Passive self-sensing active fire prevention method, system and equipment for distribution pipe gallery and cabinet, and medium

Abstract

The invention discloses a passive self-sensing active fire prevention method, system, equipment and medium for a power distribution pipe gallery and a cabinet, and belongs to the technical field of power system safety protection, and the method comprises the steps: monitoring an electromagnetic characteristic spectrum and an arc spectrum of a power distribution facility through a passive electromagnetic sensing network, and positioning and grading an early fire risk; the ignition time is predicted based on a dynamic heat model, and arrangement is optimized in combination with the suitability data of the perfluorohexanone microcapsules; and the self-powered integrated module triggers shock waves at key time to induce the microcapsules to cooperatively rupture to release the fire extinguishing agent. According to the invention, active fire prevention of passive accurate early warning and autonomous fire extinguishing is realized, and the response speed and reliability are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of power system safety protection technology, specifically to a self-sensor-based active fire prevention method, system, equipment, and medium for power distribution corridors and cabinets. Background Technology

[0002] In the past, the industry mainly relied on passive firefighting methods such as smoke detection and temperature sensors, which are essentially a reactive strategy. They often waited for open flames or thick smoke to appear before starting firefighting, which was not only too late, but could also exacerbate the risk of electrical short circuits due to malfunctions or the spraying of fire extinguishing agents.

[0003] In recent years, the concept of preventative maintenance has emerged, and technologies such as infrared thermography and partial discharge detection have been applied, achieving an initial shift from fire extinguishing to fire prevention. However, these technologies mostly rely on manual inspections or a limited number of online monitoring points, making it difficult to continuously and comprehensively monitor thousands of potential fault points within a cabinet. Existing IoT monitoring solutions are often constrained by power supply and wiring challenges, making them difficult to implement in complex, enclosed cabinets. Meanwhile, although new extinguishing agents such as perfluorohexanone have been approved, ensuring they are positioned correctly and released at the right moment, rather than being sprayed indiscriminately, remains an unsolved engineering problem.

[0004] At the perception level, monitoring a single parameter cannot provide a comprehensive view of the early electromagnetic spectrum of electrical faults. In the early stages of a loosened screw, abnormal harmonic magnetic fields and radiated noise appear far earlier than temperature rise, but existing systems lack economical, power-free micro-sensor networks to capture these "cellular mutations." Furthermore, at the decision-making level, even with some abnormal data, the system lacks comprehensive analysis. Current alarm thresholds are typically static, unable to dynamically integrate multiple signals such as slow overheating and instantaneous arcing, and even less able to calculate the remaining seconds until ignition based on real-time power consumption and heat accumulation models. This leads to frequent false alarms or missed golden windows for warnings. At the execution level, the deployment of fire extinguishing devices often relies on experience, rarely considering whether the long-term coexistence of extinguishing agent microcapsules and equipment materials will damage each other, making the fire protection system itself a reliability bottleneck. Moreover, the reliance on external power supplies for the actuators poses a vulnerability at the most critical moments. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, this invention aims to solve the systemic problems of delayed perception, blind decision-making, and passive execution in existing fire protection technologies for power distribution corridors and cabinets.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets, comprising, In response to the multi-source electromagnetic spectrum analysis and location of the power distribution facilities, early hotspot areas are identified. Within these early hotspot areas, critical extinguishing intervention points are determined based on the power parameters of the fault points. Performance impact tests are conducted on the perfluorohexanone microcapsules and the target power distribution equipment to obtain compatibility data. Based on the early hotspot areas, the critical extinguishing intervention points, and the compatibility data, the installation location of the perfluorohexanone microcapsules is comprehensively determined. A self-sensing integrated module is deployed at the installation location to execute the judgment logic for the critical extinguishing intervention point. In response to the self-sensing integrated module determining that the critical extinguishing intervention point has been reached, perfluorohexanone is released for targeted coverage and fire suppression.

[0008] As a preferred embodiment of the passive active fire prevention method for power distribution pipe corridors and cabinets described in this invention, wherein: the acquisition of early hotspot areas includes: Based on electrical principles, key monitoring nodes are identified, a monitoring network is constructed at the key monitoring nodes and preprocessed to generate a preprocessed digital signal sequence containing signal characteristics. Receive digital signal sequences, perform time-frequency domain analysis on the signal of each node, extract the corresponding feature vectors, and perform weighted similarity matching. The comprehensive risk score of each node is calculated by mapping the weighted similarity matching results. When the score is greater than or equal to the threshold, it is identified as an early hotspot area and dynamic early warning classification is carried out.

[0009] As a preferred embodiment of the passive active fire prevention method for power distribution pipe corridors and cabinets described in this invention, wherein: determining the key timing for fire suppression intervention includes: Monitor the characteristic arc spectral intensity in early hotspot areas and estimate real-time power loss by inversion; After obtaining the real-time power loss, an ignition time prediction algorithm is constructed to calculate the cumulative net heat and estimated temperature of the fault point and nearby combustibles. In response to the cumulative net heat reaching a preset proportion of the total heat required to heat the combustible to ignition, it is determined that the combustible has reached the thermal runaway critical point, and the time from the beginning to this moment is recorded and defined as the predicted ignition time. If the predicted ignition time is less than or equal to the minimum response time, the system determines that a critical extinguishing moment has been reached and immediately generates a fire extinguishing command event.

[0010] As a preferred embodiment of the passive active fire prevention method for power distribution pipe corridors and cabinets described in this invention, wherein: the acquisition of adaptability data includes: A dynamic accelerated aging coupled stress testing platform was constructed, environmental stress and electrical stress were applied to form test samples, periodic coupled stress spectrum was performed on the test samples, and multi-faceted performance parameter data were collected. Based on performance parameter data, the relative degradation rate of each performance index is calculated, and a comprehensive performance score is calculated using dynamic weight allocation based on information entropy and coefficient of variation. The comprehensive performance score is negatively correlated with the fit.

[0011] As a preferred embodiment of the self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets described in this invention, wherein determining the installation location of the perfluorohexanone microcapsules in the equipment includes: A deployment safety factor is defined for each early hotspot area based on the comprehensive performance score; Set a minimum permissible safety threshold and a priority deployment safety threshold, and make a two-level decision: If the safety factor of the layout is less than the minimum allowable safety factor, the first decision is to prohibit the use of the current plan at the current location. When the safety factor of the layout is greater than or equal to the minimum allowable safety factor, the second decision is executed: among all the layout safety factors that are greater than or equal to the minimum allowable safety factor, the layout safety factor of the scheme with the largest safety factor is selected as the preferred scheme for the current location.

[0012] As a preferred embodiment of the passive active fire prevention method for power distribution pipe corridors and cabinets described in this invention, the step of determining the critical extinguishing timing includes: The self-sensing integrated module is deployed at the second decision point and written with a unique logical address bound to the early hotspot area. Continuously monitor the voltage across the micro energy storage capacitor to initialize the low-power operating mode; After initialization, extract the flag bits that match the logical address to perform state transition; After the state transition, it automatically jumps to the trigger execution state, releasing the stored energy to the underlying actuator to send the fire extinguishing trigger command.

[0013] As a preferred embodiment of the passive active fire prevention method for power distribution pipe corridors and cabinets described in this invention, wherein: the release of perfluorohexanone for directional coverage fire extinguishing includes: Upon receiving a fire extinguishing trigger command, the system initiates multi-source signal cross-verification. If the multi-source signal cross-verification result is true, the alarm is deemed valid. After a valid alarm is triggered, the preset release strategy is retrieved according to the location code in the fire extinguishing trigger command, and a synchronous execution command is sent to all associated generators. After the generator detonates, the return status is used to determine whether the main release was successful. If the return status is unsuccessful, the backup redundancy is activated. After the release ends, the extinguishing agent concentration change in the target area is monitored until the fire is extinguished.

[0014] Another objective of this invention is to provide a passive active fire protection system for power distribution pipe corridors and cabinets.

[0015] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a passive active fire prevention system for power distribution pipe corridors and cabinets, comprising: a risk area determination module, a fire extinguishing point determination module, a matching module, an installation module, an integrated module, and a fire extinguishing module; The risk area determination module, in response to the multi-source electromagnetic characteristic spectrum analysis and location of power distribution facilities, obtains early hotspot areas; The fire extinguishing point determination module determines the critical timing for fire extinguishing intervention based on the power parameters of the fault point in the early hotspot area. The matching module performs a performance impact test on the perfluorohexanone microcapsules and the target power distribution equipment to obtain compatibility data. The installation module determines the installation location of the perfluorohexanone microcapsules based on the early hotspot areas, the key extinguishing timing points, and the compatibility data. The integrated module deploys a self-sensing integrated module at the installation location to execute the judgment logic for the key extinguishing timing point. The fire extinguishing module, in response to the self-sensing integrated module determining that a critical extinguishing moment has been reached, releases perfluorohexanone for targeted coverage and fire suppression.

[0016] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the aforementioned self-sensored active fire prevention method for power distribution pipe corridors and cabinets.

[0017] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the aforementioned self-sensored active fire prevention method for power distribution pipe corridors and cabinets.

[0018] The beneficial effects of this invention are as follows: This invention no longer relies on smoke or temperature alarms after a fire occurs, but instead starts from the source of electrical faults. By deploying miniature sensors that do not require external power supply on key electrical nodes, passive sensing is established, and the specific location in the three-dimensional model is accurately located to draw a risk hotspot map. Based on this, a dual confirmation method was introduced. At the highest-risk location, an optical probe sensitive to the spectrum of fault arc characteristics was deployed simultaneously. When the system simultaneously captures abnormal electromagnetic characteristics and typical arc flashes, it can not only confirm the high-risk state, but also use algorithms to infer the real-time heat generation power of the fault point. In addition, it will dynamically simulate the cumulative effect of this heat on the surrounding combustibles, accurately calculate how much safe time is left before the fire starts, and thus lock in the best time to intervene when action must be taken.

[0019] Rigorous testing ensures the long-term compatibility of extinguishing agents and equipment. Safety factors are dynamically calculated and deployed at each risk point for precise control. On-site micro-modules can capture fault energy, generate their own power, and autonomously trigger based on local signal logic, forming a last line of defense independent of external systems. Finally, a central system coordinates the release of extinguishing agents using shockwave induction and real-time monitoring to form a closed-loop control system, constructing a complete active fire prevention system. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating an embodiment of the present invention of a self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets.

[0022] Figure 2 This is a flowchart illustrating the early hotspot area delineation process of a passive active fire prevention method for power distribution corridors and cabinets, provided as an embodiment of the present invention.

[0023] Figure 3 This is a flowchart illustrating the key extinguishing timing of a self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets, provided as an embodiment of the present invention. Detailed Implementation

[0024] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0025] Example 1, referring to Figures 1-3 This is one embodiment of the present invention, which provides a self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets, including: S100: Response to multi-source electromagnetic characteristic spectrum analysis and localization of power distribution facilities to obtain early hotspot areas; S200. In the early hotspot area, determine the key timing for fire suppression intervention based on the power parameters of the fault point; S300: Conduct performance impact tests on perfluorohexanone microcapsules and target power distribution equipment to obtain compatibility data; S400. Based on the early hotspot areas, the key extinguishing timing points, and the compatibility data, determine the installation location of the perfluorohexanone microcapsules. S500: Deploy a self-sensing integrated module at the installation location and execute the judgment logic for the key extinguishing timing point; S600: In response to the self-sensing integrated module determining that a critical extinguishing moment has been reached, perfluorohexanone is released for targeted coverage and extinguishing of the fire. It should be noted that existing technologies cannot accurately locate potential hotspots and dynamically assess their risk levels during the early, latent stages of electrical fires through passive, continuous, and multi-dimensional sensing. Furthermore, there is a lack of a dynamic model that can simultaneously integrate real-time fault power and transient arc energy to accurately calculate the critical time window from fault occurrence to the ignition of open flames, resulting in fire intervention being either too early or too late. In addition, existing methods lack a quantitative assessment system for the long-term electro-thermal-chemical compatibility of novel extinguishing agents (such as perfluorohexanone microcapsules) with equipment materials when deploying them, and the execution module relies on external power, inherently posing a risk of failure during fault occurrence, thus failing to guarantee reliable operation at the most critical moment.

[0026] Therefore, in response to the aforementioned problems, through steps S100-S600, this invention can avoid the lag in post-event alarms of traditional smoke and heat detectors, and also transcend the limitations of simple electrical monitoring. Through multi-dimensional information fusion and precise intervention of the physical and chemical reaction chain, it can achieve proactive prevention and control before a fire occurs.

[0027] Example 2, refer to Figure 1 This is one embodiment of the present invention, which provides a self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets, including: In this embodiment of the invention, S100, in response to the multi-source electromagnetic characteristic spectrum analysis and localization of the power distribution facilities, obtains early hotspot areas, including the following steps S101-S104: Reference Figure 2 S101. Inside the power distribution corridor or cabinet, based on the electrical connection schematic diagram, identify the electrical connection points, the turning points of current-carrying conductors, and the weak points of the insulation medium as key monitoring nodes. The electrical connection points include busbar bolt connections, moving and stationary contacts of circuit breakers and disconnectors, and crimp terminals of cables and equipment; the weak points in the insulation medium include, but are not limited to, cable terminations and the surface of old insulators.

[0028] At each monitoring node, a passive electromagnetic sensing unit is fixedly installed. The passive electromagnetic sensing unit consists of a composite sensor probe and a passive processing circuit. The composite sensor probe includes a miniature broadband planar antenna and a miniature induction coil wound with a high permeability magnetic core; wherein, the miniature broadband planar antenna receives radiating electromagnetic interference in the frequency range of 1MHz to 1GHz, and the miniature induction coil senses 50Hz power frequency and odd harmonic magnetic fields in the range of 150Hz to 1kHz. The passive processing circuit integrates an analog filter, envelope detector, analog-to-digital converter, and radio frequency backscatter modulation circuit.

[0029] All passive electromagnetic sensing units are registered by the centralized data processing node during initialization through their built-in unique barcode or radio frequency identification chip, and are bound one by one to the physical location coordinates in the three-dimensional digital model of the power distribution facility to complete the network topology construction, solving the problems of difficult wiring, incomplete coverage, and unclear fault location in traditional monitoring methods.

[0030] S102. When the power distribution equipment is running, the electrical status of all monitoring nodes will be characterized by the electromagnetic field of the surrounding space, and the passive electromagnetic sensing unit installed at the node will begin preprocessing: The broadband planar antenna continuously receives radiated electromagnetic noise signals from the node, and its miniature induction coil continuously senses the near-field magnetic field signals around the node conductor. These two original analog signals are bandpass filtered by an analog filter to suppress interference from irrelevant frequency bands. The signal after bandpass filtering is sent to the envelope detector to extract the envelope of the signal strength as a function of time. The analog voltage signal output by the envelope detector is converted into a digital signal sequence by an analog-to-digital converter at a sampling rate of not less than 10 ksps, and the digital signal sequence is temporarily stored in the buffer within the unit. The centralized data processing node periodically broadcasts radio frequency query pulses of a specific frequency to the entire network through its built-in radio frequency energy transmitter, where the period can be selected to be once per second.

[0031] Furthermore, after the antenna of the passive electromagnetic sensing unit receives the radio frequency query pulse, it couples out a weak electrical energy from it to power its own circuit for a short time to complete the communication. On the other hand, it uses its backscatter modulation circuit to modulate the digital sequence representing the electromagnetic signal characteristics in the buffer within that period onto the reflected radio frequency wave for uplink wireless data transmission.

[0032] The transmitted data frames contain unit IDs, timestamps, and pre-processed digital signal sequences, fundamentally eliminating monitoring blind spots caused by line or battery failures, and achieving extremely high operational reliability and maintenance-free operation.

[0033] S103. Receive all digital signal sequences and synchronize all data according to the timestamps. For each monitoring node, a time-frequency domain analysis is performed on the digital signal sequence within an analysis time window. Three sub-frequency bands are preset, and the average power spectral density in the three sub-frequency bands is calculated by Fast Fourier Transform, and denoted as characteristic parameters respectively. , , Simultaneously, the number of pulses whose signal envelope exceeds a preset threshold value within the current window is counted and recorded as a characteristic parameter. .

[0034] For the signal sequence from the induction coil, the magnetic field strength amplitude at the fundamental frequency of 50Hz is extracted using the lock-in amplification principle. The amplitudes of the magnetic field strength of the 3rd, 5th, and 7th harmonics are also calculated. Furthermore, the ratios of the amplitudes of the 3rd, 5th, and 7th harmonics to the amplitude of the fundamental wave are calculated and denoted as characteristic parameters. , , For each monitoring node, at the end of each analysis time window, an eight-dimensional feature vector is generated, including feature parameters. , , , , , , , , which serves as the digital representation of the current node at the current moment.

[0035] S104. Set up a fault characteristic database in the control system of power distribution corridors and cabinets, apply different levels and types of faults to typical power distribution components, and collect their corresponding electromagnetic signals. The obtained current feature vector is compared with all the pre-stored feature templates in the fault feature database to calculate similarity. The similarity matching calculation adopts the weighted Euclidean distance method: calculate the difference between the current feature vector and each template vector in each dimension, square the difference in each dimension and multiply it by its corresponding preset weight coefficient, wherein the weight coefficient is pre-calibrated according to the sensitivity and reliability of the fault of the feature parameter in that dimension, and then sum and take the square root to obtain the weighted distance. The smaller the weighted distance, the higher the similarity. Furthermore, the top K templates with the smallest weighted distance to the current feature vector are identified, and the fault types and severity levels corresponding to these templates are identified. Further, a weighted vote is performed based on the reciprocal of the weighted distance of these K templates to comprehensively determine the most likely fault type of the current node, and a comprehensive risk score is calculated. The comprehensive risk score is calculated by mapping the minimum weighted distance to a value between 0 and 1. The closer the comprehensive risk score is to 1, the higher the risk. Furthermore, by traversing all monitoring nodes, nodes with a comprehensive risk score greater than or equal to the threshold α are identified as early hotspot areas, and the locations of these nodes are highlighted in the three-dimensional digital model of the power distribution facilities. The threshold α is determined through historical data statistics and has a value between 0.5 and 0.7. At the same time, dynamic classification is carried out based on the comprehensive risk score: A comprehensive risk score within the range of [0.6, 0.8) is marked as a medium-level warning and indicated by a yellow label. A comprehensive risk score within the range of [0.8, 1.0] is marked as a high-level warning and highlighted in red.

[0036] It should be noted that it not only tells users where the problem is, but also makes a preliminary judgment on what the problem is and how serious it is, so that maintenance decisions can be transformed from reactive emergency response to proactive planning, thereby improving the initiative of safety management.

[0037] In this embodiment of the invention, in step S200, determining the critical timing for fire suppression intervention based on the power parameters of the fault point in the early hotspot area includes the following steps S201-S204: Reference Figure 3 S201. In the early hotspot areas marked as high-level warning areas, a passive arc spectral sensor is installed. The sensor has a built-in narrowband filter sensitive to the 521.8 nm wavelength characteristic spectral line of copper atoms and a corresponding photodetector. It synchronously acquires the feature vector of the preprocessed digital signal sequence transmitted by the electromagnetic sensing unit. The raw signal of the 521.8 nm spectral line intensity from the arc spectral sensor .

[0038] Node pairs A moving average filter is applied to suppress random noise, resulting in a smoothed arc light intensity signal. ; The threshold for determining arc intensity is set as follows: =50 milliwatts per square centimeter. It should be noted that the arc intensity threshold was obtained through laboratory calibration of typical fault arc spectra. If the arc intensity continuously exceeds the threshold for determination, it is determined that a continuous arc is being generated.

[0039] S202, The centralized data processing node uses the feature vector from the current time t. Extracting the third harmonic magnetic field strength of the power frequency With fundamental magnetic field strength ratio According to the lookup table, by The additional contact resistance at the fault point relative to the ideal state was determined. ; The method for establishing the lookup table is as follows: On the experimental platform, different contact states, ranging from slight oxidation to severe loosening, are simulated, and the actual contact resistance under the current state is measured. Compared with harmonics Record the corresponding relationships; The node simultaneously obtains the real-time effective value of the current flowing through the branch where the current fault point is located from the power distribution system monitoring data bus, and calculates the real-time power loss of the current fault point according to Joule's law. .

[0040] S203. After obtaining the real-time power loss, construct an ignition time prediction algorithm, considering the dynamic heat accumulation equation of steady-state heating and arc pulse injection, where the input parameters include the fault power loss at the current moment. Arc light intensity First, calculate the net heat absorbed by the fault point and the adjacent combustible area: in, This represents the cumulative net heat absorbed by the fault point and adjacent combustible areas from the start of monitoring to the current time. The step size for model calculation can be set to 0.1 seconds. To indicate the next calculation time The cumulative net heat; The ambient temperature can be set to 25°C. The equivalent heat capacity of the fault point and the nearest adjacent combustible material; The average temperature of the fault area is estimated based on the current accumulated heat. It should be noted that... The calculation method is the sum of the ratio of net heat capacity to the equivalent heat capacity of the fault point and the nearest neighbor combustible material and the ambient temperature; The arc heat conversion coefficient is an experimentally calibrated constant used to convert values ​​exceeding a threshold. The electric arc light intensity is converted into equivalent additional heating power. It should be noted that the calibration method for the electric arc heat conversion coefficient is to measure the light intensity produced by an electric arc with known energy input in a controllable electric arc experimental device. The actual temperature rise caused to the standard material is calculated by reverse calculation.

[0041] From the first detection Greater than zero or Greater than Initialize at time, let =0, then with step size Iterative calculations are performed, and at each step, the net heat formula is applied in conjunction with the current measured values. and Calculate the cumulative net heat at the next moment. and estimating temperature .

[0042] After each iteration, calculate the current cumulative net heat. The total heat required to heat the adjacent combustible material (m) to ignition. The ratio of the current cumulative net heat to the total heat required for ignition is determined when the combustible material is close to the thermal runaway threshold. The time elapsed from the initial time to the current time is recorded and defined as the predicted ignition time. ; It should be noted that 85% was chosen as the critical coefficient based on the material pyrolysis kinetics. To allow for a safety margin in response, this value was determined through experiments on the critical heat flux of typical insulating materials.

[0043] It should also be noted that this invention transforms the timing of fire prevention from a fixed threshold alarm point to a dynamically calculated predictive time window based on physical models and real-time data. By setting an 85% safety margin, valuable time is gained for system response, truly enabling intervention just before a fire ignites.

[0044] S204. Set a fixed minimum response time. The minimum response time includes the maximum time required for signal transmission, decision module action, shock wave generator activation, and extinguishing agent diffusion coverage, which can be set to 300 milliseconds.

[0045] The criteria for determining the critical timing of extinguishing the fire are: ≤ In response to the determination condition of satisfying the critical extinguishing timing point in the iterative calculation, the centralized data processing node immediately generates a fire extinguishing command event, which is a digital signal packet containing: Event type, such as fire fighting; target hotspot location code; timestamp; estimated remaining time, such as... .

[0046] The fire extinguishing command event is sent to the compatibility and performance impact test via an internal communication link to initiate the subsequent fire extinguishing process.

[0047] In an embodiment of the present invention, S300 involves testing the performance impact of perfluorohexanone microcapsules on the target power distribution equipment to obtain compatibility data, including the following steps S301-S305: S301. Construct a dynamic accelerated aging coupled stress testing platform, which consists of a programmable environmental stress chamber, a multi-channel electrical stress loading device, a sample monitoring system, and a central controller.

[0048] It should be noted that the environmental stress chamber controls the temperature and relative humidity; Furthermore, the multi-channel electrical stress loading device applies a power frequency AC voltage from 0 to the rated voltage to the test sample, and can superimpose pulse voltages with adjustable repetition frequency and amplitude to simulate partial discharge. It should also be noted that the sample monitoring system includes an online partial discharge detector, an insulation resistance tester, a high-resolution optical microscope linkage device, and a gas chromatograph interface for sampling and analysis.

[0049] S302. Select typical substrate material samples from power distribution equipment, including conductive materials, insulating materials and encapsulation materials. Coat or embed different types of perfluorohexanone microcapsules to be evaluated onto the surface of each substrate material sample using standard processes to form a combined test sample. The central controller executes a preset coupled stress spectrum, wherein the coupled stress spectrum has a 72-hour cycle, and the cycle includes: During the first 24-hour period, under conditions of 85°C and 85%RH, a simulated partial discharge pulse at 1.05 times the rated voltage and the background level was applied to the sample. In the second 24-hour phase, the temperature was rapidly reduced to -25°C and maintained, the humidity was reduced to 30%RH, and the power frequency voltage was removed but periodic temperature shocks were maintained. In the third 24-hour phase, the temperature was raised to 125°C, the humidity was reduced to 10%RH, and 1.2 times the rated voltage and an enhanced simulated partial discharge pulse were applied.

[0050] The coupled stress spectrum is continuously run for no less than 15 complete cycles to simulate several years of harsh operating conditions.

[0051] S303. Before and after each stage, performance parameter data is collected through integrated sensors and external devices, specifically including: Electrical performance parameters include the rate of change of insulation resistivity under the coating and the attenuation rate of power frequency withstand voltage, which are calculated by applying a test voltage and measuring the leakage current. Mechanical and chemical integrity parameters were analyzed using high-resolution optical microscopy images to calculate the microcapsule surface rupture rate; perfluorohexanone retention was measured using gas chromatography. Functional performance parameters: After the standardized triggering at the end of the third stage, the effective release rate of perfluorohexanone is measured, which is the percentage of the actual release amount to the initial encapsulation amount. Environmental stress parameters, recording the cumulative temperature exposure and cumulative humidity exposure during each test phase, serve as quantitative indicators of stress intensity; It should be noted that this invention solves the hidden safety problem when fire extinguishing agent materials and electrical equipment coexist for a long time. Traditional methods only perform simple insulation tests, while this invention, through coupled stress testing, can expose in advance the risks that the microcapsule coating may cause under long-term comprehensive stress, such as insulation degradation, material corrosion, premature capsule rupture or failure, thus avoiding the introduction of new faults for fire extinguishing from the source.

[0052] S304. Calculate the adaptability score and layout safety factor based on the performance parameter data, generate an optimized layout scheme, and calculate the relative degradation rate of each performance parameter after undergoing a complete coupled stress spectrum test: For indicators that are negatively correlated, such as the rate of change of insulation resistivity, the relative degradation rate is the ratio of the difference between the value after the test and the value before the test to the value before the test. For indicators that are positively correlated with perfluorohexanone retention rate, the relative degradation rate is the ratio of the difference between the pre-test value and the post-test value to the pre-test value. All the obtained relative degradation rate values ​​are normalized to the interval [0, 1], where 0 represents no degradation and 1 represents complete failure.

[0053] S305. Applying a dynamic weighting model based on information entropy and coefficient of variation, calculate the comprehensive performance score through dynamic weighting, and analyze the normalized degradation rate matrix obtained from testing n samples in the same batch: The coefficient of variation of m performance indicators among different samples is calculated by the ratio of the standard deviation to the mean of each parameter throughout the entire sampling process. The larger the coefficient of variation, the higher the discrimination of the current indicator among different samples, and the greater the weight should be assigned. At the same time, the information entropy of each indicator is calculated. The smaller the entropy value, the more ordered and important the information provided by the current indicator is. The objective weight of the j-th indicator, taking into account both the coefficient of variation and information entropy. The calculation is as follows: in, Let be the objective weight of the j-th performance indicator, and the sum of the weights of all indicators is 1; The information entropy of the j-th performance metric; Let be the coefficient of variation of the j-th performance index; m is the total number of performance indexes participating in the evaluation; and k is the index variable for the summation operation, traversing from 1 to m. The overall performance score is calculated by summing the products of the objective weight of each test sample and the normalized relative degradation rate. The overall performance score is between [0,1], and the closer it is to 0, the better the overall performance is maintained and the higher the adaptability.

[0054] In this embodiment of the invention, step S400, based on the early hotspot area, the critical extinguishing timing, and the compatibility data, comprehensively determines the installation location of the perfluorohexanone microcapsules, including the following steps S401-S402: S401: Define a safety factor for each early hotspot area: in, The safety factor is used for layout; P is the comprehensive performance score, 1−P is the reliability factor; R is the fire risk level, which is determined by the dynamic classification analysis based on the comprehensive risk score. The fixed safety margin time can be set to 50 milliseconds; The baseline response time constant, a constant in seconds, represents the minimum acceptable response time of the system design, and is usually set to 200 milliseconds; The severity level is determined based on the actual environmental conditions (temperature, humidity, dirt, chemical corrosion, etc.) at the equipment installation site. In practice, it can be 0 for a room temperature cleaning cabinet and 0.8 for a humid and dusty outdoor environment. , , The adjustment coefficient is positive and is calibrated through engineering experience, historical data statistics, or multi-objective optimization simulation.

[0055] S404. Set the minimum permissible safety factor and the priority arrangement safety factor; It should be noted that the minimum allowable safety factor is obtained by statistically analyzing the lower limit of safety factors in a large number of qualified engineering cases, and is set to 0.8; the priority layout safety factor is determined by multi-objective optimization after weighing the protection effect and cost, and is set to 1.5.

[0056] The first decision is whether to deploy the device. If the deployment safety factor is less than the minimum allowable safety factor, the current solution is prohibited from use at the current location. It is necessary to reselect the microcapsule type or coating process and test it, or adjust the deployment location to a position with a smaller Env while meeting the safety distance rules and recalculate S.

[0057] When the safety factor of the layout is greater than or equal to the minimum allowable safety factor, the second decision is executed, namely, optimization layout. Among all the layout safety factors that are greater than or equal to the minimum allowable safety factor, the layout with the largest safety factor is selected as the preferred layout for the current location. All points with a safety factor greater than or equal to the priority layout safety factor are marked as first-level optimized layout points. During construction, the coating quality, thickness and uniformity must be strictly guaranteed. Points with a minimum allowable safety factor ≤ layout safety factor < priority layout safety factor are marked as secondary standard layout points and constructed according to standard procedures.

[0058] In this embodiment of the invention, step S500 involves deploying a self-sensor-integrated module at the installation location and executing the logic for determining the critical extinguishing timing, including the following steps S501-S504: S501, The self-sensorless integrated module is internally integrated through multi-layer microelectronics and microelectromechanical systems (MEMS) technology, with three core layers from top to bottom: top layer, middle layer, and bottom layer; The top layer integrates a miniaturized electromagnetic induction antenna and a magnetic field induction coil, which together form a composite electromagnetic energy harvester; the middle layer integrates an ultra-low power management integrated circuit, a miniature energy storage capacitor, and a dedicated decision logic chip; the bottom layer integrates a MEMS actuator, which is either a thermal expansion actuator based on a micro heating element or a deformation actuator based on a piezoelectric material. The self-sensing integrated module writes a unique logical address code through physical DIP switch or wireless near-field communication. The logical address code is bound to the early hotspot area, and perfluorohexanone capsules are deployed according to the scheme selected based on the deployment safety factor.

[0059] S502: Continuously monitor the voltage across the micro energy storage capacitor and set the wake-up voltage threshold; It should be noted that the wake-up voltage threshold is set between 1.8 volts and 2.2 volts to ensure that the voltage is sufficient to reliably start the subsequent ultra-low power digital logic circuits, while avoiding false wake-ups caused by minor interference signals.

[0060] Furthermore, when the capacitor voltage is greater than or equal to the wake-up voltage threshold, a power-on reset pulse signal is generated, causing the system to enter a low-power operating mode from a deep sleep state and complete initialization.

[0061] S503. After initialization, it confirms its own identity through logical address encoding, and then receives the logical addresses of each monitoring point and their corresponding real-time status flags. Filter out data items that match their own logical address codes from the data stream, including electromagnetic feature anomaly flags and arc spectrum flags; It should be noted that the electromagnetic feature anomaly flag is set to 1 when the severity score of the electromagnetic feature spectrum at the corresponding point exceeds the electromagnetic feature anomaly threshold, and is 0 otherwise; the arc spectrum flag is set to 1 when a characteristic arc spectrum is detected and the intensity exceeds the arc spectrum threshold, and is 0 otherwise. It should also be noted that the electromagnetic characteristic anomaly threshold ranges from 0.7 to 0.85, which is derived from historical fault data statistics to distinguish between general anomalies and high-risk anomalies; the arc spectrum threshold is determined by adding three times the standard deviation to the background noise level of the photoelectric sensor to exclude ambient light interference.

[0062] Furthermore, the state transition is entirely controlled by the timing combination of the input electromagnetic feature anomaly flag and the arc spectrum flag: State S0 is idle monitoring. If the electromagnetic feature anomaly flag is 1 and the arc spectrum flag is 0, then it transitions to state S1. If the electromagnetic feature anomaly flag is 1 and the arc spectrum flag is 1, then it directly transitions to state S3. State S1 is an anomaly confirmation. After entering this state, an internal timer is started, with the timing duration set to 100 milliseconds to 500 milliseconds. Within this time, if the electromagnetic feature anomaly flag remains at 1 and the arc spectrum flag changes to 1, then the process transitions to state S3; if the electromagnetic feature anomaly flag changes to 0, then the process returns to state S0; if the arc spectrum flag remains at 0 before the timer expires, then the process returns to state S0. State S3 is an emergency pending trigger. This state indicates that a high-risk scenario has been detected that simultaneously has continuous abnormal heating (electromagnetic feature abnormal flag bit continuously = 1) and instantaneous electric arc (electric arc spectrum flag bit change = 1). After entering state S3, the trigger delay timer is immediately started, and its value is equal to the minimum response time.

[0063] State S4 is the trigger execution state. When the delay timer overflows, the state machine automatically jumps to state S4.

[0064] S504, in response to entering state S4, sends a trigger enable signal to the power management integrated circuit, then disconnects the charging circuit of the micro energy storage capacitor, and directs all or most of the remaining stored energy in the capacitor to the underlying integrated MEMS actuator through a high-current switch that closes instantaneously.

[0065] If the actuator is of the thermal expansion type, a large current flows through its miniature heating resistor, causing it to heat up rapidly within milliseconds. This heats the working fluid inside the sealed cavity, generating high pressure, which drives the miniature piston to move, initiating the perfluorohexanone capsule release and extinguishing process, and sending a trigger command. If the actuator is piezoelectric, the high-voltage electric pulse drives the piezoelectric stack to produce rapid deformation, generating a pressure pulse output, initiating the perfluorohexanone capsule release extinguishing process, and sending a trigger command.

[0066] In an embodiment of the present invention, S600, in response to the self-generating sensor integrated module determining that a critical extinguishing timing point has been reached, releases perfluorohexanone for targeted coverage extinguishing, including the following steps S601-S605: S601. The release control software listens to the trigger command of the self-sensor integrated module in real time through its communication interface. The trigger command includes: the unique physical address of the trigger source, the trigger timestamp, and the associated fire risk hotspot location code. Upon receiving any trigger command, instead of immediately performing a release action, the multi-source signal cross-validation routine is initiated: Specifically, query the centralized data processing node to find out if the current electromagnetic feature severity score for the hotspot location associated with the physical address of the current trigger source is still higher than the preset high-risk threshold. Furthermore, query whether the arc spectrum flag corresponding to the current hotspot location has been activated in the past 100 milliseconds; Only when both query results are true is the current trigger command determined to be a valid and urgent true alarm, and the current trigger command and associated target location information are placed in the execution queue; Otherwise, it will be recorded as a false alarm pending investigation and enter diagnostic mode without initiating any physical release action.

[0067] S602. For a verified trigger command, retrieve the corresponding release parameters from the release strategy database based on the target location code it carries.

[0068] It should be noted that the release strategy database is established according to the deployment plan. Each record includes the following associated parameters for a specific location: the physical number of the shock wave generator responsible for covering the current location; the energy level required by the generator (divided into low, medium, and high levels, corresponding to different charge amounts or capacitor charging voltages); the shock wave waveform characteristic code (used to select the configuration of the waveform shaper); and the expected delay time after the main release (used to arrange possible supplementary releases).

[0069] Furthermore, configuration and pre-start instructions, including the aforementioned energy level and waveform characteristic codes, are sent to the designated shock wave generator via the control bus.

[0070] The shock wave generator charges the energy storage capacitor to a specified voltage and configures its internal programmable pulse forming network to generate an electric detonation pulse that meets the requirements.

[0071] S603. After configuration, send an execution command with a precise synchronization timestamp to all shock wave generators associated with the same target area.

[0072] After receiving the execution command, the microcontroller inside the generator immediately releases the energy of the energy storage capacitor to the electric detonator within microseconds. After execution, each shock wave generator must return an acknowledgment frame to the software within 10 milliseconds, containing its own number, execution status (i.e., success or failure) and the actual execution timestamp.

[0073] Collect all confirmation frames. If the execution status of all expected generators returns success, the main release action is considered complete. If the execution status returns a failure, the backup generator will be started immediately according to the preset redundancy strategy.

[0074] S604. After the main release action is completed, effect monitoring and evaluation are carried out. The release effect evaluation algorithm is set. Based on the preset ideal release pressure-time curve and the target minimum extinguishing concentration, the pressure curve collected in real time is compared with the ideal curve in terms of morphological similarity, and the average extinguishing agent concentration in the target area is calculated in real time. It should be noted that the morphological similarity comparison is performed by calculating the dynamic time-normalized distance. If the distance is less than a set threshold, the morphology is considered to match. The threshold is set by expert experience. If the monitored initial shock wave pressure pattern is successfully matched, but the rate of increase in extinguishing agent concentration is lower than normal, it is determined that the initial release coverage is insufficient, and a chain-like coordinated release needs to be initiated. The area with the lowest concentration is selected, and a coordinated triggering command is sent to the pre-deployed secondary effect enhancement device in the current area.

[0075] S605, Dynamic closed-loop adjustment and release termination judgment.

[0076] After the coordinated trigger command is issued, monitor the changes in the fire extinguishing agent concentration in the target area.

[0077] Monitor real-time concentration values ​​and plot concentration-time curves, and calculate the area under the concentration-time curve from the start of the main release to the current moment; A preset fire extinguishing efficiency threshold is set, which is equal to the product of the target fire extinguishing concentration and the required minimum suppression time. The area under the calculated concentration-time curve is compared with the fire extinguishing efficiency threshold in real time. In response to the occurrence of a concentration-time integral area exceeding the extinguishing effectiveness threshold, an electromagnetic characteristic severity score dropping below the safety threshold β, and an arc spectral marker remaining extinguished for more than 5 seconds, indicating that the fire risk has been eliminated and the extinguishing agent is sufficient, all data for this event are recorded, and all controllable release devices are reset to standby mode, awaiting the next cycle.

[0078] Example 3 is an embodiment of the present invention, illustrating a schematic scheme of a passive active fire prevention method for power distribution pipe corridors and cabinets. It should be noted that the technical solution of a passive active fire prevention system for power distribution pipe corridors and cabinets belongs to the same concept as the technical solution of the passive active fire prevention method for power distribution pipe corridors and cabinets described above. Details not described in detail in the technical solution of the passive active fire prevention system for power distribution pipe corridors and cabinets in this embodiment can be found in the description of the technical solution of the passive active fire prevention method for power distribution pipe corridors and cabinets described above.

[0079] This embodiment provides a passive active fire protection system for power distribution pipe corridors and cabinets, including: a risk area determination module, a fire extinguishing point determination module, a matching module, an installation module, an integrated module, and a fire extinguishing module; The risk area determination module collects multi-source electromagnetic characteristic spectra of power distribution facilities, analyzes and locates early hotspots prone to electrical faults and fires based on the multi-source electromagnetic characteristic spectra, and performs risk classification. The fire extinguishing point determination module simultaneously monitors the characteristic spectrum of the fault arc near the early hotspot area and, in conjunction with the fault point power parameters obtained by inversion from the electromagnetic characteristic spectrum, determines the critical timing for fire extinguishing intervention. The matching module tests the compatibility and performance impact of perfluorohexanone microcapsules with different materials of the target power distribution equipment to obtain compatibility data. The installation module comprehensively determines the installation location of perfluorohexanone microcapsules in the device based on the early hotspot areas, the key extinguishing timing points, and the compatibility data. An integrated module is deployed at the installation location. It is a self-powered module that captures fault electromagnetic energy and performs the judgment logic for the key extinguishing timing. The fire extinguishing module, in response to the self-sensing integrated module determining that a critical extinguishing moment has been reached and triggering it, activates a micro shock wave generator to induce the perfluorohexanone microcapsule network to rupture synergistically, releasing perfluorohexanone for targeted fire suppression.

[0080] This embodiment also provides an electronic device applicable to a passive active fire prevention method for power distribution pipe corridors and cabinets, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the passive active fire prevention method for power distribution pipe corridors and cabinets as proposed in the above embodiment.

[0081] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a passive active fire prevention method for power distribution corridors and cabinets as proposed in the above embodiments.

[0082] The storage medium proposed in this embodiment belongs to the same inventive concept as the self-sensing active fire prevention method for power distribution pipe corridors and cabinets proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0083] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0084] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A passive, automatic fire prevention method for power distribution pipe corridors and cabinets, characterized in that: include, In response to the multi-source electromagnetic characteristic spectrum analysis and localization of power distribution facilities, early hotspot areas can be identified; In the early hotspot areas, the critical timing for fire suppression intervention is determined based on the power parameters of the fault point. Performance impact tests were conducted on perfluorohexanone microcapsules and target power distribution equipment to obtain compatibility data. Based on the aforementioned early hotspot areas, key extinguishing timing points, and compatibility data, the installation location of the perfluorohexanone microcapsules is determined comprehensively. A self-sensing integrated module is deployed at the installation location to execute the logic for determining the key extinguishing timing. In response to the self-sensing integrated module determining that a critical extinguishing moment has been reached, perfluorohexanone is released for targeted coverage and extinguishing of the fire.

2. The self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets as described in claim 1, characterized in that, The acquisition of early hotspot areas includes: Based on electrical principles, key monitoring nodes are identified, a monitoring network is constructed at the key monitoring nodes and preprocessed to generate a preprocessed digital signal sequence containing signal characteristics. Receive digital signal sequences, perform time-frequency domain analysis on the signal of each node, extract the corresponding feature vectors, and perform weighted similarity matching. The comprehensive risk score of each node is calculated by mapping the weighted similarity matching results. When the score is greater than or equal to the threshold, it is identified as an early hotspot area and dynamic early warning classification is carried out.

3. The self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets as described in claim 2, characterized in that, The key timing for determining fire suppression intervention includes: Monitor the characteristic arc spectral intensity in early hotspot areas and estimate real-time power loss by inversion; After obtaining the real-time power loss, an ignition time prediction algorithm is constructed to calculate the cumulative net heat and estimated temperature of the fault point and nearby combustibles. In response to the cumulative net heat reaching a preset proportion of the total heat required to heat the combustible to ignition, it is determined that the combustible has reached the thermal runaway critical point, and the time from the beginning to this moment is recorded and defined as the predicted ignition time. If the predicted ignition time is less than or equal to the minimum response time, the system determines that a critical extinguishing time has been reached and immediately generates a fire extinguishing command event.

4. The self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets as described in claim 3, characterized in that, The acquisition of adaptation data includes: A dynamic accelerated aging coupled stress testing platform was constructed, environmental stress and electrical stress were applied to form test samples, periodic coupled stress spectrum was performed on the test samples, and multi-faceted performance parameter data were collected. Based on performance parameter data, the relative degradation rate of each performance index is calculated, and a comprehensive performance score is calculated using dynamic weight allocation based on information entropy and coefficient of variation. The comprehensive performance score is negatively correlated with the fit.

5. The self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets as described in claim 4, characterized in that, Determining the installation location of the perfluorohexanone microcapsules in the device includes: A deployment safety factor is defined for each early hotspot area based on the comprehensive performance score; Set a minimum permissible safety threshold and a priority deployment safety threshold, and make a two-level decision: If the safety factor of the layout is less than the minimum allowable safety factor, the first decision is to prohibit the use of the current plan at the current location. When the safety factor of the layout is greater than or equal to the minimum allowable safety factor, the second decision is executed: among all the layout safety factors that are greater than or equal to the minimum allowable safety factor, the layout safety factor of the scheme with the largest safety factor is selected as the preferred scheme for the current location.

6. The self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets as described in claim 5, characterized in that, The logic for determining the critical timing of the extinguishing operation includes: The self-sensing integrated module is deployed at the second decision point and written with a unique logical address bound to the early hotspot area. Continuously monitor the voltage across the micro energy storage capacitor to initialize the low-power operating mode; After initialization, extract the flag bits that match the logical address to perform state transition; After the state transition, it automatically jumps to the trigger execution state, releasing the stored energy to the underlying actuator to send the fire extinguishing trigger command.

7. The self-sensor-based active fire prevention method for power distribution pipe corridors and cabinets as described in claim 6, characterized in that, The method of releasing perfluorohexanone for targeted fire suppression includes: Upon receiving a fire extinguishing trigger command, the system initiates multi-source signal cross-verification. If the multi-source signal cross-verification result is true, the alarm is deemed valid. After a valid alarm is triggered, the preset release strategy is retrieved according to the location code in the fire extinguishing trigger command, and a synchronous execution command is sent to all associated generators. After the generator detonates, the return status is used to determine whether the main release was successful. If the return status is unsuccessful, the backup redundancy is activated. After the release ends, the extinguishing agent concentration change in the target area is monitored until the fire is extinguished.

8. A passive active fire protection system for power distribution pipe racks and cabinets, employing the passive active fire protection method for power distribution pipe racks and cabinets as described in any one of claims 1 to 7, characterized in that, include: Risk area determination module, fire extinguishing point determination module, matching module, installation module, integrated module, fire extinguishing module; The risk area determination module, in response to the multi-source electromagnetic characteristic spectrum analysis and location of power distribution facilities, obtains early hotspot areas; The fire extinguishing point determination module determines the critical timing for fire extinguishing intervention based on the power parameters of the fault point in the early hotspot area. The matching module performs a performance impact test on the perfluorohexanone microcapsules and the target power distribution equipment to obtain compatibility data. The installation module determines the installation location of the perfluorohexanone microcapsules based on the early hotspot areas, the key extinguishing timing points, and the compatibility data. The integrated module deploys a self-sensing integrated module at the installation location to execute the judgment logic for the key extinguishing timing point. The fire extinguishing module, in response to the self-sensing integrated module determining that a critical extinguishing moment has been reached, releases perfluorohexanone for targeted coverage and fire suppression.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the self-sensor-based active fire prevention method for power distribution corridors and cabinets as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the self-sensor-based active fire prevention method for power distribution corridors and cabinets as described in any one of claims 1 to 7.

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