Vehicle dynamic weighing system and method based on time-sensitive network technology

Abstract

The application provides a vehicle dynamic weighing system and method based on time-sensitive network technology. The system: the weighing platform is divided into a detection area and a weighing area provided with a plurality of weighing sensors; a computer is connected with the plurality of weighing sensors and a camera through a time-sensitive network gateway, and is used for realizing the method, specifically: when a vehicle enters the detection area, N times of acquisition instruction sending actions are performed, and the acquisition instruction is synchronously sent to the weighing sensors and the camera in each action; a plurality of weighing data and vehicle posture images corresponding to each action are synchronously received, the former is used for determining initial weight data of a target axle, and the latter is used for determining a weighting coefficient of the initial weight data; the weighted weight data corresponding to the N actions is subjected to smoothing filtering processing and averaging to obtain weight data of the target axle; and vehicle dynamic weighing data is obtained according to the weight data of each axle. According to the application, the problem of unsatisfactory accuracy of the existing vehicle dynamic weighing system can be solved.

Description

Technical Field

[0001] This invention belongs to the field of vehicle dynamic weighing technology, and more specifically, relates to a vehicle dynamic weighing system and method based on time-sensitive network technology. Background Technology

[0002] In recent years, with the rapid development of the highway transportation industry, vehicle dynamic weighing technology has become a key technology and development direction for vehicle load measurement. Vehicle dynamic weighing involves weighing a vehicle without stopping or slowing down. Compared with static vehicle weighing, vehicle dynamic weighing not only has many advantages such as high speed, high efficiency, and minimal impact on highway throughput capacity, but also obtains relevant information such as the number of axles, axle load, and vehicle speed while obtaining the total vehicle weight.

[0003] Existing vehicle dynamic weighing systems mainly consist of three parts: a computer, a weighing platform, and a camera. Their working principle is as follows: First, after the vehicle enters the weighing platform, the computer acquires multiple weighing data points through multiple load sensors installed on the platform and obtains vehicle posture images through the camera. Second, the computer determines the weight data of the corresponding axle based on the multiple weighing data points, determines weighting coefficients based on the vehicle posture images, and performs weighted calculations on the axle weight data, thereby reducing the influence of vehicle posture on axle weight data detection. Finally, the dynamic weighing data of the vehicle is determined based on the acquired weighted weight data of each axle.

[0004] However, although existing vehicle dynamic weighing systems can obtain relatively accurate vehicle dynamic weighing data by using vehicle attitude compensation based on axle weight data, these systems still have the following problems:

[0005] 1. Asynchronous acquisition of feature data affects the accuracy of axle-weighted weight data, which in turn affects the accuracy of vehicle dynamic weighing data: Axle-weighted weight data is acquired based on multiple pre-acquired weighing data and vehicle posture images. However, existing vehicle dynamic weighing systems cannot guarantee the synchronization of the weighing data acquisition actions of multiple load cells and the synchronization of the load cell weighing data acquisition actions with the camera image acquisition actions. If the acquisition times of the aforementioned multiple weighing data and vehicle posture images are inconsistent, it will inevitably affect the accuracy of axle-weighted weight data, thus leading to inaccurate vehicle dynamic weighing data.

[0006] Second, when a vehicle drives onto the weighing platform, it is prone to an impact vibration. This impact vibration can affect the accuracy of the vehicle's dynamic weighing, and the existing vehicle dynamic weighing system does not take this factor into account. Summary of the Invention

[0007] The purpose of this invention is to solve the problem that the existing vehicle dynamic weighing system has unsatisfactory weighing accuracy because it cannot guarantee the synchronous acquisition of characteristic data and does not consider the impact vibration of the platform on the weighing.

[0008] To achieve the above objectives, the present invention provides a vehicle dynamic weighing system and method based on time-sensitive networking technology.

[0009] According to a first aspect of the present invention, a vehicle dynamic weighing system based on time-sensitive networking technology is provided, the vehicle dynamic weighing system comprising:

[0010] The weighing platform is divided into a detection area and a weighing area. The detection area is equipped with a detection module that outputs a vehicle entry prompt information when a vehicle enters the detection area. The weighing area is equipped with multiple weighing sensors.

[0011] Cameras and time-sensitive network gateways;

[0012] The computer, with each weighing sensor and the camera connected to it via the time-sensitive network gateway, is used for:

[0013] In response to the vehicle entry prompt, N acquisition command sending actions are executed for the target axle. In each acquisition command sending action, the acquisition command is simultaneously sent to each weighing sensor and the camera, so as to enable each weighing sensor to acquire weighing data and the camera to acquire vehicle posture images.

[0014] The system synchronously receives multiple weighing data points and vehicle posture images corresponding to each acquisition command. Based on the multiple weighing data points, it determines the initial weight data of the target axle. Based on the vehicle posture images, it determines weighting coefficients and performs weighted calculations on the initial weight data to obtain weighted weight data.

[0015] The weighted weight data corresponding to N acquisition command transmission actions are smoothed and filtered, and then averaged to obtain the weight data of the target axle, where N is a positive integer greater than 2.

[0016] The weight data of each axle is summed to obtain the dynamic weighing data of the vehicle.

[0017] According to a second aspect of the present invention, a vehicle dynamic weighing method based on time-sensitive network technology is provided. This vehicle dynamic weighing method is implemented based on the aforementioned vehicle dynamic weighing system based on time-sensitive network technology and applied to the computer, comprising the following steps:

[0018] In response to the vehicle entry prompt information, N acquisition command sending actions are performed for the target axle. In each acquisition command sending action, the acquisition command is synchronously sent to each weighing sensor and the camera, so as to enable each weighing sensor to acquire weighing data and the camera to acquire vehicle posture image.

[0019] The system synchronously receives multiple weighing data and vehicle posture images corresponding to each acquisition command sending action, determines the initial weight data of the target axle based on the multiple weighing data, determines the weighting coefficient based on the vehicle posture image, and performs weighted calculation on the initial weight data to obtain weighted weight data.

[0020] The weighted weight data corresponding to the N acquisition command sending actions are smoothed and filtered, and the average value is taken to obtain the weight data of the target axle;

[0021] The weight data of each axle is summed to obtain the dynamic weighing data of the vehicle.

[0022] Optionally, the acquisition command synchronously reaches each weighing sensor and the camera, including:

[0023] The latency of each weighing sensor connected to the time-sensitive network gateway and the latency of the camera are obtained in advance;

[0024] Based on the time delay of each weighing sensor and the time delay of the camera, acquisition commands are sent to each weighing sensor and the camera through the time-sensitive network gateway.

[0025] Optionally, the step of pre-obtaining the latency of each weighing sensor connected to the time-sensitive network gateway and the latency of the camera specifically involves:

[0026] The clocks of each weighing sensor and the camera are synchronized through the time-sensitive network gateway, and test packets are sent to each weighing sensor and the camera to obtain the latency of each weighing sensor and the latency of the camera.

[0027] Optionally, determining the weighting coefficients based on the vehicle attitude image includes:

[0028] The wheelbase of the target axle, the estimated height of the vehicle's center of gravity, and the angle between the vehicle body and the ground are determined based on the vehicle attitude image.

[0029] The weighting coefficients are determined based on the wheelbase of the target axle, the estimated height of the vehicle's center of gravity, and the angle between the vehicle body and the ground.

[0030] Alternatively, the formula for determining the weighting coefficients is:

[0031]

[0032] In the above formula, m is the weighting coefficient, h is the estimated value of the vehicle's center of gravity height, l is the length of the rigid body of the vehicle body, and θ is the angle between the vehicle body and the ground.

[0033] Alternatively, the smoothing and filtering of the weighted weight data corresponding to the N acquisition command sending actions is implemented based on the Savitzky-Golay method.

[0034] Alternatively, N = 5;

[0035] The Savitzky-Golay method is implemented based on the following formula:

[0036]

[0037] In the above formula, x represents the weighted weight data, and its subscript indicates the index of the weighted weight data; y represents the weighted weight data after smoothing filtering, and its subscript indicates the index of the weighted weight data after smoothing filtering; X is a quadratic matrix, X trans It is the transpose of the quadratic matrix;

[0038]

[0039] The beneficial effects of this invention are as follows:

[0040] The vehicle dynamic weighing system based on time-sensitive networking (TSN) technology of this invention has two main aspects. First, each weighing sensor and camera is connected to a computer via a TSN gateway. Upon receiving a vehicle entry notification, the computer sends a data acquisition command that is simultaneously transmitted to each weighing sensor and camera via the TSN gateway. This achieves synchronization of the weighing data acquisition actions of multiple load cells and the image acquisition actions of the cameras. Compared to existing vehicle dynamic weighing systems, the axle-weighted weight data obtained by this invention based on synchronously acquired weighing data and vehicle posture images has higher accuracy, resulting in higher accuracy of the vehicle dynamic weighing data. Second, compared to existing vehicle dynamic weighing systems, this invention adds a smoothing and filtering step to the axle-weighted weight data to reduce the impact of vehicle impact vibration on the dynamic weighing process, thereby further improving the accuracy of the acquired vehicle dynamic weighing data.

[0041] Based on the above two aspects, it can be seen that the vehicle dynamic weighing system based on time-sensitive network technology of the present invention can effectively solve the problem that the existing vehicle dynamic weighing system has unsatisfactory weighing accuracy due to its inability to guarantee the synchronous acquisition of feature data and its failure to consider the impact vibration of the platform on the weighing.

[0042] The vehicle dynamic weighing method based on time-sensitive network technology of the present invention belongs to the same general inventive concept as the above-mentioned vehicle dynamic weighing system based on time-sensitive network technology, and has at least the same beneficial effects as the above-mentioned vehicle dynamic weighing system based on time-sensitive network technology, the beneficial effects of which will not be repeated here.

[0043] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0044] The present invention can be better understood by referring to the following description taken in conjunction with the accompanying drawings, in which the same or similar reference numerals are used throughout the drawings to denote the same or similar parts.

[0045] Figure 1 A system block diagram of a vehicle dynamic weighing system based on time-sensitive network technology according to an embodiment of the present invention is shown;

[0046] Figure 2 A flowchart illustrating the implementation of a vehicle dynamic weighing method based on time-sensitive networking technology according to an embodiment of the present invention is shown. Detailed Implementation

[0047] To enable those skilled in the art to more fully understand the technical solutions of the present invention, exemplary embodiments of the present invention will be described more comprehensively and in detail below with reference to the accompanying drawings. Obviously, the one or more embodiments of the present invention described below are merely one or more specific ways to implement the technical solutions of the present invention, and are not exhaustive. It should be understood that other ways belonging to a general inventive concept can be used to implement the technical solutions of the present invention, and should not be limited to the embodiments described exemplary. Based on one or more embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0048] Example: Figure 1 A system block diagram of a vehicle dynamic weighing system based on time-sensitive networking technology according to an embodiment of the present invention is shown. (Refer to...) Figure 1 The vehicle dynamic weighing system based on time-sensitive networking technology in this embodiment of the invention includes:

[0049] The weighing platform is divided into a detection area and a weighing area. The detection area is equipped with a detection module that outputs a vehicle entry prompt information when a vehicle enters the detection area, and the weighing area is equipped with multiple weighing sensors.

[0050] Cameras and time-sensitive network gateways;

[0051] The computer, with each load cell and camera connected via a time-sensitive network gateway, is used for:

[0052] In response to the vehicle entry prompt, N data acquisition commands are sent to the target axle. During each data acquisition command sending action, the command is simultaneously sent to each weighing sensor and camera, enabling each weighing sensor to acquire weighing data and the camera to acquire vehicle posture images.

[0053] The system synchronously receives multiple weighing data points and vehicle attitude images corresponding to each acquisition command. Based on the multiple weighing data points, it determines the initial weight data of the target axle. Based on the vehicle attitude images, it determines weighting coefficients and performs weighted calculations on the initial weight data to obtain weighted weight data.

[0054] The weighted weight data corresponding to N acquisition command transmission actions are smoothed and filtered, and then averaged to obtain the weight data of the target axle.

[0055] The weight data of each axle is summed to obtain the dynamic weighing data of the vehicle.

[0056] Specifically, in this embodiment of the invention, during the process of a vehicle passing through the weighing zone, there is one and only one axle within the weighing zone. That is, if the vehicle has two axles, a front axle and a rear axle, then during the process of the front axle passing through the weighing zone, although the rear axle moves forward, it remains outside the weighing zone. Only when the front axle leaves the weighing zone does the rear axle begin to enter the weighing zone. This configuration allows the load detection of each axle to be isolated, thereby simplifying the entire dynamic weighing process of the vehicle.

[0057] Specifically, in this embodiment of the invention, firstly, each weighing sensor and camera is connected to a computer via a time-sensitive network gateway. Upon receiving a vehicle entry prompt, the computer's acquisition command can synchronously reach each weighing sensor and camera via the time-sensitive network gateway. This achieves synchronization of the weighing data acquisition actions of multiple load cells and the image acquisition actions of the load cells and cameras. Compared to existing vehicle dynamic weighing systems, the vehicle dynamic weighing system of this embodiment of the invention obtains axle-weighted weight data with higher accuracy based on synchronously acquired weighing data and vehicle posture images, thus resulting in correspondingly higher accuracy of the vehicle dynamic weighing data. Secondly, compared to existing vehicle dynamic weighing systems, the vehicle dynamic weighing system of this embodiment of the invention adds a smoothing and filtering process to the axle-weighted weight data to reduce the impact of vehicle impact vibration on the vehicle dynamic weighing, thereby further improving the accuracy of the acquired vehicle dynamic weighing data. Thirdly, in this embodiment of the invention, the target axle is subjected to N collection command sending actions, that is, N synchronous collection of feature data is performed, and the weighted weight data of the axle after smoothing and filtering is averaged to obtain the weight data of the target axle, thereby further improving the accuracy of the obtained vehicle dynamic weighing data.

[0058] Accordingly, based on the vehicle dynamic weighing system based on time-sensitive network technology in the embodiments of the present invention, the embodiments of the present invention also propose a vehicle dynamic weighing method based on time-sensitive network technology. This vehicle dynamic weighing method is implemented based on the vehicle dynamic weighing system based on time-sensitive network technology in the embodiments of the present invention and is applied to the computer therein.

[0059] Figure 2 A flowchart illustrating the implementation of the vehicle dynamic weighing method based on time-sensitive networking technology according to an embodiment of the present invention is shown. (Refer to...) Figure 2 The vehicle dynamic weighing method based on time-sensitive networking technology in this embodiment of the invention includes the following steps:

[0060] Step S100: In response to the vehicle entry prompt information, perform N collection command sending actions for the target axle. In each collection command sending action, the collection command is synchronously sent to each weighing sensor and the camera, so as to enable each weighing sensor to collect weighing data and enable the camera to collect vehicle posture images.

[0061] Step S200: Synchronously receive multiple weighing data and vehicle posture images corresponding to each acquisition command sending action; determine the initial weight data of the target axle based on the multiple weighing data; determine the weighting coefficient based on the vehicle posture image; and perform weighted calculation on the initial weight data to obtain weighted weight data.

[0062] Step S300: Perform smoothing filtering on the weighted weight data corresponding to the N acquisition command sending actions and take the average value to obtain the weight data of the target axle;

[0063] Step S400: Sum the weight data of each axle to obtain the dynamic weighing data of the vehicle.

[0064] Specifically, in this embodiment of the invention, N is a positive integer and 2≤N≤10.

[0065] Further, in step S100 of this embodiment of the invention, the synchronous delivery of the acquisition command to each weighing sensor and the camera includes:

[0066] The latency of each weighing sensor connected to the time-sensitive network gateway and the latency of the camera are obtained in advance;

[0067] Based on the time delay of each weighing sensor and the time delay of the camera, acquisition commands are sent to each weighing sensor and the camera through the time-sensitive network gateway.

[0068] Furthermore, in this embodiment of the invention, the step of pre-obtaining the latency of each weighing sensor connected to the time-sensitive network gateway and the latency of the camera specifically involves:

[0069] The clocks of each weighing sensor and the camera are synchronized through the time-sensitive network gateway, and test packets are sent to each weighing sensor and the camera to obtain the latency of each weighing sensor and the latency of the camera.

[0070] Furthermore, in step S200 of this embodiment of the invention, determining the weighting coefficients based on the vehicle attitude image includes:

[0071] The wheelbase of the target axle, the estimated height of the vehicle's center of gravity, and the angle between the vehicle body and the ground are determined based on the vehicle attitude image.

[0072] The weighting coefficients are determined based on the wheelbase of the target axle, the estimated height of the vehicle's center of gravity, and the angle between the vehicle body and the ground.

[0073] Furthermore, in this embodiment of the invention, the formula for determining the weighting coefficients is:

[0074]

[0075] In the above formula, m is the weighting coefficient, h is the estimated value of the vehicle's center of gravity height, l is the length of the vehicle body, and θ is the angle between the vehicle body and the ground.

[0076] Furthermore, in step S300 of this embodiment of the invention, the smoothing and filtering processing of the weighted weight data corresponding to the N acquisition command sending actions is implemented based on the Savitzky-Golay method.

[0077] Furthermore, in this embodiment of the invention, N = 5;

[0078] The Savitzky-Golay method is implemented based on the following formula:

[0079]

[0080] In the above formula, x represents the weighted weight data, and its subscript indicates the index of the weighted weight data; y represents the weighted weight data after smoothing filtering, and its subscript indicates the index of the weighted weight data after smoothing filtering; X is a quadratic matrix, X trans It is the transpose of the quadratic matrix;

[0081]

[0082] While one or more embodiments of the present invention have been described above, those skilled in the art will recognize that the present invention can be implemented in any other form without departing from its spirit and scope. Therefore, the embodiments described above are illustrative and not restrictive, and many modifications and substitutions will be apparent to those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. A method for dynamic weighing of vehicles based on Time-Sensitive Networking technology, characterized in that, The application relates to a vehicle dynamic weighing method and a vehicle dynamic weighing system. The weighing platform is divided into a detection area and a weighing area, the detection area is provided with a detection module for outputting a vehicle entering prompt information when a vehicle enters the detection area, and the weighing area is provided with a plurality of weighing sensors; a camera and a time-sensitive network gateway; a computer, each weighing sensor and the camera access the computer through the time-sensitive network gateway, and the computer is used for: in response to the vehicle entering prompt information, performing N times of acquisition instruction sending actions for a target axle, in each acquisition instruction sending action, acquisition instructions are synchronously sent to each weighing sensor and the camera, so that each weighing sensor collects weighing data and the camera collects vehicle posture images, synchronously receiving a plurality of weighing data and vehicle posture images corresponding to each acquisition instruction sending action, determining initial weight data of the target axle according to the plurality of weighing data, determining a weighting coefficient according to the vehicle posture images and performing weighted calculation on the initial weight data to obtain weighted weight data, performing smoothing filtering processing on the weighted weight data corresponding to the N times of acquisition instruction sending actions and taking an average value, so as to obtain weight data of the target axle, summing up the obtained weight data of each axle to obtain dynamic weighing data of the vehicle; the vehicle dynamic weighing method is applied to the computer and comprises the following steps: in response to the vehicle entering prompt information, performing N times of acquisition instruction sending actions for a target axle, in each acquisition instruction sending action, acquisition instructions are synchronously sent to each weighing sensor and the camera, so that each weighing sensor collects weighing data and the camera collects vehicle posture images; synchronously receiving a plurality of weighing data and vehicle posture images corresponding to each acquisition instruction sending action, determining initial weight data of the target axle according to the plurality of weighing data, determining a weighting coefficient according to the vehicle posture images and performing weighted calculation on the initial weight data to obtain weighted weight data; performing smoothing filtering processing on the weighted weight data corresponding to the N times of acquisition instruction sending actions and taking an average value, so as to obtain weight data of the target axle; summing up the obtained weight data of each axle to obtain dynamic weighing data of the vehicle; the determination of the weighting coefficient according to the vehicle posture images comprises: determining an axle distance of the target axle, a vehicle gravity center height estimation value and an angle between a vehicle body and the ground according to the vehicle posture images; determining the weighting coefficient according to the axle distance of the target axle, the vehicle gravity center height estimation value and the angle between the vehicle body and the ground; the determination formula of the weighting coefficient is as follows: in the formula, m is the weighting coefficient, h is the vehicle gravity center height estimation value, l is the length of a vehicle body rigid body, and theta is the angle between the vehicle body and the ground.

2. The vehicle dynamic weighing method based on time sensitive networking technology according to claim 1, characterized in that, the synchronous sending of the acquisition instructions to each weighing sensor and the camera comprises: pre-acquiring a time delay of each weighing sensor and a time delay of the camera accessing the time-sensitive network gateway; According to the time delay of each weighing sensor and the time delay of the camera, and by the time-sensitive network gateway, sending a collection instruction to each weighing sensor and the camera.

3. The vehicle dynamic weighing method based on time sensitive networking technology according to claim 2, characterized in that, The pre-acquired time delay of each weighing sensor and the time delay of the camera accessing the time-sensitive network gateway are specifically: Through the time-sensitive network gateway, synchronizing the clock of each weighing sensor and the camera, and sending a test packet to each weighing sensor and the camera to acquire the time delay of each weighing sensor and the time delay of the camera.

4. The vehicle dynamic weighing method based on time sensitive networking technology according to claim 1, characterized in that, The smoothing filtering processing of the weighted weight data corresponding to the N times of collection instruction sending actions is realized based on the Savitzky-Golay method.

5. The vehicle dynamic weighing method based on time sensitive networking technology according to claim 4, characterized in that, N＝5； The Savitzky-Golay method is realized based on the following formula: In the above formula, x is the weighted weight data, and the subscript thereof indicates the serial number of the weighted weight data; y is the weighted weight data after smoothing filtering processing, and the subscript thereof indicates the serial number of the weighted weight data after smoothing filtering processing; X is a quadratic matrix; X trans is the transpose matrix of the quadratic matrix; and y is the weighted weight data after smoothing filtering processing. In the above formula, x is the weighted weight data, and the subscript thereof indicates the serial number of the weighted weight data; y is the weighted weight data after smoothing filtering processing, and the subscript thereof indicates the serial number of the weighted weight data after smoothing filtering processing; X is a quadratic matrix; X trans is the transpose matrix of the quadratic matrix; and y is the weighted weight data after

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