A slope piezoelectric intelligent pavement weighing characterization method based on a multi-axle heavy vehicle

Abstract

The application provides a slope piezoelectric intelligent pavement weighing characterization method based on a multi-axle heavy vehicle. The method first selects a to-be-detected pavement, and arranges a piezoelectric sensor array on the cross section of the to-be-detected pavement to form an intelligent pavement. When the vehicle passes through the intelligent pavement, the piezoresistive effect of the piezoelectric sensor converts the mechanical strain into an electric charge signal output. Then, a corresponding voltage signal is generated through a charge-voltage converter, and the relationship between the voltage and the pressure is established in combination with the sensitivity information on the piezoelectric sensor. Based on the pressure distribution data, the position of each wheel of the vehicle is determined. The vehicle speed is calculated in combination with the time interval and the position data of the wheel. Based on the pressure data and the wheel position information, the relationship between the pressure and the load is established, and then the weight applied by each wheel is calculated. The application can significantly improve the weighing accuracy under the condition of a slope pavement, and provides a more reliable and efficient solution for the weighing problem of the multi-axle heavy vehicle.

Description

Technical Field

[0001] This invention relates to the field of civil engineering, and specifically to a piezoelectric intelligent road surface weighing and characterization method based on multi-axle heavy vehicles. Background Technology

[0002] With the gradual increase in my country's expressways and the intensifying market competition in the automobile transportation industry, the number of large, heavy-duty trucks on expressways is steadily increasing. In pursuit of higher profits, some truck owners disregard weight and size limits for transportation. However, this behavior not only severely damages the transportation market and road infrastructure but also easily leads to traffic accidents. Therefore, strictly restricting overloaded vehicles is an urgent priority to safeguard the transportation market, road facilities, and public safety.

[0003] In the field of weighing multi-axle heavy vehicles, existing technologies typically employ traditional weighing systems, which suffer from limitations in accuracy and stability on sloping roads. To overcome these limitations, piezoelectric intelligent road surface weighing technology has gradually emerged in recent years. Piezoelectric sensors can acquire pressure information in real time as vehicles pass by by measuring the pressure distribution on the road surface. However, in practical applications, multi-axle heavy vehicles often face road surfaces with varying gradients, which presents a series of challenges to traditional piezoelectric intelligent road surface weighing systems.

[0004] To address the problem of accurate weighing on sloping roads, a novel algorithm is needed to effectively handle the weighing of multi-axle heavy vehicles on roads with varying gradients. Therefore, a piezoelectric intelligent road surface weighing characterization algorithm based on multi-axle heavy vehicles is proposed. This algorithm utilizes finite element models, time recognition, and correlation analysis to accurately characterize parameters such as the number of axles, weight per axle, vehicle speed, and center of gravity. This innovative algorithm significantly improves weighing accuracy and system stability on sloping roads, providing a more reliable and efficient solution to the weighing problem of multi-axle heavy vehicles. Summary of the Invention

[0005] Purpose of the invention: To solve the above-mentioned technical problems and achieve the above-mentioned solutions, this invention provides a piezoelectric intelligent road surface weighing and characterization method based on multi-axle heavy vehicles.

[0006] Technical solution: This invention provides a piezoelectric intelligent road surface weighing and characterization method based on multi-axle heavy vehicles, comprising the following steps:

[0007] S1: Select the road surface to be tested, and arrange a piezoelectric sensor array on the cross section of the road surface to form a smart road surface, which is used to measure the pressure distribution generated when a vehicle passes by.

[0008] S2: When a vehicle passes over a smart road, the applied axial pressure causes strain in the piezoelectric material of the piezoelectric sensor. The mechanical strain is converted into an electrical signal output through the positive piezoelectric effect of the piezoelectric sensor.

[0009] S3: Based on the charge signal generated in step S2, a corresponding voltage signal is generated through a charge-to-voltage converter;

[0010] S4: Using the voltage signal obtained in step S3 and combining it with the sensitivity information on the piezoelectric sensor, establish the relationship between voltage and pressure;

[0011] S5: Analyze the pressure distribution data based on step S4 to determine the position of each wheel of the vehicle;

[0012] S6: Using the wheel position information obtained in step S5, combined with the time interval and position data of the wheels, calculate the vehicle speed.

[0013] S7: Based on the pressure data and wheel position information measured in step S5, establish the relationship between pressure and load, and then calculate the weight applied to each wheel.

[0014] Furthermore, in step S1, the selection of the road surface to be tested involves selecting at least three road sections on the sloping road surface, with the length of each road section being equal to its width; the piezoelectric sensor is placed at a depth of 0.4m down the road surface section.

[0015] Furthermore, the piezoelectric sensors on each section of the road surface to be tested are arranged in a staggered, interleaved configuration, and the dimensions of each piezoelectric sensor are as follows: mm 3 The piezoelectric sensors are arranged in two rows of 18 columns along the length of the road surface; the spacing between piezoelectric sensors in adjacent columns is 100 mm, and the total width of the piezoelectric sensor array is set to 3.5 m.

[0016] Furthermore, the piezoelectric material used in step S2 is piezoelectric ceramic PZ; the charge-to-voltage converter in step S3 includes a capacitor element; the charge of this capacitor element is proportional to the input signal, and when the charge passes through the capacitor, the generated voltage signal is proportional to the amount of charge, and its voltage V is calculated by the following formula:

[0017]

[0018] In the formula, Q represents the amount of charge generated by the piezoelectric sensor, while C represents the capacitance.

[0019] Furthermore, the specific method for step S7 is as follows:

[0020] The relationship between pressure and load can be converted from the piezoelectric sensor sensitivity formula and can be expressed as follows:

[0021]

[0022] In the formula P j V represents the pressure applied by wheel j. j This indicates that wheel j corresponds to P. j Voltage at that time The sensitivity of the piezoelectric sensor is indicated and provided by the manufacturer of the piezoelectric sensor.

[0023] The load on each wheel is calculated by applying pressure P to wheel j. j Substitute into the following formula:

[0024]

[0025] In the formula F j P represents the load on wheel j. j A represents the pressure applied by wheel j. j This represents the contact area between wheel j and the ground;

[0026] Load F on each wheel j Substitute into the following formula to obtain the total vehicle load:

[0027]

[0028] In the above formula, F represents the total vehicle load. The slope angle is denoted by n, and the number of wheels is denoted by n.

[0029] Substituting the total vehicle load F into the following formula, the total vehicle weight can be obtained:

[0030]

[0031] In the above formula, G m denoted by , where g represents the total vehicle weight and g represents the acceleration due to gravity.

[0032] The present invention has the following beneficial effects:

[0033] 1. Improved Accuracy and Stability: Piezoelectric smart road surface technology significantly improves the weighing accuracy and system stability of multi-axle heavy vehicles on sloping roads. Traditional weighing systems are limited in such complex road conditions, but this algorithm overcomes the challenges through piezoelectric sensors deployed on the smart road surface and advanced data processing.

[0034] Combining real-time performance with precision: By measuring intelligent road cross-sections in real time, the algorithm can quickly and accurately perceive the pressure distribution as vehicles pass by. Real-time data, combined with a precise finite element model, enables accurate characterization of the vehicle's axle parameters.

[0035] 2. Comprehensive consideration of multiple parameters: This algorithm not only accurately identifies the number of axles and the weight of each axle, but also comprehensively considers multiple aspects of the vehicle's operating status by comparing the time correlation of the measurement signals and calculating the average speed, providing a basis for more comprehensive and accurate classification.

[0036] 3. Adaptable to different road surface slopes: Considering the influence of sloping road surfaces, the algorithm performs well under different road surface slopes, providing broad adaptability for diverse applications in real road environments.

[0037] 4. Improved System Robustness: By analyzing the correlation between the initial road cross-section signal and the measured signal, the algorithm can identify and eliminate external interference factors, improving the system's robustness to environmental changes and external influences, and ensuring algorithm reliability. In summary, the slope piezoelectric intelligent road weighing characterization algorithm based on multi-axle heavy vehicles has significant beneficial effects in improving accuracy, real-time performance, and adaptability, providing an innovative and feasible solution to the limitations of traditional weighing systems under slope road conditions. Attached Figure Description

[0038] Figure 1 This is a flowchart of a slope piezoelectric intelligent road surface weighing characterization method based on multi-axle heavy vehicles, as described in this invention.

[0039] Figure 2 A schematic diagram of the structure for arranging piezoelectric smart circuit sensors;

[0040] Figure 3 Front view of the piezoelectric smart road sensor layout;

[0041] Figure 4 A schematic diagram of the piezoelectric intelligent circuit layout;

[0042] Figure 5 This is a schematic diagram of the structure of a single-lane intelligent road surface for vehicles to traverse on a slope.

[0043] Figure 6 This is a side view diagram of a single-lane intelligent pavement.

[0044] Figure 7 This is a macroscopic schematic diagram showing the connection between the piezoelectric sensor, the voltmeter, and the power supply.

[0045] Figure 8 This is a schematic diagram of the connection structure of two sensors connected in series, with a shunt resistor and power supply.

[0046] Figure 9 This is a connection diagram for the first row of sensors;

[0047] Figure 10 This is a connection diagram for the second row of sensors;

[0048] Figure 11 This is a force analysis diagram of a vehicle on a slope.

[0049] In the diagram: 1—Piezoelectric sensor; 2—Concrete; 3—Driving direction; 4—Piezoelectric smart pavement; 5—Driving tire trajectory; 6—Surface layer; 7—Wheel; 8—Vehicle; 9—Total voltmeter of the second row of piezoelectric sensors; 10—Total voltmeter of the first row of piezoelectric sensors; 11—Power supply; 12—Shunt resistor; 13—Voltmeter for measuring shunt resistor; 14—Voltmeter of the first row; 15—Voltmeter of the second row. Detailed Implementation

[0050] The technical solution of the present invention will be further described below with reference to specific embodiments and accompanying drawings.

[0051] like Figure 1 The flowchart shown below illustrates a piezoelectric intelligent road surface weighing and characterization method based on multi-axle heavy vehicles according to the present invention, which includes the following steps:

[0052] S1: Select the road surface to be tested, and arrange an array of piezoelectric sensors on the cross-section of the road surface to form a smart road surface, used to measure the pressure distribution generated when vehicles pass over it; for example... Figure 2 , 3 As shown in Figure 4.

[0053] S2: When a vehicle passes over a smart road surface, the applied axial pressure causes strain in the piezoelectric material of the piezoelectric sensor. This strain is converted into an electrical signal output through the positive piezoelectric effect of the sensor. Figure 5 , 6 As shown in the image.

[0054] S3: Based on the charge signal generated in step S2, a corresponding voltage signal is generated through a charge-to-voltage converter; such as... Figure 7 , 8 As shown in 9 and 10.

[0055] S4: Using the voltage signal obtained in step S3, and combining it with the sensitivity information from the piezoelectric sensor, establish the relationship between voltage and pressure; for example... Figure 11 As shown in the image.

[0056] S5: Based on step S4, analyze the pressure distribution data to determine the position of each wheel of the vehicle.

[0057] S6: Using the wheel position information obtained in step S5, combined with the time interval and position data of the wheels, calculate the vehicle speed; for example... Figure 4 As shown in the image, obtaining the vehicle's speed allows for monitoring whether the vehicle is speeding.

[0058] S7: Based on the pressure data and wheel position information measured in step S5, establish the relationship between pressure and load, and then calculate the weight applied to each wheel; for example... Figure 11 As shown in the image.

[0059] When the sensor planar arrangement of the piezoelectric smart road surface is as follows Figure 2 As shown, its structure mainly consists of piezoelectric sensors 1 and concrete 2. These sensors are arranged in a perforated manner, which not only has the advantages of economy and better maintenance, but also can capture wheel information more accurately. This design not only optimizes the system performance, but also improves the sensor capture efficiency and overall maintainability.

[0060] exist Figure 5 In this process, when wheel 7 passes over the piezoelectric smart road surface 4, the wheel load is transferred to the piezoelectric sensor 1 through the road surface layer 6. When the piezoelectric sensor 1 is subjected to an external load, its material deforms, causing the piezoelectric crystal to deform. This deformation causes a change in the charge distribution inside the crystal, resulting in an imbalance of charges within the crystal. Excessive negative and positive charges appear on opposite sides of the crystal surface. The metal plate collects these charges, converts them into voltage through a charge-to-voltage converter, and sends current through a circuit, realizing the conversion of electrical energy into the piezoelectric effect. The amplitude of the voltage signal is proportional to the magnitude of the wheel load.

[0061] In this embodiment, step S1 involves selecting at least three road sections on a sloping surface, each section being the same length as its width. Piezoelectric sensors are positioned 0.4m below the road surface along its cross-section. The piezoelectric sensors on each road section are arranged in a staggered, interlocking pattern, and each sensor has the following dimensions: mm 3 The piezoelectric sensors are arranged in two rows of 18 columns along the length of the road surface; the spacing between adjacent columns is 100 mm. The width of each lane on a multi-lane highway (Class III or higher) is typically 3.5-3.75 m, so the sensor array width is taken as 3.5 m. It is worth noting that when using asphalt, the piezoelectric sensors are placed under the asphalt layer.

[0062] In this embodiment, the piezoelectric material used in step S2 is piezoelectric ceramic (PZ), which exhibits the piezoelectric effect, meaning it can generate charge when mechanical stress is applied. This material property makes it suitable for use in sensors to convert mechanical strain into a charge signal output. The charge-to-voltage converter in step S3 includes a capacitor element; the charge of this element is proportional to the input signal. When charge passes through the capacitor, the resulting voltage signal is proportional to the amount of charge, and its voltage V can be calculated using the following formula:

[0063] (1)

[0064] In the above formula, Q represents the amount of charge generated by the piezoelectric sensor, while C represents the capacitance.

[0065] The piezoelectric sensor sensitivity mentioned in step S4 is provided by the manufacturer and refers to the sensor's responsiveness to wheel pressure. The ratio of voltage to wheel pressure can be expressed using the following formula:

[0066] (2)

[0067] In the above formula, ΔV represents the voltage change, and ΔP represents the pressure change. This indicates the sensitivity of the piezoelectric sensor.

[0068] In step S5, based on the sensitivity of the piezoelectric sensor obtained in step S4, the relationship between the voltage and pressure generated by each wheel is acquired, and the corresponding wheel position is determined by analyzing the pressure distribution data. Based on the wheel positions and time intervals obtained in step S5, the average speed of the vehicle is calculated using the following formula.

[0069] (3)

[0070] In the above formula, s represents displacement, and t represents the average time taken for the vehicle to travel through the road segment.

[0071] In step S7, the relationship between pressure and load is converted using the piezoelectric sensor sensitivity formula, which can be expressed as follows:

[0072] (4)

[0073] In the above formula, P j V represents the pressure applied by wheel j. j This indicates that wheel j corresponds to P. j The voltage at that time.

[0074] The calculation of the load on each wheel is done by applying pressure P. j Substitute into the following formula:

[0075] (5)

[0076] In the above formula, F j P represents the load on wheel j. j A represents the pressure applied by wheel j. j This represents the contact area between wheel j and the ground.

[0077] Load F on each wheel j Substitute into the following formula to obtain the total vehicle load:

[0078] (6)

[0079] In the above formula, F represents the total vehicle load. The slope angle is denoted by n, and the number of wheels is denoted by n.

[0080] Substituting the total vehicle load F into the following formula, the total vehicle weight can be obtained:

[0081] (7)

[0082] In the above formula, G m This represents the total vehicle weight, and g represents the acceleration due to gravity, with a value of 9.8. .

[0083] The foregoing details the specific implementation methods of the present invention, further illustrating the technical solution and related beneficial effects. It is understood that the above description is a specific embodiment of the present invention, and any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A piezoelectric intelligent road surface weighing and characterization method based on multi-axle heavy vehicles, characterized in that, Includes the following steps: S1: Select the road surface to be tested, and arrange a piezoelectric sensor array on the cross section of the road surface to form a smart road surface, which is used to measure the pressure distribution generated when a vehicle passes by. S2: When a vehicle passes over a smart road, the applied axial pressure causes strain in the piezoelectric material of the piezoelectric sensor. The mechanical strain is converted into an electrical signal output through the positive piezoelectric effect of the piezoelectric sensor. S3: Based on the charge signal generated in step S2, a corresponding voltage signal is generated through a charge-to-voltage converter; S4: Using the voltage signal obtained in step S3 and combining it with the sensitivity information on the piezoelectric sensor, establish the relationship between voltage and pressure; S5: Analyze the pressure distribution data based on step S4 to determine the position of each wheel of the vehicle; S6: Using the wheel position information obtained in step S5, combined with the time interval and position data of the wheels, calculate the vehicle speed. S7: Based on the pressure data and wheel position information measured in step S5, establish the relationship between pressure and load, and then calculate the weight applied to each wheel. The piezoelectric material used in step S2 is piezoelectric ceramic PZ; the charge-to-voltage converter in step S3 includes a capacitor element; the charge of this capacitor element is proportional to the input signal, and when the charge passes through the capacitor, the generated voltage signal is proportional to the amount of charge, and its voltage V is calculated by the following formula: In the formula, Q represents the amount of charge generated by the piezoelectric sensor, while C represents the capacitance. The specific method for step S7 is as follows: The relationship between pressure and load is converted using the piezoelectric sensor sensitivity formula, expressed as follows: In the formula P j V represents the pressure applied by wheel j. j This indicates that wheel j corresponds to P. j Voltage at that time The sensitivity of the piezoelectric sensor is indicated and provided by the manufacturer of the piezoelectric sensor. The load on each wheel is calculated by applying pressure P to wheel j. j Substitute into the following formula: In the formula F j P represents the load on wheel j. j A represents the pressure applied by wheel j. j This represents the contact area between wheel j and the ground; Load F on each wheel j Substitute the values ​​into the following formula to obtain the total vehicle load: In the above formula, F represents the total vehicle load. The slope angle is denoted by n, and the number of wheels is denoted by n. Substitute the total vehicle load F into the following formula to obtain the total vehicle weight: In the above formula, G m denoted by , where g represents the total vehicle weight and g represents the acceleration due to gravity.

2. The method for weighing and characterizing slope piezoelectric intelligent road surfaces based on multi-axle heavy vehicles according to claim 1, characterized in that, In step S1, the selection of the road surface to be tested involves selecting at least three road sections on the sloping road surface, with the length of each road section being equal to its width. The piezoelectric sensor is placed at a depth of 0.4m down the road surface section.

3. The method for weighing and characterizing slope piezoelectric intelligent road surfaces based on multi-axle heavy vehicles according to claim 2, characterized in that, The piezoelectric sensors on each section of the road surface to be tested are arranged in a staggered, interlocked configuration, with each sensor measuring 100×100×100mm. 3 The piezoelectric sensors are arranged in two rows of 18 columns along the length of the road surface; the spacing between piezoelectric sensors in adjacent columns is 100 mm, and the total width of the piezoelectric sensor array is set to 3.5 m.

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