A mining intelligent parking system

Abstract

This invention discloses a mining intelligent parking system, belonging to the field of intelligent parking technology. The parking system comprises a solenoid valve, a parking brake, a data acquisition unit, a vehicle speed sensor, a parking electric switch button, a control module, and a gas-proof diesel engine injection control box. The vehicle speed sensor and the data acquisition unit collect vehicle speed information. When the vehicle speed changes from non-zero to zero, the control module outputs a 24V high-level voltage to apply emergency braking to the solenoid valve. The high-pressure oil for unlocking the parking brake flows back to the fuel tank through the solenoid valve, and the parking brake becomes active. This mining intelligent parking system provides a novel parking braking solution for mining vehicles, improving the reliability, efficiency, and safety of intelligent parking systems, enabling accurate parking braking of mining vehicles and providing better protection for parking operations. Furthermore, by improving the algorithm of the control module and the design of the solenoid valve, the response time from the vehicle speed changing to zero to the activation of the parking brake is shortened.

Description

Technical Field

[0001] This invention relates to the field of intelligent parking technology, specifically to an intelligent parking system for mining applications. Background Technology

[0002] The intelligent parking system for mining vehicles is an intelligent parking control system specifically designed for mining vehicles. It combines advanced electronic technology, sensors, and control algorithms to achieve safer and more reliable parking control, thereby improving the efficiency of mining operations and reducing the risk of accidents. In the Yaping Mine's WC9RJ(A) model, this system primarily enhances the safety and stability of the parking process, reducing parking accidents caused by improper operation or environmental factors.

[0003] Currently, due to the WC9RJ(A) model protocol requiring vehicles to have an automatic parking function, our company provides vehicles with a configuration based on a pressure switching valve. This means that when the pressure drops below the set pressure, the parking unlock hydraulic oil flows directly back to the oil tank, the fail-safe brake engages, and the vehicle automatically brakes. However, in actual use, customers have reported that this function is inconsistent with the on-site vehicle function definition. The reliability, efficiency, and safety of the parking system remain flawed, and mining vehicles cannot accurately apply the parking brake, thus failing to provide assurance for parking operations.

[0004] Therefore, there is an urgent need to improve this shortcoming. The present invention is to study and improve the existing technology to provide a mining intelligent parking system. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent parking system for mining applications to solve the problems mentioned in the background section.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a mining intelligent parking system, comprising, wherein the parking system consists of a solenoid valve, a parking brake, a data collector, a vehicle speed sensor, a parking electric switch button, a control module, and an explosion-proof diesel engine fuel injection control box;

[0007] The solenoid valve is used to control the flow of hydraulic oil to ensure stable vehicle parking. The solenoid valve controls the inlet and outlet of the hydraulic oil to achieve directional control functions such as forward, reverse, and closed flow of the hydraulic oil.

[0008] The parking brake is responsible for locking the wheels when parking to stabilize the vehicle, prevent the vehicle from sliding or moving, and avoid accidents caused by the vehicle rolling when parking on a sloping road.

[0009] The data collector is a microprocessor-controlled intelligent device responsible for collecting various data from the vehicle.

[0010] The vehicle speed sensor is used to detect the vehicle's speed and transmit the speed information to the control module;

[0011] The electric parking switch button is the interface for the driver to interact with the mining intelligent parking system. The driver can activate or deactivate the parking brake by pressing the button.

[0012] The control module is responsible for receiving vehicle data and determining whether the parking brake needs to be activated based on vehicle speed and braking status information. After making a decision, it sends control commands to relevant components.

[0013] The explosion-proof diesel engine fuel injection control box is responsible for controlling the diesel injection and ignition process. By adjusting the diesel injection quantity or ignition timing when the engine is stopped, the load and heat of the engine can be reduced, thereby improving the safety of stopping.

[0014] The logic of the parking system is as follows: Vehicle speed information is collected by the vehicle speed sensor and the data collector. When the vehicle speed changes from non-zero to zero, the control module outputs a 24V high-level signal to activate the solenoid valve for emergency braking. The high-pressure oil for parking brake release flows back to the oil tank through the solenoid valve, and the parking brake is activated. When the vehicle needs to start again, the parking electric switch button is pressed briefly. After receiving the brief press command, the control module stops outputting a 24V high-level signal, the solenoid valve for emergency braking is reset, the parking brake is released, and the vehicle starts normally.

[0015] Furthermore, the solenoid valve controls the opening and closing of the valve through electromagnetic force. When the control module outputs a high-level signal, the electromagnet inside the solenoid valve is excited, attracting the valve core to move, thereby changing the opening and closing state of the valve and controlling the flow of fluid.

[0016] Furthermore, the solenoid valve is combined with intelligent control technology to achieve precise control and monitoring of the solenoid valve, and the intelligent control technology includes fuzzy control and neural network control.

[0017] Furthermore, the fuzzy control is specifically as follows:

[0018] Fuzzification: The input signal is fuzzified and transformed into a fuzzy set to simulate human fuzzy thinking. The input signal includes, but is not limited to, the current, voltage, and temperature parameters of the solenoid valve.

[0019] Fuzzy rule base: Based on expert experience or actual test data, a fuzzy rule base is established. The rules describe how the solenoid valve should adjust its working state under different conditions.

[0020] Fuzzy reasoning: Based on the fuzzy input and the fuzzy rule base, fuzzy reasoning is performed to obtain fuzzy output. The output is a fuzzy set that represents the direction and degree to which the solenoid valve should be adjusted.

[0021] Defuzzification: Converting fuzzy outputs into specific control signals, such as current or voltage values, to adjust the working state of the solenoid valve.

[0022] Furthermore, the neural network control is specifically as follows:

[0023] Training and learning: Training and learning on a large amount of data to establish a complex mapping relationship between input and output, including the historical operating status of the solenoid valve, environmental parameters, etc.

[0024] Online adjustment and optimization: During actual operation, the control strategy is adjusted and optimized online based on real-time data to adapt to changes in the environment and the nonlinear characteristics of the solenoid valve.

[0025] Furthermore, the data collector enables the system to accurately determine the vehicle's parking status and the control measures that need to be taken by collecting vehicle data, and the vehicle data includes, but is not limited to, vehicle speed and braking status.

[0026] Furthermore, the control module specifically includes the following algorithm:

[0027] The derivative-first PID control algorithm only differentiates the measured value and not the deviation. It is responsible for avoiding sudden changes in the output when the set value changes, so that the change of the controlled variable is more gradual. As the vehicle speed decreases to near zero, it helps the control module to adjust the braking force more smoothly and shorten the response time.

[0028] Integral separation PID control algorithm: When the deviation is large enough, the integral action is canceled, and the integral action is introduced only when the deviation is less than this value, so as to reduce overshoot and give full play to the role of integral in eliminating steady-state error. At the moment when the vehicle speed drops to zero, the braking force adjustment process is optimized by adjusting the timing of integral action, and the response time is further shortened.

[0029] Incomplete derivative PID control algorithm: A first-order inertial filter is added to the derivative part of the PID control to improve control quality and optimize stability and response speed.

[0030] Furthermore, the first-order inertial filter is used to filter out random interference signals during the transformation process. It implements the function of a common hardware RC low-pass filter through software programming, and the algorithm formula for the first-order low-pass filter is as follows:

[0031] Y(n)=αX(n)+(1-α)Y(n-1)

[0032] Where α is the filter coefficient, X(n) is the current sample value, Y(n-1) is the previous filter output value, and Y(n) is the current filter output value.

[0033] Furthermore, the specific operation procedure for adding a first-order inertial filter to the derivative part of the PID control is as follows:

[0034] S1. Determine the filtering coefficient α: Select an appropriate α value based on the actual application scenario and requirements. The α value determines the smoothness and response speed of the filter. The larger the α value, the more sensitive the filtering result is to changes in the input signal, but more noise will be introduced. The smaller the α value, the more stable the filtering result is, but the response speed will be slower.

[0035] S2. Obtain the derivative output of PID control: In PID control, the derivative part is mainly used to predict the trend of error change, so as to adjust the control quantity in advance. Specifically, it is to obtain the derivative output value of the PID controller.

[0036] S3. Applying first-order inertial filtering: The differential output of PID control is used as the input X(n) of the first-order inertial filter. According to the algorithm formula of first-order low-pass filtering, Y(n)=αX(n)+(1-α)Y(n-1), the filtered output value Y(n) is calculated.

[0037] S4. Use the filtered derivative output for PID control: Replace the original derivative output value with the derivative output value after first-order inertial filtering for subsequent PID control calculations.

[0038] Furthermore, the hydraulic braking principle is as follows: During the parking braking process of the mining vehicle, the high-pressure oil is released back to the oil tank, causing the piston or pressure plate inside the brake to move under the action of the spring force, thereby pushing the brake shoes or brake disc to contact the wheel, thus realizing parking braking.

[0039] This invention provides an intelligent parking system for mining applications, which has the following advantages:

[0040] This invention provides a novel parking brake solution for mining vehicles, improving the reliability, efficiency, and safety of intelligent parking systems for mining vehicles. This allows mining vehicles to accurately apply parking brakes, providing better protection for parking operations. Furthermore, by improving the algorithm of the control module and the design of the solenoid valve, the response time from the vehicle speed decreasing to zero to the parking brake taking effect is shortened, further improving the braking efficiency of the system. Attached Figure Description

[0041] Figure 1 This is a schematic diagram illustrating the operating principle of a mining intelligent parking system according to the present invention;

[0042] Figure 2 This invention provides a table showing the differences in automatic parking functions between existing technologies and those of a mining intelligent parking system.

[0043] Figure 3This is a comparison table of the optimized and adjusted automatic parking functions of a mining intelligent parking system according to the present invention. Detailed Implementation

[0044] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0045] like Figures 1-3 As shown, a mining intelligent parking system is provided, which consists of a solenoid valve, a parking brake, a data collector, a vehicle speed sensor, a parking electric switch button, a control module, and an explosion-proof diesel engine fuel injection control box.

[0046] The solenoid valve is used to control the flow of hydraulic oil to ensure stable vehicle parking. By controlling the inlet and outlet of the hydraulic oil, the solenoid valve achieves directional control functions such as forward, reverse, and closed flow. The solenoid valve controls its opening and closing via electromagnetic force. When the control module outputs a high-level signal, the electromagnet inside the solenoid valve is excited, attracting the valve core to move, thereby changing the valve's opening and closing state and controlling the fluid flow. The solenoid valve incorporates intelligent control technology, including fuzzy control and neural network control, to achieve precise control and monitoring.

[0047] The fuzzy control is specifically as follows:

[0048] Fuzzification: The input signal is fuzzified and transformed into a fuzzy set to simulate human fuzzy thinking. The input signal includes, but is not limited to, the current, voltage, and temperature parameters of the solenoid valve.

[0049] Fuzzy rule base: Based on expert experience or actual test data, a fuzzy rule base is established. The rules describe how the solenoid valve should adjust its working state under different conditions.

[0050] Fuzzy reasoning: Based on the fuzzy input and the fuzzy rule base, fuzzy reasoning is performed to obtain fuzzy output. The output is a fuzzy set that represents the direction and degree to which the solenoid valve should be adjusted.

[0051] Defuzzification: Converting fuzzy outputs into specific control signals, such as current or voltage values, to adjust the working state of the solenoid valve;

[0052] The neural network control is specifically as follows:

[0053] Training and learning: Training and learning on a large amount of data to establish a complex mapping relationship between input and output, including the historical operating status of the solenoid valve, environmental parameters, etc.

[0054] Online adjustment and optimization: During actual operation, the control strategy is adjusted and optimized online based on real-time data to adapt to changes in the environment and the nonlinear characteristics of the solenoid valve;

[0055] The parking brake is responsible for locking the wheels when parking to stabilize the vehicle, prevent the vehicle from sliding or moving, and avoid accidents caused by the vehicle rolling when parking on a sloping road.

[0056] The data collector is a microprocessor-controlled intelligent device responsible for collecting various vehicle data. By collecting vehicle data, the system can accurately determine the vehicle's parking status and the control measures that need to be taken. The vehicle data includes, but is not limited to, vehicle speed and braking status.

[0057] The vehicle speed sensor is used to detect the vehicle's speed and transmit the speed information to the control module;

[0058] The electric parking switch button is the interface for the driver to interact with the mining intelligent parking system. The driver can activate or deactivate the parking brake by pressing the button.

[0059] The control module is responsible for receiving vehicle data and determining whether the parking brake needs to be activated based on vehicle speed and braking status information. After making a decision, it sends control commands to relevant components. The control module specifically includes the following algorithms:

[0060] The derivative-first PID control algorithm only differentiates the measured value and not the deviation. It is responsible for avoiding sudden changes in the output when the set value changes, so that the change of the controlled variable is more gradual. As the vehicle speed decreases to near zero, it helps the control module to adjust the braking force more smoothly and shorten the response time.

[0061] Integral separation PID control algorithm: When the deviation is large enough, the integral action is canceled, and the integral action is introduced only when the deviation is less than this value, so as to reduce overshoot and give full play to the role of integral in eliminating steady-state error. At the moment when the vehicle speed drops to zero, the braking force adjustment process is optimized by adjusting the timing of integral action, and the response time is further shortened.

[0062] Incomplete Differential PID Control Algorithm: A first-order inertial filter is added to the derivative part of the PID control to improve control quality and optimize stability and response speed. The first-order inertial filter is used to filter out random interference signals during the transformation process. It implements the function of a common hardware RC low-pass filter through software programming, and the algorithm formula for the first-order low-pass filter is as follows:

[0063] Y(n)=αX(n)+(1-α)Y(n-1)

[0064] Where α is the filter coefficient, X(n) is the current sample value, Y(n-1) is the previous filter output value, and Y(n) is the current filter output value;

[0065] The specific operation procedure for adding a first-order inertial filter to the derivative part of PID control is as follows:

[0066] S1. Determine the filtering coefficient α: Select an appropriate α value based on the actual application scenario and requirements. The α value determines the smoothness and response speed of the filter. The larger the α value, the more sensitive the filtering result is to changes in the input signal, but more noise will be introduced. The smaller the α value, the more stable the filtering result is, but the response speed will be slower.

[0067] S2. Obtain the derivative output of PID control: In PID control, the derivative part is mainly used to predict the trend of error change, so as to adjust the control quantity in advance. Specifically, it is to obtain the derivative output value of the PID controller.

[0068] S3. Applying first-order inertial filtering: The differential output of PID control is used as the input X(n) of the first-order inertial filter. According to the algorithm formula of first-order low-pass filtering, Y(n)=αX(n)+(1-α)Y(n-1), the filtered output value Y(n) is calculated.

[0069] S4. Use the filtered derivative output for PID control: Replace the original derivative output value with the derivative output value after first-order inertial filtering for subsequent PID control calculations.

[0070] The explosion-proof diesel engine fuel injection control box is responsible for controlling the diesel injection and ignition process. By adjusting the diesel injection quantity or ignition timing when the engine is stopped, the load and heat of the engine can be reduced, thereby improving the safety of stopping.

[0071] The logic of the parking system is as follows: Vehicle speed information is collected by the vehicle speed sensor and the data collector. When the vehicle speed changes from non-zero to zero, the control module outputs a 24V high-level signal to activate the solenoid valve for emergency braking. The high-pressure oil for parking brake release flows back to the oil tank through the solenoid valve, and the parking brake is activated. When the vehicle needs to start again, the parking electric switch button is pressed briefly. After receiving the brief press command, the control module stops outputting a 24V high-level signal, the solenoid valve for emergency braking is reset, the parking brake is released, and the vehicle starts normally.

[0072] The hydraulic braking principle is as follows: During the parking braking process of the mining vehicle, the high-pressure oil is released back to the oil tank, causing the piston or pressure plate inside the brake to move under the action of the spring force, thereby pushing the brake shoes or brake disc to contact the wheel and realize parking braking.

[0073] In summary, combining Figures 1-3As shown, the usage process of this intelligent parking system for mining is as follows:

[0074] Part 1: Parking Brake Procedure

[0075] Step 1: Vehicle speed sensor detection: The vehicle speed sensor detects the vehicle's speed in real time and transmits the detected speed information to the control module;

[0076] Step 2: Control module judgment: After receiving the vehicle speed information, the control module will determine whether the vehicle has come to a complete stop. If the vehicle speed changes from non-zero to zero, the control module will determine that the vehicle has stopped and prepare to activate the parking brake.

[0077] Step 3: Output a high-level signal: Once the vehicle has stopped, the control module will output a 24V high-level signal. This signal is used to activate the emergency brake solenoid valve.

[0078] Step 4: Emergency brake solenoid valve action: After receiving a high-level signal from the control module, the emergency brake solenoid valve opens, allowing the parking brake unlocking high-pressure oil to flow through the solenoid valve and back to the oil tank, thereby releasing the parking brake from its locked state.

[0079] Step 5, Parking brake activated: As high-pressure oil flows back to the oil tank, the parking brake is unlocked and activated, locking the wheels to prevent the vehicle from moving or sliding while parked.

[0080] Part Two: Vehicle Restart Procedure

[0081] Step 1: Press the parking electric switch button: When the driver is ready to start again, press the parking electric switch button;

[0082] Step 2: Control module receives instructions: When the parking electric switch button is pressed, it sends a signal to the vehicle's control module;

[0083] Step 3: Stop outputting 24V high level: After receiving the jog command, the control module will stop outputting 24V high level to the solenoid valve;

[0084] Step 4: Emergency Brake Solenoid Valve Reset: When the control module stops outputting a high level, the solenoid valve will perform a reset operation, that is, the solenoid valve will release the control of the parking brake and restore it to the non-braking state.

[0085] Step 5: Parking brake returns to the released state: As the solenoid valve resets, the parking brake will also return to the released state. At this time, the vehicle can move freely and is no longer restricted by the parking brake.

[0086] Step Six: Normal Vehicle Start-up: After the parking brake is released, the driver can perform normal starting operations.

[0087] The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A mining intelligent parking system, characterized in that, The parking system consists of a solenoid valve, a parking brake, a data acquisition unit, a vehicle speed sensor, a parking electric switch button, a control module, and an explosion-proof diesel engine fuel injection control box. The solenoid valve is used to control the flow of hydraulic oil to ensure stable vehicle parking. The solenoid valve achieves hydraulic oil direction control function by controlling the inlet and outlet of the hydraulic oil. The parking brake is responsible for locking the wheels when the vehicle is parked to stabilize the vehicle and prevent it from sliding or moving. The data collector is a microprocessor-controlled intelligent device responsible for collecting various data from the vehicle. The vehicle speed sensor is used to detect the vehicle's speed and transmit the speed information to the control module; The electric parking switch button is the interface for the driver to interact with the mining intelligent parking system. The driver can activate or deactivate the parking brake by pressing the button. The control module is responsible for receiving vehicle data and determining whether the parking brake needs to be activated based on vehicle speed and braking status information. After making a decision, it sends control commands to relevant components. The explosion-proof diesel engine fuel injection control box is responsible for controlling the diesel injection and ignition process. By adjusting the diesel injection quantity or ignition timing when the engine is stopped, the load and heat of the engine can be reduced, thereby improving the safety of stopping. The logic of the parking system is as follows: Vehicle speed information is collected by the vehicle speed sensor and the data collector. When the vehicle speed changes from non-zero to zero, the control module outputs a 24V high-level signal to activate the solenoid valve for emergency braking. The high-pressure oil for parking brake release flows back to the oil tank through the solenoid valve, and the parking brake is activated. When the vehicle needs to start again, the parking electric switch button is pressed briefly. After receiving the briefing command, the control module stops outputting a 24V high-level signal, the solenoid valve for emergency braking is reset, the parking brake is released, and the vehicle starts normally. The control module specifically includes the following algorithms: The derivative-first PID control algorithm only differentiates the measured value and not the deviation. It is responsible for avoiding sudden changes in the output when the set value changes, so that the change of the controlled variable is more gradual. As the vehicle speed decreases to near zero, it helps the control module to adjust the braking force more smoothly and shorten the response time. Integral separation PID control algorithm: When the deviation is large enough, the integral action is canceled, and the integral action is introduced only when the deviation is less than this value, so as to reduce overshoot and give full play to the role of integral in eliminating steady-state error. At the moment when the vehicle speed drops to zero, the braking force adjustment process is optimized by adjusting the timing of integral action, and the response time is further shortened. Incomplete derivative PID control algorithm: Add a first-order inertial filter to the derivative part of PID control to improve control quality and optimize stability and response speed; The first-order inertial filter is used to filter out random interference signals during the transformation process. It implements the function of a common hardware RC low-pass filter through software programming, and the algorithm formula for the first-order low-pass filter is as follows: Y(n) = αX(n) + (1-α)Y(n-1) Where α is the filter coefficient, X(n) is the current sample value, Y(n-1) is the previous filter output value, and Y(n) is the current filter output value; The specific operation procedure for adding a first-order inertial filter to the derivative part of PID control is as follows: S1. Determine the filtering coefficient α: Select an appropriate α value based on the actual application scenario and requirements. The α value determines the smoothness and response speed of the filter. The larger the α value, the more sensitive the filtering result is to changes in the input signal, but more noise will be introduced. The smaller the α value, the more stable the filtering result is, but the response speed will be slower. S2. Obtain the derivative output of PID control: In PID control, the derivative part is mainly used to predict the trend of error change, so as to adjust the control quantity in advance. Specifically, it is to obtain the derivative output value of the PID controller. S3. Applying first-order inertial filtering: The differential output of PID control is used as the input X(n) of the first-order inertial filter. According to the algorithm formula of first-order low-pass filtering, Y(n)=αX(n)+(1-α)Y(n-1), the filtered output value Y(n) is calculated. S4. Use the filtered derivative output for PID control: Replace the original derivative output value with the derivative output value after first-order inertial filtering for subsequent PID control calculations.

2. The intelligent parking system for mining vehicles according to claim 1, characterized in that, The solenoid valve controls the opening and closing of the valve through electromagnetic force. When the control module outputs a high-level signal, the electromagnet inside the solenoid valve is excited, attracting the valve core to move, thereby changing the opening and closing state of the valve and controlling the flow of fluid.

3. The intelligent parking system for mining vehicles according to claim 2, characterized in that, The solenoid valve achieves precise control and monitoring by combining intelligent control technology, which includes fuzzy control and neural network control.

4. The intelligent parking system for mining vehicles according to claim 3, characterized in that, The fuzzy control is specifically as follows: Fuzzification: The input signal is fuzzified and transformed into a fuzzy set to simulate human fuzzy thinking; Fuzzy rule base: A fuzzy rule base is established based on expert experience or actual test data; Fuzzy reasoning: Based on fuzzy input and a fuzzy rule base, fuzzy reasoning is performed to obtain fuzzy output; Defuzzification: Converting fuzzy outputs into specific control signals to adjust the working state of the solenoid valve.

5. A mining intelligent parking system according to claim 3, characterized in that, The neural network control is specifically as follows: Training and learning: Training and learning from large amounts of data to establish complex mapping relationships between inputs and outputs; Online adjustment and optimization: During actual operation, the control strategy is adjusted and optimized online based on real-time data to adapt to changes in the environment and the nonlinear characteristics of the solenoid valve.

6. The intelligent parking system for mining vehicles according to claim 1, characterized in that, The data collector collects vehicle data, enabling the system to accurately determine the vehicle's parking status and the control measures that need to be taken.

7. A mining intelligent parking system according to claim 1, characterized in that, The hydraulic braking principle is as follows: During the parking braking process of the mining vehicle, the high-pressure oil is released back to the oil tank, causing the piston or pressure plate inside the brake to move under the action of the spring force, thereby pushing the brake shoes or brake disc to contact the wheel and realize parking braking.

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