A fire hydrant intelligent operation and maintenance management method and system

Abstract

The application discloses a fire hydrant intelligent operation and maintenance management method and system, and belongs to the technical field of operation and maintenance management. The method comprises the following steps: constructing a flow field model, a pressure field model, an inclination field model and a position field model, and outputting four types of characteristic coefficients; generating a pressure-flow adaptation degree based on the inclination field coefficient, the position field coefficient, the pressure field coefficient and the flow field coefficient; and constructing a confidence model by fusing the adaptation degree and the service life, and dividing the state level according to a threshold value. The system realizes data collection, model calculation and state early warning based on the above method. The application breaks through the limitation of single parameter monitoring, dynamically perceives the equipment health degree through a multi-field coupling model, realizes accurate operation and maintenance decision by combining environmental risk and life attenuation, and improves the reliability and practicability of the fire hydrant.

Description

Technical Field

[0001] This invention belongs to the field of operation and maintenance management technology, and in particular relates to an intelligent operation and maintenance management method and system for fire hydrants. Background Technology

[0002] Fire hydrants are core facilities in urban fire protection systems, and their reliability directly impacts fire rescue efficiency. Traditional maintenance relies on manual inspections and reactive repair requests, which suffers from problems such as delayed response, high missed inspection rates, and incomplete condition assessments. Especially in complex urban environments, there is an urgent need for intelligent methods to achieve real-time monitoring and risk warning of fire hydrant health status. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides an intelligent operation and maintenance management method and system for fire hydrants, which solves the aforementioned problems.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent operation and maintenance management method for fire hydrants, comprising the following steps:

[0005] A flow field model is constructed based on the real-time flow value and flow fluctuation value (flow standard deviation within the collection period) of the fire hydrant, and the flow field coefficient is output.

[0006] Based on the real-time pressure value, pressure fluctuation value (pressure standard deviation within the acquisition period), and pressure recovery rate of the fire hydrant, a pressure change field model is constructed to output the pressure field coefficients.

[0007] An inclined field model is constructed based on the tilt angle, tilt change rate, and vibration amplitude of the fire hydrant, and the inclined field coefficients are output.

[0008] Based on the population density in the fire hydrant coverage area, the frequency of historical fires, and the quantity of other water sources (such as rivers and other water sources that can be used for fire rescue), a location field model is constructed and the location field coefficients are output.

[0009] A pressure-flow adaptation model is constructed based on the tilt field coefficient, position field coefficient, pressure field coefficient, and flow field coefficient, and the pressure-flow adaptation degree is output.

[0010] A fire hydrant confidence model is constructed based on pressure-flow adaptability and the current service life of the fire hydrant to output the fire hydrant confidence level. The fire hydrant status is then determined based on the fire hydrant confidence level.

[0011] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0012] Further technical solution: Based on pressure-flow adaptability and the current service life of the fire hydrant, a fire hydrant confidence model is constructed to output the fire hydrant confidence score. The steps for determining the fire hydrant status based on the fire hydrant confidence score are as follows:

[0013] Import the current service life of the fire hydrant into the formula. The service life index is obtained from the data. Indicates the current service life of the fire hydrant. Indicates the rated service life of the fire hydrant;

[0014] The current service life index and current pressure-flow compatibility are imported into the fire hydrant confidence model to obtain the current fire hydrant confidence level. The fire hydrant confidence model is expressed as follows:

[0015] ;

[0016] in, This indicates the current confidence level of the fire hydrant. This indicates the current pressure-flow adaptability. Indicates the lifetime degradation coefficient. Indicates the current service life index, the The higher the value, the better the condition of the fire hydrant;

[0017] Compare the current confidence level of the fire hydrant with the corresponding threshold:

[0018] like If so, the current fire hydrant is in a reliable state;

[0019] like If so, the current fire hydrant needs to be monitored;

[0020] like If so, the current fire hydrant needs maintenance or replacement.

[0021] A further technical solution: The pressure-flow adaptability is expressed as:

[0022] ;

[0023] in, Indicates pressure-flow adaptability. Indicates the field coefficient at the current position. Indicates the current tilt field coefficient. Indicates the current pressure field coefficient. Indicates the optimal pressure field coefficient. This indicates the maximum permissible deviation of the pressure field coefficient from the optimal value. This represents the current flow field coefficient. Indicates the optimal flow field coefficient. This indicates the maximum permissible deviation of the flow field coefficient from the optimal value. Furthermore, the larger the value, the better the fit between pressure and flow rate under the current location field coefficient and the current tilt field coefficient.

[0024] Further technical solution: The steps for constructing a location field model and outputting location field coefficients based on the population density of the fire hydrant coverage area, the frequency of historical fires, and the quantity of other water sources (such as rivers and other water sources that can be used for fire rescue) are as follows:

[0025] The quantity of other water sources (such as rivers and other water sources that can be used for fire rescue) is processed by maximum-min normalization to obtain the water source quantity index;

[0026] Importing personnel density into the formula The population density index was obtained from the data. Indicates population density. Indicates the maximum permissible personnel density;

[0027] Importing historical fire frequency into the formula The fire frequency index was obtained from the data. Indicates the frequency of historical fires;

[0028] The current water quantity index, current population density index, and current fire frequency index are imported into the location field model to output the current location field coefficients. The location field model is represented as follows:

[0029] ;

[0030] in, Indicates the field coefficient at the current position. This indicates the current population density index. This indicates the current water quantity index. The fire frequency index is represented by the following. Furthermore, the larger the value, the greater the risk in the location field.

[0031] Further technical solution: The steps for constructing an inclined field model and outputting the inclined field coefficients based on the fire hydrant's tilt angle, tilt change rate, and vibration amplitude are as follows:

[0032] The tilt angle, tilt change rate, and vibration amplitude are subjected to maximum-min normalization to obtain the tilt angle index, tilt change rate index, and vibration amplitude index.

[0033] The current tilt angle index, current tilt change rate index, and current vibration amplitude index are imported into the tilt field model to obtain the current tilt field coefficients. The tilt field model is expressed as follows:

[0034] ;

[0035] ;

[0036] in, Indicates the current tilt field coefficient. This represents the tilt analysis coefficient. Indicates the attenuation coefficient. Indicates the current tilt angle index. This represents the rate of change of slope index. This indicates the current vibration amplitude index. Represents the weight coefficient and The Furthermore, the higher the value, the better the physical condition of the fire hydrant.

[0037] Further technical solution: The steps for constructing a pressure change field model and outputting pressure field coefficients based on the real-time pressure value, pressure fluctuation value (pressure standard deviation within the acquisition period), and pressure recovery rate of the fire hydrant are as follows:

[0038] The pressure fluctuation value and pressure recovery rate are obtained by performing maximum-min normalization on the pressure fluctuation value and pressure recovery rate;

[0039] Import real-time pressure into the formula Obtain the real-time stress index, among which, Indicates real-time pressure. This indicates the reference real-time pressure. This indicates that deviations from the reference real-time pressure value are permissible;

[0040] The pressure field coefficients are obtained by importing the current real-time pressure index, the current pressure fluctuation index, and the current pressure recovery rate index into the pressure field model. The pressure field model is expressed as follows:

[0041] ;

[0042] in, Indicates the current pressure field coefficient. This indicates the current real-time stress index. This indicates the current pressure fluctuation index. Indicating the pressure recovery speed index, Represents the weight coefficient and The The higher the value, the better the fire hydrant pressure condition.

[0043] Further technical solution: The steps for constructing a flow field model and outputting flow field coefficients based on the real-time flow value and flow fluctuation value (flow standard deviation within the collection period) of the fire hydrant are as follows:

[0044] Import real-time traffic into the formula Obtain real-time traffic index from [the source], where [the data] is [the data]. Indicates real-time traffic. This indicates a reference to real-time traffic. This indicates that deviations from the reference real-time traffic value are allowed;

[0045] Importing flow fluctuations into the formula The traffic fluctuation index is obtained from the data. Indicates traffic fluctuations. Indicates reference flow fluctuation. This indicates that deviations from the reference flow rate fluctuation value are permissible;

[0046] The current real-time flow index and the current flow fluctuation index are imported into the flow field model to obtain the current flow field coefficients. The flow field model is expressed as follows:

[0047] ;

[0048] in, This represents the current flow field coefficient. This indicates the current real-time traffic index. This indicates the current traffic fluctuation index. Represents the weight coefficient and The Furthermore, the higher the value, the more stable the fire hydrant flow rate.

[0049] A fire hydrant intelligent operation and maintenance management system, employing the aforementioned fire hydrant intelligent operation and maintenance management method, includes:

[0050] The flow field analysis module constructs a flow field model based on the real-time flow value and flow fluctuation value of the fire hydrant and outputs the flow field coefficients.

[0051] The pressure change field analysis module constructs a pressure change field model based on the real-time pressure value, pressure fluctuation value, and pressure recovery rate of the fire hydrant, and outputs the pressure field coefficients.

[0052] The tilt field analysis module constructs a tilt field model based on the tilt angle, tilt change rate, and vibration amplitude of the fire hydrant, and outputs the tilt field coefficients.

[0053] The location field analysis module constructs a location field model based on the personnel density, historical fire frequency, and other water source quantities in the fire hydrant coverage area, and outputs location field coefficients.

[0054] The pressure-flow adaptation analysis module constructs a pressure-flow adaptation model based on the tilt field coefficient, position field coefficient, pressure field coefficient, and flow field coefficient, and outputs the pressure-flow adaptation degree.

[0055] The status analysis module constructs a fire hydrant confidence model based on pressure-flow adaptability and the current service life of the fire hydrant, outputs the fire hydrant confidence score, and judges the status of the fire hydrant based on the fire hydrant confidence score.

[0056] This invention provides an intelligent operation and maintenance management method and system for fire hydrants, which has the following advantages compared with the prior art:

[0057] 1. This invention constructs multi-dimensional data models such as flow field, pressure field, tilt field, and position field, and generates confidence index by combining pressure-flow adaptability and current service life of fire hydrants, thereby realizing dynamic assessment and graded early warning of fire hydrant status. It has the advantages of realizing dynamic assessment of fire hydrant working conditions through multi-dimensional data fusion analysis, improving the accuracy of status judgment and the reliability of operation and maintenance. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0060] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0061] Please see Figure 1 The present invention provides an intelligent operation and maintenance management method for fire hydrants, comprising the following steps:

[0062] A flow field model is constructed based on the real-time flow value and flow fluctuation value (flow standard deviation within the collection period) of the fire hydrant, and the flow field coefficient is output.

[0063] Based on the real-time pressure value, pressure fluctuation value (pressure standard deviation within the acquisition period), and pressure recovery rate of the fire hydrant, a pressure change field model is constructed to output the pressure field coefficients.

[0064] An inclined field model is constructed based on the tilt angle, tilt change rate, and vibration amplitude of the fire hydrant, and the inclined field coefficients are output.

[0065] Based on the population density in the fire hydrant coverage area, the frequency of historical fires, and the quantity of other water sources (such as rivers and other water sources that can be used for fire rescue), a location field model is constructed and the location field coefficients are output.

[0066] A pressure-flow adaptation model is constructed based on the tilt field coefficient, position field coefficient, pressure field coefficient, and flow field coefficient, and the pressure-flow adaptation degree is output.

[0067] A fire hydrant confidence model is constructed based on pressure-flow adaptability and the current service life of the fire hydrant to output the fire hydrant confidence level. The fire hydrant status is then determined based on the fire hydrant confidence level.

[0068] Through the above technical solutions, this application realizes real-time multi-dimensional monitoring of fire hydrant status, improves fault identification accuracy through dynamic correlation analysis of flow field and pressure field, realizes early warning of structural anomalies by using tilt field model, and makes status assessment adaptable to fire protection needs of different areas by combining position field coefficient. Finally, it quantifies the reliability of equipment through confidence model, providing objective basis for operation and maintenance decisions.

[0069] Preferably, the steps for constructing a flow field model and outputting flow field coefficients based on the real-time flow value and flow fluctuation value (flow standard deviation within the collection period) of the fire hydrant are as follows:

[0070] Import real-time traffic into the formula Obtain real-time traffic index from [the source], where [the data] is [the source]. Indicates real-time traffic. This indicates a reference to real-time traffic. This indicates that deviations from the reference real-time traffic value are allowed;

[0071] Importing flow fluctuations into the formula The traffic fluctuation index is obtained from the data. Indicates traffic fluctuations. Indicates reference flow fluctuation. This indicates that deviations from the reference flow rate fluctuation value are permissible;

[0072] The current real-time flow index and the current flow fluctuation index are imported into the flow field model to obtain the current flow field coefficients. The flow field model is expressed as follows:

[0073] ;

[0074] in, This represents the current flow field coefficient. This indicates the current real-time traffic index. This indicates the current traffic fluctuation index. Represents the weight coefficient and The Furthermore, the higher the value, the more stable the fire hydrant flow rate.

[0075] The real-time flow index is used to capture the deviation between real-time flow and ideal operating conditions. The flow fluctuation index reflects the dynamic stability of the system. The weighting coefficient refers to the allocation ratio of the real-time flow index and the flow fluctuation index in the flow field coefficient calculation. It can be determined using preset empirical values ​​or machine learning optimization methods. By adjusting the weight allocation, a multi-dimensional assessment of flow stability can be achieved.

[0076] Specifically, by constructing a flow field model, real-time flow values ​​are imported into an exponential function to calculate a real-time flow index. This index, through its exponential decay characteristic, transforms the deviation between the actual flow and the reference value into a value within the range of 0-1; the greater the deviation, the smaller the index. Flow fluctuation values, calculated using standard deviation, are then imported into another exponential function to generate a flow fluctuation index, which reflects the degree of matching between flow fluctuations and reference fluctuation values. The real-time flow index and the flow fluctuation index are multiplied by preset weighting coefficients and then added together to generate a comprehensive flow field coefficient. This coefficient is normalized and limited to the range of 0-1; a larger value indicates a more stable flow state, providing standardized input parameters for subsequent pressure-flow adaptability calculations.

[0077] Through the above technical solution, this application achieves real-time quantitative assessment of fire hydrant flow status, enabling timely detection of abnormal flow fluctuations and intuitively reflecting flow stability through normalized indicators, providing accurate data support for fire hydrant operation and maintenance decisions. This solution further eliminates subjective errors from manual inspections, improving the timeliness and accuracy of flow monitoring.

[0078] Preferably, the steps for constructing a pressure change field model and outputting pressure field coefficients based on the real-time pressure value, pressure fluctuation value (pressure standard deviation within the acquisition period), and pressure recovery rate of the fire hydrant are as follows:

[0079] The pressure fluctuation value and pressure recovery rate are obtained by performing maximum-min normalization on the pressure fluctuation value and pressure recovery rate;

[0080] Import real-time pressure into the formula Obtain the real-time stress index, among which, Indicates real-time pressure. This indicates the reference real-time pressure. This indicates that deviations from the reference real-time pressure value are permissible;

[0081] The pressure field coefficients are obtained by importing the current real-time pressure index, the current pressure fluctuation index, and the current pressure recovery rate index into the pressure field model. The pressure field model is expressed as follows:

[0082] ;

[0083] in, Indicates the current pressure field coefficient. This indicates the current real-time stress index. This indicates the current pressure fluctuation index. Indicating the pressure recovery speed index, Represents the weight coefficient and The The higher the value, the better the fire hydrant pressure condition.

[0084] The pressure fluctuation value refers to the standard deviation of pressure data within the acquisition period. Specifically, it can be calculated using the sliding window method to determine the standard deviation of pressure over a continuous time period, and is used to characterize the severity of pressure fluctuations. The pressure recovery rate refers to the rate at which pressure recovers to its normal value after an abnormal fluctuation. This can be calculated using the slope of the pressure-time curve, reflecting the self-regulation capability of the fire hydrant system. The real-time pressure index is used to enhance the sensitivity to critical deviations. The pressure field model is a comprehensive evaluation model integrating steady-state pressure, dynamic fluctuations, and recovery capability. Specifically, it uses a weighted summation method to combine the three sub-indicators, and adjusts the weighting coefficients to achieve adaptive assessment under different operating conditions.

[0085] Specifically, the pressure fluctuation index and pressure recovery rate index are normalized to eliminate dimensional differences, forming standardized parameters that can be compared horizontally. The real-time pressure index transforms the degree of pressure deviation into a non-linear decay relationship through an exponential function. When the real-time pressure approaches the reference value, the index approaches 1; when the deviation exceeds the allowable threshold, the index rapidly drops to 0, effectively identifying sudden pressure anomalies. The weighting coefficients in the pressure field model can be set according to the actual application scenario. For example, in areas with frequent pressure fluctuations in water supply networks, the weight of the pressure recovery rate index can be increased, allowing fire hydrants with rapid self-recovery capabilities to maintain a high pressure field coefficient even during brief pressure fluctuations, avoiding misjudgment as system failures.

[0086] Through the above technical solution, this application can dynamically identify pressure anomalies caused by pipeline leaks, valve malfunctions, or sudden changes in water consumption, accurately distinguishing between temporary fluctuations and persistent failures. For example, during peak fire water usage periods, when the pressure drops briefly but recovers at a rate that meets requirements, the system will not trigger a false alarm; however, when the pressure deviates continuously and its recovery capacity is insufficient, a maintenance warning can be issued promptly. This technical solution effectively improves the comprehensiveness and reliability of pressure status assessment, providing accurate data support for fire hydrant operation and maintenance decisions.

[0087] Preferably, the step of constructing an inclined field model and outputting the inclined field coefficients based on the fire hydrant's tilt angle, tilt change rate, and vibration amplitude is as follows:

[0088] The tilt angle, tilt change rate, and vibration amplitude are subjected to maximum-min normalization to obtain the tilt angle index, tilt change rate index, and vibration amplitude index.

[0089] The current tilt angle index, current tilt change rate index, and current vibration amplitude index are imported into the tilt field model to obtain the current tilt field coefficients. The tilt field model is expressed as follows:

[0090] ;

[0091] ;

[0092] in, Indicates the current tilt field coefficient. This represents the tilt analysis coefficient. Indicates the attenuation coefficient. Indicates the current tilt angle index. This represents the rate of change of slope index. This indicates the current vibration amplitude index. Represents the weight coefficient and The Furthermore, the higher the value, the better the physical condition of the fire hydrant.

[0093] The tilt angle refers to the offset of the fire hydrant body relative to the vertical reference plane, which can be measured using a tilt sensor. It reflects the degree of physical deformation caused by foundation settlement or external impact. The tilt change rate refers to the change in tilt angle per unit time, used to characterize the dynamic development trend of fire hydrant deformation. Vibration amplitude refers to the peak acceleration of the fire hydrant when subjected to external mechanical impact, which can be measured using a triaxial accelerometer. It indicates the impact intensity of the fire hydrant subjected to sudden events such as vehicle collisions or construction vibrations. The weighting coefficient refers to the contribution ratio assigned to each parameter, which can be assigned using the analytic hierarchy process (AHP) or expert experience. It is used to adjust the parameter sensitivity according to different fault modes such as abrupt tilt angle changes, continuous tilt deterioration, or high-frequency vibration. The attenuation coefficient refers to the rate attenuation of the tilt field coefficient as the analysis coefficient increases. It can be determined through expert experience calibration or fitting of historical fault data. It is used to nonlinearly map the multi-dimensional parameter fusion results to the state assessment value domain.

[0094] Specifically, the tilt angle index quantifies the degree to which the current deformation deviates from the baseline state through normalization, the tilt change rate index captures the acceleration trend of deformation through time difference calculation, and the vibration amplitude index reflects the instantaneous mechanical impact intensity through extreme value statistics. These three indices are linearly superimposed according to preset weights to generate tilt field analysis coefficients. The weight allocation reflects the priority of different parameters' impact on structural stability; for example, abrupt changes in tilt angle may be given higher weight to prioritize early warning of sudden tilting risks. The analysis coefficients are converted into tilt field coefficients in the range of 0 to 1 using an exponential function. As the analysis coefficients increase, the tilt field coefficients decay exponentially, consistent with the nonlinear response characteristics of fire hydrant physical condition deterioration. This model simultaneously integrates static deformation, dynamic change trends, and instantaneous impact information, overcoming the limitations of single threshold judgment and achieving a technological upgrade from discrete alarms to continuous quantitative assessment.

[0095] Through the above technical solution, this application effectively solves the problem of missed detection caused by single tilt monitoring in traditional operation and maintenance. It can simultaneously detect the deformation trend and mechanical impact damage of fire hydrants, and realize multi-dimensional dynamic assessment of their physical state. By integrating the synergistic analysis of tilt angle, rate of change and vibration parameters, it can promptly identify the risk of water pipe rupture caused by base loosening due to continuous tilting or sudden vibration, providing a quantitative basis for early warning of structural failures of fire hydrants.

[0096] Preferably, the steps for constructing a location field model and outputting location field coefficients based on the population density of the fire hydrant coverage area, the frequency of historical fires, and the quantity of other water sources (such as rivers and other water sources that can be used for fire rescue) are as follows:

[0097] The quantity of other water sources (such as rivers and other water sources that can be used for fire rescue) is processed by maximum-min normalization to obtain the water source quantity index;

[0098] Importing personnel density into the formula The population density index was obtained from the data. Indicates population density. Indicates the maximum permissible personnel density;

[0099] Importing historical fire frequency into the formula The fire frequency index was obtained from the data. Indicates the frequency of historical fires;

[0100] The current water quantity index, current population density index, and current fire frequency index are imported into the location field model to output the current location field coefficients. The location field model is represented as follows:

[0101] ;

[0102] in, Indicates the field coefficient at the current position. This indicates the current population density index. This indicates the current water quantity index. The fire frequency index is represented by the following. Furthermore, the larger the value, the greater the risk in the location field.

[0103] The population density index is a standardized parameter calculated by comparing the actual population density with a preset maximum allowable density. Specifically, it can be achieved by combining real-time population flow data collected by a sensor network with regional area calculations, quantifying the potential impact of population density on fire risk. The water source quantity index, specifically, can be calculated by performing a linear transformation on the number of available water sources such as rivers and lakes from geographic information system data, reflecting the buffering effect of alternative water sources on reliance on fire hydrants. The fire frequency index is a parameter derived from the number of historical fires through an exponential function. Specifically, it can be achieved by querying fire records for the corresponding area over the past five years from the fire department's historical accident database, characterizing the probability of fire occurrence in the area.

[0104] Specifically, this solution addresses the problem of traditional assessment methods neglecting surrounding environmental factors by constructing a multi-dimensional environmental parameter fusion model. First, the water quantity index eliminates dimensional differences through normalization; a higher value indicates a more abundant supply of alternative water sources, reducing reliance on current fire hydrants. Second, the population density index is limited to a reasonable range through threshold truncation, preventing extreme population densities from negatively impacting the model. Third, the fire frequency index uses an exponential decay function to transform historical data; the index value decreases exponentially with each additional fire occurrence, reinforcing the risk weight of high-frequency fire areas. Finally, the location field coefficient integrates the three parameters through a square root function, mathematically ensuring the output value remains within the 0-1 range. When there is high population density, scarce alternative water sources, and frequent fires, the coefficient approaches 1, accurately representing high-risk scenarios.

[0105] Through the above technical solution, this application can dynamically assess the environmental risk level of the location of fire hydrants. When the area is densely populated and lacks alternative water sources, even if the equipment itself is in good condition, a maintenance warning will still be triggered due to an increase in the location field coefficient, preventing insufficient fire rescue capabilities caused by the accumulation of environmental risks. At the same time, by integrating historical fire data, fire hydrants in high-frequency accident areas can be identified, and their status monitoring and resource allocation can be prioritized.

[0106] Preferably, the pressure-flow compatibility is expressed as:

[0107] ;

[0108] in, Indicates pressure-flow adaptability. Indicates the field coefficient at the current position. Indicates the current tilt field coefficient. Indicates the current pressure field coefficient. Indicates the optimal pressure field coefficient. This indicates the maximum permissible deviation of the pressure field coefficient from the optimal value. This represents the current flow field coefficient. Indicates the optimal flow field coefficient. This indicates the maximum permissible deviation of the flow field coefficient from the optimal value. Furthermore, the larger the value, the better the fit between pressure and flow rate under the current location field coefficient and the current tilt field coefficient.

[0109] Among them, the location field coefficient is a comprehensive quantitative index of the environmental risk surrounding the fire hydrant, used to reflect the urgency of fire protection needs at the location of the fire hydrant. The tilt field coefficient is a quantitative index of the physical state of the fire hydrant, used to reflect the direct impact of the fire hydrant's installation stability on the pressure-flow relationship. The pressure field coefficient is a quantitative index of the dynamic pressure characteristics of the fire hydrant, used to characterize pressure stability. The flow field coefficient is a quantitative index of the dynamic flow characteristics of the fire hydrant, used to characterize flow stability. The optimal pressure field coefficient and optimal flow field coefficient can be preset theoretical values ​​or statistical values ​​under historical normal conditions, and the maximum allowable deviation can be a threshold set according to actual working conditions.

[0110] Specifically, the pressure-flow adaptability is calculated as follows: First, the adaptability is weighted and adjusted using a position field coefficient. When the surrounding environmental risk is high, the pressure-flow adaptability is suppressed, reflecting the stringent requirements for fire hydrant performance in high-risk areas. Second, the adaptability is directly corrected using a tilt field coefficient. When the tilt state is abnormal, the adaptability decreases, reflecting the influence of physical conditions on pressure and flow. Furthermore, an exponential function is used to nonlinearly penalize the degree of deviation of the pressure and flow fields from their optimal values. The greater the deviation, the more significant the attenuation of the pressure-flow adaptability, thus highlighting the importance of dynamic pressure-flow balance. Finally, through multi-factor coupled calculation, considering environmental risk, physical conditions, and dynamic pressure-flow characteristics, a comprehensive adaptability index reflecting the overall performance of the fire hydrant is output.

[0111] Through the above technical solution, this application can solve the problem of inaccurate adaptability assessment caused by the lack of comprehensive consideration of environmental factors and the dynamic relationship between pressure and flow in traditional operation and maintenance. For example, in densely populated areas with scarce alternative water sources, a higher priority maintenance response can be triggered by reducing the adaptability weight; when fire hydrants are tilted or vibrating abnormally, potential physical hazards can be detected in a timely manner by suppressing adaptability; at the same time, by dynamically monitoring pressure and flow deviations, performance degradation trends can be accurately identified, thereby providing a more reliable basis for judging the condition of fire hydrants.

[0112] Preferably, the steps for constructing a fire hydrant confidence model based on pressure-flow adaptability and the current service life of the fire hydrant, and outputting the fire hydrant confidence level, are as follows:

[0113] Import the current service life of the fire hydrant into the formula. The service life index is obtained from the data. Indicates the current service life of the fire hydrant. Indicates the rated service life of the fire hydrant;

[0114] The current service life index and current pressure-flow compatibility are imported into the fire hydrant confidence model to obtain the current fire hydrant confidence level. The fire hydrant confidence model is expressed as follows:

[0115] ;

[0116] in, This indicates the current confidence level of the fire hydrant. This indicates the current pressure-flow adaptability. Indicates the lifetime degradation coefficient. Indicates the current service life index, the The higher the value, the better the condition of the fire hydrant;

[0117] Current fire hydrant confidence level Compare with the corresponding threshold:

[0118] like If so, the current fire hydrant is in a reliable state;

[0119] like If so, the current fire hydrant needs to be monitored;

[0120] like If so, the current fire hydrant needs maintenance or replacement.

[0121] The service life index reflects the cumulative effect of fire hydrant service time. Pressure-flow adaptability assesses the synergistic state of operating parameters. The lifespan decay coefficient is the rate of performance degradation of the fire hydrant with increasing service life; its value can be set differently based on material properties or environmental factors to adjust the weight of aging on the confidence level. The confidence level model is a mathematical expression that integrates the pressure-flow adaptability and service life index, implemented using an exponential function, to comprehensively characterize the immediate performance and long-term reliability of the fire hydrant. Threshold judgment divides the confidence level into three intervals corresponding to different maintenance strategies; this can be implemented using a fixed threshold or a dynamic adjustment mechanism to guide differentiated maintenance decisions.

[0122] Specifically, the service life index, by limiting its maximum value to 1, avoids excessively amplifying the aging of equipment exceeding its service life. Pressure-flow adaptability, as a fundamental parameter, reflects the hydraulic performance stability of fire hydrants under specific environments. The exponential function design in the confidence model ensures that the decay of confidence over service life exhibits a non-linear characteristic, better reflecting the actual aging patterns of engineering equipment. The introduction of a lifespan decay coefficient allows for adjustments to the weighting of aging impacts based on differences in fire hydrant materials or installation environments. Threshold division employs a tiered judgment logic: a maintenance command is triggered when the confidence level is below 0.4, while a level above 0.7 indicates a reliable state; monitoring mode is activated in the intermediate range, forming a tiered response mechanism.

[0123] A fire hydrant intelligent operation and maintenance management system, employing the aforementioned fire hydrant intelligent operation and maintenance management method, includes:

[0124] The flow field analysis module constructs a flow field model based on the real-time flow value and flow fluctuation value of the fire hydrant and outputs the flow field coefficients.

[0125] The pressure change field analysis module constructs a pressure change field model based on the real-time pressure value, pressure fluctuation value, and pressure recovery rate of the fire hydrant, and outputs the pressure field coefficients.

[0126] The tilt field analysis module constructs a tilt field model based on the tilt angle, tilt change rate, and vibration amplitude of the fire hydrant, and outputs the tilt field coefficients.

[0127] The location field analysis module constructs a location field model based on the personnel density, historical fire frequency, and other water source quantities in the fire hydrant coverage area, and outputs location field coefficients.

[0128] The pressure-flow adaptation analysis module constructs a pressure-flow adaptation model based on the tilt field coefficient, position field coefficient, pressure field coefficient, and flow field coefficient, and outputs the pressure-flow adaptation degree.

[0129] The status analysis module constructs a fire hydrant confidence model based on pressure-flow adaptability and the current service life of the fire hydrant, outputs the fire hydrant confidence score, and judges the status of the fire hydrant based on the fire hydrant confidence score.

[0130] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0131] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent operation and maintenance management of fire hydrants, characterized in that, Includes the following steps: The flow field model is constructed based on the real-time flow value and flow fluctuation value of the fire hydrant, and the flow field coefficients are output. The specific steps are as follows: Import real-time traffic into the formula Obtain real-time traffic index from [the source], where [the data] is [the source]. Indicates real-time traffic. This indicates a reference to real-time traffic. This indicates that deviations from the reference real-time traffic value are allowed; Importing flow fluctuations into the formula The traffic fluctuation index is obtained from the data. Indicates traffic fluctuations. Indicates reference flow fluctuation. This indicates that deviations from the reference flow rate fluctuation value are permissible; The current real-time flow index and the current flow fluctuation index are imported into the flow field model to obtain the current flow field coefficients. The flow field model is expressed as follows: ； in, This represents the current flow field coefficient. This indicates the current real-time traffic index. This indicates the current traffic fluctuation index. Represents the weight coefficient and The Furthermore, the higher the value, the more stable the fire hydrant flow rate; A pressure change field model is constructed based on the real-time pressure value, pressure fluctuation value, and pressure recovery rate of the fire hydrant, and the pressure field coefficients are output. The specific steps are as follows: The pressure fluctuation value and pressure recovery rate are obtained by performing maximum-min normalization on the pressure fluctuation value and pressure recovery rate; Import real-time pressure into the formula Obtain the real-time stress index, among which, Indicates real-time pressure. This indicates the reference real-time pressure. This indicates that deviations from the reference real-time pressure value are permissible; The pressure field coefficients are obtained by importing the current real-time pressure index, current pressure fluctuation index, and current pressure recovery rate index into the pressure field model. The pressure field model is expressed as follows: ； in, Indicates the current pressure field coefficient. This indicates the current real-time stress index. This indicates the current pressure fluctuation index. Indicating the pressure recovery speed index, Represents the weight coefficient and The Furthermore, the higher the value, the better the fire hydrant pressure condition; Based on the tilt angle, tilt change rate, and vibration amplitude of the fire hydrant, a tilt field model is constructed to output the tilt field coefficients. The specific steps are as follows: The tilt angle, tilt change rate, and vibration amplitude are subjected to maximum-min normalization to obtain the tilt angle index, tilt change rate index, and vibration amplitude index. The current tilt angle index, current tilt change rate index, and current vibration amplitude index are imported into the tilt field model to obtain the current tilt field coefficients. The tilt field model is expressed as follows: ； ； in, Indicates the current tilt field coefficient. This represents the tilt analysis coefficient. Indicates the attenuation coefficient. Indicates the current tilt angle index. This represents the rate of change of slope index. This indicates the current vibration amplitude index. Represents the weight coefficient and The Furthermore, the higher the value, the better the physical condition of the fire hydrant; Based on the population density, historical fire frequency, and quantity of other water sources in the fire hydrant coverage area, a location field model is constructed to output location field coefficients. The specific steps are as follows: The water source quantity index is obtained by performing maximum-min normalization on the quantity of other water sources. Importing personnel density into the formula The population density index was obtained from the data. Indicates population density. Indicates the maximum permissible personnel density; Importing historical fire frequency into the formula The fire frequency index was obtained from the data. Indicates the frequency of historical fires; The current water quantity index, current population density index, and current fire frequency index are imported into the location field model to output the current location field coefficients. The location field model is represented as follows: ； in, Indicates the field coefficient at the current position. This indicates the current population density index. This indicates the current water quantity index. The fire frequency index is represented by the following. Furthermore, the larger the value, the greater the risk in the location field; A pressure-flow adaptation model is constructed based on the tilt field coefficient, position field coefficient, pressure field coefficient, and flow field coefficient, and the pressure-flow adaptation degree is output. The pressure-flow adaptation degree is expressed as: ； in, Indicates pressure-flow adaptability. Indicates the field coefficient at the current position. Indicates the current tilt field coefficient. Indicates the current pressure field coefficient. Indicates the optimal pressure field coefficient. This indicates the maximum permissible deviation of the pressure field coefficient from the optimal value. This represents the current flow field coefficient. Indicates the optimal flow field coefficient. This indicates the maximum permissible deviation of the flow field coefficient from the optimal value. Furthermore, the larger the value, the higher the compatibility between pressure and flow rate under the current location field coefficient and the current tilt field coefficient; A fire hydrant confidence model is constructed based on pressure-flow adaptability and the current service life of the fire hydrant to output the fire hydrant confidence score. The fire hydrant status is determined based on the fire hydrant confidence score. The fire hydrant confidence score is obtained as follows: Import the current service life of the fire hydrant into the formula. The service life index is obtained from the data. Indicates the current service life of the fire hydrant. Indicates the rated service life of the fire hydrant; The current service life index and current pressure-flow compatibility are imported into the fire hydrant confidence model to obtain the current fire hydrant confidence level. The fire hydrant confidence model is expressed as follows: ； in, This indicates the current confidence level of the fire hydrant. This indicates the current pressure-flow adaptability. Indicates the lifetime degradation coefficient. Indicates the current service life index, the The higher the value, the better the condition of the fire hydrant.

2. The intelligent operation and maintenance management method for fire hydrants according to claim 1, characterized in that, The steps for determining the status of a fire hydrant based on its confidence level are as follows: Current fire hydrant confidence level Compare with the corresponding threshold: like If so, the current fire hydrant is in a reliable state; like If so, the current fire hydrant needs to be monitored; like If so, the current fire hydrant needs maintenance or replacement.

3. A fire hydrant intelligent operation and maintenance management system, characterized in that, The intelligent operation and maintenance management method for fire hydrants according to any one of claims 1-2 includes: The flow field analysis module constructs a flow field model based on the real-time flow value and flow fluctuation value of the fire hydrant and outputs the flow field coefficients. The pressure change field analysis module constructs a pressure change field model based on the real-time pressure value, pressure fluctuation value, and pressure recovery rate of the fire hydrant, and outputs the pressure field coefficients. The tilt field analysis module constructs a tilt field model based on the tilt angle, tilt change rate, and vibration amplitude of the fire hydrant, and outputs the tilt field coefficients. The location field analysis module constructs a location field model based on the personnel density, historical fire frequency, and other water source quantities in the fire hydrant coverage area, and outputs location field coefficients. The pressure-flow adaptation analysis module constructs a pressure-flow adaptation model based on the tilt field coefficient, position field coefficient, pressure field coefficient, and flow field coefficient, and outputs the pressure-flow adaptation degree. The status analysis module constructs a fire hydrant confidence model based on pressure-flow adaptability and the current service life of the fire hydrant, outputs the fire hydrant confidence score, and judges the status of the fire hydrant based on the fire hydrant confidence score.

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