Fire warning system based on multi-dimensional data linkage
Through a fire protection and early warning system with multi-dimensional data linkage, comprehensively analyzing equipment and personnel parameters, the inaccurate and untimely warning problems caused by single data analysis in the existing technology are solved, and accurate monitoring and early warning of complex environments are achieved.
Patent Information
- Application Number
- CN202410171682.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-02-06
- Publication Date
- 2024-12-27
- Estimated Expiration
- 2044-02-06
AI Technical Summary
The existing fire protection and early warning systems mainly rely on single data analysis, resulting in inaccurate and untimely warnings, and are unable to effectively deal with complex high-temperature and high-pressure environments and multi-dimensional hidden dangers.
A fire protection and early warning system based on multi-dimensional data linkage is adopted to comprehensively analyze equipment parameters and personnel parameters through multi-dimensional data acquisition, equipment data monitoring, people flow data monitoring and fire protection and early warning analysis to generate accurate risk warning information.
It improves the accuracy and timeliness of fire warnings, reduces errors, and ensures effective monitoring and early warning of complex environments.
Smart Images
Figure CN118470932B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of smart fire protection technology, and specifically to a fire warning system based on multi-dimensional data linkage. Background Art
[0002] Currently, petroleum companies, chemical companies and other places have a large number of flammable substances, complex production equipment, criss-crossing pipeline networks, and many containers and equipment under high temperature and high pressure conditions, which poses a relatively large fire hazard. The current fire warning system is mainly implemented through smoke alarms, temperature sensors or image analysis.
[0003] According to the patent with application number CN202110367410.X, the patent includes a central processing platform, working condition information acquisition equipment and disaster emergency response equipment. The central processing platform specifically includes: a rehearsal unit, a risk detection unit, an operation control unit and a processing solution generation unit; the working condition information acquisition equipment specifically includes: a regional image acquisition unit and a frequency control unit; the disaster emergency response equipment specifically includes: an on-site parameter acquisition unit, a command sending unit and a parameter sending unit.
[0004] The above patent uses electronic equipment to complete everything from fire prevention to the formulation of fire handling plans, which effectively reduces the workload of managers and reduces safety hazards caused by staff negligence or tension. However, some existing fire warning systems still use single data analysis for fire warning when in use. Due to the limitations of single data analysis, the warning may be inaccurate and untimely. Summary of the invention
[0005] In view of the shortcomings of the prior art, the present invention provides a fire warning system based on multi-dimensional data linkage, which solves the problem that the single data analysis warning has limitations and causes inaccurate and untimely warnings.
[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a fire warning system based on multi-dimensional data linkage, including: a multi-dimensional data acquisition terminal, an equipment data monitoring terminal, a crowd data monitoring terminal, a fire warning analysis terminal and a monitoring information output terminal.
[0007] The multi-dimensional data acquisition terminal is used to acquire the equipment parameters and personnel parameters of the preset target area, wherein the equipment parameters are acquired through the historical maintenance records of the equipment, and the personnel parameters are acquired through the set monitoring. The specific equipment parameters include: maintenance time and repair items, and the personnel parameters include: flow of people. Then the acquired equipment parameters and personnel parameters are transmitted separately, and the preset target area can be a work area, park, shopping mall or residential building, etc. The specific selection of the target area is set by the operator.
[0008] The equipment data monitoring terminal is used to obtain the transmitted equipment parameters, and the transmitted equipment parameters are the equipment parameters in the target area. According to the equipment parameters, the equipment in the target area is monitored and analyzed for early warning to obtain equipment monitoring information. The equipment monitoring information includes: normal signals and early warning signals. At the same time, the generated equipment monitoring information is transmitted to the monitoring information output terminal. The specific method of generating the equipment monitoring information is as follows:
[0009] S1: Get all the equipment in the target area, and label the equipment as n, where n=1, 2, ..., m. At the same time, determine whether equipment n is under maintenance, and classify equipment n into equipment with maintenance and equipment without maintenance. Then label the two equipments as a and b, respectively, where a=1, 2, ..., k and b=1, 2, ..., h, where a corresponds to equipment with maintenance and b corresponds to equipment without maintenance.
[0010] S2: Then, all the equipment a under maintenance are obtained, and at the same time, the maintenance items corresponding to the equipment a under maintenance are obtained, and the maintenance items can be understood as the maintenance reasons corresponding to the equipment, such as the pressure of the fire extinguisher, and the parameters to be analyzed corresponding to the maintenance items are obtained, and here the pressure data is used as the parameter to be analyzed for illustration, and then the parameters to be analyzed are obtained with time t as a period, and at the same time, the changes of the parameters to be analyzed within time t are obtained, and early warning analysis is performed on the equipment a under maintenance according to the changes, and the specific early warning analysis method is as follows:
[0011] Calculate the change difference of the parameter to be analyzed within time t, and calculate the overall difference mean based on the change difference of the parameter to be analyzed, then compare the difference mean with the preset value, when the difference mean is greater than the preset value, a warning signal is generated, otherwise when the difference mean is less than the preset value, a normal signal is generated, and the specific value of the preset value is determined by the operator according to historical data.
[0012] S3: Obtain all the non-maintenance equipment b, and at the same time obtain the maintenance time corresponding to the non-maintenance equipment b, recorded as Tb. The specific maintenance time Tb is expressed as the time from the current time to the current time. Then obtain the standard time length, recorded as Tz, and compare it with the maintenance time Tb. The specific standard time length is expressed as the prescribed maintenance time interval of the corresponding fire-fighting equipment. The standard time length is obtained according to different fire-fighting equipment. When the maintenance time Tb is greater than the standard time length Tz, an early warning signal is generated. On the contrary, when the maintenance time Tb is less than the standard time length Tz, a normal signal is generated. Specifically, if the maintenance time is greater than the standard time length, it means that the corresponding equipment has not been regularly maintained for a long time, and there may be dangers in use, so a warning signal is generated. On the contrary, it means that the regular maintenance time has not yet arrived.
[0013] The crowd flow data monitoring terminal is used to obtain the transmitted personnel parameters, and classify the target area into different levels according to the personnel parameters to obtain the classification information. At the same time, the personnel flow characteristics of the target area are analyzed in combination with historical data to obtain the flow characteristic information, and then the flow characteristic information is transmitted to the monitoring information output terminal. The specific method of generating the flow characteristic information is:
[0014] Q1: Get the target area and divide it into i functional areas according to its function, where i=1, 2, ..., j. Then get the flow of people corresponding to the functional area i, record it as Ri, and the flow of people is expressed as the total number of people flowing in one day. At the same time, match the obtained flow of people Ri with the grade classification standard, get the flow grade corresponding to the functional area i and get the grade classification information.
[0015] Q2: Then, the personnel flow characteristics are obtained by combining the historical data corresponding to the functional area i. The specific acquisition method is: obtain the flow of people in the functional area i per unit time, integrate the flow of people in the unit time, and divide the functional area i into peak and valley time periods;
[0016] Q3: Then, based on historical data, the number of accidents that occurred during the peak and valley time periods of functional area i is obtained and recorded as C1 i and Ci 2, respectively, where Ci 1 represents the number of accidents that occurred during the peak time period, and Ci2 represents the number of accidents that occurred during the valley time period. Substitute C1 i and C2 i into the formula The flow weight ratio Yi corresponding to the functional area i is calculated and the flow characteristic information is generated.
[0017] The fire warning analysis terminal is used to obtain the transmitted equipment monitoring information and flow characteristic information, and at the same time obtain historical data, and calculate the weight ratio corresponding to the target area according to the equipment monitoring information and flow characteristic information, and then calculate the warning value corresponding to the target area according to the weight ratio combined with historical data, and at the same time monitor the warning value in real time to generate corresponding risk warning information, and transmit the risk warning information to the monitoring information output terminal. The specific method of generating risk warning information is as follows:
[0018] P1: Calculate the time difference corresponding to device n according to the maintenance time and standard time in the equipment monitoring information, record it as TCn, and obtain the maintenance times corresponding to device n, record it as En, and then substitute the obtained data into the formula Calculate and obtain the device weight ratio Dn corresponding to device n;
[0019] P2: Then obtain the flow characteristic information and the equipment weight ratio Dn, and substitute them into the formula The warning value Fi corresponding to the functional area i is calculated, where Hi is the flow of people per unit time corresponding to the functional area, and Ci is the total number of accidents in the functional area; specifically, Hi is obtained through real-time monitoring.
[0020] P3: Compare the calculated warning value Fi with the risk warning comparison value Fy. When Fi ≥ 70% Fy, a risk warning signal is generated, otherwise a normal signal is generated. The risk warning information is generated by combining the two and transmitted to the monitoring information output terminal. The specific value of the risk warning comparison value Fy is set by the operator.
[0021] The present invention provides a fire warning system based on multi-dimensional data linkage. Compared with the prior art, it has the following beneficial effects:
[0022] The present invention analyzes the impact of equipment monitoring data and personnel parameters separately to analyze these factors on the whole, and further integrates the obtained data to perform fire warning for the whole. By analyzing data according to different aspects, the accuracy of data utilization can be guaranteed, and the error in the fire warning process can be further reduced. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION
[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0025] See also Figure 1 The present application provides a fire warning system based on multi-dimensional data linkage, including: a multi-dimensional data acquisition terminal, an equipment data monitoring terminal, a crowd data monitoring terminal, a fire warning analysis terminal and a monitoring information output terminal, and the multi-dimensional data acquisition terminal transmits the acquired data to the crowd data monitoring terminal and the equipment data monitoring terminal, and the three are electrically connected. At the same time, the multi-dimensional data is processed by the crowd data monitoring terminal and the equipment data monitoring terminal, and the processed data is transmitted to the fire warning analysis terminal. Finally, the fire warning analysis terminal performs a final analysis on the data, and transmits the analysis results to the monitoring information output terminal. All of the above units are electrically connected.
[0026] Embodiment 1
[0027] The multi-dimensional data acquisition terminal is used to acquire the equipment parameters and personnel parameters of the preset target area, wherein the equipment parameters are acquired through the historical maintenance records of the equipment, and the personnel parameters are acquired through the set monitoring. The specific equipment parameters include: maintenance time and repair items, and the personnel parameters include: flow of people. Then the acquired equipment parameters and personnel parameters are transmitted separately, and the preset target area can be a work area, park, shopping mall or residential building, etc. The specific selection of the target area is set by the operator.
[0028] The equipment data monitoring terminal is used to obtain the transmitted equipment parameters, and the transmitted equipment parameters are the equipment parameters in the target area. According to the equipment parameters, the equipment in the target area is monitored and analyzed for early warning to obtain equipment monitoring information. The equipment monitoring information includes: normal signals and early warning signals. At the same time, the generated equipment monitoring information is transmitted to the monitoring information output terminal. The specific method of generating the equipment monitoring information is as follows:
[0029] S1: Get all the equipment in the target area, and label the equipment as n, where n=1, 2, ..., m. At the same time, determine whether equipment n is under maintenance, and classify equipment n into equipment with maintenance and equipment without maintenance. Then label the two equipments as a and b, respectively, where a=1, 2, ..., k and b=1, 2, ..., h, where a corresponds to equipment with maintenance and b corresponds to equipment without maintenance.
[0030] S2: Then, all the equipment a under maintenance are obtained, and at the same time, the maintenance items corresponding to the equipment a under maintenance are obtained, and the maintenance items can be understood as the maintenance reasons corresponding to the equipment, such as the pressure of the fire extinguisher, and the parameters to be analyzed corresponding to the maintenance items are obtained, and here the pressure data is used as the parameter to be analyzed for illustration, and then the parameters to be analyzed are obtained with time t as a period, and at the same time, the changes of the parameters to be analyzed within time t are obtained, and early warning analysis is performed on the equipment a under maintenance according to the changes, and the specific early warning analysis method is as follows:
[0031] Calculate the change difference of the parameter to be analyzed within time t, and calculate the overall difference mean based on the change difference of the parameter to be analyzed, then compare the difference mean with the preset value, when the difference mean is greater than the preset value, a warning signal is generated, otherwise when the difference mean is less than the preset value, a normal signal is generated, and the specific value of the preset value is determined by the operator according to historical data.
[0032] Combined with actual analysis, taking pressure parameters as an example, the pressure parameters obtained within time t are 1.1, 1.0, 1.12, 1.03, and 1.07, respectively. Then the difference between two adjacent pressure parameters is calculated as: 0.1, 0.12, 0.09, and 0.04. The final calculated overall mean is 0.0875, and then the preset value 0.1 is obtained. The two are compared, and the overall mean is less than the preset value, so a normal signal is generated.
[0033] S3: Obtain all the non-maintenance equipment b, and at the same time obtain the maintenance time corresponding to the non-maintenance equipment b, recorded as Tb. The specific maintenance time Tb is expressed as the time from the current time to the current time. Then obtain the standard time length, recorded as Tz, and compare it with the maintenance time Tb. The specific standard time length is expressed as the prescribed maintenance time interval of the corresponding fire-fighting equipment. The standard time length is obtained according to different fire-fighting equipment. When the maintenance time Tb is greater than the standard time length Tz, an early warning signal is generated. On the contrary, when the maintenance time Tb is less than the standard time length Tz, a normal signal is generated. Specifically, if the maintenance time is greater than the standard time length, it means that the corresponding equipment has not been regularly maintained for a long time, and there may be dangers in use, so a warning signal is generated. On the contrary, it means that the regular maintenance time has not yet arrived.
[0034] The monitoring information output terminal is used to obtain the transmitted equipment monitoring information and display it to the operator through the display device.
[0035] Embodiment 2: This embodiment is implemented on the basis of embodiment 1, and differs from embodiment 1 in that the multi-dimensional data acquisition terminal transmits the acquired personnel parameters to the crowd flow data monitoring terminal.
[0036] The crowd flow data monitoring terminal is used to obtain the transmitted personnel parameters, and classify the target area into different levels according to the personnel parameters to obtain the classification information. At the same time, the personnel flow characteristics of the target area are analyzed in combination with historical data to obtain the flow characteristic information, and then the flow characteristic information is transmitted to the monitoring information output terminal. The specific method of generating the flow characteristic information is:
[0037] Q1: Get the target area and divide it into i functional areas according to its function, where i=1, 2, ..., j. Then get the flow of people corresponding to the functional area i, record it as Ri, and the flow of people is expressed as the total number of people flowing in one day. At the same time, match the obtained flow of people Ri with the grade classification standard, get the flow grade corresponding to the functional area i and get the grade classification information.
[0038] For example, the flow of people corresponding to functional area i is 500, and there are three levels in the grade classification standard, namely high, medium and low. The flow of people corresponding to the high level is 1000-2000, the flow of people corresponding to the medium level is 400-999, and the flow of people corresponding to the low level is below 400. The current functional area i is in the flow of people corresponding to the medium level, so the level it is located at is medium.
[0039] Q2: Then, the personnel flow characteristics are obtained by combining the historical data corresponding to the functional area i. The specific acquisition method is: obtain the flow of people in the functional area i per unit time, integrate the flow of people in the unit time, and divide the functional area i into peak and valley time periods;
[0040] Q3: Then, based on historical data, the number of accidents that occurred during the peak and valley time periods of functional area i is obtained and recorded as C1 i and Ci 2, respectively, where Ci 1 represents the number of accidents that occurred during the peak time period, and Ci2 represents the number of accidents that occurred during the valley time period. Substitute C1 i and C2 i into the formula The flow weight ratio Yi corresponding to the functional area i is calculated and the flow characteristic information is generated.
[0041] Combined with actual analysis, the passenger flow per unit time of functional area i is expressed as the passenger flow within one hour, and then the passenger flow per unit hour of all days is combined to divide the peak and trough time periods. For example, the peak time periods are 08:00-09:30 and 17:00-19:00, and the trough time period is 21:00-06:00.
[0042] The monitoring information output terminal is used to obtain the transmitted flow characteristic information and display it to the operator through a display device.
[0043] Embodiment 3: This embodiment is implemented on the basis of embodiment 2, and differs from embodiment 2 in that the equipment data monitoring terminal and the human flow data monitoring terminal transmit the generated equipment monitoring information and flow characteristic information to the fire warning analysis terminal.
[0044] The fire warning analysis terminal is used to obtain the transmitted equipment monitoring information and flow characteristic information, and at the same time obtain historical data, and calculate the weight ratio corresponding to the target area according to the equipment monitoring information and flow characteristic information, and then calculate the warning value corresponding to the target area according to the weight ratio combined with historical data, and at the same time monitor the warning value in real time to generate corresponding risk warning information, and transmit the risk warning information to the monitoring information output terminal. The specific method of generating risk warning information is as follows:
[0045] P1: Calculate the time difference corresponding to device n according to the maintenance time and standard time in the equipment monitoring information, record it as TCn, and obtain the maintenance times corresponding to device n, record it as En, and then substitute the obtained data into the formula Calculate and obtain the device weight ratio Dn corresponding to device n;
[0046] P2: Then obtain the flow characteristic information and the equipment weight ratio Dn, and substitute them into the formula The warning value Fi corresponding to the functional area i is calculated, where Hi is the flow of people per unit time corresponding to the functional area, and Ci is the total number of accidents in the functional area; specifically, Hi is obtained through real-time monitoring.
[0047] P3: Compare the calculated warning value Fi with the risk warning comparison value Fy. When Fi ≥ 70% Fy, a risk warning signal is generated, otherwise a normal signal is generated. The risk warning information is generated by combining the two and transmitted to the monitoring information output terminal. The specific value of the risk warning comparison value Fy is set by the operator.
[0048] Embodiment 4, as the fourth embodiment of the present invention, focuses on combining the implementation processes of Embodiment 1, Embodiment 2 and Embodiment 3 for implementation.
[0049] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.
[0050] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.
Claims
1. A fire warning system based on multi-dimensional data linkage, characterized in that: include: The multi-dimensional data acquisition terminal is used to acquire the maintenance time and repair items of the preset target area equipment, and the flow of people in the target area, and transmit the two to the equipment data monitoring terminal and the flow of people data monitoring terminal respectively; The equipment data monitoring terminal is used to obtain the transmitted equipment maintenance time and maintenance items, and classify the equipment into equipment with maintenance and equipment without maintenance, then analyze the parameters to be analyzed corresponding to the maintenance items of the equipment with maintenance to generate equipment monitoring information, analyze the maintenance time corresponding to the equipment without maintenance to generate equipment monitoring information, and transmit the equipment monitoring information to the fire warning analysis terminal; The crowd flow data monitoring terminal is used to obtain the crowd flow in the target area to be transmitted. The personnel parameters divide the target area into different levels to obtain the level division information. At the same time, the personnel flow characteristics of the target area are analyzed in combination with historical data to obtain the flow characteristic information. Then the flow characteristic information is transmitted to the monitoring information output terminal. The specific method of analyzing the level division information to obtain the flow characteristic information is as follows: Q1: Then, the personnel flow characteristics are obtained by combining the historical data corresponding to the functional area i. The specific acquisition method is: obtain the flow of people in the functional area i per unit time, integrate the flow of people in the unit time, and divide the functional area i into peak and valley time periods; Q2: Then, based on historical data, the number of accidents that occurred during the peak and valley time periods of functional area i is obtained and recorded as C1 i and Ci 2, respectively, where Ci 1 represents the number of accidents that occurred during the peak time period and Ci2 represents the number of accidents that occurred during the valley time period. Substitute C1 i and C2 i into the formula Calculate the flow weight ratio Yi corresponding to the functional area i and generate flow characteristic information; The fire warning analysis terminal is used to obtain the transmitted equipment monitoring information and flow characteristic information, and at the same time obtain historical data, and calculate the weight ratio corresponding to the target area according to the equipment monitoring information and flow characteristic information, and then calculate the warning value corresponding to the target area according to the weight ratio combined with historical data, and at the same time monitor the warning value in real time to generate corresponding risk warning information, and transmit the risk warning information to the monitoring information output terminal. The specific method of generating risk warning information is: P1: Calculate the time difference corresponding to device n according to the maintenance time and standard time in the equipment monitoring information, record it as TCn, and obtain the maintenance times corresponding to device n, record it as En, and then substitute the obtained data into the formula Calculate and obtain the device weight ratio Dn corresponding to device n; P2: Then obtain the flow characteristic information and the equipment weight ratio Dn, and substitute them into the formula The warning value Fi corresponding to the functional area i is calculated, where Hi is the flow of people per unit time corresponding to the functional area, and Ci is the total number of accidents in the functional area; P3: Compare the calculated warning value Fi with the risk warning comparison value Fy. When Fi ≥ 70% Fy, a risk warning signal is generated, otherwise a normal signal is generated. The risk warning information is generated by combining the two.
2. The fire warning system based on multi-dimensional data linkage according to claim 1 is characterized in that: The specific way in which the device data monitoring terminal classifies devices is as follows: All the equipment in the target area are obtained, and the equipment is labeled as n, where n=1, 2, ..., m. At the same time, it is determined whether equipment n needs maintenance, and the equipment n is classified into equipment with maintenance and equipment without maintenance. Then the two are labeled as a and b respectively, where a=1, 2, ..., k and b=1, 2, ..., h.
3. The fire warning system based on multi-dimensional data linkage according to claim 1 is characterized in that: The specific method for the equipment data monitoring terminal to analyze the existence of maintenance equipment and the non-existence of maintenance equipment to obtain equipment monitoring information is: S1: Obtain all the equipment a under maintenance, obtain the maintenance items corresponding to the equipment a under maintenance, and obtain the parameters to be analyzed corresponding to the maintenance items, then obtain the parameters to be analyzed with time t as a period, obtain the changes of the parameters to be analyzed within time t, and perform early warning analysis on the equipment a under maintenance according to the changes; S2: Obtain all non-existent maintenance equipment b, and at the same time obtain the maintenance time corresponding to the non-existent maintenance equipment b, record it as Tb, then obtain the standard time length, record it as Tz and compare it with the maintenance time Tb. When the maintenance time Tb is greater than the standard time length Tz, a warning signal is generated. Conversely, when the maintenance time Tb is less than the standard time length Tz, a normal signal is generated.
4. The fire warning system based on multi-dimensional data linkage according to claim 3 is characterized in that: The specific early warning analysis method in S1 is: Calculate the change difference of the parameter to be analyzed within time t, and calculate the overall difference mean based on the change difference of the parameter to be analyzed, then compare the difference mean with the preset value, when the difference mean is greater than the preset value, a warning signal is generated, otherwise when the difference mean is less than the preset value, a normal signal is generated, and the specific value of the preset value is determined by the operator according to historical data.
5. The fire warning system based on multi-dimensional data linkage according to claim 1 is characterized in that: The specific method of classifying the target area by the crowd flow data monitoring terminal is as follows: The target area is obtained and divided into i functional areas according to its function, and i=1, 2, ..., j. Then, the flow of people corresponding to the functional area i is obtained and recorded as Ri. At the same time, the obtained flow of people Ri is matched with the grade classification standard to obtain the flow grade corresponding to the functional area i and obtain the grade classification information.
6. The fire warning system based on multi-dimensional data linkage according to claim 1 is characterized in that: The monitoring information output terminal is used to obtain the transmitted equipment monitoring information, flow characteristic information and risk warning information, and display it to the operator through a display device.