Intelligent data management and risk control system and method

Abstract

The invention provides an intelligent data management and risk control system and method, and belongs to the technical field of sound insulation board processing. Comprising a first recognition module and a second recognition module, the first recognition module is used for calculating and obtaining the optimal speed value Zs of the target forklift equipment according to the advancing route condition of the target forklift equipment, collecting the real-time speed value Q of the target forklift equipment and comparing and evaluating the real-time speed value Q with the optimal speed value Zs of the target forklift equipment, and the second recognition module is used for recognizing the real-time speed value Q of the target forklift equipment. And the road condition acquisition module is used for acquiring road condition information again after the first correction instruction is executed, the road condition information comprises a slope angle theta, so that the real-time gradient omega of the goods on the target forklift equipment is calculated and evaluated with a preset threshold value, and a second correction instruction is generated according to an evaluation result and executed. According to the system, through intelligent identification, real-time monitoring and automatic regulation and control, the forklift can run more safely, efficiently and intelligently under complex working conditions, and the industrial carrying operation process is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of data management and risk control. Specifically, it relates to an intelligent data management and risk control system and method. Background Art

[0002] In the automated material handling of modern factories, intelligent forklifts have become important equipment for improving production efficiency and reducing labor costs. However, during actual operation, the traveling speed and cargo stability of intelligent forklifts are affected by various factors. Especially under different terrain conditions (such as flat ground, slippery roads, ramps), it may affect the operation efficiency and safety of the forklifts. When an intelligent forklift is fully loaded with goods, it needs to transport the goods from one location to another. During the transportation process, the intelligent forklift will encounter various road conditions. In a factory, some locations have concrete floors, some have rubber floors, and some locations are even soil. Currently, the moving speed of forklifts is mostly manually controlled. When encountering roads with different materials, operators need to manually operate, manually control the speed, and cannot accurately control the speed. For example, on a rubber road surface, it is easy to slip, and on a soil road surface, there are obstacles of different heights, and operators cannot accurately adjust the speed, which affects the traveling efficiency of intelligent forklifts and is also prone to risks such as slipping and tipping over.

[0003] Moreover, when an intelligent forklift is traveling and enters a factory workshop, it will encounter slopes. However, when the intelligent forklift keeps moving at a set speed, when going uphill, it is easy to cause the goods on the forklift to tip over, affecting the normal transportation of the goods.

[0004] Therefore, in view of the factors affecting the speed during the traveling process of intelligent forklifts and the problem of cargo inclination on slopes, it is necessary to establish an intelligent data management and risk control system to improve the safety and stability of the transportation process. Summary of the Invention

[0005] To make up for the above deficiencies, the present invention provides an intelligent data management and risk control system and method that overcomes the above technical problems or at least partially solves the above problems.

[0006] The present invention is implemented as follows:

[0007] The present invention provides an intelligent data management and risk control system, including a first recognition module and a second recognition module;

[0008] The first recognition module is used to analyze the traveling route conditions of the target forklift equipment, where the traveling route conditions include ground material, ground humidity, and wind resistance, and construct the maximum safe traveling speed Cv of the target forklift equipment on different material road surfaces max, the maximum speed Sv of the target forklift equipment when driving on the ground with different humidity levels max and the maximum speed Fv of the target forklift equipment under the influence of wind resistance max , to calculate the optimal speed value Zs of the target forklift equipment, and collect the real-time speed value Q of the target forklift equipment and compare and evaluate it with the optimal speed value Zs of the target forklift equipment. When the optimal speed value Zs of the target forklift equipment is lower than the real-time speed value Q, trigger the first alarm instruction, and generate and execute the first correction instruction;

[0009] The second recognition module is used to, after the execution of the first correction instruction, re-collect the road surface condition information. The road surface conditions include: the slope angle θ, to calculate the speed Xv of the target forklift equipment on the slope, and calculate the real-time inclination ω of the goods on the target forklift equipment according to the slope angle θ. Evaluate the real-time inclination ω of the goods on the target forklift equipment collected with the preset threshold. When the real-time inclination ω of the goods on the target forklift equipment is greater than or less than the preset threshold, trigger the second alarm instruction, and generate and execute the second correction instruction.

[0010] In a preferred solution, the first recognition module includes a ground material collection unit, a ground humidity collection unit, and a wind resistance coefficient collection unit;

[0011] The ground material collection unit uses ultrasonic and infrared sensors to collect the hardness and bearing capacity of the ground, and divides the ground material through the hardness and bearing capacity of the ground. The ground materials include dry concrete, slippery concrete, smooth tiles, asphalt, steel plates, rubber floors, and muddy ground;

[0012] The target forklift equipment uses rubber tires. Through the following formula, calculate the maximum safe driving speed Cv of the target forklift equipment on different material road surfaces max :

[0013]

[0014] In the formula, μ represents the friction coefficient of the ground material, μ can be obtained from the following table, g represents the acceleration due to gravity, g = 9.8m / s 2 , h represents the center of gravity height of the target forklift equipment, and the center of gravity height of the target forklift equipment is measured by cooperating with a pressure sensor, a laser range finder sensor, and an IMU sensor.

[0015] In a preferred solution, the ground humidity collection unit is used to construct a monitoring area with the target forklift equipment as the center and a radius of R, and construct a three-dimensional map with the initial position of the target forklift equipment as the origin to obtain the position x, y, z of the target forklift equipment; and obtain the ground humidity Ds in the monitoring area through the following formula;

[0016] Ds = H0 + (P × e t ) + RH;

[0017] Wherein, H0 is the initial humidity value of the target forklift equipment at the position (x, y, z), which is detected by a humidity sensor, RH represents the air humidity value, which is obtained by a humidity sensor, and P × e t , where P represents the precipitation value of the target forklift equipment at the position (x, y, z), which is obtained by a rain sensor, and e t indicates that the precipitation decays exponentially with time t and is obtained by the following formula;

[0018] The ground humidity acquisition unit includes a first extraction unit, and the first extraction unit is used to extract the ground humidity D in the monitoring area s , after dimensionless processing, the maximum speed Sv of the target forklift equipment traveling on the ground with different humidities is obtained by the following formula max ;

[0019]

[0020] Wherein, g is the acceleration of gravity, and g = 9.8 m / s 2 , C d represents the air resistance coefficient, which is detected by an air resistance sensor, ρ represents the air density, which is obtained by referring to a chart, and A s represents the frontal area of the target forklift equipment, m represents the total mass of the target forklift equipment and the goods, which is obtained by a weight detection sensor, and O represents the friction coefficient of the target forklift equipment on the wet ground, which is detected by a humidity sensor.

[0021] In a preferred solution, the air resistance coefficient acquisition unit is used to collect the self-weight G of the target forklift equipment, the weight M of the goods on the target forklift equipment, and the height Mh of the goods stacked on the target forklift equipment. The wind speed value P is detected by a wind sensor Z , and the frontal area A of the target forklift equipment is extracted s , after dimensionless processing, the air resistance coefficient f is calculated by the following formula x ;

[0022]

[0023] Wherein, C0 represents the no-load air resistance coefficient of the target forklift equipment, Z1, Z2, Z3, and Z4 represent weight coefficients, which are obtained through experiments, L represents the length of the target forklift equipment, which is directly measured, γ represents the cargo shape factor, which is obtained by referring to the cargo shape factor table, and L 2 represents the square of the length of the target forklift equipment;

[0024] Coefficient of wind resistance f x After dimensionless processing, the maximum speed Fv of the target forklift equipment under wind resistance factors is obtained through the following formula max ;

[0025]

[0026] In the formula, F m represents the driving force of the target forklift equipment, provided by the manufacturer of the target forklift equipment, μ r represents the rolling resistance coefficient, μ r = 0.01, g represents the acceleration due to gravity, g = 9.8m / s 2 , τ represents the air density, τ = 1.225 under standard atmospheric pressure, A s represents the frontal area of the target forklift equipment.

[0027] In a preferred embodiment, the first identification module further includes a second extraction unit;

[0028] The second extraction unit is used to extract the maximum safe driving speed Cv of the target forklift equipment on different material road surfaces max , the maximum speed Sv of the target forklift equipment when driving on the ground with different humidities max and the maximum speed Fv of the target forklift equipment under wind resistance factors max , after dimensionless processing, the optimal speed value Zs of the target forklift equipment is obtained through the following formula;

[0029]

[0030] In the formula, V0 represents the theoretical maximum speed, through the parameters provided by the manufacturer, α, β and σ are influence weights, satisfying α + β + σ = 1;

[0031] The optimal speed value Zs of the target forklift equipment is evaluated with the real-time speed value Q;

[0032] When the optimal speed value Zs of the target forklift equipment ≥ the real-time speed value Q, it means that the target forklift does not have the risk of rollover or deviation caused by wetness, and continuous monitoring is carried out;

[0033] When the optimal speed value Zs of the target forklift equipment < the real-time speed value Q, it indicates that the real-time speed value Q of the movement of the target forklift equipment has exceeded the optimal speed value Zs of the target forklift equipment, the speed is abnormal, and there is a risk of rollover or deviation caused by wetness; issue a first alarm instruction and generate a first correction instruction;

[0034] The first correction instruction includes;

[0035] When the optimal speed value Zs of the target forklift equipment < the real-time speed value Q, and the difference ratio exceeds 10%, a first alarm instruction will be generated. The speed of the target forklift equipment will be regulated through the first alarm instruction, and the corrected speed V of the target forklift equipment will be obtained through the following formula corrected ;

[0036]

[0037] In the formula, p is the adjustment coefficient, obtained from historical data, represents the difference ratio between the optimal speed value Zs and the real-time speed value Q of the target forklift equipment;

[0038] After receiving the first alarm instruction, the real-time speed Q of the target forklift equipment will be reduced by 10% - 20% through system control.

[0039] In a preferred solution, after the first correction instruction is executed, the road surface condition information is re-collected;

[0040] The second recognition module includes a slope angle monitoring unit, a third extraction unit, and a cargo tilt monitoring unit;

[0041] The slope angle detection unit is used to collect the slope angle encountered by the target forklift equipment on the traveling path, and obtain the slope angle θ.

[0042] In a preferred solution, the third extraction unit is used for the ground friction coefficient μ, the ground humidity D in the monitoring area s , the frontal area A of the target forklift equipment s , the wind resistance coefficient f x After extraction and dimensionless processing of the slope angle θ, the speed Xv of the target forklift equipment on the slope is obtained through the following formula;

[0043]

[0044] In the formula, the numerator represents the resultant force of the available driving force and resistance of the forklift on the slope, F m represents the driving force of the target forklift equipment, provided by the manufacturer of the target forklift equipment, μ×(D s ) represents the frictional force under the influence of ground humidity, D s represents the ground humidity in the monitoring area, m×g×sinθ represents the gravitational influence value of the slope on the target forklift equipment, f x ×ρ×A s , the denominator represents the influence value of the air resistance coefficient on the target forklift equipment, ρ represents the air density, A sis expressed as the frontal area of the target forklift truck equipment, Zs is expressed as the optimal speed value of the target forklift truck equipment, m is expressed as the total mass of the target forklift truck equipment and the goods, g is the acceleration due to gravity, and g = 9.8 m / s 2 .

[0045] In a preferred solution, the cargo tilt monitoring unit is used to monitor the movement of the target forklift truck equipment on a slope, obtain the tilt of the cargo on the target forklift truck equipment according to the tilt angle of the target forklift truck equipment on the slope, and obtain the real-time tilt ω of the cargo on the target forklift truck equipment through the following formula;

[0046]

[0047] In the formula, ω0 is expressed as the initial angle of the cargo, θ is expressed as the slope angle, Δα is expressed as the superposition of the self-tilt of the target forklift truck equipment affecting the cargo tilt angle, and is obtained through an angle detector, is expressed as the tilt angle caused by the inertial force caused by the speed of the target forklift truck equipment and the height of the cargo center of gravity, h c is expressed as the height of the cargo center of gravity, obtained by direct measurement, the position of the cargo center of gravity at the center of the cargo, Xv is expressed as the speed of the target forklift truck equipment on the slope, and g is the acceleration due to gravity.

[0048] In a preferred solution, the second recognition module includes a risk reminder unit and a strategy unit;

[0049] The risk reminder unit is used to monitor the driving speed of the target forklift truck equipment at the slope position, and based on the evaluation result of the tilt ω of the cargo on the target forklift truck equipment and the preset threshold;

[0050] The real-time tilt ω of the cargo on the target forklift truck equipment is evaluated with the preset threshold;

[0051] When the real-time tilt ω of the cargo on the target forklift truck equipment > the preset threshold or the real-time tilt ω of the cargo on the target forklift truck equipment < the preset threshold, it indicates that the tilt angle of the cargo on the target forklift truck equipment is too large, prone to tipping, and the behavior is abnormal, obtaining a second alarm instruction, and generating a second correction instruction through the second alarm instruction;

[0052] The real-time tilt ω of the cargo on the target forklift truck equipment = the preset threshold, indicating that the tilt angle of the cargo on the target forklift truck equipment is qualified, and continuous monitoring is carried out.

[0053] The strategy unit is used to execute the second correction instruction when the target forklift truck equipment receives the second alarm instruction;

[0054] The second correction instruction includes:

[0055] The inclination ω of the goods on the target forklift equipment exceeds the first inclination angle difference ratio by no more than 10%;

[0056] When the real-time inclination ω of the goods on the target forklift equipment > the preset threshold or the real-time inclination ω of the goods on the target forklift equipment < the preset threshold, it indicates that the inclination angle of the goods on the target forklift equipment is abnormal, and there is a risk of the goods tipping over. The moving speed of the target forklift equipment needs to be reduced by 10%-20% to avoid the goods tipping over on the target forklift equipment;

[0057] When the real-time inclination ω of the goods on the target forklift equipment = the preset threshold, it means that the inclination angle of the goods on the target forklift equipment is qualified, and continuous monitoring is carried out.

[0058] An intelligent data management and risk control method includes the following steps:

[0059] Step 1: Collect the situation of the traveling route of the target forklift equipment. The traveling route situation includes ground material, ground humidity, and wind resistance. Analyze the traveling route situation and construct the maximum safe traveling speed Cv of the target forklift equipment on different material road surfaces max , the maximum traveling speed Sv of the target forklift equipment on the ground with different humidities max and the maximum speed Fv of the target forklift equipment under the influence of wind resistance max , calculate the optimal speed value Zs of the target forklift equipment, and collect the real-time speed value Q of the target forklift equipment and compare and evaluate it with the optimal speed value Zs of the target forklift equipment. When the optimal speed value Zs of the target forklift equipment is lower than the real-time speed value Q, trigger the first alarm instruction, and generate and execute the first correction instruction;

[0060] Step 2: After the first correction instruction is executed, re-collect the road surface situation information. The road surface situation includes: slope angle θ, calculate the speed Xv of the target forklift equipment on the slope, and calculate the real-time inclination ω of the goods on the target forklift equipment according to the slope angle θ. Evaluate the real-time inclination ω of the goods collected on the target forklift equipment with the preset threshold. When the real-time inclination ω of the goods on the target forklift equipment is greater than or less than the preset threshold, trigger the second alarm instruction, and generate and execute the second correction instruction.

[0061] An intelligent data management and risk control system and method provided by the present invention has the following beneficial effects:

[0062] 1. Through this system, it is possible to detect the ground material, humidity, wind resistance, and slope angle in real time. For example, for slippery ground, slopes, and the influence of strong winds, etc., this system can monitor the ground material, humidity, wind resistance, and slope angle in real time, and calculate the optimal safe speed Zs of the forklift. By comparing the real-time speed Q with Zs, once an overspeed situation is detected, the system will immediately trigger the first alarm instruction and execute the first correction instruction to reduce the speed, preventing out-of-control, rollover, or collision accidents caused by excessive speed. Compared with traditional manual control, this system effectively and accurately controls the driving speed of the target forklift equipment, avoiding the occurrence of skidding and rollover when the target forklift equipment is driving. Through intelligent recognition, real-time monitoring, and automatic regulation, this system makes the forklift operate more safely, efficiently, and intelligently under complex working conditions, optimizing the industrial handling operation process.

[0063] 2. By combining the system with slope monitoring, it can prevent the forklift from becoming unstable due to excessive slope, improving the operation safety. Moreover, the stability of the goods on the forklift is crucial, especially when transporting under complex road conditions. The inclination of the goods may cause the forklift to lose balance, the goods to fall, or even trigger safety accidents. Therefore, a second recognition module is set up to calculate the inclination of the goods by real-time monitoring the slope angle, forklift speed, and the inclination angle of the goods, and compare and analyze it with the preset threshold. When the inclination angle exceeds the safe range, the system will trigger the second alarm instruction and execute the second correction instruction to automatically adjust the forklift speed or remind the operator to make adjustments, preventing the goods from falling or being damaged due to excessive inclination. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0065] Figure 1 It is the system block diagram of the present invention;

[0066] Figure 2 It is the step block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0068] Example 1. Refer to Figure 1 - Figure 2 , the present invention provides a technical solution: an intelligent data management and risk control system, including a first identification module and a second identification module;

[0069] The first identification module is used to analyze the travel route conditions of the target forklift equipment. The travel route conditions include ground material, ground humidity, and wind resistance, and construct the maximum safe driving speed Cv of the target forklift equipment on different material road surfaces max , the maximum driving speed Sv of the target forklift equipment on the ground with different humidities max and the maximum speed Fv of the target forklift equipment under the influence of wind resistance max , so as to calculate the optimal speed value Zs of the target forklift equipment, collect the real-time speed value Q of the target forklift equipment, and compare and evaluate it with the optimal speed value Zs of the target forklift equipment. When the optimal speed value Zs of the target forklift equipment is lower than the real-time speed value Q, trigger the first alarm instruction, generate the first correction instruction and execute it;

[0070] The second identification module is used to re-collect the road surface condition information after the execution of the first correction instruction. The road surface conditions include: slope angle θ, so as to calculate the speed Xv of the target forklift equipment on the slope, and calculate the real-time inclination ω of the goods on the target forklift equipment according to the slope angle θ. Evaluate the real-time inclination ω of the goods on the target forklift equipment collected with a preset threshold. When the real-time inclination ω of the goods on the target forklift equipment is greater than or less than the preset threshold, trigger the second alarm instruction, generate the second correction instruction and execute it.

[0071] In this embodiment, in a factory environment, a forklift may encounter various unstable factors during operation, such as slippery ground, ramps, strong wind influence, etc. This system can detect the ground material, humidity, wind resistance, and slope angle in real time, and calculate the optimal safe speed Zs of the forklift. By comparing the real-time speed Q with Zs, once an overspeed situation is detected, the system will immediately trigger the first alarm instruction and execute the first correction instruction to reduce the speed and prevent accidents such as loss of control, rollover, or collision caused by excessive speed. In addition, when operating in a slope area, the system can also combine slope monitoring to prevent the forklift from becoming unstable due to excessive slope and improve operating safety. Moreover, the stability of the goods on the forklift is crucial, especially when transporting under complex road conditions. The inclination of the goods may cause the forklift to lose balance, the goods to fall, or even trigger safety accidents. The second recognition module calculates the inclination of the goods by real-time monitoring of the slope angle, forklift speed, and inclination angle of the goods, and compares and analyzes it with a preset threshold. When the inclination angle exceeds the safe range, the system will trigger the second alarm instruction and execute the second correction instruction to automatically adjust the forklift speed or remind the operator to make adjustments to prevent the goods from tilting too much and causing falling or damage.

[0072] Embodiment 2. This embodiment is an explanatory description in Embodiment 1. Please refer to Figure 1 , specifically, the first recognition module includes a ground material acquisition unit, a ground humidity acquisition unit, and a wind resistance coefficient acquisition unit;

[0073] The ground material acquisition unit uses ultrasonic and infrared sensors to collect the hardness and bearing capacity of the ground, and divides the ground material through the hardness and bearing capacity of the ground. The ground materials include dry concrete, slippery concrete, smooth tiles, asphalt, steel plates, rubber floors, and muddy ground;

[0074] The target forklift equipment uses rubber tires. The maximum safe driving speed Cv of the target forklift equipment on different material roads is calculated through the following formula max :

[0075]

[0076] In the formula, μ represents the friction coefficient of the ground material, μ can be obtained from the following table, g represents the acceleration due to gravity, g = 9.8m / s 2 , h represents the center of gravity height of the target forklift equipment, and the center of gravity height of the target forklift equipment is measured by cooperating with a pressure sensor, a laser ranging sensor, and an IMU sensor

[0077] Friction coefficient μ of different ground materials:

[0078] Dry concrete, μ = 0.6; Slippery concrete, μ = 0.3; Smooth tile, μ = 0.2; Asphalt, μ = 0.5; Steel plate, μ = 0.6; Rubber floor, μ = 0.6; Muddy ground, μ = 0.2;

[0079] In this embodiment, when the forklift runs on different ground materials, affected by the friction coefficient and bearing capacity, its safe driving speed will be different. The ground material acquisition unit of the system uses a combination of ultrasonic sensors and infrared sensors to achieve precise acquisition of the ground hardness and bearing capacity, and through data analysis, divides the ground into various types such as dry concrete, slippery concrete, smooth tile, asphalt, steel plate, rubber floor, muddy ground, etc. The friction coefficient μ of different grounds is measured through experiments and stored in the database. The forklift can calculate the optimal safe speed C by querying the μ value in real time to ensure safe driving in different ground environments. The slippery ground has a great impact on the stability of the forklift. Especially in warehouses, factories or outdoor environments, the ground may become slippery due to factors such as rain, oil stains, snow, etc., resulting in a decrease in friction. The ground humidity acquisition unit of this system uses a humidity sensor to detect the humidity Ds in the monitoring area in real time.

[0080] Example 3, this example is an explanatory note in Example 1, please refer to Figure 1 , specifically, the ground humidity acquisition unit is used to construct a monitoring area with the target forklift equipment as the center and a radius of R, and construct a three-dimensional map with the initial position of the target forklift equipment as the origin to obtain the position x, y, z of the target forklift equipment; and obtain the ground humidity Ds in the monitoring area through the following formula;

[0081] Ds = H0 + (P × e t ) + RH;

[0082] In the formula, H0 is the initial humidity value of the position where the target forklift equipment is located at (x, y, z), which is detected by the humidity sensor, RH represents the air humidity value, which is obtained by the humidity sensor, P × e t , where P represents the precipitation value of the position where the target forklift equipment is located at (x, y, z), which is obtained by the rain sensor, e t represents that the precipitation decays exponentially with time t, and is obtained through the following formula;

[0083] The ground humidity acquisition unit includes a first extraction unit, and the first extraction unit is used to extract the ground humidity D in the monitoring area s , after dimensionless processing, obtain the maximum speed Sv of the target forklift equipment when driving on the ground with different humidities through the following formula max ;

[0084]

[0085] In the formula, g is the acceleration due to gravity, and g = 9.8 m / s 2 , C d represents the air resistance coefficient, which is detected by an air resistance sensor. ρ represents the air density, which is obtained by referring to a chart. A s represents the frontal area of the target forklift equipment, m represents the total mass of the target forklift equipment and the goods, which is obtained through a weight detection sensor, and O represents the friction coefficient of the target forklift equipment on a wet ground, which is detected by a humidity sensor;

[0086] Table of air density examples;

[0087]

[0088]

[0089] In this embodiment, when a traditional forklift travels on a wet ground, the friction may decrease due to humidity changes, thus increasing the risk of slipping and tipping over. The ground humidity acquisition unit of this system constructs a humidity monitoring area with the target forklift equipment as the center and a radius of R through three-dimensional modeling, and combines the real-time position (x, y, z) data to construct a dynamic humidity distribution model. This modeling method can accurately obtain the humidity gradient distribution in the forklift travel area, identify high-humidity areas and dynamically adjust the forklift speed to reduce the risk of loss of control caused by the wet ground. A wet environment is usually accompanied by high air humidity and wind resistance changes. If not controlled, it may lead to increased forklift energy consumption or unstable driving. Combining the optimization mechanism of humidity and wind resistance enables the forklift to maintain a low-energy consumption and high-safety operating state in a wet environment.

[0090] Example 4. This example is an explanatory description in Example 1. Please refer to Figure 1 , specifically, the wind resistance coefficient acquisition unit is used to collect the self-weight G of the target forklift equipment, the weight M of the goods on the target forklift equipment, and the height Mh of the goods stacked on the target forklift equipment. The wind speed value P is detected by a wind sensor Z , and the frontal area A of the target forklift equipment is extracted s , after dimensionless processing, the wind resistance coefficient f is calculated through the following formula x ;

[0091]

[0092] In the formula, C0 represents the no-load wind resistance coefficient of the target forklift equipment, which can be measured through experiments. Z1, Z2, Z3, and Z4 represent weight coefficients and are obtained through experiments. L represents the length of the target forklift equipment, which is directly measured. γ represents the cargo shape factor, which is obtained by referring to the cargo shape factor table. L 2It is expressed as the square of the length of the target forklift truck equipment;

[0093] Example table of the cargo shape factor;

[0094] Cylinder 0.47, cuboid (square) 1.05, cuboid (length, width, smaller height) 0.8, cube (square object) 1.0, spherical object 0.47;

[0095] The following is the wind resistance coefficient f x Example table;

[0096]

[0097] Wind resistance coefficient f x After dimensionless processing, the maximum speed Fv of the target forklift truck equipment under the wind resistance factor is obtained through the following formula max ;

[0098]

[0099] In the formula, F m is expressed as the driving force of the target forklift truck equipment, provided by the manufacturer of the target forklift truck equipment, μ r is expressed as the rolling resistance coefficient, μ r = 0.01, g is expressed as the acceleration due to gravity, g = 9.8m / s 2 , τ is expressed as the air density, τ = 1.225 under standard atmospheric pressure, A s is expressed as the frontal area of the target forklift truck equipment.

[0100] The following is the maximum speed Fv under the wind resistance factor max Example table;

[0101]

[0102] Example 5, this example is an explanation in Example 1, please refer to Figure 1 , specifically, the first recognition module further includes a second extraction unit;

[0103] The second extraction unit is used to extract the maximum safe driving speed Cv of the target forklift truck equipment on roads of different materials max , the maximum speed Sv of the target forklift truck equipment when driving on the ground with different humidities max and the maximum speed Fv of the target forklift truck equipment under the wind resistance factor max , after dimensionless processing, the optimal speed value Zs of the target forklift truck equipment is obtained through the following formula;

[0104]

[0105] Wherein, V0 represents the theoretical maximum speed, and through the parameters provided by the manufacturer, α, β, and σ are influence weights, satisfying α + β + σ = 1;

[0106] The following is an example chart of the optimal speed value Zs of the target forklift equipment;

[0107]

[0108] The optimal speed value Zs of the target forklift equipment is evaluated with the real-time speed value Q;

[0109] When the optimal speed value Zs of the target forklift equipment ≥ the real-time speed value Q, it indicates that there is no risk of rollover or deviation caused by slipperiness of the target forklift, and continuous monitoring is carried out;

[0110] When the optimal speed value Zs of the target forklift equipment < the real-time speed value Q, it indicates that the real-time speed value Q of the movement of the target forklift equipment has exceeded the optimal speed value Zs of the target forklift equipment, the speed is abnormal, and there is a risk of rollover or deviation caused by slipperiness; a first alarm instruction is issued, and a first correction instruction is generated;

[0111] The first correction instruction includes;

[0112] When the optimal speed value Zs of the target forklift equipment < the real-time speed value Q, and the difference ratio exceeds 10%, a first alarm instruction is generated. The speed of the target forklift equipment is regulated through the first alarm instruction, and the corrected speed V of the target forklift equipment is obtained through the following formula corrected ;

[0113]

[0114] Wherein, p is an adjustment coefficient, obtained based on historical data, represents the difference ratio between the optimal speed value Zs and the real-time speed value Q of the target forklift equipment;

[0115] After receiving the first alarm instruction, the real-time speed Q of the target forklift equipment will be reduced by 10% - 20% through system control.

[0116] In this embodiment, by automatically calculating and real-time adjusting the optimal speed Zs of the forklift, the system ensures that the forklift always operates at the most suitable speed, avoiding inefficient operations caused by too fast or too slow speeds, improving the transportation efficiency. The automatic speed adjustment of the system can prevent the forklift from speeding or being too slow under unnecessary circumstances, avoiding energy waste and mechanical wear, and reducing the overall operating cost of the equipment. When the speed of the forklift equipment exceeds the optimal range, the system will issue an alarm and automatically adjust the speed. This real-time feedback function enhances the operator's sense of security, ensuring that no accidents occur when the operator controls the forklift. The automated monitoring and adjustment relieve the operator's pressure, allowing them not to focus too much on speed control and enabling them to concentrate on other important operations, thereby improving the overall work efficiency.

[0117] Embodiment 6. This embodiment is an explanatory description in Embodiment 1. Please refer to Figure 1 , specifically, after executing the first correction instruction, the road surface condition information is recollected;

[0118] The second recognition module includes a slope angle monitoring unit, a third extraction unit, and a cargo tilt monitoring unit;

[0119] The slope angle detection unit is used to collect the slope angle encountered by the target forklift equipment on the traveling path, and obtain the slope angle θ.

[0120] The third extraction unit is used to extract the ground friction coefficient μ, the ground humidity D in the monitoring area s , the frontal area A of the target forklift equipment s , the air resistance coefficient f x . After the extraction and the slope angle θ are dimensionless processed, the speed Xv of the target forklift equipment on the slope is obtained through the following formula;

[0121]

[0122] In the formula, the numerator represents the resultant force of the available driving force and resistance of the forklift on the slope, F m represents the driving force of the target forklift equipment, provided by the manufacturer of the target forklift equipment, μ×(D s ) represents the frictional force under the influence of ground humidity, D s represents the ground humidity in the monitoring area, m×g×sinθ represents the gravitational influence value of the slope on the target forklift equipment, f x ×ρ×A s . The denominator represents the influence value of the air resistance coefficient of the target forklift equipment. ρ represents the air density, A s represents the frontal area of the target forklift equipment, Zs represents the optimal speed value of the target forklift equipment, m represents the total mass of the target forklift equipment and the cargo, g is the acceleration due to gravity, and g = 9.8m / s2 。

[0123] This formula is essentially derived from the mechanical equilibrium equation, involving the influence of factors such as driving force, gravity, friction, and air resistance on the forklift. The speed needs to be solved by taking the square root because the air resistance is proportional to the square of the speed. The solution of the speed naturally requires a transformation from the mechanical formula to the square root of the energy formula, and finally this formula is obtained.

[0124] The following is an example table of the speed Xv of the target forklift equipment on the slope;

[0125]

[0126]

[0127] In this embodiment, by monitoring and calculating the speed of the target forklift equipment on the slope, it is possible to accurately evaluate whether the equipment is within the safe operating speed range. If the calculation result shows that the speed of the forklift on the slope exceeds the safety threshold (i.e., the optimal speed Zs), the system will automatically alarm and adjust the speed to avoid accidents such as rollover or loss of control caused by excessive speed. By considering the ground humidity and friction coefficient, the system can more precisely adjust the forklift speed to ensure that the forklift can drive safely even on wet or high-humidity ground.

[0128] Based on a comprehensive analysis of multiple factors such as slope angle, friction, and air resistance coefficient, the system can adjust the driving speed of the forklift in real time during slope driving to avoid affecting work efficiency due to excessive or too slow speed. On ground with different slopes, the system can dynamically adjust the speed of the forklift according to the real-time collected data to ensure that the forklift can drive stably and improve work efficiency. The system automatically collects and analyzes data such as slope angle, ground humidity, and wind speed, and has intelligent adaptability, capable of automatically adjusting the driving state of the forklift according to environmental changes. Different from traditional manual control, this intelligent system greatly reduces the risk of human operation errors, automatically monitors and calculates the influence of friction coefficient and humidity, and can more precisely evaluate the safe driving speed in each environment to ensure that the forklift can maintain efficient and safe driving in various complex environments.

[0129] Embodiment 7. This embodiment is an explanatory description in Embodiment 1. Please refer to Figure 1 , specifically, the cargo tilt monitoring unit is used to move the target forklift equipment on the slope, obtain the tilt degree of the cargo on the target forklift equipment according to the tilt angle of the target forklift equipment on the slope, and obtain the real-time tilt degree ω of the cargo on the target forklift equipment through the following formula;

[0130]

[0131] In the formula, ω0 represents the initial angle of the goods, θ represents the ramp angle, and Δα represents the superimposed influence of the inclination of the target forklift equipment itself on the inclination angle of the goods, which is obtained through an angle detector. represents the inclination angle caused by the inertial force generated by the speed of the target forklift equipment and the height of the center of gravity of the goods, h c represents the height of the center of gravity of the goods, which is obtained through direct measurement. The position of the center of gravity of the goods at the center of the goods, Xv represents the speed of the target forklift equipment on the ramp, and g is the acceleration due to gravity.

[0132] The following is an example table of the real-time inclination ω of the goods on the target forklift equipment;

[0133]

[0134] In this embodiment, by real-time monitoring of the inclination angle of the goods, it is possible to timely identify whether there is an excessive inclination of the goods, reducing the risk of the goods slipping or tipping over caused by inertial force and slope influence. When the forklift is driving on the ramp, the inclination angle of the goods will be affected by multiple factors (forklift slope, acceleration, center of gravity of the goods, etc.). By monitoring and calculating the real-time inclination angle of the goods, it is possible to ensure the safe driving of the forklift operator on the ramp. Combining with devices such as angle sensors and acceleration sensors, intelligent monitoring and automatic adjustment can be achieved, reducing misjudgment in manual operations and improving the intelligent control ability of the forklift. If the inclination angle of the goods exceeds the safety threshold, the system can automatically trigger an alarm and reduce the risk by adjusting the speed of the forklift, preventing rollover or goods dropping.

[0135] Embodiment 8. This embodiment is an explanatory description in Embodiment 1. Please refer to Figure 1 , specifically, the second recognition module includes a risk reminder unit and a strategy unit;

[0136] The risk reminder unit is used to monitor the driving speed of the target forklift equipment at the ramp position and evaluate the result according to the inclination ω of the goods on the target forklift equipment and the preset threshold;

[0137] Evaluate the real-time inclination ω of the goods on the target forklift equipment and the preset threshold;

[0138] When the real-time inclination ω of the goods on the target forklift equipment > the preset threshold or the real-time inclination ω of the goods on the target forklift equipment < the preset threshold, it indicates that the inclination angle of the goods on the target forklift equipment is too large, prone to tipping over, and the behavior is abnormal. Obtain the second alarm instruction and generate the second correction instruction through the second alarm instruction;

[0139] When the real-time inclination ω of the goods on the target forklift equipment = the preset threshold, it indicates that the inclination angle of the goods on the target forklift equipment is qualified, and continuous monitoring is carried out.

[0140] The said strategy unit is used to execute a second correction instruction after the target forklift equipment receives a second alarm instruction;

[0141] The said second correction instruction includes:

[0142] The inclination ω of the goods on the target forklift equipment exceeds the first inclination angle difference ratio by no more than 10%;

[0143] When the real-time inclination ω of the goods on the target forklift equipment > the preset threshold or the real-time inclination ω of the goods on the target forklift equipment < the preset threshold, it indicates that the inclination angle of the goods on the target forklift equipment is abnormal, and there will be a risk of the goods tipping over. The moving speed of the target forklift equipment needs to be reduced by 10% - 20% to avoid the goods tipping over on the target forklift equipment;

[0144] When the real-time inclination ω of the goods on the target forklift equipment = the preset threshold, it means that the inclination angle of the goods on the target forklift equipment is qualified, and continuous monitoring is carried out.

[0145] In this embodiment, by real-time monitoring the inclination of the goods, the inclination of the goods when the forklift is driving on a slope can be identified, abnormalities can be discovered in advance, and the falling or tipping over of the goods can be prevented. When the inclination angle of the goods exceeds the preset threshold, the system will automatically issue a second alarm instruction to remind the forklift operator or automatically adjust the operating parameters of the forklift, reducing potential safety hazards. If the inclination angle is abnormal, the system will automatically reduce the speed of the forklift by 10% - 20% to avoid the goods tipping over due to inertial force or slope influence, improving the stability of the forklift on the slope. If the inclination angle of the goods is normal, the system will continuously monitor to ensure that the forklift always operates stably under different slope, speed, and goods center-of-gravity conditions. Traditional forklifts rely on the driver to judge the inclination of the goods for comparison, while this system can automatically detect, automatically alarm, and automatically adjust, reducing human error and improving transportation safety.

[0146] An intelligent data management and risk control method, please refer to Figure 2 , including the following steps:

[0147] Step 1: Collect the traveling route conditions of the target forklift equipment. The traveling route conditions include ground material, ground humidity, and wind resistance. Analyze the traveling route conditions and construct the maximum safe traveling speed Cv of the target forklift equipment on different material road surfaces max , the maximum traveling speed Sv of the target forklift equipment on the ground with different humidities max and the maximum speed Fv of the target forklift equipment under the influence of wind resistance max, calculate to obtain the optimal speed value Zs of the target forklift equipment, collect the real-time speed value Q of the target forklift equipment and compare and evaluate it with the optimal speed value Zs of the target forklift equipment. When the optimal speed value Zs of the target forklift equipment is lower than the real-time speed value Q, trigger the first alarm instruction, generate the first correction instruction and execute it;

[0148] Step 2: After the first correction instruction is executed, re-collect the road surface condition information. The road surface condition includes: the slope angle θ, calculate to obtain the speed Xv of the target forklift equipment on the slope, and calculate the real-time inclination ω of the goods on the target forklift equipment according to the slope angle θ. Evaluate the real-time inclination ω of the goods on the target forklift equipment collected with the preset threshold value. When the real-time inclination ω of the goods on the target forklift equipment is greater than or less than the preset threshold value, trigger the second alarm instruction, generate the second correction instruction and execute it.

[0149] The above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by those skilled in the art according to the actual situation. As mentioned above, it is only a preferred specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent replacements or changes, and should be covered by the protection scope of the present invention.

Claims

1. An intelligent data management and risk control system, characterized in that, It includes a first recognition module and a second recognition module; The first recognition module is used to analyze the traveling route conditions of the target forklift equipment, where the traveling route conditions include ground material, ground humidity, and wind resistance, and construct the maximum safe traveling speed Cv of the target forklift equipment on roads with different materials max , the maximum traveling speed Sv of the target forklift equipment on the ground with different humidities max and the maximum speed Fv of the target forklift equipment under the influence of wind resistance max , so as to calculate the optimal speed value Zs of the target forklift equipment, collect the real-time speed value Q of the target forklift equipment, and compare and evaluate it with the optimal speed value Zs of the target forklift equipment. When the optimal speed value Zs of the target forklift equipment is lower than the real-time speed value Q, trigger the first alarm instruction, generate the first correction instruction and execute it; The second recognition module is used to re-collect road surface condition information after the first correction instruction is executed. The road surface conditions include: the slope angle θ, to calculate the speed Xv of the target forklift equipment on the slope, and calculate the real-time inclination ω of the goods on the target forklift equipment according to the slope angle θ. The real-time inclination ω of the goods on the target forklift equipment collected is evaluated with a preset threshold. When the real-time inclination ω of the goods on the target forklift equipment is greater than or less than the preset threshold, a second alarm instruction is triggered, and a second correction instruction is generated and executed.

2. The intelligent data management and risk control system according to claim 1, characterized in that, The first recognition module includes a ground material collection unit, a ground humidity collection unit, and a wind resistance coefficient collection unit; The ground material collection unit collects the hardness and bearing capacity of the ground using ultrasonic and infrared sensors, and divides the ground material according to the hardness and bearing capacity of the ground. The ground materials include dry concrete, slippery concrete, smooth tiles, asphalt, steel plates, rubber floors, and muddy ground; The target forklift equipment uses rubber tires, and the maximum safe driving speed Cv of the target forklift equipment on different material road surfaces is calculated by the following formula max : Wherein, μ represents the friction coefficient of the ground material, g represents the acceleration of gravity, g = 9.8 m / s 2 , h represents the center-of-gravity height of the target forklift equipment, and the center-of-gravity height of the target forklift equipment is measured by cooperating with a pressure sensor, a laser ranging sensor and an IMU sensor.

3. An intelligent data management and risk control system according to claim 2, characterized in that, The ground humidity collection unit is used to construct a monitoring area with the target forklift equipment as the center and a radius of R, and construct a three-dimensional map with the initial position of the target forklift equipment as the origin to obtain the position x, y, z of the target forklift equipment; and obtain the ground humidity Ds in the monitoring area through the following formula; Ds = H0+(P×e t )+RH; Wherein, H0 is the initial humidity value of the target forklift equipment at the position (x, y, z), which is detected by a humidity sensor, RH represents the air humidity value, which is obtained by using a humidity sensor, P×e t , where P represents the precipitation value of the target forklift equipment at the position (x, y, z), which is obtained by a rain sensor, e t indicates that the precipitation decays exponentially with time t and is obtained by the following formula; The ground humidity acquisition unit includes a first extraction unit, and the first extraction unit is used to extract the ground humidity D in the monitoring area s , after dimensionless processing, the maximum driving speed Sv of the target forklift equipment on the ground with different humidities is obtained through the following formula max ; Wherein, g is the acceleration of gravity, and g = 9.8 m / s 2 , C d represents the air resistance coefficient, which is detected by an air resistance sensor. ρ represents the air density, which is obtained by referring to a chart. A s represents the frontal area of the target forklift equipment, m represents the total mass of the target forklift equipment and the goods, which is obtained by a weight detection sensor, and O represents the friction coefficient of the target forklift equipment on a wet ground, which is detected by a humidity sensor.

4. An intelligent data management and risk control system according to claim 3, characterized in that The wind resistance coefficient acquisition unit is used to collect the self-weight G of the target forklift equipment, the weight M of the goods on the target forklift equipment, and the height Mh of the goods stacked on the target forklift equipment. The wind speed value P is detected by a wind sensor Z , and the frontal area A of the target forklift equipment is extracted s . After dimensionless processing, the wind resistance coefficient f is calculated by the following formula x ; In the formula, C0 represents the no-load air resistance coefficient of the target forklift equipment, Z1, Z2, Z3, and Z4 represent the weight coefficients, which are obtained through experiments, L represents the length of the target forklift equipment, which is directly measured, γ represents the cargo shape factor, which is obtained by referring to the cargo shape factor table, and L 2 represents the square of the length of the target forklift equipment; For the wind resistance coefficient f x After dimensionless processing, the maximum speed Fv of the target forklift equipment under the influence of wind resistance is obtained through the following formula max ; In the formula, F m represents the driving force of the target forklift equipment, provided by the manufacturer of the target forklift equipment, μ r represents the rolling resistance coefficient, μ r = 0.01, g represents the acceleration due to gravity, g = 9.8m / s 2 , τ represents the air density, τ = 1.225 under standard atmospheric pressure, A s represents the frontal area of the target forklift equipment.

5. An intelligent data management and risk control system according to claim 4, characterized in that, The first recognition module also includes a second extraction unit; The second extraction unit is used to extract the maximum safe driving speed Cv of the target forklift equipment on roads with different materials max and the maximum driving speed Sv of the target forklift equipment on the ground with different humidity max and the maximum speed Fv of the target forklift equipment under the influence of wind resistance max , after dimensionless processing, the optimal speed value Zs of the target forklift equipment is obtained through the following formula; In the formula, V0 represents the theoretical maximum speed, obtained from the parameters provided by the manufacturer, and α, β, and σ are influence weights, satisfying α + β + σ = 1; The optimal speed value Zs of the target forklift equipment is evaluated with the real-time speed value Q; When the optimal speed value Zs of the target forklift equipment ≥ the real-time speed value Q, it means that the target forklift has no risk of tipping over or shifting due to slipperiness, and continuous monitoring is carried out; When the optimal speed value Zs of the target forklift equipment < the real-time speed value Q, it indicates that the real-time speed value Q of the movement of the target forklift equipment has exceeded the optimal speed value Zs of the target forklift equipment, the speed is abnormal, and there is a risk of tipping over or shifting due to slipperiness; a first alarm instruction is issued, and a first correction instruction is generated; The first correction instruction includes; When the optimal speed value Zs of the target forklift equipment < the real-time speed value Q, and the difference ratio exceeds 10%, a first alarm instruction will be generated. The speed of the target forklift equipment is regulated through the first alarm instruction, and the corrected speed V of the target forklift equipment is obtained through the following formula corrected ; where p is an adjustment coefficient obtained based on historical data, which is expressed as the difference ratio between the optimal speed value Zs of the target forklift equipment and the real-time speed value Q; After receiving the first alarm instruction, the real-time speed Q of the target forklift equipment will be reduced by 10% - 20% through the system.

6. An intelligent data management and risk control system according to claim 5, characterized in that, After the first correction instruction is executed, the road surface condition information is re-collected; The second recognition module includes a slope angle monitoring unit, a third extraction unit, and a goods inclination monitoring unit; The slope angle detection unit is used to collect the slope angle encountered by the target forklift equipment on the traveling path to obtain the slope angle θ.

7. An intelligent data management and risk control system according to claim 6, characterized in that The third extraction unit is used to perform dimensionless processing on the ground friction coefficient μ, the ground humidity D in the monitoring area s , the windward area A of the target forklift equipment s , the wind resistance coefficient f x and the slope angle θ, and then obtain the speed Xv of the target forklift equipment on the slope through the following formula; In the formula, the numerator represents the resultant force of the available driving force and resistance of the forklift on the slope, F m represents the driving force of the target forklift equipment, provided by the manufacturer of the target forklift equipment, μ×(D s ) represents the frictional force affected by the ground humidity, D s represents the ground humidity in the monitoring area, m×g×sinθ represents the gravitational influence value of the slope on the target forklift equipment, f x ×ρ×A s , the denominator represents the influence value of the air resistance coefficient received by the target forklift equipment, ρ represents the air density, A s represents the windward area of the target forklift equipment, Zs represents the optimal speed value of the target forklift equipment, m represents the total mass of the target forklift equipment and the goods, g is the acceleration due to gravity, and g = 9.8m / s 2 .

8. An intelligent data management and risk control system according to claim 7, characterized in that The goods inclination monitoring unit is used to move the target forklift equipment on the slope, and obtain the inclination of the goods on the target forklift equipment according to the inclination angle of the target forklift equipment on the slope. The real-time inclination ω of the goods on the target forklift equipment is obtained through the following formula; In the formula, ω0 represents the initial angle of the goods, θ represents the ramp angle, and Δα represents the superimposed influence of the inclination of the target forklift equipment itself on the inclination angle of the goods, which is obtained by an angle detector. represents the inclination angle caused by the inertial force resulting from the speed of the target forklift equipment and the height of the center of gravity of the goods, h c represents the height of the center of gravity of the goods, which is obtained by direct measurement. The position of the center of gravity of the goods at the center of the goods, Xv represents the speed of the target forklift equipment on the ramp, and g is the acceleration due to gravity.

9. An intelligent data management and risk control system according to claim 8, characterized in that, The second recognition module includes a risk reminder unit and a strategy unit; The risk reminder unit is used to monitor the traveling speed of the target forklift equipment at the slope position and according to the result of the evaluation of the inclination ω of the goods on the target forklift equipment with a preset threshold; The real-time inclination ω of the goods on the target forklift equipment is evaluated against a preset threshold value; When the real-time inclination ω of the goods on the target forklift equipment is > the preset threshold value or the real-time inclination ω of the goods on the target forklift equipment is < the preset threshold value, it indicates that the inclination angle of the goods on the target forklift equipment is too large, prone to tipping over, and the behavior is abnormal. A second alarm instruction is obtained, and a second correction instruction is generated through the second alarm instruction; When the real-time inclination ω of the goods on the target forklift equipment = the preset threshold value, it means that the inclination angle of the goods on the target forklift equipment is qualified, and continuous monitoring is carried out; The strategy unit is used to execute the second correction instruction when the target forklift equipment receives the second alarm instruction; The second correction instruction includes: The inclination ω of the goods on the target forklift equipment exceeds the first inclination angle difference ratio by no more than 10%; When the real-time inclination ω of the goods on the target forklift equipment is > the preset threshold value or the real-time inclination ω of the goods on the target forklift equipment is < the preset threshold value, it indicates that the inclination angle of the goods on the target forklift equipment is abnormal, and there is a risk of the goods tipping over. The moving speed of the target forklift equipment needs to be reduced by 10%-20% to avoid the goods tipping over on the target forklift equipment; When the real-time inclination ω of the goods on the target forklift equipment = the preset threshold value, it means that the inclination angle of the goods on the target forklift equipment is qualified, and continuous monitoring is carried out.

10. An intelligent data management and risk control method, comprising the intelligent data management and risk control system according to any one of claims 1-9 above, characterized in that, It includes the following steps: Step 1: Collect the driving route conditions of the target forklift equipment. The driving route conditions include ground material, ground humidity, and wind resistance. Analyze the driving route conditions and construct the maximum safe driving speed Cv of the target forklift equipment on different material road surfaces. max The maximum speed Sv of the target forklift equipment when driving on the ground with different humidity max And the maximum speed Fv of the target forklift equipment under the influence of wind resistance max to calculate the optimal speed value Zs of the target forklift equipment. Collect the real-time speed value Q of the target forklift equipment and compare and evaluate it with the optimal speed value Zs of the target forklift equipment. When the optimal speed value Zs of the target forklift equipment is lower than the real-time speed value Q, trigger the first alarm instruction, generate the first correction instruction and execute it. Step 2: After the first correction instruction is executed, the road surface condition information is collected again. The road surface condition includes: the slope angle θ, to calculate the speed Xv of the target forklift equipment on the slope, and calculate the real-time inclination ω of the goods on the target forklift equipment according to the slope angle θ. The real-time inclination ω of the goods collected on the target forklift equipment is evaluated against the preset threshold value. When the real-time inclination ω of the goods on the target forklift equipment is greater than or less than the preset threshold value, a second alarm instruction is triggered, and a second correction instruction is generated and executed.

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