Mine car driving state safety detection method and device

Abstract

The invention discloses a mine car driving state safety detection method and device, and relates to the technical field of mine car safety detection. A 3D map of a mining area is constructed, roads in the mining area are segmented, quantitative evaluation is obtained according to detailed data collection and analysis, and road state values of all road sections are obtained; by extracting key parameters in tramcar driving information and calculating a driving state value and a driving index, the driving state of the tramcar can be monitored in real time, abnormal conditions can be found in time, the driving safety of the tramcar can be evaluated more comprehensively, and data support is provided for subsequent driving path and speed optimization; a plurality of paths are generated based on a Dijkstra algorithm, the influence of the road surface condition of a road section on a mine car is reduced by calculating a congestion value, an adaptation index and a planning value, the driving safety of the mine car in a mine area is ensured, and the driving path and speed of the mine car are dynamically adjusted according to the driving index and the road state value of the mine car.

Description

Technical Field

[0001] The present invention relates to the technical field of mine car safety detection, and in particular to a mine car driving state safety detection method and device. Background Art

[0002] Mine trucks are heavy vehicles specially used for transportation in mines, mining areas or mining sites. They are usually designed to travel on rough and uneven ground to transport mineral resources or raw materials such as ore, coal, rock and soil. Mine trucks usually travel on harsh road conditions, especially on rough and uneven terrain in mining areas (such as underground mines, open-pit mines, mountainous or muddy roads, etc.), which increases the risk of mine truck rollover, skidding, tire wear, etc. Due to the particularity and high risk of the working environment of mine trucks, safety testing is essential to ensure the safety of mine truck driving.

[0003] Existing safety detection systems mainly focus on the status data collection of a single mine car. Although localized data collection can provide detailed information on a single mine car, it lacks comprehensive analysis of the entire mining area or mine car fleet and cannot provide comprehensive safety management decision support; for example, a section of road may be safe for some mine cars, but for another mine car there may be a risk of rollover or sliding. Summary of the invention

[0004] The present invention provides a method and device for safely detecting the driving state of a mine car, which are used to solve the above-mentioned technical problems.

[0005] The first aspect of the present invention provides a method for detecting the safe driving state of a mine car, comprising the following steps: Step 1: communicating with the mine car and a sensor mounted on the mine car to collect driving information of the mine car in real time; at the same time, placing sensors on the roads in the mining area to monitor and collect road information in real time;

[0006] Step 2: Use drones or fixed cameras to conduct road inspections and collect images to build a 3D map of the mining area, and divide the roads in the mining area into several sections. Analyze the road surface status of each section based on the road information to obtain the road status value;

[0007] Step 3: Based on the driving information of each mine car, the driving status of each mine car is feature extracted to obtain a driving index that comprehensively measures the driving status of the mine car, and the driving safety of each mine car is judged accordingly, and it is displayed in real time on the 3D map; if the driving index is greater than the maximum value in the set safety interval, the mine car is recorded as an abnormal mine car, and the position of the abnormal mine car is obtained in real time, and the abnormal mine car is controlled to travel to the safe area closest to the current position; if the driving index is within the set safety interval, it is marked as an adjustment mine car, the current position of the adjustment mine car is obtained in real time, and it is compared with the corresponding The driving index, the 3D map of the mining area, and the road status values ​​corresponding to each section are integrated into the planning parameters and sent to Step 4; if the driving index is less than the minimum value in the set safety interval, the mine car is marked as a normal mine car, and the current position of the normal mine car and its corresponding destination are obtained in real time. The K shortest path algorithm is used to obtain the closest path from the current position to the destination, and it is used as the target path of the normal mine car, and the mine car is controlled to travel according to its corresponding target path; abnormal mine cars, adjusted mine cars, and normal mine cars are tracked and displayed in red, yellow, and green in the 3D map of the mining area respectively;

[0008] Step 4: Dynamically adjust the mine cart based on the planning parameters to optimize the running path and speed of the mine cart.

[0009] Optionally, the specific steps for dynamically adjusting the minecart based on the planning parameters are:

[0010] S4-1: Retrieve planning parameters, including the location of the adjusted mine car, the driving index, and the road state value corresponding to each road section in the 3D map of the mining area. Sorting the adjusted mine cars in descending order according to the driving index corresponding to the adjusted mine cars, and selecting the adjusted mine car with the largest driving index as the target mine car;

[0011] S4-2: Take the location of the target mine car as the starting point, obtain the destination of the target mine car, and use the Dijkstra algorithm to generate several paths from the starting point to the target point; select any one of the paths, obtain the traffic flow of each section of the path in real time, and analyze the congestion degree of each path to obtain the congestion value;

[0012] S4-3: The road state value PQ of each section in the path and the driving index RU of the mine car are normalized and their values ​​are taken. The values ​​are calculated and analyzed by formula to obtain the adaptation index PR of each section. The specific calculation formula is:

[0013]

[0014] Where f1 and f2 are respectively set proportional constants, from which the adaptation index of each section in the path and the target mine car can be obtained, the smallest adaptation index is selected, and the adaptation index of each section and the target mine car is averaged to obtain the adaptation mean;

[0015] S4-4: Calculate the length of each section in the path, and sum them up to get the distance value of the path, record it as H; record the congestion value Ld, the adaptation mean The minimum adaptation index PRmin and the distance value H are normalized and their values ​​are taken. The values ​​are calculated by formula to obtain the planning value LG of the path, thereby obtaining the planning values ​​corresponding to several paths of the target mine car; the specific calculation formula is:

[0016]

[0017] Among them, μ1, μ2, μ3, and μ4 are the set proportional constants;

[0018] S4-5: Select the path with the largest planning value as the target path of the target mine car, control the target mine car to travel according to its corresponding target path, so as to minimize the impact of the mining area road on the mine car and achieve the purpose of ensuring the driving safety of the mine car; obtain the road state value PQ of each section in the target path of the target mine car, and compare it with the driving index RU of the target mine car through the set formula Calculate and obtain the maximum speed limit Vmax of each section in each target path, and control the speed of the target mine car in each section of the target path not to exceed the maximum speed limit Vmax; wherein n1 and n2 are respectively the set proportional coefficients, and φ is the set speed conversion coefficient;

[0019] S4-6: Repeat steps S4-1 to S4-5 until all the mine carts are adjusted.

[0020] Optionally, analyze the congestion level of each path, specifically:

[0021] The traffic volume of each section in the path is retrieved and compared with the set traffic volume interval. When the traffic volume is greater than the maximum value in the set traffic volume interval, a highly congested section is accumulated; when the traffic volume is within the set traffic volume interval, a moderately congested section is accumulated; when the traffic volume is less than the minimum value in the set traffic volume interval, a lightly congested section is accumulated; the cumulative number of highly congested sections, moderately congested sections and lightly congested sections in the path is counted and recorded as L1, L2 and L3 respectively; the traffic volume of each section in the path is averaged and the average traffic volume is calculated and recorded as L4;

[0022] The congestion value Ld of the path is obtained by formulating and analyzing the cumulative number of highly congested sections L1, the cumulative number of moderately congested sections L2, the cumulative number of lightly congested sections L3 and the average traffic volume L4; the specific calculation formula is:

[0023]

[0024] Wherein d1, d2, and d3 are respectively set proportional constants, and d1>d2>d3>2.

[0025] Optionally, the specific process of analyzing the road surface status of each road section according to the road information of each road section is as follows:

[0026] 401: Retrieving road surface information of each road section, the specific road surface information includes the number of slope sections and the slope and slope length corresponding to each slope section, the number of curve sections and the curve radius and curve length corresponding to each curve section, the road surface defect type and the defect number, defect area and defect height corresponding to each type of defect;

[0027] 402: normalizing the slope and slope length corresponding to each slope section in the road section and obtaining the values ​​thereof, performing weighted calculation on the values ​​to obtain the slope-related value of each slope section, and analyzing the influence of each slope section on the driving of the mine car according to the driving direction of the mine car to obtain the slope section value of the road section;

[0028] 403: The curve radius and curve length corresponding to each curve in the road section are recorded as W1 and W2 respectively, and they are normalized and their values ​​are obtained. The values ​​are calculated by formula to obtain the curve-related value Wβ corresponding to each curve. The specific calculation formula is:

[0029]

[0030] Where β1 and β2 are respectively set proportional constants; the curvature of the road section is analyzed according to the bend-related value corresponding to each bend to obtain the bend value of the road section;

[0031] 404: Set each type of defect to correspond to a type value, thereby obtaining the type value corresponding to each type of defect; randomly select a type of defect, traverse the corresponding defect quantity and the defect area and defect height corresponding to each defect, normalize the defect area and defect height and take their values, perform formula calculation and analysis on the values ​​to obtain the defect value; thereby obtaining the defect value corresponding to each defect under the defect type, and summing them up to obtain the total defect value of the defect type; multiplying the total defect value of each type of defect by the corresponding type value to obtain the defect assessment value of each type of defect, and summing them up to obtain the defect risk value of the road section;

[0032] 405: The slope value Pd, the curve value Wd and the defect risk value Qd of the road section are calculated by formulating the set formula to obtain the road state value PQ of the road section. The specific calculation formula is:

[0033] PQ=α1×e Pd +α2×e Wd +α3×e Qd

[0034] Among them, α1, α2, and α3 are respectively set proportional constants; thus, the road status value of each section in the 3D map of the mining area can be obtained and marked in the 3D map of the mining area.

[0035] Optionally, the slope value of the road section is obtained by analyzing the influence of each slope section on the driving direction of the mine car. The specific analysis process is as follows:

[0036] According to the forward direction of the mine car, identify the slope direction of each slope section for the mine car, specifically uphill and downhill; classify the slope sections according to the slope direction, sum up the slope-related values ​​corresponding to the slope sections with a downhill slope direction to obtain the downhill slope-related total value recorded as P1, and then sum up the slope-related values ​​corresponding to the slope sections with an uphill slope direction to obtain the slope-related total value P2, and perform formula calculation and analysis on the downhill slope-related total value P1 and the uphill slope-related total value P2 to obtain the slope section value Pd of the road section. The specific calculation formula is:

[0037] Pd=d1×P 1 +d2×P 2

[0038] Wherein d1 and d2 are respectively set proportional constants, and d1>d2.

[0039] Optionally, the curvature of the road section is analyzed according to the bend-related value corresponding to each bend, specifically:

[0040] The curve-related value of each curve is compared and analyzed with the set curve interval. When the curve-related value is greater than the set upper limit of the curve interval, a severe curve is accumulated; when the curve-related value is within the set curve interval, a moderate curve is accumulated; when the curve-related value is less than the set lower limit of the curve interval, a mild curve is accumulated; the cumulative number of severe curves, moderate curves and mild curves in the road section is counted and recorded as D1, D2 and D3 respectively; the curve-related values ​​of each curve are summed up to obtain a total curve-related value recorded as D4;

[0041] The cumulative number of heavy and medium curves D1, the cumulative number of medium curves D2, the cumulative number of light curves D3 and the total value of curves D4 are calculated and analyzed to obtain the curve value Wd. The specific calculation formula is:

[0042]

[0043] Among them, β3, β4, and β5 are respectively set proportional constants, and β3>β4>β5>1.

[0044] Optionally, based on the driving information of each mine car, feature extraction is performed on the driving state of each mine car to obtain a driving index that comprehensively measures the driving state of the mine car. The specific process is:

[0045] 701: retrieve the driving information of the mine car at each collection time, the specific driving information includes vehicle speed, tire pressure of each tire, vibration amplitude, engine temperature, engine load, vehicle body inclination, impact force, and record them as Vi, Yi1, Yi2, Yi3, Yi4, Zi, Ti, Fi, θi and Ci respectively; wherein i=1, 2, 3...I, I is a positive integer, I represents the total number of collection time, i represents the number of any collection time; superscripts 1, 2, 3 and 4 represent the number of the mine car tires; set a driving standard parameter corresponding to the mine car, the specific driving standard parameters include standard tire pressure, standard engine temperature, standard engine load, and mark them as HY, HT and HF;

[0046] 702: Perform a comprehensive analysis on tire pressure unevenness and tire pressure level according to the tire pressures of the four tires of the mine car and the standard tire pressure to obtain tire values ​​at each collection time;

[0047] 703: The tire value GYi, vibration amplitude Zi, engine temperature Ti, engine load Fi, vehicle body inclination θi, impact force Ci, standard engine temperature HT, and standard engine load HF at each collection time are normalized and their values ​​are taken. The values ​​are calculated and analyzed by formula to obtain the driving state value Ri at each collection time. The specific calculation formula is:

[0048]

[0049] Among them, η1, η2, η3, η4, and η5 are the set proportional constants respectively;

[0050] 704: construct a two-dimensional rectangular coordinate system with time as the horizontal coordinate and the driving state value as the vertical coordinate, input the driving state value into the coordinate system according to its corresponding collection time, and record the position of the driving state value in the coordinate system as a driving point; use a smooth curve to connect each driving point in sequence to obtain a driving state value curve graph of the mine car;

[0051] 705: Analyze the driving state of the mine car according to the driving state value curve diagram of the mine car to obtain a driving index.

[0052] Optionally, a comprehensive analysis of tire pressure unevenness and tire pressure level is performed based on the tire pressure of the four tires of the mine car and the standard tire pressure, specifically:

[0053] Compare the tire pressures Yi1, Yi2, Yi3, and Yi4 with the standard tire pressure HF. If the tire pressure is greater than the standard tire pressure, the difference between the two is calculated to obtain the high tire pressure difference; if the tire pressure is less than the standard tire pressure, the difference between the two is calculated to obtain the low tire pressure; calculate the average of each high tire pressure difference and low tire pressure difference to obtain the high pressure difference average and the low pressure difference average, and record them as G1 and G2 respectively; normalize the high pressure difference average G1, the low pressure difference average G2, and the tire pressures Yi1, Yi2, Yi3, and Yi4 and take their values, and perform formulaic calculation and analysis on the values ​​to obtain the tire value GYi; the specific calculation formula is:

[0054]

[0055] Among them, γ1, γ2, and γ3 are the set proportional constants, 1<γ1<γ2<γ3, is the average tire pressure of the mine car's four tires.

[0056] Optionally, the driving state of the mine car is analyzed according to the driving state value curve of the mine car, specifically:

[0057] A tangent line is drawn at each driving point, and the slope of the tangent line is calculated by data fitting and recorded as the trend value Ai; the trend values ​​greater than zero are summed up to obtain the trend increase degree, which is recorded as U1, and the trend values ​​less than zero are summed up and then the absolute value is taken to obtain the trend decrease degree, which is recorded as U2;

[0058] The driving state value Ri, trend value Ai, trend increase degree U1 and trend decrease degree U2 at each collection time are calculated and analyzed by formulating and analyzing to obtain the driving index RU. The specific calculation formula is:

[0059]

[0060] Among them, δ1, δ2, and δ3 are the set proportional constants, is the mean trend value of each driving point.

[0061] The second aspect of the present invention provides a mine car driving state safety detection device, comprising: a memory, a road section detection module, a driving detection module and a safety management module, so that the device executes the above-mentioned mine car driving state safety detection method;

[0062] The memory communicates with the mine car and the sensors mounted on the mine car to collect the driving information of the mine car in real time; at the same time, sensors are deployed on the roads in the mining area to monitor and collect road information in real time;

[0063] The road section detection module uses drones or fixed cameras to conduct road inspections and collect images to build a 3D map of the mining area, and divides the roads in the mining area into several sections. The road surface status of each section is analyzed based on the road information of each section to obtain the road status value.

[0064] The driving detection module extracts the driving status of each mine car based on its driving information to obtain a driving index that comprehensively measures the driving status of the mine car, and judges the driving safety of each mine car based on this, and displays it in real time on the 3D map; specifically:

[0065] If the driving index is greater than the maximum value in the set safety interval, the mine car will be recorded as an abnormal mine car, and the location of the abnormal mine car will be obtained in real time, and the abnormal mine car will be controlled to travel to the safe area closest to the current position;

[0066] If the driving index is within the set safety range, it will be marked as an adjustment mine car, and the current location of the adjustment mine car will be obtained in real time. It will be integrated with the driving index corresponding to the adjustment mine car, the 3D map of the mining area, and the road status values ​​corresponding to each section as planning parameters, and sent to the safety management module;

[0067] If the driving index is less than the minimum value in the set safety interval, the mine car will be marked as a normal mine car, and the current location of the normal mine car and its corresponding destination will be obtained in real time. The K shortest path algorithm is used to obtain the closest path from the current location to the destination, and it is used as the target path of the normal mine car. The mine car is controlled to travel according to its corresponding target path; abnormal mine cars, adjusted mine cars and normal mine cars are tracked and displayed in red, yellow and green in the 3D map of the mining area respectively;

[0068] The safety management module dynamically adjusts the mine car based on the planning parameters to optimize the running path and speed of the mine car.

[0069] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0070] 1. By using drones or fixed cameras to build a 3D map of the mining area and dividing the roads in the mining area into sections, the road network in the mining area can be managed in a refined manner. The road conditions of each section (such as slopes, curves, road defects, etc.) are quantitatively evaluated through detailed data collection and analysis to obtain the road condition value of each section; it can objectively reflect the potential risks of the road and provide data support for the driving and scheduling of mining vehicles in the mining area;

[0071] 2. By extracting key parameters (such as vehicle speed, tire pressure, vibration amplitude, etc.) from the driving information of the mine car, calculating the driving state value and driving index, the driving state of the mine car can be monitored in real time, abnormal situations can be discovered in time, and the driving safety of the mine car can be more comprehensively evaluated, providing data support for subsequent driving path and speed optimization; the mine car will be optimized according to the driving index, and the specific abnormal mine car will be guided to the safe area to ensure its safety; the adjusted mine car will optimize the path and speed according to the planning parameters to minimize the risk; the normal mine car will travel along the optimized path to improve the overall operation efficiency;

[0072] 3. Generate multiple paths based on the Dijkstra algorithm, and select the optimal path by calculating the congestion value, adaptation index and planning value, reduce the impact of the road conditions on the mine car, ensure the driving safety of the mine car in the mining area, and dynamically adjust the driving path and speed of the mine car according to the driving index and road state value of the mine car, reduce mutual interference between mine cars, and reduce potential safety risks;

[0073] In summary, the present invention constructs a mine car safety detection system based on comprehensive analysis of multi-vehicle data, road condition assessment and intelligent scheduling, which effectively reduces the risk of accidents occurring during the driving of mine cars and ensures safe production in mining areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0075] Figure 1 is a flow chart of the method of the present invention;

[0076] Figure 2 This is a connection diagram of the device modules of the present invention. DETAILED DESCRIPTION

[0077] Embodiments of the present invention provide a method and device for safely detecting the driving state of a mine car. The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present invention are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0078] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 In an embodiment of the present invention, a method for detecting the safe driving state of a mine car is provided. Specifically, the method comprises the following steps:

[0079] Step 1: Communicate with the mine car and the sensors mounted on the mine car to collect the driving information of the mine car in real time. The specific sensors include vehicle-mounted sensors, GPS positioning, tilt angle sensors, vibration sensors, tire pressure sensors, etc. At the same time, sensors are deployed on the roads in the mining area to monitor and collect road information in real time;

[0080] Step 2: Use drones or fixed cameras to inspect roads and collect images to build a 3D map of the mining area, and divide the roads in the mining area into several sections. Analyze the road surface status of each section based on the road information to obtain the road status value; specifically:

[0081] Retrieve the pavement information of each road section. The specific pavement information includes the number of slope sections and the slope and slope length corresponding to each slope section, the number of curve sections and the curve radius and curve length corresponding to each curve section, the types of pavement defects and the number of defects corresponding to each type of defect, the defect area and the defect height; it should be noted that pavement defects mainly refer to potholes and bulges, and the defect height refers to the depth of the pothole or the height of the bulge. Specifically, the defect height refers to the maximum vertical distance between the pavement and the bottom of the pothole or the distance between the top of the bulge and the pavement;

[0082] The slope and slope length corresponding to each slope section in the road section are normalized and their values ​​are taken, and the values ​​are weighted to obtain the slope-related value of each slope section; according to the forward direction of the mine car, the slope direction of each slope section for the mine car is identified (the specific slope direction is divided into uphill and downhill. For the mine car, the technical personnel in this field found in simulation experiments that the risk of downhill is greater than that of uphill); the slope sections are classified according to the slope direction, and the slope-related values ​​corresponding to the slope sections with a downhill slope direction are summed to obtain the downhill slope-related total value recorded as P1, and then the slope-related values ​​corresponding to the slope sections with an uphill slope direction are summed to obtain the slope-related total value P2, and the downhill slope-related total value P1 and the uphill slope-related total value P2 are formulaically calculated and analyzed to obtain the slope section value Pd of the road section. The specific calculation formula is:

[0083] Pd=d1×P 1 +d2×P 2

[0084] Where d1 and d2 are respectively set proportional constants, and d1>d2; it should be noted that the greater the slope, the greater the difficulty and risk of the mine car going uphill or downhill;

[0085] The curve radius and curve length corresponding to each curve in the road section are recorded as W1 and W2 respectively, and they are normalized and their values ​​are taken. The values ​​are calculated by formula to obtain the curve-related value Wβ corresponding to each curve. The specific calculation formula is:

[0086]

[0087] Where β1 and β2 are respectively set proportional constants. It should be noted that the shorter the curve radius, the greater the curvature of the curve, and the greater the risk of vehicle rollover or accident; the curve-related value of each curve is compared and analyzed with the set curve interval. When the curve-related value is greater than the set upper limit of the curve interval, a severe curve is accumulated; when the curve-related value is in the set curve interval, a moderate curve is accumulated; when the curve-related value is less than the set lower limit of the curve interval, a mild curve is accumulated; the cumulative number of severe curves, moderate curves and mild curves in the road section is counted, and they are recorded as D1, D2 and D3 respectively; the curve-related values ​​of each curve are summed up to obtain the total curve-related value recorded as D4; the cumulative number of severe curves D1, the cumulative number of moderate curves D2, the cumulative number of mild curves D3 and the total curve-related value D4 in the road section are formulaically calculated and analyzed to obtain the curve value Wd. The specific calculation formula is:

[0088]

[0089] Among them, β3, β4, and β5 are set proportional constants, and β3>β4>β5>1;

[0090] Each type of defect is set to correspond to a type value. It should be noted that different defect types have different damages to the mine car, so different types of defects correspond to different type values. The larger the type value, the greater the damage to the mine car. For example, the type value of the pothole is greater than the type value of the protrusion. Thus, the type value corresponding to each type of defect can be obtained, and it is recorded as η; any type of defect is selected, the corresponding number of defects and the defect area and defect height corresponding to each defect are traversed, the defect area and defect height are normalized and their values ​​are taken, and the values ​​are calculated and analyzed by formula to obtain the defect value; thus, the defect value corresponding to each defect under the defect type can be obtained, and the total defect value of the defect type is obtained by summing them up; the total defect value of each type of defect is multiplied by the corresponding type value to obtain the defect assessment value of each type of defect, and the defect risk value of the road section is obtained by summing them up, and it is recorded as Qd;

[0091] The slope value Pd, curve value Wd and defect risk value Qd of the road section are calculated by formulating the set formula to obtain the road state value PQ of the road section. The specific calculation formula is:

[0092] PQ=α1×e Pd +α2×e Wd +α3×e Qd

[0093] Among them, α1, α2, and α3 are respectively set proportional constants. It can be seen from the formula that when there are more slopes in the road section, the higher the slope, the more curved the curves, and the more defects on the road surface, the larger the road state value of the corresponding road section is, indicating that the road section is more dangerous, which will increase the uncertainty and risk of mine car driving, resulting in increased damage risk and accident probability of mine cars, especially when mine cars are basically under high load-bearing conditions; thus, the road state value of each road section in the 3D map of the mining area can be obtained and marked in the 3D map of the mining area;

[0094] By using drones or fixed cameras to build a 3D map of the mining area and dividing the roads in the mining area into sections, the road network in the mining area can be managed in a refined manner. The road condition of each section (such as slopes, curves, road defects, etc.) is quantitatively evaluated through detailed data collection and analysis to obtain the road condition value of each section. It can objectively reflect the potential risks of the road and provide data support for the driving scheduling of mine cars in the mining area.

[0095] Step 3: Based on the driving information of each mine car, the driving status of each mine car is extracted to obtain a driving index that comprehensively measures the driving status of the mine car, and the driving safety of each mine car is judged accordingly, and it is displayed in real time on the 3D map; specifically:

[0096] The driving information of the mine car at each collection time is retrieved, and the specific driving information includes vehicle speed, tire pressure of each tire, vibration amplitude, engine temperature, engine load, body inclination, impact force (refers to the impact force encountered by the mine car when driving on a bumpy road. The greater the impact, the greater the risk of damage to the structure and components of the mine car. Even when the impact force is large enough, it may cause the mine car to malfunction or the driver to lose control of the mine car), and it is recorded as Vi, Yi1, Yi2, Yi3, Yi4, Zi, Ti, Fi, θi and Ci respectively; where i = 1, 2, 3 ... I, I is a positive integer, I represents the total number of collection times, i represents the number of any collection time; superscripts 1, 2, 3 and 4 represent the number of mine car wheels. Tire number; It should be noted that if the tire pressure is low or uneven, it means that the mine car is at risk of tire damage, severe wear or deflation, which not only affects the stability of the mine car, but also may increase the potential safety hazards of driving, especially when driving at high speeds or on complex roads; The larger the vibration amplitude, the more violent the vibration of the mine car, which will affect the long-term service life of the mine car and even cause structural damage; Excessive vibration amplitude indicates poor stability of the mine car; Excessive engine temperature may mean that the engine is overloaded, which will affect the overall performance and safety of the mine car; Excessive engine load may cause the mine car to be underpowered, especially when driving uphill or loaded, increasing the risk of failure or accidents; When the tilt angle of the mine car body is large, it means that the mine car is at risk of overturning;

[0097] Set a driving standard parameter for the mine car. The specific driving standard parameters include standard tire pressure, standard engine temperature, standard engine load, and mark them as HY, HT and HF. It should be noted that the driving standard parameters (standard tire pressure, standard engine temperature, standard engine load) are usually set based on the design requirements of the mine car manufacturer, the working environment of the mine car and the purpose of use. They represent the key operating indicators that the mine car should maintain under normal and safe working conditions, helping to ensure the best performance and safety of the mine car in various working environments.

[0098] According to the tire pressures Yi1, Yi2, Yi3, Yi4 of the four tires of the mine car and the standard tire pressure HF, a comprehensive analysis is performed on the tire pressure unevenness and tire pressure level to obtain the tire value at each collection moment. The specific analysis method is as follows:

[0099] Compare the tire pressures Yi1, Yi2, Yi3, and Yi4 with the standard tire pressure HF respectively. If the tire pressure is greater than the standard tire pressure, the difference between the two is calculated to obtain the high tire pressure difference; if the tire pressure is less than the standard tire pressure, the difference between the two is calculated to obtain the low tire pressure value; it should be noted that for mine cars, low tire pressure is usually more dangerous, because it not only directly affects the stability of the mine car, but also easily leads to problems such as tire overheating, damage and tire blowout. Especially when the load is heavy and the driving time is long, the risk of low tire pressure will be higher; calculate the mean of each high tire pressure difference and low tire pressure difference to obtain the high pressure difference mean and low pressure difference mean, and record them as G1 and G2 respectively; normalize the high pressure difference mean G1, the low pressure difference mean G2, and the tire pressures Yi1, Yi2, Yi3, and Yi4 and take their values, and perform formulaic calculation and analysis on the values ​​to obtain the tire value GYi; the specific calculation formula is:

[0100]

[0101] Among them, γ1, γ2, and γ3 are the set proportional constants, 1<γ1<γ2<γ3, is the average tire pressure of the four tires of the mine car; from the formula, we can see that when the tire pressure of the mine car tire is more uneven, the tire value is larger;

[0102] The tire value GYi, vibration amplitude Zi, engine temperature Ti, engine load Fi, vehicle body inclination θi, impact force Ci, standard engine temperature HT, and standard engine load HF at each collection time are normalized and their values ​​are taken. The values ​​are calculated and analyzed by formula to obtain the driving state value Ri at each collection time. The specific calculation formula is:

[0103]

[0104] Among them, η1, η2, η3, η4, and η5 are respectively set proportional constants. It can be seen from the formula that when the tire value is larger, the vibration amplitude is larger, the body inclination is larger, and the impact force is larger, the risk of mine car driving will be greater, and the corresponding driving state value will be larger; if the engine temperature and engine load of the mine car deviate from the standard engine temperature and standard engine load, it means that the risk of mine car driving is greater, and the corresponding driving state value is larger;

[0105] A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the driving state value as the vertical coordinate. The driving state value is input into the coordinate system according to its corresponding collection time, and the position of the driving state value in the coordinate system is recorded as a driving point; a smooth curve is used to connect each driving point in sequence to obtain a driving state value curve diagram of the mine car; a tangent line of the curve is drawn at each driving point, and the slope of the tangent line is obtained by data fitting calculation and recorded as the trend value Ai. It should be noted that when the trend value is greater than zero, it means that the driving state value is in an increasing trend, and the larger the trend value, the more significant its increasing trend; when the trend value is less than zero, it means that the driving state value is in a decreasing trend, and the smaller the trend value, the more significant its decreasing trend; the trend values ​​greater than zero are summed up to obtain the trend increase degree and recorded as U1, and the trend values ​​less than zero are summed up and then the absolute value is taken to calculate the trend decrease degree and recorded as U2; the driving state value Ri, trend value Ai, trend increase degree U1 and trend decrease degree U2 at each collection time are formulaically calculated and analyzed to obtain the driving index RU, and the specific calculation formula is:

[0106]

[0107] Among them, δ1, δ2, and δ3 are the set proportional constants, is the average trend value of each driving point. From the formula, we can know that when the trend increases, the trend decreases, and the driving index increases. If the driving state value is more unstable, it means that the driving state of the mine car is more unstable, and the driving index increases.

[0108] If the driving index is greater than the maximum value in the set safety interval, it means that the driving abnormality of the mine car is more significant and the risk of danger is greater if it continues to drive. In this case, the mine car will be recorded as an abnormal mine car, and the location of the abnormal mine car will be obtained in real time. The abnormal mine car will be controlled to drive to the safe area closest to the current location, so that abnormal maintenance can be carried out in time.

[0109] If the driving index is within the set safety range, it means that the mine car has a certain safety risk, so it is marked as an adjustment mine car, and the current location of the adjustment mine car is obtained in real time. It is integrated with the driving index corresponding to the adjustment mine car, the 3D map of the mining area, and the road status values ​​corresponding to each section as planning parameters, and sent to Step 4;

[0110] If the driving index is less than the minimum value in the set safety interval, it means that the mine car is normal, then the mine car is marked as a normal mine car, and the current location of the normal mine car and its corresponding destination (usually the entrance or exit of the mining area) are obtained in real time. The K shortest path algorithm is used to obtain the shortest path from the current location to the destination, and it is used as the target path of the normal mine car, and the mine car is controlled to travel according to its corresponding target path;

[0111] Abnormal mine cars, adjusted mine cars and normal mine cars are tracked and displayed in red, yellow and green colors respectively on the 3D map of the mining area; the driving index of the mine cars is displayed in real time on the 3D map, and abnormal, adjusted and normal mine cars are marked with different colors, so that managers can intuitively understand the operation status of the mine cars;

[0112] By extracting key parameters from the mine car's driving information (such as vehicle speed, tire pressure, vibration amplitude, etc.), calculating the driving status value and driving index, it is possible to monitor the mine car's driving status in real time, detect abnormal situations in a timely manner, and more comprehensively evaluate the mine car's driving safety, providing data support for subsequent driving path and speed optimization; the mine car will be optimized and adjusted differently according to the driving index, and specific abnormal mine cars will be guided to safe areas to ensure their safety; the adjusted mine car will optimize the path and speed according to the planning parameters to minimize risks; normal mine cars will travel along the optimized path to improve overall operational efficiency.

[0113] Step 4: Dynamically adjust the mine cart based on the planning parameters to optimize the running path and speed of the mine cart to reduce mutual interference and potential safety risks; specifically:

[0114] S4-1: Retrieve planning parameters, including the location of the adjusted mine car, the driving index, and the road state value corresponding to each road section in the 3D map of the mining area. Sorting the adjusted mine cars in descending order according to the driving index corresponding to the adjusted mine cars, and selecting the adjusted mine car with the largest driving index as the target mine car;

[0115] S4-2: Take the location of the target mine car as the starting point, obtain the destination of the target mine car, and use the Dijkstra algorithm to generate several paths from the starting point to the target point; select any one of the paths, obtain the traffic flow of each section in the path in real time, and compare and analyze it with the set traffic flow interval. When the traffic flow is greater than the maximum value in the set traffic flow interval, a highly congested section is accumulated; when the traffic flow is within the set traffic flow interval, a moderately congested section is accumulated; when the traffic flow is less than the set traffic flow, a moderately congested section is accumulated. When the minimum value in the interval is reached, a lightly congested section is accumulated; the cumulative number of highly congested sections, moderately congested sections and lightly congested sections in the path is counted, and they are recorded as L1, L2 and L3 respectively; the traffic flow of each section in the path is averaged to obtain the average traffic flow and recorded as L4; the cumulative number of highly congested sections L1, the cumulative number of moderately congested sections L2, the cumulative number of lightly congested sections L3 and the average traffic flow L4 are calculated and analyzed in a formula to obtain the congestion value Ld of the path; the specific calculation formula is:

[0116]

[0117] Where d1, d2, and d3 are respectively set proportional constants, and d1>d2>d3>2;

[0118] S4-3: The road state value PQ of each section in the path and the driving index RU of the mine car are normalized and their values ​​are taken. The values ​​are calculated and analyzed by formula to obtain the adaptation index PR of each section. The specific calculation formula is:

[0119]

[0120] Among them, f1 and f2 are respectively the set proportional constants. It can be seen from the formula that when the driving index is larger, the road state value is larger, which means that the road section is less adaptable to the target mine car, and the adaptability index is smaller; when the road state value is smaller, it means that the road section is more adaptable to the target mine car, and the adaptability index is larger; thus, the adaptability index of each road section in the path and the target mine car can be obtained, and the smallest adaptability index is selected as PRmin, and the adaptability index of each road section and the target mine car is averaged to obtain the adaptation mean value recorded as

[0121] S4-4: Calculate the length of each section in the path, and sum them up to get the distance value of the path, record it as H; record the congestion value Ld, the adaptation mean The minimum adaptation index PRmin and the distance value H are normalized and their values ​​are taken. The values ​​are calculated by formula to obtain the planning value LG of the path, thereby obtaining the planning values ​​corresponding to several paths of the target mine car; the specific calculation formula is:

[0122]

[0123] Among them, μ1, μ2, μ3, and μ4 are respectively set proportional constants. It can be seen from the formula that when the path is more congested, the planning value is smaller; when the path is longer, the planning value is smaller; when the adaptation mean of the path is larger, it means that the road state of the path has less impact on the mine car, and the planning value is larger; when the minimum adaptation value is larger, the planning value is larger;

[0124] S4-5: Select the path with the largest planning value as the target path of the target mine car, control the target mine car to travel according to its corresponding target path, so as to minimize the impact of the mining area road on the mine car and achieve the purpose of ensuring the driving safety of the mine car; obtain the road state value PQ of each section in the target path of the target mine car, and compare it with the driving index RU of the target mine car through the set formula Calculate and obtain the maximum speed limit Vmax of each section in each target path, and control the speed of the target mine car in each section of the target path not to exceed the maximum speed limit Vmax; wherein n1 and n2 are respectively the set proportional coefficients, and φ is the set speed conversion coefficient;

[0125] S4-6: Repeat steps S4-1 to S4-5 until all adjustment mine cars are adjusted;

[0126] By generating multiple paths based on the Dijkstra algorithm and calculating the congestion value, adaptation index and planning value, the optimal path is selected to reduce the impact of the road conditions on the mine car and ensure the driving safety of the mine car in the mining area. According to the driving index and road status value of the mine car, the driving path and speed of the mine car are dynamically adjusted to reduce mutual interference between mine cars and reduce potential safety risks.

[0127] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 2 ,In an embodiment of the present invention, a mine car driving state safety detection device includes: a memory, a road section detection module, a driving detection module and a safety management module;

[0128] The memory communicates with the mine car and the sensors mounted on the mine car to collect the driving information of the mine car in real time; at the same time, sensors are deployed on the roads in the mining area to monitor and collect road information in real time;

[0129] The road section detection module uses drones or fixed cameras to conduct road inspections and collect images to build a 3D map of the mining area, and divides the roads in the mining area into several sections. The road surface status of each section is analyzed based on the road information of each section to obtain the road status value.

[0130] The driving detection module extracts the driving status of each mine car based on its driving information to obtain a driving index that comprehensively measures the driving status of the mine car, and judges the driving safety of each mine car based on this, and displays it in real time on the 3D map; specifically:

[0131] If the driving index is greater than the maximum value in the set safety interval, the mine car will be recorded as an abnormal mine car, and the location of the abnormal mine car will be obtained in real time, and the abnormal mine car will be controlled to travel to the safe area closest to the current position;

[0132] If the driving index is within the set safety range, it will be marked as an adjustment mine car, and the current location of the adjustment mine car will be obtained in real time. It will be integrated with the driving index corresponding to the adjustment mine car, the 3D map of the mining area, and the road status values ​​corresponding to each section as planning parameters, and sent to the safety management module;

[0133] If the driving index is less than the minimum value in the set safety interval, the mine car will be marked as a normal mine car, and the current location of the normal mine car and its corresponding destination will be obtained in real time. The K shortest path algorithm is used to obtain the closest path from the current location to the destination, and it is used as the target path of the normal mine car. The mine car is controlled to travel according to its corresponding target path; abnormal mine cars, adjusted mine cars and normal mine cars are tracked and displayed in red, yellow and green in the 3D map of the mining area respectively;

[0134] The safety management module dynamically adjusts the mine car based on the planning parameters to optimize the running path and speed of the mine car.

[0135] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0136] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting the safe driving state of a mine car, characterized in that: The following steps are involved: Step 1: Communicate with the mine car and the sensors mounted on the mine car to collect the driving information of the mine car in real time; at the same time, sensors are deployed on the roads in the mining area to monitor and collect road information in real time; Step 2: Use drones or fixed cameras to conduct road inspections and collect images to build a 3D map of the mining area, and divide the roads in the mining area into several sections accordingly; Analyze the road surface status of each road section according to the road information of each road section to obtain a road status value; Step 3: Based on the driving information of each mine car, the driving status of each mine car is feature extracted to obtain a driving index that comprehensively measures the driving status of the mine car, and the driving safety of each mine car is judged accordingly, and it is displayed in real time on the 3D map; if the driving index is greater than the maximum value in the set safety interval, the mine car is recorded as an abnormal mine car, and the position of the abnormal mine car is obtained in real time, and the abnormal mine car is controlled to travel to the safe area closest to the current position; if the driving index is within the set safety interval, it is marked as an adjustment mine car, the current position of the adjustment mine car is obtained in real time, and it is compared with the corresponding The driving index, the 3D map of the mining area, and the road status values ​​corresponding to each section are integrated into the planning parameters and sent to Step 4; if the driving index is less than the minimum value in the set safety interval, the mine car is marked as a normal mine car, and the current position of the normal mine car and its corresponding destination are obtained in real time. The K shortest path algorithm is used to obtain the closest path from the current position to the destination, and it is used as the target path of the normal mine car, and the mine car is controlled to travel according to its corresponding target path; abnormal mine cars, adjusted mine cars, and normal mine cars are tracked and displayed in red, yellow, and green in the 3D map of the mining area respectively; Step 4: Dynamically adjust the mine cart based on the planning parameters to optimize the running path and speed of the mine cart.

2. A mine car driving state safety detection method according to claim 1, characterized in that: The specific steps for dynamically adjusting the minecart based on planning parameters are: S4-1: Retrieve planning parameters, including the location of the adjusted mine car, the driving index, and the road state value corresponding to each road section in the 3D map of the mining area. Sorting the adjusted mine cars in descending order according to the driving index corresponding to the adjusted mine cars, and selecting the adjusted mine car with the largest driving index as the target mine car; S4-2: Take the location of the target mine car as the starting point, obtain the destination of the target mine car, and use the Dijkstra algorithm to generate several paths from the starting point to the target point; select any one of the paths, obtain the traffic flow of each section of the path in real time, and analyze the congestion degree of each path to obtain the congestion value; S4-3: normalizing the road state value of each section in the path and the driving index of the mine car and taking the numerical value, performing formula calculation and analysis on the numerical value to obtain the adaptation index of each section, thereby obtaining the adaptation index of each section in the path and the target mine car, selecting the smallest adaptation index, and calculating the average of the adaptation indexes of each section and the target mine car to obtain the adaptation mean; S4-4: Calculate the length of each section in the path, and sum them up to obtain the distance value of the path; normalize the congestion value, the adaptation mean, the minimum adaptation index and the distance value and take their values, and calculate the values ​​in a formula to obtain the planning value of the path, thereby obtaining the planning values ​​corresponding to several paths of the target mine car; S4-5: Select the path with the largest planning value as the target path of the target mine car, and control the target mine car to travel according to its corresponding target path; Obtain the road state value of each section in the target path of the target mine car, and perform numerical calculation and analysis on the road state value and the driving index of the target mine car to obtain the maximum speed limit Vmax of each section in the target path, and control the speed of the target mine car in each section of the target path not to exceed the maximum speed limit Vmax; S4-6: Repeat steps S4-1 to S4-5 until all the mine carts are adjusted.

3. A mine car driving state safety detection method according to claim 2, characterized in that: Analyze the congestion level of each path, specifically: The traffic volume of each section in the route is retrieved and compared with the set traffic volume interval. When the traffic volume is greater than the maximum value in the set traffic volume interval, a highly congested section is accumulated; when the traffic volume is within the set traffic volume interval, a moderately congested section is accumulated. When the traffic volume is less than the minimum value in the set traffic volume range, a lightly congested road section is accumulated; The cumulative number of highly congested sections, moderately congested sections, and slightly congested sections in the route is counted, and the traffic flow of each section in the route is averaged to obtain the traffic flow average; The congestion value of the path is obtained by formulating and analyzing the cumulative number of highly congested sections, the cumulative number of moderately congested sections, the cumulative number of lightly congested sections and the average traffic flow.

4. A mine car driving state safety detection method according to claim 1, characterized in that: The specific process of analyzing the road surface status of each section according to the road information of each section is as follows: 401: Retrieving road surface information of each road section, the specific road surface information includes the number of slope sections and the slope and slope length corresponding to each slope section, the number of curve sections and the curve radius and curve length corresponding to each curve section, the road surface defect type and the defect number, defect area and defect height corresponding to each type of defect; 402: normalizing the slope and slope length corresponding to each slope section in the road section and obtaining the values ​​thereof, performing weighted calculation on the values ​​to obtain the slope-related value of each slope section, and analyzing the influence of each slope section on the driving of the mine car according to the driving direction of the mine car to obtain the slope section value of the road section; 403: normalizing the curve radius and curve length corresponding to each curve in the road section and obtaining the values ​​thereof, formulaically calculating the values ​​to obtain a curve-related value corresponding to each curve; analyzing the curvature of the road section according to the curve-related value corresponding to each curve to obtain a curve value of the road section; 404: Set each type of defect to correspond to a type value, thereby obtaining the type value corresponding to each type of defect; randomly select a type of defect, traverse the corresponding defect quantity and the defect area and defect height corresponding to each defect, normalize the defect area and defect height and take their values, perform formula calculation and analysis on the values ​​to obtain the defect value; thereby obtaining the defect value corresponding to each defect under the defect type, and summing them up to obtain the total defect value of the defect type; multiplying the total defect value of each type of defect by the corresponding type value to obtain the defect assessment value of each type of defect, and summing them up to obtain the defect risk value of the road section; 405: The slope value, curve value and defect risk value of the road section are calculated by formulating the road state value of the road section; thereby, the road state value of each road section in the mining area 3D map can be obtained and marked in the mining area 3D map.

5. A mine car driving state safety detection method according to claim 4, characterized in that: According to the driving direction of the mine car, the influence of each slope section on the driving of the mine car is analyzed to obtain the slope value of the road section. The specific analysis process is as follows: According to the forward direction of the mine car, the slope direction of each slope section relative to the mine car is identified, specifically uphill and downhill; the slope sections are classified according to the slope direction, the slope-related values ​​corresponding to the slope sections with a downhill slope direction are summed up to obtain the slope-related total value of the downhill slope, and then the slope-related values ​​corresponding to the slope sections with an uphill slope direction are summed up to obtain the slope-related total value of the uphill slope, and the slope-related total value of the downhill slope and the slope-related total value of the uphill slope are formulated and analyzed to obtain the slope section value of the road section.

6. A mine car driving state safety detection method according to claim 5, characterized in that: The curvature of the road section is analyzed according to the bend-related value corresponding to each bend, specifically: The bend-related value of each bend is compared and analyzed with the set bend interval. When the bend-related value is greater than the set upper limit of the bend interval, a severe bend is accumulated; when the bend-related value is within the set bend interval, a moderate bend is accumulated; when the bend-related value is less than the set lower limit of the bend interval, a mild bend is accumulated; the cumulative number of severe bends, moderate bends and mild bends in the road section is counted, and the bend-related values ​​of each bend are summed up to obtain the total bend-related value; The cumulative number of severe bends, the cumulative number of medium bends, the cumulative number of mild bends and the total value related to bends are calculated and analyzed by formulating a curve value.

7. A mine car driving state safety detection method according to claim 1, characterized in that: Based on the driving information of each mine car, the driving state of each mine car is characterized and extracted to obtain a driving index that comprehensively measures the driving state of the mine car. The specific process is as follows: 701: retrieve the driving information of the mine car at each collection time, the specific driving information includes vehicle speed, tire pressure of each tire, vibration amplitude, engine temperature, engine load, vehicle body inclination, and impact force; set a driving standard parameter corresponding to the mine car, the specific driving standard parameters include standard tire pressure, standard engine temperature, and standard engine load; 702: Perform a comprehensive analysis on tire pressure unevenness and tire pressure level according to the tire pressures of the four tires of the mine car and the standard tire pressure to obtain tire values ​​at each collection time; 703: normalizing the tire value, vibration amplitude, engine temperature, engine load, vehicle body inclination, impact force, standard engine temperature, and standard engine load at each collection time and taking their values, and performing formula calculation and analysis on the values ​​to obtain the driving state value at each collection time; 704: construct a two-dimensional rectangular coordinate system with time as the horizontal coordinate and the driving state value as the vertical coordinate, input the driving state value into the coordinate system according to its corresponding collection time, and record the position of the driving state value in the coordinate system as a driving point; use a smooth curve to connect each driving point in sequence to obtain a driving state value curve graph of the mine car; 705: Analyze the driving state of the mine car according to the driving state value curve diagram of the mine car to obtain a driving index.

8. A mine car driving state safety detection method according to claim 7, characterized in that: According to the tire pressure of the four tires of the mine car and the standard tire pressure, a comprehensive analysis of the uneven tire pressure and tire pressure level is conducted, specifically: Compare the tire pressures of the four tires of the mine car with the standard tire pressure HF respectively. If the tire pressure is greater than the standard tire pressure, the difference between the two is calculated to obtain the high tire pressure difference; if the tire pressure is less than the standard tire pressure, the difference between the two is calculated to obtain the low tire pressure value; The high pressure difference average, low pressure difference average, and tire pressure of the four tires of the mine car are normalized and their values ​​are taken, and the values ​​are calculated and analyzed by formula to obtain the tire value.

9. A mine car driving state safety detection method according to claim 8, characterized in that: The driving state of the mine car is analyzed according to the driving state value curve of the mine car, specifically: Draw a tangent line of the curve at each driving point, and calculate the slope of the tangent line using data fitting as the trend value; The trend values ​​greater than zero are summed up to obtain the trend increase degree, and the trend values ​​less than zero are summed up and then the absolute value is taken to obtain the trend decrease degree; The driving state value, trend value, trend increase degree and trend decrease degree at each collection moment are calculated and analyzed in a formulaic manner to obtain the driving index.

10. A mine car driving state safety detection device, characterized in that: Applicable to a mine car driving state safety detection method as claimed in any one of claims 1 to 9, the device comprises: a memory, a road section detection module, a driving detection module and a safety management module; The memory communicates with the mine car and the sensors mounted on the mine car to collect the driving information of the mine car in real time; at the same time, sensors are deployed on the roads in the mining area to monitor and collect road information in real time; The road section detection module uses drones or fixed cameras to conduct road inspections and collect images to build a 3D map of the mining area, and divides the roads in the mining area into several sections. The road surface status of each section is analyzed based on the road information of each section to obtain the road status value. The driving detection module extracts the driving status of each mine car based on its driving information to obtain a driving index that comprehensively measures the driving status of the mine car, and judges the driving safety of each mine car based on this, and displays it in real time on the 3D map; specifically: If the driving index is greater than the maximum value in the set safety interval, the mine car will be recorded as an abnormal mine car, and the location of the abnormal mine car will be obtained in real time, and the abnormal mine car will be controlled to travel to the safe area closest to the current position; If the driving index is within the set safety range, it will be marked as an adjustment mine car, and the current location of the adjustment mine car will be obtained in real time. It will be integrated with the driving index corresponding to the adjustment mine car, the 3D map of the mining area, and the road status values ​​corresponding to each section as planning parameters, and sent to the safety management module; If the driving index is less than the minimum value in the set safety interval, the mine car will be marked as a normal mine car, and the current location of the normal mine car and its corresponding destination will be obtained in real time. The K shortest path algorithm is used to obtain the closest path from the current location to the destination, and it is used as the target path of the normal mine car. The mine car is controlled to travel according to its corresponding target path; abnormal mine cars, adjusted mine cars and normal mine cars are tracked and displayed in red, yellow and green in the 3D map of the mining area respectively; The safety management module dynamically adjusts the mine car based on the planning parameters to optimize the running path and speed of the mine car.

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