Method for measuring cargo load based on tire pressure index

Abstract

The invention discloses a method for measuring cargo load based on a tire pressure index, relates to the technical field of vehicle control, and solves the problems of inaccurate measurement result and overlarge error caused by interference of external variables when the load is calculated only through tire pressure in the existing method. The method comprises the steps that no-load calibration is conducted on the industrial vehicle, and the no-load tire pressure and the reference temperature of each tire are obtained; a plurality of cargo weights with known weights are added to the industrial vehicle until the industrial vehicle is overloaded; analyzing the relationship between the tire pressure data of each tire and the tire temperature to obtain a tire pressure-temperature fitting formula; performing temperature compensation on the tire pressure data to obtain temperature repair tire pressure; performing data fitting on the temperature repair tire pressure and the total weight of the goods; finely adjusting the total weight of the cargo, and correcting the cargo-tire pressure fitting formula; carrying out no-load self-calibration on the temperature repair tire pressure according to the tire aging process; and the central processing unit calculates the actual cargo capacity of the industrial vehicle according to the temperature repair tire pressure in the tire aging process.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle monitoring intelligent transportation, and particularly to a method for measuring the load of goods based on tire pressure indicators. Background Art

[0002] In the modern transportation industry, especially in the freight and logistics industries, the precise management of vehicle load is of great significance for ensuring transportation safety, improving transportation efficiency, and extending the service life of vehicles. With the development of intelligent transportation systems (ITS), the popularization of vehicle intelligence and Internet of Things technology, and the application of in-vehicle sensors has gradually become a trend. As a mature vehicle monitoring technology, the Tire Pressure Monitoring System (TPMS) has been widely used in the automotive industry. The TPMS was originally used to monitor the pressure status of tires and warn of tire failures. However, in recent years, researchers have found that there is a certain correlation between tire pressure changes and vehicle load. By analyzing the relationship between tire pressure and load, the load of the vehicle can be indirectly estimated, providing auxiliary information for transportation management.

[0003] Patent No. CN2024112424751 discloses a load estimation method, device, and equipment. The method includes: obtaining the initial tire pressure when the vehicle is unloaded and the first loaded tire pressure after loading goods, and determining the first pressure change amount between the initial tire pressure and the first loaded tire pressure; determining the mass estimation curve corresponding to the initial tire pressure from multiple mass estimation curves, where the mass estimation curve is used to characterize the relationship between the first pressure change amount corresponding to the initial tire pressure and the estimated load, and different mass estimation curves correspond to different initial tire pressures; determining the estimated weight according to the first pressure change amount and the corresponding mass estimation curve; it can be unrestricted by scenarios, avoid the limitations of fixed weighing, have universality, and be unaffected by external factors such as road surface, wind resistance, and tire wear, and the prediction result is more stable.

[0004] Patent No. CN2018100357731 discloses a management system for independent trailers, including a cloud platform and intelligent trailer hardware installed on the trailer. The intelligent trailer hardware includes a TPMS sensor for real-time monitoring of the tire temperature, tire pressure and status of the trailer, an axle temperature sensor for real-time monitoring of the axle temperature of the trailer, a load sensor for real-time monitoring of the load mass of the trailer and sending it to the intelligent terminal, a condenser for cooling the axle, a two-dimensional code and an intelligent terminal. The intelligent terminal is used to receive the data sent by the TPMS sensor, the axle temperature sensor and the load sensor and upload it to the cloud platform, and the cloud platform processes the data. The above invention also discloses a management method for independent trailers. The advantages of the above invention are: providing real-time information of the trailer for the vehicle owner, notifying the vehicle owner of abnormal situations in real time, and at the same time, through big data statistics of the loading times, cargo turnover and utilization rate of the trailer, etc., providing detailed trailer management functions for the vehicle owner.

[0005] Although the above patent can obtain the cargo load after detecting the tire pressure, there are differences in the structure, material and load-bearing capacity of different vehicle models and tires. Simply calculating the load by tire pressure may be interfered by external variables, resulting in inaccurate measurement results and errors. Summary of the Invention

[0006] The object of the present invention is to provide a method for measuring the cargo load based on tire pressure indicators, which can calculate the load capacity of industrial vehicles by combining tire pressure data with external variables; calibrate the no-load tire pressure according to the tire aging process through the no-load self-calibration of industrial vehicles; and then improve the measurement accuracy of the cargo load and reduce the load estimation error.

[0007] The present invention uses the following technical solutions:

[0008] A method for measuring the cargo load based on tire pressure indicators includes the following steps;

[0009] S1: When the industrial vehicle leaves the factory, perform no-load calibration on the industrial vehicle to obtain the no-load tire pressure and reference temperature of each tire;

[0010] S2: Gradually add several known-weight cargo weights to the industrial vehicle until it is overloaded, measure and record the overloaded tire pressure and several increased-load tire pressures of each tire, and record the tire temperature and the total weight of the cargo weights at the same time;

[0011] S3: Analyze the relationship between the tire pressure data and the tire temperature of each tire to obtain a tire pressure-temperature fitting formula; and perform temperature compensation on the tire pressure data according to the reference temperature to obtain the temperature-compensated tire pressure;

[0012] S4: Perform data fitting on the temperature-compensated tire pressure and the total weight of the cargo weights to obtain a cargo load-tire pressure fitting formula, and then draw a cargo load-tire pressure curve graph;

[0013] S5: Fine-tune according to the continuous change of the total weight of the cargo weights, correct the load-tire pressure fitting formula, and at the same time form a load data table and store it in the central processing unit of the industrial vehicle;

[0014] S6: When the industrial vehicle is stationary and unloaded, the central processing unit of the industrial vehicle performs no-load self-calibration on the temperature-compensated tire pressure according to the tire aging process until the tire is overloaded or bursts;

[0015] S7: During the tire aging process, the central processing unit calculates the actual load of the industrial vehicle based on the real-time temperature-compensated tire pressure and the load data table, and displays it on the display screen of the industrial vehicle.

[0016] Preferably, step S1 includes the following steps:

[0017] S11: Check the parking environment of the industrial vehicle to ensure that the ground is flat and not inclined, and remove all removable counterweight devices to confirm that the industrial vehicle is in a completely unloaded state;

[0018] S12: Deploy tire pressure sensors and temperature sensors on each tire of the industrial vehicle, and both are wirelessly and / or wiredly communicatively connected to the central processing unit;

[0019] S13: Let the industrial vehicle stand still for X hours or more to ensure that the temperature difference between the tire temperature and the ambient temperature ≤ Y °C, and at the same time check that the tire has no abnormal deformation or mechanical damage;

[0020] S14: Start the measurement, and regularly collect N times of real-time tire pressure and tire temperature from the central processing unit at preset intervals;

[0021] S15: After the measurement is completed, calculate the average value of the collected real-time tire pressures and tire temperatures, and then obtain the no-load tire pressure and reference temperature of each tire.

[0022] Preferably, step S2 includes the following steps:

[0023] S21: After the no-load measurement is completed, configure a deformation detection device in the parking environment of the industrial vehicle to measure the sidewall deformation of each tire in real time, and calculate the radial compression ratio of each tire;

[0024] S22: Initially place cargo weights of Z% of the rated load on the industrial vehicle, and after standing still for M minutes, the central processing unit collects the increased load tire pressure and tire temperature of each tire in real time;

[0025] S23: After the central processing unit initially completes the collection, each time increase the cargo weights of W% of the rated load on the industrial vehicle, and after standing still for M minutes, the central processing unit collects the increased load tire pressure and tire temperature again in real time;

[0026] S24: When the total weight of the cargo weights placed on the industrial vehicle reaches the theoretical overload value, the central processing unit calculates the tire pressure mutation rate and temperature gradient of each tire. Meanwhile, the deformation detection device measures the change rate of the grounding area according to the radial compression rate;

[0027] S25: If there is no situation where the tire pressure mutation rate ≥ a% / second, the temperature gradient > b °C / min, or the change rate of the grounding area > c%, then cargo weights with a rated load of U% are successively added to the industrial vehicle until any of the above situations occurs. At this time, the total weight of the cargo weights is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure;

[0028] If there is a situation where the tire pressure mutation rate ≥ a% / second, the temperature gradient > b °C / min, or the change rate of the grounding area > c%, then the theoretical overload value is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure.

[0029] Preferably, the tire pressure data includes the no-load tire pressure, the overload tire pressure, and several increased-load tire pressures; Step S3 includes the following steps:

[0030] S31: Using the improved polynomial regression algorithm, a tire pressure-temperature fitting formula is constructed based on the tire pressure data and the tire temperature:

[0031] P(T) = P0·[1 + α(T - T0) + β(T - T0) 2 (1)

[0032] where P(T) represents the tire pressure-temperature fitting formula, T represents the tire temperature, P0 represents the no-load tire pressure, α represents the first-order temperature coefficient, T0 represents the reference temperature, and β represents the second-order non-linear correction term;

[0033] S32: Using the tire pressure-temperature fitting formula according to the reference temperature, the tire pressure data is temperature-compensated to obtain the temperature-compensated tire pressure:

[0034]

[0035] where P comp represents the temperature-compensated tire pressure, P meas represents the tire pressure data, T ref represents the standard working condition, and T meas represents the actual working condition.

[0036] Preferably, Step S4 includes the following steps:

[0037] S41: The temperature-compensated tire pressure is divided into a set of forward tire pressures and a set of backward tire pressures according to the tire position. Each set of forward tire pressures and backward tire pressures includes the left tire pressure and the right tire pressure, and the left tire pressure and the right tire pressure are compared;

[0038] S42: If the data difference between the left tire pressure and the right tire pressure is large, the debugger is reminded that there is a problem with the tires of the current industrial vehicle; if the data difference between the left tire pressure and the right tire pressure is small, the average value of the left tire pressure and the right tire pressure is used as the forward tire pressure F2 or the backward tire pressure F3.

[0039] S43: Perform several data fittings on the total weight of the cargo weights F1, the forward tire pressure F2, and the backward tire pressure F3 to obtain a load-tire pressure fitting formula:

[0040] F1 = γ * F2 + δ * F3 (3)

[0041] where γ represents the forward deviation coefficient and δ represents the backward deviation coefficient;

[0042] S44: Draw a corresponding load-tire pressure curve according to the characteristics of the load-tire pressure fitting formula.

[0043] Preferably, the process of no-load self-calibration is as follows: when the no-load tire pressure collected by the central processing unit shows abnormal data: if the abnormal data persistence period is short, it is determined that the tire is in the initial aging stage, and the first calibration value Fa is still used as the no-load tire pressure; if the abnormal data persistence period is long, it is determined that the tire has entered the middle aging stage, and at the same time, the no-load tire pressure is replaced from the first calibration value Fa to the secondary standard value Fb; and so on, as time goes by, the no-load tire pressure is successively replaced by the tertiary standard value Fc or the quaternary standard value Fd.

[0044] Preferably, the standard value is the average value of all tire pressure data collected by the central processing unit within D minutes.

[0045] The present invention calculates the load of an industrial vehicle by combining tire pressure data with external variables; performs calibration on the no-load tire pressure according to the tire aging process through the no-load self-calibration of the industrial vehicle; thereby improving the measurement accuracy of the cargo load and reducing the load estimation error. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0047] Figure 1 is a principle block diagram of a method for measuring the cargo load based on tire pressure indicators;

[0048] Figure 2 is a mounting position diagram of the sensor;

[0049] Figure 3It is a load - tire pressure curve graph;

[0050] Figure 4 It is a force schematic diagram of an industrial vehicle;

[0051] Figure 5 It is a load condition curve graph;

[0052] Figure 6 It is a tire aging process graph. Detailed implementation mode

[0053] The present invention will be described in detail below in conjunction with the attached drawings and embodiments:

[0054] As Figures 1-6 shown, the method for measuring the load of goods based on tire pressure indicators described in the present invention includes the following steps:

[0055] S1: When the industrial vehicle leaves the factory, calibrate the industrial vehicle when it is unloaded to obtain the unloaded tire pressure and reference temperature of each tire;

[0056] S2: Gradually add several known - weight cargo weights to the industrial vehicle until it is overloaded. Measure and record the overloaded tire pressure and several increased - load tire pressures of each tire, and at the same time record the tire temperature and the total amount of cargo weights;

[0057] S3: Analyze the relationship between the tire pressure data and the tire temperature of each tire to obtain a tire - pressure - temperature fitting formula; and perform temperature compensation on the tire pressure data according to the reference temperature to obtain the temperature - compensated tire pressure;

[0058] S4: Fit the temperature - compensated tire pressure with the total amount of cargo weights to obtain a load - tire - pressure fitting formula, and then draw a load - tire - pressure curve graph;

[0059] S5: According to the continuous fine - tuning of the total amount of cargo weights, correct the load - tire - pressure fitting formula, and at the same time form a load data table and store it in the central processing unit of the industrial vehicle;

[0060] S6: When the industrial vehicle is stationary and unloaded, the central processing unit of the industrial vehicle performs unloaded self - calibration on the temperature - compensated tire pressure according to the tire aging process until the tire is overloaded or bursts;

[0061] S7: The central processing unit calculates the actual load of the industrial vehicle according to the real - time temperature - compensated tire pressure in the tire aging process, in combination with the load data table, and displays it on the display screen of the industrial vehicle.

[0062] In the present invention, step S1 includes the following steps:

[0063] S11: Check the parking environment of the industrial vehicle to ensure that the ground is flat and without inclination, and remove all removable counterweight devices to confirm that the industrial vehicle is in a completely unloaded state;

[0064] S12: Deploy a tire pressure sensor and a temperature sensor on each tire of the industrial vehicle, and both are wirelessly and / or wiredly communicatively connected to the central processor;

[0065] S13: Let the industrial vehicle stand still for X hours or more to ensure that the temperature difference between the tire temperature and the ambient temperature ≤ Y °C, and at the same time check that the tire has no abnormal deformation or mechanical damage;

[0066] S14: Start the measurement, and collect the real-time tire pressure and tire temperature N times at preset intervals from the central processor;

[0067] S15: After the measurement is completed, calculate the average value of the collected real-time tire pressures and real-time tire temperatures, and then obtain the no-load tire pressure and reference temperature of each tire.

[0068] In the present invention, step S2 includes the following steps:

[0069] S21: After the no-load measurement is completed, configure a deformation detection device in the parking environment of the industrial vehicle to measure the lateral deformation amount of each tire in real time, and calculate the radial compression rate of each tire;

[0070] S22: Initially place goods weights of Z% of the rated load on the industrial vehicle. After standing still for M minutes, the central processor collects the increased load tire pressure and tire temperature of each tire in real time;

[0071] S23: After the central processor initially completes the collection, each time increase the goods weights of W% of the rated load on the industrial vehicle. After standing still for M minutes, the central processor collects the increased load tire pressure and tire temperature again in real time;

[0072] S24: When the total amount of goods weights placed on the industrial vehicle is the theoretical overload value, the central processor calculates the tire pressure mutation rate and temperature gradient of each tire, and at the same time the deformation detection device calculates the change rate of the grounding area according to the radial compression rate;

[0073] S25: If there is no tire pressure mutation rate ≥ a% / second, temperature gradient > b °C / minute or grounding area change rate > c%, then successively increase the goods weights of U% of the rated load on the industrial vehicle until any of the above situations occurs. At this time, the total amount of goods weights is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure;

[0074] If there is a tire pressure mutation rate ≥ a% / second, temperature gradient > b °C / minute or grounding area change rate > c%, then the theoretical overload value is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure.

[0075] In the present invention, the tire pressure data includes no-load tire pressure, overload tire pressure and several increased load tire pressures; step S3 includes the following steps:

[0076] S31: Use the improved polynomial regression algorithm to construct a tire pressure-temperature fitting formula based on the tire pressure data and the tire temperature:

[0077] P(T)=P0·[1 + α(T - T0)+β(T - T0) 2 (1)

[0078] where P(T) represents the tire pressure-temperature fitting formula, T represents the tire temperature, P0 represents the no-load tire pressure, α represents the first-order temperature coefficient, T0 represents the reference temperature, and β represents the second-order nonlinear correction term;

[0079] S32: Use the tire pressure-temperature fitting formula according to the reference temperature to perform temperature compensation on the tire pressure data to obtain the temperature-compensated tire pressure:

[0080]

[0081] where P comp represents the temperature-compensated tire pressure, P meas represents the tire pressure data, T ref represents the standard working condition, and T meas represents the actual working condition.

[0082] In the present invention, step S4 includes the following steps:

[0083] S41: Divide the temperature-compensated tire pressure into a set of forward tire pressures and a set of backward tire pressures according to the tire positions. Each set of forward and backward tire pressures includes a left tire pressure and a right tire pressure, and compare the left tire pressure and the right tire pressure;

[0084] S42: If the data difference between the left tire pressure and the right tire pressure is large, remind the debugger that there is a problem with the tire of the current industrial vehicle; if the data difference between the left tire pressure and the right tire pressure is small, take the average value of the left tire pressure and the right tire pressure as the forward tire pressure F2 or the backward tire pressure F3;

[0085] S43: Perform several data fittings on the total weight of the cargo weights F1, the forward tire pressure F2, and the backward tire pressure F3 to obtain a load-tire pressure fitting formula:

[0086] F1 = γ*F2+δ*F3 (3)

[0087] where γ represents the forward deviation coefficient and δ represents the backward deviation coefficient;

[0088] S44: Draw a corresponding load-tire pressure curve according to the characteristics of the load-tire pressure fitting formula.

[0089] In the present invention, the tire aging process includes four stages: initial aging, intermediate aging, deep aging, and functional failure. The central processor of the industrial vehicle performs no-load self-calibration according to the calibration values of each stage. The calibration values include the first calibration value Fa for initial aging, the second standard value Fb for intermediate aging, the third standard value Fc for deep aging, and the fourth standard value Fd for functional failure.

[0090] In the present invention, the process of no-load self-calibration is as follows: When the no-load tire pressure collected by the central processor shows abnormal data: If the duration of the abnormal data is short, it is determined that the tire is in the initial aging stage, and the first calibration value Fa is still used as the no-load tire pressure; If the duration of the abnormal data is long, it is determined that the tire enters the intermediate aging stage, and at the same time, the no-load tire pressure is replaced from the first calibration value Fa to the second standard value Fb; And so on, as time goes by, the no-load tire pressure is successively replaced by the third standard value Fc or the fourth standard value Fd.

[0091] In this embodiment, a short cycle means that the occurrence frequency of abnormal data is low and the duration does not exceed 5 minutes; A long cycle means that the occurrence frequency of abnormal data is high and the duration is at least 5 minutes.

[0092] In the present invention, the standard value is the average value of all tire pressure data collected by the central processor within D minutes.

[0093] Embodiment:

[0094] Check the parking environment of the industrial vehicle to ensure that the ground is flat and there is no inclination, and remove all removable counterweight devices to confirm that the industrial vehicle is in a completely no-load state; Deploy the tire pressure sensor and temperature sensor on each tire of the industrial vehicle, and both are wirelessly and / or wiredly connected to the central processor; Let the industrial vehicle stand still for 4 hours or more to ensure that the temperature difference between the tire and the ambient temperature is ≤3°C, and at the same time check that the tire has no abnormal deformation or mechanical damage; Start the measurement, and collect 30 times of real-time tire pressure and tire temperature from the central processor at preset intervals; After the measurement is completed, calculate the average value of the collected real-time tire pressures and real-time tire temperatures to obtain the no-load tire pressure and reference temperature of each tire.

[0095] After the no-load measurement is completed, a deformation detection device is configured in the parking environment of the industrial vehicle to measure the sidewall deformation of each tire in real time and calculate the radial compression rate of each tire. The industrial vehicle is initially loaded with a cargo weight of 25% of the rated load. After standing for 20 minutes, the central processor collects the increased load tire pressure and tire temperature of each tire in real time. After the central processor completes the initial collection, each time a cargo weight of 15% of the rated load is added to the industrial vehicle. After standing for 20 minutes, the central processor collects the increased load tire pressure and tire temperature again in real time. When the total cargo weight placed on the industrial vehicle reaches the theoretical overload value, the central processor calculates the tire pressure mutation rate and temperature gradient of each tire. At the same time, the deformation detection device calculates the change rate of the grounding area according to the radial compression rate:

[0096] If the tire pressure mutation rate ≥ 3% / s, temperature gradient > 2°C / min, or grounding area change rate > 15% does not occur, then the cargo weight of U% of the rated load is successively added to the industrial vehicle until any of the above situations occurs. At this time, the total cargo weight is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure;

[0097] If the tire pressure mutation rate ≥ 3% / s, temperature gradient > 2°C / min, or grounding area change rate > 15% occurs, then the theoretical overload value is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure;

[0098] An improved polynomial regression algorithm is used to construct a tire pressure-temperature fitting formula based on the tire pressure data and tire temperature. According to the reference temperature, the tire pressure data is temperature-compensated using the tire pressure-temperature fitting formula to obtain the temperature-compensated tire pressure;

[0099] The temperature-compensated tire pressure is divided into a set of forward tire pressures and a set of backward tire pressures according to the tire position. Each set of forward tire pressures and backward tire pressures includes the left tire pressure and the right tire pressure, and the left tire pressure and the right tire pressure are compared: If the data difference between the left tire pressure and the right tire pressure is large, the debugger is reminded that there is a problem with the tires of the current industrial vehicle; If the data difference between the left tire pressure and the right tire pressure is small, the average value of the left tire pressure and the right tire pressure is used as the forward tire pressure F2 or the backward tire pressure F3; The total cargo weight F1, forward tire pressure F2, and backward tire pressure F3 are subjected to several data fittings to obtain a cargo-tire pressure fitting formula; According to the characteristics of the cargo-tire pressure fitting formula, the corresponding cargo-tire pressure curve graph is drawn.

[0100] When the industrial vehicle is stationary and unloaded, the central processor of the industrial vehicle performs no-load self-calibration of the temperature-compensated tire pressure according to the tire aging process until the tire is overloaded or bursts; the tire aging process includes four stages: initial aging, intermediate aging, deep aging, and functional failure; the central processor of the industrial vehicle performs no-load self-calibration according to the calibration values of each stage; the calibration values include the first calibration value Fa for initial aging, the second standard value Fb for intermediate aging, the third standard value Fc for deep aging, and the fourth standard value Fd for functional failure.

[0101] When the no-load tire pressure collected by the central processor shows abnormal data: if the abnormal data persistence period is short, it is determined that the tire is in the initial aging stage, and the first calibration value Fa is still used as the no-load tire pressure; if the abnormal data persistence period is long, it is determined that the tire enters the intermediate aging stage, and at the same time, the no-load tire pressure is replaced from the first calibration value Fa to the second standard value Fb; and so on, as time goes by, the no-load tire pressure is successively replaced with the third standard value Fc or the fourth standard value Fd.

[0102] The central processor calculates the actual load of the industrial vehicle according to the real-time temperature-compensated tire pressure in the tire aging process, combined with the load data table, and displays it on the display screen of the industrial vehicle.

Claims

1. A method for measuring the load of goods based on tire pressure indicators, characterized in that: Including the following steps: S1: When the industrial vehicle leaves the factory, perform no-load calibration on the industrial vehicle to obtain the no-load tire pressure and reference temperature of each tire; S2: Gradually add a number of known-weight cargo weights to the industrial vehicle until it is overloaded. Measure and record the overloaded tire pressure and several increased-load tire pressures of each tire, and record the tire temperature and the total weight of the cargo weights at the same time; S3: Analyze the relationship between the tire pressure data and the tire temperature of each tire to obtain a tire pressure-temperature fitting formula; and perform temperature compensation on the tire pressure data according to the reference temperature to obtain the temperature-compensated tire pressure; S4: Perform data fitting on the temperature-compensated tire pressure and the total weight of the cargo weights to obtain a load-carrying tire pressure fitting formula, and then draw a load-carrying tire pressure curve graph; S5: According to the continuous fine-tuning of the total weight of the cargo weights, correct the load-carrying tire pressure fitting formula, and at the same time form a load-carrying data table and store it in the central processor of the industrial vehicle; S6: When the industrial vehicle is stationary and unloaded, the central processor of the industrial vehicle performs no-load self-calibration on the temperature-compensated tire pressure according to the tire aging process until the tire is overloaded or bursts; S7: During the tire aging process, the central processor calculates the actual load of the industrial vehicle based on the real-time temperature-compensated tire pressure in combination with the load-carrying data table and displays it on the display screen of the industrial vehicle.

2. The method for measuring the load of goods based on tire pressure indicators according to claim 1, wherein: The steps in step S1 include the following steps: S11: Check the parking environment of the industrial vehicle to ensure that the ground is flat and there is no inclination, and remove all removable counterweight devices to confirm that the industrial vehicle is in a completely no-load state; S12: Deploy tire pressure sensors and temperature sensors on each tire of the industrial vehicle, and both are wirelessly and / or wiredly communicatively connected to the central processor; S13: Let the industrial vehicle stand still for X hours or more to ensure that the temperature difference between the tire temperature and the ambient temperature ≤ Y °C, and at the same time check that the tire has no abnormal deformation or mechanical damage; S14: Start measurement, and collect N times of real-time tire pressure and tire temperature from the central processor at preset intervals; S15: After the measurement is completed, calculate the average value of the collected several real-time tire pressures and several tire temperatures, and then obtain the no-load tire pressure and reference temperature of each tire.

3. The method for measuring the load of goods based on tire pressure indicators according to claim 1, wherein: The steps in step S2 include the following steps: S21: After the no-load measurement is completed, configure a deformation detection device in the parking environment of the industrial vehicle to measure the sidewall deformation of each tire in real time and calculate the radial compression rate of each tire; S22: Place cargo weights of Z% of the rated load on the industrial vehicle for the first time. After standing still for M minutes, the central processor collects the increased-load tire pressure and tire temperature of each tire in real time; S23: After the central processor completes the first collection, each time add cargo weights of W% of the rated load to the industrial vehicle. After standing still for M minutes, the central processor collects the increased-load tire pressure and tire temperature again in real time; S24: When the total weight of the cargo weights placed on the industrial vehicle reaches the theoretical overload value, the central processor calculates the tire pressure mutation rate and temperature gradient of each tire, and the deformation detection device calculates the change rate of the grounding area according to the radial compression rate; S25: If there is no occurrence of a tire pressure mutation rate ≥ a% / second, a temperature gradient > b °C / min, or a contact area change rate > c%, then cargo weights equivalent to U% of the rated load are successively added to the industrial vehicle until any of the above conditions occurs. At this time, the total cargo weight is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure; If there is an occurrence of a tire pressure mutation rate ≥ a% / second, a temperature gradient > b °C / min, or a contact area change rate > c%, then the theoretical overload value is the actual overload point, and the tire pressure before the mutation is determined as the overload tire pressure.

4. The method for measuring the load of goods based on tire pressure indicators according to claim 1, wherein: The tire pressure data includes the no-load tire pressure, the overload tire pressure, and several increased-load tire pressures; Step S3 includes the following steps: S31: Using an improved polynomial regression algorithm, a tire pressure-temperature fitting formula is constructed based on the tire pressure data and the tire temperature; S32: Using the tire pressure-temperature fitting formula according to the reference temperature, the tire pressure data is temperature-compensated to obtain the temperature-compensated tire pressure.

5. The method for measuring the load of goods based on tire pressure index according to claim 1, wherein: The steps in Step S4 include the following steps: S41: The temperature-compensated tire pressure is divided into a set of forward tire pressures and a set of backward tire pressures according to the tire position. Each set of forward and backward tire pressures includes the left-side tire pressure and the right-side tire pressure, and the left-side tire pressure and the right-side tire pressure are compared; S42: If the data difference between the left-side tire pressure and the right-side tire pressure is large, the debugger is reminded that there is a problem with the tires of the current industrial vehicle; if the data difference between the left-side tire pressure and the right-side tire pressure is small, the average value of the left-side tire pressure and the right-side tire pressure is used as the forward tire pressure F2 or the backward tire pressure F3; S43: The total cargo weight F1, the forward tire pressure F2, and the backward tire pressure F3 are subjected to several data fittings to obtain a cargo-tire pressure fitting formula; S44: According to the characteristics of the cargo-tire pressure fitting formula, a corresponding cargo-tire pressure curve graph is drawn.

6. The method for measuring the load of goods based on tire pressure indicators according to claim 1, wherein: The tire aging process includes four stages: initial aging, intermediate aging, deep aging, and functional failure; the central processor of the industrial vehicle performs no-load self-calibration according to the calibration values at each stage; the calibration values include the first calibration value for initial aging as , the secondary standard value for intermediate aging as , the tertiary standard value for deep aging as , and the quaternary standard value for functional failure as .

7. The method for measuring the load of goods based on tire pressure index according to claim 6, wherein: The process of no-load self-calibration is as follows: When the data of the no-load tire pressure collected by the central processor is abnormal: If the abnormal data duration is short, it is determined that the tire is in the initial aging stage, and the first calibration value is continued to be used as the no-load tire pressure; If the abnormal data duration is long, it is determined that the tire enters the middle aging stage, and at the same time, the no-load tire pressure is changed from the first calibration value to the secondary standard value ; And so on, as time goes by, the no-load tire pressure is successively replaced by the tertiary standard value or the quaternary standard value .

8. The method for measuring the load of goods based on tire pressure index according to claim 6, wherein: The standard value is the average value of all the tire pressure data collected by the central processing unit within D minutes.

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