Safety warning method and related device for over-limit transportation

Abstract

The present application provides a safety warning method and related device for overloaded transportation, the method comprising: obtaining a target image of a target vehicle, analyzing it, obtaining vehicle model information and vehicle body status; determining initial sensitivity and initial filter cutoff frequency; determining a first adjustment factor according to vehicle model information; adjusting the initial sensitivity according to the first adjustment factor to obtain target sensitivity; obtaining a target metering signal of the target vehicle; determining a second adjustment factor according to vehicle speed information; adjusting the initial filter cutoff frequency according to the second adjustment factor to obtain target filter cutoff frequency; processing the target metering signal according to the target sensitivity and target filter cutoff frequency to obtain a target metering value; if the target metering value is greater than a safety warning threshold, obtaining a target difference between the target metering value and the safety warning threshold, and generating a warning prompt message. The accuracy of safety warning for overloaded transportation can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of safety warning, and in particular to a safety warning method and related device for over-limit transportation. Background Art

[0002] In the existing overload transport management, in order to ensure the safety of highway bridges and smooth transportation, it is usually necessary to collect vehicle measurement signals to determine whether the vehicle weight exceeds the specified load limit standard and generate early warning information. However, traditional technical solutions usually only rely on fixed scales, which sense the pressure exerted by the vehicle when it passes through through pressure sensors to determine whether the vehicle is overloaded and issue an alarm. It has certain limitations in handling safety warnings for overload transport and cannot adapt to the actual conditions of different vehicles, resulting in low accuracy of early warnings and easy false alarms or missed reports.

[0003] Therefore, how to improve the accuracy of safety warnings for oversized transportation needs to be solved urgently. Summary of the invention

[0004] The embodiment of the present application provides a safety warning method and related devices for overloaded transportation, which can improve the accuracy of safety warnings for overloaded transportation by adjusting the sensitivity and filter cutoff frequency of high-speed dynamic intelligent metering instruments in real time during vehicle transportation to adapt to different vehicle models and speeds.

[0005] In a first aspect, an embodiment of the present application provides a safety warning method for overloaded transportation, which is applied to a controller of an intelligent warning system, wherein the intelligent warning system includes the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform, wherein the weighing platform is communicatively connected to the high-speed dynamic intelligent metering instrument, the weighing platform is installed below a target lane, and the weighing platform is deployed with a metering module and a ground sensing coil, wherein the method includes:

[0006] When the target vehicle is traveling in the target lane, a target image of the target vehicle is acquired through the image recognition module;

[0007] Analyze the target image to obtain the model information of the target vehicle and the body state of the target vehicle;

[0008] Determining the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent metering instrument;

[0009] determining a first adjustment factor according to the vehicle type information;

[0010] Adjusting the initial sensitivity according to the first adjustment factor to obtain a target sensitivity;

[0011] When the vehicle body state is that the vehicle body of the target vehicle is completely on the weighing platform, a target metering signal of the target vehicle is obtained through the metering module; the target metering signal is an analog signal;

[0012] Determining the speed information of the target vehicle by using the ground sensing coil;

[0013] determining a second adjustment factor according to the vehicle speed information;

[0014] The initial filter cutoff frequency is adjusted according to the second adjustment factor to obtain a target filter cutoff frequency;

[0015] The target metering signal is processed by the high-speed dynamic intelligent metering instrument according to the target sensitivity and the target filter cutoff frequency to obtain a target metering value;

[0016] If the target measurement value is greater than a preset safety warning threshold, a target difference between the target measurement value and the safety warning threshold is obtained, and warning prompt information is generated according to the target difference.

[0017] In the second aspect, the embodiment of the present application provides a safety warning device for overloaded transportation, which is applied to a controller of an intelligent warning system, wherein the intelligent warning system includes the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform, wherein the weighing platform is communicatively connected to the high-speed dynamic intelligent metering instrument, and the weighing platform is installed below the target lane, and the weighing platform is deployed with a metering module and a ground sensing coil, and the device includes an acquisition module, an analysis module, a determination module, an adjustment module, a processing module, and a warning module, wherein:

[0018] The acquisition module is used to acquire a target image of the target vehicle through the image recognition module when the target vehicle is traveling in the target lane;

[0019] The analysis module is used to analyze the target image to obtain the vehicle model information and the body state of the target vehicle;

[0020] The determination module is used to determine the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent metering instrument;

[0021] The determination module is further used to determine a first adjustment factor according to the vehicle model information;

[0022] The adjustment module is used to adjust the initial sensitivity according to the first adjustment factor to obtain a target sensitivity;

[0023] The acquisition module is further used to acquire a target measurement signal of the target vehicle through the measurement module when the vehicle body state is that the vehicle body of the target vehicle is entirely on the scale platform; the target measurement signal is an analog signal;

[0024] The determination module is further used to determine the speed information of the target vehicle through the ground sensing coil;

[0025] The determination module is further used to determine a second adjustment factor according to the vehicle speed information;

[0026] The adjustment module is further used to adjust the initial filter cutoff frequency according to the second adjustment factor to obtain a target filter cutoff frequency;

[0027] The processing module is used to process the target metering signal according to the target sensitivity and the target filter cutoff frequency through the high-speed dynamic intelligent metering instrument to obtain a target metering value;

[0028] The early warning module is used to obtain a target difference between the target measurement value and the safety warning threshold if the target measurement value is greater than a preset safety warning threshold, and generate early warning prompt information according to the target difference.

[0029] In a third aspect, an embodiment of the present application provides a controller for an intelligent early warning system, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps of any method in the first aspect of the embodiment of the present application.

[0030] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0031] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0032] By implementing the embodiments of the present application, the sensitivity and filter cutoff frequency of the high-speed dynamic intelligent metering instrument can be adjusted in real time during vehicle transportation to adapt to different vehicle models and speeds, thereby improving the accuracy of safety warnings for overload transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 This is a system architecture diagram of an intelligent early warning system provided by an embodiment of the present application;

[0035] Figure 2 It is a structural schematic diagram of a controller of an intelligent early warning system provided in an embodiment of the present application;

[0036] Figure 3 It is a flowchart of a safety warning method for over-limit transportation provided by an embodiment of the present application;

[0037] Figure 4 This is a functional module composition block diagram of a safety warning device for over-limit transportation provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0040] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article indicates that the associated objects before and after are in an "or" relationship. The "plurality" appearing in the embodiments of the present application refers to two or more.

[0041] In the embodiments of the present application, "at least one item" or similar expressions refer to any combination of these items, including any combination of single items or plural items, and refer to one or more, and multiple refers to two or more. For example, at least one item of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0042] The "connection" that appears in the embodiments of the present application refers to various connection methods such as direct connection or indirect connection to achieve communication between devices, and the embodiments of the present application do not impose any limitations on this.

[0043] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0044] The following is an explanation of the relevant terms involved in this application, as follows:

[0045] High-speed dynamic intelligent metering instrument: refers to an advanced vehicle metering device that can accurately measure and collect data on high-speed moving vehicles in a short period of time, such as vehicle weight, speed, location, etc. This high-speed dynamic intelligent metering instrument can be used in multiple fields such as traffic monitoring, overload detection, toll collection system, etc., providing important data support for vehicle management and traffic planning.

[0046] Ground sensor coil: used to detect the speed of a vehicle passing by. Based on the principle of electromagnetic induction, the ground sensor coil is usually composed of a thin and long wire, which can be buried on the road surface or under the scale. When a vehicle passes over the ground sensor coil, the metal parts carried by the vehicle will cause the magnetic field around the ground sensor coil to change, and the speed of the vehicle passing by is calculated based on the change and the time interval.

[0047] In the existing overload transportation management, in order to ensure the safety of highway bridges and smooth transportation, it is usually necessary to collect metering signals from vehicles to determine whether the weight of the vehicle exceeds the prescribed load limit standard and generate early warning information. However, traditional technical solutions usually only rely on fixed scales, which sense the pressure exerted by the vehicle when it passes through pressure sensors to determine whether the vehicle is overloaded and issue an alarm. It has certain limitations in handling safety warnings for overload transportation and cannot adapt to the actual conditions of different vehicles, resulting in low accuracy of warnings and easy false alarms or missed reports. Therefore, how to improve the accuracy of safety warnings for overload transportation needs to be solved urgently.

[0048] To solve the above problems, an embodiment of the present application provides a safety warning method and related devices for overloaded transportation, which are applied to a controller of an intelligent warning system. The intelligent warning system includes the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform. The weighing platform is communicatively connected to the high-speed dynamic intelligent metering instrument, and the weighing platform is installed under the target lane. The weighing platform is deployed with a metering module and a ground sensing coil. When the target vehicle is traveling in the target lane, the target image of the target vehicle is obtained through the image recognition module; the target image is analyzed to obtain the vehicle model information and the body state of the target vehicle; the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent metering instrument are determined; the first adjustment factor is determined according to the vehicle model information; the initial sensitivity is adjusted according to the first adjustment factor to obtain the target sensitivity; when the body state is that the body of the target vehicle is completely on the scale, the target metering signal of the target vehicle is obtained through the metering module; the target metering signal is an analog signal; the speed information of the target vehicle is determined through the ground sensing coil; the second adjustment factor is determined according to the speed information; the initial filter cutoff frequency is adjusted according to the second adjustment factor to obtain the target filter cutoff frequency; the target metering signal is processed by the high-speed dynamic intelligent metering instrument according to the target sensitivity and the target filter cutoff frequency to obtain the target metering value. Therefore, during the vehicle transportation process, the sensitivity and filter cutoff frequency of the high-speed dynamic intelligent metering instrument can be adjusted in real time to adapt to different vehicle models and speeds, thereby improving the accuracy of safety warnings for overload transportation.

[0049] Combine the following Figure 1 A system structure for executing a safety warning method for over-limit transportation in an embodiment of the present application is described. Figure 1This is a system architecture diagram of an intelligent early warning system provided in an embodiment of the present application. The intelligent early warning system includes a controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform. The weighing platform is communicatively connected to the high-speed dynamic intelligent metering instrument, the weighing platform is installed under the target lane, and the weighing platform is deployed with a metering module and a ground sensing coil.

[0050] Among them, the controller is used to coordinate and control the intelligent early warning system, process the metering data from the scale and perform real-time analysis. The image recognition module can obtain the image of the target vehicle through the camera and identify the image to obtain the vehicle model information and body status. The high-speed dynamic intelligent metering instrument is used to process the metering signal obtained from the scale to ensure high-precision detection results under different conditions. The scale is installed under the target lane and is equipped with a metering module and a ground sensor coil. The metering module includes multiple metering sensors for obtaining the target metering signal of the target vehicle, while the ground sensor coil is used to detect the driving speed of the target vehicle.

[0051] Among them, the target lanes include but are not limited to expressways, provincial roads, and national roads; the target vehicles include but are not limited to trucks, buses, heavy trucks, and trailers, and no specific limitations are made here.

[0052] In one possible embodiment, when the target vehicle is traveling in the target lane and the distance from the weighing platform is less than a preset distance threshold, the image information of the target vehicle is obtained through the image recognition module, and then the vehicle model information of the target vehicle, such as the number of axles, tire specifications, vehicle length, etc., is analyzed based on the image information. Next, the speed information of the target vehicle, such as the driving speed, acceleration, etc., is calculated through the ground sensing coil. Then, the controller adjusts the sensitivity and filter cutoff frequency of the high-speed dynamic intelligent metering instrument according to the vehicle model information and the speed information. When the target vehicle is completely on the weighing platform, the metering module obtains the target metering signal of the target vehicle through its built-in metering sensor, and sends the target metering signal to the high-speed dynamic intelligent metering instrument for processing. Then, the high-speed dynamic intelligent metering instrument processes the target metering signal according to the adjusted sensitivity and filter cutoff frequency, and outputs an accurate metering value. Finally, it is determined whether the metering value is greater than the preset safety warning threshold. If the metering value is greater than the safety warning threshold, the target difference between the metering value and the safety warning threshold is calculated, and the corresponding warning prompt information is generated according to the target difference.

[0053] It can be seen that through the above system architecture, the sensitivity and filter cutoff frequency of the high-speed dynamic intelligent metering instrument can be adjusted in real time during vehicle transportation to adapt to different vehicle models and speeds, thereby improving the accuracy of safety warnings for overload transportation.

[0054] Combine the following Figure 2The controller of the intelligent early warning system in the embodiment of the present application is described. Figure 2 is a schematic diagram of the structure of a controller of an intelligent early warning system provided in an embodiment of the present application, such as Figure 2 As shown, the controller of the intelligent early warning system includes one or more processors, a memory, a communication interface and one or more programs. The processor is communicatively connected with the memory and the communication interface via an internal communication bus.

[0055] Among them, the processor is mainly used for:

[0056] When the target vehicle is traveling in the target lane, a target image of the target vehicle is acquired through the image recognition module;

[0057] Analyze the target image to obtain the model information and body status of the target vehicle;

[0058] Determine the initial sensitivity and initial filter cutoff frequency of high-speed dynamic intelligent metering instruments;

[0059] determining a first adjustment factor according to the vehicle model information;

[0060] The initial sensitivity is adjusted according to the first adjustment factor to obtain the target sensitivity;

[0061] When the vehicle body state is that the entire body of the target vehicle is on the scale, a target metering signal of the target vehicle is obtained through the metering module; the target metering signal is an analog signal;

[0062] Determine the speed information of the target vehicle through the ground sensing coil;

[0063] determining a second adjustment factor according to the vehicle speed information;

[0064] The initial filter cutoff frequency is adjusted according to the second adjustment factor to obtain a target filter cutoff frequency;

[0065] The target metering signal is processed by a high-speed dynamic intelligent metering instrument according to the target sensitivity and the target filter cutoff frequency to obtain the target metering value;

[0066] If the target measurement value is greater than the preset safety warning threshold, the target difference between the target measurement value and the safety warning threshold is obtained, and a warning prompt message is generated according to the target difference.

[0067] The one or more programs are stored in the above-mentioned memory and are configured to be executed by the above-mentioned processor, and the one or more programs include instructions for executing any step in the above-mentioned method embodiment.

[0068] Among them, the processor can be, for example, a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, units and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of DSP and microprocessors, and the like. The communication unit can be a communication interface, a transceiver, a transceiver circuit, and the like, and the storage unit can be a memory.

[0069] The memory may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM).

[0070] It is understandable that the controller of the intelligent early warning system may include more or fewer structural elements than those in the above structural block diagram, for example, including a power module, physical buttons, Wi-Fi module, speaker, Bluetooth module, sensor, display module, etc., which are not limited here. It is understandable that the controller of the intelligent early warning system may be equipped with Figure 1 The system architecture described.

[0071] After understanding the software and hardware architecture of this application, Figure 3 A safety warning method for overloaded transportation in an embodiment of the present application is described. Figure 3 It is a flow chart of a safety warning method for overloaded transportation provided by an embodiment of the present application, which is applied to a controller of an intelligent warning system, wherein the intelligent warning system comprises the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform, wherein the weighing platform is communicatively connected with the high-speed dynamic intelligent metering instrument, the weighing platform is installed below the target lane, and the weighing platform is deployed with a metering module and a ground sensing coil, and specifically comprises the following steps:

[0072] Step S301, when the target vehicle is traveling in the target lane, the target image of the target vehicle is acquired through the image recognition module.

[0073] Specifically, when the target vehicle is traveling in the target lane and the distance between the target vehicle and the weighing platform is less than a preset distance threshold, the target image of the target vehicle is acquired through the image recognition module. The distance threshold can be set according to the recognizable range of the image recognition module to ensure that a clear target image is captured when the target vehicle approaches the weighing platform.

[0074] Step S302: Analyze the target image to obtain the vehicle model information and the body state of the target vehicle.

[0075] Specifically, the target image can be first subjected to denoising, enhancement and correction to improve its image quality, so as to facilitate subsequent recognition and analysis of the target image. Then, the target image can be analyzed through a deep learning model or feature extraction algorithm to identify the model information of the target vehicle and the body state of the target vehicle. The model information includes but is not limited to the number of axles, tire specifications, body length, and vehicle type, and the body state includes but is not limited to the body not being on the scale, the body being partially on the scale, and the body being completely on the scale, which are not specifically limited here.

[0076] Step S303: determining the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent metering instrument.

[0077] Wherein, the intelligent early warning system further includes an audio collector, and the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent meter are determined, and the specific steps include:

[0078] The original audio signal of the target vehicle is obtained through the audio collector; the original audio signal is preprocessed to obtain a reference audio signal; the reference audio signal is feature extracted to obtain a reference audio feature; the reference audio feature is compared with a preset sample feature set to determine a reference vehicle state corresponding to the reference audio feature in the sample feature set; the reference vehicle state includes any one of the following: light load state, medium load state, heavy load state; according to a mapping relationship between a preset vehicle state and working parameters, the initial working parameters of the high-speed dynamic intelligent metering instrument corresponding to the reference vehicle state are determined; the initial working parameters include the initial sensitivity and the initial filter cutoff frequency.

[0079] Specifically, the original audio signal of the target vehicle is collected by an audio collector, and then the original audio signal is preprocessed to obtain a clearer reference audio signal. Among them, the preprocessing includes steps such as denoising and signal enhancement, which are used to improve the quality of the original audio signal and make its feature extraction more accurate. Then, the reference audio signal is feature extracted to obtain the reference audio feature. The reference audio feature is compared with the preset sample feature set to determine the reference vehicle state corresponding to the reference audio feature in the sample feature set, and the reference vehicle state includes any one of the following: light load state, medium load state, and heavy load state. Among them, the sample feature set includes sample audio features under different vehicle states, and the reference vehicle state of the target vehicle can be determined based on the comparison of the sample audio features with the reference audio features. According to the mapping relationship between the preset vehicle state and the working parameters, the initial working parameters of the high-speed dynamic intelligent metering instrument corresponding to the reference vehicle state are determined, and the initial working parameters include the initial sensitivity and the initial filter cutoff frequency.

[0080] It should be noted that the corresponding initial sensitivity can be pre-set according to different load states. For example, a light load state may require a lower sensitivity to avoid over-response, while a heavy load state may require a higher sensitivity to capture a stronger signal. Different load states will also affect the frequency characteristics of the signal, so set a suitable filter cutoff frequency to effectively filter noise and ensure signal clarity. For example, a heavy load state may require a higher cutoff frequency to capture more high-frequency components.

[0081] It can be seen that by detecting the vehicle's on-board state and determining the corresponding initial working parameters according to different on-board states, the accuracy of capturing signal changes can be improved.

[0082] Step S304: determining a first adjustment factor according to the vehicle type information.

[0083] The step of determining the first adjustment factor according to the vehicle model information specifically includes:

[0084] The vehicle model information is analyzed according to a preset vehicle model database to determine key information in the vehicle model information; the key information includes at least one of the following: a target number of axles and a target tire specification; when the key information is the target number of axles and the target tire specification, a first weight corresponding to the target number of axles and a second weight corresponding to the target tire specification are determined; based on a preset mapping relationship between the number of axles and the adjustment factor, an initial first adjustment factor corresponding to the target number of axles is determined; the more axles there are, the larger the adjustment factor is; based on a preset mapping relationship between the tire specification and the adjustment factor, an initial second adjustment factor corresponding to the target tire specification is determined; the larger the tire specification is, the larger the adjustment factor is; a weighted sum is taken of the initial first adjustment factor and the first weight, and the initial second adjustment factor and the second weight to obtain the first adjustment factor.

[0085] Specifically, the key information in the vehicle model information that affects the first adjustment factor can be determined by querying and analyzing according to the preset vehicle model database, such as the number of axles and tire specifications, which are not specifically limited here. When the key information of the target vehicle is the target number of axles and the target tire specifications, the first weight corresponding to the target number of axles and the second weight corresponding to the target tire specifications are determined. Among them, the number of axles and the tire specifications will affect the load-bearing capacity of the target vehicle, and the influence of the number of axles is greater than that of the tire specifications. The first weight and the second weight can be set to 0.7 and 0.3 respectively, which are not specifically limited here. According to the mapping relationship between the preset number of axles and the adjustment factor, the initial first adjustment factor corresponding to the target number of axles is determined; the more the number of axles, the larger the adjustment factor. According to the mapping relationship between the preset tire specifications and the adjustment factor, the initial second adjustment factor corresponding to the target tire specifications is determined; the larger the tire specifications, the larger the adjustment factor. Finally, the initial first adjustment factor and the first weight are multiplied to obtain the first product, the initial second adjustment factor and the second weight are multiplied to obtain the second product, and the first product and the second product are added to obtain the first adjustment factor. The first adjustment factor is used to adjust the sensitivity of the high-speed dynamic intelligent metering instrument.

[0086] It can be seen that adjusting the first adjustment factor according to the number of axles and tire specifications of the vehicle to obtain the first adjustment factor corresponding to the vehicle can improve the accuracy and effectiveness of subsequent processing of the metering signal, thereby ensuring the reliability and accuracy of the safety warning for transport overload.

[0087] Step S305: adjusting the initial sensitivity according to the first adjustment factor to obtain a target sensitivity.

[0088] Specifically, the target sensitivity may be obtained by multiplying the initial sensitivity by the first adjustment factor, wherein the first adjustment factor may be in the range of 0-2, which is not specifically limited herein.

[0089] Step S306: when the vehicle body state is that the entire body of the target vehicle is on the weighing platform, a target metering signal of the target vehicle is obtained through the metering module.

[0090] Wherein, the target metering signal is an analog signal.

[0091] The metering module includes a plurality of metering sensors, and the target metering signal of the target vehicle is obtained through the metering module. The specific steps include:

[0092] Acquire metering signals of the multiple metering sensors to obtain multiple reference metering signals; determine the axle distribution position and loading distribution of the target vehicle according to the vehicle model information; determine the contact position of the target vehicle on the scale platform according to the axle distribution position to obtain multiple contact positions; determine the loading degree corresponding to each of the multiple contact positions according to the multiple reference metering signals to obtain multiple loading degrees; determine the loading center of gravity position of the target vehicle according to the loading distribution and the multiple loading degrees; determine the distance between the loading center of gravity position and the multiple metering sensors to obtain multiple distances; determine multiple first weights corresponding to the multiple distances; each distance corresponds to a first weight; perform weighted averaging according to the multiple reference metering signals and the multiple first weights to obtain the target metering signal.

[0093] Specifically, multiple reference metering information is obtained through multiple metering sensors, and each metering sensor corresponds to a reference metering signal. It should be noted that the metering sensors can be evenly distributed in the metering module, so as to effectively balance the signals of different contact positions, thereby reducing errors and unevenness. The axle distribution position and the loading distribution of the target vehicle are determined according to the vehicle model information. Then, the contact position of the target vehicle on the scale is determined according to the axle distribution position, and multiple contact positions are obtained. Among them, the tire position of the vehicle can be determined according to the axle distribution position, and the contact position of the vehicle on the scale can be determined. Then, the loading degree corresponding to each contact position in the multiple contact positions is determined according to the multiple reference metering signals, and multiple loading degrees are obtained. Among them, the multiple reference metering signals can reflect the pressure applied at different contact positions, so as to obtain the loading degree of each contact position. Then, the loading center of gravity position of the target vehicle can be determined according to the loading distribution and the multiple loading degrees. Then, the distance between the loading center of gravity position and the multiple metering sensors is calculated to obtain multiple distances. Determine multiple first weights corresponding to the multiple distances; each distance corresponds to a first weight, and the longer the distance, the smaller the first weight. Finally, a weighted average is performed according to the multiple reference metrology signals and the multiple first weights to obtain a target metrology signal.

[0094] The step of determining the loading center of gravity of the target vehicle according to the loading distribution and the multiple loading levels comprises:

[0095] If the loading distribution is uniform loading, the loading center of gravity position is determined according to the multiple contact positions; if the loading distribution is uneven loading, second weights are assigned to the multiple contact positions according to the multiple loading degrees to obtain multiple second weights; the loading center of gravity position is determined according to the multiple contact positions and the multiple second weights.

[0096] Specifically, if the vehicle is evenly loaded, the loading center of gravity position can be directly determined based on the multiple contact positions. If the vehicle is unevenly loaded, it is necessary to assign second weights to the multiple contact positions according to the multiple loading degrees of the vehicle, obtain multiple second weights, and determine the loading center of gravity position based on the multiple contact positions and the multiple second weights, thereby avoiding significant errors in the estimation of the loading center of gravity position due to uneven loading.

[0097] It can be seen that by considering the distance between the vehicle's loading center of gravity and the metering sensor, the metering signal can be dynamically adjusted according to the actual situation of the vehicle, so as to improve the flexibility and accuracy of the safety warning.

[0098] Step S307: determining the speed information of the target vehicle through the ground sensing coil.

[0099] Specifically, the ground sensing coil works on the principle of electromagnetic induction. When a vehicle passes through the ground sensing coil, the metal body changes the electromagnetic field around the coil, causing the current in the coil to change. Based on the time when the vehicle enters and leaves the coil, the time interval for the vehicle to pass through the coil can be calculated. Finally, the speed of the vehicle is calculated based on the length and time interval of the vehicle passing through the coil. Among them, two ground sensing coils are set in the scale, so that the first speed and the second speed of the vehicle are calculated based on the two ground sensing coils, and the acceleration of the vehicle is calculated based on the first speed and the second speed.

[0100] Step S308: determining a second adjustment factor according to the vehicle speed information.

[0101] The vehicle speed information includes the driving speed and acceleration, and the second adjustment factor is determined according to the vehicle speed information, and the specific steps include:

[0102] Determine a reference adjustment factor corresponding to the driving speed; determine a target driving state of the target vehicle according to the acceleration; the target driving state includes any one of the following: an acceleration state, a constant speed state, and a deceleration state; determine a target fine-tuning factor corresponding to the target driving state according to a preset mapping relationship between the driving state and the fine-tuning factor; fine-tune the reference adjustment factor according to the target fine-tuning factor to obtain the second adjustment factor.

[0103] Specifically, the reference adjustment factor corresponding to the vehicle's driving speed can be determined according to the mapping relationship between the preset driving speed and the reference adjustment factor, wherein the faster the driving speed, the larger the reference adjustment factor. Then the target driving state of the target vehicle is determined according to the acceleration, wherein the target driving state includes any one of the following: acceleration state, uniform speed state, and deceleration state. According to the mapping relationship between the preset driving state and the fine-tuning factor, the target fine-tuning factor corresponding to the target driving state is determined. Then the reference adjustment factor is fine-tuned according to the target fine-tuning factor to obtain a second adjustment factor, wherein the second adjustment factor is used to adjust the filter cutoff frequency of the high-speed dynamic intelligent metering instrument. It should be noted that the target fine-tuning factor corresponding to the acceleration state is a positive number, the target fine-tuning factor corresponding to the uniform speed state is 0, and the target fine-tuning factor corresponding to the deceleration state is a negative number. Among them, the numerical value of the target fine-tuning factor can also be further adjusted according to the numerical value of the acceleration, and the larger the numerical value of the acceleration, the larger the numerical value of the target fine-tuning factor.

[0104] It can be seen that determining the second adjustment factor according to the vehicle's driving speed and acceleration facilitates the subsequent adjustment of the filter cutoff frequency according to the second adjustment factor to effectively filter out high-frequency noise, thereby improving the stability of the metering signal and making the metering data more accurate, which is convenient for subsequent safety warnings for overloaded transportation, and provides accurate and reliable warning prompt information.

[0105] Step S309: adjusting the initial filter cutoff frequency according to the second adjustment factor to obtain a target filter cutoff frequency.

[0106] Specifically, the target filter cutoff frequency may be obtained by multiplying the initial filter cutoff frequency by the second adjustment factor, wherein the second adjustment factor may be in the range of 0-2, which is not specifically limited herein.

[0107] Step S310: Processing the target metering signal according to the target sensitivity and the target filter cutoff frequency by the high-speed dynamic intelligent metering instrument to obtain a target metering value.

[0108] The process of processing the target metering signal by the high-speed dynamic intelligent metering instrument according to the target sensitivity and the target filter cutoff frequency to obtain the target metering value specifically includes:

[0109] The target metering signal is filtered according to the target filtering cutoff frequency to obtain a first metering signal; the first metering signal is scaled according to the target sensitivity to obtain a second metering signal; the second metering signal is converted to obtain a target digital signal; the target digital signal is analyzed and processed according to a preset algorithm to obtain the target metering value.

[0110] Specifically, the target metering signal is filtered according to the target filter cutoff frequency to effectively remove noise and extract an effective first metering signal. The first metering signal is then scaled using the target sensitivity to adjust the amplitude of the signal for subsequent processing. The second metering signal is converted into a target digital signal through analog-to-digital signal conversion, and the target digital signal is analyzed according to a preset algorithm to extract useful information to obtain a target metering value. It should be noted that the target metering value is the weight of the target vehicle, and the preset algorithm includes but is not limited to a regression analysis algorithm, a neural network algorithm, and a numerical integration algorithm, which are not specifically limited here.

[0111] It can be seen that filtering and scaling the metering signal according to the target filter cutoff frequency and target sensitivity corresponding to the target vehicle can improve the accuracy and clarity of the metering signal, facilitate the subsequent acquisition of the target metering value of the target vehicle based on the metering signal, and make a judgment on overload transportation based on the target metering value, thereby improving the accuracy of safety warnings.

[0112] Step S311: If the target measurement value is greater than a preset safety warning threshold, a target difference between the target measurement value and the safety warning threshold is obtained, and warning prompt information is generated according to the target difference.

[0113] The step of generating early warning information according to the target difference comprises:

[0114] If the target difference is less than or equal to the preset first difference, the over-limit situation of the target vehicle is determined to be a first-level over-limit situation, and a first-level warning prompt message is issued; the first-level warning prompt message includes a text display;

[0115] If the target difference is greater than the first difference and less than or equal to a preset second difference, the over-limit situation of the target vehicle is determined to be a level 2 over-limit situation, and a level 2 warning prompt message is issued; the level 2 warning prompt message includes a text display and a flashing alarm light; the second difference is greater than the first difference;

[0116] If the target difference is greater than the second difference, the over-limit situation of the target vehicle is determined to be level three, and a level three warning prompt message is issued; the level three warning prompt message includes text display, flashing alarm lights and sound warnings.

[0117] In one possible embodiment, after determining that the target vehicle is overloaded, the current overload level and historical overload records of the target vehicle are obtained; a reference processing measure corresponding to the current overload level is determined; the reference processing measure includes at least one of the following: record archives, unloading cargo, mandatory inspection, and vehicle detention; the historical time period corresponding to the historical overload records is determined; the overload frequency corresponding to the target vehicle is determined based on the historical overload records and the historical time period; additional processing measures corresponding to the overload frequency are determined; the additional processing measures include at least one of the following: extending the monitoring period, mandatory periodic re-inspection, and restricting the driving area; the target processing measures are determined based on the reference processing measures and the additional processing measures, and the target processing measures are executed on the target vehicle.

[0118] It can be seen that after detecting that a vehicle is overloaded, the vehicle can be inspected and processed in a targeted manner according to the vehicle's overload frequency and historical records, so as to improve the management efficiency of vehicle overload transportation.

[0119] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that the controller of the intelligent early warning system includes hardware structures and / or software modules corresponding to the execution of each function in order to realize the above functions. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0120] The embodiment of the present application can divide the controller of the intelligent early warning system into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0121] In the case of dividing each functional module into corresponding functional modules, Figure 4 It is a functional module composition block diagram of a safety warning device for overloaded transportation provided by an embodiment of the present application, which is applied to a controller of an intelligent warning system. The intelligent warning system includes the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform. The weighing platform is communicatively connected with the high-speed dynamic intelligent metering instrument. The weighing platform is installed below the target lane. The weighing platform is deployed with a metering module and a ground sensing coil. The safety warning device 400 for overloaded transportation includes an acquisition module 410, an analysis module 420, a determination module 430, an adjustment module 440, a processing module 450, and an early warning module 460, wherein:

[0122] The acquisition module 410 is used to acquire a target image of the target vehicle through the image recognition module when the target vehicle is traveling in the target lane;

[0123] The analysis module 420 is used to analyze the target image to obtain the vehicle model information and the body state of the target vehicle;

[0124] The determination module 430 is used to determine the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent meter;

[0125] The determination module 430 is further configured to determine a first adjustment factor according to the vehicle model information;

[0126] The adjustment module 440 is used to adjust the initial sensitivity according to the first adjustment factor to obtain a target sensitivity;

[0127] The acquisition module 410 is further configured to acquire a target measurement signal of the target vehicle through the measurement module when the vehicle body state is that the entire vehicle body of the target vehicle is on the scale platform; the target measurement signal is an analog signal;

[0128] The determination module 430 is further configured to determine the speed information of the target vehicle through the ground sensing coil;

[0129] The determination module 430 is further configured to determine a second adjustment factor according to the vehicle speed information;

[0130] The adjustment module 440 is further configured to adjust the initial filter cutoff frequency according to the second adjustment factor to obtain a target filter cutoff frequency;

[0131] The processing module 450 is used to process the target metering signal according to the target sensitivity and the target filter cutoff frequency through the high-speed dynamic intelligent metering instrument to obtain a target metering value;

[0132] The warning module 460 is used to obtain a target difference between the target measurement value and the safety warning threshold if the target measurement value is greater than a preset safety warning threshold, and generate warning prompt information according to the target difference.

[0133] Optionally, the intelligent early warning system further includes an audio collector. In determining the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent meter, the determination module 430 specifically includes:

[0134] Acquiring the original audio signal of the target vehicle through the audio collector;

[0135] Preprocessing the original audio signal to obtain a reference audio signal;

[0136] Extracting features from the reference audio signal to obtain reference audio features;

[0137] Compare the reference audio feature with a preset sample feature set to determine a reference vehicle state corresponding to the reference audio feature in the sample feature set; the reference vehicle state includes any one of the following: light load state, medium load state, and heavy load state;

[0138] According to the preset mapping relationship between the vehicle state and the working parameters, the initial working parameters of the high-speed dynamic intelligent metering instrument corresponding to the reference vehicle state are determined; the initial working parameters include the initial sensitivity and the initial filter cutoff frequency.

[0139] Optionally, in determining the first adjustment factor according to the vehicle model information, the determination module 430 further specifically includes:

[0140] Analyze the vehicle model information according to a preset vehicle model database to determine key information in the vehicle model information; the key information includes at least one of the following: a target axle number and a target tire specification;

[0141] When the key information is the target number of axles and the target tire specification, determining a first weight corresponding to the target number of axles and a second weight corresponding to the target tire specification;

[0142] Determine the initial first adjustment factor corresponding to the target number of axles according to a preset mapping relationship between the number of axles and the adjustment factor; the more the number of axles, the greater the adjustment factor;

[0143] Determine the initial second adjustment factor corresponding to the target tire specification according to the preset mapping relationship between the tire specification and the adjustment factor; the larger the tire specification, the larger the adjustment factor;

[0144] The first adjustment factor is obtained by performing a weighted summation on the initial first adjustment factor and the first weight, and on the initial second adjustment factor and the second weight.

[0145] Optionally, the metering module includes a plurality of metering sensors. In acquiring the target metering signal of the target vehicle through the metering module, the acquisition module 410 specifically includes:

[0146] Acquire metrological signals of the plurality of metrological sensors to obtain a plurality of reference metrological signals;

[0147] Determining the axle distribution position and loading distribution of the target vehicle according to the vehicle model information;

[0148] Determine the contact position of the target vehicle on the weighing platform according to the axle distribution position, and obtain multiple contact positions;

[0149] determining a loading degree corresponding to each of the plurality of contact positions according to the plurality of reference metrology signals to obtain a plurality of loading degrees;

[0150] Determining a loading center of gravity position of the target vehicle according to the loading distribution and the multiple loading levels;

[0151] Determine the distance between the loading center of gravity position and the plurality of measuring sensors to obtain a plurality of distances;

[0152] Determine a plurality of first weights corresponding to the plurality of distances; each distance corresponds to a first weight;

[0153] The target metrology signal is obtained by performing weighted averaging according to the multiple reference metrology signals and the multiple first weights.

[0154] Optionally, in determining the loading center of gravity position of the target vehicle according to the loading distribution and the multiple loading degrees, the acquisition module 410 further specifically includes:

[0155] If the loading distribution condition is uniform loading, determining the loading center of gravity position according to the multiple contact positions;

[0156] If the loading distribution is uneven loading, assigning second weights to the multiple contact positions according to the multiple loading levels to obtain multiple second weights;

[0157] The loading center of gravity position is determined based on the plurality of contact positions and the plurality of second weights.

[0158] Optionally, the vehicle speed information includes a driving speed and an acceleration. In determining the second adjustment factor according to the vehicle speed information, the determination module 430 specifically includes:

[0159] Determining a reference adjustment factor corresponding to the driving speed;

[0160] Determine the target driving state of the target vehicle according to the acceleration; the target driving state includes any one of the following: an acceleration state, a constant speed state, and a deceleration state;

[0161] Determining a target fine-tuning factor corresponding to the target driving state according to a preset mapping relationship between the driving state and the fine-tuning factor;

[0162] The reference adjustment factor is fine-tuned according to the target fine-tuning factor to obtain the second adjustment factor.

[0163] Optionally, in the aspect of processing the target metering signal according to the target sensitivity and the target filter cutoff frequency by the high-speed dynamic intelligent metering instrument to obtain the target metering value, the processing module 450 specifically includes:

[0164] Filtering the target metering signal according to the target filter cutoff frequency to obtain a first metering signal;

[0165] Scaling the first metering signal according to the target sensitivity to obtain a second metering signal;

[0166] Performing signal conversion on the second metering signal to obtain a target digital signal;

[0167] The target digital signal is analyzed and processed according to a preset algorithm to obtain the target measurement value.

[0168] Optionally, in the aspect of generating the warning prompt information according to the target difference, the warning module 460 specifically includes:

[0169] If the target difference is less than or equal to the preset first difference, the over-limit situation of the target vehicle is determined to be a first-level over-limit situation, and a first-level warning prompt message is issued; the first-level warning prompt message includes a text display;

[0170] If the target difference is greater than the first difference and less than or equal to a preset second difference, the over-limit situation of the target vehicle is determined to be a level 2 over-limit situation, and a level 2 warning prompt message is issued; the level 2 warning prompt message includes a text display and a flashing alarm light; the second difference is greater than the first difference;

[0171] If the target difference is greater than the second difference, the over-limit situation of the target vehicle is determined to be level three, and a level three warning prompt message is issued; the level three warning prompt message includes text display, flashing alarm lights and sound warnings.

[0172] It can be seen that during the vehicle transportation process, by adjusting the sensitivity and filter cutoff frequency of the high-speed dynamic intelligent metering instrument in real time, it can adapt to different vehicle models and speeds, thereby improving the accuracy of safety warnings for overload transportation.

[0173] It should be noted that the specific implementation of each operation can adopt the corresponding description of the method embodiment shown above. The safety warning device 400 for oversized transportation can be used to execute the above method embodiment of the present application, which will not be repeated here.

[0174] An embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer includes a controller of an intelligent early warning system.

[0175] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product can be a software installation package, and the computer includes a controller of the intelligent early warning system.

[0176] It should be noted that, for the above-mentioned various embodiments, for the sake of simple description, they are all expressed as a series of action combinations. Those skilled in the art should be aware that the present application is not limited by the described order of actions, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions, steps, modules or units involved are not necessarily required by the embodiments of the present application.

[0177] In the above embodiments, the embodiments of the present application have different focuses on the description of each embodiment. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0178] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

[0179] The steps of the method or algorithm described in the embodiments of the present application can be implemented in hardware or by executing software instructions by a processor. The software instructions can be composed of corresponding software modules, and the software modules can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (electrically EPROM, EEPROM), registers, hard disks, mobile hard disks, read-only compact disks (CD-ROMs) or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and the storage medium can also exist in a terminal device or a management device as discrete components.

[0180] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0181] The modules / units included in the devices and products described in the above embodiments may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least some of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as chip, circuit module, etc.) or different components of the chip module, or at least some of the modules / units may be implemented in the form of software programs. It is implemented in the form of a software program that runs on a processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal equipment, or at least some of the modules / units can be implemented in the form of a software program that runs on a processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in hardware such as circuits.

[0182] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above description is only the specific implementation method of the embodiments of the present application and is not intended to limit the protection scope of the embodiments of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the protection scope of the embodiments of the present application.

Claims

1. A safety warning method for oversized transportation, characterized in that: A controller applied to an intelligent early warning system, the intelligent early warning system comprising the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform, the weighing platform being communicatively connected to the high-speed dynamic intelligent metering instrument, the weighing platform being installed below a target lane, the weighing platform being deployed with a metering module and a ground sensing coil, the method comprising: When the target vehicle is traveling in the target lane, a target image of the target vehicle is acquired through the image recognition module; Analyze the target image to obtain the model information of the target vehicle and the body state of the target vehicle; Determining the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent metering instrument; determining a first adjustment factor according to the vehicle type information; Adjusting the initial sensitivity according to the first adjustment factor to obtain a target sensitivity; When the vehicle body state is that the vehicle body of the target vehicle is completely on the weighing platform, a target metering signal of the target vehicle is obtained through the metering module; the target metering signal is an analog signal; Determining the speed information of the target vehicle by using the ground sensing coil; determining a second adjustment factor according to the vehicle speed information; The initial filter cutoff frequency is adjusted according to the second adjustment factor to obtain a target filter cutoff frequency; The target metering signal is processed by the high-speed dynamic intelligent metering instrument according to the target sensitivity and the target filter cutoff frequency to obtain a target metering value; If the target measurement value is greater than the preset safety warning threshold, a target difference between the target measurement value and the safety warning threshold is obtained, and a warning prompt message is generated according to the target difference; Wherein, determining the first adjustment factor according to the vehicle model information includes: Analyze the vehicle model information according to a preset vehicle model database to determine key information in the vehicle model information; the key information includes at least one of the following: a target axle number and a target tire specification; When the key information is the target number of axles and the target tire specification, determining a first weight corresponding to the target number of axles and a second weight corresponding to the target tire specification; Determine the initial first adjustment factor corresponding to the target number of axles according to a preset mapping relationship between the number of axles and the adjustment factor; the more the number of axles, the greater the adjustment factor; Determine the initial second adjustment factor corresponding to the target tire specification according to the preset mapping relationship between the tire specification and the adjustment factor; the larger the tire specification, the larger the adjustment factor; Performing a weighted summation on the initial first adjustment factor and the first weight, and the initial second adjustment factor and the second weight to obtain the first adjustment factor; The vehicle speed information includes a driving speed and an acceleration, and determining the second adjustment factor according to the vehicle speed information includes: Determining a reference adjustment factor corresponding to the driving speed; Determine the target driving state of the target vehicle according to the acceleration; the target driving state includes any one of the following: an acceleration state, a constant speed state, and a deceleration state; Determining a target fine-tuning factor corresponding to the target driving state according to a preset mapping relationship between the driving state and the fine-tuning factor; The reference adjustment factor is fine-tuned according to the target fine-tuning factor to obtain the second adjustment factor.

2. The method according to claim 1, characterized in that The intelligent early warning system also includes an audio collector, and the determining of the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent meter includes: Acquiring the original audio signal of the target vehicle through the audio collector; Preprocessing the original audio signal to obtain a reference audio signal; Extracting features from the reference audio signal to obtain reference audio features; Compare the reference audio feature with a preset sample feature set to determine a reference vehicle state corresponding to the reference audio feature in the sample feature set; the reference vehicle state includes any one of the following: light load state, medium load state, and heavy load state; According to the preset mapping relationship between the vehicle state and the working parameters, the initial working parameters of the high-speed dynamic intelligent metering instrument corresponding to the reference vehicle state are determined; the initial working parameters include the initial sensitivity and the initial filter cutoff frequency.

3. The method according to claim 1 or 2, characterized in that The metering module includes a plurality of metering sensors, and obtaining the target metering signal of the target vehicle through the metering module includes: Acquire metrological signals of the plurality of metrological sensors to obtain a plurality of reference metrological signals; Determining the axle distribution position and loading distribution of the target vehicle according to the vehicle model information; Determine the contact position of the target vehicle on the weighing platform according to the axle distribution position, and obtain multiple contact positions; determining a loading degree corresponding to each of the plurality of contact positions according to the plurality of reference metrology signals to obtain a plurality of loading degrees; Determining a loading center of gravity position of the target vehicle according to the loading distribution and the multiple loading levels; Determine the distance between the loading center of gravity position and the plurality of measuring sensors to obtain a plurality of distances; Determine a plurality of first weights corresponding to the plurality of distances; each distance corresponds to a first weight; The target metrology signal is obtained by performing weighted averaging according to the multiple reference metrology signals and the multiple first weights.

4. The method according to claim 3, characterized in that The step of determining the loading center of gravity position of the target vehicle according to the loading distribution and the multiple loading degrees includes: If the loading distribution condition is uniform loading, determining the loading center of gravity position according to the multiple contact positions; If the loading distribution is uneven loading, assigning second weights to the multiple contact positions according to the multiple loading levels to obtain multiple second weights; The loading center of gravity position is determined based on the plurality of contact positions and the plurality of second weights.

5. The method according to claim 1, characterized in that The process of processing the target metering signal according to the target sensitivity and the target filter cutoff frequency by the high-speed dynamic intelligent metering instrument to obtain the target metering value includes: Filtering the target metering signal according to the target filter cutoff frequency to obtain a first metering signal; Scaling the first metering signal according to the target sensitivity to obtain a second metering signal; Performing signal conversion on the second metering signal to obtain a target digital signal; The target digital signal is analyzed and processed according to a preset algorithm to obtain the target measurement value.

6. The method according to claim 1 or 2, characterized in that: The generating of early warning prompt information according to the target difference includes: If the target difference is less than or equal to the preset first difference, the over-limit situation of the target vehicle is determined to be a first-level over-limit situation, and a first-level warning prompt message is issued; the first-level warning prompt message includes a text display; If the target difference is greater than the first difference and less than or equal to a preset second difference, the over-limit situation of the target vehicle is determined to be a level 2 over-limit situation, and a level 2 warning prompt message is issued; the level 2 warning prompt message includes a text display and a flashing alarm light; the second difference is greater than the first difference; If the target difference is greater than the second difference, the over-limit situation of the target vehicle is determined to be level three, and a level three warning prompt message is issued; the level three warning prompt message includes text display, flashing alarm lights and sound warnings.

7. A safety warning device for oversized transportation, used to execute the safety warning method for oversized transportation as claimed in any one of claims 1 to 6, characterized in that: A controller applied to an intelligent early warning system, the intelligent early warning system comprising the controller, an image recognition module, a high-speed dynamic intelligent metering instrument, and a weighing platform, the weighing platform being communicatively connected to the high-speed dynamic intelligent metering instrument, the weighing platform being installed below a target lane, the weighing platform being deployed with a metering module and a ground sensing coil, the device comprising an acquisition module, an analysis module, a determination module, an adjustment module, a processing module, and an early warning module, wherein: The acquisition module is used to acquire a target image of the target vehicle through the image recognition module when the target vehicle is traveling in the target lane; The analysis module is used to analyze the target image to obtain the vehicle model information and the body state of the target vehicle; The determination module is used to determine the initial sensitivity and initial filter cutoff frequency of the high-speed dynamic intelligent metering instrument; The determination module is further used to determine a first adjustment factor according to the vehicle model information; The adjustment module is used to adjust the initial sensitivity according to the first adjustment factor to obtain a target sensitivity; The acquisition module is further used to acquire a target measurement signal of the target vehicle through the measurement module when the vehicle body state is that the vehicle body of the target vehicle is entirely on the scale platform; the target measurement signal is an analog signal; The determination module is further used to determine the speed information of the target vehicle through the ground sensing coil; The determination module is further used to determine a second adjustment factor according to the vehicle speed information; The adjustment module is further used to adjust the initial filter cutoff frequency according to the second adjustment factor to obtain a target filter cutoff frequency; The processing module is used to process the target metering signal according to the target sensitivity and the target filter cutoff frequency through the high-speed dynamic intelligent metering instrument to obtain a target metering value; The early warning module is used to obtain a target difference between the target measurement value and the safety warning threshold if the target measurement value is greater than a preset safety warning threshold, and generate early warning prompt information according to the target difference.

8. A controller for an intelligent early warning system, characterized in that: include: A processor, a memory, a communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for executing the steps in the method according to any one of claims 1 to 6.

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