A smart spraying control system for sprinkler trucks

Abstract

This invention belongs to the field of intelligent control of vehicles in mining areas, and discloses an intelligent spraying control system for a sprinkler truck, including a detection device, a vehicle driving status acquisition module, a spraying controller, an actuator, and a human-machine interface. The detection device includes an onboard dust sensor, multiple fixed dust sensors, and a humidity sensor; the spraying controller includes a dust level generation module, a spraying control parameter generation module, and a control command output module. This invention generates a dust level by fusing multi-source dust data, determines the initial spray volume by combining vehicle speed, humidity, and road material, and makes safety corrections based on slope angle and curve radius, achieving intelligent and precise spraying control of the sprinkler truck, improving dust suppression efficiency, saving water resources, and ensuring safe driving on slopes and curves.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control of mining vehicles, and in particular relates to an intelligent spraying control system for water sprinkler trucks. Background Technology

[0002] During open-pit coal mining, operations such as stripping, transportation, and crushing generate a large amount of dust, which not only pollutes the air quality in and around the mining area but also poses a threat to the occupational health of workers. Water spraying is currently the main method for dust control in mining areas, suppressing the spread of dust into the air by spraying water mist along transport roads and in work areas.

[0003] Traditional watering operations rely heavily on manual judgment and operation. Drivers manually control the sprinkler switch and adjust the water volume based on visual assessment of road dust levels. This method has the following problems: I. In existing watering operations, drivers mainly rely on visual judgment to determine the degree of dust pollution. When visibility is low (such as at night or during sandstorms) or when drivers are distracted, it is difficult to accurately assess the road dust situation. In addition, visual judgment is subjective, and different drivers may have different judgments on the same degree of dust, resulting in inconsistent watering volume and unstable dust suppression effect.

[0004] II. Most existing sprinkler truck control systems adopt manual on / off or timed spraying modes. In manual mode, drivers rely on experience to control the start / stop of the sprinkler and the water volume, often exhibiting a "better too much than too little" mentality, leading to overspraying. In timed mode, the sprinkler truck sprays at fixed intervals and with a fixed water volume, unable to dynamically adjust according to the actual dust concentration on the road. This results in waste in areas with light dust and insufficient water in areas with heavy dust. Although dust sensors can achieve the function of adjusting the spray volume according to dust concentration, in practice, the factors affecting spraying effect and driving safety are multidimensional, including vehicle speed and air humidity. Single-parameter decision-making models cannot adapt to the complex and ever-changing mining environment, and there is still considerable room for improvement in spraying accuracy and dust suppression efficiency.

[0005] Third, the transportation roads in open-pit mines usually include uphill and downhill sections with different gradients and curves with different radii of curvature. When watering these sections, it is necessary to consider both dust suppression and driving safety. Water accumulation on the road surface will reduce the friction coefficient between the tires and the road surface and increase the braking distance, which is especially dangerous on slopes and curves. Summary of the Invention

[0006] This invention provides an intelligent spraying control system for water trucks, which solves the problems of traditional mining area water trucks relying on manual subjective judgment for water spraying, the inability of the spray volume to dynamically adapt to the environment, resulting in water waste and low safety.

[0007] The basic solution provided by this invention is: an intelligent spraying control system for sprinkler trucks, comprising: The detection device includes an on-board dust sensor, multiple fixed dust sensors, and a humidity sensor. The on-board dust sensor is used to detect the dust concentration data at the current location of the vehicle. The fixed dust sensors are used to detect the dust concentration data at a preset fixed point. The humidity sensor is used to detect the humidity data of the current area. The vehicle driving status acquisition module is used to acquire real-time vehicle location information and driving status data of the vehicle driving system. The driving status data includes vehicle speed, acceleration, angular velocity, and heading angle. The spray controller, which communicates with the detection device and the vehicle driving status acquisition module, includes: The dust level generation module is used to generate the dust level for the current location based on the dust concentration data of the current location of the detected vehicle and preset fixed points. The spray control parameter generation module is used to determine the initial spray control parameters based on the dust level at the current location, vehicle speed, humidity, and the material type of the road section the vehicle is currently traveling on; it is also used to calculate the current slope angle and curve radius of curvature of the vehicle based on the current acceleration and angular velocity of the vehicle, and to correct the initial spray control parameters based on the slope angle and curve radius of curvature to generate the corrected spray control parameters. The control command output module converts the corrected spraying control parameters into control commands and sends them to the actuator. The actuator is connected in communication with the spray controller and is used to perform spraying actions according to control commands; The human-machine interface communicates with the spray controller and is used to display detection data and spray control parameters.

[0008] Preferably, the detection device further includes a liquid level sensor for detecting the water tank level data of the sprinkler truck. The spray controller also includes an anomaly detection module, which is used to monitor the water tank level. When the water tank level is lower than the preset level, a level alarm is generated. It is also used to monitor the drive current of each motor in the actuator. When the drive current of any motor exceeds the preset stall current threshold of that motor and the duration exceeds the preset time threshold, a motor stall alarm is generated.

[0009] Preferably, the strategy for generating the dust level at the current location is as follows: A spatial interpolation algorithm is used to calculate the background dust concentration at the current vehicle location by weighting the dust concentration data at each fixed point based on the distance between the position coordinates of multiple fixed dust sensors and the current vehicle location. The measured dust concentration value and the background dust concentration are weighted and fused using the following formula to obtain the fused dust concentration value:

[0010] in, This is the measured value of dust concentration. The background dust concentration at the vehicle's current location. The preset fusion weighting coefficients are used when the vehicle-mounted dust sensor malfunctions. =0; Based on the merged dust concentration value, the dust level at the current location is determined according to the preset concentration-level mapping table.

[0011] Preferably, the spraying control parameters include spray volume parameters and spraying mode parameters, wherein the spraying mode parameters include continuous spraying mode and intermittent spraying mode; The initial spray control parameter generation strategy is as follows: The formula for calculating the initial spray volume is:

[0012] in, This is the initial spray volume. As the baseline spraying volume, For speed compensation coefficient, This is the humidity compensation coefficient. This is the material compensation coefficient; The initial spraying mode is determined based on the dust level at the current location. If the dust level at the current location is lower than the preset threshold, the spraying mode parameters are set to intermittent spraying mode; otherwise, the spraying mode parameters are set to continuous spraying mode. The baseline spraying volume is determined according to the dust level at the current location and a preset level-spraying volume mapping table. The formula for calculating the speed compensation coefficient is as follows:

[0013] In the formula, For speed influence coefficient, For reference speed, The vehicle's speed; The formula for calculating the humidity compensation coefficient is:

[0014] In the formula, This is the high humidity limit compensation coefficient; This is the low humidity limit compensation coefficient; The humidity attenuation coefficient is... This refers to the humidity data for the current area. The material compensation coefficient is determined according to the material type of the road segment currently being driven by the vehicle, based on a preset material-coefficient mapping relationship.

[0015] More preferably, the strategy for the spray controller to correct the initial spray control parameters is as follows: When the vehicle is uphill and the absolute value of the slope angle is greater than or equal to the uphill correction starting threshold, the slope correction coefficient is calculated using the following formula:

[0016] In the formula, This is the slope correction factor. The slope angle, This is the uphill slope influence coefficient. This represents the maximum slope angle uphill. When the vehicle is downhill and the absolute value of the slope angle is greater than or equal to the downhill correction trigger threshold, the slope correction coefficient is calculated using the following formula:

[0017] in, This is the downhill slope influence coefficient. This represents the maximum slope angle on the downhill slope. Curving correction factor: When the radius of curvature R of the curve is greater than the curve correction initiation threshold hour, = 1; When the curve correction trigger threshold < Curve radius R ≤ Curve correction initiation threshold When correcting, follow the formula below:

[0018] In the formula, This is the curve correction factor. The current radius of curvature of the curve. Adjust the starting threshold for curves; When the radius of curvature R of the curve is less than or equal to the minimum radius threshold of the curve hour, = 0; The formula for calculating the corrected spray volume parameters is as follows:

[0019] When the vehicle is going uphill = When going downhill, = ; Spraying is prohibited when the slope is downhill and the absolute value of the slope angle is greater than or equal to the downhill prohibition threshold. At that time, set directly = 0, spraying is prohibited; when = 0 or the current curve curvature radius R ≤ curve mode switching threshold When necessary, switch the spray mode parameters to intermittent spray mode and turn off the nozzles on the inside of the bend.

[0020] Preferably, the human-machine interface is also used to input spray control parameters; the spray controller is also used to convert the received spray control parameters into control commands and send them to the actuator.

[0021] Preferably, the strategy for calculating the slope angle is as follows: Extract the longitudinal acceleration component from the vehicle acceleration, and then... The first road slope angle estimate is calculated based on the vehicle's speed; the angular velocity component in the vehicle's pitch direction is extracted from the vehicle's angular velocity and integrated to obtain the second road slope angle estimate; a complementary filtering algorithm is used to fuse the first and second road slope angle estimates to obtain the final slope angle.

[0022] Preferably, the strategy for calculating the radius of curvature of the curve is as follows: The angular velocity from the vehicle driving status acquisition module is used as the yaw rate. Based on the yaw rate and the vehicle speed, the curve curvature radius is calculated, and a sliding window filtering algorithm is used to smooth the calculated curve curvature radius.

[0023] The principles and advantages of this invention are as follows: 1. By fusing multi-source dust data to generate objective dust levels, the subjective and visual limitations are eliminated, and the dust reduction effect is stable and controllable.

[0024] 2. By finely adjusting the spraying volume through multi-dimensional parameters (vehicle speed, humidity, road material), on-demand spraying is achieved, avoiding the problem of overspraying in traditional timed spraying or manual operation.

[0025] 3. By real-time detection of slope angle and curve radius, a graded safety correction strategy is adopted for different working conditions (appropriate reduction on uphill slopes, strict restriction on downhill slopes, prohibition of spraying on sharp curves and closure of inner nozzles), effectively avoiding safety hazards caused by slippery road surfaces.

[0026] 4. Through the redundant fusion design of vehicle-mounted sensor and fixed station data, when the vehicle-mounted sensor fails, it can completely switch to fixed station data; when the network is interrupted, it can switch to independent working mode, and the system spraying control will not be interrupted. Attached Figure Description

[0027] Figure 1This is a system block diagram of the present invention. Detailed Implementation

[0028] The following detailed description illustrates the specific implementation method: The specific implementation process is as follows: (See details) Figure 1 A water truck intelligent spraying control system includes a detection device, a vehicle driving status acquisition module, a spraying controller, an actuator, and a human-machine interface; The detection device includes an on-board dust sensor, multiple fixed dust sensors, and a humidity sensor. The on-board dust sensor is installed on the top of the sprinkler truck or above the cab to detect the dust concentration data at the current location of the vehicle in real time. The sampling frequency is 10Hz, and the output parameters include PM2.5, PM10, and TSP concentration values. In this embodiment, the model uses the Sifang Optoelectronics PM3006S outdoor dust sensor. The multiple fixed dust sensors are deployed along the mining area roads at intervals of 200-500 meters to detect the dust concentration data at preset fixed points. In this embodiment, the model uses the GCG500Z mining dust concentration sensor. The humidity sensor is installed on the sprinkler truck body to detect the humidity data (relative humidity RH) at the current location of the sprinkler truck. The sampling frequency is 1Hz, and it communicates with the spray controller via an RS485 interface. In this embodiment, the model uses the Jianda Renke RS-WS-N01-2.

[0029] The vehicle driving status acquisition module connects to the CAN bus of the existing controller of the sprinkler truck. It acquires driving status data and real-time vehicle location information via monitoring. This driving status data includes vehicle speed, acceleration, angular velocity, and heading angle. Specifically, vehicle speed is read from the speed signal broadcast by the ABS controller or VCU; acceleration and angular velocity are read from the inertial measurement unit (IMU); the heading angle is read from the IMU or GPS module; and the real-time vehicle location information is read from the GPS module. The sampling frequency of the vehicle driving status acquisition module is 50-100Hz to ensure real-time response to dynamic changes in the vehicle.

[0030] The spray controller, which communicates with the detection device and the vehicle driving status acquisition module, includes: The dust level generation module is used to generate the dust level for the current location based on the dust concentration data of the current location of the detected vehicle and preset fixed points. The strategy for generating the dust level at the current location is as follows: 1) Using a spatial interpolation algorithm, the dust concentration data at each fixed point are weighted and calculated based on the distance between the position coordinates of multiple fixed dust sensors and the current position of the vehicle, so as to obtain the background dust concentration at the current position of the vehicle; Specifically, the inverse distance-weighted interpolation (IDW) method is used to calculate the background dust concentration at the vehicle's current location. The IDW method assumes that fixed points closer to the vehicle have a greater impact on the current background concentration; the calculation formula is as follows:

[0031] in, Let be the Euclidean distance from the i-th fixed point to the current position of the vehicle. , , The coordinates of the vehicle's current position. , Let i be the coordinates of the i-th fixed point; When there are fewer than two fixed dust sensors within the preset range of the vehicle's current location, the spatial interpolation result is unreliable. In this case, the measured value of the vehicle-mounted dust sensor is used as a substitute value for the background concentration. 2) The measured dust concentration and the background dust concentration are weighted and fused using the following formula to obtain the fused dust concentration value:

[0032] in, This is the measured value of dust concentration. The background dust concentration at the vehicle's current location. The preset fusion weight coefficient ranges from 0.5 to 0.9; in this embodiment, it is taken as... =0.7, meaning the weight of the vehicle-side measured value is 70%, and the weight of the background concentration is 30%. The basis for this weight setting is that the vehicle-side measured value has a higher spatiotemporal resolution and can accurately reflect the instantaneous dust situation at the current location of the vehicle; while the background concentration reflects the overall dust level of the surrounding area and serves as reference and redundant data. When the vehicle dust sensor malfunctions =0, using the background concentration as the fusion result entirely; 3) Based on the fused dust concentration value, determine the dust level of the current location according to the preset concentration-level mapping table.

[0033] The method for constructing the concentration-level mapping table is as follows: First, based on the concentration limits of each pollutant specified in the "Ambient Air Quality Standard" and the "Technical Regulations for Ambient Air Quality Index (AQI)," the range of dust concentration corresponding to different air quality levels is determined. Specifically, the air quality index levels are divided into six levels: excellent, good, lightly polluted, moderately polluted, heavily polluted, and severely polluted, with each level corresponding to a preset dust concentration range. Secondly, based on the actual working conditions of dust control on roads in the mining area, the above classification was optimized and adjusted to reduce the number of classifications to simplify the control logic. In addition, TSP concentration was added as an auxiliary judgment parameter to address the dust characteristics of the mining area, which is mainly composed of coarse particulate matter (TSP). Finally, the grading thresholds were corrected through on-site calibration experiments: water spraying operations were carried out under different dust concentration conditions, dust reduction effect data were collected, and statistical methods were used to determine the optimal concentration interval boundary values ​​corresponding to each level, so that the dust reduction effect between adjacent levels had significant differences, thereby generating a concentration-level mapping table.

[0034] This embodiment sets five dust levels, as follows:

[0035] In this embodiment, the dust concentration value is obtained according to the above calculation formula. =149.2μg / m³, falling within the 100-200 range, the dust level at the current location is level 3 "light pollution".

[0036] The spray control parameter generation module is used to determine the initial spray control parameters based on the dust level at the current location, vehicle speed, humidity, and the material type of the road section the vehicle is currently traveling on; it is also used to calculate the current slope angle and curve radius of curvature of the vehicle based on the current acceleration and angular velocity of the vehicle, and to correct the initial spray control parameters based on the slope angle and curve radius of curvature to generate the corrected spray control parameters. The spraying control parameters include spray volume parameters and spraying mode parameters. The spraying mode parameters include continuous spraying mode and intermittent spraying mode. The initial spray control parameter generation strategy is as follows: The formula for calculating the initial spray volume is:

[0037] in, This is the initial spray volume. As the baseline spraying volume, For speed compensation coefficient, This is the humidity compensation coefficient. This is the material compensation coefficient.

[0038] The initial spraying mode is determined based on the dust level at the current location. If the dust level at the current location is lower than a preset threshold, the spraying mode parameters are set to intermittent spraying mode; otherwise, the spraying mode parameters are set to continuous spraying mode. In this embodiment, the preset threshold is level 3, meaning that when the dust level is lower than level 3, the intermittent spraying mode is used, and when the dust level is level 3 or higher, the continuous spraying mode is used. The spraying mode is set to continuous spraying mode based on the current location's dust level of level 3 (light pollution).

[0039] The baseline spraying volume is determined based on the dust level at the current location, according to a preset level-spraying volume mapping table; specifically, the level-spraying volume mapping table is constructed using the following method: First, the initial baseline spraying amount is calculated using the median of the concentration range corresponding to the dust level as input and the minimum spraying amount required to reduce the dust concentration to the target value (the upper limit of the next level) under that concentration condition as output. Spraying operations are then conducted at different proportions of the initial baseline spraying amount (e.g., 80%, 100%, 120%) to measure the dust suppression effect and record the actual minimum spraying amount required to achieve the target dust suppression effect. Linear interpolation is used to smooth the baseline spraying amounts between adjacent levels to avoid abrupt changes in spraying amount when switching levels. The mapping table is then corrected through multiple rounds of on-site calibration experiments: the actual minimum spraying amount obtained from calibration is compared with the initial calculated value, and the optimal baseline spraying amount for each level is determined using the least squares method, ensuring that the values ​​in the mapping table are universal and adjustable under different mining areas and seasonal conditions. In this embodiment, the grade-spraying volume mapping table is as follows:

[0040] In this embodiment, the baseline spraying rate is determined to be 25 L / km based on the dust level of the current location being level 3, which is light pollution.

[0041] The formula for calculating the speed compensation coefficient is as follows:

[0042] In the formula, The speed influence coefficient represents the degree to which changes in vehicle speed affect the spray volume. In this embodiment, it is taken as... = 0.015, As a reference speed, representing the benchmark point for vehicle speed compensation, in this embodiment, we take... = 30 km / h; The vehicle speed is used for calibration of the speed influence coefficient. Under standard conditions of flat, hardened road and humidity of 50%-60%, the dust reduction effect is measured by driving at different speeds (10 km / h, 20 km / h, 30 km / h, 40 km / h, 50 km / h) and the optimal parameter value is determined by linear regression fitting.

[0043] The formula for calculating the humidity compensation coefficient is:

[0044] In the formula, The high humidity limit compensation coefficient is less than 1, representing the compensation coefficient value when RH=100%. In this embodiment, it is taken as... = 0.7; The low humidity limit compensation coefficient is greater than 1, representing the compensation coefficient value when RH=0%. In this embodiment, it is taken as... = 1.6; The humidity attenuation coefficient represents the rate at which the compensation coefficient decreases with increasing humidity. In this embodiment, it is taken as... = 0.03, This displays the humidity data for the current area.

[0045] The material compensation coefficient is determined according to the material type of the road segment currently being driven by the vehicle, based on a preset material-coefficient mapping relationship; In this embodiment, the mapping relationship used is as follows:

[0046] In this embodiment, the current vehicle speed is 36 km / h (i.e., 10 m / s). =1.09, the current humidity in the area is 50%. =0.9, the current road material type is hardened cement / asphalt pavement, according to the material-coefficient mapping table, the material compensation coefficient is 0.9. The initial spraying rate is calculated to be 29.43 L / km, with a value of 1.2.

[0047] The strategy for calculating the slope angle is as follows: Extract the longitudinal acceleration component from the vehicle acceleration, and then... The first road slope angle estimate is calculated based on the vehicle's speed; the angular velocity component in the vehicle's pitch direction is extracted from the vehicle's angular velocity and integrated to obtain the second road slope angle estimate; a complementary filtering algorithm is used to fuse the first and second road slope angle estimates to obtain the final slope angle.

[0048] Specifically, the formula for calculating the acceleration components is:

[0049] In the formula, , dt represents the change in vehicle speed, and dt represents the change in time. This differential value is obtained by performing a differential operation on the vehicle speed signal. First road inclination angle estimate based on accelerometer Calculate using the following formula:

[0050] Where g is the acceleration due to gravity, taken as 9.8 m / s².

[0051] Extract the angular velocity component in the vehicle's pitch direction from the vehicle's angular velocity. The second road tilt angle estimate based on the gyroscope is obtained through integration. :

[0052] In the formula, The angular velocity component; Finally, a complementary filtering algorithm is used to estimate the slope angle of the first road. Second road inclination estimate By merging the components, the final slope angle α is obtained:

[0053] In the formula, τ is the complementary filter coefficient, with a value range of 0.01-0.1. In this embodiment, τ = 0.05 is taken, that is, the weight of the accelerometer is 5% and the weight of the gyroscope is 95%. The basis for this weight allocation is that the gyroscope has higher accuracy in the integration result in a short time, while the accelerometer provides a long-term stable reference to eliminate integration drift.

[0054] The sign of the slope angle α indicates the direction of the slope: α>0 indicates uphill, and α<0 indicates downhill.

[0055] In this embodiment, it is assumed that the vehicle travels at 3 m / s 2 The acceleration uphill, the acceleration in the vehicle's forward direction measured by the inertial measurement unit. =4.5m / s 2 Vehicle acceleration =3m / s 2 Then the gravitational acceleration component =1.5m / s 2 First road inclination angle estimate based on accelerometer ≈8.8°. After complementary filtering and fusion, the final slope angle α≈8.8° (a positive value indicates an uphill slope).

[0056] The strategy for calculating the radius of curvature of the curve is as follows: The angular velocity from the vehicle driving status acquisition module is used as the yaw rate. Based on the yaw rate and vehicle speed, the radius of curvature of the curve is calculated, and a sliding window filtering algorithm is used to smooth the calculated radius of curvature.

[0057] The formula for calculating the radius of curvature of a curve is:

[0058] In the formula, V is the vehicle speed (unit: m / s). The yaw rate is expressed in rad / s.

[0059] When the absolute value of the yaw rate is less than the preset angular velocity threshold (In this embodiment, we take) When the radius of curvature R is 0.01 rad / s, it is determined to be straight driving, and the radius of curvature R of the curve is considered to be infinite.

[0060] To suppress computational fluctuations caused by sensor noise, a sliding window filtering algorithm is used to smooth the calculated curve curvature radius R. The sliding window length is set to 10 sampling points, that is, the arithmetic mean of the most recent 10 calculation results is taken as the curve curvature radius at the current moment.

[0061] Calculation example: Vehicle speed v = 10 m / s (36 km / h); yaw rate = 0.2 rad / s (approximately 11.5° / s); R = 10 / 0.2 = 50 m.

[0062] The strategy for the spray controller to correct the initial spray control parameters is as follows: When the vehicle is uphill and the absolute value of the slope angle is greater than or equal to the uphill correction start threshold When the slope correction factor is calculated, use the following formula. :

[0063] In the formula, This is the slope correction factor. The slope angle, This is the uphill slope influence coefficient. The maximum slope angle is the uphill angle; in this embodiment, the uphill correction start threshold is... =3°, uphill slope influence coefficient =0.3, maximum uphill slope = For a value of 15°, when |α| ≥ hour, = 1 - = 0.7.

[0064] When the vehicle is downhill and the absolute value of the slope angle |α| is greater than or equal to the downhill correction start threshold When the slope correction factor is calculated, use the following formula. :

[0065] in, This is the downhill slope influence coefficient. This represents the maximum slope angle on the downhill slope. To correct the starting threshold for downhill slopes, this embodiment takes... = 2°; The slope gradient influence coefficient is taken as [value] in this embodiment. = 0.6; In this embodiment, the maximum downhill slope angle is taken as... = 12°. When |α| ≥ hour, = 1 - = 0.4.

[0066] Different impact coefficients are used for uphill and downhill sections because slippery road surfaces have a greater impact on driving safety when going downhill, thus requiring stricter spraying restrictions. > ).

[0067] Spraying is prohibited when the slope is downhill and the absolute value of the slope angle is greater than or equal to the downhill prohibition threshold |α| ≥ At that time, directly set the final spray volume to =0, spraying is prohibited. Among them, The threshold for prohibiting spraying on downhill slopes is taken in this embodiment. = 8°.

[0068] The cornering correction strategy is as follows: When the radius of curvature R of the curve is greater than the curve correction initiation threshold hour, = 1 (no correction); When the curve correction trigger threshold < Curve radius R ≤ Curve correction initiation threshold hour, (Linear decrease), where, This is the curve correction factor. The current radius of curvature of the curve. Adjust the starting threshold for curves; When the radius of curvature R of the curve is less than or equal to the minimum radius threshold of the curve hour, = 0 (Completely stopped).

[0069] The formula for calculating the corrected spray volume parameters is as follows:

[0070] When the vehicle is going uphill = When going downhill, = ; Spraying is prohibited when the slope is downhill and the absolute value of the slope angle is greater than or equal to the downhill prohibition threshold. At that time, set directly = 0, spraying is prohibited; when = 0 or the current curve curvature radius R is less than or equal to the curve mode switching threshold. When necessary, switch the spray mode parameters to intermittent spray mode and turn off the nozzles on the inside of the bend.

[0071] The control command output module converts the corrected spraying control parameters into control commands and sends them to the actuator. The actuator, communicating with the spray controller, is used to execute spraying actions according to control commands. The actuator includes a high-side drive circuit, a spray solenoid valve, and a water pump. The high-side drive circuit is integrated into the controller and receives PWM duty cycle control commands from the spray controller to drive the spray solenoid valve and water pump to execute spraying actions. The spray solenoid valves control the left, right, rear, and inner bend nozzles respectively, and each nozzle can be controlled independently.

[0072] The human-machine interface (HMI) uses a 7-12 inch industrial-grade touchscreen, installed in the cab of the sprinkler truck, and communicates with the spray controller via CAN bus or RS485. It displays detection data and spray control parameters, and is also used to input spray control parameters. The spray controller converts the received spray control parameters into control commands and sends them to the actuators. Specifically, the HMI displays dust monitoring data, vehicle status data, and spraying operation data in real time, and receives spray control parameters input by the driver, including spray mode switching commands (automatic or manual mode), target dust threshold, spray intensity coefficient, spraying time and interval for intermittent spraying, and safety limit thresholds for slopes and curves.

[0073] The detection device also includes a level sensor for detecting the water level data in the sprinkler truck's water tank. This embodiment uses an EH801 submersible level transmitter. The spray controller also includes an anomaly detection module. This module monitors the water tank level. When the water tank level is lower than a preset level (10% in this embodiment), it generates a level alarm and displays "Water tank level too low, please add water promptly" through the human-machine interface. Simultaneously, it restricts the spray controller's output of spray commands to prevent the water pump from running dry and being damaged. It also monitors the drive current of each motor in the actuator. When the drive current of any motor exceeds its preset stall current threshold and the duration exceeds a preset time threshold, it generates a motor stall alarm. Specifically, the drive current is obtained through the current detection function built into the high-side drive circuit. Taking the water pump motor as an example, its normal operating current is 5-8A. When the water pump motor drive current exceeds the preset stall current threshold (5 times the normal operating current, i.e., 30A in this embodiment) and the duration exceeds a preset time threshold (200ms in this embodiment), it is determined that the motor is stalled, generating a motor stall alarm. The human-machine interface displays "Water pump stalled, please check," and the drive output of the motor is automatically cut off to protect the motor and drive circuit.

[0074] Preferably, it also includes a cloud server, which is connected to the spray controller network via 4G communication to collect detection data and location coordinates of dust sensors; specifically, multiple fixed dust sensors upload the collected dust concentration data and location coordinates to the cloud server via a 4G / 5G wireless network, and the spray controller obtains the fixed dust sensor data within a preset range of the vehicle's current location from the cloud server via a 4G communication module.

[0075] Preferably, the spray controller further includes a manual intervention monitoring module for detecting manual intervention operations. When the driver inputs a manual control command through a physical switch, the manual intervention monitoring module sends a hardware priority switching signal to the control command output module. The control command output module cuts off the automatic control command path output by the spray control parameter generation module based on the signal and directly sends the manual control command input by the physical switch to the actuator. After the manual intervention operation ends, after a preset delay time and simultaneously meeting the following conditions: the vehicle's current speed is less than a preset speed threshold, the absolute value of the slope angle is less than a preset slope threshold, and the radius of curvature of the curve is greater than a preset radius threshold, the automatic control command path output by the spray control parameter generation module is automatically restored.

[0076] The above are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A smart spraying control system for a sprinkler truck, characterized in that, include: The detection device includes an on-board dust sensor, multiple fixed dust sensors, and a humidity sensor. The on-board dust sensor is used to detect the dust concentration data at the current location of the vehicle. The fixed dust sensors are used to detect the dust concentration data at a preset fixed point. The humidity sensor is used to detect the humidity data of the current area. The vehicle driving status acquisition module is used to acquire real-time vehicle location information and driving status data of the vehicle driving system. The driving status data includes vehicle speed, acceleration, angular velocity, and heading angle. The spray controller, which is communicatively connected to the detection device and the vehicle driving status acquisition module, includes: The dust level generation module is used to generate the dust level for the current location based on the dust concentration data of the current location of the detected vehicle and preset fixed points. The spray control parameter generation module is used to determine the initial spray control parameters based on the dust level at the current location, vehicle speed, humidity, and the material type of the road section the vehicle is currently traveling on; it is also used to calculate the current slope angle and curve radius of curvature of the vehicle based on the current acceleration and angular velocity of the vehicle, and to correct the initial spray control parameters based on the slope angle and curve radius of curvature to generate the corrected spray control parameters. The control command output module converts the corrected spraying control parameters into control commands and sends them to the actuator. The actuator is connected in communication with the spray controller and is used to perform spraying actions according to control commands; The human-machine interface communicates with the spray controller and is used to display detection data and spray control parameters.

2. The intelligent spraying control system for sprinkler trucks according to claim 1, characterized in that: The detection device also includes a liquid level sensor for detecting the liquid level data in the water tank of the sprinkler truck. The spray controller also includes an anomaly detection module, which is used to monitor the water tank level. When the water tank level is lower than the preset level, a level alarm is generated. It is also used to monitor the drive current of each motor in the actuator. When the drive current of any motor exceeds the preset stall current threshold of that motor and the duration exceeds the preset time threshold, a motor stall alarm is generated.

3. The intelligent spraying control system for sprinkler trucks according to claim 1, characterized in that: The strategy for generating the dust level at the current location is as follows: A spatial interpolation algorithm is used to calculate the background dust concentration at the current vehicle location by weighting the dust concentration data at each fixed point based on the distance between the position coordinates of multiple fixed dust sensors and the current vehicle location. The measured dust concentration value and the background dust concentration are weighted and fused using the following formula to obtain the fused dust concentration value: in, This is the measured value of dust concentration. Background dust concentration, The preset fusion weighting coefficients are used when the vehicle-mounted dust sensor malfunctions. =0; Based on the merged dust concentration value, the dust level at the current location is determined according to the preset concentration-level mapping table.

4. The intelligent spraying control system for sprinkler trucks according to claim 1, characterized in that: The spraying control parameters include spray volume parameters and spraying mode parameters. The spraying mode parameters include continuous spraying mode and intermittent spraying mode. The initial spray control parameter generation strategy is as follows: The formula for calculating the initial spray volume is: in, This is the initial spray volume. As the baseline spraying volume, For speed compensation coefficient, This is the humidity compensation coefficient. This is the material compensation coefficient; The initial spraying mode is determined based on the dust level at the current location. If the dust level at the current location is lower than the preset threshold, the spraying mode parameters are set to intermittent spraying mode; otherwise, the spraying mode parameters are set to continuous spraying mode. The baseline spraying volume is determined according to the dust level at the current location and a preset level-spraying volume mapping table. The formula for calculating the speed compensation coefficient is as follows: In the formula, For speed influence coefficient, For reference speed, The vehicle's speed; The formula for calculating the humidity compensation coefficient is: In the formula, This is the high humidity limit compensation coefficient; This is the low humidity limit compensation coefficient; The humidity attenuation coefficient is... This refers to the humidity data for the current area. The material compensation coefficient is determined according to the material type of the road segment currently being driven by the vehicle, based on a preset material-coefficient mapping relationship.

5. The intelligent spraying control system for sprinkler trucks according to claim 4, characterized in that: The strategy for the spray controller to correct the initial spray control parameters is as follows: When the vehicle is uphill and the absolute value of the slope angle is greater than or equal to the uphill correction starting threshold, the slope correction coefficient is calculated using the following formula: In the formula, This is the slope correction factor. The slope angle, This is the uphill slope influence coefficient. This represents the maximum slope angle uphill. When the vehicle is downhill and the absolute value of the slope angle is greater than or equal to the downhill correction trigger threshold, the slope correction coefficient is calculated using the following formula: in, This is the downhill slope influence coefficient. This represents the maximum slope angle on the downhill slope. Curving correction factor: When the radius of curvature R of the curve is greater than the curve correction initiation threshold hour, = 1; When the curve correction trigger threshold < Curve radius R ≤ Curve correction initiation threshold When correcting, follow the formula below: In the formula, This is the curve correction factor. The current radius of curvature of the curve. Adjust the starting threshold for curves; When the radius of curvature R of the curve is less than or equal to the minimum radius threshold of the curve hour, = 0; The formula for calculating the corrected spray volume parameters is as follows: When the vehicle is going uphill = When going downhill, = ; Spraying is prohibited when the slope is downhill and the absolute value of the slope angle is greater than or equal to the downhill prohibition threshold. At that time, set directly =0, spraying is prohibited; when = 0 or the current curve curvature radius R ≤ curve mode switching threshold When necessary, switch the spray mode parameters to intermittent spray mode and turn off the nozzles on the inside of the bend.

6. The intelligent spraying control system for sprinkler trucks according to claim 1, characterized in that: The human-machine interface is also used to input spray control parameters; the spray controller is also used to convert the received spray control parameters into control commands and send them to the actuator.

7. The intelligent spraying control system for sprinkler trucks according to claim 1, characterized in that: The strategy for calculating the slope angle is as follows: Extract the longitudinal acceleration component from the vehicle acceleration, and then... The first road slope angle estimate is calculated based on the vehicle's speed; the angular velocity component in the vehicle's pitch direction is extracted from the vehicle's angular velocity and integrated to obtain the second road slope angle estimate; a complementary filtering algorithm is used to fuse the first and second road slope angle estimates to obtain the final slope angle.

8. The intelligent spraying control system for sprinkler trucks according to claim 1, characterized in that: The strategy for calculating the radius of curvature of the curve is as follows: The angular velocity from the vehicle driving status acquisition module is used as the yaw rate. Based on the yaw rate and the vehicle speed, the curve curvature radius is calculated, and a sliding window filtering algorithm is used to smooth the calculated curve curvature radius.

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