Fire collapse monitoring system based on GNSS-RTK and wireless accelerometer
By using a fire collapse monitoring system based on GNSS-RTK and wireless accelerometer at the fire site, the acceleration data and position information of the building structure are monitored in real time, and the problem of traditional early warning methods is difficult to accurately predict building collapse is achieved, and high-precision collapse warning and safe evacuation are achieved.
Patent Information
- Application Number
- CN202421536822.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-01
- Publication Date
- 2025-04-11
- Estimated Expiration
- 2034-07-01
AI Technical Summary
At the fire scene, traditional structural collapse warning methods are difficult to accurately predict when the building collapses. Especially in complex and dangerous fire scene environments, there is a lack of effective collapse warning methods, which seriously threatens the personal safety of firefighters.
The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer is adopted. Through the wireless accelerometer and RTK module in the test unit, the acceleration data and position information of the building structure are monitored in real time, and the data analysis is used to identify the vibration frequency, damping ratio and vibration mode of the structure, and the status parameters of the monitoring point are displayed in real time.
It improves the positioning accuracy and effectiveness of fire collapse monitoring, reduces the risk time of fire rescue personnel, provides a fast and accurate early warning of structural collapse, helps firefighters to timely understand changes in building structures during the fire, and ensures safe evacuation and rescue.
Smart Images
Figure CN222749033U_ABST
Abstract
Description
Technical Field
[0001] The utility model belongs to the field of fire monitoring, and in particular relates to a fire collapse monitoring system based on GNSS-RTK and a wireless accelerometer. Background Art
[0002] In recent years, the fire situation has become increasingly severe. Fires in large-span and large-space buildings, represented by factories, warehouses, large commercial complexes, and wholesale markets, have occurred frequently, resulting in building collapse accidents that have caused heavy casualties. In addition, when a fire occurs in a building, firefighters need to enter to extinguish the fire and rescue trapped people. Due to the lack of effective collapse warning methods, accidents in which buildings suddenly collapse during the rescue process of firefighters often occur, seriously threatening the personal safety of firefighters. Therefore, how to quickly and accurately warn of structural collapse at the fire rescue site and grasp the timing of internal attack and evacuation has become a major need for fire rescue. To this end, researchers have conducted in-depth research on the collapse mechanism and warning methods of different types of structures during fires, and have achieved many representative results.
[0003] However, fires are often sudden events, and the collapse of structures is not only related to the type of structure, but also to the combustibles and their distribution in the building, the flashover and backdraft of the fire, the way the fire spreads, the weather and climate environment, etc. Although there has been a relatively comprehensive study on the collapse mechanism, mode and influencing factors of various structures during fires, it is difficult to accurately predict when the structure will collapse in an actual building fire, and the traditional structural collapse warning method is also difficult to apply to complex and dangerous fire scenes. Therefore, it is necessary to study a new monitoring method to warn of the collapse of different types of building structures during fires. Utility Model Content
[0004] The utility model aims to provide a fire collapse monitoring system based on GNSS-RTK and wireless accelerometer to improve the above problems.
[0005] In order to solve the above technical problems, the utility model is realized by the following technical solutions:
[0006] A fire collapse monitoring system based on GNSS-RTK and wireless accelerometer includes: a test unit, an RTK base station and a LabVIEW acquisition platform; wherein:
[0007] The test unit includes a sensor protection box, a wireless accelerometer and an RTK module arranged in the sensor protection box; the test unit is fixed on a monitoring point, the wireless accelerometer is used to monitor the acceleration data at the monitoring point, and transmit the acceleration data to the LabVIEW acquisition platform by wireless transmission; the RTK module, as a mobile station, receives satellite signals and communicates with the RTK base station to obtain its own position information, and sends the position information to the LabVIEW acquisition platform;
[0008] The LabVIEW acquisition platform is used to receive acceleration data and position information sent by the test unit located at each monitoring point, and identify the state parameters of the monitoring point by an analysis method based on the acceleration data and position information, and display the state parameters in real time in the form of images.
[0009] Preferably, the sensor protection box is formed by processing non-metallic refractory materials.
[0010] Preferably, the monitoring points are locations of maximum bending moments and nodes of building beams, slabs and columns.
[0011] Preferably, the test unit is installed at each monitoring point in a contactless manner through bonding, mechanical connection or magnetic connection.
[0012] Preferably, the wireless accelerometer utilizes wireless Lora transmission technology to transmit the collected acceleration data to a wireless gateway, and then aggregates the data to a LabVIEW acquisition platform.
[0013] Preferably, the position information is transmitted to the LabVIEW acquisition platform via VISA serial port or DataSocket technology.
[0014] Preferably, the LabVIEW acquisition platform is specifically used for:
[0015] According to the received acceleration data and position information, the power spectrum method, random reduction method, Hilbert-Huang transform method and Ibrahim time domain method are used to identify the vibration frequency, damping ratio and vibration mode of each mode of the steel frame structure at the monitoring point, and display them in real time in the form of images.
[0016] Preferably, the RTK base station subtracts the measured actual coordinates from the known coordinates to obtain the corresponding errors, which are then transmitted to the mobile station for further processing and refinement, ultimately obtaining the precise position information of the mobile station.
[0017] Compared with the prior art, the advantages of the embodiments of the present invention include:
[0018] (1) GNSS-RTK technology has greatly improved positioning accuracy, operating efficiency, stability and other characteristics, and the instrument is easy to operate.
[0019] (2) The dynamic characteristics of key node positions during a building fire are utilized to fully reflect the overall fire resistance limit of the building. Compared with traditional local measurement methods, the effectiveness of fire collapse monitoring is improved.
[0020] (3) The wireless accelerometer and RTK module in the test unit do not require advance wiring, which reduces the time that firefighters spend in danger in actual applications. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] In order to more clearly illustrate the technical solutions of the embodiments of the utility model, the drawings required for describing the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the utility model. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0022] Figure 1 A schematic structural diagram of a fire collapse monitoring system based on GNSS-RTK and wireless accelerometer provided in the first embodiment of the utility model.
[0023] Figure 2 This is a diagram of the working principle of GNSS-RTK.
[0024] Figure 3 This is a flowchart of the data analysis process of the LabVIEW acquisition platform.
[0025] Figure 4 Schematic diagram of the distribution of test units on the test framework.
[0026] Figure 5 This is the front elevation view of the test frame.
[0027] Figure 6 A side elevation view of the test frame.
[0028] Figure 7 Set up schematic diagrams for the fire load. DETAILED DESCRIPTION
[0029] The following will be combined with the drawings in the embodiments of the utility model to clearly and completely describe the technical solutions in the embodiments of the utility model. Obviously, the described embodiments are only part of the embodiments of the utility model, not all of the embodiments. Based on the embodiments of the utility model, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the utility model.
[0030] See also Figure 1 The first embodiment of the utility model provides a fire collapse monitoring system based on GNSS-RTK and wireless accelerometer, which includes: a test unit 10, an RTK base station 20 and a LabVIEW acquisition platform 30; wherein:
[0031] The test unit 10 includes a sensor protection box 11 and a wireless accelerometer 12 and an RTK module 13 disposed in the sensor protection box 11 .
[0032] In this embodiment, the sensor protection box 11 is formed by non-metallic refractory materials, which mainly protects the wireless accelerometer 12 and the RTK module 13. In order to avoid metal shielding of signals, the sensor protection box 11 is formed by non-metallic processing. For example, the sensor protection box 11 can be made of cast stone, graphite, acid-resistant cement, natural acid-resistant stone, glass, etc.
[0033] In this embodiment, the test unit 10 is fixed at a monitoring point, the wireless accelerometer 12 is used to monitor the acceleration data at the monitoring point, and transmit the acceleration data to the LabVIEW acquisition platform 30 by wireless transmission, and the RTK module 13, as a mobile station, receives satellite signals and communicates with the RTK base station 20 to obtain its own precise position information, and sends the position information to the LabVIEW acquisition platform.
[0034] The monitoring points are set according to the building structure type and fire spread, usually at the maximum bending moment and nodes of the building beams, slabs and columns.
[0035] In this embodiment, considering that the monitoring points are usually located in relatively high and hidden places, they can be installed by non-contact methods such as drones. The installation methods include bonding, mechanical connection or magnetic connection, etc., which are not specifically limited in the present invention.
[0036] In this embodiment, the wireless accelerometer 12 uses wireless Lora transmission technology to transmit the collected acceleration data to the wireless gateway, and then aggregates it to the LabVIEW acquisition platform 30.
[0037] The position information generated by the RTK module 13 is transmitted to the LabVIEW acquisition platform 30 via the VISA serial port or DataSocket technology.
[0038] Among them, Figure 2As shown, an RTK device can be installed on the open ground as an RTK base station 20. The RTK base station 20 will subtract the measured actual coordinates from the known coordinates to obtain the corresponding errors, which are then transmitted to the mobile station for further processing and refinement, and finally the accurate position information of the mobile station is obtained. The obtained position information is then transmitted to the LabVIEW acquisition platform via the VISA serial port or DataSocket technology. Since GNSS technology is an existing technology, it will not be introduced in detail this time.
[0039] The LabVIEW acquisition platform 30 is used to receive acceleration data and position information sent by the test unit 10 located at each monitoring point, and identify the state parameters of the monitoring point by analyzing the acceleration data and position information, and display the state parameters in real time in the form of images.
[0040] Specifically, Figure 3 As shown, the LabVIEW acquisition platform 30 uses the power spectrum method, random reduction method, Hilbert-Huang transform method, and Ibrahim time domain method according to the received acceleration data and position information to identify the vibration frequency, damping ratio, and vibration mode of each mode of the steel frame structure at the monitoring point, and displays them in real time in the form of images.
[0041] Compared with the prior art, the advantages of the embodiments of the present invention include:
[0042] (1) GNSS-RTK technology has greatly improved positioning accuracy, operating efficiency, stability and other characteristics, and the instrument is easy to operate.
[0043] (2) The dynamic characteristics of key node positions during a building fire are utilized to fully reflect the overall fire resistance limit of the building. Compared with traditional local measurement methods, the effectiveness of fire collapse monitoring is improved.
[0044] (3) The wireless acceleration sensor and RTK module in the test unit 10 do not need to be wired in advance, which reduces the time that fire rescue personnel are exposed to danger in actual applications.
[0045] To facilitate the understanding of the present invention, a practical example is used below to illustrate the application of the present invention.
[0046] This application intends to monitor and warn of the collapse of a single-story, single-span portal steel frame structure under fire. The overall structure of the test steel frame is a three-frame portal steel frame, and the structure is not fire-protected. The scale ratio of the test frame is 1:4, the structure is 7m long, 3m wide, the eaves height is 1.7m, the ridge height is 2.05m, and the roof slope is 1 / 10. The beams and columns of the structure are all I-beams, and the cross-sectional specifications are all I80×46×3.8×5.2. The component layout of the test frame is shown in Figure 4-Figure 6 .
[0047] This test mainly studies the collapse process of three steel frames. When arranging the force load, vertical loading is carried out by hanging heavy objects to simulate the roof live load of 0.6kN / m2. Figure 7 As shown in the figure, four wood piles of the same size are evenly arranged on the left and right sides with the middle connecting beam as the boundary. In order to make the structure reach a level close to collapse, the selected fire load is 0.9kN / m2 pine wood piles to ensure that the rigid frame beam is fully exposed to fire during the test. Two different fire scenarios were considered. In the first test, the four wood piles on one side were ignited first, and then the four wood piles on the other side were ignited after burning for 2 minutes; in the second test, the four wood piles on both sides were ignited at the same time.
[0048] After the fire test began, drones were used to arrange test modules at nine node areas of the beam and column components (the tops of steel frame columns and the ridges) to simulate real fire scenarios and monitor and warn of the collapse of the steel frame structure. At the same time, a Huace T3 engineering intelligent RTK device was installed on the open ground as an RTK base station.
[0049] After obtaining real-time synchronous three-dimensional acceleration and displacement data, the LabVIEW acquisition platform performs frequency distribution, power spectrum, and mean square error analysis on the data. At the same time, it uses wavelet transform, Ibrahim time domain method, Hilbert-Huang transform method, logarithmic reduction method and other analysis methods based on the random reduction method to determine the main frequency composition, natural frequency, lightness ratio and damping of the system, and displays them in real time in the form of images on the LabVIEW acquisition platform, which is convenient for the fire scene commander to promptly understand the changes in the building structure during the fire, and to establish an early warning system for structural fire collapse.
[0050] The above description is only the preferred embodiment of the utility model, and is not intended to limit the utility model. For those skilled in the art, the utility model can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the utility model shall be included in the protection scope of the utility model.
Claims
1. A fire collapse monitoring system based on GNSS-RTK and wireless accelerometer, characterized in that: include: Test unit, RTK base station and LabVIEW acquisition platform; including: The test unit includes a sensor protection box, a wireless accelerometer and an RTK module arranged in the sensor protection box; the test unit is fixed on a monitoring point, the wireless accelerometer is used to monitor the acceleration data at the monitoring point, and transmit the acceleration data to the LabVIEW acquisition platform by wireless transmission; the RTK module, as a mobile station, receives satellite signals and communicates with the RTK base station to obtain its own position information, and sends the position information to the LabVIEW acquisition platform; The LabVIEW acquisition platform is used to receive acceleration data and position information sent by the test unit located at each monitoring point, and identify the state parameters of the monitoring point by an analysis method based on the acceleration data and position information, and display the state parameters in real time in the form of images.
2. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The sensor protection box is formed by processing non-metallic refractory materials.
3. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The monitoring points are the maximum bending moments and nodes of the building beams, slabs and columns.
4. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The test unit utilizes a contactless method and is installed at each monitoring point by bonding, mechanical connection or magnetic connection.
5. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The wireless accelerometer uses wireless Lora transmission technology to transmit the collected acceleration data to the wireless gateway, and then aggregates it to the LabVIEW acquisition platform.
6. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The position information is transmitted to the LabVIEW acquisition platform via VISA serial port or DataSocket technology.
7. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The LabVIEW acquisition platform is specifically used for: According to the received acceleration data and position information, the power spectrum method, random reduction method, Hilbert-Huang transform method and Ibrahim time domain method are used to identify the vibration frequency, damping ratio and vibration mode of each mode of the steel frame structure at the monitoring point, and display them in real time in the form of images.
8. The fire collapse monitoring system based on GNSS-RTK and wireless accelerometer according to claim 1, characterized in that: The RTK base station subtracts the measured actual coordinates from the known coordinates to obtain the corresponding errors, which are then transmitted to the mobile station for further processing and refinement, ultimately obtaining the precise position information of the mobile station.