Vehicle dynamic weighing detection device and method based on speed bump multi-point pressure sensing

Abstract

This invention discloses a vehicle dynamic weighing detection device and method using multi-point pressure sensing based on speed bumps, belonging to the field of intelligent transportation detection technology. The device includes a speed bump body, a pressure plate, pressure sensors, and a mounting bracket. The upper surface of the pressure plate is fixedly attached to the speed bump body, and the upper surface of the pressure sensor is tightly connected to the lower surface of the pressure plate. The mounting bracket is fixed to the road surface foundation, and the pressure sensor is mounted on the mounting bracket, forming a stable force transmission structure from top to bottom. The pressure sensors are divided into front and rear sensor groups along the vehicle's travel direction. The method synchronously collects pressure signals through the dual sensor groups, calculates the original detection weight of a single axle based on the pressure superposition method, and compensates for the vehicle tilt error caused by the speed bump protrusion using the torque balance principle, accumulating the weight axle by axle to obtain the total vehicle weight. This invention achieves the integrated fusion of physical deceleration and dynamic weighing functions.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation detection technology, specifically to a vehicle dynamic weighing detection device and method with speed bump multi-point pressure sensing. Background Technology

[0002] Speed ​​bumps, as a conventional infrastructure in road traffic that forces vehicles to travel at low speeds, are widely deployed at intersections, factory areas, residential areas, bridge entrances, and overload detection sections. Currently, conventional speed bumps on the market only have a single physical deceleration function, relying on rubber or steel structures to limit vehicle speed. They do not integrate any sensor detection modules, making it impossible to collect vehicle load parameters while achieving deceleration, thus failing to fully realize the reuse value of road infrastructure. Vehicle load information is the core basis for judging overload, controlling road load, and protecting the safety of road and bridge structures. Traditional fixed weighbridges require road excavation for installation, have long construction periods, and poor mobility; conventional portable axle load meters are cumbersome to operate. Both need to be deployed separately as independent devices, unable to be linked with road deceleration control, resulting in a disconnect between road deceleration control and vehicle weighing detection functions. This wastes road infrastructure resources and increases construction and maintenance costs.

[0003] Furthermore, existing technologies integrating weighing functions into road structures generally lack a well-designed force transmission structure. Due to the varying widths of vehicle tires and the random offset of their contact points, if the sensor directly bears the road load, problems such as localized concentrated force, uneven force distribution, or even the tire failing to reach the sensor's detection area can easily occur. This leads to discontinuous and unstable pressure signal acquisition, severely impacting the accuracy and reliability of weighing detection. Therefore, how to integrate weighing detection functions with the speed bump structure and construct a stable and uniform force transmission path is a crucial technical problem that needs to be solved to achieve dynamic weighing via speed bumps. Summary of the Invention

[0004] The purpose of this invention is to provide a vehicle dynamic weighing detection device and method with a speed bump dual-row array pressure sensor. It deeply integrates the weighing detection module with conventional road speed bumps, realizing the dual functions of physical deceleration and dynamic weighing. It eliminates the need for separate weighing equipment and large-scale road construction. It can collect vehicle axle load and total weight data in real time and accurately while the vehicle is passing over the speed bump at low speed, improve the load monitoring dimension of the intelligent transportation system, and realize the integrated linkage of traffic control and load detection.

[0005] To achieve the above objectives, the present invention proposes the following technical solution: a vehicle dynamic weighing detection device with multi-point pressure sensing for speed bumps, comprising:

[0006] Speed ​​bump body;

[0007] The pressure plate is fixedly attached to the speed bump body on its upper surface.

[0008] The pressure sensor is divided into a front row sensing group and a rear row sensing group along the vehicle's driving direction. The upper surface of the pressure sensor is tightly attached to the lower surface of the pressure plate.

[0009] The mounting bracket is fixed to the road surface foundation, and the pressure sensor is mounted entirely on the mounting bracket.

[0010] The speed bump body, the pressure plate, the pressure sensor, and the mounting bracket form a force transmission structure from top to bottom.

[0011] Furthermore, in this invention, the front row sensor group and the rear row sensor group are arranged in parallel with uniform spacing, and multiple pressure sensors are evenly distributed in each row along the width direction of the speed bump.

[0012] Furthermore, in this invention, each row of the front and rear sensor groups is equipped with 5 pressure sensors, for a total of 10 pressure sensors forming an array-type detection layout.

[0013] Furthermore, in this invention, the pressure plate is an integral rigid flat plate structure, and its effective force-bearing width covers the full width of the speed bump body, which is used to evenly spread and transfer the local concentrated load when the vehicle tire rolls over it to the pressure sensor below.

[0014] Furthermore, in this invention, the speed bump body adopts a high-strength wear-resistant rubber or steel one-piece molded structure, which has a raised arc and compressive strength.

[0015] It also includes a sealing device and an elastic sealing device. The pressure sensor and the mounting bracket are sealed and protected by the sealing device and the elastic sealing device to form an independent sealed cavity. The cavity is filled with waterproof and insulating sealant to block the intrusion path of rainwater and sand.

[0016] The elastic sealing device is made of weather-resistant, flexible, and waterproof elastic material. It has an overall elastic sealing ring structure and is tightly bonded to the upper outer side of the sealing device.

[0017] The detection method of the vehicle dynamic weighing detection device based on the above-mentioned speed bump multi-point pressure sensing is characterized by employing a dual-row array pressure sensor consisting of a front row sensor group and a rear row sensor group arranged along the vehicle's driving direction inside the speed bump, and includes the following steps:

[0018] S1: When the vehicle wheels run over the speed bump, the pressure sensors of the front and rear sensor groups synchronously collect pressure signals.

[0019] S2: Sum the pressure values ​​of each pressure sensor in the front row sensor group to obtain the total front row pressure; sum the pressure values ​​of each pressure sensor in the rear row sensor group to obtain the total rear row pressure; add the total front row pressure to the total rear row pressure to obtain the original single-axis measured weight. The calculation formula is as follows:

[0020]

[0021] In the formula, This is the original weight measured on a single axis. This is the sum of the pressure values ​​from all the pressure sensors in the front row sensor group. This is the sum of the pressure values ​​of all pressure sensors in the rear row sensor group;

[0022] S3: Based on the principle of torque balance, combined with parameters such as the height of the speed bump, the vehicle wheelbase, and the center of gravity, the vehicle body tilt error caused by the speed bump is compensated and corrected to obtain the true weight of a single axle.

[0023] S4: Repeat steps S1 to S3 for each axle of the vehicle, and add up the actual weight of each axle one by one to obtain the total detected weight of the vehicle.

[0024] Furthermore, in this invention, a system wake-up and self-test phase is included before step S1:

[0025] Initialize and perform fault self-check on all pressure sensor channels of the front and rear sensor groups;

[0026] When the detection channel is normal, the weighing and detection process begins; when the detection channel is abnormal, a fault alarm is triggered and the detection process is terminated.

[0027] Furthermore, in this invention, a sensor redundancy verification and fault self-correction stage is also included between step S1 and step S2:

[0028] Perform three quantitative checks on each pressure sensor: signal validity, neighborhood correlation, and time consistency, and identify faulty sensors.

[0029] The neighborhood correlation deviation rate is calculated using the following formula:

[0030] ;

[0031] In the formula, For the first Neighborhood correlation deviation rate of road sensors For the first Real-time pressure data collected by the road sensor. For the first The average pressure of adjacent effective sensors in the same row of the road sensor; when If the correlation is greater than 20%, the sensor's neighborhood correlation test is deemed to have failed.

[0032] The time consistency deviation rate is calculated using the following formula:

[0033] ;

[0034] In the formula, For the first Time consistency deviation rate of road sensors For the first The trigger time of the road sensor For the first The dual rows of road sensors correspond to the sensor trigger times. The average standard trigger time difference between the front and rear sensors; when If the error rate is greater than 50%, the time consistency check of the sensor is deemed to have failed.

[0035] Based on the number and location of faulty sensors, a hierarchical weighted completion strategy is used to complete the faulty sensor data to obtain the corrected effective pressure value.

[0036] The effective accuracy deviation rate is calculated based on the number of faulty sensors, and the detection accuracy level is determined.

[0037] Furthermore, in this invention, the specific calculation of tilt error compensation correction in step S3 includes:

[0038] Based on the height of the speed bump With vehicle wheelbase Calculate the vehicle body tilt angle, using a small angle approximation:

[0039]

[0040] In the formula, The vehicle body tilt angle, The height of the speed bump. This refers to the vehicle's wheelbase.

[0041] Calculate the forward shift of the vehicle's center of gravity in the horizontal direction:

[0042]

[0043] In the formula, This is the amount by which the center of gravity shifts forward horizontally. The height of the vehicle's center of gravity. The height of the speed bump. This refers to the vehicle's wheelbase.

[0044] Based on the moment balance equation with the non-measured axis as the fulcrum, the tilt error value is calculated as follows:

[0045]

[0046] In the formula, This is the tilt error value. This is the original weight measured on a single axis. The height of the vehicle's center of gravity. The height of the speed bump. This refers to the vehicle's wheelbase.

[0047] Calculate the actual weight of a single axis:

[0048]

[0049] In the formula, This is the actual weight of a single axis. This is the original weight measured on a single axis. This represents the tilt error value, and the error direction is determined and corrected based on the vehicle's tilt posture.

[0050] Furthermore, in this invention, the method further includes the following after step S4:

[0051] The total measured weight data was filtered for noise reduction and stability verification.

[0052] The axle load, total weight, and inspection time information are stored locally and then uploaded to the management platform.

[0053] The total detected weight is compared with the preset over-limit threshold. When the total detected weight exceeds the limit, an over-limit alarm is triggered and the detection record is saved; when the limit is not exceeded, the detection process is completed and the system returns to standby mode.

[0054] Beneficial effects: The technical solution of this application has the following technical effects:

[0055] This invention deeply integrates the pressure sensor and the speed bump body into an integrated structure, which retains the original physical deceleration function of the speed bump while giving it dynamic weighing and detection capabilities. It eliminates the need to install separate weighing equipment on the road and large-scale road construction, making full use of road infrastructure resources and effectively reducing construction, installation and subsequent operation and maintenance costs. It realizes the integrated linkage of road deceleration control and vehicle load detection functions.

[0056] This invention, by setting a pressure plate to cover the full width of the speed bump, evenly distributes and transmits the localized concentrated load when a vehicle tire rolls over it to the pressure sensor below. Simultaneously, the pressure sensor is mounted on a bracket fixed to the road surface, forming a stable force transmission structure from top to bottom: "speed bump body – pressure plate – pressure sensor – mounting bracket." This effectively avoids problems such as uneven force distribution, localized suspension, or inability to reach the sensor detection area caused by narrow tire width or offset rolling position. It ensures the continuity, stability, and reliability of pressure signal acquisition, significantly improving the accuracy of dynamic weighing detection.

[0057] It should be understood that all combinations of the foregoing concepts and the additional concepts described in more detail below can be considered part of the inventive subject matter of this disclosure, provided that such concepts do not contradict each other.

[0058] The foregoing and other aspects, embodiments, and features of the teachings of the present invention will be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the invention, such as features and / or beneficial effects of exemplary embodiments, will become apparent from the following description or may be learned through practice of specific embodiments according to the teachings of the present invention. Attached Figure Description

[0059] The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component shown in the various figures may be denoted by the same reference numeral. For clarity, not every component is labeled in each figure. Embodiments of various aspects of the invention will now be described by way of example and with reference to the accompanying drawings, wherein:

[0060] Figure 1 This is a schematic diagram of the structure of the present invention;

[0061] Figure 2 Schematic diagram of pressure sensor installation;

[0062] Figure 3 This is a flowchart of the testing process;

[0063] Figure 4 This is a schematic diagram of a pressure sensor receiver.

[0064] Figure 5 A diagram showing the front wheels of a vehicle driving over a speed bump;

[0065] Figure 6 A diagram showing the rear wheels of a vehicle driving over a speed bump;

[0066] Figure 7 This is a schematic diagram of the module architecture;

[0067] Figure 8 This is a schematic diagram of a pressure sensor being fixed to a load-bearing plate by bolts.

[0068] The meanings of the reference numerals in the figure are as follows: 10, speed bump body; 20, pressure plate; 30, pressure sensor; 40, mounting bracket; 50, sealing device; 60, elastic sealing device; 70, bolt. Detailed Implementation

[0069] The embodiments of the invention are described in detail below with reference to the accompanying drawings to clearly illustrate the structure, purpose, advantages, positional relationships, and connection methods of each component. It should be noted that the directional indications (such as "front," "back," "up," and "down") involved in this embodiment are based on the posture shown in the drawings and are only used to describe the relative positional relationships and movement of the components. If the posture changes, the directional indications will be adjusted accordingly. The term "connection" includes mechanical connections and electrical connections, and can be fixed connections, detachable connections, or indirect connections through an intermediate medium. The specific meaning is understood by those skilled in the art based on the context.

[0070] Example 1: Vehicle dynamic weighing detection device with multi-point pressure sensing for speed bumps

[0071] The overall structure of the device is as follows Figure 1 , Figure 2 As shown, this embodiment provides a vehicle dynamic weighing detection device with multi-point pressure sensing based on speed bumps. This device is an integrated structure, mainly composed of a speed bump body 10, a pressure plate 20, a pressure sensor 30, a mounting bracket 40, a sealing device 50, and an elastic sealing device 60. The components are arranged in the following order: speed bump body 10—pressure plate 20—pressure sensor 30—mounting bracket 40. The elastic sealing device 60 is installed on top of the sealing device 50, and both are installed around the pressure sensor 30 to seal and protect it, achieving integrated functionality of physical deceleration and dynamic weighing. The overall structure is compact, easy to install, and suitable for long-term use in various road scenarios such as intersections, factory areas, residential areas, bridge entrances, and overload detection sections.

[0072] The speed bump body 10 is located on the top layer of the device, directly contacting the vehicle tires. It serves as the outer load-bearing structure and the physical deceleration actuator of the entire device. The speed bump body 10 is made of high-strength, wear-resistant rubber or steel in a single molded structure, possessing the raised curvature and compressive strength of a conventional speed bump. It generates a forced deceleration effect when a vehicle passes over it, compelling the vehicle to pass through the detection area at a low speed, providing a stable low-speed detection condition for dynamic weighing. The raised curvature design of the speed bump body 10 ensures both the deceleration effect when the vehicle passes over it and avoids damage to the internal sensors from excessive impact force. The bottom surface of the speed bump body 10 is flat, designed to tightly adhere to the upper surface of the pressure plate 20 below, ensuring no relative displacement or gap between them, and guaranteeing that the load during vehicle crushing can be transmitted downwards completely and without loss.

[0073] The pressure plate 20 is located below the speed bump body 10, and its upper surface is fixedly attached to the speed bump body 10. The pressure plate 20 adopts an integral rigid plate structure, and its effective force-bearing width covers the full width of the speed bump body 10. The core function of the pressure plate 20 is to achieve uniform load distribution and stable transmission. When a vehicle tire rolls over the speed bump, the contact area between the tire and the speed bump body 10 is limited, resulting in a localized concentrated load. If this load is directly applied to the pressure sensor 30 below, it will lead to uneven force distribution, overload of some sensors, and no signal from other sensors. Through its integral rigid plate structure, the pressure plate 20 can evenly distribute the localized concentrated load from above into a surface-distributed load and stably transmit it to the multiple pressure sensors 30 below. This design effectively avoids problems such as uneven force distribution, localized suspension, or inability to reach the sensor detection area caused by narrow tire width or offset rolling position, ensuring the continuity, stability, and reliability of pressure signal acquisition. The lower surface of the pressure plate 20 is a precision-machined plane, which is used to fit tightly and rigidly connect with the upper bearing surface of the pressure sensor 30 below, ensuring that the force transmission path is uninterrupted and attenuated. Specifically, the upper bearing surface of the pressure sensor 30 and the lower surface of the pressure plate 20 are connected by a pre-tightening locking method to achieve tight fit and rigid connection. The symmetrically arranged internal hexagon countersunk bolts are vertically pre-tightened to ensure that when the sensor is subjected to pressure and produces a small elastic displacement within the allowable range, there is always no gap, no slippage, and no off-center load between the two, ensuring that the pressure is transmitted vertically and uniformly, without affecting the normal force output and dynamic detection accuracy of the sensor.

[0074] The load-bearing pressure plate 20 is made of Q345B low-alloy high-strength structural steel or 6061 T6 hard aluminum alloy, with a galvanized anti-corrosion treatment. The thickness is 12mm to 20mm, with 12mm to 16mm used for regular road sections and 16mm to 20mm used for heavy-load inspection sections. It is fixed to the speed bump body 10 by a combination of mechanical locking and structural adhesive bonding. The bottom of the speed bump body 10 has a recessed installation groove, and the load-bearing pressure plate 20 is fully embedded and tightly fitted. It is rigidly connected to the speed bump body 10 by internal hexagon countersunk bolts evenly distributed around the plate and in the center. The bonding surface is coated with polyurethane or epoxy resin high-strength structural adhesive to eliminate micro gaps, and the joints are filled with waterproof sealant to achieve integrated fixing with no relative displacement and reliable sealing.

[0075] The pressure sensor 30 is the core detection component of the entire device, responsible for converting mechanical pressure signals into electrical signals to achieve quantitative acquisition of vehicle axle load. The upper bearing surface of the pressure sensor 30 is tightly fitted and rigidly connected to the lower surface of the force-bearing plate 20, and the lower end is integrally mounted on the mounting bracket 40. The pressure sensor 30 is preferably a resistance strain gauge pressure sensor, suitable for high-precision dynamic compressive load sensors, specifically designed for vehicle dynamic weighing scenarios. It avoids piezoelectric and capacitive types, which are unsuitable for long-term static loads and continuous dynamic data acquisition. Its key performance parameters should meet the following requirements: measurement range coverage of 0–30kN (normal road sections) and 0–100kN (heavy-load detection road sections), capable of covering the maximum single-wheel load of common vehicles; sampling frequency not less than 1kHz, ensuring no signal loss during dynamic compaction; overall accuracy level not less than 0.05; nonlinearity error ≤ ±0.05% FS; hysteresis error ≤ ±0.03% FS; repeatability error ≤ ±0.02% FS; response time ≤ 1ms; protection level not less than IP68; operating temperature -30℃ to +80℃; and characteristics of impact resistance, fatigue resistance, and long-term stable output, adapting to the high-frequency acquisition and high-precision measurement requirements of low-speed dynamic road weighing.

[0076] like Figure 2 , Figure 4 As shown, the pressure sensors 30 are divided into a front row sensor group and a rear row sensor group along the vehicle's direction of travel. The front row sensor group and the rear row sensor group are arranged parallel to each other and evenly spaced. Five pressure sensors 30 are evenly distributed in each row along the width of the speed bump. The front row sensor group includes pressure sensors 1 to 5 (i.e., P1, P2, P3, P4, P5), and the rear row sensor group includes pressure sensors 6 to 10 (i.e., P6, P7, P8, P9, P10, P11, P12, P13, P14, P15). 10 A total of 10 pressure sensors (30 in total) form a double-row, five-column array detection layout.

[0077] The purpose and advantages of adopting the above-mentioned double-row array layout are:

[0078] First, full-width coverage detection. Five pressure sensors 30 are evenly distributed along the width of the speed bump in each row. No matter where the left or right wheel is rolling over the speed bump, multiple pressure sensors 30 can be simultaneously covered, forming a full-width force detection, completely avoiding detection blind spots caused by wheel misalignment or under-stress.

[0079] Second, tilt error compensation. The front and rear sensor groups are arranged along the driving direction, with a fixed spacing between them. When the vehicle wheels drive over a speed bump, the raised structure of the speed bump body 10 causes the vehicle body to tilt and the center of gravity to shift, causing the measured value of the axle to deviate from the true value. By comparing the pressure difference between the front and rear sensor groups and combining the torque balance principle, the system error caused by the vehicle body tilt can be calculated and accurately compensated and corrected, thereby obtaining the true axle weight of the vehicle.

[0080] Third, redundancy in detection. The dual-row, 10-channel sensor array forms a redundant detection array. Even if a local sensor malfunctions or becomes abnormal, the data from adjacent normal sensors can be used to supplement the detection, without affecting the accuracy of the overall detection results. This enhances the stability and reliability of the device during long-term operation in harsh road environments.

[0081] The mounting bracket 40 is located at the bottom of the entire device, securely embedded or fixed to the road surface foundation, and serves as the structural foundation and mechanical support component of the entire device. The mounting bracket 40 provides a stable mounting reference surface and rigid support for the pressure sensor 30, ensuring that the pressure sensor 30 does not shift, settle, or tilt under dynamic conditions of repeated vehicle traffic. The pressure sensor 30 is mounted entirely on the mounting bracket 40, which ultimately transfers the entire load borne by the sensor to the road surface foundation, forming a complete closed force transmission chain from top to bottom. The structural rigidity and fixing reliability of the mounting bracket 40 directly determine the stability and accuracy of the data collected by the pressure sensor 30.

[0082] This device adopts a fully enclosed, integrated sealed protection design, which is suitable for long-term harsh working conditions such as outdoor roads, rainwater, mud, sand, high and low temperatures, ensuring the stable and reliable operation of internal sensors and circuits.

[0083] The pressure sensor 30 and the mounting bracket 40 are sealed and protected by a sealing device 50 and an elastic sealing device 60, forming an independent sealed cavity. The cavity is filled with waterproof and insulating sealant to block the intrusion path of rainwater and sand. Specifically, the elastic sealing device 60 is mainly made of weather-resistant flexible waterproof elastic material and has an overall elastic sealing ring structure. It is tightly bonded to the upper outer side of the sealing device 50, adapting to the dynamic stress conditions when a vehicle runs over a speed bump. When the wheel rolls over the speed bump, causing the pressure plate 20 to undergo a slight elastic displacement downward, the elastic sealing device 60 can undergo controllable tensile and compressive deformation with the displacement, always maintaining a gapless and non-detached sealing interface. While ensuring the reliability of the seal, it absorbs dynamic impact stress, protects the sealing device 50 and the internal pressure sensor 30, and achieves the dual functions of sealing and buffering.

[0084] All electrical cables are led out using a double-sealing method with waterproof aviation plugs and sealing rings, and the lead-out holes are sealed with glue. The overall protection level of the device is no less than IP68, which can withstand rain immersion, siltation and high and low temperature cycles, and meet the protection requirements for long-term continuous use on outdoor roads.

[0085] The overall working principle of the device in this embodiment is as follows: When a vehicle passes over a speed bump at low speed, the speed bump body 10 first bears the crushing load of the vehicle tires and achieves physical deceleration. The load is transferred through the speed bump body 10 to the force-bearing plate 20, which is fixedly attached to it. The force-bearing plate 20 uses its integral rigid flat plate structure to evenly distribute the local concentrated load into a surface distributed load. The evenly distributed load is transferred to the pressure sensor 30, which is tightly attached below. The five pressure sensors in the front row and the five pressure sensors in the rear row synchronously collect force data and convert the mechanical pressure signal into an electrical signal output. The pressure sensor 30 transfers the entire load to the mounting bracket 40 installed on the road surface, completing the final force transmission closure. The system performs single-axle weight calculation, tilt error compensation correction, and multi-axle cumulative calculation based on the pressure data collected by the front and rear row sensors, and finally accurately obtains the true weight of each axle of the vehicle and the total weight of the vehicle. The entire detection process is automatically completed within a few seconds of the vehicle passing over the speed bump without manual intervention, realizing the integrated linkage of physical deceleration and dynamic weighing.

[0086] Example 2: Vehicle dynamic weighing detection method using speed bump multi-point pressure sensing

[0087] This embodiment provides a vehicle dynamic weighing detection method using a speed bump multi-point pressure sensor, such as... Figure 3 The method employs a dual-row array of pressure sensors, consisting of a front row sensor group and a rear row sensor group, arranged along the vehicle's direction of travel inside the speed bump, as described in Embodiment 1. The front row sensor group comprises 5 pressure sensors P1-P5, and the rear row sensor group comprises 5 pressure sensors P6-P7. 10 .

[0088] Based on the principles of rigid body statics force balance and torque error compensation, the system automatically completes five stages during the process of a vehicle driving over a speed bump at low speed: system wake-up and self-test, sensor redundancy verification and fault self-correction, single-axle weighing and error compensation, multi-axle detection and total weight calculation, and over-limit judgment and process completion. This fully automated process accurately detects the actual weight of each axle and the total weight of the vehicle. The specific steps, calculation formulas, and functional principles of each stage are explained in detail below.

[0089] During the system wake-up and self-test phase, when a vehicle enters the monitoring area at low speed, the system is woken up and enters the self-test process. The purpose of this phase is to ensure that all sensor channels are working properly and that signal transmission is stable, providing a reliable hardware foundation for subsequent accurate weighing.

[0090] The system initializes and performs fault self-checks on 10 pressure sensor channels in the front and rear sensor groups. The initialization process includes zero-point calibration, range verification, and communication link connectivity testing for each sensor. After the self-check, the system determines whether the detection channels are normal: if all channels are normal, the system proceeds to the formal weighing test; if any channel is abnormal, a fault alarm is triggered, and the current testing process is immediately terminated to prevent erroneous data from interfering with the test results.

[0091] The functional principle of this stage is as follows: Dynamic weighing requires extremely high accuracy of sensor data; any hardware failure or signal abnormality in the sensor will lead to distortion of the subsequent weight calculation results. By setting up a self-testing step before formal testing, the risk of hardware failure can be eliminated at the source, ensuring that the sensor array entering the weighing process is in good working order.

[0092] The sensor redundancy verification and fault self-correction stage is performed after pressure signal acquisition and before single-axis raw weight calculation. Based on the array redundancy characteristics of the dual-row, five-column, ten-channel pressure sensor, it sequentially completes three sub-steps: sensor fault quantification and judgment, fault data weighted completion, and detection accuracy level quantification. The input for this stage is the pressure value P acquired by the sensor. x and trigger time T x The output is the corrected effective pressure value P. comp (x) Detection accuracy grade (Grade) and accuracy deviation rate (AR), the output results are directly input into the single-axis raw weight calculation step to participate in G. 轴原 The solution.

[0093] Sensor fault quantification is performed on each pressure sensor by checking signal validity, neighborhood correlation, and time consistency. If any check fails, the sensor is determined to be faulty.

[0094] Signal validity verification determines whether the acquired value is 0 (open circuit fault) or exceeds the sensor's range (short circuit fault). This is the most basic hardware fault detection, used to rule out obvious electrical faults. The execution logic is as follows: Open circuit fault detection occurs when the x-th sensor acquires the pressure value P... x = 0, and there is no pressure signal output during the effective rolling period of the wheel, indicating a short circuit fault (wire disconnection, no power supply, or no signal output) for the sensor. Short circuit fault determination occurs when the x-th sensor collects the pressure value P. x >110% × F s (F) s (Based on the sensor's rated range), a short-circuit fault (circuit short circuit, signal drift overload, or hardware breakdown) is determined for the sensor. Threshold explanation: 10% exceeding the range is a common engineering safety threshold, which covers normal load fluctuations while reliably identifying short-circuit overload anomalies.

[0095] The triple verification adopts a serial priority execution mechanism. Only after the previous verification passes can the subsequent verification proceed. If any verification fails, the sensor is directly judged as faulty and the subsequent verification process is terminated. The execution order is as follows: First, the signal validity verification, a basic hardware verification, is performed to exclude hardware-level faults such as open circuits and short circuits. Only sensors that pass the verification proceed to the next stage. Second, the neighborhood correlation verification is performed on the sensors with valid signals, that is, the consistency of the forces on adjacent sensors in the same row in the spatial dimension. Finally, the time consistency verification is performed on the sensors that have passed the first two verifications, that is, the matching of the trigger times of the front and rear rows in the time dimension.

[0096] Neighborhood correlation verification is based on the mechanical characteristics that adjacent sensors in the same row should have correlated forces when the same axle rolls over a speed bump. The reasonableness of the data is determined by comparing the pressure deviation of a certain sensor with its adjacent sensors in the same row. The neighborhood correlation deviation rate DR(x) of the x-th sensor is calculated according to formula (1):

[0097] (1)

[0098] In the formula, P x P represents the real-time pressure reading (in N) of the x-th sensor, x ∈ [1, 10], where x = 15 for the front sensors and x = 610 for the rear sensors; neighbor(x) The average pressure of adjacent effective sensors in the same row as the x-th sensor is calculated according to formula (2):

[0099] (2)

[0100] In the formula, n is the number of adjacent sensors in the same row that are in normal condition. If DR(x) > 20%, the neighborhood correlation verification of the sensor is deemed to have failed. The 20% threshold is set based on the fact that under normal operating conditions, the pressure difference between adjacent sensors in the same row is usually no more than 15% due to the uniform diffusion of the load on the pressure plate. The 20% threshold provides a certain margin and can reliably distinguish between normal fluctuations and fault anomalies.

[0101] Time consistency verification is based on the kinematic characteristics that the time interval between the wheels rolling over the front and rear row sensors should match the vehicle speed and row spacing. The time consistency of the sensor responses is determined by comparing the trigger time differences of the corresponding sensors in the front and rear rows. The time consistency deviation rate TDR(x) between the x-th sensor and the corresponding sensors in both rows is calculated according to equation (3):

[0102] (3)

[0103] In the formula, T x T is the trigger time of the x-th sensor (in milliseconds); pair(x)The trigger time of the double row of sensors corresponding to the x-th sensor (e.g., x=1 corresponds to x=6, x=2 corresponds to x=7, and so on). The average standard trigger time difference of the front and rear row sensors is calculated by formula (4) based on experimental calibration:

[0104] (4)

[0105] In the formula, L is the center-to-center distance between the front and rear rows of sensors (unit: m), V avg The average vehicle speed (in m / s) on the road section is calculated from historical data. If TDR(x) > 50%, the sensor's time consistency check fails. The spacing d between the front and rear sensor groups along the vehicle's direction of travel is 80mm to 150mm, with 100mm being the preferred standard spacing. This spacing is designed to ensure that when a single axle wheel is rolling over a tire, the front and rear sensors can simultaneously cover the same tire contact area, achieving stable pressure difference data acquisition and meeting the mechanical calculation requirements for torque balance error compensation. Simultaneously, it avoids signal coupling interference due to excessively small spacing and the inability to simultaneously trigger dual-row detection on a single axle due to excessively large spacing. It is suitable for tire widths of various small cars to heavy trucks and low-speed dynamic weighing conditions, ensuring tilt error compensation and axle load detection accuracy.

[0106] The synergistic effect of the triple verification is that signal validity verification eliminates hardware-level faults, neighborhood correlation verification eliminates spatial data anomalies, and time consistency verification eliminates temporal response anomalies. The three cross-verify from different dimensions to achieve a comprehensive and accurate determination of sensor faults.

[0107] Faulty sensor data is weighted and completed. Based on the number and location of faulty sensors, a hierarchical weighted completion strategy is adopted. The completed pressure value P comp (x) is used as valid data in subsequent weight calculations.

[0108] For single-channel sensor fault completion, when only a single-channel sensor is faulty, weighted interpolation is performed using data from adjacent normal sensors in the same row. The completion pressure value of the faulty sensor in channel x is calculated according to formula (5):

[0109]

[0110] In the formula, Pᵢ is the pressure value (in N) of the i-th adjacent normal sensor in the same row; Wᵢ is the weighting coefficient of adjacent sensors, with 0.6 for the immediate neighbor sensor and 0.4 for the next neighbor sensor, and Wᵢ=1 for only one neighbor; K pos(x) is the position correction coefficient. The coefficient is 1.1 for edge column sensors (x=1,5,4,10), 1.05 for middle column sensors (x=2,6,3,9), and 1.0 for center column sensors (x=3,8). This coefficient is calibrated based on the speed bump width and tire contact characteristics.

[0111] The design principle of the position correction coefficient is that although the pressure plate can evenly distribute the load, the sensor at the edge position is affected by the tire contact range, and its force characteristics are different from those at the center position. By correcting the completion value of the sensor at different positions through the position correction coefficient, the completion accuracy can be improved.

[0112] For fault completion of two adjacent sensors in the same row, when two adjacent sensors in the same row fail simultaneously, the available data in the same row is insufficient to complete accurate interpolation. Therefore, cross-row completion is performed using the normal sensor data of the corresponding columns in both rows. The completion pressure value of the faulty sensor x-th channel is calculated according to formula (6):

[0113] (6)

[0114] In the formula, P pair (x) represents the average pressure (in N) of all normal sensors in the corresponding column of the double row; K row To adjust for the load differences between the front and rear wheels, a correction factor of 0.95 is used for front-row faults and 1.05 for rear-row faults; K load The load correction factor is dynamically calculated according to equation (7):

[0115] (7)

[0116] In the formula, P axis The estimated load on the current axle (in N) is initially calculated from the sum of the pressures from the front and rear sensors; P std(axis) The standard axle load (unit: N) for this vehicle model is retrieved from the vehicle model load database built into the device.

[0117] The principle of the cross-row completion strategy is that the dual-row sensors form a redundant detection pair in the same column. The sensors at the corresponding positions of the front and rear rows detect the load of the same wheel passing through at different times. There is a definite mechanical correlation between the two. Therefore, the data of the faulty row can be calculated using the data of the normal row. The row correction coefficient and the load correction coefficient compensate for the load difference between the front and rear rows and the influence of the actual load deviating from the standard value.

[0118] After completing the fault data, the system quantifies the accuracy level of the test results, making the reliability of the test results digital and transparent. First, the effective accuracy deviation rate AR is calculated according to formula (8), and then the accuracy level Grade is determined according to formula (9). The accuracy level and the test results are uploaded to the management platform simultaneously.

[0119]

[0120] In the formula, N fault N represents the number of faulty sensors. total The total number of sensors (N) total =10); α is the single-path fault accuracy influence coefficient, experimentally calibrated to 0.05; β is the sensor's inherent basic deviation coefficient, taken as 0.02.

[0121]

[0122] In the formula, Grade A represents the highest accuracy with no faults, and the test results can be directly accepted; Grade B represents the accuracy with minor faults, with a deviation of less than 5%, and can be used normally; Grade C represents the accuracy with more faults, with a deviation of 5~10%, and the device automatically sends fault repair prompts to the operation and maintenance platform.

[0123] The purpose of quantifying the detection accuracy level is to enable the control platform to use the detection data reasonably according to the accuracy level. Level A data can be directly used for law enforcement judgment, Level B data can be used for screening and early warning, and Level C data is only for reference and triggers equipment maintenance, thereby avoiding misjudgment or missed judgment due to sensor failure.

[0124] The overall synergistic effect of the sensor redundancy verification and fault self-correction stage is as follows: fault quantification identifies problematic sensors, data weighting and completion utilizes array redundancy characteristics to recover missing data, and accuracy level quantification evaluates the reliability of the completed data. These three sub-steps form a complete closed loop of "identifying problems, repairing data, and evaluating quality," ensuring that subsequent weight calculations have both data input and quality assurance.

[0125] The single-axis weighing and error compensation stage is the core calculation step of the entire detection method, which sequentially completes the two steps of calculating the original weight of the single axis and correcting the tilt error.

[0126] For single-axle raw weight calculation, when a single axle wheel of the vehicle runs over a speed bump, the front 5-channel pressure sensors and the rear 5-channel pressure sensors synchronously collect real-time pressure signals to achieve full-wheel width coverage detection. The system first calculates the total pressure of the front and rear sensor groups separately, and then adds the total pressure of both groups to obtain the raw detection weight of the corresponding single axle. The specific calculation formula is as follows:

[0127] Total pressure from front sensors:

[0128]

[0129] Total pressure from rear sensors:

[0130]

[0131] Single-axis raw measurement weight:

[0132]

[0133] In the formula: P 前总 P represents the total pressure from the front sensors (unit: N). 后总 The total pressure from the rear sensors (unit: N), G 轴原 The original weight measured on a single axis (unit: N); P comp(1) To P comp(10) These are the effective pressure values ​​of each channel after processing through the sensor redundancy verification and fault self-correction stages.

[0134] The pressure integration method employs a combination of summing the pressure values ​​from the front five rows and summing them from the rear five rows. The principle is as follows: when a wheel rolls over a speed bump, the load is evenly distributed to the front and rear rows of sensors below via a pressure plate. Each row of sensors bears a portion of the load, and the sum of these two loads represents the total pressure exerted by the axle on the speed bump. The full coverage deployment of five sensors per row along the width ensures that regardless of the lateral position of the wheel, at least one sensor is effectively loaded. The sum of the pressure values ​​from each row reflects the total lateral load borne by that row.

[0135] Tilt error compensation correction, such as Figure 5 , Figure 6 As shown, because the speed bump body 10 has a raised structure, when a single axle wheel of a vehicle runs over the speed bump, the tested axle is raised, the vehicle body tilts, and the vehicle's center of gravity shifts horizontally, disrupting the original inter-axle torque balance and causing the force on the tested axle to deviate from the true value. The greater the height of the protrusion and the greater the tilt angle, the more significant the measurement error. Therefore, this structural systematic error must be compensated and corrected to obtain the true weight of a single axle.

[0136] The specific calculation steps for tilt error compensation correction are as follows:

[0137] Step 1: Calculate the vehicle tilt angle θ. Based on the speed bump protrusion height h (in meters) and the vehicle wheelbase L (in meters, the horizontal distance between the front and rear axles), when the front axle hits the speed bump while the rear axle remains on the road, the front axle is raised by h. A small angle approximation is used:

[0138]

[0139] The applicable conditions for this small angle approximation are: the height h of a typical speed bump is generally 3070mm, the wheelbase L of a vehicle is generally 2.57m, the h / L ratio is on the order of 0.004~0.028, the tilt angle is extremely small, and the error introduced by the small angle approximation can be ignored.

[0140] Step 2: Calculate the horizontal forward shift of the center of gravity, Δx. After the vehicle tilts, the vehicle's center of gravity shifts forward in the horizontal direction:

[0141]

[0142] In the formula, H G The height of the vehicle's center of gravity (unit: m). The mechanical consequence of shifting the center of gravity forward is that the torque balance with the non-measured axle as the fulcrum is broken, the support reaction force of the measured axle increases, and the measured value is larger than the true value.

[0143] The vehicle's center of gravity height H in the tilt error compensation formula G The vehicle wheelbase L is obtained through a combination of vehicle model database matching and real-time detection and recognition: The system first identifies vehicle brand, model, and other characteristics, matches them with the built-in standard vehicle model parameter library, and retrieves the standard center of gravity height HG0 and standard wheelbase L0 for the corresponding vehicle model; then, combining the trigger time difference of the dual-row sensors and vehicle speed, it calculates the measured wheelbase L in real time and calibrates and corrects the standard wheelbase; the center of gravity height HG0 is obtained through a combination of these parameters. G Then adopt the standard center of gravity height H of the same model. G0 By combining the axle load detection results with a small adaptive correction, the final H value used for compensation calculation is obtained. G With L, ensure that the error compensation parameters are accurate and usable.

[0144] Step 3: Calculate the tilt error value ΔG based on the torque balance equation. Using the non-measured shaft as the torque fulcrum, write the torque balance equation:

[0145]

[0146] Substituting the forward shift of the center of gravity Δx into the above formula and rearranging, the error value can be obtained. Combining the mechanical relationship between the total pressure difference ΔP of the dual-row sensors and the wheelbase and row spacing, the error value is calibrated and optimized. The final compensation error formula adapted to this device is:

[0147]

[0148] In the formula: ΔG is the tilt system error value (unit: N), G 轴原 H represents the original uniaxial weight (in N) obtained by grouping and summing. G , where h is the height of the vehicle's center of gravity (unit: m), h is the height of the speed bump (unit: m), and L is the vehicle's wheelbase (unit: m).

[0149] Step 4: Calculate the actual weight G of a single axis. 轴真 .

[0150]

[0151] Where: G 轴真This represents the actual weight of a single axis (unit: N). Because the measured axis is tilted forward, the measured value is too high; therefore, a subtraction correction is used: G 轴真 =G 轴原 −ΔG is used to correct and eliminate the detection deviation caused by the height difference of the bump. The error direction is determined based on the vehicle's tilt posture. When the front axle is on the speed bump and the rear axle is on the road, the front axle detection value is too high, so subtraction is used; when the rear wheel runs over the speed bump, the rear axle detection value is too high, so subtraction is also used.

[0152] The underlying mechanical principle of tilt error compensation is as follows: the speed bump raises the axle under test, causing a slight rotation of the vehicle around the non-tested axle. This changes the lever arm of the center of gravity relative to the non-tested axle. According to the static torque equilibrium condition of rigid bodies, the support reaction force of the tested axle must change accordingly. This method derives a quantitative deviation relationship between the detected value and the true value by accurately calculating the change in lever arm caused by the center of gravity shift, thereby achieving precise compensation for system errors. The front-to-rear arrangement of dual-row sensors provides the structural basis for this compensation—the pressure difference between the front and rear rows directly reflects the tilt force state of the vehicle on the speed bump, providing measured data support for the error correction model.

[0153] In the multi-axle detection and total weight calculation stage, after the front axle detection is completed and the accurate detection weight is output, the system determines whether the rear axle has entered the detection area: if the rear axle signal is detected, the entire process of the single axle weighing and error compensation stage is repeated to complete the accurate weighing of the rear axle (and each axle of the subsequent multi-axle vehicle); if the rear axle signal is not detected within the time limit, the system automatically exits the detection.

[0154] After each axle is inspected, based on the principle of conservation of mechanics that the total weight of the vehicle equals the sum of the actual weights of each axle, the actual weights of all axles are added up one axle at a time to obtain the total inspected weight of the vehicle.

[0155]

[0156] Where: G 总 G represents the total weight of the vehicle (in N). 轴1真 G 轴2真 ...G 轴n真 These are the actual weights of each axle after error compensation (unit: N), where n is the total number of axles in the vehicle.

[0157] The total weight data undergoes filtering, noise reduction, and stability verification to eliminate impact interference signals generated during dynamic compaction, ensuring the final output data is stable and reliable. Information such as axle load, total weight, and inspection time is stored locally and simultaneously uploaded to the intelligent traffic management platform.

[0158] The principle behind the axle-by-axle measurement and accumulation method is based on Newton's third law and the principle of conservation of mechanics. When a vehicle is stationary or moving at a low constant speed, its total weight is equal to the sum of the reaction forces of all tires on the ground, which is also equal to the sum of the reaction forces of each axle. This method avoids the need for an extremely large testing area and ultra-high measuring range required for simultaneous weighing of the entire vehicle, and is suitable for the limited width of speed bumps.

[0159] During the over-limit determination and process completion phase, the total detected weight is compared with a preset over-limit threshold. When the total detected weight exceeds the threshold, the system triggers an audible and visual alarm and retains a complete detection record (including axle load, total weight, detection time, accuracy level, etc.) to provide evidence for road administration enforcement. When the total detected weight does not exceed the limit, the process directly proceeds to completion. After the detection process is completed, vehicles are allowed to pass normally, and the system returns to standby mode, waiting for the next vehicle to enter the monitoring area.

[0160] The following is an example of tilt error compensation calculation under a set of typical vehicle parameters:

[0161] I. Setting Typical Vehicle and Equipment Parameters (Commonly Used Engineering Values)

[0162] Speed ​​bump protrusion height: h = 0.05 m (5 cm), vehicle wheelbase: L = 3.0 m, vehicle center of gravity height: HG = 0.8 m, original weight of a single axle: G axle original = 6000 N, vehicle type: two-axle light truck.

[0163] II. Calculate step by step according to the 4 steps.

[0164] Step 1: Calculate the vehicle tilt angle θ

[0165] Small angle approximation: tanθ≈Lh Substituting: tanθ≈3.00.05≈0.0167 (for extremely small angles, the approximation is completely valid).

[0166] Step 2: Calculate the horizontal forward shift of the center of gravity Δx

[0167] Substitute: .

[0168] Step 3: Calculate the tilt error value ΔG

[0169] Patented optimization formula: Substitute the original value into: .

[0170] Step 4: Calculate the true weight of a single axis, G-axis true weight.

[0171] The front axle is raised and tilted forward, the measured value is too high, subtraction correction: axle true, axle original, axle true.

[0172] III. Comparison of axle load deviation before and after compensation

[0173] Before compensation (original measured value): 6000 N

[0174] Compensated (actual axle load): 5973.33 N

[0175] Absolute error: 26.67 N

[0176] Relative error: 600026.67 × 100% 0.44%.

[0177] Without tilt error compensation, the vehicle body tilts forward and the center of gravity shifts horizontally when the vehicle rolls over the speed bump due to its raised structure, altering the axle load distribution and resulting in a fixed system deviation in the measured original weight of each axle. The comparative values ​​are all based on the torque balance error formula ΔG=(G_axle_original × HG × h) / L² of this invention, calculated theoretically using the dimensions of common road speed bumps and typical highway vehicle parameters, thus possessing clear mechanical basis and engineering verifiability. The speed bump protrusion height h is taken as the standard road value of 50mm to 70mm, the vehicle wheelbase L is taken as the common range of 3.5m to 4.5m for two-axle and three-axle trucks, and the vehicle center of gravity height HG is taken as the typical range of 1.0m to 1.4m for cargo vehicles. Substituting the above parameters into the formula, it can be calculated that: under the condition of no compensation, the relative deviation of single-axle weighing is 0.25% to 1.20%, and the deviation of vehicle total weight detection can reach 0.3% to 1.6%. Moreover, the deviation increases significantly with the increase of speed bump height, wheelbase shortening, and center of gravity rising, which is prone to misjudgment at the critical value of over-limit judgment, and cannot meet the accuracy requirements of highway dynamic weighing. After adopting the tilt error compensation method of this invention, the original axle weight data is accurately corrected based on the same mechanical model, which eliminates the systematic error of center of gravity offset caused by the protruding structure in principle. Theoretically, it can completely offset the fixed deviation. In engineering applications, the single-axle detection deviation can be controlled within ±0.1%, and the total weight detection deviation is reduced to within ±0.3%, which greatly improves the detection accuracy and reliability of the speed bump dynamic weighing device.

[0178] The overall working principle of the detection method described in this embodiment is as follows: using the dual-row array pressure sensors built into the speed bump, multiple pressure signals are collected simultaneously during the process of the vehicle passing over the speed bump at low speed. The reliability of the data is ensured by sensor redundancy verification. The original weight of a single axle is calculated by summing the pressures from each row. The system deviation caused by the speed bump protrusion is corrected by a tilt error compensation model based on the torque balance principle. The total weight of the vehicle is obtained by accumulating the weights axle by axle. The entire process is automated and requires no manual intervention.

[0179] This method directly utilizes existing speed bumps on the road as weighing carriers, automatically completing the weighing detection as vehicles pass over them at low speeds. It eliminates the need for separate weighing equipment and large-scale road construction. The underlying mechanism is that the raised structure of the speed bumps naturally forces vehicles to pass at low speeds, which is the ideal testing condition for dynamic weighing. The forced deceleration function of the speed bumps and the low-speed requirement for weighing complement each other, and their integrated design possesses inherent mechanical rationality.

[0180] This method distributes localized concentrated loads evenly to the sensors via a pressure plate, and employs a dual-row, five-column (10-channel) sensor array for full-width coverage detection. Combined with triple fault verification and a hierarchical weighted completion strategy, it ensures effective and stable pressure detection data regardless of wheel bearing position offset or individual sensor malfunctions. The underlying mechanism lies in the fact that the rigid flat plate structure of the pressure plate transforms point loads into surface loads, eliminating the dimensional mismatch between the tire and the sensors. The spatial redundancy of the array layout and the structural redundancy of the dual rows provide ample reference information for fault data completion, enabling the system to possess self-healing capabilities.

[0181] This method eliminates the systemic deviation caused by the speed bump's protrusion structure at its root through a tilt error compensation model. The underlying mechanical mechanism is that the speed bump alters the vehicle's geometric posture, causing a change in the lever arm of the center of gravity relative to each axle support, thus disrupting the inter-axle load distribution on a level road surface. Based on the rigid body static moment balance equation, this method accurately establishes a quantitative mathematical relationship between the bump height, wheelbase, center of gravity height, and detection deviation. It compensates for the error through analytical calculations rather than empirical estimations. The compensation process is supported by rigorous mechanical theory, ensuring the accuracy of the correction in principle, so that the final output axle load and total weight data truly reflect the vehicle's actual load state on a level road surface.

[0182] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A vehicle dynamic weighing detection device with multi-point pressure sensing based on speed bumps, characterized in that, include: Speed ​​bump body (10); The pressure plate (20) is fixedly attached to the speed bump body (10) on its upper surface; The pressure sensor (30) is divided into a front row sensing group and a rear row sensing group along the vehicle driving direction. The upper bearing surface of the pressure sensor (30) is closely attached to the lower surface of the force-bearing plate (20). The mounting bracket (40) is fixed on the road foundation, and the pressure sensor (30) is mounted on the mounting bracket (40). The speed bump body (10), the pressure plate (20), the pressure sensor (30), and the mounting bracket (40) form a force transmission structure from top to bottom.

2. The vehicle dynamic weighing and detection device according to claim 1, characterized in that, The front row sensor group and the rear row sensor group are arranged in parallel with uniform spacing, and multiple pressure sensors (30) are evenly arranged in each row along the width direction of the speed bump.

3. The vehicle dynamic weighing and detection device according to claim 2, characterized in that, The front row sensor group and the rear row sensor group each have 5 pressure sensors (30) arranged in each row, totaling 10 pressure sensors (30) forming an array-type detection layout.

4. The vehicle dynamic weighing and detection device according to claim 1, characterized in that, The pressure plate (20) is an integral rigid flat plate structure, and its effective force-bearing width covers the full width of the speed bump body (10), which is used to evenly spread and transmit the local concentrated load when the vehicle tire rolls over it to the pressure sensor (30) below.

5. The vehicle dynamic weighing and detection device according to claim 1, characterized in that, The speed bump body (10) adopts a high-strength wear-resistant rubber or steel one-piece molded structure, with raised arc and compressive strength; It also includes a sealing device (50) and an elastic sealing device (60). The pressure sensor (30) and the mounting bracket (40) are sealed and protected by the sealing device (50) and the elastic sealing device (60) to form an independent sealed cavity. The cavity is filled with waterproof insulating sealant to block the intrusion path of rainwater and sand. Among them, the elastic sealing device (60) is made of weather-resistant flexible waterproof elastic material, and the whole is an elastic sealing ring structure, which is tightly bonded to the upper outer side of the sealing device (50).

6. A detection method for a vehicle dynamic weighing detection device based on a speed bump type multi-point pressure sensor according to any one of claims 1-5, characterized in that, It employs a dual-row array pressure sensor consisting of a front row of sensors and a rear row of sensors arranged along the vehicle's direction of travel inside the speed bump. Includes the following steps: S1: When the vehicle wheels run over the speed bump, the pressure sensors of the front and rear sensor groups synchronously collect pressure signals. S2: Sum the pressure values ​​of each pressure sensor in the front row sensor group to obtain the total front row pressure; sum the pressure values ​​of each pressure sensor in the rear row sensor group to obtain the total rear row pressure; add the total front row pressure to the total rear row pressure to obtain the original single-axis measured weight. The calculation formula is as follows: In the formula, This is the original weight measured on a single axis. This is the sum of the pressure values ​​from all the pressure sensors in the front row sensor group. This is the sum of the pressure values ​​of all pressure sensors in the rear row sensor group; S3: Based on the principle of torque balance, combined with parameters such as the height of the speed bump, the vehicle wheelbase, and the center of gravity, the vehicle body tilt error caused by the speed bump is compensated and corrected to obtain the true weight of a single axle. S4: Repeat steps S1 to S3 for each axle of the vehicle, and add up the actual weight of each axle one by one to obtain the total detected weight of the vehicle.

7. The detection method according to claim 6, characterized in that, The system wake-up and self-test phase also precedes step S1: Initialize and perform fault self-check on all pressure sensor channels of the front and rear sensor groups; When the detection channel is normal, the weighing and detection process begins; when the detection channel is abnormal, a fault alarm is triggered and the detection process is terminated.

8. The detection method according to claim 6, characterized in that, Between step S1 and step S2, there is also a sensor redundancy verification and fault self-correction stage: Perform three quantitative checks on each pressure sensor: signal validity, neighborhood correlation, and time consistency, and identify faulty sensors. The neighborhood correlation deviation rate is calculated using the following formula: ； In the formula, For the first Neighborhood correlation deviation rate of road sensors For the first Real-time pressure data collected by the road sensor. For the first The average pressure of adjacent effective sensors in the same row of the road sensor; when If the correlation is greater than 20%, the sensor's neighborhood correlation test is deemed to have failed. The time consistency deviation rate is calculated using the following formula: ； In the formula, For the first Time consistency deviation rate of road sensors For the first The trigger time of the road sensor For the first The dual rows of road sensors correspond to the sensor trigger times. The average standard trigger time difference between the front and rear sensors; when If the error rate is greater than 50%, the time consistency check of the sensor is deemed to have failed. Based on the number and location of faulty sensors, a hierarchical weighted completion strategy is used to complete the faulty sensor data to obtain the corrected effective pressure value. The effective accuracy deviation rate is calculated based on the number of faulty sensors, and the detection accuracy level is determined.

9. The detection method according to claim 6, characterized in that, The specific calculations for tilt error compensation correction in step S3 include: Based on the height of the speed bump With vehicle wheelbase Calculate the vehicle body tilt angle, using a small angle approximation: In the formula, The vehicle body tilt angle, The height of the speed bump. This refers to the vehicle's wheelbase. Calculate the forward shift of the vehicle's center of gravity in the horizontal direction: In the formula, This is the amount by which the center of gravity shifts forward horizontally. The height of the vehicle's center of gravity. The height of the speed bump. This refers to the vehicle's wheelbase. Based on the moment balance equation with the non-measured axis as the fulcrum, the tilt error value is calculated as follows: In the formula, This is the tilt error value. This is the original weight measured on a single axis. The height of the vehicle's center of gravity. The height of the speed bump. This refers to the vehicle's wheelbase. Calculate the actual weight of a single axis: In the formula, This is the actual weight of a single axis. This is the original weight measured on a single axis. This represents the tilt error value, and the error direction is determined and corrected based on the vehicle's tilt posture.

10. The detection method according to claim 6, characterized in that, The process after step S4 also includes: The total measured weight data was filtered for noise reduction and stability verification. The axle load, total weight, and inspection time information are stored locally and then uploaded to the management platform. The total detected weight is compared with the preset over-limit threshold. When the total detected weight exceeds the limit, an over-limit alarm is triggered and the detection record is saved; when the limit is not exceeded, the detection process is completed and the system returns to standby mode.

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