CN116026441A - Method, device, equipment and storage medium for detecting abnormal load capacity of vehicle - Google Patents
Method, device, equipment and storage medium for detecting abnormal load capacity of vehicle Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a storage medium for detecting abnormal load capacity of a vehicle, wherein the method comprises the following steps: collecting the original carrying capacity of a vehicle when the vehicle exits from a loading and unloading area, and collecting the carrying capacity of the vehicle in the transportation process in real time; calculating a load fluctuation ratio according to the original load capacity and the load capacity in the transportation process, and determining that the load of the vehicle is abnormal under the condition that the load fluctuation ratio is larger than or equal to a preset fluctuation threshold value; and alarming the abnormal load of the vehicle according to the abnormal load of the vehicle. According to the vehicle load capacity abnormality detection method provided by the embodiment of the application, whether the load capacity during transportation of the vehicle is abnormal or not can be detected in real time, and when the load abnormality is determined, alarm information is sent. The method can effectively reduce the influence of cargo leakage, scattering and the like on road safety, effectively avoid illegal loading and unloading behaviors and cargo loss during transportation, and protect the cargo safety.
Description
Technical Field
The invention relates to the technical field of internet of vehicles, in particular to a method, a device, equipment and a storage medium for detecting abnormal load capacity of a vehicle.
Background
With the rapid development of modern transportation industry, vehicles are continuously driven into urban distribution chains under the encouragement of national policies. At present, the whole vehicle logistics of vehicles (such as heavy trucks and vans) is a manual driving mode. In the transportation, the condition that logistics drivers privately receive single goods, or the goods are loaded and unloaded illegally, or the condition that the goods fall off and the goods leak in the transportation exists, seriously threatens the safety of the goods. The existing technology is difficult to monitor the load condition of the vehicle in the transportation in real time, so that when the load abnormality occurs to the vehicle, the vehicle cannot be known in real time, and the cargo condition is difficult to search in time.
Disclosure of Invention
The embodiment of the application provides a vehicle load capacity abnormality detection method, device, equipment and storage medium. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In a first aspect, an embodiment of the present application provides a method for detecting a load abnormality of a vehicle, including:
collecting the original carrying capacity of a vehicle when the vehicle exits from a loading and unloading area, and collecting the carrying capacity of the vehicle in the transportation process in real time;
calculating a load fluctuation ratio according to the original load capacity and the load capacity in the transportation process, and determining that the load of the vehicle is abnormal under the condition that the load fluctuation ratio is larger than or equal to a preset fluctuation threshold value;
and alarming the abnormal load of the vehicle according to the abnormal load of the vehicle.
In an alternative embodiment, collecting the original load capacity of the vehicle exiting the loading area includes:
acquiring a loading and unloading area in the transportation process of the vehicle, and setting up an electronic fence in the loading and unloading area;
and determining the original carrying capacity according to the carrying capacity corresponding to the last piece of position data in the current electronic fence.
In an alternative embodiment, calculating the load variability from the raw load capacity and the load capacity on the way includes:
under the condition that the vehicle is in a running state, collecting a plurality of continuous load capacity values, and calculating the load fluctuation rate of the vehicle according to the plurality of continuous load capacity values and the original load capacity;
under the condition that the vehicle is in a parking state, collecting the current load capacity value of the vehicle, and calculating the load fluctuation rate of the vehicle according to the current load capacity value and the original load capacity.
In an alternative embodiment, calculating the load change rate of the vehicle from the plurality of consecutive load values and the raw load value comprises calculating according to the following formula:
wherein P represents the load fluctuation ratio, n represents the number of collected continuous load capacity values, M i Load value representing continuous point, M 0 Representing the original load capacity, and mu represents the accuracy of the vehicle-mounted weighing device;
calculating the load change rate of the vehicle according to the current load value and the original load value, wherein the calculation comprises the following formula:
wherein P represents the load change rate, M i Representing the current load value, M 0 Represents the original load capacity and mu represents the accuracy of the vehicle-mounted weighing device.
In an alternative embodiment, after determining the vehicle load abnormality, further comprising:
determining the moment of abnormal load of the vehicle;
taking a preset first period before the moment and a preset second period after the moment as video storage periods;
storing video files shot by a shooting device on the vehicle according to the video storage period;
and storing the video file and license plate number information, driver information and time information corresponding to the video file into a blockchain.
In an optional embodiment, after storing the video file captured by the capturing device on the vehicle according to the video storage period, the method further includes:
extracting a plurality of images from the video file;
inputting the extracted multiple images into a preset event identification model to obtain an identified load change event, wherein the load change event comprises at least one of cargo leakage, cargo falling and illegal loading and unloading.
In an alternative embodiment, the warning of abnormal load of the vehicle is carried out, comprising:
generating voice prompt information according to the determined load abnormality of the vehicle and the identified load change event, and sending the voice prompt information to a driver terminal;
and sending the vehicle load abnormality prompt and the video file to the vehicle-mounted terminal and the cargo owner terminal.
In a second aspect, an embodiment of the present application provides a vehicle load capacity abnormality detection device, including:
the collecting module is used for collecting the original carrying capacity of the vehicle when the vehicle exits the loading and unloading area and collecting the carrying capacity of the vehicle in the transportation process in real time;
the judging module is used for calculating the load fluctuation rate according to the original load capacity and the load capacity in the transportation process, and determining that the load of the vehicle is abnormal under the condition that the load fluctuation rate is greater than or equal to a preset fluctuation threshold value;
and the alarm module is used for alarming the abnormal load of the vehicle according to the abnormal load of the vehicle.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory storing program instructions, where the processor is configured to execute the method for detecting a vehicle load capacity abnormality provided in the above embodiment when executing the program instructions.
In a fourth aspect, embodiments of the present application provide a computer readable medium having stored thereon computer readable instructions that are executed by a processor to implement a vehicle load capacity anomaly detection method provided by the above embodiments.
The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:
the embodiment of the application provides a detection method for abnormal load of a vehicle, which is characterized in that the load capacity during transportation is monitored in real time, the abnormal load judgment is carried out according to the monitored load capacity and the original load capacity, whether the abnormal load of the vehicle occurs during transportation is determined in real time, and after the abnormal load is determined, alarm information is sent out. The method can effectively reduce the influence of cargo leakage, scattering and the like on road safety, effectively avoid illegal loading and unloading behaviors and cargo loss during transportation, and protect the cargo safety.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a flow chart diagram illustrating a method of detecting a vehicle load anomaly, according to an exemplary embodiment;
FIG. 2 is a schematic diagram illustrating a method of detecting a vehicle load anomaly, according to an exemplary embodiment;
FIG. 3 is a schematic diagram illustrating a method of detecting a load change event according to an exemplary embodiment;
fig. 4 is a schematic structural view showing a vehicle load capacity abnormality detection device according to an exemplary embodiment;
FIG. 5 is a schematic diagram of an electronic device, according to an example embodiment;
fig. 6 is a schematic diagram of a computer storage medium shown according to an example embodiment.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them.
It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of systems and methods that are consistent with aspects of the invention as detailed in the accompanying claims.
According to the method, the vehicle load situation can be detected in real time by combining the peripheral vehicle-mounted weighing device, the vehicle-mounted video device and the vehicle-mounted terminal, abnormal change of the vehicle load during transportation is intelligently judged according to the abnormal change strategy of the vehicle-mounted cargo weight outside the rail of the loading and unloading area, the abnormal change of the vehicle load during transportation comprises the conditions of leakage, scattering, illegal loading and unloading, loss and the like during transportation, if the strategy is met, the system automatically reports the abnormal change of the vehicle load to alarm and reserves video evidence of the accident period, and simultaneously, voice or short message reminding is timely sent out to transportation enterprises, owners and drivers, the influence of the leakage, scattering and the like of the cargo on the road safety can be effectively reduced, the illegal loading and unloading behavior during transportation and the cargo loss are effectively avoided, and the cargo safety is protected.
The following describes in detail the method for detecting abnormal load capacity of a vehicle according to the embodiment of the present application with reference to the accompanying drawings. Referring to fig. 1, the method specifically includes the following steps.
S101, collecting the original load capacity of the vehicle when the vehicle exits from the loading and unloading area, and collecting the load capacity of the vehicle in the transportation process in real time.
In one possible implementation, a loading and unloading area on the way of the vehicle is acquired, and an electronic fence is set up in the loading and unloading area. By setting up the electronic fence in the loading and unloading area range, the abnormal detection of the load capacity of the vehicle is not carried out in the electronic fence. Only when the vehicle finishes loading and unloading in the loading and unloading area, the vehicle starts to detect the load capacity change after exiting the electronic fence. And determining the original carrying capacity according to the carrying capacity corresponding to the last piece of position data in the current electronic fence where the vehicle is located. Wherein, measuring equipment such as a weighing sensor and the like can be arranged on the vehicle body to detect the carrying capacity.
Further, after the vehicle exits the electronic fence of the loading and unloading area, the carrying capacity of the vehicle in the transportation process is collected in real time.
The collected non-compliance data is filtered by analyzing the vehicle location data. The method comprises the steps of collecting position data of a vehicle through a GPS and a Beidou positioning system, removing position data with longitude and latitude not in China, removing data with longitude and latitude of zero or longitude of zero from front and rear continuous two positions with mileage offset exceeding 5 km, removing data with longitude and latitude not in a range of 0-360 degrees from the direction of the vehicle, removing data with GPS time and receiving time interval exceeding 10 minutes from continuous two normal positions, and removing data with vehicle weight value smaller than 0 or larger than 55 preset limit value. By preprocessing the data, accurate acquired data can be obtained.
S102, calculating a load fluctuation ratio according to the original load capacity and the load capacity in the transportation process, and determining that the load of the vehicle is abnormal when the load fluctuation ratio is larger than or equal to a preset fluctuation threshold value.
According to the embodiment of the application, different load change rate calculation methods are adopted according to the running speed of the vehicle. Under the condition that the vehicle is in a running state, a plurality of continuous load capacity values are collected, and the load fluctuation ratio of the vehicle is calculated according to the plurality of continuous load capacity values and the original load capacity. The number of the collected continuous load capacity values is not specifically limited herein, for example, the load capacity values of two continuous position data may be collected, and the load capacity values of three continuous position data may be collected.
Specifically, in the out-of-rail running state of the loading and unloading area, that is, when the GPS speed of the vehicle position data is greater than 0, the load change rate of the vehicle is calculated according to a plurality of continuous load capacity values and original load capacities, including the following formula:
wherein P represents the load fluctuation ratio, n represents the number of collected continuous load capacity values, M i Represents the i-th load value, M, of the collection 0 Representing the original load capacity, μ represents the on-board weighing device accuracy, which in one embodiment is 3%.
The vehicle weight change scene is closer to the real weight change scene in the running state, the change rate calculated by weighting a plurality of points continuously exceeds a threshold value to be recorded as abnormal vehicle load, and abnormal vehicle load change alarming caused by vehicle load change due to road bump is prevented.
Under the condition that the vehicle is in a parking state, the current load capacity value of the vehicle is collected, and the load variation rate of the vehicle is calculated according to the current load capacity value and the original load capacity.
Specifically, in the parking state outside the loading and unloading area electronic fence, namely when the GPS speed of the vehicle position data is equal to 0, the carrying capacity according to 1 piece of vehicle position data is compared with the original carrying capacity. Comprising calculation according to the following formula:
wherein P represents the load change rate, M i Representing the current load value, M 0 Represents the original load capacity and mu represents the accuracy of the vehicle-mounted weighing device. In one embodiment, the on-board weighing device accuracy is 3%.
Further, after the load fluctuation rate is calculated, the load fluctuation rate is compared with a preset fluctuation threshold value, and if the load fluctuation rate is equal to or greater than the preset fluctuation threshold value, the load abnormality of the vehicle is determined. The specific value of the preset variation threshold is not specifically limited in the embodiment of the present application, and may be set according to practical situations, for example, the preset variation threshold is set to 0.02, 0.03, and so on.
According to the step, whether the load of the vehicle is abnormal or not can be accurately analyzed in real time based on the running state of the vehicle, the precision of the weighing device, the real-time collected load capacity and the original load capacity when the vehicle exits the electronic fence.
S103, alarming the abnormal load of the vehicle according to the abnormal load of the vehicle.
After determining that the vehicle load is abnormal, the method further comprises: determining the abnormal moment of the load of the vehicle, and taking a preset first time period before the moment and a preset second time period after the moment as a video storage time period; and storing the video file shot by the shooting device on the vehicle according to the video storage period.
In one embodiment, a video camera is mounted on a vehicle such that the video camera can capture a panoramic image of a vehicle cabin. After the abnormal load of the vehicle is determined, a video record with a period of time is stored, so that whether illegal transportation behaviors exist or not can be checked afterwards.
Since the storage space is limited, only video images within the vehicle-mounted weight abnormality period can be saved. Specifically, when the abnormal load of the vehicle is identified, the current time is obtained, the abnormal load moment of the vehicle is determined, for example, the abnormal load moment of the vehicle is 9:00, a preset first time period before the moment and a preset second time period after the moment are taken as video storage time periods, for example, the time periods of five minutes before the moment and 5 minutes after the moment are taken as video storage time periods, and video files in the time range of 8:55-9:05 are stored. The specific values of the preset first period and the preset second period are not limited in this application, and can be set by a person skilled in the art.
The videos before and after the abnormal moment of the vehicle load are stored, so that the process video when the vehicle weight is abnormal can be accurately analyzed afterwards.
Further, information such as license plate number information, driver information and shooting time information corresponding to the video file is obtained, and the video file, the license plate number information, the driver information and the time information corresponding to the video file are stored in the blockchain. By storing the video file into the blockchain, the data can be ensured not to be tampered, and the credibility of the data is improved.
In an alternative embodiment, after the video file is obtained, the video image may also be identified based on a pre-trained event recognition model, and a load change event may be detected. Load change events include various events such as cargo leakage, cargo dropping, illegal loading and unloading, etc.
Specifically, a cargo leakage picture, a cargo scattering picture, a cargo illegal loading and unloading picture, a cargo normal transportation picture and the like corresponding to a plurality of pieces of multi-type cargos are obtained, the obtained plurality of images are marked manually, corresponding load change events are marked, and a constructed training data set is obtained.
Further, an event recognition model is trained from the constructed training data set. The event recognition model is a neural network model, such as a model based on a convolutional neural network, and can be FasterR-CNN, YOLO, maskR-CNN and the like. And obtaining a trained event recognition model.
After the video file shot by the shooting device on the vehicle is stored according to the video storage period, the method further comprises the steps of extracting a plurality of images from the video file, inputting the extracted images into a preset event identification model, and obtaining an identified load change event, wherein the load change event comprises at least one of cargo leakage, cargo falling and illegal loading and unloading.
Specifically, as shown in fig. 3, the method for identifying the load change event includes:
s301, labeling a load change event in the image, and constructing a training data set.
S302, training a neural network model according to the constructed training data set to obtain a trained event recognition model.
S303 extracts a plurality of images from the saved video file.
S304, inputting the extracted images into a preset event recognition model to obtain a recognized load change event.
S305 generates alarm information based on the identified load change event.
By identifying the load change event, the cause of the abnormal load of the vehicle can be accurately identified, and a driver can know the cause of the abnormal load without getting off the vehicle to check.
In an alternative embodiment, after determining the load abnormality of the vehicle, a voice prompt may be generated based on the identified load change event. For example, the identified load change event is a load scattering, and a voice prompt message "vehicle load abnormality" is generated, possibly due to the load scattering, requesting a timely parking inspection. And sending the generated voice prompt information to a mobile phone, a vehicle-mounted terminal and other devices of a driver to carry out alarm prompt.
In an alternative implementation mode, the vehicle load abnormity prompt information and the stored video file can be sent to the vehicle-mounted terminal and the goods owner terminal, so that a driver and the goods owner can review video recordings conveniently, and the goods dynamics can be known.
The system automatically reports abnormal change of the vehicle load to give an alarm and reserves video evidence of the accident period, and simultaneously timely sends out voice or short message reminding to transportation enterprises, owners and drivers, so that the influence of cargo leakage, scattering and the like on road safety can be effectively reduced, illegal loading and unloading behaviors and cargo loss during transportation are effectively avoided, and the cargo safety is protected.
In order to facilitate understanding of the vehicle load capacity abnormality detection method provided in the embodiment of the present application, the following description is made with reference to fig. 2. As shown in fig. 2, the method includes the following steps.
The method comprises the steps of firstly collecting vehicle position data and load data, preprocessing the collected data, and removing illegal and non-compliance data. And then, carrying out intelligent judgment, collecting a plurality of continuous load capacity values under the condition that the vehicle is in a running state, and calculating the load fluctuation ratio of the vehicle according to the plurality of continuous load capacity values and the original load capacity. Under the condition that the vehicle is in a parking state, the current load capacity value of the vehicle is collected, and the load variation rate of the vehicle is calculated according to the current load capacity value and the original load capacity. And determining that the load of the vehicle is abnormal under the condition that the load fluctuation rate is greater than or equal to a preset fluctuation threshold value.
After the load abnormality is determined, alarm processing is carried out, including video recording and intelligent reminding. A voice prompt may be generated based on the identified load change event. For example, the identified load change event is a load scattering, and a voice prompt message "vehicle load abnormality" is generated, possibly due to the load scattering, requesting a timely parking inspection. And sending the generated voice prompt information to a mobile phone, a vehicle-mounted terminal and other devices of a driver to carry out alarm prompt. The vehicle load abnormity prompt information and the stored video file can be sent to the vehicle-mounted terminal and the cargo owner terminal, so that a driver and the cargo owner can review video recordings conveniently, and cargo dynamics can be known.
In one exemplary scenario, heavy goods vehicle Beijing A10000 is an operating vehicle under the transportation enterprise A, responsible for transporting goods from Beijing North six-ring manufacturing enterprise B factory area to the goods distribution center warehouse C. The system sets the factory area of the enterprise B and the area where the warehouse C of the commodity distribution center is located as an electronic fence of a loading and unloading area, the accuracy error of the vehicle-mounted weighing equipment is 3%, and the fluctuation judgment threshold value is 2%.
And recording the 15 tons of load capacity value reported by the last piece of position data of the vehicle when the speed of the factory area of the enterprise B is 0KM/H as the original load capacity. The vehicle starts from the factory area of the enterprise B and runs on a Beijing north six-loop, 10 points 01 and 30 seconds report a piece of non-stop position data, the loading capacity is 14.2 tons, 10 points 02 and 00 seconds report a piece of non-stop position data, and the loading capacity is 14.3 tons and is brought into a calculation formula:
wherein the load change rate is 0.0492>0.02. At the moment, the system generates abnormal vehicle load change alarm, the voice prompt is issued to the vehicle-mounted terminal of Beijing A10000 to guide a driver to stop and check, meanwhile, the short message informs relevant responsible persons of enterprises A and B, a video recording storage command is issued to the vehicle-mounted terminal, and the vehicle-mounted terminal reports a video file to the system and is associated with the alarm so as to be checked afterwards.
The application provides a vehicle load abnormal change judging method and an intelligent reminding system in a vehicle networking scene. According to the vehicle-mounted cargo weight abnormal change strategy outside the rail of the loading and unloading area, abnormal change of the vehicle load (including illegal transportation or conditions of leakage, scattering, illegal loading and unloading, losing and the like in the middle of transportation) is intelligently judged, if the strategy is met, the system automatically reports the abnormal change alarm of the vehicle load and reserves video evidence of the time period of occurrence, and simultaneously timely sends out voice or short message reminding to transportation enterprises, owners and drivers, so that the influence of the leakage and scattering of the cargo on the road safety can be effectively reduced, the illegal loading and unloading behavior and the cargo loss in the middle of transportation are effectively avoided, and the cargo safety is protected.
The embodiment of the present application further provides a vehicle load capacity abnormality detection device for executing the vehicle load capacity abnormality detection method of the above embodiment, as shown in fig. 4, the device includes:
the collection module 401 is used for collecting the original carrying capacity of the vehicle when the vehicle exits the loading and unloading area and collecting the carrying capacity of the vehicle in the transportation process in real time;
a judging module 402, configured to calculate a load variation rate according to the original load capacity and the load capacity during transportation, and determine that the vehicle load is abnormal if the load variation rate is greater than or equal to a preset variation threshold;
and the alarm module 403 is used for alarming the abnormal load of the vehicle according to the abnormal load of the vehicle.
It should be noted that, when the vehicle load capacity abnormality detection apparatus provided in the foregoing embodiment performs the vehicle load capacity abnormality detection method, only the division of the foregoing functional modules is exemplified, and in practical application, the foregoing functional allocation may be performed by different functional modules, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the vehicle load capacity abnormality detection device provided in the above embodiment and the vehicle load capacity abnormality detection method embodiment belong to the same concept, which embody the detailed implementation process and are not described herein again.
The embodiment of the application also provides an electronic device corresponding to the method for detecting the abnormal load capacity of the vehicle provided by the previous embodiment, so as to execute the method for detecting the abnormal load capacity of the vehicle.
Referring to fig. 5, a schematic diagram of an electronic device according to some embodiments of the present application is shown. As shown in fig. 5, the electronic device includes: processor 500, memory 501, bus 502 and communication interface 503, processor 500, communication interface 503 and memory 501 being connected by bus 502; the memory 501 stores a computer program executable on the processor 500, and the processor 500 executes the vehicle load capacity abnormality detection method provided in any one of the foregoing embodiments of the present application when executing the computer program.
The memory 501 may include a high-speed random access memory (RAM: random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 503 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.
The processor 500 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in the processor 500. The processor 500 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but may also be a Digital Signal Processor (DSP), application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 501, and the processor 500 reads the information in the memory 501, and in combination with its hardware, performs the steps of the method described above.
The electronic device provided by the embodiment of the application and the vehicle load capacity abnormality detection method provided by the embodiment of the application are the same in conception and have the same beneficial effects as the method adopted, operated or realized by the electronic device.
The present embodiment also provides a computer readable storage medium corresponding to the method for detecting a vehicle load capacity abnormality provided in the foregoing embodiment, referring to fig. 6, the computer readable storage medium is shown as an optical disc 600, on which a computer program (i.e. a program product) is stored, and the computer program, when executed by a processor, performs the method for detecting a vehicle load capacity abnormality provided in any of the foregoing embodiments.
It should be noted that examples of the computer readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical or magnetic storage medium, which will not be described in detail herein.
The computer readable storage medium provided by the above embodiment of the present application has the same advantageous effects as the method adopted, operated or implemented by the application program stored therein, because the same inventive concept is adopted as the method for detecting the abnormal load capacity of the vehicle provided by the embodiment of the present application.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A vehicle load abnormality detection method, characterized by comprising:
collecting the original carrying capacity of a vehicle when the vehicle exits from a loading and unloading area, and collecting the carrying capacity of the vehicle in the transportation process in real time;
calculating a load fluctuation ratio according to the original load capacity and the load capacity in the transportation process, and determining that the load of the vehicle is abnormal under the condition that the load fluctuation ratio is larger than or equal to a preset fluctuation threshold value;
and alarming the abnormal load of the vehicle according to the abnormal load of the vehicle.
2. The method of claim 1, wherein collecting the original load capacity of the vehicle exiting the loading area comprises:
acquiring a loading and unloading area in the transportation process of the vehicle, and setting up an electronic fence in the loading and unloading area;
and determining the original carrying capacity according to the carrying capacity corresponding to the last piece of position data in the current electronic fence.
3. The method of claim 1, wherein calculating a load variability from the original load capacity and the load capacity on the way to transportation comprises:
under the condition that the vehicle is in a running state, collecting a plurality of continuous load capacity values, and calculating the load fluctuation rate of the vehicle according to the plurality of continuous load capacity values and the original load capacity;
under the condition that the vehicle is in a parking state, collecting the current load capacity value of the vehicle, and calculating the load fluctuation rate of the vehicle according to the current load capacity value and the original load capacity.
4. A method according to claim 3, wherein calculating the load change rate of the vehicle from the plurality of successive load values and the original load value comprises calculating according to the formula:
wherein P represents the load fluctuation ratio, n represents the number of collected continuous load capacity values, M i Load value representing continuous point, M 0 Representing the original load capacity, and mu represents the accuracy of the vehicle-mounted weighing device;
calculating the load change rate of the vehicle according to the current load value and the original load value, wherein the calculation comprises the following formula:
wherein P represents the load change rate, M i Representing the current load value, M 0 Represents the original load capacity and mu represents the accuracy of the vehicle-mounted weighing device.
5. The method of claim 1, wherein after determining the vehicle load anomaly, further comprising:
determining the moment of abnormal load of the vehicle;
taking a preset first period before the moment and a preset second period after the moment as video storage periods;
storing video files shot by a shooting device on the vehicle according to the video storage period;
and storing the video file and license plate number information, driver information and time information corresponding to the video file into a blockchain.
6. The method of claim 5, further comprising, after storing the video file captured by the capturing device on the vehicle according to the video storage period:
extracting a plurality of images from the video file;
inputting the extracted multiple images into a preset event identification model to obtain an identified load change event, wherein the load change event comprises at least one of cargo leakage, cargo falling and illegal loading and unloading.
7. The method of claim 6, wherein alerting for a vehicle load anomaly comprises:
generating voice prompt information according to the determined load abnormality of the vehicle and the identified load change event, and sending the voice prompt information to a driver terminal;
and sending the vehicle load abnormality prompt and the video file to the vehicle-mounted terminal and the cargo owner terminal.
8. A vehicle load abnormality detection device, characterized by comprising:
the collecting module is used for collecting the original carrying capacity of the vehicle when the vehicle exits the loading and unloading area and collecting the carrying capacity of the vehicle in the transportation process in real time;
the judging module is used for calculating the load fluctuation rate according to the original load capacity and the load capacity in the transportation process, and determining that the load of the vehicle is abnormal under the condition that the load fluctuation rate is greater than or equal to a preset fluctuation threshold value;
and the alarm module is used for alarming the abnormal load of the vehicle according to the abnormal load of the vehicle.
9. An electronic device comprising a processor and a memory storing program instructions, the processor being configured, when executing the program instructions, to perform the vehicle load capacity anomaly detection method of any one of claims 1 to 7.
10. A computer readable medium having stored thereon computer readable instructions executable by a processor to implement a method of vehicle load anomaly detection according to any one of claims 1 to 7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310126708.0A CN116026441A (en) | 2023-02-16 | 2023-02-16 | Method, device, equipment and storage medium for detecting abnormal load capacity of vehicle |
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| CN202310126708.0A CN116026441A (en) | 2023-02-16 | 2023-02-16 | Method, device, equipment and storage medium for detecting abnormal load capacity of vehicle |
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| CN116912747A (en) * | 2023-08-04 | 2023-10-20 | 北京中电汇智科技有限公司 | Data processing system based on video identification load foreign matter |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116912747A (en) * | 2023-08-04 | 2023-10-20 | 北京中电汇智科技有限公司 | Data processing system based on video identification load foreign matter |
| CN116912747B (en) * | 2023-08-04 | 2024-04-05 | 北京中电汇智科技有限公司 | Data processing system based on video identification load foreign matter |
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