A stable identification and early warning method for an aerial platform fire rescue vehicle

Abstract

A kind of climbing platform fire rescue vehicle stable identification early warning method belongs to the technical field of automation instruction early warning, the identification early warning method includes the following steps: multiple distance sensors are arranged at the bottom of the climbing platform fire rescue vehicle, to adjust the driving stroke of multiple hydraulic cylinders in the hydraulic system based on the distance parameter detected by the distance sensor, so that the climbing platform fire rescue vehicle is stably placed at the corresponding rescue position;The rising height of the working platform of the climbing platform fire rescue vehicle is collected, the vibration change parameter of the working platform of the climbing platform fire rescue vehicle is collected, and the driving stroke of the hydraulic cylinder of the climbing platform fire rescue vehicle is combined to form an identification early warning matrix, and the correlation operation of the identification early warning matrix is carried out with the weight coefficient to obtain an identification early warning coefficient;The specific numerical value of the identification early warning coefficient is analyzed and processed, the identification early warning deviation is eliminated, and the overall stability of the climbing platform fire rescue vehicle is determined according to the specific numerical value of the identification early warning coefficient.

Description

Technical Field

[0001] This invention relates to a method for identifying and issuing early warnings about the stability of a fire rescue vehicle operating from an elevated platform. Background Technology

[0002] Aerial platform fire rescue vehicles are special vehicles equipped with aerial booms and fire extinguishing devices for high-altitude fire fighting and rescue. They have a manned platform and a large load-bearing capacity, and the working platform has a relatively high load-bearing capacity, which facilitates fire fighting and rescue work.

[0003] At the structural level, the aerial platform fire rescue vehicle is mainly composed of core components such as chassis, power take-off (PTO), subframe and outriggers, boom system, slewing mechanism, turntable, work platform, electrical control system, hydraulic system, and leveling mechanism. In actual rescue operations, the aerial platform fire rescue vehicle is first fixed in the designated rescue position by the hydraulic system, and then the leveling mechanism and work platform are driven to rise to the designated height under the integrated control of the electrical control system to carry out fire fighting and rescue operations.

[0004] Due to the unique nature of the work of aerial platform fire rescue vehicles, it is necessary to prepare for identification and early warning regarding their overall operational stability. However, most existing identification and early warning methods rely on rescue personnel to conduct on-site observations and control the real-time operational status of the aerial platform fire rescue vehicles in combination with on-site environmental and weather conditions. This method is greatly affected by subjective judgment factors, resulting in biased early warning effects and failing to guarantee the safety and reliability of rescue operations. Summary of the Invention

[0005] This invention provides a stability identification and early warning method for aerial platform fire rescue vehicles. The method features a rational structural design and integrates multiple correlation coefficients during firefighting and rescue operations. It monitors and provides real-time feedback on parameters such as the platform's elevation, hydraulic system drive stroke, and platform vibration changes, forming an identification and early warning matrix to accurately identify and understand the real-time operating status of the aerial platform fire rescue vehicle. This avoids the influence of subjective judgment by rescue personnel. If the aerial platform fire rescue vehicle experiences significant swaying or other instability due to weather or environmental conditions during actual operation, it can provide timely early warning feedback, halting firefighting and rescue operations. This eliminates identification and early warning deviations, ensuring the safety and reliability of actual firefighting and rescue work, and solves the problems existing in the prior art.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows: A method for identifying and warning of the stability of a fire rescue vehicle on an elevated platform, the method comprising the following steps: S1, Multiple distance sensors are installed at the bottom of the aerial platform fire rescue vehicle. The distance sensors are arranged in an array to detect the flatness of the corresponding rescue position of the aerial platform fire rescue vehicle. Based on the distance parameters detected by the distance sensors, the drive stroke of multiple hydraulic cylinders in the hydraulic system is adjusted so that the aerial platform fire rescue vehicle is stably placed at the corresponding rescue position. S2 collects the lifting height of the working platform of the aerial platform fire rescue vehicle and the vibration change parameters of the working platform. These parameters, combined with the drive stroke of the hydraulic cylinders of the aerial platform fire rescue vehicle, constitute the identification and early warning matrix A, defined as: A = (H, S, L) Where H is the rising height of the working platform of the aerial platform fire rescue vehicle, S is the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and L is the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. Specifically, L = (l1, l2, l3, ..., l n ) Among them, l n This refers to the specific drive stroke of the nth hydraulic cylinder; S3, perform correlation calculation on the identification and early warning matrix A in conjunction with the weighting coefficients to obtain the identification and early warning coefficients, defined as: Q = ( (β,γ)(H,S,L) Where Q is the identification and warning coefficient. β is the weighting coefficient corresponding to the lifting height of the working platform of the aerial platform fire rescue vehicle, β is the weighting coefficient corresponding to the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and γ is the weighting coefficient corresponding to the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. S4 analyzes and processes the specific values ​​of the identification and warning coefficients to eliminate identification and warning deviations. Based on the specific values ​​of the identification and warning coefficients, it determines the overall stability of the aerial platform fire rescue vehicle, thereby ensuring the safety and reliability of the aerial platform fire rescue vehicle in actual fire fighting and rescue operations.

[0007] The distance sensors consist of eight units arranged in a 3-2-3 array. During the process of detecting the flatness of the corresponding rescue location on the aerial platform fire rescue vehicle, the position coordinates and corresponding distance parameters of each distance sensor are recorded, forming the set of drive stroke settings for the hydraulic cylinders of the aerial platform fire rescue vehicle. F(L) = [(x n y n )→d n ] Among them, (x n y n Let d be the position coordinates of the nth distance sensor. nFor the corresponding distance parameters obtained from detection, F() is a set of correlation operations, and → is a correlation mapping to map the detected distance parameters to the distance sensors one by one; The aerial platform fire rescue vehicle has six hydraulic cylinders, which are evenly distributed on the vehicle. The drive stroke of each hydraulic cylinder is set with reference to the distance parameters detected by at least three distance sensors around it.

[0008] The process of collecting the lifting height of the working platform of the aerial platform fire rescue vehicle, collecting vibration change parameters of the working platform, and combining these with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle to construct the identification and early warning matrix A includes the following steps: S2.1, During the ascent of the working platform of the aerial platform fire rescue vehicle, multiple time points are set, and the ascent height h of the working platform is collected at each time point. n The rising height H of the working platform of the fire rescue vehicle on the elevated platform is obtained by collecting data. S2.2, Vibration sensors and anemometers are installed on the working platform of the aerial platform fire rescue vehicle. Vibration coefficient and wind speed parameters are detected and fed back in sequence according to time nodes, and then the vibration change parameter S of the working platform of the aerial platform fire rescue vehicle is obtained. S2.3, combined with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle obtained through correlation calculation, constitutes the identification and early warning matrix A.

[0009] The steps involved in performing correlation calculations on the identification and early warning matrix A using weighted coefficients to obtain the identification and early warning coefficients are as follows: S3.1, a dynamic function is used to calculate the weighting coefficients so as to assign different values ​​to the weighting coefficients according to the actual environmental conditions and weather conditions; S3.2, set thresholds for different weighting coefficients to avoid excessively large weighting coefficients; set standard values ​​H0, S0 and L0 for the rise height, vibration change parameter and drive stroke respectively; S3.3, the different weighting coefficients are calculated corresponding to the rise height, vibration change parameters, and drive stroke, and then compared with the above standard values ​​to obtain the identification and warning coefficient, i.e.: Q = ( H / H0, βS / S0, γL / L0); S3.4, preprocess the identification and warning coefficients to remove information data with large deviations.

[0010] The weighting coefficient is used to divide the total amount of overall stability identification and assessment of the aerial platform fire rescue vehicle into rise height component, vibration change parameter component and drive stroke component, so as to accurately identify the overall stability of the aerial platform fire rescue vehicle from three component levels.

[0011] The dynamic function is: G ( ) = T(0,1)| -λ|+(1- s(0,1))| -λ| G(β)=T(0,1)|β-λ|+(1- s(0,1))|β-λ| G(γ)=T(0,1)|γ-λ|+(1- s(0,1))|γ-λ| Where T(0,1) is a binary dynamic deviation model, and the closer the weight coefficient is to the actual application requirements, the closer the value is to 1; λ is the reference value of the weight coefficient, which can be set according to the actual application requirements, and its value range is (0.4, 0.75).

[0012] Analyzing and processing the specific values ​​of the identification and warning coefficients to eliminate identification and warning bias includes the following steps: S4.1, set the iterative operation function to continuously calculate the identification warning coefficient to adapt to the continuous working process of fire fighting and rescue operations; S4.2, after multiple iterations, the final identification and warning coefficient is obtained, and the overall stability of the aerial platform fire rescue vehicle is determined based on the final identification and warning coefficient; S4.3 sets the maximum threshold for the lifting height, vibration change parameter, and hydraulic cylinder drive stroke of the aerial platform fire rescue vehicle's working platform. When any one of these components exceeds the maximum threshold, the final identification warning coefficient fluctuates significantly, indicating that the stability of the aerial platform fire rescue vehicle is too low and does not meet the conditions for fire fighting and rescue operations. Fire fighting and rescue operations must be stopped immediately.

[0013] The iterative operation function is:

[0014] Among them, Q n Q is the current identification and warning coefficient. n+1 H is the identification and warning coefficient for one iteration of the calculation. n S represents the ascent height of the work platform corresponding to the current identification and warning coefficient. n L is the vibration change parameter of the working platform corresponding to the current identification warning coefficient. n The current identification warning coefficient corresponds to the hydraulic cylinder drive stroke; k1, k2, and k3 are optimization operation constants.

[0015] The number of iterations is no more than 5, and can be set to correspond to the time nodes; the value range of the optimization operation constant is (0.2, 0.7).

[0016] This invention employs the aforementioned structure, using an array of distance sensors to detect the flatness of the corresponding rescue position of the aerial platform fire rescue vehicle. Based on the distance parameters obtained from the sensors, the drive stroke of multiple hydraulic cylinders within the hydraulic system is adjusted to ensure the aerial platform fire rescue vehicle is stably placed at the corresponding rescue position. By collecting the rising height and vibration variation parameters of the aerial platform fire rescue vehicle's working platform, combined with the drive stroke of the hydraulic cylinders, an identification and early warning matrix is ​​constructed for stability analysis. By analyzing and processing the specific values ​​of the identification and early warning coefficients, identification and early warning deviations are eliminated, thereby ensuring the safety and reliability of the aerial platform fire rescue vehicle in actual firefighting and rescue operations. It possesses the advantages of safety, reliability, accuracy, and practicality. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the process of the present invention.

[0018] Figure 2 This is a schematic diagram of the array-type distribution structure of the distance sensor of the present invention.

[0019] Figure 3 This is a schematic diagram of the operation of the distance sensor of the present invention.

[0020] Figure 4 This is a schematic diagram illustrating the calculation of the drive stroke of the present invention.

[0021] Figure 5 This is a schematic diagram illustrating the calculation of vibration change parameters in this invention.

[0022] In the diagram, 1 is a distance sensor, and 2 is a hydraulic cylinder. Detailed Implementation

[0023] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific implementation methods and in conjunction with the accompanying drawings.

[0024] like Figure 1-5 As shown, a method for identifying and warning of the stability of a fire rescue vehicle on an elevated platform includes the following steps: S1, Multiple distance sensors are installed at the bottom of the aerial platform fire rescue vehicle. The distance sensors are arranged in an array to detect the flatness of the corresponding rescue position of the aerial platform fire rescue vehicle. Based on the distance parameters detected by the distance sensors, the drive stroke of multiple hydraulic cylinders in the hydraulic system is adjusted so that the aerial platform fire rescue vehicle is stably placed at the corresponding rescue position. S2 collects the lifting height of the working platform of the aerial platform fire rescue vehicle and the vibration change parameters of the working platform. These parameters, combined with the drive stroke of the hydraulic cylinders of the aerial platform fire rescue vehicle, constitute the identification and early warning matrix A, defined as: A = (H, S, L) Where H is the rising height of the working platform of the aerial platform fire rescue vehicle, S is the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and L is the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. Specifically, L = (l1, l2, l3, ..., l n ) Among them, l n This refers to the specific drive stroke of the nth hydraulic cylinder; S3, perform correlation calculation on the identification and early warning matrix A in conjunction with the weighting coefficients to obtain the identification and early warning coefficients, defined as: Q = ( (β,γ)(H,S,L) Where Q is the identification and warning coefficient. β is the weighting coefficient corresponding to the lifting height of the working platform of the aerial platform fire rescue vehicle, β is the weighting coefficient corresponding to the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and γ is the weighting coefficient corresponding to the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. S4 analyzes and processes the specific values ​​of the identification and warning coefficients to eliminate identification and warning deviations. Based on the specific values ​​of the identification and warning coefficients, it determines the overall stability of the aerial platform fire rescue vehicle, thereby ensuring the safety and reliability of the aerial platform fire rescue vehicle in actual fire fighting and rescue operations.

[0025] The distance sensors consist of eight units arranged in a 3-2-3 array. During the process of detecting the flatness of the corresponding rescue location on the aerial platform fire rescue vehicle, the position coordinates and corresponding distance parameters of each distance sensor are recorded, forming the set of drive stroke settings for the hydraulic cylinders of the aerial platform fire rescue vehicle. F(L) = [(x n y n )→d n ] Among them, (x n y n Let d be the position coordinates of the nth distance sensor. n For the corresponding distance parameters obtained from detection, F() is a set of correlation operations, and → is a correlation mapping to map the detected distance parameters to the distance sensors one by one; The aerial platform fire rescue vehicle has six hydraulic cylinders, which are evenly distributed on the vehicle. The drive stroke of each hydraulic cylinder is set with reference to the distance parameters detected by at least three distance sensors around it.

[0026] The process of collecting the lifting height of the working platform of the aerial platform fire rescue vehicle, collecting vibration change parameters of the working platform, and combining these with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle to construct the identification and early warning matrix A includes the following steps: S2.1, During the ascent of the working platform of the aerial platform fire rescue vehicle, multiple time points are set, and the ascent height h of the working platform is collected at each time point. n The rising height H of the working platform of the fire rescue vehicle on the elevated platform is obtained by collecting data. S2.2, Vibration sensors and anemometers are installed on the working platform of the aerial platform fire rescue vehicle. Vibration coefficient and wind speed parameters are detected and fed back in sequence according to time nodes, and then the vibration change parameter S of the working platform of the aerial platform fire rescue vehicle is obtained. S2.3, combined with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle obtained through correlation calculation, constitutes the identification and early warning matrix A.

[0027] The steps involved in performing correlation calculations on the identification and early warning matrix A using weighted coefficients to obtain the identification and early warning coefficients are as follows: S3.1, a dynamic function is used to calculate the weighting coefficients so as to assign different values ​​to the weighting coefficients according to the actual environmental conditions and weather conditions; S3.2, set thresholds for different weighting coefficients to avoid excessively large weighting coefficients; set standard values ​​H0, S0 and L0 for the rise height, vibration change parameter and drive stroke respectively; S3.3, the different weighting coefficients are calculated corresponding to the rise height, vibration change parameters, and drive stroke, and then compared with the above standard values ​​to obtain the identification and warning coefficient, i.e.: Q = ( H / H0, βS / S0, γL / L0); S3.4, preprocess the identification and warning coefficients to remove information data with large deviations.

[0028] The weighting coefficient is used to divide the total amount of overall stability identification and assessment of the aerial platform fire rescue vehicle into rise height component, vibration change parameter component and drive stroke component, so as to accurately identify the overall stability of the aerial platform fire rescue vehicle from three component levels.

[0029] The dynamic function is: G ( ) = T(0,1)| -λ|+(1- s(0,1))| -λ| G(β)=T(0,1)|β-λ|+(1- s(0,1))|β-λ| G(γ)=T(0,1)|γ-λ|+(1- s(0,1))|γ-λ| Where T(0,1) is a binary dynamic deviation model, and the closer the weight coefficient is to the actual application requirements, the closer the value is to 1; λ is the reference value of the weight coefficient, which can be set according to the actual application requirements, and its value range is (0.4, 0.75).

[0030] Analyzing and processing the specific values ​​of the identification and warning coefficients to eliminate identification and warning bias includes the following steps: S4.1, set the iterative operation function to continuously calculate the identification warning coefficient to adapt to the continuous working process of fire fighting and rescue operations; S4.2, after multiple iterations, the final identification and warning coefficient is obtained, and the overall stability of the aerial platform fire rescue vehicle is determined based on the final identification and warning coefficient; S4.3 sets the maximum threshold for the lifting height, vibration change parameter, and hydraulic cylinder drive stroke of the aerial platform fire rescue vehicle's working platform. When any one of these components exceeds the maximum threshold, the final identification warning coefficient fluctuates significantly, indicating that the stability of the aerial platform fire rescue vehicle is too low and does not meet the conditions for fire fighting and rescue operations. Fire fighting and rescue operations must be stopped immediately.

[0031] The iterative operation function is:

[0032] Among them, Q n Q is the current identification and warning coefficient. n+1 H is the identification and warning coefficient for one iteration of the calculation. n S represents the ascent height of the work platform corresponding to the current identification and warning coefficient. n L is the vibration change parameter of the working platform corresponding to the current identification warning coefficient. n The current identification warning coefficient corresponds to the hydraulic cylinder drive stroke; k1, k2, and k3 are optimization operation constants.

[0033] The number of iterations is no more than 5, and can be set to correspond to the time nodes; the value range of the optimization operation constant is (0.2, 0.7).

[0034] The working principle of the stability identification and early warning method for a high-altitude platform fire rescue vehicle in this embodiment of the invention is as follows: During the fire fighting and rescue operation of the high-altitude platform fire rescue vehicle, multiple types of correlation coefficients are integrated to detect and provide feedback on the rising height of the working platform, the driving stroke of the hydraulic system, and the vibration change parameters of the working platform in real time. This forms an identification and early warning matrix to accurately identify and grasp the real-time working status of the high-altitude platform fire rescue vehicle, avoiding the influence of subjective judgment by rescue personnel. Once the high-altitude platform fire rescue vehicle experiences significant shaking or other instability due to weather or environmental conditions during actual operation, an early warning can be issued in a timely manner to stop the fire fighting and rescue operation, thereby eliminating identification and early warning deviations and ensuring the safety and reliability of actual fire fighting and rescue work.

[0035] The core innovation of this invention lies in the acquisition, calculation, and analysis of the identification and early warning coefficients. Since the subjective nature of on-site observation by rescue personnel accounts for a large proportion, existing identification and early warning methods are prone to deviation and cannot meet the requirements for the stable and safe fire fighting and rescue operations of aerial platform fire rescue vehicles. Therefore, this invention adopts accurate and specific numerical analysis and calculation to determine the stability of the aerial platform fire rescue vehicle based on the specific fluctuation of the coefficients.

[0036] In the overall solution, the identification and early warning method includes the following steps: Multiple distance sensors are installed at the bottom of the aerial platform fire rescue vehicle. These sensors are arranged in an array to detect the flatness of the corresponding rescue position. The drive stroke of multiple hydraulic cylinders in the hydraulic system is adjusted based on the distance parameters detected by the distance sensors, so that the aerial platform fire rescue vehicle can be stably placed at the corresponding rescue position. The rising height of the working platform of the aerial platform fire rescue vehicle and the vibration change parameters of the working platform are collected. These parameters, combined with the drive stroke of the hydraulic cylinders of the aerial platform fire rescue vehicle, constitute the identification and early warning matrix A, defined as follows: A = (H, S, L) Where H is the rising height of the working platform of the aerial platform fire rescue vehicle, S is the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and L is the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. Specifically, L = (l1, l2, l3, ..., l n ) Among them, l n This refers to the specific drive stroke of the nth hydraulic cylinder; By combining the weighting coefficients with the correlation calculation of the identification and early warning matrix A, the identification and early warning coefficients are obtained, defined as: Q = ( (β,γ)(H,S,L) Where Q is the identification and warning coefficient. β is the weighting coefficient corresponding to the lifting height of the working platform of the aerial platform fire rescue vehicle, β is the weighting coefficient corresponding to the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and γ is the weighting coefficient corresponding to the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. The specific values ​​of the identification and warning coefficients are analyzed and processed to eliminate identification and warning deviations. The overall stability of the aerial platform fire rescue vehicle is determined based on the specific values ​​of the identification and warning coefficients, thereby ensuring the safety and reliability of the aerial platform fire rescue vehicle in actual fire fighting and rescue operations.

[0037] There are eight distance sensors arranged in a 3-2-3 array. During the process of detecting the flatness of the corresponding rescue location on the aerial platform fire rescue vehicle, the position coordinates and corresponding distance parameters of each distance sensor are recorded. This data forms the set of drive stroke settings for the hydraulic cylinders of the aerial platform fire rescue vehicle. F(L) = [(x n y n )→d n ] Among them, (x n y n Let d be the position coordinates of the nth distance sensor. n For the corresponding distance parameters obtained from detection, F() is a set of correlation operations, and → is a correlation mapping to map the detected distance parameters to the distance sensors one by one; The hydraulic cylinders of the aerial platform fire rescue vehicle consist of 6 cylinders, which are evenly distributed on the vehicle. The drive stroke of each hydraulic cylinder is set with reference to the distance parameters detected by at least 3 distance sensors around it.

[0038] For the correlation calculation between distance sensors and hydraulic cylinder drive stroke, generally, the drive stroke setting of a hydraulic cylinder should refer to the distance parameters detected by at least three distance sensors around it. By using the correlation and consistency calculation of the coordinate position and distance parameters of the drive stroke setting set, comprehensive data can be collected to obtain the actual flatness of the rescue position of the aerial platform fire rescue vehicle. Then, the drive stroke of each hydraulic cylinder can be set according to the actual flatness, so that the aerial platform fire rescue vehicle is stably placed in the corresponding rescue position without horizontal deviation or vertical floating. Since the drive stroke of the hydraulic cylinder is set by the distance parameters detected by the surrounding distance sensors, after setting the drive stroke of each hydraulic cylinder in the overall macroscopic way, it is also necessary to fine-tune and correct the drive stroke of the hydraulic cylinder in the local fine details according to the detected distance parameters to form a complete control drive closed loop, which is closer to the actual application scenario and further ensures the overall stability of the aerial platform fire rescue vehicle at the rescue position.

[0039] Preferably, the identification and early warning matrix A is constructed by collecting the lifting height of the working platform of the aerial platform fire rescue vehicle, collecting the vibration change parameters of the working platform of the aerial platform fire rescue vehicle, and combining them with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. The steps include: Multiple time points were set during the ascent of the working platform of the aerial platform fire rescue vehicle, and the ascent height h of the working platform was collected at each time point. n The rising height H of the working platform of the fire rescue vehicle on the elevated platform is obtained by collecting data. Vibration sensors and anemometers are installed on the working platform of the aerial platform fire rescue vehicle. Vibration coefficient and wind speed parameters are detected and fed back in sequence according to time nodes, and then the vibration change parameter S of the working platform of the aerial platform fire rescue vehicle is obtained. The identification and early warning matrix A is formed by combining the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle obtained through correlation calculation.

[0040] Based on the time nodes and the changing trends of the corresponding coefficient parameters, the specific working conditions can also be analyzed. Once an anomaly occurs, the corresponding detection parameters will show sudden changes and large fluctuations.

[0041] In this invention, it is necessary to obtain as many correlation coefficients as possible for multiple categories of operations in order to accurately reflect the specific progress of fire fighting and rescue operations. Therefore, the identification and early warning matrix constructed in this invention covers a variety of different correlation coefficients.

[0042] Preferably, the process of performing correlation calculations on the identification and early warning matrix A in conjunction with weighting coefficients to obtain the identification and early warning coefficients includes the following steps: A dynamic function is used to calculate the weighting coefficients, so that different values ​​are assigned to the weighting coefficients according to the actual environmental and weather conditions; Thresholds are set for different weighting coefficients to avoid excessively large weighting coefficients; standard values ​​H0, S0, and L0 are set for the rise height, vibration change parameter, and drive stroke, respectively. Different weighting coefficients are calculated in relation to the lift height, vibration variation parameters, and drive stroke, and then compared with the aforementioned standard values ​​to obtain the identification and warning coefficient, i.e.: Q = ( H / H0, βS / S0, γL / L0); The identification and early warning coefficients are preprocessed to remove information data with large deviations.

[0043] In this invention, the weighting coefficient is used to divide the total amount of overall stability identification and assessment of the aerial platform fire rescue vehicle into the rising height component, the vibration change parameter component, and the driving stroke component, so as to accurately identify the overall stability of the aerial platform fire rescue vehicle from three component levels; therefore, the specific value of the weighting coefficient can be set according to the time application scenario, and the specific calculation ratio of each component can be flexibly adjusted.

[0044] Furthermore, the dynamic function is: G ( ) = T(0,1)| -λ|+(1- s(0,1))| -λ| G(β)=T(0,1)|β-λ|+(1- s(0,1))|β-λ| G(γ)=T(0,1)|γ-λ|+(1- s(0,1))|γ-λ| Where T(0,1) is a binary dynamic deviation model, and the closer the weight coefficient is to the actual application requirements, the closer the value is to 1; λ is the reference value of the weight coefficient, which can be set according to the actual application requirements, and its value range is (0.4, 0.75).

[0045] Generally, introducing reference values ​​for weighting coefficients can ensure that each weighting coefficient does not have a large calculation deviation, thus guaranteeing the smooth progress of subsequent calculations.

[0046] In this invention, the core technical feature is the analysis and processing of the identification and early warning coefficient, which specifically includes the following steps: An iterative calculation function is set to continuously calculate the identification warning coefficient to adapt to the continuous working process of fire fighting and rescue operations; After multiple iterative calculations, the final identification and warning coefficient is obtained, and the overall stability of the aerial platform fire rescue vehicle is determined based on the final identification and warning coefficient. The maximum thresholds for the lifting height of the working platform of the aerial platform fire rescue vehicle, the vibration change parameter, and the hydraulic cylinder drive stroke are set respectively. When any one of these components exceeds the maximum threshold, the final identification warning coefficient fluctuates significantly, indicating that the stability of the aerial platform fire rescue vehicle is too low and does not meet the conditions for fire fighting and rescue operations. Fire fighting and rescue operations must be stopped immediately.

[0047] Furthermore, the iterative operation function is:

[0048] Among them, Q n Q is the current identification and warning coefficient. n+1 H is the identification and warning coefficient for one iteration of the calculation. n S represents the ascent height of the work platform corresponding to the current identification and warning coefficient.n L is the vibration change parameter of the working platform corresponding to the current identification warning coefficient. n The current identification warning coefficient corresponds to the hydraulic cylinder drive stroke; k1, k2, and k3 are optimization operation constants.

[0049] In actual calculations, the number of iterations should not exceed 5, which can be set according to the time nodes. The value of the optimization operation constant should be assigned within the range of (0.2, 0.7) to obtain more accurate calculation values.

[0050] It should be noted that the identification and early warning method of the present invention is designed for the continuous workflow of fire fighting and rescue operations. Therefore, the dynamic analysis and calculation method can stop the operation at any time in case of an emergency, further improving the overall stability and safety of fire fighting and rescue operations of the aerial platform fire rescue vehicle.

[0051] In summary, the stability identification and early warning method for aerial platform fire rescue vehicles in this embodiment of the invention integrates multiple types of correlation coefficients during firefighting and rescue operations. It performs real-time detection and feedback on parameters such as the lifting height of the working platform, the hydraulic system drive stroke, and the vibration changes of the working platform, forming an identification and early warning matrix to accurately identify and grasp the real-time working status of the aerial platform fire rescue vehicle. This avoids the influence of subjective judgment by rescue personnel. If the aerial platform fire rescue vehicle experiences significant swaying or other instability due to weather or environmental conditions during actual operation, it can provide timely early warning feedback, halting firefighting and rescue operations. This eliminates identification and early warning deviations, ensuring the safety and reliability of actual firefighting and rescue work.

[0052] The above specific embodiments should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, any alternative improvements or modifications made to the embodiments of the present invention shall fall within the scope of protection of the present invention.

[0053] Any aspects of this invention not described in detail are well-known to those skilled in the art.

Claims

1. A method for identifying and issuing early warnings about the stability of a fire rescue vehicle operating from an elevated platform, characterized in that, The identification and early warning method Includes the following steps: S1, Multiple distance sensors are installed at the bottom of the aerial platform fire rescue vehicle. The distance sensors are arranged in an array to detect the flatness of the corresponding rescue position of the aerial platform fire rescue vehicle. Based on the distance parameters detected by the distance sensors, the drive stroke of multiple hydraulic cylinders in the hydraulic system is adjusted so that the aerial platform fire rescue vehicle is stably placed at the corresponding rescue position. S2 collects the lifting height of the working platform of the aerial platform fire rescue vehicle and the vibration change parameters of the working platform. These parameters, combined with the drive stroke of the hydraulic cylinders of the aerial platform fire rescue vehicle, constitute the identification and early warning matrix A, defined as: A = (H, S, L) Where H is the rising height of the working platform of the aerial platform fire rescue vehicle, S is the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and L is the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. Specifically, L = (l1, l2, l3, ..., l n ) Among them, l n This refers to the specific drive stroke of the nth hydraulic cylinder; S3, perform correlation calculation on the identification and early warning matrix A using the weighting coefficients to obtain the identification and early warning coefficients, defined as: Q=( , b, c) (H, S, L) Where Q is the identification and warning coefficient. β is the weighting coefficient corresponding to the lifting height of the working platform of the aerial platform fire rescue vehicle, β is the weighting coefficient corresponding to the vibration change parameter of the working platform of the aerial platform fire rescue vehicle, and γ is the weighting coefficient corresponding to the driving stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle. S4 analyzes and processes the specific values ​​of the identification and warning coefficients to eliminate identification and warning deviations. Based on the specific values ​​of the identification and warning coefficients, it determines the overall stability of the aerial platform fire rescue vehicle, thereby ensuring the safety and reliability of the aerial platform fire rescue vehicle in actual fire fighting and rescue operations.

2. The stability identification and early warning method for a fire rescue vehicle on an elevated platform according to claim 1, characterized in that: The distance sensors consist of eight units arranged in a "3-2-3" array. During the process of detecting the flatness of the corresponding rescue location on the aerial platform fire rescue vehicle, the position coordinates and corresponding distance parameters of each distance sensor are recorded, forming the set of drive stroke settings for the hydraulic cylinders of the aerial platform fire rescue vehicle. F(L)=[(x n ,y n )→d n ] Among them, (x n y n Let d be the position coordinates of the nth distance sensor. n For the corresponding distance parameters obtained from detection, F() is a set of correlation operations, and → is a correlation mapping to map the detected distance parameters to the distance sensors one by one; The aerial platform fire rescue vehicle has six hydraulic cylinders, which are evenly distributed on the vehicle. The drive stroke of each hydraulic cylinder is set with reference to the distance parameters detected by at least three distance sensors around it.

3. The method for stability identification and early warning of a fire rescue vehicle on an elevated platform according to claim 2, characterized in that, The process of collecting the lifting height of the working platform of the aerial platform fire rescue vehicle, collecting vibration change parameters of the working platform, and combining these with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle to construct the identification and early warning matrix A includes the following steps: S2.1, During the ascent of the working platform of the aerial platform fire rescue vehicle, multiple time points are set, and the ascent height h of the working platform is collected at each time point. n The rising height H of the working platform of the fire rescue vehicle on the elevated platform is obtained by collecting data. S2.2, Vibration sensors and anemometers are installed on the working platform of the aerial platform fire rescue vehicle. Vibration coefficient and wind speed parameters are detected and fed back in sequence according to time nodes, and then the vibration change parameter S of the working platform of the aerial platform fire rescue vehicle is obtained. S2.3, combined with the drive stroke of the hydraulic cylinder of the aerial platform fire rescue vehicle obtained through correlation calculation, constitutes the identification and early warning matrix A.

4. The method for stability identification and early warning of a fire rescue vehicle on an elevated platform according to claim 1, characterized in that, The steps involved in performing correlation calculations on the identification and early warning matrix A using weighted coefficients to obtain the identification and early warning coefficients are as follows: S3.1, a dynamic function is used to calculate the weighting coefficients so as to assign different values ​​to the weighting coefficients according to the actual environmental conditions and weather conditions; S3.2, set thresholds for different weighting coefficients to avoid excessively large weighting coefficients; set standard values ​​H0, S0 and L0 for the rise height, vibration change parameter and drive stroke respectively; S3.3, the different weighting coefficients are calculated corresponding to the rise height, vibration change parameters, and drive stroke, and then compared with the above standard values ​​to obtain the identification and warning coefficient, i.e.: Q=( H / H0,βS / S0,γL / L0); S3.4 preprocesses the identification and warning coefficients to remove information data with large deviations.

5. The stability identification and early warning method for a fire rescue vehicle on an elevated platform according to claim 4, characterized in that: The weighting coefficient is used to divide the total amount of overall stability identification and assessment of the aerial platform fire rescue vehicle into rise height component, vibration change parameter component and drive stroke component, so as to accurately identify the overall stability of the aerial platform fire rescue vehicle from three component levels.

6. The stability identification and early warning method for a fire rescue vehicle on an elevated platform according to claim 4, characterized in that: The dynamic function is: G( )=T(0,1)| -λ|+(1- s(0,1))| -l| G(β)=T(0,1)|β-λ|+(1- s(0,1))|β-λ| G(γ)=T(0,1)|γ-λ|+(1- s(0,1))|γ-λ| Where T(0,1) is a binary dynamic deviation model, and the closer the weight coefficient is to the actual application requirements, the closer the value is to 1; λ is the reference value of the weight coefficient, which can be set according to the actual application requirements, and its value range is (0.4, 0.75).

7. The method for stability identification and early warning of a fire rescue vehicle on an elevated platform according to claim 1, characterized in that, Analyzing and processing the specific values ​​of the identification and warning coefficients to eliminate identification and warning bias includes the following steps: S4.1, set the iterative operation function to continuously calculate the identification warning coefficient to adapt to the continuous working process of fire fighting and rescue operations; S4.2, after multiple iterations, the final identification and warning coefficient is obtained, and the overall stability of the aerial platform fire rescue vehicle is determined based on the final identification and warning coefficient; S4.3 sets the maximum threshold for the lifting height, vibration change parameter, and hydraulic cylinder drive stroke of the aerial platform fire rescue vehicle's working platform. When any one of these components exceeds the maximum threshold, the final identification warning coefficient fluctuates significantly, indicating that the stability of the aerial platform fire rescue vehicle is too low and does not meet the conditions for fire fighting and rescue operations. Fire fighting and rescue operations must be stopped immediately.

8. The method for stability identification and early warning of a fire rescue vehicle on an elevated platform according to claim 7, characterized in that, The iterative operation function is: Among them, Q n Q is the current identification and warning coefficient. n+1 H is the identification and warning coefficient for one iteration of the calculation. n S represents the ascent height of the work platform corresponding to the current identification and warning coefficient. n L is the vibration change parameter of the working platform corresponding to the current identification warning coefficient. n The current identification warning coefficient corresponds to the hydraulic cylinder drive stroke; k1, k2, and k3 are optimization operation constants.

9. The stability identification and early warning method for a fire rescue vehicle on an elevated platform according to claim 7, characterized in that: The number of iterations is no more than 5, and can be set to correspond to the time nodes; the value range of the optimization operation constant is (0.2, 0.7).

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