An intelligent weighing management system

Abstract

The invention relates to the technical field of weighing management, and specifically discloses an intelligent weighing management system for solving the problem that the accuracy of weighing results of existing vehicles is significantly reduced when the vehicles are traveling at high speed, and the problem that the accuracy of weighing results is affected by the redistribution of goods due to bumps and vibrations. The invention divides the vehicle load into a plurality of weight point areas according to the wheel axle at the bottom of the vehicle, obtains the load weight of each weight point area in real time, extracts the load weight of each weight point area during a monitoring period, calculates the vehicle load coefficient, obtains the in-vehicle weight data based on the in-vehicle weight distribution sorting during the monitoring period, calculates the uniform value of the vehicle load distribution, and effectively solves the influence of the vehicle's high-speed driving and uneven load distribution on the weighing accuracy by analyzing the influence of the vehicle speed fluctuation value and environmental interference on the vehicle weighing accuracy, and significantly improves the accuracy, reliability and stability of the weighing data.

Description

Technical Field

[0001] The present invention relates to the technical field of weighing management, and more specifically, to an intelligent weighing management system. Background Art

[0002] The vehicle dynamic weighing system is often used in the process of vehicle driving. Through sensors and data acquisition equipment installed on the road or weighing platform, the vehicle is weighed in real time. It is widely used in the fields of traffic management, freight logistics and road infrastructure protection. The traditional static weighing method requires the vehicle to stop completely and weigh on the weighing platform, which is not only time-consuming and labor-intensive, but also has a great impact on traffic flow. In order to solve these problems, dynamic weighing technology came into being, allowing vehicles to be weighed during normal driving, thereby improving weighing efficiency and reducing interference with traffic. The core component of the dynamic weighing system is the weighing sensor, which is installed on the road surface, bridge or dedicated weighing crossing to detect the force generated when the vehicle passes in real time and convert it into an electrical signal. Although the existing technology can weigh the vehicle while it is driving, there are certain restrictions on the speed of the vehicle. When the speed exceeds the specified range, the accuracy of the weighing result will be significantly reduced; and the uneven distribution of goods on the vehicle will also lead to inaccurate weighing results. Especially in long-distance transportation, the goods may be redistributed due to bumps and vibrations, thereby affecting the accuracy of the weighing results. In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0003] In order to overcome the above-mentioned defects of the prior art, the present invention provides an intelligent weighing management system, which obtains the in-vehicle weight data based on the in-vehicle weight distribution sorting within the monitoring period, calculates the uniform value of the vehicle load distribution, and effectively solves the influence of high-speed driving and uneven load distribution on the weighing accuracy by analyzing the influence of vehicle speed fluctuation value and environmental interference on the vehicle weighing accuracy, and significantly improves the accuracy, reliability and stability of the weighing data, so as to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] An intelligent weighing management system includes a vehicle weighing sensor, a vehicle load distribution monitoring center, a vehicle weighing management center, and an intelligent data management platform. The vehicle load distribution monitoring center includes a weight point division module, a plurality of load weighing sensors, a first data acquisition module, a vehicle load coefficient calculation module, and a load distribution uniformity judgment module; the weight point division module is used to divide the vehicle load into a plurality of weight point areas according to the bottom axle of the vehicle, and a load weighing sensor is set in each weight point area; the load weighing sensor is used to obtain the load weight of each weight point area in real time; the first data acquisition module is used to extract the load weight of each weight point area within a monitoring period, and calculate the load factor of the monitoring period. The load weight values ​​of each weight point area during the period are arranged in descending order to obtain the in-vehicle weight distribution ranking during the monitoring period, and the load weight average of each weight point area is calculated according to the in-vehicle weight distribution ranking; the vehicle load coefficient calculation module is used to calculate the vehicle load coefficient; the load distribution uniformity judgment module is used to extract the vehicle load coefficient and the in-vehicle weight distribution ranking during the monitoring period, obtain the in-vehicle weight data based on the in-vehicle weight distribution ranking during the monitoring period, import the vehicle load coefficient and the in-vehicle weight data during the monitoring period into the load distribution uniformity calculation formula, and calculate the vehicle load distribution uniformity. The load distribution uniformity calculation formula is:

[0006] ;

[0007] Where: is the uniform value of vehicle load distribution, is the number of weight point areas, is the vehicle load factor, is the number of in-vehicle weight data in the xth weight point area, The in-vehicle weight data of the in-vehicle weight distribution sorted as a in the x-th weight point area, The in-vehicle weight data of the in-vehicle weight distribution in the x-th weight point area with the order of a+1, The largest in-vehicle weight data in the in-vehicle weight distribution sorting of the x-th weight point area, is the smallest in-vehicle weight data in the in-vehicle weight distribution sorting of the x-th weight point area, Adjustment parameter to prevent the denominator from being zero.

[0008] As a further solution of the present invention, the vehicle load factor calculation module is used to calculate the vehicle load factor by extracting the load weight mean value within the monitoring period, obtaining the load weight value of each weight point area at the beginning of the monitoring period and the load weight value of each weight point area at the end of the monitoring period, and importing them into the vehicle load factor calculation formula to calculate the vehicle load factor. The calculation formula of the vehicle load factor is:

[0009] ;

[0010] Where: is the vehicle load factor, is the number of weight point areas, is the load weight value of the xth weight point area at the beginning of the monitoring cycle, is the load weight value of the xth weight point area at the end of the monitoring period, is the mean load weight in the xth weight point area.

[0011] As a further solution of the present invention, the first abnormal response module is used to obtain the load distribution uniformity threshold through the intelligent data management platform, and compare the load distribution uniformity value with the load distribution uniformity threshold. If the load distribution uniformity value is greater than or equal to the load distribution uniformity threshold, the vehicle load distribution uniformity is qualified; if the load distribution uniformity value is less than the load distribution uniformity threshold, the vehicle load distribution uniformity is unqualified, and a first abnormal alarm will be issued at this time.

[0012] As a further solution of the present invention, the vehicle weighing management center includes a vehicle speed monitoring module, a speed compensation analysis module, a signal receiving module, an environmental interference compensation analysis module, a weighing correction module and a second abnormal response module.

[0013] As a further solution of the present invention, the vehicle speed monitoring module is used to monitor the speed fluctuation range data of the vehicle before it is ready for weighing, and arrange the speed fluctuation range data in order from large to small according to the monitoring time, obtain the speed fluctuation data arrangement, and calculate the speed fluctuation mean of the vehicle according to the speed fluctuation data arrangement; the speed compensation analysis module is used to extract the maximum speed fluctuation value in the speed fluctuation data arrangement and the minimum speed fluctuation , get the mean speed fluctuation of the vehicle , and determine The speed correction value The relationship between When , the signal X is fed back to the signal receiving module; when When the feedback signal X is received, the vehicle fluctuation value has no influence on the vehicle weighing; when the feedback signal Y is received, the vehicle fluctuation value will have influence on the vehicle weighing.

[0014] As a further solution of the present invention, the environmental interference compensation analysis module is used to obtain environmental temperature range data through a temperature sensor, obtain environmental humidity range data through a humidity sensor, and obtain wind speed range data through a wind speed sensor. An environmental interference compensation analysis model is constructed based on the environmental temperature range data, the environmental humidity range data, and the wind speed range data to calculate the environmental interference compensation value. The formula of the environmental interference compensation analysis model is:

[0015] ;

[0016] Where: is the environmental interference compensation value, is the number of data items for the ambient temperature range data, ambient humidity range data, and wind speed range data, is the maximum value of the range data corresponding to the hth item in the ambient temperature range data, ambient humidity range data and wind speed range data, is the minimum value of the hth item corresponding to the range data in the ambient temperature range data, ambient humidity range data and wind speed range data, It is the hth item in the ambient temperature range data, ambient humidity range data and wind speed range data.

[0017] As a further solution of the present invention, the weighing correction module is used to obtain the speed fluctuation data arrangement, environmental interference compensation value, vehicle load distribution uniformity value, vehicle weighing value and vehicle net weight when the vehicle fluctuation value will affect the vehicle weighing, construct a vehicle weighing accuracy value calculation model, and calculate the vehicle weighing accuracy value. The formula of the vehicle weighing accuracy value calculation model is:

[0018] ;

[0019] Where: The accurate value of vehicle weight. is the environmental interference compensation value, is the uniform value of vehicle load distribution, is the maximum value of speed fluctuation in the speed fluctuation data arrangement, is the minimum value of speed fluctuation in the speed fluctuation data arrangement, is the mean speed fluctuation of the vehicle, is the speed allowable correction value, is the vehicle weight, The net weight of the vehicle.

[0020] The technical effects and advantages of an intelligent weighing management system of the present invention are as follows: the present invention divides the vehicle load into several weight point areas according to the wheel axle at the bottom of the vehicle, obtains the load weight of each weight point area in real time, monitors the vehicle load distribution in a refined manner, and provides detailed load data to facilitate subsequent correction and compensation; extracts the load weight of each weight point area within the monitoring period, calculates the vehicle load coefficient, dynamically adjusts and compensates the weighing data, and ensures that accurate weighing results can still be provided when the load changes; obtains the in-vehicle weight data based on the in-vehicle weight distribution sorting within the monitoring period, calculates the uniform value of the vehicle load distribution, evaluates and adjusts the load distribution, reduces the weighing error caused by uneven load, and improves data accuracy; by analyzing the influence of vehicle speed fluctuation values ​​and environmental interference on vehicle weighing accuracy, it can effectively solve the influence of high-speed driving and uneven load distribution on weighing accuracy, and significantly improve the accuracy, reliability and stability of weighing data. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of the structure of an intelligent weighing management system provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solution in the present invention. Obviously, the described technical solution is only a part of the present invention, not all of it. Based on the technical solution in the present invention, all other technical solutions obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Figure 1 FIG. 1 shows a schematic diagram of the structure of an intelligent weighing management system provided by Embodiment 1 of the present invention. Figure 1 As shown, an intelligent weighing management system in this embodiment includes a vehicle weighing sensor, a vehicle load distribution monitoring center, a vehicle weighing management center, and an intelligent data management platform; the vehicle weighing sensor is connected to the vehicle weighing management center and the intelligent data management platform respectively, and the intelligent data management platform is connected to the vehicle weighing sensor, the vehicle load distribution monitoring center, and the vehicle weighing management center respectively;

[0024] The vehicle weighing sensor is used to obtain the vehicle weighing value;

[0025] The vehicle load distribution monitoring center is used to monitor and analyze the uniformity of the vehicle's load distribution;

[0026] The vehicle weighing management center is used to analyze the vehicle weighing accuracy;

[0027] The intelligent data management platform is used to store data obtained by vehicle weighing sensors, vehicle load distribution monitoring center and vehicle weighing management center.

[0028] The vehicle load distribution monitoring center includes a weight point division module, a plurality of load weighing sensors, a first data acquisition module, a vehicle load factor calculation module, a load distribution uniformity judgment module and a first abnormal response module;

[0029] The weight point division module is connected to a plurality of load weighing sensors, the plurality of load weighing sensors are connected to the first data acquisition module, the first data acquisition module is connected to the vehicle load factor calculation module, the vehicle load factor calculation module is connected to the load distribution uniformity judgment module, and the load distribution uniformity judgment module is connected to the first abnormal response module;

[0030] The weight point division module is used to divide the vehicle load into several weight point areas according to the bottom axle of the vehicle, and a load weighing sensor is set in each weight point area;

[0031] The load weighing sensor is used to obtain the load weight of each weight point area in real time;

[0032] The first data acquisition module is used to extract the load weight of each weight point area during the monitoring period, and arrange the load weight values ​​of each weight point area during the monitoring period in descending order to obtain the in-vehicle weight distribution ranking during the monitoring period, and calculate the load weight mean of each weight point area according to the in-vehicle weight distribution ranking;

[0033] The vehicle load factor calculation module is used to extract the average load weight within the monitoring period, obtain the load weight value of each weight point area at the beginning of the monitoring period and the load weight value of each weight point area at the end of the monitoring period, and import them into the vehicle load factor calculation formula to calculate the vehicle load factor. The calculation formula of the vehicle load factor is:

[0034] ;

[0035] Where: is the vehicle load factor, is the number of weight point areas, is the load weight value of the xth weight point area at the beginning of the monitoring cycle, is the load weight value of the xth weight point area at the end of the monitoring period, is the mean load weight of the xth weight point area;

[0036] The load distribution uniformity judgment module is used to extract the vehicle load coefficient and the in-vehicle weight distribution ranking within the monitoring period, obtain the in-vehicle weight data based on the in-vehicle weight distribution ranking within the monitoring period, import the vehicle load coefficient and the in-vehicle weight data within the monitoring period into the load distribution uniformity calculation formula, and calculate the vehicle load distribution uniformity value. The load distribution uniformity calculation formula is:

[0037] ;

[0038] Where: is the uniform value of vehicle load distribution, is the number of weight point areas, is the vehicle load factor, is the number of in-vehicle weight data in the xth weight point area, The in-vehicle weight data of the in-vehicle weight distribution sorted as a in the x-th weight point area, The in-vehicle weight data of the in-vehicle weight distribution in the x-th weight point area with the order of a+1, The largest in-vehicle weight data in the in-vehicle weight distribution sorting of the x-th weight point area, is the smallest in-vehicle weight data in the in-vehicle weight distribution sorting of the x-th weight point area, Adjustment parameter to prevent the denominator from being zero.

[0039] The first abnormal response module is used to obtain the load distribution uniformity threshold through the intelligent data management platform, and compare the load distribution uniformity value with the load distribution uniformity threshold. If the load distribution uniformity value is greater than or equal to the load distribution uniformity threshold, the vehicle load distribution uniformity is qualified; if the load distribution uniformity value is less than the load distribution uniformity threshold, the vehicle load distribution uniformity is unqualified, and the first abnormal alarm will be issued.

[0040] The vehicle load is divided into several weight point areas according to the bottom axle of the vehicle, and a load weighing sensor is set in each area to obtain the load weight of each weight point area in real time. The vehicle load is divided into several weight point areas according to the bottom axle of the vehicle, and a load weighing sensor is set in each area to obtain the load weight of each weight point area in real time; the load weight of each weight point area during the monitoring period is extracted, and these data are arranged in order from large to small, and the average load weight of each weight point area is calculated. Through real-time data acquisition and sorting, the load distribution of the vehicle can be dynamically monitored, and load changes can be discovered and responded to in time, so as to improve the timeliness and reliability of weighing data; the average load weight within the monitoring period is extracted, the load weight values ​​at the beginning and end of the monitoring period are calculated, and the formula is imported to calculate the vehicle load coefficient, which can quantitatively evaluate the load change, effectively analyze the load stability and uniformity, and provide basic data for further load distribution uniformity judgment; the vehicle load coefficient and the in-vehicle weight distribution sorting within the monitoring period are extracted, and the load distribution uniformity value is calculated, which can effectively judge whether the vehicle load is evenly distributed and avoid weighing errors caused by uneven load.

[0041] Through detailed weight point area division, real-time data collection and analysis, and multi-parameter load uniformity evaluation and anomaly detection, the intelligent weighing management system can effectively solve the accuracy problems of existing weighing systems under high-speed driving and uneven load conditions, and can greatly improve the accuracy and reliability of weighing data.

[0042] The vehicle weighing management center includes a vehicle speed monitoring module, a speed compensation analysis module, a signal receiving module, an environmental interference compensation analysis module, a weighing correction module and a second abnormal response module; the vehicle speed monitoring module is connected to the speed compensation analysis module, the speed compensation analysis module is connected to the signal receiving module, the signal receiving module is connected to the weighing correction module, the environmental interference compensation analysis module is connected to the weighing correction module, and the weighing correction module is connected to the second abnormal response module.

[0043] The vehicle speed monitoring module is used to monitor the speed fluctuation range data of the vehicle before it is ready for weighing, and to arrange the speed fluctuation range data in order from large to small according to the monitoring time, to obtain the speed fluctuation data arrangement, and to calculate the speed fluctuation mean of the vehicle according to the speed fluctuation data arrangement;

[0044] It should be noted that the speed fluctuation range data before the vehicle is ready to be weighed refers to obtaining the distance from the location where the vehicle first starts to decelerate before being weighed in history, and there are no obstacles in the distance, and determining the time range before the vehicle is ready to be weighed by calculating the average time required for the vehicle to pass through the distance; obtaining the vehicle speed fluctuation data within the time range before the vehicle is ready to be weighed, wherein the calculation formula of the vehicle speed fluctuation data is:

[0045] ;

[0046] Where: is the vehicle speed fluctuation data at time d, is the vehicle speed data at time d+1, is the vehicle speed data at time d;

[0047] The speed fluctuation range data is formed by acquiring the vehicle speed fluctuation data within a time range before the vehicle is ready to be weighed.

[0048] The speed compensation analysis module is used to extract the maximum speed fluctuation value in the speed fluctuation data array. and the minimum speed fluctuation , get the mean speed fluctuation of the vehicle , and determine The speed correction value The relationship between When , the signal X is fed back to the signal receiving module; when When , the signal Y is fed back to the signal receiving module;

[0049] The signal receiving module is used to receive feedback signals. When the feedback signal X is received, the vehicle fluctuation value has no impact on the vehicle weighing; when the feedback signal Y is received, the vehicle fluctuation value will have an impact on the vehicle weighing;

[0050] By monitoring the speed fluctuation range data of the vehicle before weighing and calculating the speed fluctuation mean, the influence of vehicle speed fluctuation on the weighing result can be effectively identified and compensated to ensure the accuracy of the weighing data; the maximum, minimum and mean values ​​in the speed fluctuation data are extracted to determine the influence of speed fluctuation on weighing and feedback the signal. By dynamically analyzing the speed fluctuation data, the weighing data can be judged and adjusted in time to avoid errors caused by speed fluctuation.

[0051] By integrating multiple modules such as vehicle speed monitoring, speed compensation analysis, environmental interference compensation and weighing correction, the intelligent weighing management system can effectively solve the accuracy problem of the existing system under the conditions of vehicle speed fluctuation and uneven load distribution. The system's real-time data monitoring, dynamic compensation and abnormal response mechanism significantly improve the accuracy and reliability of weighing data.

[0052] The environmental interference compensation analysis module is used to obtain environmental temperature range data through a temperature sensor, obtain environmental humidity range data through a humidity sensor, and obtain wind speed range data through a wind speed sensor. An environmental interference compensation analysis model is constructed based on the environmental temperature range data, the environmental humidity range data, and the wind speed range data to calculate the environmental interference compensation value. The formula of the environmental interference compensation analysis model is:

[0053] ;

[0054] Where: is the environmental interference compensation value, is the number of data items for the ambient temperature range data, ambient humidity range data, and wind speed range data, is the maximum value of the range data corresponding to the hth item in the ambient temperature range data, ambient humidity range data and wind speed range data, is the minimum value of the hth item corresponding to the range data in the ambient temperature range data, ambient humidity range data and wind speed range data, is the hth item in the ambient temperature range data, ambient humidity range data and wind speed range data;

[0055] The weighing correction module is used to obtain the speed fluctuation data arrangement, environmental interference compensation value, vehicle load distribution uniformity value, vehicle weighing value and vehicle net weight when the vehicle fluctuation value will affect the vehicle weighing, build a vehicle weighing accuracy value calculation model, and calculate the vehicle weighing accuracy value. The formula of the vehicle weighing accuracy value calculation model is:

[0056] ;

[0057] Where: The accurate value of vehicle weight. is the environmental interference compensation value, is the uniform value of vehicle load distribution, is the maximum value of speed fluctuation in the speed fluctuation data arrangement, is the minimum value of speed fluctuation in the speed fluctuation data arrangement, is the mean speed fluctuation of the vehicle, is the speed allowable correction value, is the vehicle weight, is the vehicle's net weight;

[0058] The second abnormal response module is used to extract the vehicle weighing accuracy value and compare the vehicle weighing accuracy value with the preset vehicle weighing correction threshold. If the vehicle weighing accuracy value is greater than or equal to the preset vehicle weighing correction threshold, the vehicle weighing accuracy is qualified; if the vehicle weighing accuracy value is less than the preset vehicle weighing correction threshold, the vehicle weighing accuracy is unqualified.

[0059] Analyze the impact of environmental interference (such as temperature, humidity, wind speed) on weighing data, conduct compensation analysis, comprehensively consider the impact of environmental factors on weighing data, make effective compensation, and ensure the stability and reliability of the data; correct the weighing data and detect whether there are any abnormalities in the corrected data. Through real-time monitoring and dynamic correction, the weighing accuracy of vehicles in the case of speed fluctuations and uneven loads can be significantly improved, which helps to promptly discover and deal with abnormal situations and improve the safety of the system; through detailed module design and comprehensive compensation and correction mechanism, the intelligent weighing management system can effectively solve the accuracy problems of existing weighing systems in the case of speed fluctuations and environmental interference, and greatly improve the accuracy and reliability of weighing data.

[0060] The embodiment of the present invention divides the vehicle load into several weight point areas according to the wheel axle at the bottom of the vehicle, obtains the load weight of each weight point area in real time, monitors the vehicle load distribution in a refined manner, and provides detailed load data to facilitate subsequent correction and compensation; extracts the load weight of each weight point area within the monitoring period, calculates the vehicle load coefficient, and dynamically adjusts and compensates the weighing data to ensure that accurate weighing results can still be provided when the load changes; obtains the in-vehicle weight data based on the in-vehicle weight distribution sorting within the monitoring period, calculates the uniform value of the vehicle load distribution, evaluates and adjusts the load distribution, reduces the weighing error caused by uneven load, and improves data accuracy; by analyzing the influence of vehicle speed fluctuation values ​​and environmental interference on vehicle weighing accuracy, it can effectively solve the influence of high-speed driving and uneven load distribution on weighing accuracy, and significantly improve the accuracy, reliability and stability of weighing data.

[0061] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0062] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent weighing management system, comprising a vehicle weighing sensor, a vehicle load distribution monitoring center, a vehicle weighing management center, and an intelligent data management platform, characterized in that: The vehicle load distribution monitoring center includes a weight point division module, a plurality of load weighing sensors, a first data acquisition module, a vehicle load coefficient calculation module, and a load distribution uniformity judgment module; the weight point division module is used to divide the vehicle load into a plurality of weight point areas according to the bottom axle of the vehicle, and a load weighing sensor is set in each weight point area; the load weighing sensor is used to obtain the load weight of each weight point area in real time; the first data acquisition module is used to extract the load weight of each weight point area within the monitoring period, and arrange the load weight values ​​of each weight point area within the monitoring period in a descending order, obtain the in-vehicle weight distribution ranking within the monitoring period, and calculate the load weight mean of each weight point area according to the in-vehicle weight distribution ranking; The vehicle load factor calculation module is used to calculate the vehicle load factor; The load distribution uniformity judgment module is used to extract the vehicle load coefficient and the in-vehicle weight distribution ranking within the monitoring period, obtain the in-vehicle weight data based on the in-vehicle weight distribution ranking within the monitoring period, import the vehicle load coefficient and the in-vehicle weight data within the monitoring period into the load distribution uniformity calculation formula, and calculate the vehicle load distribution uniformity value. The load distribution uniformity calculation formula is: ； Where: is the uniform value of vehicle load distribution, is the number of weight point areas, is the vehicle load factor, is the number of in-vehicle weight data in the xth weight point area, The in-vehicle weight data of the in-vehicle weight distribution sorted as a in the x-th weight point area, The in-vehicle weight data of the in-vehicle weight distribution in the x-th weight point area with the order of a+1, The largest in-vehicle weight data in the in-vehicle weight distribution sorting of the x-th weight point area, is the smallest in-vehicle weight data in the in-vehicle weight distribution sorting of the x-th weight point area, To prevent the adjustment parameter from reaching zero denominator; The vehicle load factor calculation module is used to calculate the vehicle load factor. By extracting the average load weight within the monitoring period, the load weight value of each weight point area at the beginning of the monitoring period and the load weight value of each weight point area at the end of the monitoring period are obtained, and imported into the vehicle load factor calculation formula to calculate the vehicle load factor. The calculation formula of the vehicle load factor is: ； Where: is the vehicle load factor, is the number of weight point areas, is the load weight value of the xth weight point area at the beginning of the monitoring cycle, is the load weight value of the xth weight point area at the end of the monitoring period, is the mean load weight of the xth weight point area; The vehicle weighing management center includes a vehicle speed monitoring module, a speed compensation analysis module, a signal receiving module, an environmental interference compensation analysis module, a weighing correction module and a second abnormal response module; The vehicle speed monitoring module is used to monitor the speed fluctuation range data of the vehicle before it is ready to be weighed. The speed fluctuation range data of the vehicle before it is ready to be weighed refers to obtaining the distance from the location where the vehicle first started to decelerate before being weighed in history, and there are no obstacles in the distance. The time range before the vehicle is ready to be weighed is determined by calculating the average time required for the vehicle to pass through the distance; the vehicle speed fluctuation data within the time range before the vehicle is ready to be weighed is obtained, and the speed fluctuation range data is arranged in order from large to small according to the monitoring time, to obtain the speed fluctuation data arrangement, and the speed fluctuation mean of the vehicle is calculated according to the speed fluctuation data arrangement; the speed compensation analysis module is used to extract the maximum speed fluctuation in the speed fluctuation data arrangement and the minimum speed fluctuation , get the mean speed fluctuation of the vehicle , and determine The speed correction value The relationship between When , the signal X is fed back to the signal receiving module; when When the feedback signal X is received, the vehicle fluctuation value has no influence on the vehicle weighing; when the feedback signal Y is received, the vehicle fluctuation value will have influence on the vehicle weighing; The environmental interference compensation analysis module is used to obtain environmental temperature range data through a temperature sensor, obtain environmental humidity range data through a humidity sensor, and obtain wind speed range data through a wind speed sensor. An environmental interference compensation analysis model is constructed based on the environmental temperature range data, the environmental humidity range data, and the wind speed range data to calculate the environmental interference compensation value. The formula of the environmental interference compensation analysis model is: ； Where: is the environmental interference compensation value, is the number of data items for the ambient temperature range data, ambient humidity range data, and wind speed range data, is the maximum value of the range data corresponding to the hth item in the ambient temperature range data, ambient humidity range data and wind speed range data, is the minimum value of the hth item corresponding to the range data in the ambient temperature range data, ambient humidity range data and wind speed range data, is the hth item in the ambient temperature range data, ambient humidity range data and wind speed range data; The weighing correction module is used to obtain the speed fluctuation data arrangement, environmental interference compensation value, vehicle load distribution uniformity value, vehicle weighing value and vehicle net weight when the vehicle fluctuation value will affect the vehicle weighing, build a vehicle weighing accuracy value calculation model, and calculate the vehicle weighing accuracy value. The formula of the vehicle weighing accuracy value calculation model is: ； Where: The accurate value of vehicle weight. is the environmental interference compensation value, is the uniform value of vehicle load distribution, is the maximum value of speed fluctuation in the speed fluctuation data arrangement, is the minimum value of speed fluctuation in the speed fluctuation data arrangement, is the mean speed fluctuation of the vehicle, is the speed allowable correction value, is the vehicle weight, The net weight of the vehicle.

2. The intelligent weighing management system according to claim 1, characterized in that: The first abnormal response module is used to obtain the load distribution uniformity threshold through the intelligent data management platform, and compare the load distribution uniformity value with the load distribution uniformity threshold. If the load distribution uniformity value is greater than or equal to the load distribution uniformity threshold, the vehicle load distribution uniformity is qualified; if the load distribution uniformity value is less than the load distribution uniformity threshold, the vehicle load distribution uniformity is unqualified, and the first abnormal alarm will be issued.

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