Early warning processing method and device of electronic truck scale, terminal and medium
By using two identical weighing instruments in the electronic truck scale system for data acquisition and noise reduction, combined with camera-assisted judgment, the problem of weighing errors caused by abnormal driver operation was solved, and efficient and accurate abnormal early warning processing was achieved.
Patent Information
- Application Number
- CN202511101696.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-07
- Publication Date
- 2026-01-27
AI Technical Summary
In existing electronic truck scales, drivers may take abnormal measures during the weighing process, resulting in a weighing result that is less than the actual vehicle weight. The existing solutions rely on manual processing, which has low efficiency and accuracy.
Data is collected using two identical electronic truck scales. Through noise reduction processing and early warning assessment parameter generation, combined with camera-assisted judgment, the accuracy of abnormal early warning is improved.
It improves the accuracy of anomaly warnings, reduces the need for manual intervention, and enhances the automation and accuracy of the weighing process.
Smart Images
Figure CN121409375A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the fields of data processing and early warning processing technology, specifically to an early warning processing method, device, terminal and medium for electronic truck scales. Background Technology
[0002] With the rapid development of modern technology, intelligent and automated technologies have become the mainstream of industry development. To improve the efficiency of cargo transportation and handling, strengthen management, and standardize and intelligentize the weighing process, thereby enhancing the comprehensive management capabilities of enterprises and reducing operating costs, electronic truck scales are typically used to weigh trucks.
[0003] However, when using electronic truck scales to weigh vehicles, some drivers may take abnormal measures to reduce the vehicle's weight on the scale, resulting in a lower weighing result than the actual vehicle weight. Current solutions for handling such anomalies typically rely on manual anomaly detection and warning, leading to low efficiency and accuracy in the process. Summary of the Invention
[0004] This application provides a method, device, terminal, and medium for early warning processing of electronic truck scales, which can use two electronic truck scales to collect data and make early warning judgments, thereby improving the accuracy of abnormal early warning.
[0005] A first aspect of this application provides an early warning processing method for electronic truck scales, applied to an electronic truck scale system, the electronic truck scale system including a first electronic truck scale and a second electronic truck scale, the first electronic truck scale and the second electronic truck scale being installed sequentially, the method comprising: After the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence, the first detection parameter of the first electronic truck scale and the second detection parameter of the second electronic truck scale are obtained. Early warning assessment parameters are generated based on the first detection parameters and the second detection parameters; Early warning information is generated based on the aforementioned early warning assessment parameters; The aforementioned warning information is displayed.
[0006] In one possible implementation, generating the early warning evaluation parameters based on the first detection parameter and the second detection parameter includes: The first detection parameter is denoised to obtain the first intermediate parameter; The second detection parameter is denoised to obtain the second intermediate parameter; Early warning assessment parameters are generated based on the first intermediate parameter and the second intermediate parameter.
[0007] In one possible implementation, the step of denoising the first detection parameter to obtain the first intermediate parameter includes: Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; The first noise figure is determined based on the installation environment information and the usage environment information. The second noise figure is determined based on the usage duration; The first noise figure and the second noise figure are fused to obtain the target noise figure; The first detection parameter is denoised using the target noise coefficient to obtain the first intermediate parameter.
[0008] In one possible implementation, the step of denoising the first detection parameter using the target noise coefficient to obtain the first intermediate parameter includes: Determine the denoising parameters based on the target noise figure and correction factor; The product of the denoising parameter and the first detection parameter is determined as the first intermediate parameter.
[0009] In one possible implementation, the method further includes: Multiple images of the vehicle to be inspected as it passes through the first and second electronic truck scales in sequence are acquired to obtain a first image set. Based on the first image set, determine the driving posture information of the vehicle to be detected; If the driving posture information indicates an abnormal posture, an alarm message is generated.
[0010] A second aspect of this application provides an early warning processing device for an electronic truck scale, applied to an electronic truck scale system, the electronic truck scale system including a first electronic truck scale and a second electronic truck scale, the first electronic truck scale and the second electronic truck scale being installed sequentially, the device comprising: The acquisition unit is used to acquire the first detection parameters of the first electronic truck scale and the second detection parameters of the second electronic truck scale after the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence. The first generation unit is used to generate early warning evaluation parameters based on the first detection parameters and the second detection parameters; The second generation unit is used to generate early warning information based on the early warning assessment parameters; The display unit is used to display the warning information.
[0011] In one possible implementation, the first generation unit is specifically used for: The first detection parameter is denoised to obtain the first intermediate parameter; The second detection parameter is denoised to obtain the second intermediate parameter; Early warning assessment parameters are generated based on the first intermediate parameter and the second intermediate parameter.
[0012] In one possible implementation, regarding the denoising process of the first detection parameter to obtain the first intermediate parameter, the first generation unit is specifically used for: Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; The first noise figure is determined based on the installation environment information and the usage environment information. The second noise figure is determined based on the usage duration; The first noise figure and the second noise figure are fused to obtain the target noise figure; The first detection parameter is denoised using the target noise coefficient to obtain the first intermediate parameter.
[0013] In one possible implementation, regarding the denoising of the first detection parameter using the target noise coefficient to obtain the first intermediate parameter, the first generation unit is specifically configured to: Determine the denoising parameters based on the target noise figure and correction factor; The product of the denoising parameter and the first detection parameter is determined as the first intermediate parameter.
[0014] In one possible implementation, the device is further used for: Multiple images of the vehicle to be inspected as it passes through the first and second electronic truck scales in sequence are acquired to obtain a first image set. Based on the first image set, determine the driving posture information of the vehicle to be detected; If the driving posture information indicates an abnormal posture, an alarm message is generated.
[0015] A third aspect of this application provides a terminal including a processor, an input device, an output device, and a memory, wherein the processor, input device, output device, and memory are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to execute the step instructions as described in the first aspect of this application.
[0016] A fourth aspect of this application provides a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of this application.
[0017] A fifth aspect of this application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of this application. The computer program product may be a software installation package.
[0018] Implementing the embodiments of this application has the following beneficial effects: By acquiring the first detection parameters of the first electronic truck scale and the second detection parameters of the second electronic truck scale after the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence, generating early warning evaluation parameters based on the first detection parameters and the second detection parameters, generating early warning information based on the early warning evaluation parameters, and displaying the early warning information, the system can use two electronic truck scales to collect data and make early warning judgments, thereby improving the accuracy of issuing abnormal early warnings. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This application provides a schematic diagram of the structure of an electronic truck scale system. Figure 2 This application provides a flowchart illustrating an early warning processing method for an electronic truck scale. Figure 3 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application; Figure 4 This application provides a schematic diagram of the structure of an early warning processing device for an electronic truck scale. Detailed Implementation
[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0022] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.
[0023] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.
[0024] To better understand the early warning processing method for electronic truck scales provided in this application embodiment, a brief introduction to the electronic truck scale system applying the early warning processing method is given below. The electronic truck scale system includes a first electronic truck scale 1 and a second electronic truck scale 2, and may also include a camera 3, etc. The first electronic truck scale 1 and the second electronic truck scale 2 are installed sequentially. Specifically, the first electronic truck scale is installed before the vehicle's travel path, while the second electronic truck scale is installed after the vehicle's travel path. That is, the vehicle passes through the first electronic truck scale for inspection first, and then passes through the second electronic truck scale for inspection. The first and second electronic truck scales have the same specifications; specifically, they are manufactured by the same company, have the same model, and the same graduation value. Early warning processing can be performed based on the detection data from the first and second electronic truck scales, thereby improving the accuracy of abnormal early warning.
[0025] Since abnormal states can take many forms, cameras can be used for auxiliary early warning. Specifically, images captured by the camera can be used for initial assessment. If the initial assessment indicates a normal state, the image data can be used to correct the early warning evaluation parameters, further improving efficiency and accuracy. If the state is abnormal, the abnormal state can be directly identified, and an early warning message can be generated.
[0026] Please see Figure 2 , Figure 2 This application provides a flowchart illustrating an early warning processing method for an electronic truck scale. For example... Figure 2 As shown, an electronic truck scale system is applied, the electronic truck scale system including a first electronic truck scale and a second electronic truck scale, the first electronic truck scale and the second electronic truck scale being installed sequentially, the method including: 201. Obtain the first detection parameters of the first electronic truck scale and the second detection parameters of the second electronic truck scale after the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence.
[0027] The vehicle to be tested can be any vehicle that needs to be weighed. The vehicle can travel through the first and second electronic truck scales under the driver's operation. As it passes through the first and second electronic truck scales, data is collected by each scale, resulting in a first detection parameter for the first scale and a second detection parameter for the second scale.
[0028] Specifically, the first detection parameter can be the weight data of the vehicle to be tested, and the second detection parameter can be the weight data of the vehicle to be tested.
[0029] The first and second electronic truck scales have identical specifications. Specifically, this means they are manufactured by the same company, have the same model, and the same graduation value. This allows for mutual verification between the first and second detection parameters, preventing the possibility of a single truck scale being compromised and thus failing to issue abnormal warnings. For example, the mutual verification between the first and second detection parameters can be used to determine fluctuations. Because the first and second electronic truck scales have the same specifications, the data they collect will fall within a relatively small fluctuation range, allowing for verification based on this fluctuation range.
[0030] 202. Generate early warning assessment parameters based on the first detection parameters and the second detection parameters.
[0031] Specifically, the detection parameters may be affected by factors such as the installation environment, usage environment, and usage duration, resulting in certain errors. These errors may lead to differences in the basic conditions of the first and second electronic truck scales. Therefore, it is necessary to reduce the errors caused by such factors and further improve the accuracy of generating early warning assessment parameters. For example, the first and second detection parameters can be denoised to generate intermediate parameters, which can then be used to generate the early warning assessment parameters.
[0032] 203. Generate early warning information based on the aforementioned early warning assessment parameters.
[0033] Warning information can be generated based on the numerical range of the warning assessment parameters. Specifically, the data range of the warning assessment parameters can be extracted, and then the warning information can be determined according to the mapping relationship table between the numerical range and the warning information. Different numerical ranges have different warning information. Warning information may include, for example, that the vehicle to be inspected has an abnormal weighing and needs to be handled; or that the vehicle to be inspected has no abnormalities.
[0034] Data ranges can be preset, with each range being independent and adjacent to the others. For example, the first range might be less than a preset evaluation parameter threshold, and the second range might be greater than or equal to that threshold. For instance, in the first range, the corresponding warning message would be that the vehicle under inspection has no abnormalities; in the second range, the corresponding warning message would be that the vehicle under inspection has a weighing abnormality and requires intervention.
[0035] 204. Display the aforementioned warning information.
[0036] The warning information can be displayed using common information display methods, such as displaying the warning information on a screen or through voice broadcast.
[0037] In this example, by acquiring the first detection parameter of the first electronic truck scale and the second detection parameter of the second electronic truck scale after the vehicle to be detected passes through the first electronic truck scale and the second electronic truck scale in sequence, a warning evaluation parameter is generated based on the first detection parameter and the second detection parameter, and a warning information is generated and displayed based on the warning evaluation parameter. This method can use two electronic truck scales to collect data and make warning judgments, which improves the accuracy of issuing abnormal warnings.
[0038] In one possible implementation, a method for generating early warning assessment parameters based on the first detection parameter and the second detection parameter includes: A1. Denoise the first detection parameter to obtain the first intermediate parameter; A2. Denoise the second detection parameter to obtain the second intermediate parameter; A3. Generate early warning assessment parameters based on the first intermediate parameter and the second intermediate parameter.
[0039] This process may involve acquiring the installation environment information, usage environment information, and usage duration information of the first electronic vehicle scale, determining the target noise figure using the installation environment information, usage environment information, and usage duration information, and finally using the target noise figure to denoise the first detection parameter to obtain the first intermediate parameter.
[0040] Similarly, when denoising the second detection parameter, the installation environment information, usage environment information, and usage duration information of the second vehicle electronic scale can be obtained. The corresponding noise figure can be determined through the installation environment information, usage environment information, and usage duration information. Finally, the corresponding noise figure can be used to denoise the second detection parameter to obtain the second intermediate parameter.
[0041] The offset between the first and second intermediate parameters can be calculated and used as the early warning assessment parameter. The offset can be the absolute value of the difference between the first and second intermediate parameters.
[0042] After noise reduction, even if the weight values of the same vehicle weighed on two identical electronic scales are different, they will be within a very small error range. Therefore, the offset can be used to determine whether there is an abnormality, thereby improving the accuracy of anomaly detection.
[0043] In one possible implementation, a method for denoising the first detection parameter to obtain a first intermediate parameter includes: B1. Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; B2. Determine the first noise figure based on the installation environment information and the usage environment information; B3. Determine the second noise figure based on the usage duration; B4. Combine the first noise figure and the second noise figure to obtain the target noise figure; B5. The first detection parameter is denoised using the target noise coefficient to obtain the first intermediate parameter.
[0044] Specifically, the installation environment information, usage environment information, and usage duration information of the first electronic truck scale can be obtained from a database. The database stores this information. The installation environment information includes the flatness of the installation and the foundation information. Since electronic truck scales typically weigh large, heavy-duty trucks, the flatness of the installation and the stability of the foundation are extremely important. Uneven installation (a tilt angle) can lead to significant weighing errors. Furthermore, weighing large, heavy-duty trucks involves immense pressure; even slight shifts in the foundation over time can affect weighing accuracy.
[0045] The first noise figure can then be determined based on the installation and usage environment information. Specifically, the flatness and foundation information can be extracted from the installation environment information. If the flatness information indicates the existence of an installation slope (which may be very small), the first sub-noise figure can be generated based on the installation slope. The higher the slope, the larger the first sub-noise figure; the smaller the slope, the smaller the first sub-noise figure. The foundation information indicates the stability during subsequent use. Different foundation information has different levels of stability, so the stability corresponding to the foundation information can be determined based on this mapping relationship. The higher the stability, the smaller the second sub-noise figure; the lower the stability, the larger the second sub-noise figure. The first and second sub-noise figures are then added together to obtain the first noise figure.
[0046] As electronic truck scales age with use, the longer they are used, the higher the second noise figure becomes, and the shorter the usage time, the lower the second noise figure becomes.
[0047] The noise figure determined above can be used to denoise the first detection parameter. Denoising can be understood as standardizing it so that the processed first detection parameter and the second detection parameter are at the same error level for comparison, thereby improving accuracy.
[0048] The target noise figure can be determined by summing the first noise figure and the second noise figure. Alternatively, a weighted calculation can be performed to obtain the target noise figure. The first intermediate parameter can be determined by multiplying the target noise figure by the first detection parameter. For example, the target noise figure can be a percentage coefficient. Finally, the target noise figure is multiplied by the first detection parameter to obtain the first intermediate parameter, thereby achieving denoising of the first detection parameter and improving the accuracy of subsequent processing.
[0049] Alternatively, the denoising parameters can be determined based on the target noise figure and the correction factor, and the product of the denoising parameters and the first detection parameter can be used to determine the first intermediate parameter.
[0050] In one possible implementation, a method for denoising the first detection parameter using the target noise coefficient to obtain a first intermediate parameter includes: C1. Determine the denoising parameters based on the target noise figure and correction factor; C2. The product of the denoising parameter and the first detection parameter is determined as the first intermediate parameter.
[0051] The correction factor is related to the type of electronic truck scale, and different types of electronic truck scales have different correction factors, which can be preset. The product of the target noise figure and the correction factor can be used to determine the denoising parameter.
[0052] In one possible implementation, a preliminary judgment can be performed before generating the warning information to filter out some obvious abnormal states. The method also includes: D1. Obtain multiple images of the vehicle to be inspected as it passes through the first and second electronic truck scales in sequence to obtain the first image set. D2. Determine the driving posture information of the vehicle to be detected based on the first image set; D3. If the driving posture information indicates an abnormal posture, an alarm message is generated. This process involves using a camera to capture multiple images of the vehicle being inspected as it sequentially passes through the first and second electronic truck scales, creating a first image set. A general image processing method can then be used to extract the vehicle's driving posture information from this first image set. This driving posture information indicates the vehicle's driving state as it passes through the first and second electronic truck scales; for example, it may include a normal passage state or a state where some wheels are suspended in the air.
[0053] If a state other than the normal passage state is identified as an abnormal posture, an alarm message will be generated.
[0054] If the driving posture information indicates a normal posture, then subsequent warning evaluation parameters will be generated and subsequent evaluations will be performed.
[0055] In this example, a preliminary judgment can be made to identify obvious abnormal states, and then warning information for the detection parameters can be generated to identify more subtle abnormal states, thus improving accuracy.
[0056] One specific implementation provides another early warning method for electronic truck scales, as follows: Two electronic truck scales, manufactured by the same company, of the same model, and with the same graduation value, are installed side-by-side. The same truck passes through both scales one after the other, and the weighing data is compared. The two weighing data are automatically compared in the software system. The system can be set to trigger an alarm if the weighing data exceeds one (or two) graduation values, indicating a problem. This is because, regardless of current cheating methods, it is impossible to simultaneously control the weighing of two electronic truck scales, nor can the weighing cheating on the two scales be synchronized; some discrepancies will inevitably exist.
[0057] This application provides another early warning processing method for electronic truck scales. The early warning processing method for electronic truck scales is applied to an electronic truck scale system, which includes a first electronic truck scale and a second electronic truck scale, which are installed sequentially. The method includes: 301. Obtain the first detection parameters of the first electronic truck scale and the second detection parameters of the second electronic truck scale after the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence. 302. Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; 303. Determine the first noise figure based on the installation environment information and the usage environment information; 304. Determine the second noise figure based on the stated usage duration; 305. The first noise figure and the second noise figure are fused to obtain the target noise figure; 306. The first detection parameter is denoised using the target noise figure to obtain the first intermediate parameter; 307. The second detection parameter is denoised to obtain the second intermediate parameter; 308. Generate early warning assessment parameters based on the first intermediate parameter and the second intermediate parameter; 309. Generate early warning information based on the aforementioned early warning assessment parameters; 310. Display the aforementioned warning information.
[0058] The specific implementation of steps 301-310 can refer to the implementation of the corresponding steps in the foregoing embodiments.
[0059] Therefore, after noise reduction, even if the weight values of the same vehicle weighed on two identical electronic scales are different, they will be within a very small error range. Thus, the offset can be used to determine whether there is an abnormality, thereby improving the accuracy of anomaly detection.
[0060] For examples consistent with the above embodiments, please refer to... Figure 3 , Figure 3 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application, such as... Figure 3 As shown, it includes a processor, an input device, an output device, and a memory, which are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions. The program includes instructions for performing the following steps. After the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence, the first detection parameter of the first electronic truck scale and the second detection parameter of the second electronic truck scale are obtained. Early warning assessment parameters are generated based on the first detection parameters and the second detection parameters; Early warning information is generated based on the aforementioned early warning assessment parameters; The aforementioned warning information is displayed.
[0061] In this example, by acquiring the first detection parameter of the first electronic truck scale and the second detection parameter of the second electronic truck scale after the vehicle to be detected passes through the first electronic truck scale and the second electronic truck scale in sequence, a warning evaluation parameter is generated based on the first detection parameter and the second detection parameter, and a warning information is generated and displayed based on the warning evaluation parameter. This method can use two electronic truck scales to collect data and make warning judgments, which improves the accuracy of issuing abnormal warnings.
[0062] The above mainly describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the terminal includes the corresponding hardware structure and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0063] This application embodiment can divide the terminal into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.
[0064] For those consistent with the above, please refer to Figure 4 , Figure 4 This application provides a schematic diagram of the structure of an early warning processing device for an electronic truck scale. For example... Figure 4 As shown, this device is applied to an electronic truck scale system, which includes a first electronic truck scale and a second electronic truck scale, which are installed sequentially. The device includes: The acquisition unit 401 is used to acquire the first detection parameters of the first electronic truck scale and the second detection parameters of the second electronic truck scale after the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence. The first generation unit 402 is used to generate early warning evaluation parameters based on the first detection parameters and the second detection parameters; The second generation unit 403 is used to generate early warning information based on the early warning evaluation parameters; Display unit 404 is used to display the warning information.
[0065] In this example, by acquiring the first detection parameter of the first electronic truck scale and the second detection parameter of the second electronic truck scale after the vehicle to be detected passes through the first electronic truck scale and the second electronic truck scale in sequence, a warning evaluation parameter is generated based on the first detection parameter and the second detection parameter, and a warning information is generated and displayed based on the warning evaluation parameter. This method can use two electronic truck scales to collect data and make warning judgments, which improves the accuracy of issuing abnormal warnings.
[0066] In one possible implementation, the first generation unit 402 is specifically used for: The first detection parameter is denoised to obtain the first intermediate parameter; The second detection parameter is denoised to obtain the second intermediate parameter; Early warning assessment parameters are generated based on the first intermediate parameter and the second intermediate parameter.
[0067] In one possible implementation, regarding the denoising process of the first detection parameter to obtain the first intermediate parameter, the first generation unit 402 is specifically configured to: Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; The first noise figure is determined based on the installation environment information and the usage environment information. The second noise figure is determined based on the usage duration; The first noise figure and the second noise figure are fused to obtain the target noise figure; The first detection parameter is denoised using the target noise coefficient to obtain the first intermediate parameter.
[0068] In one possible implementation, regarding the denoising of the first detection parameter using the target noise coefficient to obtain the first intermediate parameter, the first generation unit 402 is specifically configured to: Determine the denoising parameters based on the target noise figure and correction factor; The product of the denoising parameter and the first detection parameter is determined as the first intermediate parameter.
[0069] In one possible implementation, the device is further used for: Multiple images of the vehicle to be inspected as it passes through the first and second electronic truck scales in sequence are acquired to obtain a first image set. Based on the first image set, determine the driving posture information of the vehicle to be detected; If the driving posture information indicates an abnormal posture, an alarm message is generated; If the driving posture information indicates a normal posture, then the correction information for the warning evaluation parameters is determined based on the driving posture information; The correction information is used to correct the early warning assessment parameters to obtain the corrected early warning assessment parameters.
[0070] This application also provides a computer storage medium storing a computer program for electronic data exchange, which causes a computer to perform some or all of the steps of any of the early warning processing methods for electronic truck scales described in the above method embodiments.
[0071] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps of any of the electronic truck scale early warning processing methods described in the above method embodiments.
[0072] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
[0073] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.
[0074] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.
[0075] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0076] Furthermore, the functional units in the various embodiments of the application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.
[0077] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.
[0078] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk, etc.
[0079] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for early warning processing of electronic truck scales, characterized in that, The method, applied to an electronic truck scale system, comprising a first electronic truck scale and a second electronic truck scale, wherein the first and second electronic truck scales are installed sequentially, includes: After the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence, the first detection parameter of the first electronic truck scale and the second detection parameter of the second electronic truck scale are obtained. Early warning assessment parameters are generated based on the first detection parameters and the second detection parameters; Early warning information is generated based on the aforementioned early warning assessment parameters; The aforementioned warning information is displayed.
2. The early warning processing method for electronic truck scales according to claim 1, characterized in that, The step of generating early warning assessment parameters based on the first detection parameter and the second detection parameter includes: The first detection parameter is denoised to obtain the first intermediate parameter; The second detection parameter is denoised to obtain the second intermediate parameter; Early warning assessment parameters are generated based on the first intermediate parameter and the second intermediate parameter.
3. The early warning processing method for electronic truck scales according to claim 2, characterized in that, The step of denoising the first detection parameter to obtain the first intermediate parameter includes: Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; The first noise figure is determined based on the installation environment information and the usage environment information. The second noise figure is determined based on the usage duration; The first noise figure and the second noise figure are fused to obtain the target noise figure; The first detection parameter is denoised using the target noise coefficient to obtain the first intermediate parameter.
4. The early warning processing method for electronic truck scales according to claim 3, characterized in that, The step of denoising the first detection parameter using the target noise coefficient to obtain the first intermediate parameter includes: Determine the denoising parameters based on the target noise figure and correction factor; The product of the denoising parameter and the first detection parameter is determined as the first intermediate parameter.
5. The early warning processing method for electronic truck scales according to claim 4, characterized in that, The method further includes: Multiple images of the vehicle to be inspected as it passes through the first and second electronic truck scales in sequence are acquired to obtain a first image set. Based on the first image set, determine the driving posture information of the vehicle to be detected; If the driving posture information indicates an abnormal posture, an alarm message is generated.
6. An early warning processing device for an electronic truck scale, characterized in that, The device is applied to an electronic truck scale system, the electronic truck scale system including a first electronic truck scale and a second electronic truck scale, the first electronic truck scale and the second electronic truck scale being installed sequentially, the device comprising: The acquisition unit is used to acquire the first detection parameters of the first electronic truck scale and the second detection parameters of the second electronic truck scale after the vehicle to be inspected passes through the first electronic truck scale and the second electronic truck scale in sequence. The first generation unit is used to generate early warning evaluation parameters based on the first detection parameters and the second detection parameters; The second generation unit is used to generate early warning information based on the early warning assessment parameters; The display unit is used to display the warning information.
7. The early warning processing device for electronic truck scales according to claim 6, characterized in that, The first generation unit is specifically used for: The first detection parameter is denoised to obtain the first intermediate parameter; The second detection parameter is denoised to obtain the second intermediate parameter; Early warning assessment parameters are generated based on the first intermediate parameter and the second intermediate parameter.
8. The early warning processing device for electronic truck scales according to claim 7, characterized in that, In the process of denoising the first detection parameter to obtain the first intermediate parameter, the first generation unit is specifically used for: Obtain the installation environment information, usage environment information, and usage duration information of the first electronic truck scale; The first noise figure is determined based on the installation environment information and the usage environment information. The second noise figure is determined based on the usage duration; The first noise figure and the second noise figure are fused to obtain the target noise figure; The first detection parameter is denoised using the target noise coefficient to obtain the first intermediate parameter.
9. A terminal, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the early warning processing method for an electronic truck scale as described in any one of claims 1-5.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the early warning processing method for the electronic truck scale as described in any one of claims 1-5.