Fire point automatic identification method of intelligent charging station

Abstract

The application provides a fire point automatic identification method of an intelligent charging station, comprising: grouping each section according to thermal radiation intensity and measured thickness of a smoke layer, identifying an abnormal area of accumulated thickness of a vortex stagnation of a beam recess in each section; obtaining smoke layer deposition thickness distribution data, classifying thermal radiation intensity attenuation of the beam recess position according to the smoke layer deposition thickness distribution data, generating an attenuation distribution diagram, and identifying a potential fire point shielding area in a smoke exhaust path; according to the potential fire point shielding area, extracting a beam recess smoke layer shielding rate with a longer stagnation time from the smoke layer thickness distribution diagram, rechecking the smoke layer shielding rate in combination with the vortex stagnation time of the beam recess and the beam recess spacing, obtaining a rechecked thermal radiation intensity distribution sequence; and according to the rechecked thermal radiation intensity distribution sequence, iteratively updating thermal radiation attenuation characteristics along the slope under the influence of the ceiling slope angle, and determining a real fire point position coordinate under the smoke layer shielding.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a method for automatic fire point identification in smart charging stations. Background Technology

[0002] In the field of safety management of smart charging stations, early fire identification and accurate location are crucial, as they directly relate to personnel safety and equipment protection, and are an indispensable part of ensuring the operation of new energy facilities. With the widespread adoption of electric vehicles, charging stations, as high-density energy locations, pose a significant fire risk, and any delay in addressing a fire can lead to serious consequences. When a fire breaks out due to battery thermal runaway or electrical short circuit within a charging station, the high-temperature smoke released from the fire source rises continuously under buoyancy, forming a thermal plume that eventually spreads horizontally along the lower surface of the roof after being blocked by the roof surface, gradually forming a continuous smoke accumulation layer in the roof area. However, existing methods often struggle to adapt to dynamically changing scenarios when dealing with fire identification in complex environments, especially regarding the impact of the roof structure on smoke flow, lacking in-depth consideration. These methods focus more on the simple patterns of overall smoke distribution, ignoring the local interference of the specific roof structure on smoke accumulation, leading to deviations in fire location judgment under certain conditions and affecting the accuracy of early warnings. A deeper technical challenge lies in the impact of the roof slope, a key factor, on the thickness of the smoke accumulation layer. The slope of the ceiling is intended to accelerate the upward discharge of smoke and reduce its accumulation through its inclination angle. However, when the slope is steep, the smoke flows at high speed in the grooves between the transverse structural beams of the ceiling. This flow obstruction creates swirling airflow, leading to prolonged smoke retention time and increased smoke accumulation thickness in certain areas. This phenomenon contradicts the expected reduction in accumulation due to the increased slope, creating a complex technical challenge. In particular, when smoke lingers between the beams, it obscures the thermal signals of fire ignition points below, making accurate fire location difficult. For example, in a charging station, the ceiling was designed with a steep slope to facilitate smoke discharge. However, during a fire, the smoke swirled repeatedly in the grooves between the beams, resulting in smoke layers in some areas far thicker than those on gentler slopes. This prevented detection equipment positioned below the ceiling from penetrating the thick smoke layer, leading to misjudgments of the fire location and even missing the optimal time for fire suppression. This problem of localized smoke accumulation caused by the interaction between the slope and structural beams severely affects the reliability of fire location. Therefore, how to accurately identify local changes in smoke accumulation under the combined effect of ceiling slope and structural beams, and locate the actual fire point through the complex smoke layer, has become a key problem that this study urgently needs to solve. Summary of the Invention

[0003] This invention provides an automatic fire point identification method for intelligent charging stations, mainly including: By deploying infrared probes and smoke layer thickness measuring instruments along the longitudinal direction of the ceiling, the thermal radiation intensity, measured smoke layer thickness, and eddy current retention time in the grooves between beams of each section are collected. At the same time, the ceiling slope angle and the spacing between beams are measured, and a preliminary flue gas distribution dataset is obtained by fusion. Based on the thermal radiation intensity and the measured thickness of the smoke layer, each section was grouped and processed to identify the abnormal areas of accumulated thickness in each section where the eddy current retention time in the groove between beams was prominent. Assess the thermal radiation intensity in areas with abnormal accumulation thickness. When the thermal radiation intensity exceeds the preset radiation threshold, calculate the depth of smoke deposition between beams using the roof slope angle and beam spacing. Based on the depth of smoke deposition between beams, redetermine the measured thickness of the smoke layer in areas with abnormal accumulation thickness and obtain the smoke layer deposition thickness distribution data. Acquire smoke layer deposition thickness distribution data, classify the thermal radiation intensity attenuation at the location of the interbeam groove based on the smoke layer deposition thickness distribution data, generate attenuation distribution map, and identify potential fire point shielding areas in the smoke exhaust path. Based on the potential fire point shielding area, the smoke shielding rate of the inter-beam groove with a longer residence time is extracted from the smoke layer thickness distribution map. The smoke shielding rate is then verified by combining the eddy residence time of the inter-beam groove with the inter-beam spacing, and the verified thermal radiation intensity distribution sequence is obtained. Based on the verified heat radiation intensity distribution sequence, the heat radiation attenuation characteristics along the slope under the influence of the roof slope angle are iteratively updated to determine the coordinates of the actual fire point location under the smoke layer cover. Consistency analysis was performed on the actual fire point location coordinates and the preliminary flue gas distribution dataset. When the consistency of the coordinate positioning was lower than the preset consistency threshold, the accumulation thickness distribution was recalculated by integrating the eddy current residence time in the inter-beam groove and the inter-beam spacing to determine the fire point location.

[0004] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses an automatic fire point identification method for intelligent charging stations. Addressing the challenges of complex smoke distribution and precise fire point location in charging station ceiling environments, this method integrates multi-dimensional data such as thermal radiation intensity, smoke layer thickness, and eddy current retention time in beam-interval grooves to construct a comprehensive smoke distribution dataset. First, data is collected using infrared detectors and smoke layer thickness measuring instruments to identify areas with abnormal accumulation thickness. The smoke deposition depth is calculated by combining the ceiling slope angle and beam spacing, thus redetermining the smoke layer thickness distribution and generating a smoke layer thickness distribution map. Potential fire point shielding areas and smoke layer shielding rates are then extracted. Finally, by iteratively updating thermal radiation attenuation characteristics, the actual fire point location coordinates are accurately determined. In consistency analysis, if the consistency is insufficient, multiple parameters are integrated to recalculate the accumulation thickness distribution, ensuring accurate positioning. The core of this invention lies in significantly improving the accuracy and reliability of fire point identification in complex environments through multi-source data fusion and iterative optimization, providing efficient technical support for fire prevention and control in charging stations. Attached Figure Description

[0005] Figure 1 This is a flowchart of the automatic fire point identification method for the intelligent charging station of the present invention.

[0006] Figure 2 This is a schematic diagram of the automatic fire point identification method for the intelligent charging station of the present invention.

[0007] Figure 3 This is another schematic diagram of the automatic fire point identification method for the intelligent charging station of the present invention. Detailed Implementation

[0008] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0009] like Figures 1-3 The automatic fire point identification method for the smart charging station in this embodiment may specifically include: Step S101: By deploying infrared probes and smoke layer thickness measuring instruments along the longitudinal direction of the ceiling, the thermal radiation intensity, measured smoke layer thickness, and eddy current retention time in the grooves between beams of each section are collected. At the same time, the ceiling slope angle and the spacing between beams are measured, and a preliminary smoke distribution dataset is obtained by fusion.

[0010] An array of infrared probes is arranged at preset intervals along the longitudinal direction of the charging station roof. Each infrared probe corresponds to a roof section and records the corresponding acquisition timestamp, collecting the thermal radiation intensity values ​​of each section. Simultaneously, smoke layer thickness measuring instruments are installed at the groove positions between adjacent beams, and their corresponding acquisition timestamps are recorded to obtain the measured smoke layer thickness in each groove. Based on the spatial coordinates of the infrared probes and smoke layer thickness measuring instruments, section division markers are established. By deploying airflow sensors in each groove and recording their corresponding acquisition timestamps, the vortex motion trajectory of the smoke after entering the groove is recorded. The time it takes for the vortex to complete one cycle in the groove is counted as the vortex residence time in the groove. An inclination sensor is used to measure the roof slope angle and record the corresponding acquisition timestamp. A laser rangefinder is used to measure the beam spacing between adjacent structural beams and record the corresponding acquisition timestamp. The roof slope angle and beam spacing are categorized and stored according to the section division markers. Based on the segment division identifier, the thermal radiation intensity, measured smoke layer thickness, eddy current retention time in the inter-beam groove, roof slope angle and inter-beam spacing are aligned according to the same segment. The data from each sensor are synchronously matched and fused together using the acquisition timestamp to obtain a preliminary flue gas distribution dataset containing multi-dimensional measurement information of each segment.

[0011] In one embodiment, when deploying an infrared probe array along the longitudinal direction of the charging station roof, each infrared probe is fixed sequentially at a preset interval. The detection range of each infrared probe covers an independent roof section. While collecting thermal radiation intensity values, the infrared probe records the corresponding collection timestamp. This timestamp is used to mark the time when the data is generated. Based on the installation coordinates of the infrared probe and the smoke layer thickness measuring instrument on the roof plane, the spatial boundaries of each section are delineated to form a section division identifier.

[0012] For example, the smoke layer thickness measuring instrument is installed in the groove between adjacent structural beams. It emits ultrasonic waves into the smoke layer and receives the echo signal to measure the round-trip time of the ultrasonic waves through the smoke layer. The measured thickness of the smoke layer is calculated according to the formula d=v×t / 2, where d is the smoke layer thickness, v is the speed of sound, and t is the round-trip time.

[0013] Specifically, the process of obtaining the vortex residence time in the inter-beam groove is as follows: airflow sensors are deployed on the inner wall of each inter-beam groove. When the flue gas enters the groove, it is blocked by the side wall of the groove, forming a rotating airflow. The airflow sensor continuously records the flow direction and velocity changes of the flue gas. The software analyzes these data to calculate the average velocity v of the flue gas in the groove. Then, the effective length L of the groove is divided by v to obtain the average residence time t=L / v, where L is the groove depth and v is the average velocity. This residence time reflects the degree of retention of the flue gas in the groove. The longer the residence time, the greater the possibility of flue gas accumulating in this area.

[0014] In one possible implementation, an inclination sensor is fixed to the ceiling surface and uses a built-in accelerometer to sense the angle between the direction of gravity and the normal direction of the ceiling surface, outputting the ceiling slope angle value. A laser rangefinder is mounted on a structural beam, emits lasers to adjacent structural beams and measures the reflection time to obtain the beam spacing.

[0015] It should be noted that during data fusion processing, the thermal radiation intensity, measured thickness of the smoke layer, eddy current residence time in the groove between beams, roof slope angle and beam spacing of the same section are collected together according to the section division identifier. By comparing the collection timestamps recorded by each sensor, data with a timestamp difference of no more than 5 seconds are selected for matching. The matched multi-dimensional data are spliced ​​together to form a preliminary flue gas distribution dataset, which contains complete measurement information of each section at the same time.

[0016] Step S102: Based on the thermal radiation intensity and the measured thickness of the smoke layer, each section is grouped and processed to identify the abnormal areas of accumulated thickness in each section where the eddy current retention time in the inter-beam groove is prominent.

[0017] The thermal radiation intensity and measured smoke layer thickness of each section are extracted from the preliminary flue gas distribution dataset. If the thermal radiation intensity exceeds a preset radiation threshold, the section is classified into a high-radiation group. Within the high-radiation group, the section is further divided according to whether the measured smoke layer thickness exceeds a preset thickness threshold to obtain a thickness anomaly group. For each section within the thickness anomaly group, the eddy current residence time in the inter-beam groove is extracted. If the residence time exceeds a preset residence threshold, the section is marked as an area with an accumulation thickness anomaly.

[0018] In one embodiment, the thermal radiation intensity values ​​of each section are read one by one from the preliminary flue gas distribution dataset. The values ​​are compared with a preset radiation threshold. When the thermal radiation intensity exceeds the preset radiation threshold, it indicates that there is a high heat source influence in the section, and it is classified into the high radiation group. Within the high radiation group, the measured thickness of the smoke layer of each section is further extracted, and the measured thickness of the smoke layer is compared with a preset thickness threshold. When the measured thickness of the smoke layer exceeds the preset thickness threshold, the section is classified into the thickness abnormal group.

[0019] Specifically, for each section within the thickness anomaly group, the corresponding eddy current retention time in the inter-beam groove is read, and the retention time is compared with a preset retention threshold. If the retention time exceeds the preset retention threshold, it indicates that the flue gas has formed a long-term eddy current retention in the inter-beam groove of that section, and that section is marked as an area with abnormal accumulation thickness.

[0020] It should be noted that by using a two-level grouping screening based on thermal radiation intensity and measured smoke layer thickness, combined with the judgment of eddy current retention time, it is possible to locate local areas with a high degree of smoke accumulation from multiple sections.

[0021] Step S103: Evaluate the thermal radiation intensity of the area with abnormal accumulation thickness. When the thermal radiation intensity exceeds the preset radiation threshold, calculate the depth of smoke deposition between beams by using the ceiling slope angle and the beam spacing. Based on the depth of smoke deposition between beams, redetermine the measured thickness of the smoke layer in the area with abnormal accumulation thickness to obtain the smoke layer deposition thickness distribution data.

[0022] For the regions with abnormal accumulation thickness, the corresponding thermal radiation intensity values ​​are extracted for each region. These thermal radiation intensities are then compared one by one with a preset radiation threshold. If the thermal radiation intensity exceeds the preset threshold, the region is marked as a high-radiation-abnormal region, and its location is identified. Based on the location identifiers of these high-radiation-abnormal regions, the corresponding ceiling slope angle, beam spacing, and inter-beam groove depth are extracted from the preliminary flue gas distribution dataset. The groove depth is a pre-measured parameter. The beam spacing is considered as a horizontal distance s, and multiplied by the tangent of the ceiling slope angle θ to obtain the vertical infiltration distance d = s × tan(θ) along the slope direction. This distance represents the vertical rise height of the flue gas. Adding d to the groove depth h yields the flue gas deposition depth between the beams, which compensates for the hidden flue gas depth between the beams. The measured thickness t of the smoke layer in the high-radiation anomaly area is corrected based on the depth of smoke deposition between beams. The correction formula is: Corrected thickness = t + (d + h - t'), where t' is the estimated visible thickness. Physically, t' compensates for the hidden deposition effect after deducting the duplicated portion, avoiding inconsistencies, and thus yields the corrected smoke layer deposition thickness. The corrected smoke layer deposition thicknesses for each area are then summarized and organized according to the spatial arrangement of the high-radiation anomaly areas along the longitudinal direction of the ceiling, resulting in smoke layer deposition thickness distribution data.

[0023] In one embodiment, the identification of high radiation anomaly areas is based on the comparison between thermal radiation intensity and a preset radiation threshold. When the thermal radiation intensity of a certain accumulation thickness anomaly area exceeds the preset radiation threshold, it indicates that there is a strong heat source below the area. The accumulation of flue gas in the area has a significant shielding effect on the thermal radiation signal. The area is marked as a high radiation anomaly area, and its position in the longitudinal direction of the ceiling is recorded. The position identifier is used to extract the corresponding geometric parameters from the preliminary flue gas distribution dataset.

[0024] Specifically, the preset radiation threshold is set based on the background value of thermal radiation under normal operating conditions in the charging station. When the detected thermal radiation intensity is significantly higher than the background value, the high radiation anomaly area is marked.

[0025] It should be noted that the ceiling slope angle, beam spacing, and inter-beam groove depth are three key geometric parameters for calculating the depth of flue gas deposition between beams. The ceiling slope angle determines the inclination direction of flue gas as it flows along the ceiling surface, the beam spacing determines the horizontal span between adjacent structural beams, and the inter-beam groove depth determines the vertical accommodating space of the groove itself. These three parameters are extracted from the preliminary flue gas distribution dataset according to the location markers of high radiation anomaly areas.

[0026] In one possible implementation, the calculation of the vertical infiltration distance reflects the vertical component of flue gas as it infiltrates along the slope of the inclined ceiling surface. When the flue gas rises from the fire point to the ceiling and flows along the slope, it moves horizontally and vertically due to the slope of the ceiling. The beam spacing is taken as the horizontal distance of the flue gas movement, and multiplied by the tangent of the ceiling slope angle, which represents the ratio of vertical displacement to horizontal displacement, thus obtaining the vertical infiltration distance of the flue gas when it moves one beam spacing along the slope. This distance reflects the additional vertical deposition depth of the flue gas caused by the inclination of the ceiling.

[0027] For example, the determination of the depth of flue gas deposition between beams involves adding the vertical penetration distance to the depth of the inter-beam groove. The vertical penetration distance represents the depth to which flue gas penetrates due to the slope, while the groove depth represents the inherent depth of the groove itself. Adding these two values ​​yields the total actual depth of flue gas deposition within the inter-beam groove in this high-radiation-anomaly area. Furthermore, the correction of the measured smoke layer thickness is based on the cumulative effect of the flue gas deposition depth on the smoke layer thickness. The measured smoke layer thickness is a value directly measured by a smoke layer thickness measuring instrument. This value only reflects the visible thickness of the smoke layer in the vertical direction and does not consider the deposition depth of flue gas within the inter-beam groove. When flue gas is deposited inside the groove, some of it is contained by the groove structure. Although this portion of flue gas is not directly reflected in the visible smoke layer thickness, it still has a shielding effect on the thermal radiation signal. Therefore, adding the depth of flue gas deposition between beams to the measured smoke layer thickness yields a corrected smoke layer deposition thickness that reflects the actual shielding capacity of the flue gas.

[0028] It is understandable that the corrected smoke layer deposition thickness is greater than the original measured smoke layer thickness. The difference is the depth of smoke deposition between beams. This correction process makes the smoke layer thickness data more accurately reflect the actual degree of smoke shielding of thermal radiation signals.

[0029] In one embodiment, according to the spatial arrangement order of each high radiation anomaly region in the longitudinal direction of the ceiling from low to high, the corrected smoke layer deposition thickness value and its corresponding location identifier of each region are recorded in sequence. The data of all high radiation anomaly regions are summarized and organized to form smoke layer deposition thickness distribution data. This distribution data includes the location information of each region and the corresponding corrected deposition thickness value, which can intuitively show the difference in the deposition thickness of flue gas at different locations on the ceiling.

[0030] Step S104: Obtain smoke layer deposition thickness distribution data, classify the thermal radiation intensity attenuation at the location of the inter-beam groove based on the smoke layer deposition thickness distribution data, generate an attenuation distribution map, and identify potential fire point shielding areas in the smoke exhaust path.

[0031] Acquire smoke layer deposition thickness distribution data, extract the deposition thickness value d corresponding to each inter-beam groove location, read the original thermal radiation intensity before smoke layer shielding and the currently detected thermal radiation intensity at that location, and subtract the current thermal radiation intensity from the original thermal radiation intensity to obtain the radiation attenuation amount at each inter-beam groove location. Classify each inter-beam groove location according to the product of the radiation attenuation amount multiplied by the thickness d and a preset attenuation coefficient k. If the value exceeds a preset attenuation threshold, the location is marked as a high attenuation zone; if the value is below the preset attenuation threshold, the location is marked as a low attenuation zone. Generate a smoke layer thickness distribution map according to the spatial distribution of the high and low attenuation zones in the longitudinal direction of the ceiling. Determine the smoke exhaust path direction based on the ceiling slope angle, and traverse along the smoke exhaust path direction in the smoke layer thickness distribution map. If multiple consecutive inter-beam groove locations belong to the high attenuation zone, the continuous area is identified as a potential fire point shielding zone.

[0032] In one embodiment, the calculation of radiation attenuation is based on the principle of energy loss of thermal radiation signals when penetrating the smoke layer. When the smoke accumulates in the groove between the beams to form a thick smoke layer, the thermal radiation signal emitted by the infrared probe is absorbed and scattered by the smoke particles during the process of penetrating the smoke layer, resulting in the detected thermal radiation intensity being lower than the original thermal radiation intensity before the smoke layer was formed. The difference between the original thermal radiation intensity and the currently detected thermal radiation intensity is the radiation attenuation at the location of the groove between the beams. The greater the radiation attenuation, the higher the degree of shielding of the thermal radiation signal by the smoke layer at that location.

[0033] Specifically, the radiation attenuation at each groove location between beams is compared with a preset attenuation threshold. This threshold is set based on the typical shielding effect of smoke layer thickness on thermal radiation, and is usually set to 0.5, representing 50% attenuation. When the radiation attenuation exceeds the preset attenuation threshold, it indicates that the smoke layer thickness at that location is large and has a strong shielding effect on thermal radiation, and it is marked as a high attenuation zone. When the radiation attenuation is lower than the preset attenuation threshold, it is marked as a low attenuation zone.

[0034] For example, the high attenuation zone and the low attenuation zone are distinguished and marked with different symbols according to their spatial positions in the longitudinal direction of the ceiling, forming a smoke layer thickness distribution map. This distribution map intuitively shows the difference in the degree of smoke layer shading at the groove positions between beams.

[0035] In one possible implementation, the direction of the flue gas discharge path is determined based on the roof slope angle. Since the flue gas flows upward along the inclined surface of the roof under the action of buoyancy, the roof slope angle determines the main flow direction of the flue gas. The path direction of the flue gas discharged from the low point to the high point is determined based on the roof slope angle measured by the tilt sensor installed on the roof.

[0036] It should be noted that when traversing the locations of the inter-beam grooves sequentially along the flue gas discharge path in the smoke layer thickness distribution map, if multiple consecutive adjacent inter-beam groove locations are detected to be in high attenuation zones, it indicates that the flue gas has formed a continuous thick smoke layer in this area. This continuous area is identified as a potential fire point shielding zone, where the fire point thermal signal is blocked by the thick smoke layer and is difficult to detect directly.

[0037] Step S105: Based on the potential fire point shielding area, extract the smoke shielding rate of the inter-beam groove with a longer residence time from the smoke layer thickness distribution map, and verify the smoke shielding rate by combining the eddy residence time of the inter-beam groove with the inter-beam spacing to obtain the verified thermal radiation intensity distribution sequence.

[0038] Based on the potential fire point shielding zone, the locations of the inter-beam grooves with longer retention times are identified from the smoke layer thickness distribution map. The smoke layer deposition thickness and radiation attenuation corresponding to these locations are extracted. The radiation attenuation is divided by the original thermal radiation intensity to obtain the smoke layer shielding rate for each inter-beam groove location. The eddy current retention time and beam spacing of the inter-beam grooves are obtained. If the eddy current retention time exceeds a preset time threshold and the beam spacing is less than a preset spacing threshold, it is determined that there is an aggravated smoke retention phenomenon at this location. The smoke layer shielding rate is multiplied by a preset correction coefficient to obtain the verified smoke layer shielding rate. The thermal radiation transmittance is calculated based on the verified smoke layer shielding rate. The thermal radiation transmittance is the value of 1 minus the verified smoke layer shielding rate. The original thermal radiation intensity is multiplied by the thermal radiation transmittance to obtain the compensated thermal radiation intensity. The compensated thermal radiation intensity of each inter-beam groove location is arranged in the longitudinal direction of the ceiling to obtain the verified thermal radiation intensity distribution sequence.

[0039] In one embodiment, the smoke shielding rate is used to characterize the degree to which the smoke layer blocks thermal radiation signals. From the potential fire point shielding area, the inter-beam groove position with a longer eddy current retention time is selected. The smoke shielding rate value of this position is between 0 and 1. The closer the value is to 1, the stronger the shielding effect of the smoke layer on thermal radiation, and the higher the degree to which the thermal signal of the fire point is blocked.

[0040] Specifically, the eddy current residence time and the beam spacing together affect the accumulation state of flue gas in the groove. When the eddy current residence time exceeds the preset time threshold, it indicates that the flue gas stays in the groove for a long time. When the beam spacing is less than the preset spacing threshold, it indicates that the space between adjacent structural beams is relatively narrow and the flue gas is difficult to be discharged quickly. When both conditions are met at the same time, it is determined that there is an aggravated flue gas retention phenomenon at this location.

[0041] For example, the preset correction coefficient is a value greater than 1. When it is determined that there is an aggravated smoke retention, the smoke layer shading rate is multiplied by the preset correction coefficient so that the verified smoke layer shading rate is higher than the original smoke layer shading rate, so as to reflect the enhanced effect of the aggravated smoke retention on the degree of shading.

[0042] In one possible implementation, thermal radiation transmittance and verified smoke layer shading rate are complementary. Thermal radiation transmittance is equal to the value 1 minus the verified smoke layer shading rate. Thermal radiation transmittance represents the proportion of thermal radiation signal retained after penetrating the smoke layer. The original thermal radiation intensity is multiplied by the thermal radiation transmittance to obtain the compensated thermal radiation intensity, which reflects the true thermal radiation level after removing the smoke layer shading effect.

[0043] It should be noted that the compensated thermal radiation intensity of the groove positions between each beam is arranged sequentially along the longitudinal direction of the ceiling to form a verified thermal radiation intensity distribution sequence. The positions with higher thermal radiation intensity in this sequence are more likely to contain fire points.

[0044] Step S106: Iteratively update the thermal radiation attenuation characteristics along the slope under the influence of the roof slope angle based on the verified thermal radiation intensity distribution sequence, and determine the coordinates of the actual fire point location under the smoke layer cover.

[0045] The verified thermal radiation intensity distribution sequence is obtained. Compensated thermal radiation intensity values ​​at the groove locations between beams are extracted along the longitudinal direction of the ceiling. Using the lowest point of the ceiling slope as a reference point, the slope height difference relative to the reference point is calculated based on the ceiling slope angle. A correspondence between the compensated thermal radiation intensity and the slope height difference is established, resulting in a thermal radiation distribution curve along the slope. The maximum point of thermal radiation intensity is searched on this curve, and the corresponding slope height difference is marked as the peak position. If multiple maximum points exist, the maximum point with the largest thermal radiation intensity value is selected as the main peak position. For the thermal radiation distribution curve along the slope, the least squares method is used to fit the attenuation trend of thermal radiation intensity with the slope height difference, resulting in a slope attenuation characteristic curve. The measured compensated thermal radiation intensity is compared with the predicted value of the slope attenuation characteristic curve. If the deviation exceeds a preset deviation threshold, the fitting parameters are adjusted and refitted. The slope attenuation characteristic curve is iteratively updated until the deviation converges. Based on the slope height difference corresponding to the main peak position, the slope height difference is divided by the sine of the roof slope angle to obtain the distance along the slope direction. This distance is then multiplied by the cosine of the roof slope angle to obtain the horizontal projection distance. Combined with the spatial coordinates of the reference point, the coordinates of the actual fire point location under the smoke layer are determined.

[0046] In one embodiment, the thermal radiation distribution curve along the slope is established based on the spatial distribution law of thermal radiation signals propagating on the inclined roof surface. Since the charging station roof has a certain slope angle, the thermal radiation signal released by the fire point will gradually attenuate as the propagation distance increases when it propagates along the roof slope direction. The compensated thermal radiation intensity values ​​of each inter-beam groove position are extracted from the verified thermal radiation intensity distribution sequence. At the same time, according to the roof slope angle and the arrangement order of each position in the longitudinal direction, the slope height difference of each position relative to the reference benchmark is calculated. The compensated thermal radiation intensity is used as the vertical axis and the slope height difference is used as the horizontal axis to draw the thermal radiation distribution curve along the slope.

[0047] Specifically, the reference point is selected based on the lowest point of the roof slope, which is usually located at one end of the charging station roof. The roof slope angle is measured by the tilt sensor installed on the roof. The sensor measures the slope by sensing the direction of gravity. The product of the distance between the grooves between each beam and the sine of the slope angle is accumulated along the slope direction to obtain the slope height difference at each location.

[0048] It should be noted that the purpose of least squares fitting is to extract the overall attenuation trend of thermal radiation intensity as a function of slope height difference from the discrete thermal radiation distribution curve along the slope. Least squares fits a curve that minimizes the sum of squares of the distances from all measured data points to the curve. The specific process is as follows: assuming that thermal radiation intensity decreases exponentially with slope height difference, an initial attenuation coefficient is set, the vertical distance from each data point to the fitted curve is calculated, and the sum of the squares of all distances is obtained to get the sum of squares of the residuals. By adjusting the attenuation coefficient, the sum of squares of the residuals is minimized. The curve obtained at this point is the slope attenuation characteristic curve, which reflects the attenuation law of thermal radiation intensity along the slope direction under the current roof slope angle.

[0049] In one possible implementation, the iterative update process addresses the deviation between the fitted results and the measured data. The deviation value is obtained by subtracting the compensated thermal radiation intensity at each location from the predicted value of the slope attenuation characteristic curve at the corresponding slope height difference. The root mean square of the deviation values ​​at all locations is calculated as the overall deviation index. If the overall deviation exceeds the preset deviation threshold, the attenuation coefficient is adjusted and the least squares fitting is re-executed. The above process is repeated until the overall deviation is lower than the preset deviation threshold, at which point the iteration is considered to have converged.

[0050] For example, the search for the maximum point is performed on the discrete sampling points of the compensated thermal radiation distribution curve along the slope. The thermal radiation intensity values ​​of adjacent sampling points are compared sequentially along the slope height difference direction. When the thermal radiation intensity of a sampling point is greater than the thermal radiation intensity of its previous and next sampling points at the same time, the sampling point is marked as the maximum point.

[0051] Understandably, in actual fire scenarios, due to the uneven distribution of smoke and the local shielding effect of the inter-beam grooves, multiple maxima may appear on the slope attenuation characteristic curve. In this case, the maximum value of the thermal radiation intensity is selected as the main peak position, as the thermal radiation signal at this position is the strongest, indicating the highest probability of a fire point. Further, the trigonometric function calculation process uses the roof slope angle to convert the slope height difference into spatial coordinates within the charging station plane. According to geometric relationships, dividing the slope height difference by the sine of the roof slope angle yields the inclined distance from the fire point along the roof slope direction to the reference benchmark. Multiplying this inclined distance by the cosine of the roof slope angle yields the horizontal projection distance of the fire point relative to the reference benchmark. Multiplying this inclined distance by the sine of the roof slope angle yields the vertical height difference of the fire point relative to the reference benchmark. These are then combined with the known spatial coordinates of the reference benchmark within the charging station plane for calculation.

[0052] In one embodiment, the horizontal position coordinates of the fire point are obtained by adding the horizontal projection distance of the fire point to the horizontal coordinates of the reference point, and the vertical height coordinates of the fire point are obtained by adding the height difference of the fire point to the vertical coordinates of the reference point. This determines the position coordinates of the actual fire point in the three-dimensional space of the charging station under the cover of smoke. This coordinate information can indicate the specific orientation of the fire point relative to the ground and walls of the charging station.

[0053] Step S107: Perform consistency analysis on the actual fire point location coordinates and the preliminary smoke distribution dataset. When the consistency of the coordinate positioning is lower than the preset consistency threshold, recalculate the accumulation thickness distribution by integrating the eddy current residence time of the inter-beam groove and the inter-beam spacing to determine the fire point location.

[0054] The actual fire point location coordinates and preliminary smoke distribution dataset are obtained. The thermal radiation intensity of the segment corresponding to the fire point location coordinates is extracted from the preliminary smoke distribution dataset. The thermal radiation intensity at the fire point location coordinates is subtracted from the original thermal radiation intensity of that segment to obtain the deviation value. The deviation value is divided by the original thermal radiation intensity to obtain the deviation ratio. The deviation ratio is subtracted from the value 1 to obtain the coordinate positioning accuracy. If the accuracy is lower than a preset accuracy threshold, the eddy current retention time and beam spacing in the inter-beam groove are re-extracted from the preliminary smoke distribution dataset. The eddy current retention time is multiplied by the beam spacing to obtain the smoke retention volume index of each segment. The smoke layer deposition thickness is proportionally redistributed according to the proportion of the smoke retention volume index in the total of each segment, resulting in a corrected accumulation thickness distribution. Based on the corrected accumulation thickness distribution, the segment with the largest accumulation thickness value is located. The center position of this segment is used as the horizontal coordinate of the fire point, and the corresponding ceiling height is used as the vertical coordinate of the fire point to determine the fire point location.

[0055] In one embodiment, the consistency calculation is used to evaluate the degree of matching between the actual fire point location coordinates and the preliminary smoke distribution dataset. The thermal radiation intensity value of the segment corresponding to the fire point location coordinates is read from the preliminary smoke distribution dataset. This value is subtracted from the original thermal radiation intensity of the segment recorded before the fire occurred to obtain the deviation value. The deviation value reflects the difference between the thermal radiation detection result at the fire point location and the original state. The deviation value is divided by the original thermal radiation intensity to obtain the deviation ratio. Subtracting the deviation ratio from the value 1 gives the consistency of the coordinate location. The closer the consistency is to the value 1, the higher the degree of matching between the fire point location coordinates and the smoke distribution data.

[0056] Specifically, the calculated matching degree is compared with a preset matching degree threshold. When the matching degree is lower than the preset matching degree threshold, it indicates that there is a large deviation in the current fire point position coordinates, triggering the subsequent correction process.

[0057] It should be noted that the introduction of the flue gas retention volume index is a key basis for correcting the location of the fire point. This index is obtained by multiplying the eddy current retention time of the inter-beam groove in each section by the inter-beam spacing. The eddy current retention time of the inter-beam groove reflects the length of time that the flue gas stays in the inter-beam groove, and the inter-beam spacing reflects the spatial capacity of the inter-beam groove. The product of the two represents the cumulative volume of flue gas retained in the inter-beam groove of that section. The larger the flue gas retention volume index of a section, the higher the degree of flue gas accumulation at that location, and the greater the possibility that the fire point is located near that section.

[0058] In one possible implementation, the total retention volume is obtained by summing the flue gas retention volume indices of each section. The proportion coefficient of each section is obtained by dividing the flue gas retention volume index of each section by the total retention volume. The initial accumulation thickness of each section is initially calculated based on the flue gas retention volume index. The total smoke layer deposition thickness is obtained by summing the initial accumulation thickness of each section. The total smoke layer deposition thickness is multiplied by the proportion coefficient of each section to obtain the corrected accumulation thickness distribution of each section.

[0059] For example, the accumulation thickness values ​​of each segment are traversed in the corrected accumulation thickness distribution, the segment with the largest accumulation thickness value is located, the center position of the segment in the charging station plane is calculated as the corrected horizontal coordinate of the fire point, that is, the coordinate of the center point of the segment in the plane, and the ceiling height corresponding to the segment is directly used as the corrected vertical coordinate of the fire point to reflect the position of the fire point in the vertical direction, thereby determining the fire point location after consistency verification and correction.

[0060] If the technical solution of this application involves the processing of personal information, the relevant products have established a sound user authorization mechanism: before collecting, using, or sharing personal information, the obligation to inform is fulfilled in accordance with the law, and the individual's voluntary and explicit consent is obtained; if sensitive personal information is involved, the user's separate and explicit consent is further obtained. Specific measures include, but are not limited to: setting up prominent prompts in the information collection area, or clearly displaying the processing rules (including the processor, purpose, method, information type, etc.) through electronic interfaces such as pop-ups, checkboxes, and active submissions, to ensure that users voluntarily authorize based on their knowledge. All personal information processing activities strictly comply with national laws and regulations, especially the relevant provisions of the "Personal Information Protection Law of the People's Republic of China," to effectively safeguard the legitimate rights and interests of personal information subjects.

[0061] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. A method for automatic fire point identification in intelligent charging stations, characterized in that, The method includes: By deploying infrared probes and smoke layer thickness measuring instruments along the longitudinal direction of the ceiling, the thermal radiation intensity, measured smoke layer thickness, and eddy current retention time in the grooves between beams of each section are collected. At the same time, the ceiling slope angle and the spacing between beams are measured, and a preliminary flue gas distribution dataset is obtained by fusion. Based on the thermal radiation intensity and the measured thickness of the smoke layer, each section was grouped and processed to identify the abnormal areas of accumulated thickness in each section where the eddy current retention time in the groove between beams was prominent. Assess the thermal radiation intensity in areas with abnormal accumulation thickness. When the thermal radiation intensity exceeds the preset radiation threshold, calculate the depth of smoke deposition between beams using the roof slope angle and beam spacing. Based on the depth of smoke deposition between beams, redetermine the measured thickness of the smoke layer in areas with abnormal accumulation thickness and obtain the smoke layer deposition thickness distribution data. Acquire smoke layer deposition thickness distribution data, classify the thermal radiation intensity attenuation at the location of the interbeam groove based on the smoke layer deposition thickness distribution data, generate attenuation distribution map, and identify potential fire point shielding areas in the smoke exhaust path. Based on the potential fire point shielding area, the smoke shielding rate of the inter-beam groove with a longer residence time is extracted from the smoke layer thickness distribution map. The smoke shielding rate is then verified by combining the eddy residence time of the inter-beam groove with the inter-beam spacing, and the verified thermal radiation intensity distribution sequence is obtained. Based on the verified heat radiation intensity distribution sequence, the heat radiation attenuation characteristics along the slope under the influence of the roof slope angle are iteratively updated to determine the coordinates of the actual fire point location under the smoke layer cover. Consistency analysis was performed on the actual fire point location coordinates and the preliminary flue gas distribution dataset. When the consistency of the coordinate positioning was lower than the preset consistency threshold, the accumulation thickness distribution was recalculated by integrating the eddy current residence time in the inter-beam groove and the inter-beam spacing to determine the fire point location.

2. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The process involves deploying infrared probes and smoke layer thickness measuring instruments along the longitudinal direction of the ceiling to collect data on the thermal radiation intensity, measured smoke layer thickness, and eddy current retention time in the inter-beam grooves of each section. Simultaneously, the ceiling slope angle and inter-beam spacing are measured, and the data are fused to obtain a preliminary smoke distribution dataset, including: An array of infrared probes is arranged at preset intervals along the longitudinal direction of the charging station roof. Each infrared probe corresponds to a roof section and records the corresponding collection timestamp. The thermal radiation intensity values ​​of each section are collected. At the same time, a smoke layer thickness measuring instrument is installed at the groove position between adjacent beams and records the corresponding collection timestamp. The measured thickness of the smoke layer in each groove between beams is obtained. Based on the spatial coordinates of the infrared probes and the smoke layer thickness measuring instrument, a section division mark is established. By deploying airflow sensors in the grooves between beams and recording the corresponding acquisition timestamps, the vortex motion trajectory of flue gas after entering the grooves is recorded. The time it takes for the vortex to complete one cycle in the groove is counted as the vortex residence time in the groove between beams. The roof slope angle is measured by an inclination sensor and the corresponding acquisition timestamp is recorded. The beam spacing between adjacent structural beams is measured by a laser rangefinder and the corresponding acquisition timestamp is recorded. The roof slope angle and beam spacing are classified and stored according to the section division identifier. Based on the segment division identifier, the thermal radiation intensity, measured smoke layer thickness, eddy current retention time in the inter-beam groove, and roof slope angle and inter-beam spacing are aligned according to the same segment. The data from each sensor are synchronously matched and fused together using the acquisition timestamp to obtain a preliminary flue gas distribution dataset containing multi-dimensional measurement information of each segment.

3. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The process of grouping each section based on thermal radiation intensity and measured smoke layer thickness, and identifying anomalous areas of accumulated thickness in each section with prominent eddy current retention time in the inter-beam grooves, includes: The thermal radiation intensity and measured thickness of the smoke layer of each section are extracted from the preliminary flue gas distribution dataset. If the thermal radiation intensity exceeds the preset radiation threshold, the corresponding section is classified into the high radiation group. Within the high radiation group, the smoke layer is further divided according to whether the measured thickness exceeds the preset thickness threshold to obtain the thickness anomaly group. For each segment within the thickness anomaly group, the eddy current retention time in the inter-beam groove is extracted. If the retention time exceeds a preset retention threshold, the corresponding segment is marked as an area with accumulated thickness anomalies.

4. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The assessment evaluates the thermal radiation intensity of areas with abnormal accumulation thickness. When the thermal radiation intensity exceeds a preset radiation threshold, the depth of smoke deposition between beams is calculated using the ceiling slope angle and beam spacing. Based on this depth, the measured thickness of the smoke layer in the abnormal accumulation thickness area is re-determined, resulting in smoke layer deposition thickness distribution data, including: For the regions with abnormal accumulation thickness, extract the corresponding thermal radiation intensity values ​​for each region, compare the thermal radiation intensity with a preset radiation threshold one by one, and if the thermal radiation intensity exceeds the preset radiation threshold, mark the corresponding region as a high radiation abnormal region and obtain the location identifier of the high radiation abnormal region. Based on the location markers of the high radiation anomaly areas, the corresponding ceiling slope angle, beam spacing, and beam groove depth are extracted from the preliminary flue gas distribution dataset, where the groove depth is a pre-measured parameter. The distance between beams is considered as the horizontal distance s. Multiplying it by the tangent of the roof slope angle θ, we obtain the vertical infiltration distance d = s × tan(θ) of the flue gas along the slope direction. The vertical infiltration distance represents the vertical rise height of the flue gas. Adding d to the trench depth h, we obtain the depth of flue gas deposition between beams. The depth of hidden flue gas between beams is compensated based on the depth of flue gas deposition between beams. The measured thickness t of the smoke layer in the high radiation anomaly area is corrected based on the depth of smoke deposition between beams to obtain the corrected smoke layer deposition thickness. Based on the spatial arrangement of the high-radiation anomaly areas in the longitudinal direction of the ceiling, the corrected smoke layer deposition thickness of each area is summarized and organized to obtain smoke layer deposition thickness distribution data.

5. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The process of acquiring smoke layer deposition thickness distribution data, classifying the thermal radiation intensity attenuation at the inter-beam groove location based on the smoke layer deposition thickness distribution data, generating an attenuation distribution map, and identifying potential fire point shielding areas in the smoke exhaust path includes: The data on the distribution of smoke layer deposition thickness are obtained, the deposition thickness value d corresponding to the location of each inter-beam groove is extracted, the original thermal radiation intensity and the currently detected thermal radiation intensity of each inter-beam groove location before smoke layer shielding are read, and the original thermal radiation intensity is subtracted from the current thermal radiation intensity to obtain the radiation attenuation of each inter-beam groove location. If the radiation attenuation multiplied by the thickness d exceeds the preset attenuation threshold, it will be marked as a high attenuation zone; if it is below the preset attenuation threshold, it will be marked as a low attenuation zone. A smoke layer thickness distribution map is generated according to the spatial distribution of the high attenuation zone and the low attenuation zone in the longitudinal direction of the ceiling. The direction of the flue gas discharge path is determined based on the slope angle of the ceiling. The flue gas discharge path is traversed along the flue gas discharge path in the smoke layer thickness distribution map. If multiple consecutive inter-beam groove positions belong to the high attenuation zone, they will be identified as potential fire point shielding zones.

6. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The process involves extracting the smoke layer shielding rate of the inter-beam grooves with longer residence times from the smoke layer thickness distribution map based on potential fire point shielding zones. This smoke layer shielding rate is then verified by combining the eddy residence time of the inter-beam grooves with the inter-beam spacing, resulting in a verified thermal radiation intensity distribution sequence, including: Based on the potential fire point shielding area, locate the inter-beam grooves with longer retention time from the smoke layer thickness distribution map, extract the corresponding smoke layer deposition thickness and radiation attenuation, divide the radiation attenuation by the original thermal radiation intensity, and obtain the smoke layer shielding rate of each inter-beam groove location. The eddy current retention time in the inter-beam groove and the inter-beam spacing are obtained. If the eddy current retention time exceeds the preset time threshold and the inter-beam spacing is less than the preset spacing threshold, it is determined that there is an aggravated smoke retention phenomenon. The smoke layer shading rate is multiplied by the preset correction coefficient to obtain the verified smoke layer shading rate. The thermal radiation transmittance is calculated based on the verified smoke layer shading rate. The thermal radiation transmittance is the value 1 minus the verified smoke layer shading rate. The original thermal radiation intensity is multiplied by the thermal radiation transmittance to obtain the compensated thermal radiation intensity. The compensated thermal radiation intensity is arranged in the longitudinal direction of the ceiling at the positions of the grooves between the beams to obtain the verified thermal radiation intensity distribution sequence.

7. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The step of iteratively updating the attenuation characteristics of heat radiation along the slope under the influence of the roof slope angle based on the verified heat radiation intensity distribution sequence, and determining the coordinates of the actual fire point location under the smoke layer cover, includes: The verified heat radiation intensity distribution sequence is obtained, and the compensated heat radiation intensity values ​​of the groove positions between beams are extracted along the longitudinal direction of the ceiling. The lowest point of the ceiling slope is used as the reference benchmark. The slope height difference of each position relative to the reference benchmark is calculated according to the ceiling slope angle. The correspondence between the compensated heat radiation intensity and the slope height difference is established, and the heat radiation distribution curve along the slope is obtained. Search for the maximum value of thermal radiation intensity on the thermal radiation distribution curve along the slope, and mark the slope height difference position corresponding to the maximum value point as the peak value position of thermal radiation. If there are multiple maximum value points, select the maximum value point with the largest thermal radiation intensity value as the main peak value position. For the heat radiation distribution curve along the slope, the least squares method is used to fit the attenuation trend of heat radiation intensity in the curve with the change of slope height difference to obtain the slope attenuation characteristic curve. The measured compensated heat radiation intensity is compared with the predicted value of the slope attenuation characteristic curve. If the deviation exceeds the preset deviation threshold, the fitting parameters are adjusted and refitted. The slope attenuation characteristic curve is iteratively updated until the deviation converges. Based on the slope height difference corresponding to the main peak position, the slope height difference is divided by the sine of the roof slope angle to obtain the distance along the slope direction. The distance along the slope direction is multiplied by the cosine of the roof slope angle to obtain the horizontal projection distance. Combined with the spatial coordinates of the reference point, the coordinates of the actual fire point position under the smoke layer are determined.

8. The automatic fire point identification method for intelligent charging stations according to claim 1, characterized in that, The consistency analysis of the actual fire point location coordinates and the preliminary smoke distribution dataset, when the consistency of the coordinate positioning is lower than a preset consistency threshold, involves recalculating the accumulation thickness distribution by integrating the eddy current residence time in the inter-beam grooves and the inter-beam spacing to determine the fire point location, including: Obtain the actual fire point location coordinates and the preliminary smoke distribution dataset. Extract the thermal radiation intensity of the segment corresponding to the fire point location coordinates from the preliminary smoke distribution dataset. Subtract the thermal radiation intensity at the fire point location coordinates from the original thermal radiation intensity of the segment to obtain the deviation value. Divide the deviation value by the original thermal radiation intensity to obtain the deviation ratio. Subtract the deviation ratio from the value 1 to obtain the coordinate positioning accuracy. If the degree of agreement is lower than the preset degree of agreement threshold, the eddy co-current residence time and the beam spacing are re-extracted from the preliminary flue gas distribution dataset. The eddy co-current residence time is multiplied by the beam spacing to obtain the flue gas retention volume index of each section. According to the proportion of the flue gas retention volume index in the total of each section, the smoke layer deposition thickness is redistributed proportionally to obtain the corrected accumulation thickness distribution. Based on the corrected accumulation thickness distribution, locate the section with the largest accumulation thickness value, use the center position of this section as the horizontal coordinate of the fire point, and use the ceiling height corresponding to this section as the vertical coordinate of the fire point to determine the fire point location.

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