Intelligent monitoring system, fire hydrant and intelligent monitoring method

Abstract

The invention relates to the technical field of fire fighting equipment, and aims to solve the technical problem that conditions such as water stealing, water stealing, collision or damage cannot be recognized. In order to solve the technical problem, the invention provides an intelligent monitoring system, a fire hydrant and an intelligent monitoring method. The device comprises an intelligent blank cap; the intelligent assembly comprises a PCB (Printed Circuit Board), a positioning system for acquiring the geographic position of the fire hydrant and a battery for providing a power supply; the positioning system is electrically connected to the top of the PCB; the vibration monitoring assembly comprises two middle connecting parts and a vibration sensor; the end part of the middle connecting part is connected with the fire hydrant; a pressure sensor of the valve core assembly is used for monitoring a pipe network water pressure signal of underground water of the fire hydrant; the working condition of the fire hydrant is judged to be normal, water outlet, collision or water stealing through the water pressure signal and the vibration signal. According to the water pressure signal and the vibration signal, whether the pipe network water pressure of underground water of the fire hydrant is normal or not and the working condition of the fire hydrant can be monitored.

Description

Technical Field

[0001] The present invention relates to the technical field of fire-fighting equipment, and in particular to an intelligent monitoring system, a fire hydrant and an intelligent monitoring method. Background Art

[0002] Fire hydrants, formally known as fire hydrants, are a type of fixed fire-fighting facility. The main function of fire hydrants is to control combustibles, isolate combustion-supporting materials, and eliminate fire sources; they are divided into indoor fire hydrants and outdoor fire hydrants.

[0003] However, outdoor fire hydrants are exposed on the road surface, which poses many hidden dangers, such as water theft, impact or damage, and insufficient water pressure in the fire hydrants due to problems with local sewer pipes. If these situations cannot be monitored and repaired in time, the fire hydrants may not be able to be used normally in emergency situations such as fires. Replacing the entire fire hydrant with a new one is not only costly, but also difficult and labor-intensive. Summary of the invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the above-mentioned problems existing in the prior art.

[0005] In order to solve the above technical problems, the present invention provides an intelligent monitoring system, comprising:

[0006] The smart cover comprises an upper shell, a lower shell connected to the upper shell, and a smart component; the top of the lower shell is provided with a top cover, and the bottom is sealed and connected to the large water outlet of the fire hydrant; the upper shell is provided with an installation cavity for installing the smart component; the smart component comprises a PCB board, a positioning system for obtaining the geographical location of the fire hydrant, and a battery for providing power; the positioning system is electrically connected to the top of the PCB board, and the battery is electrically connected to the bottom of the PCB board;

[0007] The vibration monitoring assembly includes two intermediate connecting parts and a vibration sensor connected between the two intermediate connecting parts; the vibration sensor is used to collect the vibration signal of the fire hydrant, and the vibration sensor is electrically connected to the PCB board; the end of the intermediate connecting part is connected to the fire hydrant;

[0008] The valve core assembly includes a valve core and a pressure sensor arranged on the valve core. The pressure sensor is used to monitor the water pressure signal of the underground water pipe network of the fire hydrant. The pressure sensor is electrically connected to the PCB board. The working condition of the fire hydrant is judged as normal, water discharge, impact or water theft through the water pressure signal and the vibration signal.

[0009] In one embodiment of the present invention, the vibration monitoring assembly also includes a magnetic connection portion arranged at the end of the intermediate connection portion, and the intermediate connection portion is adsorbed and fixed inside the cover of the small water outlet of the fire hydrant through the magnetic connection portion; the intermediate connection portion is made of metal.

[0010] In one embodiment of the present invention, a Bluetooth module for data transmission is integrated on the PCB board.

[0011] In one embodiment of the present invention, a communication module is integrated on the PCB board, and the communication module communicates with the cloud server.

[0012] In one embodiment of the present invention, an analog-to-digital conversion module for monitoring battery voltage is also integrated on the PCB board.

[0013] In one embodiment of the present invention, a through hole is provided on the top cover, and a waterproof aviation plug is installed in the through hole.

[0014] The present invention also provides a fire hydrant, comprising:

[0015] The smart monitoring system in any of the above embodiments;

[0016] The fire hydrant body is provided with an internal cavity, a large water outlet and two small water outlets; the large water outlet and the small water outlet are both connected to the internal cavity, and the small water outlet is connected with a cover;

[0017] Among them, the end of the middle connecting part of the intelligent monitoring system is connected to the cover; the intelligent cover of the intelligent monitoring system is sealed and connected to the large water outlet; the vibration monitoring component and the valve core component are arranged in the internal cavity.

[0018] The present invention further provides an intelligent monitoring method, which uses the fire hydrant in any of the above embodiments for monitoring; the steps include:

[0019] Data collection, collecting data through the above-mentioned fire hydrants, and converting the collected data into measured values ​​through numerical conversion formulas;

[0020] Estimated value calculation, converting the measured value into an estimated value through a filtering algorithm.

[0021] In one embodiment of the present invention, the collected data includes geographic location, water pressure, vibration, and battery voltage.

[0022] In one embodiment of the present invention, data at N time nodes are collected, and the data include water pressure data, voltage data, and GPS positioning data;

[0023] Given the initial data value: the state transfer matrix A at time node m m , the observation matrix C at time node m m , the noise transition matrix G at time node m m , process noise covariance Q m , observation noise covariance R m , N, select batch [m, α];

[0024] Execute the initialization batch calculation to get the initial value of the iteration part: the estimated value at time node α

[0025] Let i = α + 1 to perform the iterative calculation part and calculate the estimated value at time node i

[0026] Determine whether i=n is true: If true, get the estimated value of the required time node n, then At this point, the iteration ends and n=n+1 is set; if it does not hold, then i=i+1 (i.e. the time node moves forward), and then the iterative calculation part is executed to calculate the estimated value at time node i

[0027] The above technical solution of the present invention has the following advantages compared with the prior art:

[0028] 1. Based on the water pressure signal and vibration signal, it can monitor whether the water pressure of the fire hydrant groundwater pipe network is normal and the working condition of the fire hydrant (including normal, water discharge, impact, theft, etc.).

[0029] 2. Compared with replacing the entire fire hydrant, this embodiment only needs to replace the cover of the largest water outlet with the smart cover, place the sensor inside the fire hydrant, and replace the valve core against the water outlet. The installation is simple, the construction amount is small, and the cost is low. In addition, there are no exposed parts, which ensures that the appearance of existing fire hydrants on the market remains unchanged.

[0030] 3. In this embodiment, the current status of the fire hydrant can be queried through a paging call on the server to ensure the validity and real-time nature of the data; data can also be uploaded at a scheduled time.

[0031] 4. This embodiment is provided with a positioning system disposed on the top of the PCB board, which can monitor the geographical location of the fire hydrant in real time, and can quickly find the available fire hydrant on the map through the networked data.

[0032] 5. When a water thief opens the small water outlet of a fire hydrant to steal water, the middle connection part will vibrate, thereby triggering the vibration sensor. If the large water outlet of a fire hydrant is opened, the vibration sensor will be directly triggered because it is directly connected to the smart cover. Therefore, when the smart component receives the vibration signal to trigger the alarm, it will be sent in time to remind the monitoring personnel that there is water theft. This embodiment adopts a mechanical connection method, which can simultaneously detect the water theft signals of the two small water outlets and one large water outlet of the fire hydrant. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0034] Figure 1 It is a structural schematic diagram of a fire hydrant in a preferred embodiment of the present invention;

[0035] Figure 2 yes Figure 1 A cross-sectional view of

[0036] Figure 3 yes Figure 1 Schematic diagram of the structure of the intelligent monitoring system in Figure 1 ;

[0037] Figure 4 yes Figure 1 Schematic diagram of the structure of the intelligent monitoring system in Figure 2 ;

[0038] Figure 5 yes Figure 1 An exploded diagram of the smart monitoring system in Figure 1;

[0039] Figure 6 is a flow chart of the monitoring method;

[0040] Figure 7 is a flow chart of the maximum likelihood finite impulse response filter algorithm.

[0041] Description of the reference numerals in the specification: 1000, fire hydrant;

[0042] 100, fire hydrant body; 110, internal cavity; 120, large water outlet; 130, small water outlet 130; 140, cover;

[0043] 200. Intelligent monitoring system; 210. Intelligent sealing cover; 211. Upper shell; 212. Lower shell; 2121. Top cover; 2122. Sealing ring; 213. PCB board; 214. Positioning system; 215. Battery; 216. First support member; 217. Second support member; 218. Waterproof aviation plug; 220. Vibration monitoring assembly; 221. Middle connecting part; 222. Vibration sensor; 223. Magnetic connecting part; 230. Valve core assembly; 231. Valve core; 232. Pressure sensor. DETAILED DESCRIPTION

[0044] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0045] Reference Figure 1 to Figure 7As shown, an embodiment of the present invention provides a fire hydrant, including: a fire hydrant body 100 and a smart monitoring system 200. The fire hydrant body 100 is provided with an internal cavity 110, a large water outlet 120 and two small water outlets 130; the large water outlet 120 and the small water outlet 130 are both connected to the internal cavity 110, and the small water outlet 130 is connected to a cover 140.

[0046] The smart monitoring system 200 includes: a smart cover 210, a vibration monitoring component 220 and a valve core 231 component 230. Among them:

[0047] The smart cover 210 includes an upper shell 211, a lower shell 212 connected to the upper shell 211, and a smart component; the top of the lower shell 212 is provided with a top cover 2121, and the bottom is sealed and connected to the large water outlet 120 of the fire hydrant 1000. The top cover 2121 separates the fire hydrant 1000 from the smart component to prevent the smart component from malfunctioning due to water ingress. In some embodiments, the connection end of the lower shell 212 is provided with a thread, which matches the thread diameter of the large water outlet 120 of the fire hydrant 1000, and a sealing ring 2122 is installed in the lower shell 212 to achieve a sealed connection between the smart cover 210 and the large water outlet 120 of the fire hydrant 1000. This can prevent water ingress caused by long-term immersion of water inside the fire hydrant 1000. The upper housing 211 is provided with a mounting cavity for mounting the smart component; the smart component includes a PCB board 213, a positioning system 214 for obtaining the geographical location of the fire hydrant 1000, and a battery 215 for providing power; the positioning system 214 is electrically connected to the top of the PCB board 213 (for example, using a high-precision GPS antenna), and the battery 215 is electrically connected to the bottom of the PCB board 213. In some embodiments, the smart component also includes a first support member 216 and a second support member 217 fixedly connected to the upper housing, the first support member 216 is used to mount the positioning system 214, and the second support member 217 is used to mount the battery 215. The PCB board 213 also integrates an ADC module and a storage chip of a single-chip microcomputer.

[0048] The vibration monitoring assembly 220 includes two intermediate connecting parts 221 and a vibration sensor 222 connected between the two intermediate connecting parts 221; the vibration sensor 222 is used to collect the vibration signal of the fire hydrant 1000, and the vibration sensor 222 is electrically connected to the PCB board 213. The end of the intermediate connecting part 221 is connected to the fire hydrant 1000.

[0049] The valve core 231 assembly 230 includes a valve core 231 and a pressure sensor 232 disposed on the valve core 231. The pressure sensor 232 is used to monitor the water pressure signal of the underground water network of the fire hydrant 1000. The pressure sensor 232 is electrically connected to the PCB board 213; that is, the water pressure of the municipal pipe network can be collected through the pressure sensor 232. In some possible implementations, a through hole is opened on the valve core 231, and a mounting interface matching the pressure sensor 232 is installed in the through hole. The pressure sensor 232 is installed at the mounting interface so that the water of the water administration pipe network contacts the sensing part of the pressure sensor 232 to measure the water pressure in the municipal pipe network.

[0050] The end of the middle connection part 221 of the smart monitoring system 200 is connected to the cover 140 ; ​​the smart cover 210 of the smart monitoring system 200 is sealed and connected to the large water outlet 120 ; the vibration monitoring component 220 and the valve core 231 component 230 are arranged in the internal cavity 110 .

[0051] The present application determines the working condition of the fire hydrant 1000 as normal, water discharge, impact or water theft through water pressure signal and vibration signal. The specific classification is as follows:

[0052] When the fire hydrant 1000 is in a normal state (valve not opened): the water pressure of the underground pipe network is a static fixed value of water pressure (the water pressure of each fire hydrant 1000 in a normal state is basically fixed, basically between 0.2-0.35 MPa).

[0053] When the fire hydrant 1000 is in the water discharge state (valve open): the fire hydrant 1000 starts to discharge water, and the water pressure in the fire hydrant 1000 will have a small but obvious change in the static fixed value of the water pressure, and the vibration sensor 222 will have a signal feedback. In one embodiment, a fire hydrant 1000 is monitored. When the fire hydrant 1000 is in a normal state: its normal state is in a fixed water pressure of 0.25-0.26 MPa. When the fire hydrant 1000 is in the water discharge state (valve open): the water pressure value will become 0.30-0.32 MPa (slightly different depending on the size of the valve opening).

[0054] When the fire hydrant 1000 is in a collision state or a water theft state: the water pressure is a static fixed value and the water pressure does not change; and the vibration sensor 222 has a feedback signal. And through the difference in the vibration sensor 222 signal (single vibration feedback and continuous periodic vibration feedback correspond to different alarm conditions. For example, a single vibration feedback collision alarm condition. Continuous periodic vibration feedback water theft alarm condition) it can be fed back whether it is in a collision state or a water theft state.

[0055] The specific subdivision working conditions will be determined in the system based on the duration of the feedback signal from the vibration sensor 222 and the analysis and basis of our large amount of experimental data.

[0056] Therefore, based on whether the water pressure changes and whether the vibration sensor 222 has signal feedback or the information of the vibration sensor 222 signal feedback, it can be determined whether the fire hydrant 1000 is in a normal state, a water discharge state, a collision state or a water theft state.

[0057] This embodiment has the following beneficial effects:

[0058] 1. This embodiment can monitor whether the water pressure of the underground water network of the fire hydrant 1000 is normal and the working condition of the fire hydrant 1000 (including normal, water discharge, collision, theft, etc.) according to the water pressure signal and the vibration signal.

[0059] 2. Compared with replacing the entire fire hydrant 1000, during installation, this embodiment only needs to replace the cover of the largest water outlet 120 with the smart cover 210, place the sensor inside the fire hydrant 1000, and replace the valve core 231 against the water outlet. The installation is simple, the construction work is small, and the cost is low. In addition, there are no exposed parts, which ensures that the appearance of the existing fire hydrant 1000 on the market does not change.

[0060] 3. In this embodiment, the current status of the fire hydrant 1000 can be queried through a paging call on the server to ensure the validity and real-time nature of the data; data can also be uploaded at a scheduled time.

[0061] 4. This embodiment is provided with a positioning system 214 disposed on the top of the PCB board 213, which can monitor the geographical location of the fire hydrant 1000 in real time, and can quickly find the available fire hydrant 1000 on the map through network data.

[0062] 5. When a water thief opens the small water outlet 130 of the fire hydrant 1000 to steal water, the middle connection part 221 will vibrate, thereby triggering the vibration sensor 222. If the large water outlet 120 of the fire hydrant 1000 is opened, the vibration sensor 222 will be directly triggered because it is directly connected to the smart cover 210. Therefore, when the smart component receives the vibration signal to trigger the alarm, it will be sent in time to remind the monitoring personnel that there is water theft. This embodiment adopts a mechanical connection method, which can simultaneously detect the water theft signals of the two small water outlets 130 and one large water outlet 120 of the fire hydrant 1000.

[0063] In summary, this application has small construction volume, low cost, long working time, stable data detection, and accurate working condition judgment.

[0064] Furthermore, the vibration monitoring assembly 220 also includes a magnetic connection part 223 disposed at the end of the intermediate connection part 221, and the intermediate connection part 221 is fixed to the inside of the cover 140 of the small water outlet 130 of the fire hydrant 1000 by adsorption through the magnetic connection part 223; the intermediate connection part 221 is made of metal. Specifically, this embodiment realizes a detachable connection between the intermediate connection part 221 and the cover 140, which is convenient for opening the cover 140 quickly and without causing damage to other components when the fire hydrant 1000 is put into use, and can also monitor whether someone steals water.

[0065] Furthermore, a Bluetooth module for data transmission is integrated on the PCB board 213. In this way, the Bluetooth module can be directly connected to the mobile phone APP, and the working parameters such as the data upload and transmission frequency, initialization parameters, water pressure threshold, detection frequency, detection sensitivity, and device number of the smart fire hydrant 1000 can be set through the mobile phone APP.

[0066] Furthermore, a communication module is integrated on the PCB board 213, and the communication module communicates with the cloud server. The communication module is used to communicate with the cloud server to realize data interaction. In this way, the monitored data can be uploaded regularly. Compared with devices that can only upload fixed data, this device can also page the smart fire hydrant 1000 at any time through the cloud server or mobile phone APP. After paging, it will actively send data, which can truly replace manual inspections and realize remote management and monitoring of the fire hydrant 1000, effectively improving the necessity and real-time nature of the data.

[0067] Furthermore, the PCB board 213 is also integrated with an analog-to-digital conversion module ADC for monitoring the voltage of the battery 215. The analog-to-digital conversion module ADC can monitor the voltage of the battery 215, and by detecting the voltage of the battery 215, the usage and service life of the battery 215 can be reflected.

[0068] Furthermore, the upper shell and the lower shell are made of high-strength nylon. Compared with traditional engineering plastics, high-strength nylon materials are more wear-resistant and have better toughness. Considering the wear and tear during the installation of the fire hydrant 1000 and the damage to the present invention caused by the use of the fire hydrant 1000 wrench, the upper shell and the lower shell made of high-strength nylon can effectively extend the service life of the present invention and expand the use conditions of the present invention, ensuring the safety of internal components.

[0069] Furthermore, a through hole is provided on the top cover 2121, and a waterproof aviation plug 218 is installed in the through hole. In this way, the wires of the vibration sensor 222 and the pressure sensor 232 pass through the waterproof aviation plug 218 on the top cover 2121 and are electrically connected to the PCB board 213. This embodiment effectively avoids water ingress into the smart cover 210 caused by long-term immersion due to water accumulation inside the fire hydrant 1000.

[0070] Furthermore, the present invention also has a built-in storage function for power-off protection, which can effectively store recent device data in the event of device abnormality or power failure, thereby realizing data protection and backup functions.

[0071] The present invention further provides an intelligent monitoring method, which uses the fire hydrant 1000 in any of the above embodiments for monitoring; the steps include:

[0072] Data collection, through the fire hydrant data collection, the collected data is converted into measurement values ​​through the numerical conversion formula; the collected data includes geographic location data, water pressure data, vibration data and battery 215 voltage data. Since the pressure sensor 232, vibration sensor 222, etc. output analog quantities, they are read through the ADC module of the single-chip microcomputer on the PCB board 213. Then the ADC module of the single-chip microcomputer converts the collected ADC values ​​into corresponding water pressure measurement values, vibration measurement values, battery 215 voltage measurement values, etc. through the numerical conversion formula.

[0073] Estimated value calculation, the measured value is converted into an estimated value through a filtering algorithm. Because: the water pressure measured by the pressure sensor 232 will change due to the water pressure fluctuation when the fire hydrant 1000 releases water and the pressure fluctuation of the municipal pipe network when the water is used. In addition, there will be errors in the pressure sensor 232 itself and the acquisition of the single-chip ADC module. Similarly, there are errors in the acquisition of geographic location data, vibration signal acquisition, and battery 215 voltage signal acquisition. If the measurement data is inaccurate, it may cause firefighters to misjudge the water pressure state in the fire hydrant 1000 when they encounter a fire and need water. Seriously, it may lead to the wrong selection of the fire hydrant 1000, and the pressure is too low or even no water is available, resulting in delays. It can be seen that the accuracy of the measurement of the fire hydrant 1000 pressure sensor 232, the accuracy of the battery 215 voltage measurement, the accuracy of the fire hydrant 1000 position positioning measurement, and the accuracy of the vibration sensor 222 measurement are all crucial. After analysis, the reason for these data errors is the existence of noise disturbance. Therefore, the measured value is converted into an estimated value through a filtering algorithm. Thereby improving the accuracy of the data.

[0074] See also Figure 6 , the workflow of this application is as follows:

[0075] The device (the fire hydrant cover) is powered on, relevant parameters are configured, the device wakes up, and it is determined whether it is a scheduled wake-up. If it is a scheduled wake-up, data is collected and the maximum likelihood finite impulse response filter algorithm is called for calculation, and the device is sent to the server and goes into sleep mode. If it is not a scheduled wake-up, it is determined whether it is a vibration wake-up. If it is a vibration wake-up, the impact or water theft alarm is determined based on the number of vibrations and sent to the server, and then data is collected and the maximum likelihood finite impulse response filter algorithm is called for calculation, and the device is sent to the server and goes into sleep mode. If it is not a vibration wake-up, it is determined whether it is a wake-up due to low water pressure. If it is a wake-up due to low water pressure, the impact or water theft alarm is determined based on the number of vibrations and sent to the server, and then data is collected and the maximum likelihood finite impulse response filter algorithm is called for calculation, and the device is sent to the server and goes into sleep mode. If it is not a wake-up due to low water pressure, data is directly collected and the maximum likelihood finite impulse response filter algorithm is called for calculation, and the device is sent to the server and goes into sleep mode.

[0076] See also Figure 7 , the workflow of the maximum likelihood finite impulse response filter algorithm calculation is as follows:

[0077] Collect data at N time nodes, including water pressure data, voltage data, and GPS positioning data;

[0078] Given the initial data value: the state transfer matrix A at time node m m , the observation matrix C at time node m m , the noise transition matrix G at time node m m , process noise covariance Q m , observation noise covariance R m , N, select batch [m, α];

[0079] Execute the initialization batch calculation to get the initial value of the iteration part: the estimated value at time node α

[0080] Let i = α + 1 to perform the iterative calculation part and calculate the estimated value at time node i

[0081] Determine whether i=n is true: If true, get the estimated value of the required time node n, then At this point, the iteration ends and n=n+1; if it does not hold, then i=i+1

[0082] (i.e. the time node moves forward), and then executes the iterative calculation part to calculate the estimated value at time node i

[0083] See also Figure 7 , the maximum likelihood finite impulse response filter algorithm is as follows:

[0084] 1. In the storage chip carried by the smart fire hydrant, the estimated values ​​of water pressure, vibration, battery voltage, and coordinate position calculated by the filter are set as The specific implementation of the maximum likelihood finite impulse response filter is as follows, and the following state space model is defined as:

[0085] x n =A n x n-1 +G n w n -------Formula 1

[0086] y n =C n x n +v n ----------Formula 2

[0087] In formula 1 and formula 2: x n True is the status value; A t is the state transfer matrix, t is the time node, A n is the state transfer matrix at time node n, A n Determined by the specific system; G t is the noise conversion matrix, G n is the noise conversion matrix at time node n, w n To satisfy the Gaussian distribution N(0,Q n ) is a white process noise, where Q n is the process noise covariance, y n is the measured value, C t is the observation matrix, C n is the observation matrix at time node n, x n True is the state value; v n To satisfy the Gaussian distribution N(0,R n ) measurement noise, where R n is the observation noise covariance,

[0088] 2. An extended state space model similar to the original model (i.e., Formula 1 and Formula 2) on the interval [m=n-N+1,n] is constructed as follows, where N is the range length; m and n are both time nodes:

[0089] X n,m =A n,m x m-1 +G n,m Wn,m -------------Formula 1.1

[0090] Y n,m =C n,m x m-1 +L n,m W n,m +V n,m -------Formula 2.1

[0091] In formula 1.1 and formula 2.1: X n,m , W n,m , Y n,m 、V n,m are all extended vectors, i.e., vectors expanded over the time range [m, n];

[0092] x m-1 is the state value at time m-1, which is artificially given; A n,m , G n,m , C n,m , L n,m are all extended matrices, where:

[0093]

[0094] In Formula 3, Formula 4, Formula 5 and Formula 6: n, m are time nodes; generally n≥m, and when n=m,

[0095] is a diagonal matrix;

[0096] 3. Estimated value It can be calculated by the following algorithm:

[0097] First, determine the maximum likelihood finite impulse response filter calculation horizon [m, n], i is the iterative calculation range time node i∈[ε, n], where ε=max{m+K, m+2}, K is the state dimension; iterative calculation part:

[0098]

[0099] In formula 7: A i is the state transition matrix A at time node i, i∈[ε,n]; is the estimated value at time node i-1;

[0100] I is the identity matrix, C iis the observation matrix at time node i; P t is the parameter P at time node t, P i is the parameter P at time node i; R i is the observation noise covariance at time node i; G i is the noise transfer matrix at time node i; Q i is the process noise covariance at time node i; I is the identity matrix, when i - 1 = α, α is the time node, initial value from calculate, where, A α is the state transition matrix at time node α; D α-1 is the parameter D at time node α - 1; is for Δ α-1,m the inverse matrix of,

[0101] E[…] represents taking the expectation of a certain value; C α-1,m is calculated from the aforementioned formula 5 (where the time node n takes α - 1); y i is the measurement value at time node i.

[0102] 4. Batch calculation part:

[0103] Initialize the batch calculation range [m, α] part, α = ε - 1, where m < α < n, m and α are time nodes;

[0104]

[0105] In formula 8: is the parameter D at time node t, D α is the parameter D at time node α;

[0106]

[0107]

[0108] In formula 9: P α is the parameter P at time node α;

[0109] is the first row of matrix G n,m ; E[…] represents taking the expectation of a certain value; A α is the state transition matrix at time node α; D t is the parameter D at time node t, Dα is the parameter D at time node α-1;

[0110]

[0111] E[…] means to find the expectation of a value.

[0112] After testing, the filtering algorithm of the present application can judge various working conditions such as normal, water release, impact, damage, etc. according to the data of vibration sensor and water pressure sensor. After experimental comparison of data, the accuracy of working condition judgment is as high as 98%.

[0113] In actual operation, the water pressure and positioning data collected by the sensor are recorded as the observation value y n The water pressure and positioning data calculated by the algorithm are recorded as estimated values

[0114] When the fire hydrant is powered on, current fluctuations (battery voltage, pressure sensor), peak current (battery voltage, pressure sensor), weather and other factors (GPS) will produce abnormal data with large errors. The use of this filtering algorithm can significantly reduce the data abnormality rate, improve the accuracy of equipment detection, and ensure the effective measurement of the water pressure of the municipal pipe network connected to the fire hydrant. The fire hydrant can accurately inform firefighters of the internal water pressure of the pipe network to prevent the situation where the pipe network pressure is insufficient when water is needed due to errors in collecting pressure. The estimated values ​​of water pressure and positioning will be used as a more accurate value for firefighters to refer to.

[0115] Obviously, the above embodiments are merely examples for the purpose of clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. An intelligent monitoring system, characterized in that: include: The smart cover comprises an upper shell, a lower shell connected to the upper shell, and a smart component; the top of the lower shell is provided with a top cover, and the bottom is sealed and connected to the large water outlet of the fire hydrant; the upper shell is provided with an installation cavity for installing the smart component; the smart component comprises a PCB board, a positioning system for obtaining the geographical location of the fire hydrant, and a battery for providing power; the positioning system is electrically connected to the top of the PCB board, and the battery is electrically connected to the bottom of the PCB board; A vibration monitoring component, comprising two intermediate connecting parts and a vibration sensor connected between the two intermediate connecting parts; the vibration sensor is used to collect the vibration signal of the fire hydrant, and the vibration sensor is electrically connected to the PCB board; the end of the intermediate connecting part is connected to the fire hydrant; A valve core assembly, comprising a valve core and a pressure sensor disposed on the valve core, wherein the pressure sensor is used to monitor the water pressure signal of the pipe network of the fire hydrant groundwater, and the pressure sensor is electrically connected to the PCB board; The working condition of the fire hydrant is judged as normal, water discharge, impact or water theft by the water pressure signal and the vibration signal.

2. The intelligent monitoring system according to claim 1, characterized in that: The vibration monitoring component also includes a magnetic connection part arranged at the end of the intermediate connection part, and the intermediate connection part is adsorbed and fixed inside the cover of the small water outlet of the fire hydrant through the magnetic connection part; the intermediate connection part is made of metal.

3. The intelligent monitoring system according to claim 1, characterized in that: The PCB board is integrated with a Bluetooth module for data transmission.

4. The intelligent monitoring system according to claim 3, characterized in that: A communication module is integrated on the PCB board, and the communication module communicates with the cloud server.

5. The intelligent monitoring system according to claim 1, characterized in that: The PCB board is also integrated with an analog-to-digital conversion module for monitoring the battery voltage.

6. The intelligent monitoring system according to claim 1, characterized in that: The top cover is provided with a through hole, in which a waterproof aviation plug is installed.

7. A fire hydrant, characterized in that: include: The intelligent monitoring system according to any one of claims 1 to 6; A fire hydrant body, wherein the fire hydrant body is provided with an internal cavity, a large water outlet and two small water outlets; the large water outlet and the small water outlet are both connected to the internal cavity, and the small water outlet is connected with a cover; Among them, the end of the middle connecting part of the smart monitoring system is connected to the cover; the smart cover of the smart monitoring system is sealed and connected to the large water outlet; the vibration monitoring component and the valve core component are arranged in the internal cavity.

8. An intelligent monitoring method, characterized in that: The fire hydrant of claim 7 is used for monitoring; the steps include: Data collection, collecting data through the fire hydrant, and converting the collected data into measured values ​​through a numerical conversion formula; Estimated value calculation, converting the measured value into an estimated value through a filtering algorithm.

9. The intelligent monitoring system according to claim 8, characterized in that: The data collected includes geographic location, water pressure, vibration and battery voltage.

10. The intelligent monitoring system according to claim 8, characterized in that: Collect data at N time nodes, including water pressure data, voltage data, and GPS positioning data; Given the initial data value: the state transfer matrix A at time node m m , the observation matrix C at time node m m , the noise transition matrix G at time node m m , process noise covariance Q m , observation noise covariance R m , N, select batch [m, α]; Execute the initialization batch calculation to get the initial value of the iteration part: the estimated value at time node α Let i = α + 1 to perform the iterative calculation part and calculate the estimated value at time node i Determine whether i=n is true: If true, get the estimated value of the required time node n, then At this point, the iteration ends and n=n+1 is set; if it does not hold, then i=i+1 (i.e. the time node moves forward), and then the iterative calculation part is executed to calculate the estimated value at time node i

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