etc., and the judgment speed is relatively fast. When it is determined that there is a risk of abnormal condition, the observation mechanism is triggered for further confirmation, and a second judgment result is obtained. This further improves the accuracy of the judgment and greatly reduces the occurrence of false judgments and missed judgments. When it is determined that there is an abnormal condition, the abnormal condition data is determined in detail, including the duration of the abnormality, the curves of current and voltage changes over time, and the environmental parameters at the time of the abnormality. This data provides rich information for in-depth analysis of the causes and effects of the abnormal condition, and helps to better reflect the performance of the electromagnetic pulse protection filter under abnormal conditions. The filtering effect of the electromagnetic pulse protection filter is evaluated based on the output power supply operating condition data and abnormal operating condition data, resulting in a comprehensive and accurate evaluation result that can reflect the filter's performance in a comprehensive manner. At the same time, this application considers environmental impact factors, making the evaluation results more consistent with the actual situation. Finally, the optimized parameters are obtained based on the evaluation results, and the preset initial filtering parameters in the electromagnetic pulse protection filter are adaptively adjusted to obtain the optimal filtering parameters. This adaptive adjustment mechanism enables the filter to dynamically optimize its performance according to the actual working conditions, ensuring that the best filtering effect can be achieved in different power supply environments. Through continuous adjustment and optimization, the adaptability and stability of the filter are improved, and the impact of environmental changes and abnormal working conditions on the filtering effect is reduced. Through the above series of monitoring, judgment, evaluation and adjustment measures, this application can promptly detect and resolve problems that occur during the operation of the filter, improve the reliability and stability of the entire power supply system, reduce damage to equipment caused by electromagnetic interference, reduce the incidence of system failures, ensure the normal operation of the equipment, and improve production efficiency and product quality.

[0008] In one specific implementation scheme, the detention and observation mechanism triggered when the first judgment result indicates the existence of an abnormal operating condition risk includes: Within a preset time period, the initial power condition data corresponding to the first judgment result is continuously acquired in real time; The relative fluctuation rate of the initial power condition data over a preset period of time is obtained based on the initial power condition data. The global trend of data change is determined based on all the initial power condition data within the specified time period, and the actual rate of change is obtained based on the global trend of change and the relative fluctuation rate. The actual rate of change is compared with a preset speed threshold to obtain a second judgment result.

[0009] In one specific implementation scheme, determining the global change trend of the data based on all the initial power condition data within the specified time period, and obtaining the actual change rate based on the global change trend and the relative fluctuation rate, includes: If the initial power condition data continues to increase over time during the specified period, then the global trend is upward. If the initial power condition data continues to decrease over time during the specified period, the global trend is decreasing. When the global trend is increasing or decreasing, the relative fluctuation rate is directly taken as the actual rate of change. Otherwise, the data trend fitting and discrimination mechanism is triggered to obtain the global change trend, and the actual change rate is obtained based on the global change trend and the relative fluctuation rate; The data trend fitting and discrimination mechanism includes: The initial power supply condition data within the specified time period and their corresponding time points are input into a preset curve fitting algorithm model to obtain the fitted curve. ; Calculate the fitted curve Average operating condition data over the specified time period; Calculate the sum of variances between all the initial power condition data and the average condition data acquired within the specified time period, and compare the sum of variances with a preset fluctuation threshold to obtain the global trend.

[0010] In one specific implementation scheme, obtaining the actual rate of change based on the global trend and the relative fluctuation rate includes: If the global change trend is generally flat, then the relative fluctuation rate is directly taken as the actual change rate. If the global change trend is oscillation, then the correction speed value is obtained based on several initial power condition data within the time period, and the correction speed value is substituted into a preset absolute change speed calculation formula to obtain the actual change speed. The formula for calculating the speed value used for correction is as follows: ; in, Represents the fitted curve In the interval Average operating condition data in the data; The speed value used to correct the initial power supply condition data over a period of time; The formula for calculating the absolute rate of change is as follows: ; ; in, Indicates the actual rate of change; express Weight parameters; express The weight parameters.

[0011] By adopting the above technical solution, the initial power condition data corresponding to the first judgment result is continuously acquired in real time within a preset period of time. This ensures that there is enough data for subsequent analysis, and continuous monitoring can capture all the details of the changes in the initial power condition data during this period, avoiding judgment errors caused by insufficient data sampling. For example, some abnormal conditions may not be obvious in a short period of time, but will gradually appear over time. Continuous monitoring can detect these potential problems in a timely manner. The relative fluctuation rate of the initial power supply data within a preset time period is obtained. This indicator can intuitively reflect the dynamic changes of the data. The relative fluctuation rate can help determine whether the data is in a stable state or a rapidly changing state. For example, if the relative fluctuation rate of the initial current data is too fast, it may mean that there is a potential abnormality such as a short circuit. If the relative fluctuation rate is too slow, it may indicate that the system is in a relatively stable operating state, but it is still necessary to further confirm whether there is a slowly developing fault. This method determines the global trend of data changes based on all initial power supply condition data over a period of time, and obtains the actual rate of change based on the global trend and relative fluctuation rate. Analyzing the data from a macroscopic perspective reveals long-term patterns, while combining the actual rate of change obtained from the relative fluctuation rate comprehensively considers both short-term and long-term trends, making the judgment more comprehensive and accurate. For example, even if the relative fluctuation rate of the data is relatively fast at a certain moment, but the global trend is moving towards the normal range, it may not necessarily indicate an abnormal operating condition. This application quantifies these data to identify suspected abnormal operating conditions, effectively avoiding interference from subjective factors, making the judgment more objective and reliable, and helping to promptly identify potential problems and take corresponding measures, thereby improving the reliability and stability of the electromagnetic pulse filter. Furthermore, this mechanism can adapt to different power supply environments and operating condition changes, exhibiting strong adaptability and flexibility.

[0012] In one specific implementation, the output power condition data includes the output voltage data and the output current data; the initial power condition data includes the initial voltage data and the initial current data; the abnormal condition data includes the abnormal duration and environmental parameters; the quality evaluation of the filtering effect of the electromagnetic pulse filter based on the output power condition data yields the following evaluation results: The current harmonic suppression rate is obtained based on the initial current data, the output current data, the initial voltage data, and the output voltage data. The input signal power is calculated based on the initial current data and the initial voltage data, the output signal power is calculated based on the output current data and the output voltage data, and the insertion loss is obtained based on the input signal power and the output signal power. The residual pulse suppression amount is obtained based on the pulse peak value in the abnormal duration, output current data, and output voltage data. The environmental impact factor is obtained based on the environmental parameters. The harmonic suppression rate threshold, the insertion loss threshold, and the pulse suppression residual threshold are dynamically corrected based on the environmental impact factors, and the evaluation results are obtained based on the corrected data.

[0013] Secondly, this application provides a smart terminal, which adopts the following technical solution: A smart terminal is characterized by comprising a memory and a processor, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement a monitoring method for a filter as described in the first aspect.

[0014] Thirdly, this application provides an electromagnetic pulse protection device, which adopts the following technical solution: An electromagnetic pulse protection device includes an electromagnetic pulse protection filter and the intelligent terminal described in the second aspect; The electromagnetic pulse filter is used to suppress electromagnetic pulse interference and filter harmonics in the input power supply according to the pre-stored initial filtering parameters. The intelligent terminal is used to identify and warn of abnormal operating conditions of the electromagnetic pulse filter, and to evaluate the filtering effect of the electromagnetic pulse filter to obtain the evaluation result. Then, the initial filtering parameters are adaptively adjusted according to the evaluation result.

[0015] Fourthly, this application provides a monitoring system for filters, employing the following technical solution: A monitoring system for a filter includes: Data acquisition devices are respectively installed at the input and output ends of the electromagnetic pulse filter, and are used to acquire the initial power condition data at the input end of the electromagnetic pulse filter and the output power condition data at the output end of the electromagnetic pulse filter in real time. As described in the third aspect, the intelligent terminal is communicatively connected to the data acquisition device. Specifically, the intelligent terminal is used to acquire the initial power condition data in the data acquisition device and to identify and warn of abnormal operating conditions of the electromagnetic pulse filter based on the initial power condition data. The intelligent terminal is further used to acquire the output power condition data from the data acquisition device, and to evaluate the filtering effect of the electromagnetic pulse filter in combination with the output power condition data to obtain the evaluation result.

[0016] In one specific implementation, the data acquisition device includes a current acquisition unit and a voltage acquisition unit. The current acquisition unit is used to acquire the initial current data at the input terminal of the electromagnetic pulse filter or the output current data at the output terminal of the electromagnetic pulse filter. A protection sub-unit is provided before each current acquisition unit. The input terminal of the protection sub-unit is connected to the power output terminal, and the output terminal is connected to the input terminal of the current acquisition unit. The protection sub-circuit includes several voltage divider resistors and an operational amplifier, which are used to adjust the scaling ratio of the current signal strength input to the current acquisition unit by adjusting the resistance value of the voltage divider resistors and the amplification factor of the operational amplifier, so as to protect the current acquisition unit. The voltage acquisition unit is used to acquire the initial voltage data at the input terminal of the electromagnetic pulse filter or the output voltage data at the output terminal of the electromagnetic pulse filter. An error compensation subunit is provided after each voltage acquisition unit. The input terminal of the error compensation subunit is connected to the output terminal of the voltage acquisition unit. The error compensation subunit includes a temperature sensor and a compensation operational amplifier. The error compensation subunit is used to monitor and acquire real-time temperature parameters through the temperature sensor, and to compensate and adjust the voltage data in the voltage acquisition subunit using the compensation operational amplifier and the real-time temperature parameters to obtain the initial voltage data or the output voltage data.

[0017] Fifthly, this application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement a monitoring method for a filter as described in the first aspect.

[0018] In summary, this application includes at least one of the following beneficial technical effects: 1. To address the shortcomings of traditional filters in "inability to monitor in real time," this application achieves real-time capture and hierarchical judgment of abnormal operating conditions such as voltage surges and current inrushes by periodically collecting input power supply operating condition data and combining it with a retention and observation mechanism. Among them, the retention and observation mechanism effectively distinguishes between short-term fluctuations and gradual degradation by continuously monitoring the relative fluctuation rate and global trend of the data, effectively avoiding misjudgment and omission of traditional methods, significantly improving the accuracy and timeliness of abnormal operating condition identification, and providing a reliable data foundation for filter performance evaluation.

[0019] 2. This application effectively improves the lag problem of traditional filters relying on periodic manual inspection, transforming the filter's operating status from a "black box operation" to visualized, digital, and real-time monitoring, providing data support for early fault diagnosis.

[0020] 3. This application constructs multi-dimensional evaluation indicators (harmonic suppression rate, insertion loss, and residual pulse suppression), and dynamically adjusts the evaluation threshold in conjunction with environmental impact factors, thereby realizing a quantitative evaluation of the filtering effect. In addition, this application, through the linkage of a preset parameter optimization strategy library and hardware adjustable components (such as programmable capacitor arrays and digital potentiometers), can automatically generate and execute optimization parameters, forming a closed-loop mechanism of "evaluation-adjustment-verification". This enables the filter to dynamically optimize its performance according to real-time operating conditions, solving the limitations of traditional passive filtering that relies on static hardware, and improving its adaptability and stability in complex environments. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of a monitoring system for a filter according to an embodiment of this application.

[0022] Figure 2 This is a schematic diagram of the circuit structure of a data acquisition device according to an embodiment of this application.

[0023] Figure 3 This is a schematic diagram of the circuit structure of an absorber unit according to an embodiment of this application.

[0024] Figure 4 This is a schematic diagram of the circuit structure of a filter subunit according to an embodiment of this application.

[0025] Figure 5 This is a schematic diagram of the overall circuit structure of a monitoring system for a filter according to an embodiment of this application.

[0026] Figure 6 This is a flowchart illustrating a monitoring method for a filter according to another embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0028] The following describes in further detail, with reference to the accompanying drawings, an embodiment of a monitoring method, system, and electromagnetic pulse protection device for a filter according to this application.

[0029] One embodiment of this application discloses a monitoring system for a filter.

[0030] Reference Figure 1A monitoring system for a filter includes a data acquisition device and an electromagnetic pulse (EMP) shielding device, wherein the EMP shielding device includes an EMP shielding filter and an intelligent terminal communicatively connected to the EMP shielding filter. An electromagnetic pulse (EMP) filter is installed at the power input terminal to suppress EMP interference and filter harmonics in the input power supply based on pre-stored initial filtering parameters. Two data acquisition devices are installed, one at the input end and the other at the output end of the electromagnetic pulse filter. They are used to acquire the initial power condition data at the input end of the electromagnetic pulse filter and the output power condition data at the output end of the electromagnetic pulse filter in real time.

[0031] It should be noted that, referring to Figure 2 The data acquisition device in this embodiment specifically includes a current acquisition unit and a voltage acquisition unit. These units work together to achieve highly reliable signal acquisition, as detailed below: The current acquisition unit specifically includes two current acquisition sub-units. One current acquisition sub-unit is located at the very front of the power input (i.e., between the power supply and the electromagnetic pulse filter), and the other current acquisition sub-unit is located after the output of the electromagnetic pulse filter. The current acquisition sub-unit is used to acquire the initial current data at the input of the electromagnetic pulse filter or the output current data at the output of the electromagnetic pulse filter. The current acquisition sub-unit is specifically a high-precision current sensor. In this embodiment, the current sensor adopts a closed-loop current sensor based on the principle of electromagnetic induction. This closed-loop current sensor integrates a feedback winding and a high-permeability magnetic core. By detecting the magnetic field generated by the primary current in real time, and using the feedback winding to generate a reverse magnetic field for dynamic balance, a zero-flux detection state is formed, thereby linearly converting the input current into a low-voltage signal (such as a 1V / A proportional output) to obtain the initial current data. This is existing technology and will not be described in detail here.

[0032] To protect the current acquisition unit and prevent damage from excessive input current from the power supply, the current acquisition unit also includes two protection sub-units. These protection sub-units are located before each current acquisition sub-unit. Specifically, each protection sub-unit is a signal scaling circuit. It utilizes a voltage divider resistor network and an operational amplifier to build a proportional scaling circuit. This circuit precisely controls the scaling ratio of the input signal strength corresponding to the current directly output from the power supply by adjusting the resistor values ​​and the amplification factor of the operational amplifier. For example, when the detected current signal exceeds the sensor's rated range, the protection sub-unit will automatically switch the resistor range or adjust the amplification factor to stabilize the output signal within the safe input range of the analog-to-digital converter (ADC) (e.g., 0-5V). This effectively ensures that the current acquisition sub-unit will not be damaged by the impact when faced with large signals corresponding to excessive current. This is existing technology and will not be elaborated further here.

[0033] The voltage acquisition unit specifically includes two voltage acquisition subunits. One voltage acquisition subunit is located at the very beginning of the power input (i.e., between the power supply and the electromagnetic pulse (EMP) filter), and the other voltage acquisition subunit is located after the output of the EMP filter. The voltage acquisition subunit is used to acquire voltage data at the input or output of the EMP filter. Specifically, the voltage acquisition subunit is a voltage acquisition device. In this embodiment, the voltage acquisition device adopts a resistor divider structure, which can reduce the input power supply voltage proportionally to a range that is easy to measure by using precise resistors to obtain voltage data. Specifically, the voltage acquisition subunit is used to acquire the initial voltage data at the input of the EMP filter or the output voltage data at the output of the EMP filter. Furthermore, considering that voltage data acquisition is easily affected by changes in ambient temperature, in this embodiment, the voltage acquisition unit also includes an error compensation subunit, which is placed after each voltage acquisition subunit. The error compensation subunit is specifically a circuit composed of components such as a temperature sensor and a compensation operational amplifier, used to monitor and obtain real-time temperature parameters, and to compensate and adjust the voltage data in the voltage acquisition subunit according to the real-time temperature parameters and the compensation operational amplifier, so as to obtain the initial voltage data and the output voltage data.

[0034] In summary, the data acquisition device achieves high-precision and high-reliability acquisition of the input / output power signals of the electromagnetic pulse filter through the coordinated operation of the current / voltage acquisition subunit, protection subunit, and error compensation subunit at both the input and output ends. The specific workflow is as follows: Input current acquisition: The raw current signal from the power input first flows through the protection subunit (signal scaling circuit) located between the power supply and the filter. This circuit monitors the current signal strength in real time through a proportional scaling module composed of a voltage divider resistor network and an operational amplifier. If the signal corresponding to the input current exceeds the rated range of the closed-loop current sensor (e.g., output voltage > 5V when > 50A), the protection subunit automatically switches the resistance level or adjusts the amplification factor (e.g., switching the 1V / A proportional output to 0.5V / A) to stabilize the signal amplitude within the safe input range (0-5V) of the analog-to-digital converter (ADC), thus preventing large current signals from damaging the downstream sensor. The protected current signal enters the input current acquisition subunit (closed-loop current sensor). The sensor uses the dynamic balance mechanism (zero flux detection) between the internal feedback winding and the high permeability magnetic core to linearly convert the primary current into a low voltage signal (e.g., 10A current corresponds to 10V output, which is scaled to 1V) to generate initial current data, which truly reflects the characteristics of the unfiltered power supply input current (e.g., harmonic distortion, pulse spikes).

[0035] Output current acquisition: The output current signal, after being processed by the electromagnetic pulse filter, flows through the current acquisition subunit at the output end. It adopts the same closed-loop current sensor and protection subunit design as the input end, and acquires the filtered output current data (such as residual harmonic current and current fluctuations after pulse suppression) in real time. It also ensures safe signal input through the same signal scaling mechanism.

[0036] Input voltage acquisition: The original voltage signal of the power input is connected to the input voltage acquisition subunit (resistive voltage divider voltage acquisition unit). The high voltage (e.g., 220VAC) is proportionally reduced to a safe measurement range (e.g., 2.2V) through a precision resistor (e.g., a 100:1 voltage divider ratio). After being buffered and isolated by an operational amplifier, the initial voltage data is output, preserving the waveform details of the original power supply voltage (e.g., voltage surge, harmonic superposition).

[0037] The acquired voltage signal enters the error compensation subunit. The temperature sensor monitors the ambient temperature in real time (accuracy ±0.5℃). If the temperature change causes the temperature coefficient of the voltage divider resistor to drift (e.g., >5ppm / ℃), the compensation operational amplifier generates a reverse compensation voltage (e.g., a -0.01V compensation signal is superimposed when the temperature rises by 10℃) according to the preset temperature-resistance deviation model. This corrects the influence of temperature on the voltage acquisition accuracy and outputs the final calibrated initial voltage data.

[0038] Output voltage acquisition: After the filtered output voltage signal is divided by the output voltage acquisition subunit, it is also corrected for temperature drift by the error compensation subunit to generate calibrated output voltage data, which accurately reflects the quality of the filtered voltage (such as ripple amplitude and residual pulse voltage).

[0039] The electromagnetic pulse protection filter specifically includes an absorption subunit, a filtering subunit, and a signal transmission subunit; Among them, reference Figure 3 The absorption subunit includes a circuit board, a varistor, a transient suppression diode, and a discharge tube. The varistor and transient suppression diode are both mounted on the circuit board and connected by lines on the printed circuit board (PCB). The absorption subunit is connected in series at the power input terminal, located after the data acquisition device, and is used to process strong electromagnetic pulse interference in the input power supply in the first instance. When the power supply outputs a momentary high-energy strong electromagnetic pulse, the resistance value of the varistor will drop sharply under the action of the strong electromagnetic pulse voltage, dissipating the strong electromagnetic pulse energy through itself, playing a preliminary role in suppressing strong electromagnetic pulses. After the resistance of the varistor drops, the transient suppression diode further clips and stabilizes the residual strong electromagnetic pulse, limiting the strong electromagnetic pulse voltage within a safe range and protecting the subsequent circuits.

[0040] Reference Figure 4 In this embodiment, the filtering subunit is composed of several inductors and capacitors, specifically an LC filter circuit formed by interleaving several π-type filter circuits and T-type filter circuits. The inductors are made of high-permeability magnetic cores, and the capacitors are a combination of ceramic capacitors and electrolytic capacitors to meet the filtering requirements of different frequency bands. The filtering subunit is specifically set before the absorption subunit and the signal transmission subunit. The power supply is connected through the inductors and capacitors through the circuit according to the above-described filtering circuit structure to form a complete filtering network. When the power supply signal (including the initial current data and initial voltage data mentioned above) enters the filter sub-unit, for low-frequency interference signals, the inductor will block the low-frequency signal from passing through due to its high inductive reactance, so that most of its energy is consumed in the inductor; while for high-frequency interference signals, the capacitor will bypass the high-frequency signal to ground due to its low capacitive reactance, thereby effectively suppressing interference signals of different frequencies and making the output unit signal purer.

[0041] The signal transmission subunit specifically includes a photoelectric converter transmitter, an optical fiber, a photoelectric converter receiver, and related signal conditioning circuitry. The photoelectric converter transmitter converts electrical signals into optical signals, the photoelectric converter receiver converts the optical signals back into electrical signals, and the signal conditioning circuitry amplifies and shapes the signals before and after conversion. The optical fiber serves as the optical signal transmission medium, connecting the photoelectric converter transmitter and the photoelectric converter receiver. These are all existing technologies and will not be described in detail here. In this embodiment, the photoelectric converter transmitter is connected to the current acquisition subunit and voltage acquisition subunit in the data acquisition device to receive the acquired electrical signals (including initial current data and initial voltage data) and convert them into optical signals. The photoelectric converter receiver is connected to the information processing subcircuit to convert the optical signals from the photoelectric converter transmitter back into electrical signals and transmit the converted electrical signals to the smart terminal. When the electrical signal output by the data acquisition device first enters the photoelectric converter transmitter, the electrical signal is first converted into an optical signal by a light-emitting diode (LED) or a laser diode (LD). Then, the optical signal, due to its immunity to electromagnetic interference, is transmitted stably in the optical fiber. After reaching the photoelectric converter receiver, it is converted back into an electrical signal by a photodiode (PD). After being processed by the signal conditioning circuit, the processed electrical signal is transmitted to the smart terminal. For a detailed and complete signal processing procedure, please refer to [link to relevant documentation]. Figure 5 .

[0042] The intelligent terminal is located at the core control position of the entire electromagnetic pulse filtering equipment. It is closely connected to all sub-units of the electromagnetic pulse filter through various interfaces to realize the reception, processing and transmission of control commands. In addition, the smart terminal is also connected to the data acquisition equipment to acquire the initial power condition data (including initial power data and initial voltage data) and output power condition data (including output power data and output voltage data) from the data acquisition equipment. The smart terminal is also used to identify and warn of abnormal operating conditions based on the initial power condition data, and to evaluate the filtering effect of the electromagnetic pulse filter in combination with the output power condition data to obtain the evaluation results. Then, the optimization parameters are obtained based on the evaluation results, and finally, the initial filtering parameters in the electromagnetic pulse filter are adaptively adjusted based on the optimization parameters.

[0043] The intelligent terminal includes a processor and a memory for storing at least one instruction, at least one program, code set, or instruction set; the processor performs the steps of a monitoring method for a filter when executing at least one instruction, at least one program, code set, or instruction set.

[0044] The implementation of the method will be explained in detail below with reference to the above system: Reference Figure 6 Another embodiment of this application provides a monitoring method for a filter, comprising: S100 periodically acquires the initial power condition data of the input terminal of the electromagnetic pulse protection device; The initial power supply condition data includes initial current data and initial voltage data. S200 determines whether there is an abnormal operating condition based on the initial power supply condition data and obtains the first judgment result; The first judgment result includes one of the following: the existence of abnormal operating conditions, the absence of abnormal operating conditions, and the existence of abnormal operating condition risk. The existence of abnormal operating condition risk means that although the initial power supply operating condition data has not reached a clear abnormal standard, it is close to the critical value or has shown some abnormal trends. For example, if the current data rises continuously in a short period of time and approaches the overload threshold, it is judged as having an abnormal operating condition risk. Specifically, in S200, in the process of judging whether the electromagnetic pulse filter is in an abnormal operating condition, it is necessary to pre-set the judgment standard for abnormal operating conditions. The judgment standard can be set based on the normal operating range of the power supply, historical data statistics, and industry standards. In this embodiment, the normal current range is set to 0-10A and the normal voltage range is set to 210-230V. When the initial current data exceeds 10A or is lower than 0A, or the initial voltage data exceeds 230V or is lower than 210V, it is directly judged as having an abnormal operating condition. The abnormal operating condition types in this embodiment include, but are not limited to, voltage surge, voltage drop, current overload, and high-frequency electromagnetic pulse interference. This embodiment can identify different types of abnormal operating conditions by performing time-frequency domain analysis (such as fast Fourier transform, wavelet analysis, etc.) on the initial current data and initial voltage data. For example, if a sudden abnormal increase in high-frequency components is found in the frequency domain analysis and the increase pattern is consistent with the historical interference characteristics, it is determined that there is high-frequency electromagnetic pulse interference. This is existing technology and will not be described in detail here.

[0045] S300, if the first judgment result is that there is a risk of abnormal working conditions, the detention and observation mechanism is triggered to obtain the second judgment result; The second judgment result includes either the existence of an abnormal operating condition or the absence of an abnormal operating condition; specifically, S300 includes: S310 continuously acquires the initial power condition data corresponding to the first judgment result in real time within a preset period of time; Among them, the initial power supply condition data is one of the initial voltage data and the initial current data; S320 obtains its relative fluctuation rate over a preset period of time based on the initial power supply condition data; The relative fluctuation rate has positive and negative values, representing the direction of change of the initial power supply operating data over a preset period of time. A positive value represents an increase in current / voltage, and a negative value represents a decrease in current / voltage. The formula for calculating the relative fluctuation rate is: ; in, This indicates the relative rate of fluctuation of initial power supply condition data over a period of time; This represents the last initial power condition data acquired within a certain period of time; This represents the first initial power condition data acquired within a certain period of time. Indicates the duration of a period of time.

[0046] S330 determines the global trend of data change based on all initial power condition data over a period of time and obtains the actual rate of change based on the global trend and relative fluctuation rate. The overall trend includes fluctuations, increases, decreases, and overall stagnation; specifically, S330 includes the following steps S331-S333: S331, if the initial power condition data continues to increase over a preset period of time, the global trend is increasing; if the initial power condition data continues to decrease over a preset period of time, the global trend is decreasing. S332, when the global trend is increasing or decreasing, the relative fluctuation rate in S320 is directly used as the actual rate of change; S333, otherwise, trigger the data trend fitting and discrimination mechanism to obtain the global change trend and obtain the actual change rate based on the global change trend and the relative fluctuation rate; Specifically, S333 includes: S3331: Input several initial power supply condition data over a period of time and their corresponding time points into a preset curve fitting algorithm model to obtain the fitted curve. ; Among them, the fitted curve The curve fitting algorithm model is used to reflect the changing trend of initial power supply condition data over a preset period of time. It is based on the least squares method, which is an existing technology and will not be described in detail here.

[0047] S3332, Calculate the fitted curve Average operating condition data over a period of time; Among them, the average operating condition data is the fitted curve over a period of time. The average value of all consecutive initial power supply operating condition data; the formula for calculating this average operating condition data is: ; in, Represents the fitted curve In the interval Average operating condition data.

[0048] S3333, calculate the sum of variances between all initial power condition data and average condition data acquired within a certain period of time, and compare the sum of variances with a preset fluctuation threshold to obtain the global trend of change. Specifically, if the sum of variances is greater than the fluctuation threshold, the overall trend is oscillation; if the sum of variances is less than or equal to the fluctuation threshold, the overall trend is relatively flat. In this embodiment, the fluctuation threshold is taken as 1. The formula for calculating the sum of variances is: ; in, Indicates the first time obtained within a certain period of time Initial power condition data; This indicates the total number of initial power condition data points acquired within a given period. It represents the sum of variances between all initial power supply condition data and the average condition data over a period of time.

[0049] S3334 If the overall trend of change is relatively flat, then the relative fluctuation speed in S320 will be directly used as the actual rate of change.

[0050] S3335, if the global trend is oscillation, then the speed value for correction is obtained based on several initial power supply condition data over a period of time, and the speed value for correction is substituted into a preset absolute change rate calculation formula to obtain the actual change rate. The speed value used for correction is derived from a fitted curve based on several initial power supply condition data over a period of time. The calculation is obtained by calculation, and the formula is as follows: ; in, Represents the fitted curve In the interval Average operating condition data in the data; The speed value used to correct the initial power supply condition data over a period of time; The specific formula for calculating the absolute rate of change in S3335 is as follows: ; ; in, Indicates the actual rate of change; express Weight parameters; express The weighting parameters in this embodiment; With 0.7, Take 0.3 as an example.

[0051] S340, compare the actual rate of change with the preset speed threshold to obtain a second judgment result; Wherein, if the initial power supply condition data is the initial current data, the speed threshold in this embodiment is 5A / second; if the initial power supply condition data is the initial voltage data, the first speed threshold in this embodiment is 10V / second.

[0052] S400: When the first or second judgment result indicates the existence of an abnormal operating condition, determine the abnormal operating condition data and acquire the output power condition data of the output terminal of the electromagnetic pulse protection device in real time. The abnormal operating condition data includes the duration of the abnormality, the current operating curve over time, the voltage operating curve over time, and the environmental parameters at the time of the abnormality. Both the current and voltage operating curves include several peak and trough values ​​of the voltage / current under the current abnormal operating condition. In this embodiment, the environmental parameters specifically refer to real-time temperature parameters. The output power supply operating condition data includes output current data and output voltage data. Specifically, the method for determining the abnormal operating condition data is as follows: The duration of an anomaly is determined by marking the corresponding anomaly start time and the current time: When the initial power condition data (initial current data or initial voltage data) is detected to exceed the normal range for the first time, this moment is immediately recorded as the anomaly start time; each anomaly duration corresponds to an anomaly start time. If multiple anomaly start times are close together, such as three anomaly start times being marked within 5 minutes, and a first or second judgment result of an anomaly is obtained at the third mark (i.e., the current time), then the time point of the first occurrence of the anomaly is taken as the anomaly start time for that anomaly duration; specifically, the anomaly duration is equal to the current time minus the anomaly start time; for example, if the anomaly start time is 10:00:00 and the current time is 10:00:15, then the anomaly detected so far has lasted for 15 seconds. To accurately depict the changes in current and voltage over time, initial current data needs to be collected at an appropriate frequency. The collection frequency should be determined based on the characteristics of the power supply system and possible abnormal situations. In this embodiment, the collection frequency is a preset value. For example, for rapidly changing electromagnetic pulse interference, a higher collection frequency (e.g., 1000 times per second) is required; for relatively slow current fluctuations, the collection frequency can be appropriately reduced (e.g., 10 times per second). During the duration of abnormal operating conditions, the intelligent terminal continuously records the initial current data according to the set collection frequency and stores the data in the memory. Each data point should include the collection time and the corresponding current / voltage value. By observing the shape and trend of the curve, one can intuitively understand the changes in current during abnormal operating conditions, such as whether the current suddenly increases or decreases, whether there are periodic fluctuations, and the fluctuations in voltage under abnormal operating conditions, such as whether there are sudden voltage rises, falls, or oscillations.

[0053] S500 evaluates the filtering effect of the electromagnetic pulse filter based on output power supply condition data and abnormal condition data, and obtains the evaluation results. The evaluation results include those that severely affect the filtering effect, those that slightly affect the filtering effect, and those that do not affect the filtering effect; specifically, S500 includes: S510 obtains several different evaluation indicators based on output power condition data and abnormal condition data. The evaluation metrics include harmonic suppression rate, insertion loss, and pulse suppression residual; specifically, S510 includes: S511 obtains the current harmonic suppression rate based on the initial current data, output current data, initial voltage data, and output voltage data; In this embodiment, the amplitude of each harmonic in the input and output signals is calculated by the Fast Fourier Transform (FFT) algorithm, and the amplitude of each harmonic at the output end is compared with the corresponding harmonic amplitude at the input end to obtain the harmonic suppression rate; the harmonic suppression rate is used to measure the ability of the electromagnetic pulse filter to suppress harmonic components in the power supply. S512 calculates the input signal power based on the input power supply condition data, calculates the output signal power based on the output power supply condition data, and obtains the insertion loss based on the input signal power and the output signal power. The formula for calculating insertion loss is as follows: ; Among them, P in P is the input signal power. out 1 is the output signal power; IL is the insertion loss, which reflects the degree of attenuation of the received electrical signal by the current electromagnetic pulse filter.

[0054] S513 obtains the pulse suppression residual amount based on the pulse peak value in the abnormal duration, output current data, and output voltage data; The calculation of pulse suppression residual requires first identifying the maximum current value during electromagnetic pulse interference by traversing the acquired output current data sequence. This maximum value is the pulse peak value of the output current. For example, during an electromagnetic pulse interference event, the acquired output current data are 1.2A, 1.5A, 2.3A, 1.8A, etc. After comparison, 2.3A is found to be the maximum value, so the pulse peak value of the output current under this interference is 2.3A. Then, the pulse peak value of the output voltage is obtained using the same method. Finally, the current peak value, voltage peak value, and abnormal duration are weighted according to a certain weight to calculate the pulse suppression residual value. The pulse suppression residual value is used to evaluate the suppression effect of the electromagnetic pulse filter on electromagnetic pulses.

[0055] S520, environmental impact factors are obtained based on environmental parameters; The environmental impact factor reflects the objective influence of ambient temperature on the performance of the electromagnetic pulse (EMP) filter. Specifically, the environmental impact factor can be calculated by establishing a correlation model between real-time temperature parameters and filter performance: performance data such as harmonic suppression rate and insertion loss of the filter are collected in advance at different temperatures to construct a temperature-performance curve; after obtaining the real-time temperature parameters at the moment when the current abnormal operating condition occurs, the environmental impact factor is calculated based on the slope of the subsequent operating curve and the temperature change trend. If the temperature rises sharply in a short period of time and exceeds the normal operating temperature range of the filter, the environmental impact factor increases, indicating that the negative impact of temperature on the filter performance is enhanced.

[0056] S530, the assessment results are obtained based on environmental impact factors and assessment indicators; Specifically, the S530 includes: S531, dynamically corrects the harmonic suppression rate threshold, insertion loss threshold and pulse suppression residual threshold based on environmental impact factors; The larger the environmental impact factor, the lower the harmonic suppression rate threshold and the pulse suppression residual threshold, and the higher the insertion loss threshold, so as to reflect the impact of environmental factors on the filtering effect evaluation criteria.

[0057] S532, if the harmonic suppression rate is lower than the corrected threshold, the insertion loss is higher than the corrected threshold, and the residual pulse suppression is greater than the corrected threshold, then the evaluation result is that the filtering effect is severely affected. If some of the above indicators deviate from the threshold but not all exceed the limit, the evaluation result is that the filtering effect is slightly affected. If all indicators meet the revised threshold requirements, the evaluation result is that the filtering effect has not been affected.

[0058] It should be noted that the evaluation results in S532 can be corrected based on evaluation results from multiple time periods to avoid misjudging the filtering effect under short-term abnormal operating conditions. This is achieved through the following mechanism: The system presets a time window (e.g., the last 5 monitoring periods) in the smart terminal to store historical evaluation results. When the evaluation results for a certain period show "the filtering effect is severely affected" or "the filtering effect is slightly affected", the system will continuously track the changing trend of evaluation indicators in subsequent periods. If the harmonic suppression rate, insertion loss, and residual pulse suppression gradually approach the corrected threshold range for several consecutive periods (e.g., 3 periods), and the real-time temperature parameters show that the environmental impact factor is decreasing (e.g., the temperature returns to the normal operating temperature range of the filter), then the abnormal state of the current filtering effect is determined to be a transient fluctuation caused by short-term interference, rather than permanent component degradation or circuit failure. At this time, the system corrects the initial evaluation results based on the dynamic changing trend of historical evaluation results. If the number of times "no impact on filtering effect" appears in the last 3 evaluation results is 2 or more, the current evaluation result will be revised to "the filtering effect is slightly affected" or "no impact on filtering effect", depending on the degree of indicator recovery. If the evaluation metrics for all subsequent time periods remain stable within the threshold range, the final evaluation result is determined as "no impact on the filtering effect".

[0059] For example, if a transient electromagnetic pulse interference causes the residual pulse suppression level to exceed the standard at a certain moment, the initial assessment result might be "the filtering effect is severely affected." However, if, during continuous monitoring over the next 10 minutes, the residual pulse suppression level gradually decreases to the normal range, and the harmonic suppression rate and insertion loss remain stable, the system determines that the anomaly is a transient response caused by short-term interference, rather than a substantial degradation of filter performance. Therefore, the assessment result is corrected to "no impact on the filtering effect." This time-series-based dynamic correction mechanism effectively distinguishes the impact of short-term interference from long-term degradation on the filtering effect, avoiding the misjudgment problem caused by a single instance of exceeding the standard in traditional assessment methods, and improving the robustness and accuracy of the monitoring system.

[0060] S600, the optimized parameters are obtained based on several evaluation results corresponding to multiple consecutive time periods; The smart terminal has a built-in preset parameter optimization strategy library. This strategy library is built based on the characteristics of adjustable hardware components of the filter (such as programmable capacitor arrays and digital potentiometers) and historical operating data, and includes parameter adjustment rules corresponding to different evaluation results. When the final evaluation result is "the filtering effect is severely affected", a deep optimization strategy is triggered: if the harmonic suppression rate is lower than the threshold, the optimal capacitor / inductor combination for the corresponding frequency band is retrieved from the strategy library based on the current harmonic exceeding the standard (e.g., the 3rd harmonic is the main one) (e.g., increasing the capacitor by 10μF to enhance low-frequency harmonic suppression); if the residual pulse suppression exceeds the standard, an instruction to adjust the parameters of the electromagnetic pulse absorption device is generated (e.g., increasing the clamping voltage level of the TVS diode). When the final evaluation result is "the filtering effect is slightly affected", an adaptive fine-tuning strategy is executed: the deviation between the evaluation index and the threshold is calculated by fuzzy logic algorithm, and fine-tuning parameters are generated proportionally (e.g., when the insertion loss is 1dB higher than the threshold, the resistance of the digital potentiometer is fine-tuned to increase the inductance value by 5%). When the final evaluation result is "no impact on the filtering effect", the current filtering parameters are maintained, and only abnormal operating condition data is recorded for updating the strategy library.

[0061] S700 adaptively adjusts the preset initial filtering parameters in the electromagnetic pulse protection filter according to the optimization parameters to obtain the optimal filtering parameters, and realizes real-time optimization control of the electromagnetic pulse protection filter based on the optimal filtering parameters. The adjustable parameter module (such as a programmable LC unit) inside the electromagnetic pulse filter receives the optimization parameters sent by the smart terminal and performs adjustment operations through a hardware interface. For programmable capacitor arrays, the switching state of specific capacitor combinations is optimized by using parameters (such as binary code "101" to indicate the connection of 10nF+1nF capacitors), and the capacitor connection state is switched by a relay or MOSFET controlled by the drive circuit. For digital potentiometers, the optimization parameter is the resistance adjustment code (such as the 4096-level resistance value corresponding to a 12-bit ADC), which is sent to the potentiometer chip via the SPI bus to adjust the inductor matching resistance value in real time to optimize the impedance characteristics. After adjustment, the intelligent terminal enters the parameter verification stage: within a preset verification time window (e.g., 30 seconds), it continuously monitors the output power supply operating condition data, calculates the adjusted harmonic suppression rate, insertion loss, and other indicators. If the evaluation results do not meet expectations (e.g., the harmonic suppression rate is improved by less than 20%), iterative optimization is initiated—the parameters are adjusted a second time based on the gradient descent algorithm until the indicators meet the threshold requirements or the maximum number of adjustments (e.g., 5 times) is reached, triggering a manual intervention prompt. Through the closed-loop mechanism of "evaluation-adjustment-verification", the optimal filtering parameters adapted to the real-time operating conditions are finally determined, realizing the dynamic optimization of filter performance.

[0062] Based on the same inventive concept described above, this application also discloses an electromagnetic pulse protection device, which includes a memory and a processor. The memory stores at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement a monitoring method for a filter as provided in the above method embodiments.

[0063] Based on the same inventive concept described above, this application also discloses a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set can be loaded and executed by a processor to implement the monitoring method for a filter provided in the above method embodiments.

[0064] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0065] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code.

[0066] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A monitoring method for a filter, characterized in that, include: Periodically acquire initial power condition data at the input of the electromagnetic pulse protection device; Based on the initial power condition data, determine whether there is an abnormal condition and obtain a first determination result; If the first judgment result indicates that there is a risk of abnormal working conditions, the observation and detention mechanism is triggered to obtain the second judgment result; When the first judgment result or the second judgment result indicates the existence of an abnormal operating condition, the abnormal operating condition data is determined, and the output power condition data of the output terminal of the anti-electromagnetic pulse device is acquired in real time. The filtering effect of the electromagnetic pulse filter is evaluated based on the output power supply operating condition data and the abnormal operating condition data, and the evaluation results are obtained. The optimization parameters are obtained based on several evaluation results corresponding to multiple consecutive time periods. The initial filtering parameters preset in the electromagnetic pulse protection filter are adaptively adjusted according to the optimization parameters to obtain the optimal filtering parameters, and the real-time optimization control of the electromagnetic pulse protection filter is realized according to the optimal filtering parameters. The detention and observation mechanism triggered when the first judgment result indicates the existence of an abnormal operating condition risk includes: Within a preset time period, the initial power condition data corresponding to the first judgment result is continuously acquired in real time. The relative fluctuation rate of the initial power condition data over the specified time period is obtained based on the initial power condition data. The global trend of the initial power condition data is determined based on all the initial power condition data within the specified time period, and the actual rate of change is obtained based on the global trend and the relative fluctuation rate. The actual rate of change is compared with a preset speed threshold to obtain a second judgment result.

2. The monitoring method for a filter according to claim 1, characterized in that, The step of determining the global change trend of the data based on all the initial power condition data within the specified time period, and obtaining the actual change rate based on the global change trend and the relative fluctuation rate, includes: If the initial power condition data continues to increase over time during the specified period, then the global trend is determined to be increasing. If the initial power condition data continues to decrease over time during the specified period, then the global trend is determined to be decreasing. When the global trend is increasing or decreasing, the relative fluctuation rate is directly taken as the actual rate of change. Otherwise, the data trend fitting and discrimination mechanism is triggered to obtain the global change trend, and the actual change rate is obtained based on the global change trend and the relative fluctuation rate; The data trend fitting and discrimination mechanism includes: Input several initial power supply condition data within the time period and their corresponding time points into a preset curve fitting algorithm model to obtain the fitting curve E(t). Calculate the average operating data of the fitted curve E(t) within the time interval of the time period; Calculate the sum of variances between all the initial power condition data and the average condition data acquired within the specified time period, and compare the sum of variances with a preset fluctuation threshold to obtain the global trend.

3. The monitoring method for a filter according to claim 2, characterized in that, The process of obtaining the actual rate of change based on the global trend and the relative fluctuation rate includes: If the global change trend is generally flat, then the relative fluctuation rate is directly taken as the actual change rate. If the global change trend is oscillation, then the correction speed value is obtained based on several initial power condition data within the time period, and the correction speed value is substituted into a preset absolute change speed calculation formula to obtain the actual change speed. The formula for calculating the speed value used for correction is as follows: Where t0 represents the duration of a preset time period; V represents the average operating data of the fitted curve E(t) in the interval [0, t0]; 纠偏 The speed value used to correct the initial power supply condition data over a period of time; The formula for calculating the absolute rate of change is as follows: V0 ’ = w1V0 + w2V 纠偏 ; w1 + w2 = 1; Among them, V0 ’ V0 represents the actual rate of change; w1 represents the relative fluctuation rate of the initial power supply condition data over a period of time; w2 represents the weighting parameter of V0; w1 represents the weighting parameter of V0. 纠偏 The weight parameters.

4. The monitoring method for a filter according to claim 1, characterized in that, The output power condition data includes output voltage data and output current data; the initial power condition data includes initial voltage data and initial current data; the abnormal condition data includes the duration of the abnormality and environmental parameters; the quality evaluation of the filtering effect of the electromagnetic pulse filter based on the output power condition data yields the following evaluation results: The current harmonic suppression rate is obtained based on the initial current data, the output current data, the initial voltage data, and the output voltage data. The input signal power is calculated based on the initial current data and the initial voltage data, the output signal power is calculated based on the output current data and the output voltage data, and the insertion loss is obtained based on the input signal power and the output signal power. The residual pulse suppression amount is obtained based on the pulse peak value in the abnormal duration, output current data, and output voltage data. The environmental impact factor is obtained based on the environmental parameters. The harmonic suppression rate threshold, insertion loss threshold, and pulse suppression residual threshold are dynamically corrected based on the environmental impact factors, and the evaluation results are obtained based on the corrected data.

5. A smart terminal, characterized in that, The system includes a memory and a processor, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the monitoring method for a filter as described in any one of claims 1 to 4.

6. An electromagnetic pulse protection device, characterized in that, Includes an electromagnetic pulse filter and the smart terminal as described in claim 5; The electromagnetic pulse filter is used to suppress electromagnetic pulse interference and filter harmonics in the input power supply according to the pre-stored initial filtering parameters. The intelligent terminal is used to identify and warn of abnormal operating conditions of the electromagnetic pulse filter, and to evaluate the filtering effect of the electromagnetic pulse filter to obtain the evaluation result. Then, the initial filtering parameters are adaptively adjusted according to the evaluation result.

7. A monitoring system for a filter, characterized in that, include: Data acquisition devices are respectively installed at the input and output ends of the electromagnetic pulse filter, and are used to acquire the initial power condition data at the input end of the electromagnetic pulse filter and the output power condition data at the output end of the electromagnetic pulse filter in real time. As described in claim 6, the intelligent terminal is communicatively connected to the data acquisition device, and the intelligent terminal is specifically used to acquire the initial power condition data in the data acquisition device, and to identify and warn of abnormal operating conditions of the electromagnetic pulse filter based on the initial power condition data. The intelligent terminal is further used to acquire the output power condition data from the data acquisition device, and to evaluate the filtering effect of the electromagnetic pulse filter in combination with the output power condition data to obtain the evaluation result.

8. The monitoring system for a filter according to claim 7, characterized in that, The data acquisition device includes a current acquisition unit and a voltage acquisition unit. The current acquisition unit is used to acquire the initial current data at the input terminal of the electromagnetic pulse filter or the output current data at the output terminal of the electromagnetic pulse filter. A protection subunit is provided before each current acquisition unit. The input terminal of the protection subunit is connected to the power output terminal, and the output terminal is connected to the input terminal of the current acquisition unit. The protection subunit includes several voltage divider resistors and an operational amplifier, which are used to adjust the scaling ratio of the current signal strength input to the current acquisition unit by adjusting the resistance value of the voltage divider resistors and the amplification factor of the operational amplifier, so as to protect the current acquisition unit. The voltage acquisition unit is used to acquire the initial voltage data at the input terminal of the electromagnetic pulse filter or the output voltage data at the output terminal of the electromagnetic pulse filter; An error compensation subunit is provided after each voltage acquisition unit. The input terminal of the error compensation subunit is connected to the output terminal of the voltage acquisition unit. The error compensation subunit includes a temperature sensor and a compensation operational amplifier. The error compensation subunit is used to monitor and acquire real-time temperature parameters through the temperature sensor, and to compensate and adjust the voltage data in the voltage acquisition unit through the compensation operational amplifier and the real-time temperature parameters to obtain the initial voltage data or the output voltage data.

9. A computer-readable storage medium, characterized in that, The readable storage medium stores at least one instruction, at least one program, code set, or instruction set, which is loaded and executed by a processor to implement the monitoring method for a filter as described in any one of claims 1 to 4.

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