WO2023173744A1 - Procédé et système complets de pesage de véhicule en temps réel, intelligents et de haute précision - Google Patents

Procédé et système complets de pesage de véhicule en temps réel, intelligents et de haute précision Download PDF

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Publication number
WO2023173744A1
WO2023173744A1 PCT/CN2022/126960 CN2022126960W WO2023173744A1 WO 2023173744 A1 WO2023173744 A1 WO 2023173744A1 CN 2022126960 W CN2022126960 W CN 2022126960W WO 2023173744 A1 WO2023173744 A1 WO 2023173744A1
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Prior art keywords
weighing
resistance
chip
resistance strain
strain gauge
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PCT/CN2022/126960
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English (en)
Chinese (zh)
Inventor
孙科学
魏来
成谢锋
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南京邮电大学
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Publication of WO2023173744A1 publication Critical patent/WO2023173744A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
    • G01G19/03—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion
    • G01G19/035—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion using electrical weight-sensitive devices
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G3/00—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances
    • G01G3/12—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances wherein the weighing element is in the form of a solid body stressed by pressure or tension during weighing
    • G01G3/14—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances wherein the weighing element is in the form of a solid body stressed by pressure or tension during weighing measuring variations of electrical resistance

Definitions

  • the invention relates to a comprehensive high-precision intelligent vehicle real-time weighing system, belonging to the technical field of weighing systems.
  • the traditional strain gauge load cell solution for on-board real-time weighing mainly installs an ordinary weighing sensor between the carriage and the frame, and one end of the sensor is fixed on the newly added part of the frame. On the component, the other end is suspended in the air and is used to hold up the carriage, which is equivalent to transforming the carriage into a weighing pan.
  • the entire compartment needs to be raised during installation, which will damage the car structure and raise the center of gravity of the car body, posing safety risks.
  • the current vehicle-mounted weighing system is difficult to achieve a balance between accuracy, cost, and reliability.
  • there are also problems such as installation trouble and safety hazards.
  • the technical problem to be solved by the present invention is to overcome the defects of the existing technology and provide a comprehensive high-precision intelligent vehicle real-time weighing method and its system, which can display the vehicle cargo weight in real time and has the characteristics of safety, reliability, low cost and accuracy. High enough advantage.
  • a comprehensive high-precision intelligent vehicle real-time weighing method including the following steps:
  • strain resistance sensors set strain resistance sensors on several load-bearing axles on the vehicle.
  • the strain resistance sensors are Wheatstone full-bridge circuits composed of four resistance strain gauges. The input end of the Wheatstone full-bridge circuit is controlled by weighing. The device provides power;
  • the amplified and adjusted voltage signal undergoes analog-to-digital conversion through the AD chip of the weighing controller, and then is transmitted to the microcontroller MCU of the weighing controller for data processing;
  • the microcontroller MCU transmits the processed weight data to the digital tube display for display, and controls the microcontroller MCU through the control buttons.
  • the first resistance strain gauge and the third resistance strain gauge are located on one side of the left-right direction, and the second resistance strain gauge and the fourth resistance strain gauge are located on the other side of the left-right direction, satisfying the relationship
  • V s is the power supply provided by the weighing controller
  • V O1 is the voltage output by the full-bridge Wheatstone circuit composed of four resistance strain gauges
  • k is the coefficient of the strain gauge
  • ⁇ 1 , ⁇ 2 , ⁇ 3 , ⁇ 4 are respectively the strain amounts of the first resistance strain gauge, the second resistance strain gauge, the third resistance strain gauge and the fourth resistance strain gauge.
  • the signal collected at the input end of the AD chip is the voltage signal after differential amplification, which satisfies
  • V 1 and V 2 are the two output terminal voltages of the Wheatstone full-bridge circuit
  • R 1 and R 2 are the set proportional resistors, and their resistance values are the same.
  • R p is the matching resistor
  • R f is the proportional reference.
  • Resistor the size of the resistance is determined by the resistance of R 1 and R 2.
  • V O2 is the size of the voltage signal after differential amplification.
  • the weight value calculated by the microcontroller MCU is the average of the weights weighed on multiple axles.
  • the microcontroller MCU adopts multi-level calibration to establish a linear relationship between the strain resistance sensor signal and the weighing weight.
  • the single-chip MCU uses the Kalman filter algorithm to predict the signal, compares and calculates the covariance of the current signal and the predicted signal, and then obtains the next predicted signal.
  • Each predicted signal constitutes an output sequence, and this output sequence is obtained after filtering.
  • the Kalman filter formula is specifically:
  • this estimated value is EVN
  • the last estimated value is EVP
  • the current estimated covariance ECN the next estimated value is ECX
  • the measured value is MV
  • the current measured covariance is MCN
  • the next measured covariance is MCN.
  • the variance is MCX and the estimated change ratio is ECR.
  • a comprehensive high-precision intelligent vehicle real-time weighing system including several strain resistance sensors arranged on the axle.
  • the strain resistance sensors are composed of a Wheatstone full-bridge circuit and include four resistance strain gauges.
  • the resistance strain gauges are geometrically symmetrically distributed in the up and down and left and right directions of the axle.
  • the input end of the Wheatstone full bridge circuit is connected to the power supply provided by the weighing controller, and the output end of the Wheatstone full bridge circuit is connected in turn.
  • the attenuation circuit is connected to the input end of the weighing controller.
  • the weighing controller includes an AD chip and a single-chip microcomputer MCU.
  • the input end of the AD chip is connected to the input end of the weighing controller.
  • the attenuation circuit is connected, and the output end of the AD chip is connected to the input end of the single-chip computer MCU.
  • the single-chip computer MCU is connected to a digital tube display and control
  • the AD chip model is AD1256, and the microcontroller MCU model is STM32F103C8T6.
  • the resistance strain gauge includes a base, which is a PEEK film.
  • a cover sheet is provided on the base.
  • a sensitive grid is provided between the base and the cover sheet. The base, the sensitive grid and the The base and the cover are fixed by adhesive.
  • the present invention provides a comprehensive high-precision intelligent vehicle real-time weighing method and its system, which does not change the original structure of the vehicle and does not affect the safety of the vehicle. It uses a high-precision Wheatstone full-bridge circuit, and It is not a traditional Wheatstone quarter-bridge circuit for resistance strain gauge weighing measurement. It uses four resistance strain gauges, that is, variable resistance, instead of a single resistance strain gauge. Compared with the Wheatstone quarter-bridge circuit, it has more The variable items can effectively eliminate interferences such as compression or tension, as well as bending, shearing or torsional stress, and can achieve high-precision real-time vehicle weighing. The weighing equipment can be directly installed on the axle without any changes.
  • the body structure moves with the vehicle, ensuring safety and convenient installation; calibration is performed before weighing, and the single-chip MCU uses multi-level calibration, which can reduce system errors and further improve measurement accuracy; the single-chip MCU uses the Kalman filter algorithm, which has high accuracy. Features of strong stability.
  • Figure 1 is a system connection diagram of a comprehensive high-precision intelligent vehicle real-time weighing system according to the present invention
  • Figure 2 is a front view of an axle with a resistance strain gauge installed according to the present invention
  • Figure 3 is a Wheatstone full-bridge circuit diagram composed of four resistance strain gauges according to the present invention.
  • Figure 4 is a circuit structure diagram of the differential amplifier circuit of the present invention.
  • Figure 5 is the sampling part of the AD chip and the MCU control part of the microcontroller of the present invention.
  • Figure 6 is a comparison between multi-level calibration of the present invention, single-level calibration and actual values
  • Figure 7 is a diagram showing the effect of Kalman filtering adopted in the present invention.
  • the reference numbers in the figure are as follows: 1-the first patch resistance strain gauge; 2-the second patch resistance strain gauge; 3-the third patch resistance strain gauge; 4-the fourth patch resistance strain gauge; 5-axle ;6-Vehicle.
  • the present invention provides a comprehensive high-precision intelligent vehicle real-time weighing system.
  • the deformation of the axle can trigger changes in the output end of the full-bridge circuit of the strain resistance sensor.
  • the controller calculates the Kalman filter algorithm and displays the weight of the vehicle on the digital tube inside the vehicle cab.
  • the specific structure includes a strain resistance sensor composed of four resistance strain gauges arranged on multiple axles, a weighing controller, a protective shell of the weighing controller and an external power supply.
  • the external power supply is used to power the weighing controller.
  • the input end of the strain resistance sensor is powered by the weighing controller.
  • the strain resistance sensor is composed of a Wheatstone full bridge circuit.
  • the output end reflects the weight through a voltage signal, and then processes the voltage signal through a differential amplification circuit and a zero adjustment and attenuation circuit.
  • the processed voltage signal is sampled by the AD chip and then connected to the input end of the microcontroller MCU of the weighing controller.
  • the signal collected by the AD chip is the voltage signal after differential amplification.
  • the differential amplification circuit differentially amplifies the signal output by the strain resistance sensor, making the voltage signal easier to measure and process.
  • the weighing controller implements the Kalman filter algorithm and multi-level calibration; the weighing controller is connected to the digital tube display and control buttons installed inside the vehicle cab.
  • the strain resistance sensor is actually a full-bridge Wheatstone circuit composed of four resistance strain gauges that are geometrically symmetrical on the left and right sides of the axle.
  • the resistance strain gauge is composed of a sensitive grid, a substrate, a cover sheet and an adhesive.
  • the resistance strain gauge includes a base, a cover sheet is disposed on the base, and a sensitive grid is disposed between the base and the cover sheet.
  • the base and the sensitive grid, as well as the base and the cover sheet, are fixed by an adhesive.
  • the resistance strain gauge consists of a sensitive grid, leads, base, cover and adhesive.
  • the sensitive grid is an important part of the strain gauge; the lead is a thin metal wire drawn from the sensitive grid of the strain gauge; the base is used to maintain the sensitive grid. , the geometric shape and relative position of the leads; the cover sheet not only maintains the geometric shape and relative position of the sensitive grid and leads, but also protects the sensitive grid; the adhesive is used to fix the sensitive grid on the base and stick the cover sheet to the base together.
  • the first resistance strain gauge 1 and the third resistance strain gauge 3 are located on the left, and the second resistance strain gauge 2 and the fourth resistance strain gauge 4 are located on the right.
  • the vehicle 6 has at least two axles 5 for load-bearing, and the weight value calculated by the weighing controller is the average of the weights weighed on the multiple axles 5 .
  • Each axle 5 forms an individual measuring channel. When the vehicle 6 is placed on multiple axles, each axle forms a separate measurement channel and will have actual data.
  • the final weight value obtained is the average weight of multiple measurement channels, which reduces the system error and effectively improves accuracy.
  • V s is the power supply provided by the weighing controller
  • V O1 is the voltage output by the full-bridge Wheatstone circuit composed of four resistance strain gauges
  • k is the coefficient of the strain gauge
  • ⁇ 1 , ⁇ 2 , ⁇ 3 , ⁇ 4 respectively. is the strain amount of the four resistance strain gauges, and their relationship satisfies
  • the measurement circuit uses a Wheatstone full-bridge circuit that can eliminate interference such as compression or tension, as well as bending, shearing or torsional stress.
  • the output voltage changes are collected and amplified by a differential amplifier circuit, and zeroing and attenuation are added.
  • the circuit adjusts the voltage changes to improve the range and accuracy of the entire weighing device.
  • the circuit structure of the differential amplifier circuit is shown in Figure 4, in which the values of V1-V2 are equal to the voltage V O1 output by the full-bridge Wheatstone circuit composed of four resistance strain gauges.
  • the voltage V O1 output by the full-bridge Wheatstone circuit composed of four resistance strain gauges, and the voltage signal V O2 after amplification, zero adjustment and attenuation by the differential circuit, are collected by the AD circuit and transmitted to the microcontroller MCU of the weighing controller. , after calculation by the microcontroller MCU, the digital tube display installed inside the vehicle cab is finally controlled to display the weight, and various weighing functions can be realized through the control buttons.
  • the signal collected at the input end of the AD chip is the voltage signal after differential amplification, which satisfies
  • V 1 and V 2 are the two output terminal voltages of the Wheatstone full-bridge circuit
  • R 1 and R 2 are the set proportional resistors, and their resistance values are the same.
  • R p is the matching resistor
  • R f is the proportional reference.
  • Resistor the size of the resistance is determined by the resistance of R 1 and R 2.
  • V O2 is the size of the voltage signal after differential amplification.
  • the weighing controller is composed of AD chip and microcontroller MCU.
  • the AD chip sampling part and the microcontroller MCU control part are shown in Figure 5. It has the functions of sampling voltage values, calculating weight values and filtering to display weight stably.
  • the AD chip model is AD1256, and the microcontroller MCU model is STM32F103C8T6.
  • calibration must be carried out before weighing, so that the weighing device has a definition of the weight, that is, a linear relationship is established between the sensor and the weight, and then the vehicle is weighed based on this linear relationship.
  • General weighing devices use single-level calibration, but this device uses multi-level calibration to make the data more accurate.
  • the calibration process and the comparison between single-stage calibration and multi-stage calibration and actual values are shown in Figure 6.
  • the calibrated weight can be chosen arbitrarily, but it must be on the same order of magnitude as the weight of the weighing object, generally between one-tenth and one-fifth of the weight of the weighing object.
  • the microcontroller MCU uses the Kalman filter algorithm and multi-level calibration methods to process the voltage sampled by the AD chip to achieve the high-precision characteristics of this system.
  • the sensor is under pressure.
  • the microcontroller MCU uses the Kalman filter algorithm to predict the signal. It compares and calculates the covariance of the current signal and the predicted signal, and then obtains the next predicted signal. From this, each prediction is The signals form the output sequence. This output sequence is the stable signal obtained after filtering. Then based on the linear relationship established by multi-level calibration. The weight of the required weighing frame is obtained through the linear relationship established during calibration.
  • the single-chip MCU controls the digital tube display installed inside the vehicle cab to display the weight, and realizes various weighing functions through buttons. .
  • the Kalman filter adopted in the present invention is an algorithm that utilizes linear system state equations to optimally estimate the system state through system input and output observation data. Since the observation data includes the influence of noise and interference in the system, the optimal estimation can also be regarded as a filtering process.
  • Kalman filter is a data processing technology that removes noise and restores real data. Kalman filter can estimate the state of a dynamic system from a series of data with measurement noise when the measurement variance is known. It facilitates computer programming and can update and process the data collected on site in real time to keep the collected data stable. In the present invention, through Kalman filtering, we can obtain stable and high-precision weight values.
  • the Kalman gain is KG
  • this estimated value is EVN
  • the last estimated value is EVP
  • the current estimated covariance ECN the next estimated value is ECX
  • the measured value is MV
  • the current measured covariance is MCN
  • the next measured covariance is MCN.
  • the variance is MCX and the estimated change ratio is ECR.
  • the comprehensive high-precision intelligent vehicle real-time weighing system of the present invention adopts multi-level calibration.
  • the multi-level calibration result of line 1 is closer to the actual measured value of line 3, which reduces the system error and further improves the accuracy.
  • the comprehensive high-precision intelligent vehicle real-time weighing system uses the Kalman filter algorithm, uses the linear system state equation, and uses the system input and output observation data to optimally estimate the system state.
  • the messy scattered points are actual measured values, and stable values are output after Kalman filtering.
  • Kalman filter is a data processing technology that removes noise and restores real data. Kalman filter can estimate the state of a dynamic system from a series of data with measurement noise when the measurement variance is known. It facilitates computer programming and can update and process the data collected on site in real time to keep the collected data stable. In this device, through Kalman filtering, we can obtain stable and high-precision weight values.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Vehicle Body Suspensions (AREA)
  • Measurement Of Length, Angles, Or The Like Using Electric Or Magnetic Means (AREA)

Abstract

L'invention concerne un procédé complet de pesage de véhicule en temps réel, intelligent et de haute précision, comprenant les étapes suivantes : disposer respectivement des capteurs de résistance à la déformation sur plusieurs essieux (5) porteurs de charge sur un véhicule (6), chacun des capteurs de résistance à la déformation étant un circuit en pont complet de Wheatstone composé de quatre jauges de déformation de résistance ; S02, les circuits en pont complet de Wheatstone délivrent en sortie des variations de signal de tension, et un circuit d'amplification différentielle collecte et amplifie celles-ci, et ajuste les variations de signal de tension au moyen d'un circuit de mise à zéro et d'atténuation ; S03, réaliser une conversion analogique-numérique sur les signaux de tension amplifiés et ajustés au moyen d'une puce AD d'un dispositif de commande de pesage, et transmettre ensuite les signaux de tension à une MCU de micro-ordinateur monopuce du dispositif de commande de pesage pour un traitement de données ; et S04, la MCU de micro-ordinateur monopuce transmet, à un écran d'affichage à tube numérique pour un affichage, des données de poids qui sont obtenues après traitement. L'invention concerne également un système complet de pesage de véhicule en temps réel, intelligent et de haute précision. Un poids de cargaison de véhicule peut être affiché en temps réel, et les avantages de sécurité, de fiabilité, de coûts relativement bas et de précision suffisamment élevée sont obtenus.
PCT/CN2022/126960 2022-03-15 2022-10-24 Procédé et système complets de pesage de véhicule en temps réel, intelligents et de haute précision WO2023173744A1 (fr)

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CN117633984A (zh) * 2023-12-01 2024-03-01 四川农业大学 基于弯曲应变和剪切应变的车辆时空分布信息识别方法

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