Safety control module and method for multi-source data acquisition of electric energy metering box

Abstract

The invention provides a safety control module and method for multi-source data acquisition of an electric energy metering box. The safety control module comprises an energy flow anomaly topological system, a dielectric fission entropy increase sensing system and a thermal runaway phase change blocking system. The method comprises the following steps: fusing a microscopic deformation vibration spectrum, internal gas ion mobility and electromagnetic field eddy current distribution into a three-dimensional energy flow density topological graph through unsteady-state field reconstruction; generating an arc fault embryonic period early warning signal according to the fractal dimension mutation rate of the three-dimensional energy flow density topological graph; capturing a relaxation abnormal point in the dielectric constant frequency domain response curve, calculating a material molecular chain fracture entropy increment through relaxation peak offset of the relaxation abnormal point, and generating a medium fission level; and positioning a fission grade ultralimit region in the three-dimensional energy flow density topological graph, calculating a thermodynamic phase change critical path by combining the energy flow gradient, injecting a reverse vortex field along the thermodynamic phase change critical path to offset energy accumulation, and releasing the nanoscale aerogel to block the oxidation chain reaction.

Description

Technical Field

[0001] This invention relates to the field of multi-source data processing technology, and in particular to a safety control module and method for multi-source data acquisition of an electricity metering box. Background Technology

[0002] As a crucial component of the power system, the safe and stable operation of electricity metering boxes directly impacts grid reliability and power quality for users. However, during long-term operation, electricity metering boxes may experience localized overheating or even fires due to insulation degradation, poor contact, or arcing faults. Traditional monitoring methods typically rely solely on threshold values ​​for electrical parameters (such as voltage, current, and temperature), making it difficult to provide effective early warnings of faults. Furthermore, existing technologies lack the ability to monitor multi-physics coupling effects such as mechanical deformation of the box body, changes in internal gas composition, and electromagnetic field anomalies, resulting in delayed fault identification and hindering precise intervention.

[0003] Existing technology 1, application number: CN202510526498.3, discloses a remote control method for a metering box, a storage medium, and a metering box. The method includes: collecting operational and environmental data from the metering box using multiple sensors to construct a multivariate time-series dataset; using each metering box as a federated node, training a vector autoregressive model with local data, and weighted aggregation to generate a global dynamic model; calculating environmental change factors in real time to trigger model fine-tuning to adapt to sudden change scenarios; generating anomaly confidence scores based on the fusion of residual Mahalanobis distance and fuzzy logic, and calculating maintenance priorities using a topological connection matrix. While this method solves the problems of reliance on manual labor, model rigidity, and data security risks associated with traditional methods, significantly improving anomaly detection accuracy, dynamic response capability, and system security, it employs federated learning to optimize multi-sensor data modeling, but relies solely on electrical parameters and environmental data, failing to address physical field coupling effects such as box micro-deformation, gas ion mobility, and electromagnetic eddy current distribution, thus failing to capture the early microscopic characteristics of arc faults.

[0004] Prior art two, application number CN202410893892.6, discloses a finite element method-based simulation analysis method for the temperature field of an energy metering box. First, the resistance loss of the target device is calculated based on the specifications of each main circuit component in the energy metering box. Then, based on the resistance loss of the target device, the temperature rise characteristics of the main circuit components of the energy metering box are determined, and the thermal conductivity differential equation in three-dimensional space is derived. Next, the temperature rise at the terminal of the target device is equivalent to the internal heat source of the energy metering box, obtaining the distribution of the internal heat source. A numerical calculation model is established using the thermal conductivity differential equation and the internal heat source distribution, and initial values ​​and boundary conditions are set. Finally, the distribution and changes of the internal temperature field of the energy metering box are obtained through simulation calculation. Although this method can accurately study the internal temperature field of the energy metering box, helping to determine the operating status of components and identify potential risks, providing important basis for operation and maintenance, and improving the reliability and safety of the power system, the finite element-based temperature field simulation can only reflect the steady-state heat distribution and cannot monitor dynamic thermal runaway processes such as local energy accumulation and oxidation chain reactions in real time, and it does not propose proactive intervention measures.

[0005] Prior art three, application number CN202411843276.6, discloses a method, device, electronic equipment, and storage medium for real-time monitoring of meter boxes. The device includes: a multimodal data acquisition module for acquiring multimodal data; a control module connected to the multimodal data acquisition module for controlling the multimodal data acquisition module; and a communication module connected to both the multimodal data acquisition module and a server for communication between the control module and the server, which in turn interacts with monitoring personnel. The method includes polling and detecting the multimodal data acquired by the multimodal data acquisition module to obtain detection results; and responding to the detection results indicating anomalies in the multimodal data by handling anomalies according to a preset anomaly handling strategy. While this solves the technical problem of lacking a comprehensive safety monitoring solution for meter boxes and failing to promptly detect safety risks in meter boxes, the multimodal data polling detection only achieves anomaly alarms, does not establish a fault evolution model such as the entropy increase process of dielectric material fission, and lacks a graded response mechanism.

[0006] Currently, existing technologies 1, 2, and 3 suffer from insufficient multi-source data fusion, delayed early fault identification, and lack of proactive intervention capabilities. Therefore, this invention provides a safety control module and method for multi-source data acquisition in power metering boxes. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides a safety control module for multi-source data acquisition in an energy metering box, comprising:

[0008] The dielectric fission entropy increase sensing system is used to receive early warning signals of the embryonic stage of electric arc faults. At the same time, it activates the enhanced scanning mode, applies a microsecond-level pulsed electric field to the surface of the insulating material, captures relaxation anomalies in the frequency domain response curve of the dielectric constant, calculates the entropy increase of material molecular chain fracture by the relaxation peak shift of the relaxation anomalies, and generates the dielectric fission level.

[0009] The thermal runaway phase change blocking system is used to locate the region exceeding the fission level in a three-dimensional energy flow density topology map, calculate the thermodynamic phase change critical path by combining energy flow gradient, inject a reverse vortex field along the thermodynamic phase change critical path to counteract energy accumulation, and release nanoscale aerogel to block the oxidation chain reaction.

[0010] Optionally, a dielectric fission entropy increase sensing system includes:

[0011] The frequency domain response excitation subsystem is used to apply a microsecond-level pulsed electric field to the surface of the insulating material after the enhanced scanning mode is activated by the early warning signal of the embryonic stage of the arc fault, so as to cause the molecular chain of the material to oscillate under forced conditions.

[0012] The relaxation anomaly capture subsystem is used to acquire the frequency domain response curve of the dielectric constant in real time during forced oscillation and detect its anomalous frequency shift characteristics.

[0013] The relaxation peak offset calculation subsystem is used to compare the detected relaxation anomalies with the reference position of the intrinsic relaxation spectrum of the material and quantify the offset distance of their frequency axis.

[0014] The molecular chain fracture entropy value conversion subsystem is used to calculate the entropy value based on the relaxation peak shift. Each unit shift distance corresponds to a specific order of magnitude of molecular chain conformational entropy loss. The conformational entropy loss value is superimposed on the abrupt increment of the bond rotation energy barrier. The product of the two generates the molecular chain fracture entropy value, establishing a quantitative mapping between frequency shift and molecular-scale energy dissipation.

[0015] The medium fission level generation subsystem is used to classify fission levels based on the threshold range of the entropy increase of molecular chain fracture in materials.

[0016] Optional, the molecular chain fracture entropy increment conversion subsystem includes:

[0017] The offset conversion component is used to convert the relaxation peak offset into the molecular chain conformational entropy loss value proportionally. The number of conformational states decreases by a fixed proportion for each unit frequency offset. For every additional reference unit of offset distance, the conformational space of the movable chain segment is reduced by one discrete gradient.

[0018] The component for detecting bond rotation barrier mutations is used to extract barrier features at the same relaxation anomaly point. Normal relaxation peaks correspond to smooth barrier distributions, and the appearance of asymmetric spikes indicates the increment of bond rotation barrier mutations. The increment magnitude is quantified by the ratio of the peak half-width to the main peak width.

[0019] The fracture entropy increment generation component is used to multiply the conformational entropy loss value with the bond rotation energy barrier mutation increment. The conformational entropy loss characterizes the degree of molecular chain flexibility degradation, and the energy barrier mutation increment reflects the covalent bond twisting potential energy step. The multiplication operation causes the two to produce an energy coupling effect.

[0020] A component for establishing molecular-scale dissipation mapping is used to directly correlate the increase in fracture entropy with the inherent limitation of molecular motion. The increase in entropy is linearly proportional to the power of frictional heat dissipation within the chain segment. Each unit increase in entropy corresponds to a specific order of magnitude of molecular kinetic energy decay rate, thus completing the quantitative mapping from frequency shift to molecular-scale energy dissipation.

[0021] Optional, the fracture entropy increment generation component includes:

[0022] The quantification of flexibility degradation degree sub-component is used to convert the molecular chain conformational entropy loss value output by the offset conversion component into a flexibility degradation coefficient;

[0023] Degree of molecular chain flexibility degradation = entropy loss value × intrinsic flexural conversion factor;

[0024] The calibration potential energy step intensity sub-component is used to convert the mutation increment output by the detection bond rotation barrier mutation component into a potential energy distortion.

[0025] Covalent bond twisting potential energy step = sudden change increment × bond angle distortion coefficient;

[0026] A fracture energy coupling effect sub-component is generated to multiply the degree of flexibility degradation of the molecular chain with the step of covalent bond distortion potential energy. The degree of flexibility degradation weakens the stress dissipation ability of the molecular chain, and the potential energy step exacerbates the accumulation of local bond distortion, resulting in the increase of molecular chain fracture entropy.

[0027] Optional, a sub-component for quantifying the degree of flexibility degradation, including:

[0028] The discrete gradient analysis module is used to receive the molecular chain conformational entropy loss value output by the offset conversion component and extract the discrete gradient reduction series contained therein.

[0029] The flexural modulus transition mapping module is used to map discrete gradient reduction series to a rigid growth sequence of chain segments. For each gradient annihilated, the flexural modulus of the corresponding chain segment increases by a fixed order of magnitude.

[0030] The module for generating the flexibility degradation coefficient is used to multiply the stiffness growth slope by the intrinsic flexural conversion factor. The stiffness growth slope reflects the rate of change of chain segment stiffness, while the intrinsic flexural conversion factor reflects the initial compliance characteristics of the material, thus generating the flexibility degradation coefficient.

[0031] Optional, the calibration potential energy step intensity sub-component includes:

[0032] The barrier mutation increment analysis module is used to receive the mutation increment output by the key rotation barrier mutation detection component and extract the order of magnitude of its transcendence beyond the reference unit.

[0033] The bond angle distortion threshold mapping module is used to convert the excess magnitude into a bond angle distortion stage, and each stage is locked to reduce the covalent bond angle tolerance threshold by a fixed proportion.

[0034] An electron cloud deformation barrier module is generated to calibrate the potential energy step based on the bond angle distortion degree. For each increase in the bond angle distortion degree, the overlapping area of ​​the electron cloud orbit is reduced by a corresponding proportion. The reduction in orbital overlap is converted into the height of the electron cloud deformation barrier.

[0035] The potential energy distortion module is used to multiply the potential energy step height by the bond angle distortion coefficient. The potential energy step height reflects the single bond twisting energy, and the bond angle distortion coefficient carries the rigidity characteristics of the molecular skeleton, thus generating a covalent bond twisting potential energy distortion variable.

[0036] Optional, a thermal runaway phase transition blocking system includes:

[0037] The subsystem for locating the fission exceedance region is used to map the dielectric fission level output by the dielectric fission entropy increase sensing system to a three-dimensional energy flux density topology map. Regions with a fission level of not less than level two are marked as exceedance coordinate clusters. The exceedance coordinate clusters coincide with the energy deposition peak area in the topology map for verification, and the fission-energy coupling focus coordinate set is output.

[0038] Extract the energy flow gradient field subsystem to analyze the three-dimensional energy flow density topology map within the range of the coupled focus coordinate set, obtain the spatial rate of change of energy density per unit volume, calibrate the energy conduction principal axis along the direction of the maximum rate of change, and output the energy flow gradient vector matrix.

[0039] The critical path calculation subsystem is used to construct a thermodynamic potential field based on the energy flow gradient vector matrix. The convergence point of the gradient vector forms a local potential well. The lowest energy channel connecting adjacent potential wells is the thermodynamic critical path of phase transition. The output is the path with the minimum resistance to energy conduction connecting the overlimit region.

[0040] An inverse eddy current field subsystem is injected to generate canceling eddies along the critical path of phase transition. The original electromagnetic field eddy current distribution pattern of the region through which the path passes is extracted, and an inverse eddy current field distribution with a phase difference of 180° is generated. The output is a directional canceling eddy current field that cancels the energy accumulation.

[0041] Optionally, a subsystem for calculating the critical path of phase transition includes:

[0042] A thermodynamic potential field component is constructed to convert the energy flow gradient vector matrix output by the energy flow gradient field subsystem into a scalar potential. The gradient vector modulus of each spatial coordinate point is converted into the potential energy height, and the vector direction determines the tilt orientation of the potential energy surface, outputting a three-dimensional thermodynamic potential energy surface.

[0043] Identify local potential well components to scan the thermodynamic potential energy surface. Regions with potential energy heights lower than the coordinates of the eight adjacent directions are marked as local potential wells. The potential well depth is quantized by the potential energy difference between the center point and the edge point. Output the set of potential well coordinates in the out-of-limit region.

[0044] The calculation component for the conduction resistance between potential wells is used to construct energy channels between adjacent potential wells. The energy loss value is integrated along the connection line of the potential energy surface. The loss value is equal to the product of the path length and the rate of change of the potential energy curvature. The output is the energy conduction resistance coefficient between the potential well pairs.

[0045] Generate a minimum resistance channel component to traverse the potential well connection combination, select a conduction path with no less than 3 series potential wells, calculate the total resistance coefficient of each path, and take the channel with the minimum total resistance coefficient as the thermodynamic phase change critical path.

[0046] Optionally, an energy flow anomaly topology system is used to collect in real time the microscopic deformation vibration spectrum of the power metering box, the internal gas ion mobility, and the electromagnetic field eddy current distribution through multi-source sensors; the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution are fused into a three-dimensional energy flow density topology map through unsteady field reconstruction; and an early warning signal for the embryonic stage of electric arc fault is generated based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map.

[0047] This invention provides a safety control method for multi-source data acquisition in an energy metering box, comprising the following steps:

[0048] The microscopic deformation vibration spectrum of the power metering box, the internal gas ion mobility, and the electromagnetic field eddy current distribution are collected in real time by multi-source sensors. The microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution are fused into a three-dimensional energy flow density topology map through unsteady field reconstruction. An early warning signal for the embryonic stage of electric arc fault is generated based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map.

[0049] It receives early warning signals of the embryonic stage of electric arc faults and simultaneously activates the enhanced scanning mode to apply a microsecond-level pulsed electric field to the surface of the insulating material, captures relaxation anomalies in the frequency domain response curve of dielectric constant, calculates the entropy increment of material molecular chain fracture by the relaxation peak offset of relaxation anomalies, and generates the medium fission level.

[0050] In the three-dimensional energy flow density topology map, the region exceeding the fission level is located. The critical path of thermodynamic phase change is calculated by combining the energy flow gradient. A reverse vortex field is injected along the critical path of thermodynamic phase change to counteract energy accumulation. At the same time, nanoscale aerogel is released to block the oxidation chain reaction.

[0051] This invention achieves early fault identification and proactive suppression of power metering boxes through multi-system collaboration. The energy flow anomaly topology system constructs a three-dimensional energy flow density topology map through multi-source sensor data fusion, and detects early characteristics of arc faults based on fractal dimension mutation rates, enabling non-contact identification of fault precursors. The dielectric fission entropy increase sensing system utilizes dielectric relaxation anomaly point analysis under pulsed electric field excitation to quantify the entropy increase process of molecular chain breakage in insulating materials, achieving precise classification of dielectric degradation and improving the reliability of fault assessment. The thermal runaway phase change blocking system counteracts energy accumulation through a reverse eddy current field and combines it with nano-aerogels to inhibit oxidation reactions, achieving thermodynamic balance control of the fault region and preventing thermal runaway propagation caused by local energy accumulation.

[0052] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0053] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0054] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0055] Figure 1 This is a block diagram of the safety control module for multi-source data acquisition in the power metering box in Embodiment 1 of the present invention;

[0056] Figure 2 This is a schematic diagram of the safety control module for multi-source data acquisition in the power metering box in Embodiment 1 of the present invention.

[0057] Figure 3 This is a block diagram of the energy flow anomaly topology system in Embodiment 2 of the present invention;

[0058] Figure 4 This is a block diagram of the dielectric fission entropy increase sensing system of Embodiment 4 of the present invention;

[0059] Figure 5 This is a block diagram of the thermal runaway phase transition blocking system in Embodiment 9 of the present invention;

[0060] Figure 6This is a flowchart of the safety control method for multi-source data acquisition of the power metering box in Embodiment 13 of the present invention. Detailed Implementation

[0061] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0062] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0063] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application. In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0064] Example 1: As Figure 1 As shown, this embodiment of the invention provides a safety control module for multi-source data acquisition in an energy metering box, comprising:

[0065] An energy flow anomaly topology system is used to collect the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution of an energy metering box in real time through multi-source sensors; the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution are fused into a three-dimensional energy flow density topology map through unsteady field reconstruction; and an early warning signal for the embryonic stage of an electric arc fault is generated based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map.

[0066] The dielectric fission entropy increase sensing system is used to receive early warning signals of the embryonic stage of electric arc faults. At the same time, it activates the enhanced scanning mode, applies a microsecond-level pulsed electric field to the surface of the insulating material, captures relaxation anomalies in the frequency domain response curve of the dielectric constant, calculates the entropy increase of material molecular chain fracture by the relaxation peak shift of the relaxation anomalies, and generates the dielectric fission level.

[0067] The thermal runaway phase change blocking system is used to locate the region exceeding the fission level in a three-dimensional energy flow density topology map, calculate the thermodynamic phase change critical path by combining energy flow gradient, inject a reverse vortex field along the thermodynamic phase change critical path to counteract energy accumulation, and release nanoscale aerogel to block the oxidation chain reaction.

[0068] The working principle and beneficial effects of the above technical solution are as follows: The energy flow anomaly topology system of this embodiment collects the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution of the power metering box in real time through multi-source sensors; it integrates the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution into a three-dimensional energy flow density topology map through unsteady field reconstruction; it generates an early warning signal for the embryonic stage of an electric arc fault based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map; the dielectric fission entropy increase sensing system receives the early warning signal for the embryonic stage of an electric arc fault and simultaneously activates the enhanced scanning mode to apply a microsecond-level pulsed electric field to the surface of the insulating material, captures the relaxation anomaly point in the frequency domain response curve of the dielectric constant, calculates the entropy increase of the material molecular chain fracture through the relaxation peak shift of the relaxation anomaly point, and generates the dielectric fission level; the thermal runaway phase change blocking system locates the region exceeding the fission level limit in the three-dimensional energy flow density topology map, calculates the thermodynamic phase change critical path in combination with the energy flow gradient, injects a reverse eddy current field along the thermodynamic phase change critical path to counteract energy accumulation, and simultaneously releases nanoscale aerogel to block the oxidation chain reaction (the specific principle is as follows). Figure 2 (As shown). The above scheme achieves early fault identification and active suppression of the power metering box through multi-system collaboration; the energy flow anomaly topology system constructs a three-dimensional energy flow density topology map through multi-source sensor data fusion, and detects early characteristics of arc faults based on fractal dimension mutation rate, realizing non-contact identification of fault precursors. The dielectric fission entropy increase sensing system uses dielectric relaxation anomaly point analysis under pulsed electric field excitation to quantify the entropy increase process of molecular chain breakage in insulating materials, realizes accurate classification of dielectric degradation, and improves the reliability of fault assessment. The thermal runaway phase change blocking system cancels energy accumulation through reverse eddy current field and combines it with nano-aerogel to inhibit oxidation reaction, realizing thermodynamic balance control of the fault area and preventing thermal runaway propagation caused by local energy accumulation.

[0069] In summary, this embodiment forms a closed-loop control structure of monitoring-evaluation-suppression, which intervenes before a fault fully develops, reducing the safety risks to the power metering box caused by electric arcs or insulation deterioration.

[0070] Example 2: Figure 3 As shown, based on Embodiment 1, the energy flow anomaly topology system provided in this embodiment of the invention includes:

[0071] The preprocessing subsystem is used to convert the micro-deformation vibration spectrum of the box into spatial oscillation boundary conditions, map the internal gas ion mobility into the trajectory of energy-carrying particles, and calibrate the basic energy deposition location by electromagnetic field eddy current distribution.

[0072] The data coupling subsystem is used to constrain the three types of data in a time-varying field through dynamic coupling: the spatial oscillation boundary condition modulates the diffusion range of the energy-carrying particle trajectory, the energy-carrying particle motion trajectory modulates the aggregation intensity of the energy deposition location, and the energy deposition location is fed back to the spatial boundary deformation rate to generate a three-dimensional energy flux density topology map with fractal growth characteristics.

[0073] The mutation point identification subsystem is used to identify accelerated mutation points of the fractal structure dimension in the three-dimensional energy flow density topology map within a continuous time window. When the mutation rate exceeds the material entropy increase bearing limit, an early warning signal for the embryonic stage of electric arc fault is generated.

[0074] The working principle and beneficial effects of the above technical solution are as follows: The preprocessing subsystem of this embodiment is used to convert the microscopic deformation vibration spectrum of the box into spatial oscillation boundary conditions, and the internal gas ion mobility is mapped to the trajectory of the energy-carrying particles. The electromagnetic field eddy current distribution is used to calibrate the basic energy deposition position. The data coupling subsystem is used to constrain the three types of data in the time-varying field through dynamic coupling: the spatial oscillation boundary conditions correct the diffusion range of the energy-carrying particle trajectory, the energy-carrying particle trajectory modulates the aggregation intensity of the energy deposition position, and the energy deposition position is fed back to the spatial boundary deformation rate to generate a three-dimensional energy flux density topology map with fractal growth characteristics. The mutation point identification subsystem is used to identify the accelerated mutation points of the fractal structure dimension in the topology map within a continuous time window. When the mutation rate exceeds the material entropy increase bearing limit, an early warning signal for the embryonic stage of electric arc fault is generated. The above scheme achieves topological reconstruction of energy flow through multi-level dynamic coupling. The spatial oscillation boundary conditions output by the preprocessing subsystem serve as the initial constraint framework, and the fluctuation frequency gradient of this framework directly determines the diffusion threshold of the energy-carrying particle trajectory. When the particle swarm migrates in the time-varying field, its path spontaneously forms a probability density cloud. The expansion coefficient of the cloud is dynamically suppressed by the maximum curvature point in the boundary conditions, thus forming a non-uniform diffusion mode in the three-dimensional field. Subsequently, the aggregated distribution of the energy-carrying particle swarm triggers the self-organizing behavior of energy deposition sites. The activation intensity of each deposition point has a non-linear response relationship with the local concentration of the particle cloud. Deposition points in high-density areas will generate a chain polarization effect. The polarization effect is not uniformly transmitted, but forms an energy conduction network along the fractal edge of the particle cloud. The energy accumulation rate at the network nodes will react on the original boundary deformation field. The boundary deformation field undergoes topological reconstruction under the feedback of the energy network, and the reconstruction direction is determined by the polarization principal axis of the deposition point group. The reconstructed boundary will generate new curvature extrema, which will become the source of the next round of particle diffusion constraints. After three iterations of coupling, the system emerges with a dynamic equilibrium structure with self-similar characteristics. At this time, the energy flux density exhibits a stable fractal growth mode in the three-dimensional field.

[0075] In summary, in this embodiment, the spatial oscillation boundary, particle trajectory, and energy deposition location form a closed-loop evolution system. The output of each subsystem is precisely converted into the control parameters for the next stage, and the conversion process follows nonlinear dynamic constraints. When the system detects a sudden change in the second derivative of the fractal dimension within a continuous time window, it is determined to be the critical point of the material's entropy increase bearing limit. At this point, the topological structure of energy flow will undergo an irreversible phase transition.

[0076] Example 3: Based on Example 2, the data coupling subsystem provided in this embodiment of the invention includes:

[0077] The energy-carrying particle trajectory correction component is used to apply the generated spatial oscillation boundary conditions to the trajectory of the energy-carrying particles, compressing the particle diffusion range into the deformation boundary envelope region in real time. The instantaneous increase in deformation amplitude directly reduces the distribution radius of the particle trajectory, forming a dynamic spatial constraint field.

[0078] An energy deposition intensity modulation component is used to superimpose energy levels between the compressed energy-carrying particle trajectory and the basic energy deposition location: the increase in particle trajectory density per unit volume triggers a nonlinear increase in energy accumulation intensity at the deposition location; the local accumulation of particle trajectories directly enhances the energy level amplitude of the corresponding eddy current hot spot.

[0079] The boundary deformation rate feedback component is used to generate reverse feedback at the enhanced energy deposition location: the high-energy deposition zone uses the Lorentz force to infer the deformation acceleration of the spatial oscillation boundary; for each threshold increase in the deposition energy level, the boundary deformation rate increases by a corresponding gradient level, forming a positive feedback loop of deformation and energy.

[0080] The fractal topology generation component is used for iterative looping within a millisecond time window: the corrected particle trajectory continuously updates the energy deposition intensity, the updated deposition intensity drives the boundary deformation acceleration in real time, and the accelerated deformation further compresses the particle trajectory range; enabling the three types of data to achieve dynamic equilibrium in the time-varying field, and finally outputting a three-dimensional energy flow density topology map with a self-similar branching structure, whose fractal dimension is determined by the iteration ratio of energy feedback intensity and boundary constraint force.

[0081] The working principle and beneficial effects of the above technical solution are as follows: The energy-carrying particle trajectory correction component in this embodiment is used to apply the generated spatial oscillation boundary conditions to the trajectory of the energy-carrying particles, compressing the particle diffusion range into the deformation boundary envelope region in real time. The instantaneous increase in deformation amplitude directly reduces the distribution radius of the particle trajectory, forming a dynamic spatial constraint field. The energy deposition intensity modulation component is used to superimpose the energy levels of the compressed energy-carrying particle trajectory and the basic energy deposition position: the increase in particle trajectory density per unit volume triggers a nonlinear increase in the energy accumulation intensity at the deposition position; the local accumulation of particle trajectories directly enhances the energy level amplitude of the corresponding eddy current hot spot; the boundary deformation rate feedback component is used to increase... The enhanced energy deposition location generates reverse feedback: the high-energy deposition zone uses the Lorentz force to infer the deformation acceleration of the spatial oscillation boundary; for each threshold increase in deposition energy level, the boundary deformation rate increases by a corresponding gradient level, forming a positive feedback loop of deformation and energy; the fractal topology generation component is used for iterative cycling within a millisecond time window: the corrected particle trajectory continuously updates the energy deposition intensity, and the updated deposition intensity drives the boundary deformation acceleration in real time, which further compresses the particle trajectory range; enabling the three types of data to achieve dynamic equilibrium in the time-varying field, ultimately outputting a three-dimensional energy flow density topology map with a self-similar branching structure, the fractal dimension of which is determined by the iteration ratio of energy feedback intensity and boundary constraint force. The above scheme achieves precise topological control of energy flow through multi-level dynamic closed-loop control. The establishment of a dynamic spatial constraint field: the spatial oscillation boundary conditions compress the diffusion range of energy-carrying particles in real time, ensuring that the particle trajectory is always controlled within the envelope of the current deformation amplitude, ensuring that the energy transport process is always within the calculable physical boundary. Enhanced Nonlinear Energy Accumulation: The increased particle trajectory density after compression directly modulates the energy level distribution at the energy deposition site, causing the eddy current intensity of local hotspots to increase exponentially with particle aggregation, forming a controllable high-energy deposition zone. Deformation-Energy Positive Feedback Cycle: The enhanced energy deposition reacts to the boundary deformation rate through the Lorentz force, causing the system to enter a self-excited oscillation state. The deposition energy level and deformation acceleration form a stable gradient coupling relationship, preventing uncontrolled energy dissipation. Adaptive Generation of Fractal Topology: Through millisecond-level iterative cycles, particle trajectory correction, energy deposition modulation, and boundary deformation feedback form a dynamic balance. The final output three-dimensional energy flux density topology map exhibits a stable self-similar branching structure, with its fractal dimension determined by the dynamic ratio of energy feedback intensity to boundary constraint force, ensuring the system maintains optimal energy distribution before the critical threshold.

[0082] In summary, this embodiment achieves high-precision dynamic control of energy flow in a time-varying field, enabling the system to maintain a stable fractal energy topology under complex boundary conditions, and providing quantifiable physical evidence for anomaly detection.

[0083] Example 4: Figure 4As shown, based on Embodiment 1, the dielectric fission entropy increase sensing system provided in this embodiment of the invention includes:

[0084] The frequency domain response excitation subsystem is used to apply a microsecond-level pulsed electric field to the surface of the insulating material after the enhanced scanning mode is activated by the early warning signal of the arc fault embryo stage, so as to cause the molecular chain of the material to oscillate under forced conditions. The electric field strength of the microsecond-level pulsed electric field is strictly controlled below the dielectric saturation threshold, and only non-destructive polarization response is excited.

[0085] The relaxation anomaly point capture subsystem is used to acquire the dielectric constant frequency domain response curve in real time during forced oscillation and detect its anomalous frequency shift characteristics: the relaxation peak of normal molecular chains presents a symmetrical broad peak shape, while molecular chains with pre-fracture will generate relaxation anomalies in a specific frequency band, which are manifested as asymmetrical sharp peaks on the side of the main peak.

[0086] The relaxation peak shift calculation subsystem is used to compare the detected relaxation anomalies with the reference positions of the intrinsic relaxation spectrum of the material and quantify the shift distance of their frequency axis. The relaxation peak shift directly reflects the degree of obstruction of dipole moment rearrangement within the molecular chain segment. The larger the shift, the more severe the loss of the chain segment's degrees of freedom.

[0087] The molecular chain fracture entropy value conversion subsystem is used to calculate the entropy value based on the relaxation peak shift. Each unit shift distance corresponds to a specific order of magnitude of molecular chain conformational entropy loss. The conformational entropy loss value is superimposed on the abrupt increment of the bond rotation energy barrier. The product of the two generates the molecular chain fracture entropy value, establishing a quantitative mapping between frequency shift and molecular-scale energy dissipation.

[0088] The medium fission level generation subsystem is used to classify fission levels according to the threshold range of the entropy increase of molecular chain fracture in materials.

[0089] First-order fission: Entropy increase < chain segment untangling limit, local stress concentration in molecular chain; Second-order fission: Entropy increase ≥ untangling limit but < main chain fracture threshold, multiple chain segments co-rigidify; Third-order fission: Entropy increase ≥ main chain fracture threshold, covalent bond breakage begins.

[0090] The working principle and beneficial effects of the above technical solution are as follows: The frequency domain response excitation subsystem of this embodiment is used to apply a microsecond-level pulsed electric field to the surface of the insulating material after the arc fault embryonic stage early warning signal activates the enhanced scanning mode, causing the material molecular chains to generate forced oscillations; the electric field strength of the microsecond-level pulsed electric field is strictly controlled below the dielectric saturation threshold, and only non-destructive polarization response is excited; the relaxation anomaly point capture subsystem is used to collect the dielectric constant frequency domain response curve in real time during the forced oscillation process and detect its anomalous frequency shift characteristics: the relaxation peak of the normal molecular chain presents a symmetrical broad peak shape, while the molecular chain with pre-fracture will generate relaxation anomalies in a specific frequency band, which is manifested as asymmetrical sharp peaks on the flanks of the main peak; the relaxation peak offset calculation subsystem is used to compare the detected relaxation anomalies with the reference position of the intrinsic relaxation spectrum of the material and quantify the offset of its frequency axis. The shift distance; the relaxation peak shift directly reflects the degree of obstruction to dipole moment rearrangement within the molecular chain segment. The larger the shift, the more severe the loss of the chain segment's degrees of freedom. The molecular chain fracture entropy value conversion subsystem is used to calculate the entropy value based on the relaxation peak shift. Each unit shift distance corresponds to a specific order of magnitude of molecular chain conformational entropy loss. The conformational entropy loss value is superimposed on the abrupt increase of the bond rotation energy barrier. The product of the two generates the material's molecular chain fracture entropy value, establishing a quantitative mapping between frequency shift and molecular-scale energy dissipation. The medium fission level generation subsystem is used to classify the fission level according to the threshold range of the material's molecular chain fracture entropy value. First-level fission: entropy value < chain segment untangling limit, local stress concentration in the molecular chain; Second-level fission: entropy value ≥ untangling limit but < main chain fracture threshold, multiple chain segments co-rigidify; Third-level fission: entropy value ≥ main chain fracture threshold, covalent bond fracture begins. The above scheme achieves early quantitative warning of molecular chain fracture through non-destructive dielectric response analysis. A second-level pulsed electric field excites forced oscillations of the material's molecular chains below the dielectric saturation threshold, avoiding insulation damage while ensuring the signal-to-noise ratio of the relaxation response signal meets detection requirements. By real-time monitoring of the dielectric constant frequency domain response curve, anomalous frequency shift characteristics (asymmetric spikes) are identified, transforming the pre-fracture state of the molecular chains into quantifiable relaxation anomaly signals. The relaxation peak shift is directly related to the degree of obstruction to dipole moment rearrangement; the loss of chain segment motion degrees of freedom is calculated through the frequency shift distance, establishing a correlation model between microscopic motion restriction and macroscopic dielectric response. The relaxation peak shift is converted into molecular chain conformational entropy loss and bond rotation energy barrier increment, generating fracture entropy increment, realizing the conversion of dielectric signal into a physical quantity of molecular-scale energy dissipation. Based on the comparison results of entropy increment with chain segment untangling limit and main chain fracture threshold, a three-level fission warning is output, providing a graded criterion for the degradation state of insulating materials.

[0091] In summary, this embodiment achieves a quantitative assessment of the entropy increase process before molecular chain breakage by non-destructive testing of frequency domain dielectric response characteristics, providing a microscale criterion for early warning of insulation material failure.

[0092] Example 5: Based on Example 4, the molecular chain fracture entropy increment conversion subsystem provided in this embodiment of the invention includes:

[0093] The offset conversion component is used to convert the relaxation peak offset into the molecular chain conformational entropy loss value proportionally. The number of conformational states decreases by a fixed proportion for each unit frequency offset. For every additional reference unit of offset distance, the conformational space of the movable chain segment is reduced by one discrete gradient.

[0094] The component for detecting bond rotation barrier mutations is used to extract barrier features at the same relaxation anomaly point. Normal relaxation peaks correspond to smooth barrier distributions, and the appearance of asymmetric spikes indicates the increment of bond rotation barrier mutations. The increment magnitude is quantified by the ratio of the peak half-width to the main peak width.

[0095] The fracture entropy increment generation component is used to multiply the conformational entropy loss value with the bond rotation energy barrier mutation increment. The conformational entropy loss characterizes the degree of molecular chain flexibility degradation, and the energy barrier mutation increment reflects the covalent bond twisting potential energy step. The multiplication operation causes the two to produce an energy coupling effect.

[0096] A component for establishing molecular-scale dissipation mapping is used to directly correlate the increase in fracture entropy with the inherent limitation of molecular motion. The increase in entropy is linearly proportional to the power of frictional heat dissipation within the chain segment. Each unit increase in entropy corresponds to a specific order of magnitude of molecular kinetic energy decay rate, thus completing the quantitative mapping from frequency shift to molecular-scale energy dissipation.

[0097] The working principle and beneficial effects of the above technical solution are as follows: The offset conversion component in this embodiment is used to convert the relaxation peak offset into the molecular chain conformational entropy loss value proportionally. The unit frequency offset corresponds to a fixed proportion of the decay of the number of conformational states. For every additional reference unit of offset distance, the conformational space of the movable chain segment is reduced by one discrete gradient. The bond rotation barrier mutation detection component is used to extract barrier features at the same relaxation anomaly point. The normal relaxation peak corresponds to a smooth barrier distribution. The appearance of the asymmetric peak indicates the increment of the bond rotation barrier mutation. The increment amplitude is determined by the ratio of the peak half-width to the main peak width. Peak width ratio quantification; the fracture entropy increment generation component is used to multiply the conformational entropy loss value with the bond rotation energy barrier mutation increment. The conformational entropy loss characterizes the degree of molecular chain flexibility degradation, and the energy barrier mutation increment reflects the covalent bond twisting potential energy step. The product operation makes the two produce an energy coupling effect; the molecular scale dissipation mapping establishment component is used to directly relate the fracture entropy increment to the nature of molecular motion restriction. The entropy increment is linearly proportional to the frictional heat dissipation power within the chain segment. Each unit of entropy increment corresponds to a specific order of magnitude of molecular kinetic energy decay rate, completing the quantitative mapping from frequency shift to molecular scale energy dissipation. The above scheme transforms the relaxation peak shift into a quantitative index of molecular-scale energy dissipation and establishes a correlation model between dielectric response and microscopic fracture mechanism. It converts the relaxation peak shift into molecular chain conformational entropy loss through a linear proportional relationship, directly reflecting the degree of reduction in the conformational space of movable chain segments and characterizing the degradation of molecular chain flexibility. It extracts the energy barrier abrupt change increment using the asymmetric peak characteristics of relaxation anomalies, and quantifies the step amplitude of covalent bond twisting potential energy using the ratio of half-width at half-maximum (WHM) to main peak width. The product operation of conformational entropy loss and bond rotation energy barrier abrupt change reflects their synergistic effect; the fracture entropy increase simultaneously encompasses the loss of chain segment motion degrees of freedom and the degradation of covalent bond stability. The entropy increase is linearly related to the frictional heat dissipation power within the chain segment, directly correlated with the molecular kinetic energy decay rate, realizing the physical quantity conversion from frequency domain signal to molecular-scale energy dissipation.

[0098] In summary, this embodiment transforms dielectric relaxation anomalies into energy dissipation indices for molecular chain breakage by coupling conformational entropy with bond rotation energy barriers, providing quantifiable thermodynamic criteria for the microscopic damage mechanism of materials.

[0099] Example 6: Based on Example 5, the fracture entropy increment generation component provided in this embodiment of the invention includes:

[0100] The quantification of flexibility degradation degree sub-component is used to convert the molecular chain conformation entropy loss value output by the offset conversion component into a flexibility degradation coefficient. The reduction of conformation space for each discrete gradient corresponds to an increase of one order of magnitude in the chain segment flexural modulus. The larger the entropy loss value, the steeper the slope of the molecular chain rigidity growth.

[0101] Degree of molecular chain flexibility degradation = entropy loss value × intrinsic flexural conversion factor;

[0102] The calibration potential energy step intensity sub-component is used to convert the mutation increment output by the detection bond rotation energy barrier mutation component into a potential energy distortion variable. The energy barrier increment amplitude corresponds to the covalent bond angle distortion threshold. For each increment value exceeding the reference unit, the bonded electron cloud deformation barrier is raised by one energy level.

[0103] Covalent bond twisting potential energy step = sudden change increment × bond angle distortion coefficient;

[0104] A fracture energy coupling effect sub-component is generated to multiply the degree of flexibility degradation of the molecular chain with the step of covalent bond distortion potential energy. The degree of flexibility degradation weakens the stress dissipation ability of the molecular chain, and the potential energy step exacerbates the accumulation of local bond distortion, resulting in the increase of molecular chain fracture entropy.

[0105] The working principle and beneficial effects of the above technical solution are as follows: The quantification of flexibility degradation degree sub-component in this embodiment is used to convert the molecular chain conformation entropy loss value output by the offset conversion component into a flexibility degradation coefficient. The reduction of conformation space for each discrete gradient corresponds to an increase of one order of magnitude in the chain segment flexural modulus. The larger the entropy loss value, the steeper the slope of the molecular chain rigidity growth. Molecular chain flexibility degradation degree = entropy loss value × intrinsic flexural conversion factor; The calibration of potential energy step intensity sub-component is used to convert the mutation increment output by the detection of bond rotation energy barrier mutation component into a potential energy distortion variable. The magnitude of the energy barrier increment corresponds to the covalent bond angle distortion threshold. For each increment value exceeding the reference unit, the bonding electron cloud deformation barrier increases by one energy level; Covalent bond distortion potential energy step = mutation increment × bond angle distortion coefficient; The generation of fracture energy coupling effect sub-component is used to multiply the molecular chain flexibility degradation degree by the covalent bond distortion potential energy step. The flexibility degradation degree weakens the stress dissipation ability of the molecular chain, and the potential energy step intensifies the accumulation of local bonding distortion, generating a molecular chain fracture entropy increment. The above scheme achieves precise control of entropy change and energy coupling calculation in the fracture process of polymer materials through the synergistic effect of three sub-components. The sub-component for quantifying the degree of flexibility degradation constructs a quantitative mapping relationship between the molecular chain conformational entropy loss value and macroscopic mechanical properties. Through a discrete gradient transformation algorithm, it converts the conformational space reduction into the chain segment flexural modulus increment, establishing a continuous descriptive model of the transformation from an entropy-elastic body to a rigid body, achieving linear coupling between molecular chain flexibility and conformational entropy. The sub-component for calibrating the potential energy step intensity uses the bond rotation energy barrier differential to quantify the bond angle distortion threshold into a potential energy step value, accurately characterizing the anharmonic distortion of the potential energy field caused by covalent bond distortion. The sub-component for generating fracture energy coupling effects achieves energy coupling between the molecular chain scale and the bonding scale, causing the fracture activation energy to exhibit an exponential increase.

[0106] In summary, this embodiment forms a complete fracture entropy change control system: conformational entropy loss reduces the molecular chain configuration degree of freedom, bond rotation is hindered to induce potential energy step, and multi-scale energy coupling generates a nonlinear fracture threshold.

[0107] Example 7: Based on Example 6, the quantification of flexibility degradation degree sub-component provided in this embodiment of the invention includes:

[0108] The discrete gradient analysis module is used to receive the molecular chain conformational entropy loss value output by the offset conversion component and extract the discrete gradient reduction series contained therein; each discrete gradient corresponds to the annihilation of a specific set of motion degrees of freedom in the molecular chain conformational state space.

[0109] The flexural modulus transition mapping module is used to map discrete gradient reduction series to a rigid growth sequence of chain segments. Each time a gradient is annihilated, the flexural modulus of the corresponding chain segment increases by a fixed order of magnitude. As the gradient reduction series increases, the modulus growth exhibits an exponential acceleration characteristic.

[0110] Rigid growth slope = gradient reduction series × modulus step constant;

[0111] The module for generating the flexibility degradation coefficient is used to multiply the stiffness growth slope by the intrinsic flexural conversion factor. The stiffness growth slope reflects the rate of change of chain segment stiffness, while the intrinsic flexural conversion factor reflects the initial compliance characteristics of the material. The product of the two generates the flexibility degradation coefficient.

[0112] The working principle and beneficial effects of the above technical solution are as follows: The discrete gradient analysis module of this embodiment is used to receive the molecular chain conformational entropy loss value output by the offset conversion component and extract the discrete gradient reduction series contained therein; each discrete gradient corresponds to the annihilation of a specific set of motion degrees of freedom in the conformational state space of the molecular chain; the flexural modulus transition mapping module is used to map the discrete gradient reduction series to the chain segment rigidity growth sequence. Each annihilation of a gradient corresponds to a fixed increase in the chain segment flexural modulus. When the gradient reduction series increases, the modulus growth exhibits an exponential acceleration characteristic; the rigidity growth slope = gradient reduction series × modulus step constant; the flexible degradation coefficient generation module is used to multiply the rigidity growth slope by the intrinsic flexural conversion factor. The rigidity growth slope reflects the rate of change of chain segment stiffness, and the intrinsic flexural conversion factor carries the initial compliance characteristics of the material. The product of the two generates the flexible degradation coefficient. The above solution realizes the quantitative prediction of the evolution of molecular chain flexibility through conformational entropy loss, discrete gradient reduction, flexural modulus transition, and flexible degradation coefficient generation; and provides a theoretical calculation basis for the entropy regulation of the mechanical properties of polymer materials.

[0113] Example 8: Based on Example 6, the calibration potential energy step intensity sub-component provided in this embodiment of the invention includes:

[0114] The barrier mutation increment module is used to receive the mutation increment output by the detection bond rotation barrier mutation component, extract the order of exceedance of the reference unit, and each order of exceedance corresponds to the number of stages in which the bond rotation degrees of freedom are locked.

[0115] The bond angle distortion threshold mapping module is used to convert the exceedance level into the bond angle distortion stage. Each stage lock reduces the covalent bond angle tolerance threshold by a fixed proportion. When the exceedance level increases, the bond angle distortion exhibits a step-like transition.

[0116] Bond angle distortion = Exceeding order of magnitude × Intrinsic bond angle tolerance coefficient;

[0117] An electron cloud deformation barrier module is generated to calibrate the potential energy step based on the bond angle distortion degree. For each increase of the bond angle distortion degree, the electron cloud orbital overlap area is reduced by a corresponding proportion. The amount of orbital overlap reduction is directly converted into the height of the electron cloud deformation barrier.

[0118] Potential energy step height = bond angle distortion × orbital coupling attenuation factor;

[0119] The potential energy distortion module is used to multiply the potential energy step height by the bond angle distortion coefficient. The potential energy step height reflects the single bond twisting energy, and the bond angle distortion coefficient carries the rigidity characteristics of the molecular skeleton, thus generating a covalent bond twisting potential energy distortion variable.

[0120] The working principle and beneficial effects of the above technical solution are as follows: The analytical barrier mutation increment module in this embodiment is used to receive the mutation increment output by the detection bond rotation barrier mutation component, extract the transcendence level of the reference unit, and each transcendence level corresponds to the number of stages in which the bond rotation degrees of freedom are locked; the bond angle distortion threshold mapping module is used to convert the transcendence level into bond angle distortion stages, and each stage lock reduces the covalent bond angle tolerance threshold by a fixed proportion. When the transcendence level increases, the bond angle distortion exhibits a step-like transition; bond angle distortion degree = transcendence level × intrinsic bond angle. The tolerance coefficient; the electron cloud deformation barrier generation module is used to calibrate the potential energy step based on the bond angle distortion degree. For each increase in the bond angle distortion degree, the electron cloud orbital overlap area is reduced by a corresponding proportion. The reduction in orbital overlap is directly converted into the increase in the electron cloud deformation barrier height; the potential energy step height = bond angle distortion degree × orbital coupling attenuation factor; the potential energy distortion variable synthesis module is used to multiply the potential energy step height by the bond angle distortion coefficient. The potential energy step height reflects the single bond twisting energy, and the bond angle distortion coefficient carries the rigidity characteristics of the molecular skeleton, generating the covalent bond twisting potential energy distortion variable. The above scheme achieves accurate calibration of the covalent bond twisting potential energy through the collaborative calculation of barrier mutation analysis and bond angle distortion mapping. The specific technical effects are as follows: the barrier mutation increment analysis module quantifies the bond rotation barrier mutation increment into discrete orders of magnitude exceeding the reference unit. Each order of magnitude corresponds to the number of stages in which the bond rotation degrees of freedom are locked, establishing a step-like mapping relationship. The bond angle distortion threshold mapping module uses a tolerance reduction model to convert the magnitude of the distortion into bond angle distortion stages. Locking at each stage causes the bond angle tolerance threshold to decay, reflecting the geometric constraint strengthening effect caused by hindered bond rotation. The electron cloud deformation barrier generation module, based on orbital overlap theory, converts the bond angle distortion degree into a potential energy step height, quantifying the increase in electron cloud repulsion energy caused by bond angle distortion. The potential energy distortion synthesis module generates the final distortion variable through multiplication operations, forming a complete description of the potential energy distortion.

[0121] Example 9: As Figure 5 As shown, based on Example 1, the thermal runaway phase transition blocking system provided in this embodiment of the invention includes:

[0122] The subsystem for locating the fission exceedance region is used to map the dielectric fission level output by the dielectric fission entropy increase sensing system to a three-dimensional energy flux density topology map. Regions with a fission level of not less than level two are marked as exceedance coordinate clusters. The exceedance coordinate clusters coincide with the energy deposition peak area in the topology map for verification, and the fission-energy coupling focus coordinate set is output.

[0123] Extract the energy flow gradient field subsystem to analyze the three-dimensional energy flow density topology map within the range of the coupled focus coordinate set, obtain the spatial rate of change of energy density per unit volume, calibrate the energy conduction principal axis along the direction of the maximum rate of change, and output the energy flow gradient vector matrix.

[0124] The critical path calculation subsystem is used to construct a thermodynamic potential field based on the energy flow gradient vector matrix. The convergence point of the gradient vector forms a local potential well. The lowest energy channel connecting adjacent potential wells is the thermodynamic critical path of phase transition. The output is the path with the minimum resistance to energy conduction connecting the overlimit region.

[0125] An inverse eddy current field subsystem is injected to generate canceling eddies along the critical path of phase transition, extract the original electromagnetic field eddy current distribution pattern of the region through which the path passes, generate an inverse eddy current field distribution with a phase difference of 180°, and output a eddy current field that directionally cancels the energy accumulation.

[0126] Reverse field strength = Original field strength × (fission level / third-order fission threshold).

[0127] The working principle and beneficial effects of the above technical solution are as follows: The positioning fission over-limit region subsystem of this embodiment is used to map the dielectric fission level output by the dielectric fission entropy increase sensing system to a three-dimensional energy flux density topology map. Regions with fission levels not less than level two are marked as over-limit coordinate clusters. The over-limit coordinate clusters coincide with the energy deposition peak region in the topology map for verification, and the fission-energy coupling focus coordinate set is output. The energy flux gradient field extraction subsystem is used to analyze the three-dimensional energy flux density topology map within the range of the coupling focus coordinate set, obtain the spatial rate of change of energy density per unit volume, calibrate the energy conduction principal axis along the direction of the maximum rate of change, and output the energy flux gradient field. The flow gradient vector matrix is ​​used to construct a thermodynamic potential field based on the energy flow gradient vector matrix. The convergence point of the gradient vector forms a local potential well, and the lowest energy channel connecting adjacent potential wells is the thermodynamic phase transition critical path. The output is the path with the least resistance to energy conduction connecting the over-limit region. The reverse eddy field injection subsystem is used to generate offsetting eddies along the phase transition critical path, extract the original electromagnetic field eddy current distribution pattern of the path through the region, generate a reverse eddy current field distribution with a phase difference of 180°, and output a directional eddy current field to offset energy accumulation. The reverse field strength = original field strength × (fission level / third-level fission threshold). The above scheme achieves active suppression of energy accumulation region through multi-physics field coupling control of thermodynamic and electromagnetic fields. The specific technical effects are as follows: The fission over-limit region positioning subsystem uses threshold screening and spatial matching algorithms to verify the spatial coincidence of the medium fission level and the peak energy flow density region, and outputs a high-confidence fission-energy coupling coordinate set to provide a target domain for subsequent gradient field extraction. The energy flow gradient field extraction subsystem obtains the spatial rate of change of energy density using a three-dimensional gradient operator, and uses eigenvalue decomposition to determine the direction of the maximum rate of change, generating a gradient vector matrix to quantify the preferred energy conduction path. The phase transition critical path calculation subsystem constructs a thermodynamic potential field based on the gradient vector matrix, identifies local minima, and searches for and outputs the minimum energy path connecting the over-limit regions, reflecting the optimal dynamic channel for the system's spontaneous phase transition. The reverse eddy current field injection subsystem, based on the principle of electromagnetic field superposition, first extracts the original eddy current field distribution, then generates a phase reversal field to achieve electromagnetic cancellation of energy accumulation.

[0128] Example 10: Based on Example 9, the subsystem for calculating the critical phase transition path provided in this embodiment of the invention includes:

[0129] A thermodynamic potential field component is constructed to convert the energy flow gradient vector matrix output by the energy flow gradient field subsystem into a scalar potential. The gradient vector modulus of each spatial coordinate point is converted into the potential energy height, and the vector direction determines the tilt orientation of the potential energy surface, outputting a three-dimensional thermodynamic potential energy surface.

[0130] Identify local potential well components to scan the thermodynamic potential energy surface. Regions with potential energy heights lower than the coordinates of the eight adjacent directions are marked as local potential wells. The potential well depth is quantized by the potential energy difference between the center point and the edge point. Output the set of potential well coordinates in the out-of-limit region.

[0131] The calculation component for the conduction resistance between potential wells is used to construct energy channels between adjacent potential wells. The energy loss value is integrated along the connection line of the potential energy surface. The loss value is equal to the product of the path length and the rate of change of the potential energy curvature. The output is the energy conduction resistance coefficient between the potential well pairs.

[0132] Generate a minimum resistance channel component to traverse potential well connection combinations, select a conduction path with ≥3 series potential wells, calculate the total resistance coefficient of each path, and take the channel with the minimum total resistance coefficient as the thermodynamic phase change critical path.

[0133] The working principle and beneficial effects of the above technical solution are as follows: The thermodynamic potential field construction component in this embodiment is used to convert the energy flow gradient vector matrix output by the energy flow gradient field extraction subsystem into a scalar potential. The gradient vector modulus of each spatial coordinate point is converted into potential energy height. The vector direction determines the tilt orientation of the potential energy surface, and a three-dimensional thermodynamic potential energy surface is output. The local potential well identification component is used to scan the thermodynamic potential energy surface. Regions with potential energy heights lower than those of the eight adjacent directional coordinates are marked as local potential wells. The potential well depth is quantized by the potential energy difference between the center point and the edge point, and the potential well coordinate set in the overlimit region is output. The potential well conduction resistance calculation component is used to construct energy channels between adjacent potential wells and integrate the conduction energy loss value along the potential energy surface connection line. The loss value is equal to the product of the path length and the rate of change of potential energy curvature, and the energy conduction resistance coefficient between potential well pairs is output. The minimum resistance channel generation component is used to traverse the potential well connection combination, select conduction paths with a series potential well number ≥ 3, calculate the total resistance coefficient of each path, and take the channel with the smallest total resistance coefficient as the thermodynamic phase change critical path. The above scheme forms an analytical chain of potential field construction, potential well identification, resistance calculation, and path optimization. The output result is the minimum energy dissipation channel connecting the overlimit region and its quantified resistance value, providing a precise dynamic intervention target for phase transition blocking.

[0134] Example 11: Based on Example 10, the minimum resistance channel generation component provided in this embodiment of the invention includes:

[0135] Construct adjacent potential well pair sub-components to receive and identify the potential well coordinate set output by the local potential well component, generate potential well connection pairs according to spatial adjacency, and each potential well connection pair constitutes the basic segmented unit of the energy conduction path;

[0136] The single-segment conduction loss value extraction sub-component is used to extract the conduction energy loss value corresponding to the current potential well pair from the resistance coefficient set output by the inter-potential well conduction resistance component. The conduction energy loss value already includes the coupling effect of path length and potential energy curvature change.

[0137] The cumulative resistance calculation sub-component is used for conduction paths with ≥3 series potential wells. It sequentially reads all adjacent potential well pairs contained in the path, sums up the conduction energy loss values ​​of each potential well pair, and outputs the cumulative path loss value.

[0138] A path tortuosity factor sub-component is introduced to calculate the geometric tortuosity of the path, measure the straight-line distance between the first and last potential wells of the path, calculate the ratio of the actual path length to the straight-line distance, and use the square of the ratio as the tortuosity factor;

[0139] The total drag coefficient sub-component is generated by multiplying the cumulative path loss value by the tortuosity factor. The cumulative loss value represents the total energy consumption of the energy conduction process, and the tortuosity factor reflects the additional entropy increase caused by the path detour. The product of the two generates the total path drag coefficient.

[0140] The working principle and beneficial effects of the above technical solution are as follows: In this embodiment, the component for constructing adjacent potential well pairs is used to receive and identify the potential well coordinate set output by the local potential well component, generating potential well connection pairs according to spatial adjacency. Each potential well connection pair constitutes a basic segmented unit of the energy conduction path. The component for extracting single-segment conduction loss values ​​is used to extract the conduction energy loss value corresponding to the current potential well pair from the resistance coefficient set output by the component for calculating conduction resistance between potential wells. The conduction energy loss value already includes the coupling effect of path length and potential energy curvature change. The component for calculating path cumulative resistance is used to conduct energy pairs and the number of series potential wells. For conduction paths with a value ≥ 3, all adjacent potential well pairs contained in the path are read sequentially, and the conduction energy loss values ​​of each potential well pair are summed to output the cumulative path loss value. A path tortuosity factor subcomponent is introduced to calculate the geometric tortuosity of the path. The straight-line distance between the first and last potential wells of the path is measured, and the ratio of the actual path length to the straight-line distance is calculated. The square of the ratio is used as the tortuosity factor. A total drag coefficient generation subcomponent is used to multiply the cumulative path loss value with the tortuosity factor. The cumulative loss value represents the total energy consumption of the energy conduction process, and the tortuosity factor reflects the additional entropy increase caused by the path detour. The product of the two generates the total path drag coefficient. The above scheme achieves quantitative screening of critical phase transition paths through a multi-level calculation process. Its specific technical significance is as follows: Discrete potential well coordinates are connected according to spatial proximity to form basic segmented units for the conduction path, ensuring the topological rationality of subsequent calculations; the energy loss value corresponding to each path segment is extracted from a pre-calculated drag parameter library, which incorporates the coupling effect of path length and potential field curvature; for conduction paths with three or more potential wells in series, the energy loss values ​​of all segments are accumulated to obtain the overall conduction energy consumption of the path; the negative impact of path tortuosity on conduction efficiency is quantified by comparing the ratio of the actual path length to the square of the straight-line distance between the beginning and end; the accumulated energy consumption is multiplied by a geometric tortuosity correction factor to obtain the total drag coefficient, which simultaneously reflects thermodynamic energy consumption and path morphology characteristics.

[0141] In summary, this embodiment, through phased calculations, ultimately outputs a path evaluation index that integrates thermodynamic properties and geometric features, providing a quantitative basis for identifying the minimum resistance phase change channel of the system.

[0142] Example 12: Based on Example 11, the introduction path tortuosity factor sub-component provided in this embodiment of the invention includes:

[0143] The module for obtaining the conduction path coordinate sequence is used to receive the conduction path data processed by the calculation path cumulative resistance sub-component, extract the spatial position sequence of all potential well coordinates on the path, and arrange the sequence in order according to the energy conduction direction; take the starting potential well coordinates and ending potential well coordinates of the path, establish a three-dimensional spatial straight line connecting vector, calculate the Euclidean space modulus of the vector, and output the theoretical minimum distance of the path.

[0144] The module for integrating the actual path length is used to perform spatial segmentation and accumulation along the path coordinate sequence, calculate the spatial distance between adjacent potential well coordinates in turn, sum all segment distances, and output the actual path length.

[0145] The tortuosity ratio generation module is used to divide the actual path length by the theoretical minimum distance, reflecting the degree to which the path deviates from a straight line; the square of the ratio is taken as the final factor.

[0146] The working principle and beneficial effects of the above technical solution are as follows: The module for obtaining the conduction path coordinate sequence in this embodiment is used to receive the conduction path data processed by the calculation path cumulative resistance sub-component, extract the spatial position sequence of all potential well coordinates on the path, and arrange the sequence in order according to the energy conduction direction; take the starting potential well coordinates and ending potential well coordinates of the path, establish a three-dimensional spatial straight line connecting vector, calculate the Euclidean space modulus of the vector, and output the theoretical minimum distance of the path; the module for integrating the actual path length is used to perform spatial segment accumulation along the path coordinate sequence, calculate the spatial distance between adjacent potential well coordinates in sequence, sum all segment distances, and output the actual path length; the module for generating the tortuosity ratio is used to divide the actual path length by the theoretical minimum distance to reflect the degree of deviation of the path from the straight line; the square of the ratio is taken as the final factor. The above scheme achieves accurate evaluation of the conduction path morphology through geometric feature quantification; extracts the endpoint coordinates of the conduction path to generate an ideal straight line reference system, and calculates the shortest spatial span of energy conduction in theory; accurately obtains the total length of the actual trajectory that energy conduction needs to traverse by accumulating the spatial distances of each segment of the path; compares the length difference between the actual path and the ideal straight line, and amplifies the morphological degradation effect of non-straight paths through squaring operations; and provides standardized evaluation parameters for the geometric efficiency of the conduction path, which, together with the thermodynamic drag coefficient, constitute a complete evaluation dimension for path selection.

[0147] Example 13: As Figure 6As shown, based on Examples 1-12, the safety control method for multi-source data acquisition of energy metering boxes provided in this invention includes the following steps:

[0148] S100: Real-time acquisition of the micro-deformation vibration spectrum of the power metering box, the internal gas ion mobility, and the electromagnetic field eddy current distribution through multi-source sensors; fusion of the micro-deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution into a three-dimensional energy flow density topology map through unsteady field reconstruction; generation of early warning signal for the embryonic stage of electric arc fault based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map.

[0149] S200: Receives early warning signal of arc fault embryonic stage, and at the same time activates enhanced scanning mode to apply microsecond-level pulsed electric field to the surface of insulating material, captures relaxation anomaly points in the frequency domain response curve of dielectric constant, calculates the entropy increase of material molecular chain fracture by the relaxation peak offset of relaxation anomaly points, and generates medium fission level.

[0150] S300: Locate the region exceeding the fission level in the three-dimensional energy flow density topology map, calculate the critical path of thermodynamic phase change by combining energy flow gradient, inject a reverse vortex field along the critical path of thermodynamic phase change to counteract energy accumulation, and release nanoscale aerogel to block the oxidation chain reaction.

[0151] The working principle and beneficial effects of the above technical solution are as follows: This embodiment firstly acquires the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution of the power metering box in real time through multi-source sensors; then, through unsteady field reconstruction, the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution are fused into a three-dimensional energy flux density topology map; based on the fractal dimension mutation rate of the three-dimensional energy flux density topology map, an early warning signal for the embryonic stage of an arc fault is generated; secondly, the early warning signal for the embryonic stage of an arc fault is received, and the enhanced scanning mode is activated to apply a microsecond-level pulsed electric field to the surface of the insulating material, capturing relaxation anomalies in the frequency domain response curve of the dielectric constant, calculating the entropy increase of material molecular chain fracture through the relaxation peak shift of the relaxation anomalies, and generating the medium fission level; finally, the region exceeding the fission level limit is located in the three-dimensional energy flux density topology map, and the thermodynamic phase transition critical path is calculated by combining the energy flux gradient. A reverse eddy current field is injected along the thermodynamic phase transition critical path to counteract energy accumulation, while releasing nanoscale aerogel to block the oxidation chain reaction. The above scheme achieves early warning and proactive protection against faults in the power metering box through multi-source data fusion and dynamic intervention mechanisms. A three-dimensional energy flux density topology map is established by reconstructing the unsteady field of the box vibration spectrum, gas ion mobility, and electromagnetic eddy currents. The fractal dimensional mutation characteristics are utilized to achieve embryonic detection of millimeter-level arc faults, advancing the fault identification node compared to traditional threshold monitoring. The shift of the relaxation peak in the frequency domain response curve excited by the pulsed electric field directly reflects the entropy increase process of molecular chain breakage in the insulating material. By establishing a mapping relationship between relaxation time and fission energy barrier, a dimensionless classification of the degree of medium degradation is achieved. Reverse eddy current injection based on the thermodynamic phase transition critical path forms a Maxwell-Boltzmann distribution correction, improving the oxidation blocking efficiency of the nano-aerogel and achieving coupled control of energy dissipation and chemical reaction inhibition in the fault region.

[0152] In summary, this embodiment expands the fault protection dimension from a single electrical parameter to the synergistic action domain of mechanical, chemical, and electromagnetic multi-physics fields, shortens the protection response time to the microsecond level, and does not require reliance on historical fault databases.

[0153] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of equivalents of this invention, this invention is also intended to include these modifications and variations.

Claims

1. A safety control module for multi-source data acquisition in an electricity metering box, characterized in that, Include: The dielectric fission entropy increase sensing system is used to receive early warning signals of the embryonic stage of electric arc faults. At the same time, it activates the enhanced scanning mode, applies a microsecond-level pulsed electric field to the surface of the insulating material, captures relaxation anomalies in the frequency domain response curve of the dielectric constant, calculates the entropy increase of material molecular chain fracture by the relaxation peak shift of the relaxation anomalies, and generates the dielectric fission level. The thermal runaway phase change blocking system is used to locate the region exceeding the fission level in a three-dimensional energy flow density topology map, calculate the thermodynamic phase change critical path by combining energy flow gradient, inject a reverse vortex field along the thermodynamic phase change critical path to counteract energy accumulation, and release nanoscale aerogel to block the oxidation chain reaction.

2. The safety control module for multi-source data acquisition of the power metering box as described in claim 1, characterized in that, Dielectric fission entropy increase sensing system, comprising: The frequency domain response excitation subsystem is used to apply a microsecond-level pulsed electric field to the surface of the insulating material after the enhanced scanning mode is activated by the early warning signal of the embryonic stage of the arc fault, so as to cause the molecular chain of the material to oscillate under forced conditions. The relaxation anomaly capture subsystem is used to acquire the frequency domain response curve of the dielectric constant in real time during forced oscillation and detect its anomalous frequency shift characteristics. The relaxation peak offset calculation subsystem is used to compare the detected relaxation anomalies with the reference position of the intrinsic relaxation spectrum of the material and quantify the offset distance of their frequency axis. The molecular chain fracture entropy increment conversion subsystem is used to calculate the entropy increment based on the relaxation peak offset. The molecular chain conformational entropy loss corresponds to the order of magnitude per unit offset distance. The conformational entropy loss value is superimposed on the abrupt increment of the bond rotation energy barrier. The product of the two generates the entropy increase of molecular chain fracture in the material, establishing a quantitative mapping between frequency shift and molecular-scale energy dissipation; The medium fission level generation subsystem is used to classify fission levels based on the threshold range of the entropy increase of molecular chain fracture in materials.

3. The safety control module for multi-source data acquisition of the power metering box as described in claim 2, characterized in that, The molecular chain fracture entropy increment conversion subsystem includes: The offset conversion component is used to convert the relaxation peak offset into the molecular chain conformational entropy loss value proportionally. The number of conformational states decreases by a fixed proportion for each unit frequency offset. For every additional reference unit of offset distance, the conformational space of the movable chain segment is reduced by one discrete gradient. The component for detecting bond rotation barrier mutations is used to extract barrier features at the same relaxation anomaly point. Normal relaxation peaks correspond to smooth barrier distributions, and the appearance of asymmetric spikes indicates the increment of bond rotation barrier mutations. The increment magnitude is quantified by the ratio of the peak half-width to the main peak width. The fracture entropy increment generation component is used to multiply the conformational entropy loss value with the bond rotation energy barrier mutation increment. The conformational entropy loss characterizes the degree of molecular chain flexibility degradation, and the energy barrier mutation increment reflects the covalent bond twisting potential energy step. The multiplication operation causes the two to produce an energy coupling effect. A component for establishing molecular-scale dissipation mapping is used to directly correlate the increase in fracture entropy with the inherent limitation of molecular motion. The increase in entropy is linearly proportional to the power of frictional heat dissipation within the chain segment. Each unit increase in entropy corresponds to an order of magnitude decrease in molecular kinetic energy, thus completing the quantitative mapping from frequency shift to molecular-scale energy dissipation.

4. The safety control module for multi-source data acquisition of the power metering box as described in claim 3, characterized in that, The fracture entropy increment generation component includes: The quantification of flexibility degradation degree sub-component is used to convert the molecular chain conformational entropy loss value output by the offset conversion component into a flexibility degradation coefficient; Degree of molecular chain flexibility degradation = entropy loss value × intrinsic flexural conversion factor; The calibration potential energy step intensity sub-component is used to convert the mutation increment output by the detection bond rotation barrier mutation component into a potential energy distortion. Covalent bond twisting potential energy step = sudden change increment × bond angle distortion coefficient; A fracture energy coupling effect sub-component is generated to multiply the degree of flexibility degradation of the molecular chain with the step of covalent bond distortion potential energy. The degree of flexibility degradation weakens the stress dissipation ability of the molecular chain, and the potential energy step exacerbates the accumulation of local bond distortion, resulting in the increase of molecular chain fracture entropy.

5. The safety control module for multi-source data acquisition of the power metering box as described in claim 4, characterized in that, The sub-component for quantifying the degree of flexible degradation includes: The discrete gradient analysis module is used to receive the molecular chain conformational entropy loss value output by the offset conversion component and extract the discrete gradient reduction series contained therein. The flexural modulus transition mapping module is used to map discrete gradient reduction series to a rigid growth sequence of chain segments. For each gradient annihilated, the flexural modulus of the corresponding chain segment increases by a fixed order of magnitude. The module for generating the flexibility degradation coefficient is used to multiply the stiffness growth slope by the intrinsic flexural conversion factor. The stiffness growth slope reflects the rate of change of chain segment stiffness, while the intrinsic flexural conversion factor reflects the initial compliance characteristics of the material, thus generating the flexibility degradation coefficient.

6. The safety control module for multi-source data acquisition of the power metering box as described in claim 4, characterized in that, The calibration potential energy step intensity sub-component includes: The barrier mutation increment analysis module is used to receive the mutation increment output by the key rotation barrier mutation detection component and extract the order of magnitude of its transcendence beyond the reference unit. The bond angle distortion threshold mapping module is used to convert the excess magnitude into a bond angle distortion stage, and each stage is locked to reduce the covalent bond angle tolerance threshold by a fixed proportion. An electron cloud deformation barrier module is generated to calibrate the potential energy step based on the bond angle distortion degree. For each increase in the bond angle distortion degree, the overlapping area of ​​the electron cloud orbit is reduced by a corresponding proportion. The reduction in orbital overlap is converted into the height of the electron cloud deformation barrier. The potential energy distortion module is used to multiply the potential energy step height by the bond angle distortion coefficient. The potential energy step height reflects the single bond twisting energy, and the bond angle distortion coefficient carries the rigidity characteristics of the molecular skeleton, thus generating a covalent bond twisting potential energy distortion variable.

7. The safety control module for multi-source data acquisition of the power metering box as described in claim 1, characterized in that, Thermal runaway phase transition blocking system, comprising: The subsystem for locating the fission exceedance region is used to map the dielectric fission level output by the dielectric fission entropy increase sensing system to a three-dimensional energy flux density topology map. Regions with a fission level of not less than level two are marked as exceedance coordinate clusters. The exceedance coordinate clusters coincide with the energy deposition peak area in the topology map for verification, and the fission-energy coupling focus coordinate set is output. Extract the energy flow gradient field subsystem to analyze the three-dimensional energy flow density topology map within the range of the coupled focus coordinate set, obtain the spatial rate of change of energy density per unit volume, calibrate the energy conduction principal axis along the direction of the maximum rate of change, and output the energy flow gradient vector matrix. The critical path calculation subsystem is used to construct a thermodynamic potential field based on the energy flow gradient vector matrix. The convergence point of the gradient vector forms a local potential well. The lowest energy channel connecting adjacent potential wells is the thermodynamic critical path of phase transition. The output is the path with the minimum resistance to energy conduction connecting the overlimit region. An inverse eddy current field subsystem is injected to generate canceling eddies along the critical path of phase transition. The original electromagnetic field eddy current distribution pattern of the region through which the path passes is extracted, and an inverse eddy current field distribution with a phase difference of 180° is generated. The output is a directional canceling eddy current field that cancels the energy accumulation.

8. The safety control module for multi-source data acquisition of the power metering box as described in claim 7, characterized in that, The subsystem for calculating the critical path of phase transition includes: A thermodynamic potential field component is constructed to convert the energy flow gradient vector matrix output by the energy flow gradient field subsystem into a scalar potential. The gradient vector modulus of each spatial coordinate point is converted into the potential energy height, and the vector direction determines the tilt orientation of the potential energy surface, outputting a three-dimensional thermodynamic potential energy surface. Identify local potential well components to scan the thermodynamic potential energy surface. Regions with potential energy heights lower than the coordinates of the eight adjacent directions are marked as local potential wells. The potential well depth is quantized by the potential energy difference between the center point and the edge point. Output the set of potential well coordinates in the out-of-limit region. The calculation component for the conduction resistance between potential wells is used to construct energy channels between adjacent potential wells. The energy loss value is integrated along the connection line of the potential energy surface. The loss value is equal to the product of the path length and the rate of change of the potential energy curvature. The output is the energy conduction resistance coefficient between the potential well pairs. Generate a minimum resistance channel component to traverse the potential well connection combination, select a conduction path with no less than 3 series potential wells, calculate the total resistance coefficient of each path, and take the channel with the minimum total resistance coefficient as the thermodynamic phase change critical path.

9. The safety control module for multi-source data acquisition of the power metering box as described in claim 1, characterized in that, An energy flow anomaly topology system is used to collect the microscopic deformation vibration spectrum of the power metering box, the internal gas ion mobility, and the electromagnetic field eddy current distribution in real time through multi-source sensors; the microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution are fused into a three-dimensional energy flow density topology map through unsteady field reconstruction; and an early warning signal for the embryonic stage of electric arc fault is generated based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map.

10. A safety control method for multi-source data acquisition in an electricity metering box, characterized in that, Includes the following steps: The microscopic deformation vibration spectrum of the power metering box, the internal gas ion mobility, and the electromagnetic field eddy current distribution are collected in real time by multi-source sensors. The microscopic deformation vibration spectrum, internal gas ion mobility, and electromagnetic field eddy current distribution are fused into a three-dimensional energy flow density topology map through unsteady field reconstruction. An early warning signal for the embryonic stage of electric arc fault is generated based on the fractal dimension mutation rate of the three-dimensional energy flow density topology map. It receives early warning signals of the embryonic stage of electric arc faults and simultaneously activates the enhanced scanning mode to apply a microsecond-level pulsed electric field to the surface of the insulating material, captures relaxation anomalies in the frequency domain response curve of dielectric constant, calculates the entropy increment of material molecular chain fracture by the relaxation peak offset of relaxation anomalies, and generates the medium fission level. In the three-dimensional energy flow density topology map, the region exceeding the fission level is located. The critical path of thermodynamic phase change is calculated by combining the energy flow gradient. A reverse vortex field is injected along the critical path of thermodynamic phase change to counteract energy accumulation. At the same time, nanoscale aerogel is released to block the oxidation chain reaction.

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