Method for integrating multi-source data into source overload control data

Abstract

The invention relates to the technical field of transportation, and discloses a method for integrating multi-source data into source overload control data, which comprises the following steps: S1, establishing communication between different source data devices and an edge computing gateway; s2, calculating the number of axles; s3, reading weighing data of the wagon balance; s4, capturing pictures of a vehicle body and a vehicle head and recording a vehicle video; and S5, weighing, integrating the data, and uploading the integrated data to an overload control supervision platform. On the basis of original wagon balance equipment, the axle sensor and the camera are additionally arranged, statistics of factory vehicle information is achieved through judgment, processing and integration of related data source data, automation is achieved, labor cost is greatly reduced, and equipment cost is reduced. After data of different sources are integrated, comprehensive judgment is performed through a sliding window mean filtering algorithm, and finally integration and reporting of vehicle information are automatically completed, so that manual intervention is avoided, and low-cost and high-efficiency source overload control data acquisition is realized on the basis of fully utilizing existing equipment.

Description

Technical Field

[0001] This invention relates to the field of transportation technology, and more particularly to the field of monitoring the source of overloaded vehicles, specifically a method for integrating multi-source data into source control data for overloading. Background Technology

[0002] Overloaded vehicle source monitoring refers to a series of measures and methods implemented by traffic management departments to fundamentally prevent and address the problem of overloaded freight vehicles. These measures involve moving the regulatory focus upstream, monitoring, managing, and controlling key stages such as vehicle departure from the factory, cargo loading, and vehicle departure from the road, starting at the point of cargo loading (i.e., the "source"). The goal is to prevent overloaded vehicles from leaving the loading site, thus cutting off overloading at its source.

[0003] To effectively control and prevent overloading from the source (i.e., the starting point of the transportation process), rather than relying solely on roadside detection or post-event handling, manufacturers are required to report information on vehicles leaving the factory. In the case of only weighbridge equipment in the factory area, the reporting can only be done manually, which is inefficient. If the weighbridge equipment is replaced, the corresponding equipment cost will be high. Therefore, we need to propose a method based on the integration of multi-source data into source-based overloading control data. Summary of the Invention

[0004] The purpose of this invention is to provide a method for source control of overloading based on the integration of multi-source data. By judging, processing and integrating relevant data sources, the method realizes the statistics of vehicle information leaving the factory. Compared with manual statistics, it achieves automation and greatly reduces labor costs; compared with equipment replacement, it reduces equipment costs, thereby solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for integrating multi-source data into source-based overload control data, comprising the following steps: S1, the wheel axle sensor, weighbridge, vehicle body capture camera, vehicle front capture camera, and video recording camera establish communication with the edge computing gateway respectively; S2. Before the vehicle is weighed, the wheels pass over the axle sensors, generating pulse signals and starting to calculate the number of axles; S3. During the wheel and axle count calculation process, the vehicle enters the weighbridge but is not fully on the weighbridge and is in motion. The weighbridge data changes and increases continuously. After the vehicle stops on the weighbridge, the wheel and axle count stops and the weighbridge weighing data is read. S4. Call the vehicle body capture camera to capture images of the vehicle body, the front capture camera to capture images of the front of the vehicle and recognize the license plate, and record video of the vehicle driving. S5. The vehicle leaves the weighbridge, the vehicle is deemed to have left the factory, the weighbridge data is reset to zero, and the wheel axle count is also reset to zero. The edge computing gateway packages and sends the acquired vehicle wheel axle count, weighing data, vehicle body image, vehicle front image, and recorded video to the overload control supervision platform.

[0006] Preferably, the wheel axle sensor communicates with the edge computing gateway via digital input, the weighbridge communicates with the edge computing gateway via serial communication, and the vehicle body capture camera, the front capture camera, and the video recording camera communicate with the edge computing gateway via Ethernet.

[0007] Preferably, the edge computing gateway integrates an RS485 interface, a DI interface, and multiple Ethernet interfaces. The edge computing gateway is connected to the weighbridge via the RS485 interface, the edge computing gateway is connected to the wheel axle sensor via the DI interface, and the edge computing gateway is connected to the vehicle body capture camera, the front capture camera, the video recording camera, and the overload control monitoring platform via the multiple Ethernet interfaces.

[0008] Preferably, the edge computing gateway continuously reads the raw data frames sent by the weighbridge via the RS485 interface. The DI interface of the edge computing gateway monitors the level changes of the wheel axle sensors, and records the wheel axle count once for each high-level pulse detected. The edge computing gateway also listens to the recognition results pushed by the vehicle body capture camera, the front capture camera, and the video recording camera.

[0009] Preferably, the edge computing gateway parses the acquired multiple data, integrates the parsed data into structured data, and uploads it to the overload control supervision platform via an Ethernet interface.

[0010] Preferably, the weighbridge uses the Modbus protocol to continuously send data frames at a set frequency. The edge computing gateway extracts the register value representing the weight from the data frame and converts it into a decimal number. When parsing the wheel axle signal, the edge computing gateway converts the physical level signal into a logical count, that is, the number of pulses equals the number of axles. When parsing the license plate information, the edge computing gateway parses the received structured data and extracts the license plate number and timestamp field.

[0011] Preferably, after a vehicle enters the weighbridge, the edge computing gateway reads the weighbridge weight data in real time and uses a sliding window mean filtering algorithm to determine whether the weighbridge weight data is stable. If the fluctuation of the edge computing gateway's five consecutive sample values ​​is less than 2%, it is determined that the weighbridge weight is stable, meaning that the vehicle has come to a stop on the weighbridge.

[0012] Preferably, after the vehicle's status on the weighbridge stabilizes, the edge computing gateway controls the vehicle body capture camera and the front capture camera to capture images, and controls the video recording camera to record a 10-second video of the vehicle.

[0013] Preferably, when a vehicle enters the factory normally, the vehicle first passes through the wheel axle sensor, receives the wheel axle signal, then the weighbridge data rises and gradually stabilizes, and after the vehicle stabilizes, a picture of the vehicle is captured and a video is recorded. Finally, the vehicle leaves the weighbridge, the weighbridge returns to zero, and the wheel axle count returns to zero. When the vehicle enters from the opposite direction, the edge computing gateway first obtains the weighbridge data, then receives the wheel axle signal, determines that the vehicle is in the entry state, and does not process or trigger data integration.

[0014] Preferably, the wheel axle sensor is embedded in the road surface at the entrance of the weighbridge and adopts the piezoelectric or magnetic induction principle. It generates an electrical pulse signal every time an axle passes by. The weighbridge has a built-in resistance strain gauge that outputs an analog voltage signal, which is converted into digital weight data by an AD module.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention adds wheel axle sensors and cameras to the existing weighbridge equipment. By judging, processing and integrating relevant data sources, it realizes the statistics of vehicle information leaving the factory. Compared with manual statistics, it realizes automation and greatly reduces labor costs; compared with replacing equipment, it reduces equipment costs.

[0016] 2. In this invention, different source data devices communicate with the edge computing gateway. The edge computing gateway translates various raw data streams into meaningful engineering values ​​(such as weight, number of axles, and license plate number). Then, based on the temporal and logical relationships between them, a sliding window mean filtering algorithm is used for comprehensive judgment. Finally, the integration and reporting of vehicle information is automatically completed, avoiding manual intervention. Based on the full utilization of existing equipment, low-cost and high-efficiency source control data collection is achieved. Attached Figure Description

[0017] Figure 1 This is a schematic diagram showing the locations of different data source devices in this invention; Figure 2 This is a schematic diagram of the data judgment, processing, and integration process of the present invention; Figure 3 This is a flowchart of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1-3 This invention provides a technical solution: a method for integrating multi-source data into source-based traffic control data, comprising the following steps: S1, the wheel axle sensor, weighbridge, vehicle body capture camera, vehicle front capture camera, and video recording camera establish communication with the edge computing gateway respectively; S2. Before the vehicle is weighed, the wheels pass over the axle sensors, generating pulse signals and starting to calculate the number of axles; S3. During the wheel and axle count calculation process, the vehicle enters the weighbridge but is not fully on the weighbridge and is in motion. The weighbridge data changes and increases continuously. After the vehicle stops on the weighbridge, the wheel and axle count stops and the weighbridge weighing data is read. S4. Call the vehicle body capture camera to capture images of the vehicle body, the front capture camera to capture images of the front of the vehicle and recognize the license plate, and record video of the vehicle driving. S5. The vehicle leaves the weighbridge, the vehicle is deemed to have left the factory, the weighbridge data is reset to zero, and the wheel axle count is also reset to zero. The edge computing gateway packages and sends the acquired vehicle wheel axle count, weighing data, vehicle body image, vehicle front image, and recorded video to the overload control supervision platform.

[0020] After establishing communication between the devices, data acquisition is performed first. Before a vehicle passes over the wheel axle sensor, a pulse signal is generated, and the number of wheel axles is counted. The weight data of the weighbridge is read in real time. The stability of the data is determined by a sliding window mean filtering algorithm. Once the weighbridge data is stable, the system automatically triggers the capture of images of the vehicle's front and body and records a 10-second video of the vehicle, while simultaneously recognizing the license plate. Then, the data is processed and judged. Under normal factory conditions, the edge computing gateway receives the wheel axle signal → the weighbridge data rises → the weighbridge data stabilizes → the vehicle is captured and recorded → it leaves the weighbridge; and the wheel axle count, vehicle image and video information are bound to the same vehicle through timestamps, with the weighbridge data as the main timeline.

[0021] When entering the site in the opposite direction, the weighbridge data rises → a wheel axle signal is received. At this time, the vehicle is marked as entering the site, and data integration is not triggered.

[0022] Finally, the data is integrated and reported. After the vehicle is weighed, structured data including vehicle weight, number of axles, license plate, photos, and videos are automatically generated and uploaded to the overload control supervision platform.

[0023] The wheel axle sensor communicates with the edge computing gateway via digital input, the weighbridge communicates with the edge computing gateway via serial communication, and the vehicle body capture camera, the front capture camera, and the video recording camera communicate with the edge computing gateway via Ethernet.

[0024] The edge computing gateway integrates an RS485 interface, a DI interface, and multiple Ethernet interfaces. The edge computing gateway is connected to the weighbridge via the RS485 interface, the wheel axle sensor via the DI interface, and the vehicle body capture camera, the front capture camera, the video recording camera, and the overload control monitoring platform via the multiple Ethernet interfaces.

[0025] The edge computing gateway has a built-in ARM processor, runs a Linux system, and deploys logic for data parsing, stability assessment, and license plate recognition result integration.

[0026] ARM processors can handle multiple tasks simultaneously, such as concurrent data acquisition (weighbridges, wheel axle sensors), network communication (interaction with cameras), and logical operations. Linux systems support multiple programming languages, enabling the development of complex data processing logic and the integration of third-party libraries (such as the pymodbus library for protocol parsing and the requests library for HTTP communication). Linux systems can stably manage concurrent data reception, parsing, evaluation, and reporting processes, ensuring that critical tasks are not interrupted.

[0027] The edge computing gateway runs a Modbus protocol parser that continuously listens to the serial port, receives raw data frames from the weighbridge, extracts the weight value from the frame based on the pre-configured device address, register address, and data format, and converts it into engineering units.

[0028] An interrupt service routine or level monitoring script is deployed within the edge computing gateway. When a wheel runs over the axle sensor, causing a level change (such as from low to high), an interrupt event is immediately triggered, and the interrupt service routine then increments the axle counter.

[0029] The edge computing gateway continuously listens to or polls the JSON format data packets actively pushed by the vehicle body capture camera and the front capture camera. After receiving the data, it uses a JSON parsing library to extract key information such as license plate number, recognition timestamp, and confidence level.

[0030] The edge computing gateway is also equipped with a communication module, which is used to upload the integrated data to the overload control supervision platform.

[0031] The edge computing gateway continuously reads the raw data frames sent by the weighbridge via the RS485 interface. The DI interface of the edge computing gateway monitors the level changes of the wheel axle sensors. Each time a high-level pulse is detected, the wheel axle count is recorded. The edge computing gateway also listens to the recognition results pushed by the vehicle body capture camera, the front capture camera, and the video recording camera.

[0032] If license plate recognition fails, other data will still be reported, the license plate field will be marked as "unrecognized", and the license plate information will not be saved.

[0033] The edge computing gateway parses the acquired data, integrates the parsed data into structured data, and uploads it to the overload control monitoring platform via an Ethernet interface.

[0034] The weighbridge uses the Modbus protocol to continuously send data frames at a set frequency. The edge computing gateway extracts the register value representing the weight from the data frame and converts it into a decimal number. When parsing the wheel axle signal, the edge computing gateway converts the physical level signal into a logical count, that is, the number of pulses equals the number of axles. When parsing the license plate information, the edge computing gateway parses the received structured data and extracts the license plate number and timestamp field.

[0035] After a vehicle enters the weighbridge, the edge computing gateway reads the weighbridge weight data in real time and uses a sliding window mean filtering algorithm to determine whether the weighbridge weight data is stable. If the fluctuation of the edge computing gateway's five consecutive sample values ​​is less than 2%, it is determined that the weighbridge weight is stable, meaning that the vehicle has come to a complete stop on the weighbridge.

[0036] Once the vehicle is stable on the weighbridge, the edge computing gateway controls the vehicle body capture camera and the front capture camera to capture images, and controls the video recording camera to record a 10-second video of the vehicle.

[0037] When a vehicle enters the factory normally, it first passes through the wheel axle sensor, receives the wheel axle signal, then the weighbridge data rises and gradually stabilizes, and after the vehicle stabilizes, it captures a picture of the vehicle and records a video. Finally, the vehicle leaves the weighbridge, the weighbridge returns to zero, and the wheel axle count returns to zero. When the vehicle enters from the opposite direction, the edge computing gateway first obtains the weighbridge data, then receives the wheel axle signal, determines that the vehicle is in the entry state, and does not process or trigger data integration.

[0038] The wheel axle sensor is embedded in the road surface at the entrance of the weighbridge. It adopts the piezoelectric or magnetic induction principle and generates an electrical pulse signal every time an axle passes. The weighbridge has a built-in resistance strain gauge that outputs an analog voltage signal, which is converted into digital weight data by an AD module.

[0039] It is worth noting that the edge computing gateway also includes a built-in signal conditioning module, which includes an opto-isolation unit, a filtering unit, and an AD conversion unit. The wheel axle sensor signal needs to pass through the opto-isolation unit and the filtering unit to prevent interference pulses from being counted incorrectly. The weighbridge analog signal is sampled with high precision through an AD conversion unit (such as ADS1256).

[0040] The edge computing gateway also includes a built-in storage and caching unit, which supports resume transmission after network outage and caches historical weighbridge data.

[0041] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for integrating multi-source data into source-based overload control data, characterized in that, Includes the following steps: S1, the wheel axle sensor, weighbridge, vehicle body capture camera, vehicle front capture camera, and video recording camera establish communication with the edge computing gateway respectively; S2. Before the vehicle is weighed, the wheels pass over the axle sensors, generating pulse signals and starting to calculate the number of axles; S3. During the wheel and axle count calculation process, the vehicle enters the weighbridge but is not fully on the weighbridge and is in motion. The weighbridge data changes and increases continuously. After the vehicle stops on the weighbridge, the wheel and axle count stops and the weighbridge weighing data is read. S4. Call the vehicle body capture camera to capture images of the vehicle body, the front capture camera to capture images of the front of the vehicle and recognize the license plate, and record video of the vehicle driving. S5. The vehicle leaves the weighbridge, the vehicle is deemed to have left the factory, the weighbridge data is reset to zero, and the wheel axle count is also reset to zero. The edge computing gateway packages and sends the acquired vehicle wheel axle count, weighing data, vehicle body image, vehicle front image, and recorded video to the overload control supervision platform.

2. The method for integrating multi-source data into source-based overload control data according to claim 1, characterized in that: The wheel axle sensor communicates with the edge computing gateway via digital input, the weighbridge communicates with the edge computing gateway via serial communication, and the vehicle body capture camera, the front capture camera, and the video recording camera communicate with the edge computing gateway via Ethernet.

3. The method for integrating multi-source data into source-based overload control data according to claim 2, characterized in that: The edge computing gateway integrates an RS485 interface, a DI interface, and multiple Ethernet interfaces. The edge computing gateway is connected to the weighbridge via the RS485 interface, the wheel axle sensor via the DI interface, and the vehicle body capture camera, the front capture camera, the video recording camera, and the overload control monitoring platform via the multiple Ethernet interfaces.

4. The method for integrating multi-source data into source-based overload control data according to claim 3, characterized in that: The edge computing gateway continuously reads the raw data frames sent by the weighbridge through the RS485 interface. The DI interface of the edge computing gateway monitors the level changes of the wheel axle sensors. Each time a high-level pulse is detected, the wheel axle count is recorded. The edge computing gateway monitors the recognition results pushed by the vehicle body capture camera, the front capture camera, and the video recording camera.

5. The method for integrating multi-source data into source-based overload control data according to claim 4, characterized in that: The edge computing gateway parses the acquired data, integrates the parsed data into structured data, and uploads it to the overload control monitoring platform via an Ethernet interface.

6. The method for integrating multi-source data into source-based overload control data according to claim 1, characterized in that: The weighbridge uses the Modbus protocol to continuously send data frames at a set frequency. The edge computing gateway extracts the register value representing the weight from the data frame and converts it into a decimal number. When parsing the wheel axle signal, the edge computing gateway converts the physical level signal into a logical count, that is, the number of pulses equals the number of axles. When the edge computing gateway parses license plate information, it parses the received structured data and extracts the license plate number and timestamp fields.

7. The method for integrating multi-source data into source-based overload control data according to claim 1, characterized in that: After a vehicle enters the weighbridge, the edge computing gateway reads the weighbridge weight data in real time and uses a sliding window mean filtering algorithm to determine whether the weighbridge weight data is stable. If the fluctuation of the edge computing gateway's five consecutive sample values ​​is less than 2%, it is determined that the weighbridge weight is stable, meaning that the vehicle has come to a complete stop on the weighbridge.

8. The method for integrating multi-source data into source-based overload control data according to claim 7, characterized in that: Once the vehicle is stable on the weighbridge, the edge computing gateway controls the vehicle body capture camera and the front capture camera to capture images, and controls the video recording camera to record a 10-second video of the vehicle.

9. The method for integrating multi-source data into source-based overload control data according to claim 1, characterized in that: When a vehicle enters the factory normally, it first passes through the wheel axle sensor, receives the wheel axle signal, then the weighbridge data rises and gradually stabilizes, and after the vehicle stabilizes, it captures a picture of the vehicle and records a video. Finally, the vehicle leaves the weighbridge, the weighbridge returns to zero, and the wheel axle count returns to zero. When the vehicle enters from the opposite direction, the edge computing gateway first obtains the weighbridge data, then receives the wheel axle signal, determines that the vehicle is in the entry state, and does not process or trigger data integration.

10. The method for integrating multi-source data into source-based overload control data according to claim 1, characterized in that: The wheel axle sensor is embedded in the road surface at the entrance of the weighbridge. It adopts the piezoelectric or magnetic induction principle and generates an electrical pulse signal every time an axle passes. The weighbridge has a built-in resistance strain gauge that outputs an analog voltage signal, which is converted into digital weight data by an AD module.

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