Intelligent control system for spreader of snow sweeper

Abstract

The invention relates to an intelligent control system for a spreader of a snow sweeper, which comprises a computer, a main controller, a variable frequency driving module, an execution module, a sensing module, a remote communication module and a man-machine interaction module, and is characterized in that the main controller, the variable frequency driving module, the execution module, the sensing module, the remote communication module and the man-machine interaction module are electrically connected with the computer; according to the intelligent control system for the spreader of the snow sweeper, overall data detection of complex road conditions is achieved through the vehicle speed, the environment temperature, the humidity, the accumulated snow thickness and the camera, then precise intelligent control over the spreading amount is achieved, waste of a snow melting agent is reduced, and the cost is reduced. And remote Internet of Things control is realized through the remote communication module and the man-machine interaction module, so that remote adjustment is realized, and the intelligent degree is improved.

Description

Technical Field

[0001] The present invention relates to an intelligent control system for a snowplow spreader. Background Art

[0002] The intelligent control system of the existing snowplow spreader generally determines the spreading amount of the spreader through the data of road surface temperature, humidity and snow accumulation thickness collected by sensors. The control method of this control system is relatively single and the comprehensive performance is poor. When the road conditions of the snow-covered road surface are relatively complex, accurate spreading amount data cannot be obtained, which often causes a large waste of snow melting agent. Summary of the Invention

[0003] The present invention provides an intelligent control system for a snowplow spreader.

[0004] The technical solution adopted by the present invention to solve its technical problems is: an intelligent control system for a snowplow spreader, including a computer, a main controller, a frequency conversion drive module, an execution module, a sensing module, a remote communication module and a human-computer interaction module. The main controller, the frequency conversion drive module, the execution module, the sensing module, the remote communication module and the human-computer interaction module are all electrically connected to the computer;

[0005] The computer is used to run the intelligent control algorithm;

[0006] The main controller includes a PLC;

[0007] The frequency conversion drive module includes a drive motor and an inverter;

[0008] The execution module includes an execution motor and a cylinder;

[0009] The remote communication module includes a wireless signal transceiver unit;

[0010] The human-computer interaction module includes an in-vehicle touch screen, a remote monitoring platform and an audible and visual alarm system;

[0011] The sensing module includes a vehicle speed sensor, a spreading amount sensor, a temperature sensor, a humidity sensor, a snow accumulation thickness detector, a wind speed sensor and a camera unit. The camera unit includes a camera;

[0012] The vehicle speed sensor is used to monitor the vehicle driving speed in real time;

[0013] The spreading amount sensor is used to detect the actual spreading amount of the spreader;

[0014] The humidity sensor is used to detect the air humidity;

[0015] The temperature sensor is used to monitor the road surface temperature and temperature change;

[0016] The snow depth detector uses laser or ultrasonic waves to detect the snow depth;

[0017] The wind speed sensor is used to detect the wind speed;

[0018] The camera is used to monitor the spreading effect in real time.

[0019] Preferably, the intelligent control algorithm formula is: Q = (A * S * (Tm - Tr)) / (K * E), where Q is the spreading dosage, A is the road surface area correction coefficient, S is the snow depth, Tm is the minimum working temperature of the snow melting agent, Tr is the actual road surface temperature, K is the snow melting agent type parameter, and E is the environmental factor.

[0020] Preferably, the road surface area correction coefficient includes a geometric component, a texture component, and an environmental component. Among them, the calculation formula for the geometric component is: A g = 1 + 0.03 * |G| + 0.002C, where G is the slope percentage and C is the reciprocal of the radius of curvature; the calculation formula for the texture component is: A t = 1 + 0.15 * (Ra - 0.3) / 0.7, where Ra is the road surface coefficient; the calculation formula for the environmental component is: A e = 1 + 0.02 * max(0, W - 5) - 0.1D, where W is the wind speed and D is the drainage coefficient. The road surface area correction coefficient is: A = A g * A t * A e .

[0021] Preferably, the environmental factor E = Et * Eh * Ew * Ep, where Et is the temperature factor, Eh is the humidity factor, Ew is the wind speed factor, and Ep is the precipitation factor.

[0022] Preferably, when Tm > Tr, Et = 1 - 0.015 * (Tm - Tr); when Tm ≤ Tr, Et = 1.

[0023] Preferably, when RH > 70%, Eh = 1.2 - 0.006 * RH; when RH ≤ 70%, Eh = 1, where RH is the relative humidity.

[0024] Preferably, Ew = 1 / (1 + 0.05 * W ^ 1.2).

[0025] The beneficial effect of the present invention is that the intelligent control system for the spreading machine of the snow removal vehicle realizes the overall data detection of complex road conditions through the vehicle speed, environmental temperature, humidity, snow depth, and camera, and then realizes the precise and intelligent control of the spreading amount, reduces the waste of the snow melting agent, and realizes remote Internet of Things control through the remote communication module and the human-computer interaction module, realizes remote adjustment, and improves the degree of intelligence. Brief Description of the Drawings

[0026] The present invention will be further described below in conjunction with the drawings and embodiments.

[0027] Figure 1 It is the system schematic diagram of the intelligent control system for the snowplow spreader of the present invention. Detailed Description of the Preferred Embodiment

[0028] The present invention will now be described in further detail with reference to the drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0029] As Figure 1 shown, an intelligent control system for a snowplow spreader includes a computer, a main controller, a variable frequency drive module, an execution module, a sensing module, a remote communication module, and a human-machine interaction module. The main controller, the variable frequency drive module, the execution module, the sensing module, the remote communication module, and the human-machine interaction module are all electrically connected to the computer;

[0030] The computer is used to run the intelligent control algorithm;

[0031] The main controller includes a PLC;

[0032] The variable frequency drive module includes a drive motor and an inverter;

[0033] The execution module includes an execution motor and a cylinder;

[0034] The remote communication module includes a wireless signal transceiver unit;

[0035] The human-machine interaction module includes an in-vehicle touch screen, a remote monitoring platform, and an audible and visual alarm system;

[0036] The sensing module includes a vehicle speed sensor, a spreading amount sensor, a temperature sensor, a humidity sensor, a snow depth detector, a wind speed sensor, and a camera unit. The camera unit includes a camera;

[0037] The vehicle speed sensor is used to monitor the vehicle speed in real time;

[0038] The spreading amount sensor is used to detect the actual spreading amount of the spreader;

[0039] The humidity sensor is used to detect the air humidity;

[0040] The temperature sensor is used to monitor the road surface temperature and temperature changes;

[0041] The snow depth detector uses laser or ultrasonic waves to detect the snow depth;

[0042] The wind speed sensor is used to detect the wind speed;

[0043] The camera is used to monitor the spreading effect in real time.

[0044] This system measures the vehicle speed through the vehicle speed sensor of the sensor module, detects the real-time spreading amount through the spreading amount sensor, detects the road surface temperature through the temperature sensor, detects the road surface humidity through the humidity sensor, detects the road surface snow accumulation thickness through the snow accumulation thickness detector, detects the real-time wind speed through the wind speed sensor, and detects the spreading effect through the camera of the camera unit. Then, these data are fed back to the computer. The computer calculates the real-time spreading amount through a preset intelligent algorithm, and then controls the frequency conversion drive module and the execution module through the main controller. By controlling the drive motor and the frequency converter, the control of the falling amount of the snow melting agent is realized. By controlling the execution motor and the cylinder, the spreading amount of the snow melting agent is controlled in real time. And through the remote communication module, such as the Internet of Things, Bluetooth, etc., the data is transmitted to the remote monitoring platform, the human-computer interaction module, etc. The operator can control on-site or remotely.

[0045] Preferably, the formula of the intelligent control algorithm is: Q = (A * S * (Tm - Tr)) / (K * E), where Q is the spreading dosage, A is the road surface area correction coefficient, S is the snow accumulation thickness, Tm is the lowest working temperature of the snow melting agent, Tr is the actual road surface temperature, K is the snow melting agent type parameter, and E is the environmental factor.

[0046] Preferably, the road surface area correction coefficient includes a geometric component, a texture component, and an environmental component. Among them, the calculation formula of the geometric component is: A g = 1 + 0.03 * |G| + 0.002C, where G is the slope percentage and C is the reciprocal of the radius of curvature; the calculation formula of the texture component is: A t = 1 + 0.15 * (Ra - 0.3) / 0.7, where Ra is the road surface coefficient; the calculation formula of the environmental component is: A e = 1 + 0.02 * max(0, W - 5) - 0.1D, where W is the wind speed and D is the drainage coefficient. The road surface area correction coefficient is: A = A g * A t * A e .

[0047] Preferably, the environmental factor E = Et * Eh * Ew * Ep, where Et is the temperature factor, Eh is the humidity factor, Ew is the wind speed factor, and Ep is the precipitation factor.

[0048] Preferably, when Tm > Tr, Et = 1 - 0.015 * (Tm - Tr); when Tm ≤ Tr, Et = 1.

[0049] Preferably, when RH > 70%, Eh = 1.2 - 0.006 * RH; when RH ≤ 70%, Eh = 1, where RH is the relative humidity.

[0050] Preferably, Ew = 1 / (1 + 0.05 * W^1.2).

[0051] Road geometric features:

[0052] 1. Standard straight section, the range of A value is 1.0 - 1.1;

[0053] 2. Gentle slope section, the slope ≤ 5%, the range of A value is 1.1 - 1.3;

[0054] 3. Gentle slope section, the slope > 5%, the range of A value is 1.3 - 1.6;

[0055] 4. S-shaped curve, the range of A value is 1.4 - 1.8;

[0056] 5. Interchange ramp, the range of A value is 1.5 - 2.0.

[0057] Pavement texture features:

[0058] 1. Smooth asphalt, the micro-texture Ra < 0.3mm, the A value correction is 0%;

[0059] 2. Standard asphalt, the micro-texture Ra is 0.3 - 0.8mm, the A value correction is +5 - 8%;

[0060] 3. Textured concrete, the micro-texture Ra > 1.0mm, the A value correction is +10 - 15%;

[0061] 4. Damaged pavement, pitted and uneven, without micro-pavement, the A value correction is +20 - 25%;

[0062] Environmental features:

[0063] 1. Crosswind effect: When the wind speed > 5m / s, for every 1m / s increase, the A value needs to be increased by 2 - 3%;

[0064] 2. Drainage condition: In areas with poor drainage, the A value is reduced by 10 - 15% to avoid excessive accumulation.

[0065] Calculation example of the pavement area correction parameter for urban elevated curved roads:

[0066] The slope is 4%, the radius of curvature is 50m, the Ra of the textured concrete is 1.2mm, and the wind speed is 8m / s, then A g = 1 + 0.03 * 4 + 0.002 * 1 / 50 ≈ 1.12, A t = 1 + 0.15 * (1.2 - 0.3) / 0.7 ≈ 1.19,

[0067] A e = 1 + 0.02 * (8 - 5) ≈ 1.06, then A = 1.12 * 1.19 * 1.06 ≈ 1.41.

[0068] Calculation example of the pavement area correction parameter for the straight section of the expressway:

[0069] With a slope of 1%, an infinite radius of curvature, a standard asphalt pavement Ra = 0.05 mm, and a wind speed of 3 m / s, then A g = 1 + 0.03 * 1 ≈ 1.03, A t = 1 + 0.15 * (0.5 - 0.3) / 0.7 ≈ 1.04. When the wind speed is less than 5 m / s, A e = 1, then A = 1.03 * 1.04 ≈ 1.07.

[0070] The environmental factor is the total parameter that quantifies the impact of environmental conditions on the effectiveness of the snow melting agent. The value range is usually 0.5 - 1.5. The smaller the value, the more severe the environmental conditions, and the more snow melting agent needs to be added for compensation.

[0071] Calculation example:

[0072] 1. The minimum effective working temperature of sodium chloride snow melting agent is -6 °C, and the actual road surface is -10 °C, then Et = 1 - 0.015 * (-6 - (-10)) = 0.94, and 0.015 is the empirical temperature attenuation coefficient;

[0073] 2. When the humidity is 85%, Eh = 1.2 - 0.006 * 85 = 0.69;

[0074] 3. When the wind speed is 8 m / s, Ew = 1 / (1 + 0.05 * 8^1.2) ≈ 0.72;

[0075] 4. The value of the precipitation factor is:

[0076] When there is no precipitation, Ep = 1;

[0077] When there is light snow and the snowfall is < 2 mm / h, Ep = 0.9;

[0078] When there is moderate snow and the snowfall is 2 - 5 mm / h, Ep = 0.7;

[0079] When there is heavy snow and the snowfall is > 5 mm / h, Ep = 0.5;

[0080] When there is freezing rain, Ep = 0.6;

[0081] When there is sleet, Ep = 0.8;

[0082] 5. Comprehensive calculation: Using calcium chloride, Tm = -15°C, road surface temperature Tr = -20°C, relative humidity 80%, wind speed 6 m / s, moderate snow, snowfall amount 3 mm / h, then:

[0083] Et = 1 - 0.015*(-15 - (-20)) = 0.925;

[0084] Eh = 1.2 - 0.006*80 = 0.72;

[0085] Ew = 1 / (1 + 0.05*6^1.2) ≈ 0.81;

[0086] Ep = 0.7, moderate snow;

[0087] E = 0.925*0.72*0.81*0.7 ≈ 0.38.

[0088] Compared with the prior art, the intelligent control system for the spreader of the snow removal vehicle realizes the overall data detection of complex road conditions through vehicle speed, environmental temperature, humidity, snow accumulation thickness, and cameras, and then realizes the precise intelligent control of the spreading amount, reduces the waste of snow melting agent, and realizes remote Internet of Things control through the remote communication module and the human-machine interaction module, realizes remote adjustment, and improves the degree of intelligence.

[0089] Taking the ideal embodiments based on the present invention as inspiration, through the above description, relevant staff can completely make various changes and modifications within the scope not deviating from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. An intelligent control system for a snowplow spreader, characterized in that, It includes a computer, a main controller, a variable-frequency drive module, an execution module, a sensing module, a remote communication module and a human-machine interaction module. The main controller, the variable-frequency drive module, the execution module, the sensing module, the remote communication module and the human-machine interaction module are all electrically connected to the computer; The computer is used to run an intelligent control algorithm; The main controller includes a PLC; The variable-frequency drive module includes a drive motor and an inverter; The execution module includes an execution motor and a cylinder; The remote communication module includes a wireless signal transceiver unit; The human-machine interaction module includes an in-vehicle touch screen, a remote monitoring platform and an audible and visual alarm system; The sensing module includes a vehicle speed sensor, a spreading amount sensor, a temperature sensor, a humidity sensor, a snow depth detector, a wind speed sensor and a camera unit. The camera unit includes a camera; The vehicle speed sensor is used to monitor the vehicle driving speed in real time; The spreading amount sensor is used to detect the actual spreading amount of the spreader; The humidity sensor is used to detect the air humidity; The temperature sensor is used to monitor the road surface temperature and temperature changes; The snow depth detector uses laser or ultrasonic waves to detect the snow depth; The wind speed sensor is used to detect the wind speed; The camera is used to monitor the spreading effect in real time.

2. The intelligent control system for the snowplow spreader according to claim 1, characterized in that, The formula of the intelligent control algorithm is: Q = (A * S * (Tm - Tr)) / (K * E), where Q is the spreading dosage, A is the road surface area correction coefficient, S is the snow depth, Tm is the minimum working temperature of the snow melting agent, Tr is the actual road surface temperature, K is the snow melting agent type parameter, and E is the environmental factor.

3. The intelligent control system for the snowplow spreader according to claim 2, characterized in that, The road surface area correction coefficient includes a geometric component, a texture component, and an environmental component. Among them, the calculation formula for the geometric component is: A g = 1 + 0.03 * |G| + 0.002C, where G is the slope percentage and C is the reciprocal of the radius of curvature; the calculation formula for the texture component is: A t = 1 + 0.15 * (Ra - 0.3) / 0.7, where Ra is the road surface coefficient; the calculation formula for the environmental component is: A e = 1 + 0.02 * max(0, W - 5) - 0.1D, where W is the wind speed and D is the drainage coefficient. The road surface area correction coefficient is: A = A g * A t * A e .

4. The intelligent control system for the snowplow spreader according to claim 3, wherein The environmental factor E = Et * Eh * Ew * Ep, where Et is the temperature factor, Eh is the humidity factor, Ew is the wind speed factor, and Ep is the precipitation factor.

5. The intelligent control system for the snowplow spreader according to claim 4, characterized in that, When Tm > Tr, Et = 1 - 0.015(Tm - Tr); when Tm ≤ Tr, Et = 1.

6. The intelligent control system for the snowplow spreader according to claim 4, characterized in that, When RH > 70%, Eh = 1.2 - 0.006 * RH; when RH ≤ 70%, Eh = 1, where RH is the relative humidity.

7. The intelligent control system for the snowplow spreader according to claim 5, characterized in that, Ew = 1 / (1 + 0.05*W ^ 1.2).

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