Protection monitoring method and device based on electromagnetic environment imaging and related medium

Abstract

The invention discloses a protection monitoring method and device based on electromagnetic environment imaging and a related medium. The method comprises the following steps: acquiring original electromagnetic signal data of each area in a plant; preprocessing the original electromagnetic signal data to obtain an electromagnetic signal feature vector; comparing the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result; calculating space coordinates of an interference source according to the electromagnetic interference identification result to obtain an electromagnetic interference positioning result; evaluating the electromagnetic sensitivity of the peripheral equipment of the electromagnetic interference positioning result to generate an electromagnetic influence evaluation result; and carrying out joint modeling on the electromagnetic influence evaluation result and pre-input electromagnetic measurement data to obtain an electromagnetic environment imaging result. According to the method, the electromagnetic influence evaluation result obtained through calculation and the electromagnetic measurement data are subjected to joint modeling, so that the electromagnetic environment imaging result is obtained, and therefore, the position of electromagnetic interference can be accurately identified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of safety protection, and particularly relates to a protection monitoring method and device based on electromagnetic environment imaging and related media. BACKGROUND

[0002] In the prior art, artificial inspection and fixed sensor monitoring are commonly used to evaluate the protection measures of a nuclear power plant room. However, such traditional methods generally have slow response speed, limited monitoring coverage, poor data real-time performance and other problems, and are difficult to meet the needs of modern nuclear power plant rooms for fast, accurate and safe monitoring. Especially in the face of emergencies or small changes, the traditional methods lack sufficient sensitivity and intelligent response capability, which may lead to untimely identification of hidden dangers and affect decision-making deployment. In summary, the existing evaluation method for the protection measures of a nuclear power plant room has obvious deficiencies in monitoring accuracy. SUMMARY

[0003] Embodiments of the present application provide a protection monitoring method and device based on electromagnetic environment imaging and related media, aiming to solve the problem of inaccurate identification of electromagnetic interference in a nuclear power plant room in the prior art.

[0004] In a first aspect, the embodiments of the present application provide a plant monitoring method based on electromagnetic environment imaging, comprising:

[0005] obtaining original electromagnetic signal data of each region in the plant;

[0006] preprocessing the original electromagnetic signal data to obtain an electromagnetic signal feature vector;

[0007] comparing the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result;

[0008] calculating the spatial coordinates of the interference source according to the electromagnetic interference identification result to obtain an electromagnetic interference positioning result;

[0009] evaluating the electromagnetic sensitivity of the surrounding equipment of the electromagnetic interference positioning result to generate an electromagnetic influence evaluation result;

[0010] jointly modeling the electromagnetic influence evaluation result and pre-recorded electromagnetic measurement data to obtain an electromagnetic environment imaging result.

[0011] In a second aspect, the embodiments of the present application provide a plant monitoring device based on electromagnetic environment imaging, comprising:

[0012] a data acquisition unit configured to obtain original electromagnetic signal data of each region in the plant;

[0013] a data processing unit configured to preprocess the original electromagnetic signal data to obtain an electromagnetic signal feature vector;

[0014] a data comparison unit configured to compare the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result;

[0015] a positioning calculation unit configured to calculate spatial coordinates of an interference source according to the electromagnetic interference identification result to obtain an electromagnetic interference positioning result;

[0016] an electromagnetic evaluation unit configured to evaluate electromagnetic sensitivity of peripheral equipment of the electromagnetic interference positioning result to generate an electromagnetic influence evaluation result;

[0017] an electromagnetic imaging unit configured to jointly model the electromagnetic influence evaluation result and pre-recorded electromagnetic measurement data to obtain an electromagnetic environment imaging result.

[0018] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the electromagnetic environment imaging-based plant monitoring method of the first aspect when executing the computer program.

[0019] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program is executable on a processor to implement the electromagnetic environment imaging-based plant monitoring method of the first aspect.

[0020] The embodiment of the present application provides an electromagnetic environment imaging-based plant monitoring method, including obtaining original electromagnetic signal data of each region in a plant; pre-processing the original electromagnetic signal data to obtain an electromagnetic signal feature vector; comparing the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result; calculating spatial coordinates of an interference source according to the electromagnetic interference identification result to obtain an electromagnetic interference positioning result; evaluating electromagnetic sensitivity of peripheral equipment of the electromagnetic interference positioning result to generate an electromagnetic influence evaluation result; and jointly modeling the electromagnetic influence evaluation result and pre-recorded electromagnetic measurement data to obtain an electromagnetic environment imaging result. The electromagnetic influence evaluation result obtained by calculation is jointly modeled with the electromagnetic measurement data, so that the electromagnetic environment imaging result is obtained, and thus the position of electromagnetic interference can be accurately identified.

[0021] The embodiment of the present application also provides an electromagnetic environment imaging-based plant monitoring device, a computer device, and a storage medium, which also have the beneficial effects described above. BRIEF DESCRIPTION OF DRAWINGS

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart illustrating a factory monitoring method based on electromagnetic environment imaging, provided in an embodiment of the present invention;

[0024] Figure 2 Amplitude superposition diagram provided for embodiments of the present invention Figure 1 ;

[0025] Figure 3 Amplitude superposition diagram provided for embodiments of the present invention Figure 2 ;

[0026] Figure 4 Amplitude superposition diagram provided for embodiments of the present invention Figure 3 ;

[0027] Figure 5 Amplitude superposition diagram provided for embodiments of the present invention Figure 4 ;

[0028] Figure 6 Amplitude superposition diagram provided for embodiments of the present invention Figure 5 ;

[0029] Figure 7 Amplitude superposition diagram provided for embodiments of the present invention Figure 6 ;

[0030] Figure 8 This is a schematic block diagram of a factory monitoring device based on electromagnetic environment imaging, provided as an embodiment of the present invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0033] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0034] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0035] Please see below. Figure 1 , Figure 1 The flowchart of a factory monitoring method based on electromagnetic environment imaging provided in this embodiment of the invention specifically includes steps S101 to S106.

[0036] S101. Obtain the raw electromagnetic signal data of each area within the factory building;

[0037] S102. Preprocess the original electromagnetic signal data to obtain electromagnetic signal feature vectors;

[0038] S103. The electromagnetic signal feature vector is compared with a preset reference electromagnetic signal to generate an electromagnetic interference identification result.

[0039] S104. Calculate the spatial coordinates of the interference source based on the electromagnetic interference identification results to obtain the electromagnetic interference location results;

[0040] S105. Evaluate the electromagnetic sensitivity of the surrounding equipment based on the electromagnetic interference location results, and generate electromagnetic impact evaluation results.

[0041] S106. The electromagnetic influence assessment results are combined with the pre-recorded electromagnetic measurement data to form a joint model, thereby obtaining the electromagnetic environment imaging results.

[0042] Environmental imaging technology is a monitoring method based on the principle of electromagnetic wave interaction. It primarily acquires and analyzes information generated during the propagation and scattering of electromagnetic waves in space to image and monitor objects, media, or scenes within a target area. This technology can obtain multi-dimensional information related to the target, including parameters such as location, shape, size, and material properties, and boasts advantages such as non-contact operation, visualization, and real-time performance. In the protection assessment of nuclear power plants, electromagnetic environmental imaging technology can be used to monitor radiation leaks, equipment hazards, and environmental changes in real time, providing accurate and comprehensive data support for the formulation and adjustment of protection strategies, and significantly improving the safety level of nuclear power plant operations.

[0043] In step S101, raw electromagnetic signal data from various areas within the plant are acquired. This can be done by deploying highly sensitive electromagnetic field detectors or spectrum analyzers to comprehensively collect electromagnetic signals in key areas of the nuclear power plant. Detector deployment must cover areas within the plant where electromagnetic anomalies may exist, ensuring no blind spots in monitoring. The collected data includes characteristics such as the frequency, amplitude, and direction of the electromagnetic signals, which are used for subsequent analysis.

[0044] In step S102, the original electromagnetic signal data undergoes denoising, filtering, and normalization to remove background interference and extract key time-frequency domain features. By comparing the electromagnetic background data of a nuclear power plant under normal operating conditions, an electromagnetic signal feature vector representing the current signal characteristics is constructed, facilitating subsequent analysis and modeling.

[0045] In step S103, the electromagnetic signal feature vector is compared with the preset normal operating condition reference electromagnetic signal in the electromagnetic environment database in both the time and frequency domains to calculate the difference and identify abnormal signals. A spectrum analysis tool is used to identify the frequency band of the abnormal signal, determine its interference level, and mark the interference type, ultimately generating an electromagnetic interference identification result.

[0046] In step S104, a positioning dataset is constructed by acquiring signal strength and direction data from at least three electromagnetic detectors with known locations. Based on the principle of triangulation, the relative distance between the interference source and each detector point is calculated, and a multivariate spatial positioning model is established using geometric equations. The multivariate spatial positioning model is analyzed using mathematical solution methods, and the positioning accuracy is improved through an error correction algorithm, thereby determining the three-dimensional spatial coordinates of the interference source and obtaining the electromagnetic interference positioning results.

[0047] In step S105, based on the electromagnetic interference location results, historical electromagnetic field measurement data of equipment within the affected area are extracted, and combined with the electromagnetic tolerance indicators of various types of equipment, their current electromagnetic exposure levels are analyzed. Furthermore, an electromagnetic interference suppression scheme is constructed, and electromagnetic compatibility verification is performed using a simulation platform to assess the potential impact of interference on the operating status of critical equipment, thus forming an electromagnetic impact assessment result.

[0048] In step S106, electromagnetic measurement data and electromagnetic impact assessment results from the electromagnetic environment database are used to construct a multi-dimensional data set. The multi-dimensional data set is then imported into the nuclear power plant information model to generate a spatial electromagnetic field distribution map. Based on preset judgment rules, the electromagnetic field intensity in the map is divided into intervals and marked with hot zones. Finally, a three-dimensional imaging map of the electromagnetic environment is output to assist in plant operation and maintenance and safety protection decisions.

[0049] In one embodiment, step S103 includes:

[0050] The electromagnetic signal feature vector is compared with the reference electromagnetic signal in the time-frequency domain to obtain time-frequency domain difference data.

[0051] The interference deviation index is calculated based on the time-frequency domain difference data to obtain the interference signal;

[0052] The interference signal was analyzed using a spectrum analysis tool to obtain the interference analysis results.

[0053] The interference analysis results are stored in the electromagnetic interference identification module, and electromagnetic interference identification results are generated.

[0054] In this embodiment, the electromagnetic signal feature vector is compared with a pre-defined reference electromagnetic signal in both the time and frequency domains to generate corresponding time-frequency domain difference data. The reference electromagnetic signal typically originates from electromagnetic background data accumulated over a long period under normal operating conditions in a nuclear power plant, and is representative and stable. By comparing the frequency distribution, amplitude variation, and energy concentration range of the current feature vector with that of the reference signal, the presence of abnormal signals can be significantly highlighted. Based on the obtained time-frequency domain difference data, an interference deviation index is calculated. This interference deviation index is used to quantify the degree to which the current electromagnetic signal deviates from the normal range, thereby filtering out signal regions that may contain electromagnetic interference and obtaining the interference signal. The calculation process can employ statistical methods such as mean square error, maximum deviation, and energy difference to ensure accurate extraction of the interference signal.

[0055] Furthermore, a spectrum analyzer is used to analyze the frequency components, amplitude, and temporal evolution trends of the interference signal to determine whether it falls within a preset interference frequency band and to classify the signal strength level. The spectrum analysis results effectively reflect the persistence, suddenness, or periodicity of the interference signal, aiding in subsequent classification, identification, and response decisions. The interference analysis results are stored in the electromagnetic interference identification module to generate electromagnetic interference identification results. These results serve as the foundational data for subsequent interference source location, impact assessment, and other processing steps, and can be synchronously updated to the electromagnetic environment database for continuous optimization of the plant's electromagnetic anomaly identification model and interference risk assessment system.

[0056] In one embodiment, the step of using a spectrum analysis tool to perform signal range analysis on the interference signal to obtain interference analysis results includes:

[0057] When the interference signal is determined to belong to the first signal range, a first-level warning is issued;

[0058] When the interference signal is determined to belong to the second signal range, a second-level warning is issued;

[0059] When the interference signal is determined to belong to the third signal range, a third-level warning is issued;

[0060] The peak values ​​of the first signal range, the second signal range, and the third signal range increase sequentially.

[0061] In this embodiment, after electromagnetic interference identification is completed, the extracted interference signal is input into a spectrum analysis tool for processing. The spectrum analysis tool can meticulously analyze the signal's frequency range, peak amplitude, and its time-varying trends, thereby forming a complete interference signal spectrum. Based on preset interference level determination criteria, the peak value of the frequency band to which the interference signal belongs is compared with multi-level classification thresholds to determine its risk level. Specifically:

[0062] When the frequency and amplitude characteristics of the interference signal are within the first signal range, meaning its peak value does not exceed the set low-risk threshold, the system determines that the interference is mild and triggers a first-level warning. This type of interference typically does not have a substantial impact on critical equipment within the plant; it is only recommended to record and continuously monitor it.

[0063] When the characteristics of the interference signal fall within the second signal range—that is, its peak value reaches the medium-risk threshold but does not exceed the high-risk threshold—the system determines that the interference is of medium severity and triggers a level two warning. This type of interference may affect some sensitive equipment; it is recommended that maintenance personnel intervene to inspect and assess the potential risks.

[0064] When the interference signal exceeds the second signal range and enters the third signal range, and its peak value exceeds the set high-risk threshold, the system determines it as severe interference and immediately triggers a third-level warning. This level of warning indicates that the interference is highly destructive or poses a high risk of accidents. The system should automatically issue an alarm notification and initiate response procedures in conjunction with the emergency response mechanism.

[0065] The peak thresholds for the first, second, and third signal ranges mentioned above are set based on historical electromagnetic test data, electromagnetic compatibility standards (such as Class A limits), and the interference tolerance of key equipment in the factory, ensuring that the interference level classification is scientific and reasonable. The actual application test scenarios will be described in detail below.

[0066] In one embodiment, step S104 includes:

[0067] Acquire electromagnetic signal intensity and direction variation data from at least three electromagnetic detectors with known spatial coordinates to construct a localization dataset;

[0068] The relative distance data is obtained by calculating the signal propagation distance between each electromagnetic detector and the interference source corresponding to the electromagnetic interference identification result using the positioning dataset.

[0069] Based on the relative distance data and the spatial coordinates of each of the electromagnetic detectors, a set of geometric equations for spatial triangulation is established to obtain a multivariate spatial equation model for solving the location of the interference source.

[0070] The multivariate spatial equation model is solved, and error correction is performed to generate electromagnetic interference location results.

[0071] In this embodiment, electromagnetic signal intensity and direction variation data collected from at least three electromagnetic detectors deployed within a nuclear power plant building, each with known spatial coordinates, are acquired to construct a raw dataset for localization. The electromagnetic detectors should be deployed at different locations to form a non-collinear electromagnetic spatial distribution, satisfying the triangulation localization conditions. Each electromagnetic detector records the amplitude, phase, and incident direction information of the electromagnetic signal it receives at the moment of interference, forming a localization dataset. Using the signal intensity and direction variations in the localization dataset, combined with the known electromagnetic detector coordinates, the propagation distance between each electromagnetic detector and the target interference source is calculated using a signal propagation model. This propagation distance can be estimated based on an electromagnetic wave attenuation model under specific conditions or based on a time-delay ranging method, forming relative distance data between the interference source and each detector. Based on the aforementioned relative distance data and the spatial coordinates of each detector, a set of geometric equations for spatial triangulation is established. Using a three-dimensional coordinate system, the problem of locating the electromagnetic interference source is transformed into a multivariate spatial equation model containing multiple unknowns, in the form of:

[0072]

[0073] Among them, (x i ,y i ,z i Let d be the spatial coordinates of the i-th detector. i Let (x, y, z) be the relative distance between the detector and the interference source, and let (x, y, z) be the coordinates of the interference source to be solved.

[0074] Furthermore, the aforementioned multivariate spatial equation model is mathematically solved. Common methods include numerical analysis algorithms such as least squares, polynomial fitting, or Newton's iteration to obtain a set of optimal coordinate estimates. To further improve positioning accuracy, an error correction mechanism needs to be introduced. This involves residual analysis and correction based on the measurement errors of each detector, the influence of environmental factors, and historical positioning error data to eliminate error accumulation caused by inconsistent detector sensitivity or signal attenuation. Finally, electromagnetic interference positioning results are generated, namely the spatial coordinate information of the interference source within the nuclear power plant building. This positioning result can be used for subsequent interference source tracking, equipment impact assessment, and response strategy formulation.

[0075] In one embodiment, step S105 includes:

[0076] Extract historical electromagnetic field measurement data of the area corresponding to the electromagnetic interference location result to obtain the electromagnetic field intensity distribution of the corresponding area;

[0077] The electromagnetic field intensity distribution is analyzed to determine the electromagnetic exposure level of the surrounding equipment;

[0078] An electromagnetic interference suppression scheme is constructed based on the electromagnetic exposure level, and the electromagnetic compatibility of the electromagnetic interference suppression scheme is verified using a simulation model to obtain the electromagnetic impact assessment results.

[0079] In this embodiment, historical electromagnetic field measurement data of the area corresponding to the electromagnetic interference location result is extracted. This historical electromagnetic field measurement data is collected periodically or continuously by electromagnetic field detectors deployed inside the nuclear power plant, covering the electromagnetic field intensity, frequency components, and trends of each area. By retrieving and filtering historical data of the interference source location area, the electromagnetic field intensity distribution of the area under different operating conditions is obtained, providing basic data support for subsequent assessment. The electromagnetic field intensity distribution is analyzed to determine the electromagnetic exposure level of surrounding equipment in the area. During the analysis, the electromagnetic susceptibility standards, i.e., electromagnetic tolerance values, of various equipment in the plant's electromagnetic environment database are used to determine whether they are in a potential risk exposure state. For example, for devices such as relays, communication interface modules, and sensors that are sensitive to high-frequency interference, the focus is on their electromagnetic exposure peaks during transient events, and long-term or intermittent electromagnetic over-limit risk points are identified.

[0080] Furthermore, based on the above assessment results (i.e., electromagnetic exposure level), an electromagnetic interference suppression scheme is constructed. The scheme formulation needs to consider the frequency characteristics of the interference source, radiation path, and equipment distribution, and propose reasonable electromagnetic shielding and grounding designs from multiple levels, including equipment level, area level, and system level. For example, filter circuits or shielding covers can be added at the equipment end; local grounding grids or isolation devices can be deployed at the area end; and grounding methods can be optimized at the system level to avoid problems such as resonance or loop interference. Simultaneously, the structural materials and grounding methods of the shielding body must match the interference frequency to ensure the effectiveness of the shielding. Then, an electromagnetic compatibility verification of the above electromagnetic interference suppression scheme is conducted using a simulation model. Electromagnetic simulation software is used to model the internal structure of the plant, cable layout, and equipment configuration, simulating field strength changes under different interference conditions to verify the effectiveness of the proposed scheme in reducing electromagnetic propagation paths and interference effects. After successful verification, a complete electromagnetic impact assessment result can be formed, serving as the basis for subsequent electromagnetic environment imaging and operational optimization.

[0081] In one embodiment, step S106 includes:

[0082] Based on the electromagnetic influence assessment results, extract equipment information within the area to be modeled;

[0083] Electromagnetic measurement data and equipment technical specification data corresponding to the equipment information are retrieved from the electromagnetic environment database to obtain a multi-dimensional data set.

[0084] The multi-dimensional data set is imported into the power plant information model to generate a three-dimensional distribution map of the electromagnetic field;

[0085] Based on preset judgment criteria, the electromagnetic field intensity in the three-dimensional distribution map is divided into intervals and spatially marked to generate electromagnetic environment imaging results.

[0086] In this embodiment, based on the electromagnetic impact assessment results, relevant equipment information is extracted from the area to be modeled. Equipment information includes basic data such as equipment type, model, operating status, and installation location, used to clarify the spatial distribution of the modeling objects and their potential contribution or sensitivity to the electromagnetic environment. Electromagnetic measurement data and equipment technical specification data corresponding to the equipment information are retrieved from the electromagnetic environment database to form a multi-dimensional data set. Electromagnetic measurement data includes historical field strength values, frequency characteristics, and time-domain waveforms; technical specification data includes indicators such as the equipment's electromagnetic tolerance, electromagnetic compatibility standards, and electrical interface parameters. By integrating these two types of data, the interaction between the equipment and the surrounding electromagnetic environment can be comprehensively reflected.

[0087] Furthermore, multi-dimensional data sets are imported into the power plant information model to construct a digital plant spatial structure. Electromagnetic field modeling and simulation are then performed on this structure to generate a three-dimensional distribution map of the electromagnetic field within the plant. The power plant information model can be implemented using BIM (Building Information Modeling), GIS (Geographic Information System), or other three-dimensional spatial visualization platforms. During the simulation, continuous electromagnetic field distribution data is constructed using algorithms such as spatial interpolation and equipotential surface fitting to reflect the propagation characteristics and intensity changes of electromagnetic signals in different areas. Based on preset judgment criteria, the electromagnetic field intensity in the three-dimensional distribution map is divided into intervals and spatially marked to generate electromagnetic environment imaging results. Specifically, the electromagnetic field intensity is divided into normal areas, areas of concern, and warning areas according to set thresholds, and visual enhancement is achieved through color coding and spatial labels, enabling plant managers to quickly identify "hot" and "cold" areas. In addition, the potential relationship between specific electromagnetic behaviors and equipment status can be identified based on the temporal correlation between the frequency of electromagnetic events and equipment operating modes.

[0088] It is important to note that "hotspots" refer to areas in electromagnetic environment imaging where the electromagnetic field intensity is significantly higher than the surrounding area or exceeds a preset safety threshold. These areas typically present potential risks such as radiation leakage, electromagnetic interference sources, localized overheating, electrical faults, or electromagnetic shielding failure. Therefore, "hotspots" are high-risk areas of primary concern in electromagnetic environment monitoring, requiring early warning, location, and further intervention.

[0089] "Cold spots" refer to areas in electromagnetic environment imaging where the electromagnetic field strength is significantly lower than expected or where abnormal signal attenuation occurs. Causes may include electromagnetic signal obstruction, sensor failure, abnormal signal transmission, or equipment malfunction. "Cold spots" typically indicate blind spots in monitoring coverage or areas with limited signal propagation, and should be given attention to prevent overlooking potential problems.

[0090] In one embodiment, after step S106, the following steps are included:

[0091] The electromagnetic environment imaging results are compared and analyzed with the preset environmental modeling results to obtain the emergency response results;

[0092] Assess the severity of the emergency response outcome and generate emergency instructions;

[0093] The emergency command is sent to the electromagnetic environment database to provide operational optimization.

[0094] In this embodiment, the electromagnetic environment imaging results are compared and analyzed with preset environmental modeling results. The preset environmental modeling results are based on a standard electromagnetic distribution model constructed under normal operating conditions of a nuclear power plant, covering typical radiation source distribution, temperature field layout, and background electromagnetic environment information around equipment. By spatially matching and comparing the real-time imaging results with this standard electromagnetic distribution model, the offset of electromagnetic "hot spots" and "cold spots" can be quickly identified, thereby determining whether potential problems such as radiation leakage, equipment overheating, or electromagnetic anomalies exist. In the imaging image, hot spots and cold spots are typically spatially marked using different color codes (e.g., red represents high-intensity hot spots, and blue represents low-intensity cold spots), facilitating users to quickly identify abnormal areas and formulate corresponding operation and maintenance or emergency strategies. Emergency response results are generated based on the comparison results, and the severity of the situation is assessed. This process combines indicators such as the magnitude of electromagnetic field intensity changes in the differing areas, the duration of the anomaly, the affected area, and the importance of associated equipment for comprehensive judgment, and classifies the current state according to preset multi-level response rules. For example, minor anomalies can be marked as observation level, with regular monitoring recommended; moderate anomalies trigger warning level, requiring personnel to inspect; severe anomalies enter emergency response level, requiring emergency measures such as automatic shutdown, power outage, or activation of the shielding system. Emergency instructions are automatically generated based on the above assessment results. These instructions may include operational adjustment suggestions for specific equipment, system alarm notifications, shielding strategy adjustment parameters, or emergency plan activation signals. To improve response efficiency, emergency instructions can be generated according to a standardized format, compatible with the calling interfaces of various intelligent control systems and operation and maintenance management systems within the plant. Finally, the emergency instructions are sent to the electromagnetic environment database, and the current electromagnetic environment status record is updated accordingly for subsequent analysis and optimization. After database synchronization, this information can provide real-time operational optimization suggestions for plant operation and maintenance personnel, while also providing data support for subsequent system training, model correction, and long-term electromagnetic environment management.

[0095] Based on the above technical solution, the first test scenario example is provided as follows:

[0096] When testing the overall electromagnetic environment of the server rack facility, a spectrum analyzer is used in conjunction with an electromagnetic probe for systematic detection. During the test, operators must move back and forth within the facility to ensure there are no blind spots within a spherical area with a radius of 3 meters, guaranteeing complete spatial coverage. Each test must last at least 3 minutes to obtain sufficient electromagnetic signal data.

[0097] The electromagnetic environment data obtained from the tests mainly focused on the frequency bands related to communication base stations, particularly the 1.82GHz, 2.14GHz, and 2.56GHz ranges for 4G signals and their derivative frequencies. Verification showed that these signals do not cause significant interference to most equipment within the factory and can generally be ignored. Apart from the aforementioned communication frequency bands, the peak intensity of other electromagnetic signals met the national Class A limit standards, indicating that the overall electromagnetic environment of the cabinet factory is at an acceptable safety level. These test results provide a foundation for subsequent equipment electromagnetic compatibility analysis and factory electromagnetic environment optimization.

[0098] When the rated power of all equipment in the factory is less than 20kVA:

[0099]

[0100] When the rated power of all equipment in the factory exceeds 20kVA:

[0101]

[0102] When the spectrum analyzer shows the presence of other signals, pay attention to signal spikes in the 30MHz-1GHz range.

[0103] When electromagnetic signals exceeding limits or exhibiting sensitive characteristics are detected within the server rack facility, a directional antenna in conjunction with a spectrum analyzer can be used to detect the signal directionality to further confirm the location of the interference source. By rotating the directional antenna, the change in signal strength observed in the spectrum analyzer is noted; the direction of the strongest signal is the initial direction of the electromagnetic signal source. To verify the accuracy of the location results, an electromagnetic shielding mesh or shielding layer can be installed at the suspected signal source location. If the signal immediately disappears from the spectrum analyzer, the signal source has been correctly located; if the signal still exists, the directional antenna must be used to continue tracing along the path step by step to further pinpoint the signal source.

[0104] In addition, to ensure that the cabinet itself does not become a source of electromagnetic leakage or interference, specific tests must be conducted on each critical component of the cabinet. During testing, a spectrum analyzer and electromagnetic probe are used to scan the target cabinet's ventilation openings, power cable interfaces, grounding terminals, cabinet door gaps, and cable entry / exit ports—areas prone to leakage—at close range. During the testing process, it should be noted that when the electromagnetic wave frequency is below 8kHz, due to its extremely long wavelength, such low-frequency electromagnetic waves usually have little substantial impact on the equipment; while when the frequency is above 1.82GHz, although high-frequency signals possess strong energy, their short wavelengths usually make it difficult to penetrate the metal casing or other shielding structures of the cabinet. Therefore, during testing, special attention should be paid to mid-to-high frequency electromagnetic signals, especially the risk of signal leakage at gaps in the shielding structure, to comprehensively assess the cabinet's electromagnetic compatibility and shielding effectiveness.

[0105] Ventilation outlet electromagnetic signal standard:

[0106]

[0107] Electromagnetic signal standards for cabinet door gaps and cable entry / exit ports:

[0108]

[0109] Power cord interface, grounding terminal electromagnetic signal standard:

[0110]

[0111]

[0112] When conducting electromagnetic interference (EMI) tests on major equipment within a cabinet, special attention should be paid to the EMI characteristics of critical control components such as relays and valves. Relays, as automatic switching devices with electrical isolation capabilities, are widely used in remote control, telemetry, communication, automatic control, mechatronics, and power electronic equipment. They are among the most important execution and protection components in nuclear power plant control systems. Although relays themselves have a certain degree of anti-interference capability, they inevitably generate strong EMI signals during their switching operations, especially when disconnecting inductive loads. When the relay coil is de-energized, its inductive characteristics generate a transient high voltage, with peak values ​​reaching several kilovolts, which can easily damage sensitive electronic components in the vicinity. Simultaneously, this transient process is accompanied by a large number of high-frequency harmonics. These harmonic signals can couple to other circuits through distributed capacitance or insulation defects in the circuit, inducing malfunctions in the control system and even causing systemic functional abnormalities.

[0113] Therefore, to ensure the safe and stable operation of various devices within the cabinet, it is essential to effectively suppress the electromagnetic interference generated by relays and their contacts. Suppression measures may include: adding absorption circuits (such as RC buffer circuits, varistors, etc.) across the relay contacts to reduce sudden high voltage; optimizing cable routing to reduce electromagnetic coupling paths; and increasing shielding and grounding measures to isolate high-frequency interference paths. Through these methods, the impact of instantaneous high voltage and harmonic interference caused by relays on system operation can be effectively reduced, improving the electromagnetic compatibility and operational reliability of the entire plant control system.

[0114] When the relay and valve operate, measure the electromagnetic signal spike at a distance of 30cm from the relay:

[0115]

[0116] When conducting electromagnetic interference (EMI) assessments for digital systems within server racks, particular attention should be paid to the EMI issues of high-speed digital circuits. The effective signal loops in high-speed digital systems often exist in differential mode, with typically low loop impedances, generally around 50Ω, significantly lower than the characteristic impedance of free space (377Ω). This low impedance characteristic makes digital circuits more sensitive to external EMI and results in relatively poor interference immunity.

[0117] In practical applications, digital systems employ a wide variety of logic levels, commonly including TTL (Transistor-to-Transistor Logic), CMOS (Complementary Metal-Oxide-Semiconductor), LVTTL, LVCMOS, ECL (Emitter-Coupled Logic), PECL, LVPECL, GTL (Terminated Logic), and various serial communication interface standards such as RS232, RS422 / 485, and LVDS. The differences in electrical parameters among these different logic levels significantly impact their noise immunity.

[0118] Taking TTL logic as an example, its typical operating voltages include 5V, 3.3V, 2.5V, and 1.8V. 1.8V is mostly used in high-speed processing chips and has less widespread application. In contrast, voltage levels of 3.3V and below are commonly used in low-voltage logic systems, corresponding to LVTTL or LVCMOS standards, respectively. Regarding interference immunity, 5V TTL and 3.3V TTL have essentially the same logic level parameters, so their interference immunity is similar. However, 2.5V LVTTL, due to its lower operating voltage, has relatively weaker interference immunity, and special attention should be paid to signal integrity and electromagnetic compatibility protection during system design.

[0119] Therefore, when conducting electromagnetic environment testing on digital systems within a cabinet, it is necessary to identify key modules that may be affected by interference, taking into account the logic level type and operating voltage level used. Furthermore, the overall anti-interference capability and electromagnetic stability of the system can be improved through measures such as cabling optimization, shielding, or interface circuit isolation.

[0120] Logic level parameters and input / output of 5V TTL devices:

[0121] UCC UOH UOL UIH UIL 5V ≥2.4V ≤0.5V ≥2V ≤0.8V

[0122] Logic level parameters and input / output of 3.3V TTL and LVTTL devices:

[0123] UCC UOH UOL UIH UIL 3.3V ≥2.4V ≤0.4V ≥2V ≤0.8V

[0124] Logic level parameters and input / output of 2.5V LVTTL devices:

[0125] UCC UOH UOL UIH UIL 2.5V ≥2.0V ≤0.2V ≥1.7V ≤0.7V

[0126] CMOS can be further divided into three categories based on typical voltage: 5V, 3V, and 2.5V. Compared to TTL, CMOS has stronger anti-interference capabilities, but its input impedance is much higher than TTL, making it more susceptible to interference. Moreover, 3.3V CMOS has stronger anti-interference capabilities than 2.5V CMOS, but the CMOS transistor structure contains parasitic thyristors, which may burn out the chip when the input / output level is higher than Ucc and the current is large enough.

[0127] Logic level parameters and input / output of 5V CMOS devices:

[0128] UOH UOL UIH UIL ≥ UCC - 2.4 V ≤0.1V ≥ 0.7 UCC ≤ 0.3 UCC

[0129] Logic level parameters and input / output of 3V LVCMOS devices:

[0130] UCC UOH UOL UIH UIL 3.3V 3.2V ≤0.1V ≥2V ≤0.7V

[0131] Logic level parameters and input / output of 2.5V LVCMOS devices:

[0132] UCC UOH UOL UIH UIL 2.5V 2V ≤0.1V ≥1.7V ≤0.7V

[0133] ECL and PECL: ECL has the characteristics of high speed, strong driving capability and low noise, but it has high power consumption and requires a negative power supply. Therefore, in order to simplify the power supply, PECL and LVPECL were manufactured. Compared with CMOS, the anti-interference capability is further improved.

[0134] Logic level parameters and input / output of ECL devices:

[0135] UCC UEE UOH UOL UIH UIL 0V -5.2V -0.88V -1.72V -1.24V -1.36V

[0136] Logic level parameters and input / output of PECL devices:

[0137] UCC UOH UOL UIH UIL 5V 4.12V 3.28V 3.78V 3.64V

[0138] Logic level parameters and input / output of LVPECL devices:

[0139] UCC UOH UOL UIH UIL 3.3V 2.42V 1.58V 2.06V 1.94V

[0140] For GTL, PGTL, and GTL+, please refer to CMOS.

[0141] Logic level parameters and input / output of GTL devices:

[0142] UCC UOH UOL UIH UIL 1.2V ≥1.1V ≤0.4V ≥0.85V ≤0.75V

[0143] Logic level parameters and input / output of PGTL / GTL+ devices:

[0144] UCC UOH UOL UIH UIL 1.5V ≥1.4V ≤0.46V ≥1.2V ≤0.8V

[0145] RS232 and other data transmission circuits generally include interface circuits, which use LC filtering, where L is a ferrite bead (sometimes a resistor can be used instead) and C is a capacitor.

[0146] A near-field probe is used to perform a comprehensive scan of all components within a digital board during operation.

[0147]

[0148] When conducting electromagnetic compatibility (EMC) tests on analog systems within a server rack, a key focus should be placed on the high sensitivity of analog circuits to external interference. Compared to digital systems, analog signals, with their continuously varying amplitude and frequency, are more susceptible to electromagnetic interference, especially in scenarios requiring high precision and stability, where anti-interference design is crucial. In actual circuits, voltage and current constantly change between various components and wires. These dynamic changes induce electromagnetic induction, radiating electromagnetic waves into space. Once these electromagnetic waves enter sensitive analog circuits, they can adversely affect their normal function, causing signal distortion, deviation, or malfunctions. In environments with extremely high system stability requirements, such as nuclear power plants, these effects can lead to the failure of critical power management functions, triggering a cascading failure.

[0149] Analog chips are widely used in power management modules in modern electronic systems. Different functional subsystems often correspond to different voltage levels and power consumption requirements, resulting in the possible presence of multiple independent power management chips in the system. With the development of technologies such as intelligent control and ADAS (Advanced Driver Assistance Systems), a large number of sensors, cameras, and embedded computing devices are being integrated into systems, placing higher demands on the quantity and performance of power management chips and further increasing the complexity of electromagnetic interference protection.

[0150] Based on the generation mechanism of electromagnetic interference in actual system operation, several typical radiation-driven modes can be summarized:

[0151] Common-mode voltage caused by high-impedance return path: When the impedance of the signal return path is high, the current passing through the loop will generate a voltage drop, which will form a common-mode voltage. In particular, when a path is formed between the cable and the ground or other large conductors, it is easy to induce common-mode current and form a radiation source.

[0152] Differential mode current leakage leads to common mode interference: Even if a signal return line is set in the cable design, at higher frequencies in practice, stray parameters in the space may form additional return paths, causing some differential mode current to fail to return to the signal source and instead form common mode radiation.

[0153] Parasitic loops between cables and the ground cause magnetic coupling interference: When a parasitic loop between a cable and the ground is subjected to magnetic field coupling, it will induce current, forming a common-mode current source, which becomes another channel for interference.

[0154] To detect the aforementioned sources of interference, this invention employs a near-field probe to scan a simulated circuit board in operation, acquiring the electromagnetic radiation intensity distribution around each component. During the evaluation process, it is also necessary to consider the component's tolerance parameters and operating characteristics to determine whether the measured electromagnetic wave signal has substantially affected its normal function, ensuring the accuracy of the test results and the appropriateness of the protective measures.

[0155] Here is an example of a second test scenario:

[0156] When conducting overall electromagnetic environment testing on cable rooms and power supply facilities, a spectrum analyzer combined with an electromagnetic probe is used to systematically scan the area. During the test, operators must move back and forth within the facility to ensure coverage of all spatial areas without any blind spots in electromagnetic measurements. Specifically, the spatial coverage area for each testing point should be at least a spherical area with a radius of 3 meters. The entire reciprocating test process must last at least 3 minutes to ensure the stability and comprehensiveness of the data.

[0157] In actual testing, the overall electromagnetic environment of the plant was relatively clear, with the measured signals mainly concentrated in typical 4G communication frequency bands such as 1.82GHz, 2.14GHz, and 2.56GHz. These signals mostly originate from communication base stations near the plant, and their interference with the internal equipment of the power station is relatively weak and can generally be considered negligible. Apart from the aforementioned communication frequencies, the peak values ​​of electromagnetic signals in other frequency bands all met the Class A limits of the national standard, indicating that under these test conditions, the overall electromagnetic environment of the plant was within a controlled and safe range.

[0158] The test results can provide effective data support for the electromagnetic compatibility analysis of cable systems, power interfaces and related equipment, and serve as an important reference for routine electromagnetic monitoring during plant operation.

[0159] When the rated power of all equipment in the factory is less than 20kVA, the peak electric field strength must meet the following requirements (refer to the national standard for electromagnetic compatibility design of power supply terminals):

[0160]

[0161] When the rated power of all equipment in the factory is less than 20kVA, the average electric field strength must meet the following requirements:

[0162]

[0163] When the rated power of all equipment in the plant exceeds 20kVA, the peak electric field strength must meet the following requirements:

[0164]

[0165]

[0166] When the rated power of all equipment in the factory exceeds 20kVA, the average electric field strength must meet the following requirements:

[0167]

[0168] When an over-limit or sensitive signal is detected, a directional antenna in conjunction with a spectrum analyzer is used to test the electromagnetic signal. The direction of maximum signal strength from the directional antenna is the direction of the signal source. After adding an electromagnetic shielding mesh or layer, observe the spectrum analyzer signal. If the original signal disappears, the signal source is correctly located. If the original signal persists, the location of the suspected signal source is re-established using the directional antenna step by step. Whether it's the electrical fast transient / burst immunity test specified in IEC 61000-4-4 and ISO 7637-2, ISO 7637-3, or the conducted interference immunity test specified in IEC 61000-4-6 and ISO 11452-4, ISO 11452-7, interference is injected directly into the cable in common-mode form. If the cable is shielded, the interference signal is injected directly into the shielding layer; if the cable is unshielded, the interference is injected directly into each signal on the cable.

[0169] Cable radiation is one of the most common problems in engineering; over 90% of equipment failures in radiated emission tests are due to cable radiation. In practice, it is often observed that removing the external cable from the equipment allows it to pass tests smoothly, and electromagnetic interference issues disappear when the cable is unplugged. This is because a cable acts as a highly efficient receiving and radiating antenna. There are two mechanisms by which cables generate radiation: differential-mode radiation from the signal current (differential-mode current) loop within the cable; and common-mode radiation from the common-mode current in the conductors (including the shielding layer). Cable radiation primarily originates from common-mode radiation. Common-mode radiation is generated by common-mode current, whose loop area is formed by the cable and the ground (or other nearby large conductors), resulting in a large loop area and strong radiation.

[0170] If the cable is close to the ground plane, the electromagnetic field induction in the cable is strongest when the electric field component is perpendicular to the ground plane and the magnetic field component is perpendicular to the loop formed by the conductor and the ground plane. If the cable is far from the ground plane, the electromagnetic field induction in the cable is strongest when the electric field component is parallel to the ground plane and the magnetic field component is perpendicular to the loop formed by the conductor and the ground plane. Although theoretically the voltage induced in a cable by the electromagnetic field can be divided into common mode and differential mode, in the independent operation of a single product, the voltage induced in the conductor by the electromagnetic field is mainly in the common mode form. The voltage on the load is referenced to the common conductor or the ground in the system, generally the reference ground plane in the system. For multi-core cables, this means that all conductors in the cable are exposed to the same field, and the voltage induced on them depends on the impedance and induced current between each conductor and the reference point.

[0171] The formulas for estimating the induced current on the two types of antennas are as follows:

[0172] When L≤λ / 4, the induced current on the symmetrical dipole antenna

[0173]

[0174] The approximate formula is:

[0175]

[0176] When L≥λ / 2, the induced current on the symmetrical dipole antenna

[0177]

[0178] The approximate formula is:

[0179]

[0180] Where I represents the current at the center of the symmetrical dipole antenna (A); d represents the conductor diameter (m); E represents the electric field strength (V / m); F MHz The signal frequency (MHz) is represented by λ; L represents the length of the symmetrical dipole antenna (or twice the length of the monopole antenna); and λ represents the signal wavelength (m).

[0181] For example, if a microphone cable is 1m long and 5mm in diameter, when it is exposed to an electromagnetic field with a frequency of 27MHz and an electric field strength of 1V / m, the induced current on the cable can be calculated as follows: Since the microphone is connected to the amplifier at only one end, its equivalent model is approximately a monopole antenna, and the equivalent symmetrical dipole antenna length is 2×1m=2m.

[0182] The wavelength of a 27MHz frequency is λ = 300 / 27 ≈ 11m. Since the equivalent symmetrical dipole antenna length L = 2m, then: L < λ / 4. Therefore, the induced current I on the cable is:

[0183]

[0184] By considering the over-limit error ranges of the cables and upstream and downstream equipment of the power supply, it can be determined whether the error in this electromagnetic environment is within the allowable range.

[0185] Here is an example of a third test scenario:

[0186] When conducting electromagnetic compatibility (EMC) tests on large motor equipment workshops, a spectrum analyzer with probes is used to perform reciprocating tests throughout the entire workshop, ensuring there are no blind spots with a spherical radius of 10m. The reciprocating test time is no less than 3 minutes. The electromagnetic environment of the equipment rack workshop is generally clear. The spectrum analyzer test data mainly focuses on 4G signals and derived signals within the base station, specifically the 1.82GHz, 2.14GHz, and 2.56GHz bands. 4G signals and derived signals do not cause significant interference to most equipment in the power station and can be ignored. Other electromagnetic signal spikes meet Class A limits.

[0187] When the rated power of all equipment in the factory is less than 20kVA:

[0188]

[0189] When the rated power of all equipment in the factory exceeds 20kVA:

[0190]

[0191]

[0192] When the spectrum analyzer shows the presence of other signals, special attention should be paid to signal spikes in the 800MHz-1GHz range.

[0193] For locating electromagnetic signal sources, when excessive or sensitive signals are detected, a directional antenna is used in conjunction with a spectrum analyzer to test the electromagnetic signals. The direction of maximum signal strength from the directional antenna indicates the direction of the signal source. After installing an electromagnetic shielding mesh or layer, the spectrum analyzer signal is observed. If the original signal disappears, the signal source has been correctly located. If the original signal persists, the location of the suspected signal source is re-established by using the directional antenna step by step.

[0194] For testing motor equipment, electromagnetic interference mainly refers to two aspects: abrupt changes in the magnetic field in the windings and spark discharges generated between the commutator and brushes. The electromagnetic wave frequencies of these interferences are approximately 10Hz-1000MHz, with a wide bandwidth and both vertical and horizontal polarization. The field strength and frequency are basically normally distributed. The peak value of the interference pulse in a motor is related to many factors, including the motor's structure, workload, winding insulation aging, and the gap and wear between the commutator and brushes. If the current path through the motor coil windings is interrupted due to abrupt changes in the magnetic field or aging, the magnetic field in the coils suddenly disappears, generating transient overvoltages of hundreds or even thousands of volts. This voltage resembles the exponential decay curve of a first-order circuit, leading to a massive energy release. The released energy surges through the control loop, causing a huge electrical energy impact on other electronic devices in the system, interfering with their normal operation, ultimately leading to basic equipment and system malfunctions, logical errors, and even breakdown or burnout of other electromechanical components. The transient overvoltage is related to the load size and line impedance.

[0195] One scenario is when the motor is operating normally under rated load, and the power supply current is suddenly cut off. At this time, the armature is still rotating at high speed under the excitation of the stator, and the rotor armature winding will generate a self-induced electromotive force. The induced electromotive force is superimposed on the original armature electromotive force in the same direction, forming an overvoltage. Its transient peak value can reach 6-8 times the rated voltage, and the rise time is about 100μs. It decays exponentially until the armature stops rotating.

[0196] Another type of transient overvoltage occurs when the supply current is suddenly cut off, causing an inductive load surge in the coil winding. This transient voltage usually manifests as a series of high-amplitude negative pulses and low-amplitude positive pulses, with the highest peak value reaching more than 10 times the rated voltage and lasting for about 300ms.

[0197] For brushed motors, spark discharge between the commutator and brushes generates a wide-spectrum noise (continuously distributed across the medium wave to very high frequency bands), interfering with radio broadcasting, television, and various electronic devices over a large area. Many other electronic products use DC power supplies rectified by bridge rectifiers and capacitor filters. Because the conduction angle of the rectifier diodes is very small, peak input current only flows near the peak of the input AC voltage. This distorted current waveform is generally low-frequency, but rich in higher harmonics, with a pulse width of approximately 5ms (1 / 4r). These peak current pulses not only severely pollute the power grid but also interfere with various other electrical devices.

[0198] The peak level of electromagnetic interference for brushed motors should meet the following requirements:

[0199]

[0200] The average electromagnetic interference of brushed motors should meet the following requirements:

[0201] The peak electromagnetic interference level for brushless motors should meet the following requirements:

[0202]

[0203]

[0204] The average electromagnetic interference of brushless motors should meet the following requirements:

[0205]

[0206] Here is an example of the fourth test scenario:

[0207] When conducting electromagnetic compatibility (EMC) tests in open areas, a spectrum analyzer and probe are used to repeatedly test the entire area, ensuring there are no blind spots with a radius of 10m within the plane. When the measurement distance cannot be less than 10m and can only reach 30m, an inverse proportionality factor of 20dBV / 10 times the distance is required to normalize the data to the specified distance to determine compliance. The electromagnetic environment in cabinet manufacturing facilities is generally clear. Spectrum analyzer test data mainly focuses on 4G signals and derived signals within the base station, specifically the 1.82GHz, 2.14GHz, and 2.56GHz bands. 4G signals and derived signals do not significantly interfere with most equipment in the power station and can be ignored. Other electromagnetic signal spikes meet Class A limits and public area electromagnetic radiation limits, and the range should meet the following requirements:

[0208]

[0209] Combination Figures 2 to 7 As shown, this invention conducts electromagnetic tests on the cabinet before and during the overhaul to assess whether there are any changes in the electromagnetic distribution of the cabinet before and after the overhaul. The specific test results are as follows:

[0210] Electromagnetic distribution of the cabinet before overhaul ( Figure 2 , Figure 3 , Figure 4 ):

[0211] Figure 2 This is a schematic diagram of the amplitude superposition between 22.78MHz and 170.5MHz (50-55dbuV);

[0212] Figure 3 This is a schematic diagram of the amplitude superposition in the range of 988MHz-1.108Hz (53-59dbuV);

[0213] Figure 4 This is a schematic diagram showing the amplitude superposition between 1.369GHz and 1.528GHz (52-60dbuV).

[0214] Electromagnetic distribution of server racks during overhaul ( Figure 5 , Figure 6 , Figure 7 ):

[0215] Figure 5 A schematic diagram (65dBm) showing the amplitude superposition between 22.78MHz and 170.5MHz;

[0216] Figure 6 A schematic diagram of amplitude superposition in the range of 988MHz-1.108Hz (65dBm);

[0217] Figure 7 This is a schematic diagram of the amplitude superposition in the range of 1.369 GHz to 1.528 GHz (64 dBuV).

[0218] In summary, the electromagnetic environment imaging-based plant monitoring method provided by this invention, combined with high-precision detection equipment, intelligent analysis platform and three-dimensional imaging model, can realize rapid identification, accurate location, scientific assessment and visualization of electromagnetic interference in nuclear power plant buildings, providing strong technical support for improving the safety and reliability of plant operation.

[0219] Combination Figure 8 As shown, Figure 8 A schematic block diagram of a factory monitoring device based on electromagnetic environment imaging provided in this embodiment of the invention. The factory monitoring device 800 based on electromagnetic environment imaging includes:

[0220] The data acquisition unit 801 is used to acquire raw electromagnetic signal data from various areas within the factory building.

[0221] Data processing unit 802 is used to preprocess the original electromagnetic signal data to obtain electromagnetic signal feature vectors;

[0222] The data comparison unit 803 is used to compare the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result.

[0223] The positioning calculation unit 804 is used to calculate the spatial coordinates of the interference source based on the electromagnetic interference identification result, and obtain the electromagnetic interference positioning result.

[0224] The electromagnetic evaluation unit 805 is used to evaluate the electromagnetic susceptibility of the surrounding equipment based on the electromagnetic interference location results and generate electromagnetic impact evaluation results.

[0225] The electromagnetic imaging unit 806 is used to jointly model the electromagnetic influence assessment results with the pre-recorded electromagnetic measurement data to obtain electromagnetic environment imaging results.

[0226] In this embodiment, the data acquisition unit 801 acquires raw electromagnetic signal data from various areas within the factory; the data processing unit 802 preprocesses the raw electromagnetic signal data to obtain electromagnetic signal feature vectors; the data comparison unit 803 compares the electromagnetic signal feature vectors with preset reference electromagnetic signals to generate electromagnetic interference identification results; the positioning calculation unit 804 calculates the spatial coordinates of the interference source based on the electromagnetic interference identification results to obtain electromagnetic interference positioning results; the electromagnetic evaluation unit 805 evaluates the electromagnetic sensitivity of surrounding equipment based on the electromagnetic interference positioning results to generate electromagnetic impact evaluation results; and the electromagnetic imaging unit 806 jointly models the electromagnetic impact evaluation results with pre-recorded electromagnetic measurement data to obtain electromagnetic environment imaging results.

[0227] In one embodiment, the data comparison unit 803 is specifically used for:

[0228] The electromagnetic signal feature vector is compared with the reference electromagnetic signal in the time-frequency domain to obtain time-frequency domain difference data.

[0229] The interference deviation index is calculated based on the time-frequency domain difference data to obtain the interference signal;

[0230] The interference signal was analyzed using a spectrum analysis tool to obtain the interference analysis results.

[0231] The interference analysis results are stored in the electromagnetic interference identification module, and electromagnetic interference identification results are generated.

[0232] In one embodiment, the data comparison unit 803 is further specifically used for:

[0233] When the interference signal is determined to belong to the first signal range, a first-level warning is issued;

[0234] When the interference signal is determined to belong to the second signal range, a second-level warning is issued;

[0235] When the interference signal is determined to belong to the third signal range, a third-level warning is issued;

[0236] The peak values ​​of the first signal range, the second signal range, and the third signal range increase sequentially.

[0237] In one embodiment, the positioning calculation unit 804 is specifically used for:

[0238] Acquire electromagnetic signal intensity and direction variation data from at least three electromagnetic detectors with known spatial coordinates to construct a localization dataset;

[0239] The relative distance data is obtained by calculating the signal propagation distance between each electromagnetic detector and the interference source corresponding to the electromagnetic interference identification result using the positioning dataset.

[0240] Based on the relative distance data and the spatial coordinates of each of the electromagnetic detectors, a set of geometric equations for spatial triangulation is established to obtain a multivariate spatial equation model for solving the location of the interference source.

[0241] The multivariate spatial equation model is solved, and error correction is performed to generate electromagnetic interference location results.

[0242] In one embodiment, the electromagnetic evaluation unit 805 is specifically used for:

[0243] Extract historical electromagnetic field measurement data of the area corresponding to the electromagnetic interference location result to obtain the electromagnetic field intensity distribution of the corresponding area;

[0244] The electromagnetic field intensity distribution is analyzed to determine the electromagnetic exposure level of the surrounding equipment;

[0245] An electromagnetic interference suppression scheme is constructed based on the electromagnetic exposure level, and the electromagnetic compatibility of the electromagnetic interference suppression scheme is verified using a simulation model to obtain the electromagnetic impact assessment results.

[0246] In one embodiment, the electromagnetic imaging unit 806 is specifically used for:

[0247] Based on the electromagnetic influence assessment results, extract equipment information within the area to be modeled;

[0248] Electromagnetic measurement data and equipment technical specification data corresponding to the equipment information are retrieved from the electromagnetic environment database to obtain a multi-dimensional data set.

[0249] The multi-dimensional data set is imported into the power plant information model to generate a three-dimensional distribution map of the electromagnetic field;

[0250] Based on preset judgment criteria, the electromagnetic field intensity in the three-dimensional distribution map is divided into intervals and spatially marked to generate electromagnetic environment imaging results.

[0251] In one embodiment, the factory monitoring device based on electromagnetic environment imaging further includes:

[0252] The data analysis unit is used to compare and analyze the electromagnetic environment imaging results with the preset environmental modeling results to obtain emergency response results;

[0253] The data assessment unit is used to assess the severity of the emergency response results and generate emergency instructions.

[0254] The instruction sending unit is used to send the emergency instructions to the electromagnetic environment database to provide operational optimization.

[0255] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0256] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, 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.

[0257] This invention also provides a computer device, which may include a memory and a processor. The memory stores a computer program, and when the processor calls the computer program in the memory, it can implement the steps provided in the above embodiments. Of course, the computer device may also include various network interfaces, power supplies, and other components.

[0258] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0259] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A factory monitoring method based on electromagnetic environment imaging, characterized in that, include: Acquire raw electromagnetic signal data from various areas within the factory building; The original electromagnetic signal data is preprocessed to obtain electromagnetic signal feature vectors; The electromagnetic signal feature vector is compared with a preset reference electromagnetic signal to generate an electromagnetic interference identification result. The spatial coordinates of the interference source are calculated based on the electromagnetic interference identification results to obtain the electromagnetic interference location results; The electromagnetic sensitivity of surrounding equipment based on the electromagnetic interference location results is evaluated to generate electromagnetic impact assessment results. The electromagnetic influence assessment results are combined with pre-recorded electromagnetic measurement data to form a joint model, resulting in electromagnetic environment imaging results.

2. The factory monitoring method based on electromagnetic environment imaging according to claim 1, characterized in that, The step of comparing the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result includes: The electromagnetic signal feature vector is compared with the reference electromagnetic signal in the time-frequency domain to obtain time-frequency domain difference data. The interference deviation index is calculated based on the time-frequency domain difference data to obtain the interference signal; The interference signal was analyzed using a spectrum analysis tool to obtain the interference analysis results. The interference analysis results are stored in the electromagnetic interference identification module, and electromagnetic interference identification results are generated.

3. The factory monitoring method based on electromagnetic environment imaging according to claim 2, characterized in that, The step of using a spectrum analysis tool to perform signal range analysis on the interference signal to obtain interference analysis results includes: When the interference signal is determined to belong to the first signal range, a first-level warning is issued; When the interference signal is determined to belong to the second signal range, a second-level warning is issued; When the interference signal is determined to belong to the third signal range, a third-level warning is issued; The peak values ​​of the first signal range, the second signal range, and the third signal range increase sequentially.

4. The factory monitoring method based on electromagnetic environment imaging according to claim 1, characterized in that, The step of calculating the spatial coordinates of the interference source based on the electromagnetic interference identification result to obtain the electromagnetic interference location result includes: Acquire electromagnetic signal intensity and direction variation data from at least three electromagnetic detectors with known spatial coordinates to construct a localization dataset; The relative distance data is obtained by calculating the signal propagation distance between each electromagnetic detector and the interference source corresponding to the electromagnetic interference identification result using the positioning dataset. Based on the relative distance data and the spatial coordinates of each of the electromagnetic detectors, a set of geometric equations for spatial triangulation is established to obtain a multivariate spatial equation model for solving the location of the interference source. The multivariate spatial equation model is solved, and error correction is performed to generate electromagnetic interference location results.

5. The factory monitoring method based on electromagnetic environment imaging according to claim 1, characterized in that, The process of evaluating the electromagnetic susceptibility of surrounding equipment based on the electromagnetic interference location results to generate electromagnetic impact evaluation results includes: Extract historical electromagnetic field measurement data of the area corresponding to the electromagnetic interference location result to obtain the electromagnetic field intensity distribution of the corresponding area; The electromagnetic field intensity distribution is analyzed to determine the electromagnetic exposure level of the surrounding equipment; An electromagnetic interference suppression scheme is constructed based on the electromagnetic exposure level, and the electromagnetic compatibility of the electromagnetic interference suppression scheme is verified using a simulation model to obtain the electromagnetic impact assessment results.

6. The factory monitoring method based on electromagnetic environment imaging according to claim 1, characterized in that, The process of jointly modeling the electromagnetic impact assessment results with pre-recorded electromagnetic measurement data to obtain electromagnetic environment imaging results includes: Based on the electromagnetic influence assessment results, extract equipment information within the area to be modeled; Electromagnetic measurement data and equipment technical specification data corresponding to the equipment information are retrieved from the electromagnetic environment database to obtain a multi-dimensional data set. The multi-dimensional data set is imported into the power plant information model to generate a three-dimensional distribution map of the electromagnetic field; Based on preset judgment criteria, the electromagnetic field intensity in the three-dimensional distribution map is divided into intervals and spatially marked to generate electromagnetic environment imaging results.

7. The factory monitoring method based on electromagnetic environment imaging according to claim 1, characterized in that, After jointly modeling the electromagnetic influence assessment results with pre-recorded electromagnetic measurement data to obtain electromagnetic environment imaging results, the process includes: The electromagnetic environment imaging results are compared and analyzed with the preset environmental modeling results to obtain the emergency response results; Assess the severity of the emergency response outcome and generate emergency instructions; The emergency command is sent to the electromagnetic environment database to provide operational optimization.

8. A factory monitoring device based on electromagnetic environment imaging, characterized in that, include: The data acquisition unit is used to acquire raw electromagnetic signal data from various areas within the factory building. The data processing unit is used to preprocess the original electromagnetic signal data to obtain electromagnetic signal feature vectors; The data comparison unit is used to compare the electromagnetic signal feature vector with a preset reference electromagnetic signal to generate an electromagnetic interference identification result. The positioning calculation unit is used to calculate the spatial coordinates of the interference source based on the electromagnetic interference identification result to obtain the electromagnetic interference positioning result; An electromagnetic assessment unit is used to assess the electromagnetic susceptibility of surrounding equipment based on the electromagnetic interference location results and generate electromagnetic impact assessment results. The electromagnetic imaging unit is used to jointly model the electromagnetic influence assessment results with the pre-recorded electromagnetic measurement data to obtain electromagnetic environment imaging results.

9. A computer device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the factory monitoring method based on electromagnetic environment imaging as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the factory monitoring method based on electromagnetic environment imaging as described in any one of claims 1 to 7.

Images