Fire-fighting equipment power supply monitoring and alarming system

Abstract

The invention discloses a fire-fighting equipment power supply monitoring and alarm system, and relates to the technical field of electrical safety and intelligent monitoring, and the system comprises a multi-source data synchronous collection module which is used for synchronously collecting electrical parameter data and environment data; the environment factor modeling and compensation processing module is used for constructing a compensation coefficient reflecting the working environment state of the power supply circuit according to the acquired environment information; the abnormal feature extraction and enhancement processing module is used for extracting indexes based on the electrical parameter change trend and frequency domain features; and the risk assessment and grading module is used for fusing the composite index, the voltage fluctuation damage index and the environment state compensation parameter. According to the method, electrical harmonic waves, voltage sag and environmental high-risk factors are fused, comprehensive modeling of fire-fighting power supply risks is achieved, monitoring accuracy and perspectiveness are improved, a harmonic health degree calculation method based on probability entropy is introduced, and the limitation that only the total harmonic distortion rate is seen traditionally is overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical safety and intelligent monitoring technology, and in particular to a fire-fighting equipment power supply monitoring and alarm system. Background Art

[0002] In recent years, the stable operation of firefighting equipment in critical locations (such as hospitals, shopping malls, and underground spaces) has relied on highly reliable power supply systems. Because firefighting power supplies are typically independent of conventional power lines and feature redundant configurations, traditional monitoring systems focus primarily on basic status parameters such as current and voltage interruptions and successful power switching. These systems lack in-depth analysis and early warning mechanisms for electrical health trends and environmental coupling risks.

[0003] However, with the increasing complexity of building structures, the increasing proportion of wooden structures, and the impact of high temperature and high humidity environments brought about by global warming, the operational safety of fire power supplies faces the following new risks:

[0004] Non-linear loads lead to increased harmonic interference: The widespread use of equipment such as UPS and inverters causes the superposition of 3rd- to 13th-order harmonic currents, affecting power supply stability. Long-term operation may cause increased power loss and insulation aging.

[0005] Abnormal moisture content of wooden structures causes electrical hazards: When fire-fighting cables pass through wooden walls or beams, if they encounter high humidity and high temperature environments, the increased moisture content of the wood will form a "conductive channel" or increase the risk of fire spread.

[0006] Therefore, there is an urgent need for a fire-fighting equipment power supply monitoring and alarm system to solve the above problems. Summary of the Invention

[0007] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0008] In view of the above problems in the prior art, the present invention is proposed.

[0009] To solve the above technical problems, the present invention provides the following technical solution: a fire-fighting equipment power supply monitoring and alarm system, characterized in that it includes:

[0010] Multi-source data synchronous acquisition module: used to synchronously acquire electrical parameter data and environmental data, and bind all data to the same timestamp t i ;

[0011] The environmental factor modeling and compensation processing module constructs compensation coefficients reflecting the working environment status of the power line based on the acquired environmental information to attribute and correct changes in electrical parameters;

[0012] The abnormal feature extraction and enhancement processing module extracts indicators based on the electrical parameter change trend and frequency domain characteristics, and combines them with the environmental compensation coefficient to output a composite indicator that characterizes the stability of power supply operation;

[0013] A risk assessment and grading module integrates the composite index with the voltage fluctuation damage index and the environmental state compensation parameter to form a power supply risk grade assessment value;

[0014] The feedback control and alarm response module dynamically adjusts the monitoring strategy according to the risk level classification results, and triggers alarms and linkage control actions according to different levels.

[0015] As a preferred solution of the fire-fighting equipment power supply monitoring and alarm system of the present invention, the environmental data includes: obtaining the moisture content of the wood structure through which the power line passes through by a microwave sensor, and obtaining the annual high temperature days at the installation location by calling a meteorological database;

[0016] The electrical parameter data includes: the amplitude of each order harmonic current, the rated voltage and the instantaneous voltage of the power supply system collected from the current sensor.

[0017] As a preferred solution of the fire-fighting equipment power supply monitoring and alarm system of the present invention, the method for constructing the compensation coefficient of the environmental state is:

[0018] S101: First, determine the relative moisture content influencing factor based on the multiple of the actual wood structure moisture content relative to the benchmark moisture content;

[0019] S102: Calculate the climate temperature impact factor by establishing an exponential function based on the annual high temperature days and the safe climate reference value;

[0020] S103: The environmental compensation coefficient β is obtained by combining the product of the relative moisture content influencing factor and the climate temperature influencing factor.

[0021] As a preferred solution of the fire-fighting equipment power supply monitoring and alarm system described in the present invention, the process of extracting indicators based on the electrical parameter change trend and frequency domain characteristics is as follows:

[0022] S201: Extract the amplitude of each harmonic I k , k is the harmonic order, the value range is 3≤k≤13, and the harmonic energy is obtained by squaring the current amplitude;

[0023] S202: Accumulate the energy of all harmonics to obtain total harmonic energy, and divide the energy of each order harmonic by the total energy to obtain energy probability distribution;

[0024] S203: Calculate the information entropy contribution of each probability item. The calculation formula is: p k log2p k ; Then accumulate the entropy contributions of all orders, the expression is:

[0025] S204: Add a negative sign to convert the output to a positive value, and the final system entropy value E that quantifies the degree of harmonic disorder of the system h The calculation formula is:

[0026] As a preferred solution of the fire equipment power supply monitoring and alarm system of the present invention, the frequency domain information entropy E h Combined with the environmental compensation coefficient β, the output weighted correction result E' h , which is a quantitative composite index that comprehensively characterizes the stability of the system. Its calculation formula is:

[0027] E' h =E h (1+ηβ), where η represents the weight factor of the environmental compensation coefficient.

[0028] As a preferred solution of the fire-fighting equipment power supply monitoring and alarm system of the present invention, the method for determining the voltage fluctuation damage index is:

[0029] S301: Mapping different levels of voltage sag events to a dimensionless standard scale by calculating the ratio of the voltage sag depth (the difference between the voltage and the rated voltage when the sag occurs) to the rated voltage of the power system to facilitate unified comparison;

[0030] S302: amplifying the above ratio by square, so as to emphasize the influence weight of the severe sag event on the system, so that the contribution of the larger sag to the result is more significant;

[0031] S303: Calculate the average value D of the calculation results of all sag events v , to form a holistic description and avoid misleading interference from occasional values.

[0032] As a preferred solution of the fire-fighting equipment power supply monitoring and alarm system described in the present invention, the calculation formula of the power supply risk level assessment value is:

[0033] R=αE′ h +γD v +μβ;

[0034] Among them, αE' h Indicates the activity level of frequency domain fluctuations and is sensitive to abnormal load behavior. vIt represents the reliability impact reflecting the time-domain fluctuation, associated with the power supply stability. μβ represents the influence degree of long-term factors such as high temperature. Specifically, α, γ, and μ are the weight coefficients corresponding to the three indicators, satisfying the normalization condition: α + γ + μ = 1.

[0035] As a preferred solution of the fire equipment power supply monitoring and alarm system described in the present invention, wherein: if the environmental compensation coefficient β is greater than the set compensation standard value β t , the harmonic order is extended to k = 3 - 21, and the updated compensation entropy value is calculated

[0036] According to the distribution of the extended high-order harmonics, the environmental compensation coefficient is re-corrected as:

[0037]

[0038] If β' > the environmental disaster-causing critical value β c , the high-sensitivity insulation detection mode is activated.

[0039] As a preferred solution of the fire equipment power supply monitoring and alarm system described in the present invention, wherein: if R ≤ the first threshold θ1, it indicates that the fire equipment is green-safe and low-risk. At this time, the system maintains the current sampling frequency;

[0040] If R > the second threshold θ2 and satisfies the additional condition: β' > the environmental disaster-causing critical value β c , a red alarm for the fire equipment is triggered, and the risk level is high-risk. At this time, the high-sensitivity insulation detection mode is activated:

[0041] That is, the on-line insulation resistance detection module is activated to detect whether there is a leakage risk; the fire power supply cabinet is controlled to switch to the DC standby power supply, and the output power is limited to less than 70% of the rated value; the harmonic spectrum diagram + environmental parameter snapshot (temperature, humidity + moisture content) within the last 10 seconds is forcibly uploaded to the cloud platform;

[0042] If θ1 < R ≤ θ2 and satisfies the additional condition: D v > the voltage tolerance upper limit D max , a yellow warning alarm for the fire is triggered. At this time, the actions to be performed are: increasing the harmonic current sampling rate; expanding the voltage sag analysis window to capture slow-response fluctuations; controlling the surface humidity regulator of the wooden structure to start the local dehumidification mode to reduce the risk of potential carbonized conductive paths.

[0043] As a preferred solution of the fire equipment power supply monitoring and alarm system described in the present invention, wherein: if only R > the second threshold θ2 and does not satisfy the additional condition: β' > the environmental disaster-causing critical value β c ; then the system is reduced to the fire warning alarm level;

[0044] Or only θ1 < R ≤ θ2, not satisfying the additional condition: D v > upper voltage tolerance limit D max , then the system is reduced to the green safety level.

[0045] Advantages of the present invention:

[0046] 1. The present invention integrates electrical harmonics, voltage sags, and environmental high-risk factors (moisture content, high-temperature days), achieving a comprehensive modeling of the fire protection power supply risk, thereby improving the accuracy and forward-looking of monitoring. And it introduces a harmonic health calculation method based on probability entropy, overcoming the limitations of only looking at the total harmonic distortion rate (THD) in the traditional method, and enhancing the sensitivity of abnormal recognition.

[0047] 2. The present invention designs a dynamically extended harmonic order feedback mechanism. When a high-temperature and high-humidity environment is sensed, the analysis can be extended to the 21st harmonic to enhance the ability to capture potential insulation degradation risks; it introduces a voltage sag damage coefficient and an environmental compensation factor to participate in the calculation of the comprehensive risk value, realizing a coupled judgment mechanism for multi-dimensional data; it constructs a hierarchical, feedbackable, and linkable alarm control strategy, which can not only report the risk status but also link devices for adaptive adjustment to ensure the highly reliable operation of the fire protection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them:

[0049] Figure 1 It is a schematic diagram of the calculation process of the risk level assessment value in a fire protection equipment power supply monitoring and alarm system proposed by the present invention;

[0050] Figure 2 It is an execution diagram of the alarm strategy for different risk levels in a fire protection equipment power supply monitoring and alarm system proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific embodiments of the present invention with reference to the drawings in the specification.

[0052] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0053] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0054] Reference Figure 1-2 , as an embodiment of the present invention, provides a fire equipment power supply monitoring and alarm system, which includes: a multi-source data synchronization acquisition module, an environmental factor modeling and compensation processing module, an abnormal feature extraction and enhancement processing module, a risk assessment and grading module, and a feedback control and alarm response module.

[0055] Specifically, the multi-source data synchronous acquisition module is used to synchronously acquire electrical parameter data and environmental data, and bind all data to the same timestamp t i ; To ensure that the collected data has a unified time stamp to achieve high-precision timing alignment. Environmental data include: obtaining the moisture content of the wooden structure through which the power line passes through through a microwave sensor, and calling the meteorological database to obtain the number of high-temperature days per year at the installation site; the higher the moisture content, the stronger the conductivity of the wood, which is likely to aggravate current leakage and harmonic anomalies. Similarly, the more high-temperature days per year, the faster the wood ages and the insulation deteriorates, which can easily induce power failures. Therefore, in order to objectively reflect the operating risk status of the fire power supply line under different environmental conditions, it is necessary to comprehensively consider the above factors. The present invention designs a compensation factor that can dynamically adjust the risk assessment index. Electrical parameter data include: the amplitude of each order harmonic current collected from the current sensor, the rated voltage of the power supply system, and the instantaneous voltage

[0056] The environmental factor modeling and compensation processing module is used to construct a compensation coefficient reflecting the working environment status of the power supply line based on the acquired environmental information, so as to attribute and correct the changes in electrical parameters.

[0057] The compensation coefficient of the environmental state is constructed as follows:

[0058] S101: First, determine the relative moisture content influencing factor based on the multiple of the actual wood structure moisture content relative to the benchmark moisture content; the calculation formula can be expressed as: M W / M r Among them, M W Indicates the current structural moisture content, M r Indicates the benchmark moisture content. If the current structure moisture content is higher than the benchmark moisture content, which is a safety reference value (such as 12% for hardwood and 15% for softwood), this item is greater than 1, indicating that there is a potential conductivity risk; conversely, if it is lower than the reference value, it is less than 1, indicating that the humidity environment is relatively safe.

[0059] S102: Calculate the climate temperature impact factor by establishing an exponential function based on the annual high temperature days and the safe climate reference value; the calculation formula can be: Among them, T h Indicates the number of high temperature days per year at the installation location, T r It represents the set safety climate reference value, and λ represents the response coefficient of temperature change to risk. The larger the value, the more significant the temperature impact. h >T r When the index is greater than 1, it means that high temperature exacerbates structural degradation and harmonic anomalies;

[0060] S103: The environmental compensation coefficient β is obtained by multiplying the relative moisture content factor and the climate temperature factor. The combined product model ensures the synergistic amplification effect of the two environmental variables on risk.

[0061] When M W and T h At the same time, when it is high, β increases rapidly, which is used to trigger subsequent feedback and early warning mechanisms;

[0062] This method is superior to the simple weighting method and can more sensitively reflect electrical anomalies caused by harsh environments.

[0063] The abnormal feature extraction and enhancement processing module extracts indicators based on the electrical parameter change trend and frequency domain characteristics, and combines the environmental compensation coefficient to output a composite indicator that characterizes the stability of power supply operation.

[0064] Specifically, the process of extracting indicators based on the electrical parameter change trend and frequency domain characteristics is as follows:

[0065] S201: Extract the amplitude of each harmonic I k , k is the harmonic order, the value range is 3≤k≤13, and the harmonic energy is obtained by squaring the current amplitude;

[0066] S202: Accumulate the energy of all harmonics to obtain total harmonic energy, and divide the energy of each order harmonic by the total energy to obtain energy probability distribution;

[0067] The calculation formula can be: Among them, p k It represents the proportion of the k-th order harmonic energy in all harmonics, that is, the energy probability value of the k-th order harmonic, I k It indicates that the amplitude of each order harmonic current is collected from the current sensor. This formula is used to calculate the proportion of each order harmonic in the overall harmonic energy. In essence, it constructs a normalized probability distribution sequence, laying the foundation for subsequent information entropy calculation.

[0068] S203: Calculate the information entropy contribution of each probability item. The calculation formula is: p k log2pk (When a certain order harmonic is extremely weak, p k When it is very small, its log2p k is a large negative number, indicating that it introduces more disturbance information); then the entropy contribution of all orders is accumulated, and the expression is:

[0069] S204: Add a negative sign to convert the output to a positive value, and the final system entropy value E that quantifies the degree of harmonic disorder of the system h The calculation formula is:

[0070] To be more precise, the above calculation process extracts the frequency domain probability distribution characteristics (p k ) and frequency domain chaos information entropy (E h ) is a description of power quality from the frequency domain perspective. h As the entropy value of energy distribution, it is a measure of frequency domain complexity. When several harmonics occupy the main energy (i.e., energy concentration), E h A smaller value indicates that the system is relatively “single and orderly” and has low risk. When the energy is distributed over multiple harmonics (i.e., energy is discrete), E h Larger values ​​indicate increased system complexity and potentially higher risks.

[0071] In addition, considering the working state of the power supply line in the wooden structure building, it is easily affected by the moisture content of the wood and the number of high temperature days in the installation location, which indirectly affects the harmonic characteristics. h Combined with the environmental compensation coefficient β, the output weighted correction result E' h , which is a quantitative composite index that comprehensively characterizes the stability of the system. Its calculation formula is:

[0072] E' h =E h (1+ηβ), where η represents the weight factor of the environmental compensation coefficient.

[0073] If the environmental compensation coefficient β is greater than the set compensation standard value β t , then expand the harmonic order to k = 3-21, and calculate the updated compensation entropy value

[0074] According to the expanded high-order harmonic distribution, the environmental compensation coefficient is revised as follows:

[0075]

[0076] If β'> environmental disaster critical value β c , then start the high-sensitivity insulation detection mode (see the introduction of the feedback control and alarm response module for details).

[0077] This is because for typical harmonic sources in fire protection power supply systems (such as UPS, uninterruptible power supply, inverter, etc.):

[0078] 3rd, 5th, and 7th order: low-order harmonics, often caused by nonlinear loads or transformer saturation;

[0079] 9th, 11th, and 13th order harmonics: These are mid-order harmonics related to the PWM control of power supply equipment and are prone to causing resonance or coupling interference.

[0080] The 3–13 order range covers more than 95% of the harmonic energy distribution in common power supply systems, is easy to process by embedded monitoring equipment, has low computational cost and high real-time performance.

[0081] When environmental factor β>β t , indicating that the system may be in a high-humidity and high-heat environment. This type of environment may induce insulation aging and discharge, which is manifested in the spectrum as an abnormal increase in high-order harmonic energy. Harmonics 14–21 are high-order harmonics and are often caused by:

[0082] High-frequency power supply pulse modulation distortion;

[0083] Flyback interference in the control circuit;

[0084] Discharge signals before insulation breakdown; monitoring these high-order signals helps to identify system hidden dangers in advance and improve the sensitivity of entropy anomaly detection.

[0085] The risk assessment and grading module integrates composite indicators with voltage fluctuation damage indicators and environmental status compensation parameters to form a power supply risk level assessment value.

[0086] It should be noted that voltage sag is a key indicator of power quality degradation, especially in fire protection power supply systems. Frequent voltage sag events can cause critical equipment (such as fire pumps and emergency lighting) to malfunction or fail to start. Therefore, this step calculates the voltage fluctuation damage index by statistically analyzing all voltage sag events within a monitoring period to assess the degree of damage to the power supply system.

[0087] The method for determining the voltage fluctuation damage index is:

[0088] S301: Mapping different levels of voltage sag events to a dimensionless standard scale by calculating the ratio of the voltage sag depth (the difference between the voltage and the rated voltage when the sag occurs) to the rated voltage of the power system to facilitate unified comparison;

[0089] S302: amplifying the above ratio by square, so as to emphasize the influence weight of the severe sag event on the system, so that the contribution of the larger sag to the result is more significant;

[0090] S303: Calculate the average value D of the calculation results of all sag events v , to form a holistic description and avoid misleading interference from occasional values.

[0091] Specifically, the overall calculation formula of the above S301-S303 process can be expressed as:

[0092]

[0093] Among them, V d It represents the depth of the i-th voltage sag, which is defined as the difference between the voltage and the rated voltage when the sag occurs;

[0094] V n Indicates the rated voltage of the power supply system;

[0095] N represents the total number of voltage sags that occurred during the monitoring period;

[0096] D v It represents the normalized voltage sag damage coefficient, indicating the overall sag impact.

[0097] The calculation formula for the power supply risk level assessment value is:

[0098] R=αE′ h +γD v +μβ;

[0099] Among them, αE' h Indicates the activity level of frequency domain fluctuations and is sensitive to abnormal load behavior. v It reflects the reliability impact of time domain fluctuations and is related to power supply stability. μβ indicates the influence of long-term factors such as high temperature. Specifically, α, γ, and μ are the weight coefficients corresponding to the three indicators, satisfying the normalization condition: α+γ+μ=1.

[0100] The feedback control and alarm response module dynamically adjusts the monitoring strategy according to the risk level classification results, and triggers alarms and linkage control actions according to different levels.

[0101] If R≤the first threshold θ1, it indicates that the firefighting equipment is green, safe and low-risk, and the system maintains the current sampling frequency;

[0102] If R> the second threshold θ2, and the additional condition is met: β'> the environmental disaster critical value β c , triggering the red alarm of the fire equipment, the risk level is high, and the high-sensitivity insulation detection mode is activated at this time:

[0103] That is, start the on-line insulation resistance detection module to detect whether there is a risk of electric leakage; control the fire power supply cabinet to switch to the DC standby power supply and limit the output power to less than 70% of the rated value; force the upload of the harmonic spectrum map + environmental parameter snapshot (temperature and humidity + moisture content) within the last 10 seconds to the cloud platform;

[0104] If θ1 < R ≤ θ2 and the additional condition: D v > upper limit of voltage tolerance D max , trigger the fire yellow warning alarm. At this time, the actions to be performed are: increase the harmonic current sampling rate; expand the voltage sag analysis window to capture slow-response fluctuations; control the surface humidity regulator of the wooden structure to start the local dehumidification mode to reduce the risk of potential carbonized conductive paths.

[0105] If only R > the second threshold θ2 and the additional condition: β ' > environmental disaster-causing critical value β c ; then the system is reduced to the fire warning alarm level;

[0106] Or only θ1 < R ≤ θ2 and the additional condition: D v > upper limit of voltage tolerance D max , then the system is reduced to the green safety level.

[0107] In summary, the present invention integrates electrical harmonics, voltage sags and environmental high-risk factors (moisture content, high-temperature days), realizes a comprehensive modeling of the fire power supply risk, thereby improving the accuracy and forward-looking of monitoring, and introduces a harmonic health calculation method based on probability entropy to overcome the limitation of only looking at the total harmonic distortion rate (THD) in the traditional method, enhancing the sensitivity of abnormal recognition, and designs a dynamically extended harmonic order feedback mechanism. When a high-temperature and high-humidity environment is sensed, the analysis can be extended to the 21st harmonic to enhance the ability to capture the risk of potential insulation deterioration; introduces the voltage sag damage coefficient and environmental compensation factor to participate in the calculation of the comprehensive risk value, realizing a coupling judgment mechanism for multi-dimensional data; constructs a hierarchical, feedbackable and linkageable alarm control strategy, which can not only report the risk status, but also联动设备自适应调节,保障消防系统高可靠运行.

[0108] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limitations. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A fire equipment power supply monitoring and alarm system, characterized in that: include: Multi-source data synchronous acquisition module: used to synchronously acquire electrical parameter data and environmental data, and bind all data to the same timestamp t i ; The environmental factor modeling and compensation processing module constructs compensation coefficients reflecting the working environment status of the power line based on the acquired environmental information to attribute and correct changes in electrical parameters; The abnormal feature extraction and enhancement processing module extracts indicators based on the electrical parameter change trend and frequency domain characteristics, and combines them with the environmental compensation coefficient to output a composite indicator that characterizes the stability of power supply operation; A risk assessment and grading module integrates the composite index with the voltage fluctuation damage index and the environmental state compensation parameter to form a power supply risk grade assessment value; The feedback control and alarm response module dynamically adjusts the monitoring strategy according to the risk level classification results, and triggers alarms and linkage control actions according to different levels.

2. A fire-fighting equipment power supply monitoring and alarm system according to claim 1, characterized in that: The environmental data includes: obtaining the moisture content of the wooden structure through which the power line passes through by using a microwave sensor, and obtaining the annual high temperature days at the installation location by calling a meteorological database; The electrical parameter data includes: the amplitude of each order harmonic current, the rated voltage and the instantaneous voltage of the power supply system collected from the current sensor.

3. A fire-fighting equipment power supply monitoring and alarm system according to claim 2, characterized in that: The method for constructing the compensation coefficient of the environmental state is: S101: First, determine the relative moisture content influencing factor based on the multiple of the actual wood structure moisture content relative to the benchmark moisture content; S102: Calculate the climate temperature impact factor by establishing an exponential function based on the annual high temperature days and the safe climate reference value; S103: The environmental compensation coefficient β is obtained by combining the product of the relative moisture content influencing factor and the climate temperature influencing factor.

4. A fire-fighting equipment power supply monitoring and alarm system according to claim 3, characterized in that: The process of extracting indicators based on the electrical parameter change trend and frequency domain characteristics is as follows: S201: Extract the amplitude of each harmonic I k , k is the harmonic order, the value range is 3≤k≤13, and the harmonic energy is obtained by squaring the current amplitude; S202: Accumulate the energy of all harmonics to obtain total harmonic energy, and divide the energy of each order harmonic by the total energy to obtain energy probability distribution; S203: Calculate the information entropy contribution of each probability item. The calculation formula is: p k log2p k ; Then accumulate the entropy contributions of all orders, the expression is: S204: Add a negative sign to convert the output to a positive value, and the final system entropy value E that quantifies the degree of harmonic disorder of the system h The calculation formula is:

5. A fire-fighting equipment power supply monitoring and alarm system according to claim 4, characterized in that: The frequency domain information entropy E h Combined with the environmental compensation coefficient β, the output weighted correction result E' h , which is a quantitative composite index that comprehensively characterizes the stability of the system. Its calculation formula is: E' h =E h (1+ηβ), where η represents the weight factor of the environmental compensation coefficient.

6. A fire-fighting equipment power supply monitoring and alarm system according to claim 5, characterized in that: The method for determining the voltage fluctuation damage index is as follows: S301: Mapping different levels of voltage sag events to a dimensionless standard scale by calculating the ratio of the voltage sag depth (the difference between the voltage and the rated voltage when the sag occurs) to the rated voltage of the power system; S302: amplifying the above ratio by square, so as to emphasize the influence weight of the severe sag event on the system, so that the contribution of the larger sag to the result is more significant; S303: Calculate the average value D of the calculation results of all sag events v , to form a holistic description and avoid misleading interference from occasional values.

7. A fire-fighting equipment power supply monitoring and alarm system according to claim 6, characterized in that: The calculation formula for the power supply risk level assessment value is: R=αE' h +γD v +mv; Among them, αE' h Indicates the activity level of frequency domain fluctuations and is sensitive to abnormal load behavior. v It reflects the reliability impact of time domain fluctuations and is related to power supply stability. μβ indicates the influence of long-term factors such as high temperature. Specifically, α, γ, and μ are the weight coefficients corresponding to the three indicators, satisfying the normalization condition: α+γ+μ=1.

8. A fire-fighting equipment power supply monitoring and alarm system according to claim 7, characterized in that: If the environmental compensation coefficient β is greater than the set compensation standard value β t , then expand the harmonic order to k = 3-21, and calculate the updated compensation entropy value According to the expanded high-order harmonic distribution, the environmental compensation coefficient is revised as follows: If β'> environmental disaster critical value β c , the high-sensitivity insulation detection mode is started.

9. A fire-fighting equipment power supply monitoring and alarm system according to claim 8, characterized in that: If R≤the first threshold θ1, it indicates that the firefighting equipment is green, safe and low-risk, and the system maintains the current sampling frequency; If R> the second threshold θ2, and the additional condition is met: β'> the environmental disaster critical value β c , triggering the red alarm of the fire equipment, the risk level is high, and the high-sensitivity insulation detection mode is activated at this time: That is, the online insulation resistance detection module is activated to detect whether there is a leakage risk; the fire power supply cabinet is controlled to switch to the DC backup power supply and the output power is limited to less than 70% of the rated value; the harmonic spectrum and environmental parameter snapshots within the last 10 seconds are forcibly uploaded to the cloud platform; If θ1 < R ≤ θ2 and the additional condition is satisfied: D v > upper voltage tolerance limit D max , trigger the fire yellow warning alarm. At this time, the actions to be taken are: increase the harmonic current sampling rate; expand the voltage sag analysis window to capture slow-response fluctuations; control the surface humidity regulator of the wooden structure to start the local dehumidification mode to reduce the risk of potential carbonized conductive paths.

10. A fire-fighting equipment power supply monitoring and alarm system according to claim 9, characterized in that: If only R> the second threshold θ2, the additional condition is not met: β'> the environmental disaster critical value β c ; then the system is reduced to the fire warning alarm level; Or only θ1 < R ≤ θ2, without satisfying the additional condition: D v > upper voltage tolerance limit D max , then the system is reduced to the green safety level.

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