CN110069749B - Freight car no-load weight estimation method, device and terminal - Google Patents
Freight car no-load weight estimation method, device and terminal Download PDFInfo
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- CN110069749B CN110069749B CN201910287657.3A CN201910287657A CN110069749B CN 110069749 B CN110069749 B CN 110069749B CN 201910287657 A CN201910287657 A CN 201910287657A CN 110069749 B CN110069749 B CN 110069749B
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Abstract
The embodiment of the application provides a method, a device and a terminal for estimating the unloaded weight of a truck, wherein the method for estimating the unloaded weight of the truck comprises the following steps: discretizing a possible value range of the vehicle weight of the target vehicle type, and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other; acquiring vehicle weighing data of a target vehicle type; obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data; constructing a probability distribution map of the vehicle weight; traversing the value range of the vehicle weight in the vehicle weight probability distribution graph from left to right by using an odd-order sliding window to obtain a corresponding table of the ratio of the vehicle weight at the center of the window to the number of vehicles in the window; searching a first appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large; the vehicle weight at the window center position corresponding to the peak of the occupancy ratio is set as the empty weight of the target vehicle type. According to the method and the device, the classified truck dead weight estimation of the large sample can be realized without emptying the goods.
Description
Technical Field
The application relates to the technical field of computers, in particular to a method, a device and a terminal for estimating the unloaded weight of a truck.
Background
The statements in this application as background to the related art related to this application are merely provided to illustrate and facilitate an understanding of the contents of the present application and are not to be construed as an admission that the applicant expressly or putatively admitted the prior art of the filing date of the present application at the first filing date.
The weight of the transported goods is the main object of road freight statistics and is obtained by subtracting the empty weight of the vehicle from the vehicle weight obtained by weighing. In the existing statistical system, regardless of the standard for classifying toll vehicle types on expressways or the standard for classifying common road traffic investigation vehicle types, the vehicle types are classified according to the number of axles, and the corresponding vehicle weights are recorded. The truck can be subjected to field sampling investigation by acquiring the weight of the unloaded vehicle. And respectively counting the empty load weight of the truck according to the number of the shafts to become the basic work of the industry. The truck on-site sampling survey needs a large amount of manpower, the space time range of the survey is relatively limited, and the result cannot comprehensively reflect the empty load weight of the vehicles in the region and also cannot continuously track the change of the empty load weight.
Disclosure of Invention
The embodiment of the application provides a method, a device and a terminal for estimating the empty weight of a truck, and the self-weight estimation of the truck of a large sample can be realized without great manpower investment.
In a first aspect, the present application provides a method for estimating an empty weight of a truck, including:
discretizing a possible value range of the vehicle weight of the target vehicle type, and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other;
acquiring vehicle weighing data of a target vehicle type;
obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data:
constructing a probability distribution map of the vehicle weight;
traversing the value range of the vehicle weight in the vehicle weight distribution diagram from left to right by using an odd-order sliding window to obtain a corresponding table of the ratio of the vehicle weight at the center of the window to the number of vehicles in the window;
searching the first window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large in the corresponding table, and taking the vehicle weight at the window center position corresponding to the ratio peak value as the no-load weight of the target vehicle type.
In a second aspect, an embodiment of the present application provides a device for estimating an empty weight of a truck, including:
the discrete unit is used for discretizing a possible value range of the vehicle weight of the target vehicle type and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other;
the data acquisition unit is used for acquiring vehicle weighing data of a target vehicle type;
the statistical unit is used for obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the acquired vehicle weighing data;
a construction unit for constructing a probability distribution map of the vehicle weight;
the corresponding unit is used for traversing the value range of the vehicle weight in the vehicle weight probability distribution graph from left to right by using an odd-order sliding window to obtain a window center position vehicle weight and vehicle number ratio corresponding table in the window;
and the result acquisition unit is used for searching the first-appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large, and taking the vehicle weight at the window center position corresponding to the ratio peak value as the unloaded weight of the target vehicle type.
In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of any one of the above methods.
In a fourth aspect, an embodiment of the present application provides a terminal, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of any one of the above methods when executing the program.
The embodiment of the application has the following beneficial effects:
according to the method for estimating the empty load weight of the truck, the possible value range of the truck weight of the target truck type is discretized and equally divided into a plurality of continuous equal-interval and non-overlapping truck weight intervals; acquiring vehicle weighing data of a target vehicle type; obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data; constructing a probability distribution map of the vehicle weight; traversing the value range of the vehicle weight in the vehicle weight distribution diagram from left to right by using a sliding window, and constructing a corresponding table of the vehicle weight at the center of the window and the number of vehicles in the window; searching a first appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large; the vehicle weight at the window center position corresponding to the peak of the occupancy ratio is set as the empty weight of the target vehicle type. . The self-weight estimation of the truck with the large sample can be realized without a large amount of manpower.
Drawings
FIG. 1 is a flow chart illustrating a first embodiment of a truck empty weight estimation method of the present application;
FIG. 2 is a diagram illustrating a truck weight distribution of an embodiment of the truck empty weight estimation method according to the present application;
fig. 3 shows an exemplary diagram of a possible value range of the odd-order sliding window traversing the truck weight in the truck empty weight estimation method of the present application;
FIG. 4 is a schematic structural diagram illustrating an embodiment of the truck empty weight estimation device of the present application;
fig. 5 shows a block diagram of a terminal according to an embodiment of the present application;
fig. 6 shows a block diagram of a terminal according to another embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to specific examples, but the present application is not limited thereto. In the following description, different "one embodiment" or "an embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
The embodiment of the application provides a method for estimating the empty weight of a truck, and fig. 1 shows a flowchart of a first embodiment of the method for estimating the empty weight of the truck. Referring to fig. 1, the method for estimating the empty weight of a truck comprises the following steps:
discretizing a possible value range of the vehicle weight of the target vehicle type, and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other;
acquiring vehicle weighing data of a target vehicle type;
obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data;
constructing a vehicle weight probability distribution map;
traversing the value range of the vehicle weight in the vehicle weight distribution diagram from left to right by using an odd-order sliding window to obtain a corresponding table of the ratio of the vehicle weight at the center of the window to the number of vehicles in the window;
and searching the first-appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large, and taking the vehicle weight at the window center position corresponding to the ratio peak value as the no-load weight of the target vehicle type.
In the embodiment of the application, the possible value range of the vehicle weight of the target vehicle type is discretized and equally divided into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other; acquiring vehicle weighing data of a target vehicle type; obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data; on the basis, constructing a vehicle weight probability distribution map; traversing the value range of the vehicle weight in the vehicle weight distribution diagram from left to right by using an odd-order sliding window, and constructing a corresponding table of the ratio of the vehicle weight at the center of the window to the number of vehicles in the window; searching a first appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large; and taking the vehicle weight at the window center position corresponding to the peak of the proportion as the unloaded weight of the target vehicle type. According to the method and the device, the characteristic that the cargo weight difference is larger than the vehicle dead weight difference is utilized to construct the probability distribution of the weight of the truck, and the vehicle weight corresponding to the vehicle number peak in the first sliding window is searched from the minimum vehicle weight to serve as the estimation result of the unloaded vehicle weight. The self-weight estimation of the large-sample truck can be realized without emptying the goods.
In the embodiments of the present application, the steps do not necessarily represent a sequential order. For example, the step "discretizing the possible value range of the vehicle weight of the target vehicle type, equally dividing the possible value range into a plurality of continuous vehicle weight sections with equal intervals and without overlapping" may be interchanged with the step "acquiring the vehicle weight data of the target vehicle type".
In the embodiment of the application, the vehicle weight probability distribution map can be different vehicle weight ratio distribution maps. The horizontal axis represents the vehicle weight, and the vertical axis represents the ratio of the number of vehicles corresponding to the vehicle weight to the total number of vehicles. When the odd-order sliding window traverses the value range of the vehicle weight in the vehicle weight distribution diagram from left to right, the vehicle weight at the center position of the window and the ratio of the number of the vehicles in the window can be obtained, and thus a corresponding table of the ratio of the vehicle weight at the center position of the window and the number of the vehicles in the window can be obtained.
In the embodiment of the application, no special empty weight data of the truck is required to be acquired. Only the vehicle weighing data of the target vehicle type is obtained. It is not necessary to distinguish whether the vehicle weighing data is loaded weighing data or unloaded weighing data. The data source is wide, and special invested personnel is not needed for investigation. In an exemplary embodiment, obtaining vehicle weighing data for a target vehicle type includes at least one of: acquiring vehicle weighing data of a target vehicle type through a high-speed toll station; acquiring vehicle weighing data of a target vehicle type through a traffic axle load survey station; and acquiring vehicle weighing data of the target vehicle type through an overload inspection pre-inspection station. A large amount of vehicle weighing data can be obtained in any of the above-described ways. No special manpower input is required.
In the embodiment of the application, the possible value range of the vehicle weight of the target vehicle type is discretized and equally divided into a plurality of continuous vehicle weight intervals which are equally spaced and not overlapped with each other. Providing a basis for estimating the empty weight of the truck. The interval between the vehicle weight sections can be set as required. For example, the vehicle weight intervals may be 0.5 ton intervals.
In some embodiments, traversing the value range of the vehicle weight in the vehicle weight probability distribution map from left to right by using an odd-order sliding window, and constructing a corresponding table of the ratio of the vehicle weight at the center of the window to the number of vehicles in the window, includes:
constructing an odd-order sliding window;
and traversing the vehicle weight intervals in the vehicle weight probability distribution map from small to large by the sliding window to obtain a corresponding table of the ratio of the vehicle weight at the central position of the sliding window to the number of vehicles in the sliding window.
In the embodiment of the present application, the size of the odd-order sliding window may be determined according to different situations. For example, the size of the odd-order sliding window may be 1, 3, 5, 7, etc., wherein the sliding window with the order of 1 is equivalent to directly finding the first-occurring duty ratio peak on the left side in the vehicle weight probability distribution map.
In some embodiments, the correspondence relationship between the vehicle weight at the center position of the sliding window and the number of vehicles in the sliding window is obtained, and may be, for example, a correspondence table between the vehicle weight at the center position of the sliding window and the number of vehicles in the sliding window. By searching the corresponding table according to the vehicle weight from small to large, the vehicle weight value of the window center position corresponding to the window center position where the number of vehicles appearing for the first time in the sliding window is larger than the peak value can be obtained.
The method of the embodiment of the present application will be described below by taking a six-axle truck of a certain province as an example.
Discretizing a possible value range of the vehicle weight, and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other, for example, referring to fig. 2 and 3, and taking 0.5 ton as an interval.
Processing 2700 thousands of charging data containing vehicle weight information on a certain provincial expressway from 1 to 6 months in 2018 to obtain the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles; on the basis, a vehicle weight probability distribution map can be constructed. See figure 2 for a six-axle truck weight profile. The horizontal axis represents the vehicle weight, and the vertical axis represents the ratio of the number of vehicles corresponding to the vehicle weight to the total number of vehicles.
Referring to fig. 3, an odd-order sliding window is constructed, the sliding window sequentially traverses possible value intervals of the vehicle weights from small to large, and records the vehicle number ratio contained in the corresponding window, so as to obtain a correspondence table of the vehicle weight at the center position of the window and the vehicle number ratio (the ratio of the vehicle number in the window to the total number of the vehicles,%) in the window, wherein the vehicle ratio in the window refers to the sum of the vehicle numbers corresponding to the various vehicle weights contained in the window in the total number of the vehicles.
Searching for the first in-window vehicle weight ratio peak value according to the vehicle weight from small to large in the vehicle weight and vehicle number ratio corresponding table at the window center position to obtain the vehicle weight value at the corresponding window center position, and taking the vehicle weight value at the corresponding window center position as the vehicle no-load weight. Taking the six-axle vehicle as an example, the result shows that the vehicle weight is from small to large, the percentage peak value in the first appearing window is 1.969%, and the corresponding vehicle weight is 16 tons, and then 16 tons is taken as the estimation result of the unloaded weight of the six-axle vehicle in the province. The window position is now as shown in figure 3.
The method of the embodiment of the application is used for processing charging data containing vehicle weight information of 2700 ten thousand of vehicles with various axle numbers on the expressway in some province from 1 to 6 months in 2018, and the obtained average no-load weight of the vehicles with various axle numbers is shown in table 1.
TABLE 1 estimation of average empty weight of truck (ton)
| Vehicle model | 2 |
3 shaft | 4-shaft | 5 shaft | 6 shaft | 7 shaft and above |
| Vehicle weight | 5.1 | 11.0 | 14.5 | 17.0 | 16.0 | 33.0 |
Table 2 shows the average empty weight of trucks of each vehicle type obtained by sampling survey. The sample size for each vehicle model was 200.
TABLE 2 truck average empty weight sample survey results (ton)
| Vehicle model | 2 |
3 shaft | 4-shaft | 5 shaft | 6 shaft | 7 shaft and above |
| Vehicle weight | 4.3 | 10.5 | 12.5 | 16 | 15.5 | 33.0 |
By comparing the data of tables 1 and 2, the two sets of data averaged 8% error. The method of the embodiment of the application can be used for estimating the empty weight of the truck. Because the sample size of the sampling investigation is far smaller than that of the sample size adopted by the application, the result obtained by the method of the embodiment of the application has higher reliability.
The application also discloses a device for estimating the empty weight of the truck, which can realize the method of the embodiment, and the embodiments of the method can be used for explaining the embodiment of the device. Referring to fig. 4, the freight car empty weight estimating apparatus includes:
the discrete unit 10 is used for discretizing a possible value range of the vehicle weight of the target vehicle type and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other;
a data acquisition unit 20 for acquiring vehicle weighing data of a target vehicle type;
the statistical unit 30 is used for obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data;
a construction unit 40 for constructing a probability distribution map of the vehicle weight;
the corresponding unit 50 is used for traversing the value range of the vehicle weight in the vehicle weight probability distribution graph from left to right by using an odd-order sliding window to obtain a window center position vehicle weight and vehicle number in window ratio corresponding table;
and a result obtaining unit 60, configured to search the correspondence table for a peak value of the number of vehicles in the window that appears first from the smallest vehicle weight to the largest vehicle weight, and use the vehicle weight at the center position of the window corresponding to the peak value of the number of vehicles in the window as the empty weight of the target vehicle type.
In the embodiment of the application, the discretization unit 10 discretizes the possible value range of the vehicle weight of the target vehicle type, and equally divides the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and are not overlapped with each other; the data acquisition unit 20 acquires vehicle weighing data of a target vehicle type; the statistical unit 30 obtains the proportion of the number of vehicles in each vehicle weight interval to the total number of vehicles according to the obtained vehicle weighing data; on the basis, the construction unit 40 can construct a probability distribution map of the vehicle weight; the corresponding unit 50 traverses the value range of the vehicle weight in the vehicle weight probability distribution graph from left to right by using an odd-order sliding window to obtain a window center position vehicle weight and vehicle number ratio corresponding table in the window; the result obtaining unit 60 searches for the first occurring peak value of the number of vehicles in the window in the correspondence table from small to large according to the vehicle weight, and takes the vehicle weight at the center position of the window corresponding to the peak value of the number of vehicles in the correspondence table as the unloaded weight of the target vehicle type. According to the method and the device, the characteristic that the cargo weight difference is larger than the self weight difference of the vehicles is utilized, the probability distribution of the weight of the trucks is constructed, the number of the vehicles in the sliding window which appears for the first time is found according to the sequence that the weights of the vehicles are from small to large, and the corresponding weights of the vehicles are used as the estimation result of the unloaded weight of the vehicles. The self-weight estimation of the truck of the large sample can be realized without emptying the truck and manpower investigation.
In an exemplary embodiment, the data acquisition unit 20 acquires vehicle weighing data of a target vehicle type, including at least one of: acquiring vehicle weighing data of a target vehicle type through a high-speed toll station; acquiring vehicle weighing data of a target vehicle type through a traffic axle load survey station; and acquiring vehicle weighing data of the target vehicle type through an overload inspection pre-inspection station. A large amount of vehicle weighing data can be obtained in any of the above-described ways. No special manpower input is required.
In the embodiment of the application, the possible value range of the vehicle weight of the target vehicle type is discretized and equally divided into a plurality of continuous vehicle weight intervals which are equally spaced and not overlapped with each other. Providing a basis for estimating the empty weight of the truck. The interval between the vehicle weight sections can be set as required. For example, the vehicle weight intervals may be 0.5 ton intervals.
In some embodiments, the result obtaining unit 60 obtains the correspondence relationship between the vehicle weight at the center position of the sliding window and the vehicle number ratio in the sliding window, for example, may be a correspondence table in which the result obtaining unit 60 obtains the correspondence relationship between the vehicle weight at the center position of the sliding window and the vehicle number ratio in the sliding window. By searching the correspondence table, the vehicle weight value at the window center position corresponding to the maximum value of the number of vehicles in the sliding window can be obtained.
It is obvious to those skilled in the art that the division of "unit" or "module" in the embodiments of the present application is only a division of one logic function, and there may be another division in actual implementation, for example, multiple "units" or "modules" may be combined or integrated into one "unit" or "module" to implement the corresponding functions. Or one "unit" or "module" is decomposed into a plurality of pieces to realize the corresponding functions together. The "unit" or "module" in the embodiments of the present application may be software and/or hardware that can perform a specific function independently or in cooperation with other components, where the hardware may be, for example, an FPGA (Field-Programmable Gate Array), an IC (Integrated Circuit), and the like, and details thereof are not repeated herein.
The embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to implement the steps of the method of any one of the foregoing embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nano-devices (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
The embodiment of the present application further provides a terminal, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the program, the steps of any of the above-mentioned embodiments of the method are implemented.
Fig. 5 shows a block diagram of a terminal according to an embodiment of the present application. Referring to fig. 5, the terminal includes a processor 510, a memory 520, a camera 530, and a microphone 540.
In this embodiment, the processor 510 is a control center of a computer system, and may be a processor of a physical machine or a processor of a virtual machine. In the embodiment of the present application, the memory 520 stores at least one instruction, and the instruction is loaded and executed by the processor 510 to implement the application control method in the above embodiments. The terminal in the embodiment of the present application includes, but is not limited to, a smart phone, a tablet computer, a laptop computer, and other devices.
In an alternative embodiment of the present application, the camera 530 may include a front camera and may also include a rear camera.
In alternative embodiments of the present application, the microphone 540 may be a first microphone and a second microphone. One of the first microphone and the second microphone may be a primary microphone for receiving sounds of a user's conversation, voice or recording activity, and the other microphone may be a secondary microphone for reducing noise in cooperation with the primary microphone.
Fig. 6 shows a block diagram of a terminal 600 according to another embodiment of the present application. Referring to fig. 6, the terminal 600 includes: a processor 601 and a memory 602.
The processor 601 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The processor 601 may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 601 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state.
The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments of the present application, a non-transitory computer readable storage medium in the memory 602 is used to store at least one instruction for execution by the processor 601 to implement the application control method in embodiments of the present application.
In an optional embodiment of the present application, the terminal 600 further includes: a peripheral interface 603 and at least one peripheral. The processor 601, memory 602, and peripheral interface 603 may be connected by buses or signal lines. Various peripheral devices may be connected to the peripheral interface 603 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of a display screen 604, a camera 605, an audio circuit 606, and a power supply 607.
The peripheral interface 603 may be used to connect at least one peripheral related to I/O (Input/Output) to the processor 601 and the memory 602. In some embodiments of the present application, the processor 601, memory 602, and peripheral interface 603 are integrated on the same chip or circuit board; in some other embodiments of the present application, any one or both of the processor 601, the memory 602, and the peripheral interface 603 may be implemented on separate chips or circuit boards. The embodiment of the present application is not particularly limited to this.
The display screen 604 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 604 is a touch display screen, the display screen 604 also has the ability to capture touch signals on or over the surface of the display screen 604. The touch signal may be input to the processor 601 as a control signal for processing. At this point, the display screen 604 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments of the present application, the display screen 604 may be one, and is provided as a front panel of the terminal 600; in other embodiments of the present application, the display screens 604 may be at least two, respectively disposed on different surfaces of the terminal 600 or in a folding design; in still other embodiments of the present application, the display 604 may be a flexible display disposed on a curved surface or a folded surface of the terminal 600. Even further, the display screen 604 may be arranged in a non-rectangular irregular pattern, i.e. a shaped screen. The Display screen 604 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), and the like.
The camera 605 is used to capture images or video. Optionally, the camera 605 includes a front camera and a rear camera. Generally, a front camera is disposed at a front panel of the terminal, and a rear camera is disposed at a rear surface of the terminal. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments of the present application, camera 605 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.
Audio circuitry 606 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 601 for processing. For the purpose of stereo sound collection or noise reduction, a plurality of microphones may be provided at different portions of the terminal 600. The microphone may also be an array microphone or an omni-directional pick-up microphone.
Power supply 607 is used to provide power to the various components in terminal 600. The power supply 607 may be ac, dc, disposable or rechargeable. When power supply 607 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. The wired rechargeable battery is a battery charged through a wired line, and the wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery may also be used to support fast charge technology.
The block diagram of the terminal structure shown in the embodiments of the present application does not constitute a limitation to the terminal 600, and the terminal 600 may include more or less components than those shown, or combine some components, or adopt a different arrangement of components.
In this application, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or order; the term "plurality" means two or more unless expressly limited otherwise. The terms "mounted," "connected," "fixed," and the like are to be construed broadly, and for example, "connected" may be a fixed connection, a removable connection, or an integral connection; "coupled" may be direct or indirect through an intermediary. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
In the description of the present application, it is to be understood that the terms "upper", "lower", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the referred device or unit must have a specific direction, be configured and operated in a specific orientation, and thus, should not be construed as limiting the present application.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (7)
1. A truck empty weight estimation method comprises the following steps:
discretizing a possible value range of the vehicle weight of the target vehicle type, and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other;
acquiring vehicle weighing data of a target vehicle type;
obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the obtained vehicle weighing data:
constructing a probability distribution map of the vehicle weight;
traversing the value range of the vehicle weight in the vehicle weight probability distribution diagram from left to right by using an odd-order sliding window to obtain a corresponding table of the vehicle weight at the center of the window and the number of vehicles in the window, wherein the number of the vehicles corresponding to various vehicle weights in the vehicle ratio indicating window in the window is the sum of the ratios of the total number of the vehicles;
and searching the first-appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large, and taking the vehicle weight at the window center position corresponding to the ratio peak value as the no-load weight of the target vehicle type.
2. The method of claim 1, wherein obtaining vehicle weighing data for a target vehicle type comprises at least one of:
acquiring vehicle weighing data of a target vehicle type through a high-speed toll station;
acquiring vehicle weighing data of a target vehicle type through a traffic axle load survey station;
and acquiring vehicle weighing data of the target vehicle type through an overload inspection pre-inspection station.
3. The method of claim 1, wherein the vehicle weight intervals are spaced at 0.5 ton intervals.
4. The method of claim 1, wherein traversing the range of values of the vehicle weight in the vehicle weight probability distribution map from left to right using an odd-order sliding window to construct a window center position vehicle weight to number of vehicles in the window ratio correspondence table comprises:
constructing an odd-order sliding window;
and traversing the vehicle weight intervals in the vehicle weight probability distribution map from small to large by the sliding window in sequence to obtain a corresponding relation table of the vehicle weight at the central position of the sliding window and the number of vehicles in the sliding window.
5. An empty weight estimation device for a truck, comprising:
the discrete unit is used for discretizing a possible value range of the vehicle weight of the target vehicle type and equally dividing the possible value range into a plurality of continuous vehicle weight intervals which are equally spaced and do not overlap with each other;
the data acquisition unit is used for acquiring vehicle weighing data of a target vehicle type;
the statistical unit is used for obtaining the proportion of the number of vehicles in each vehicle weight interval to the total number of the vehicles according to the acquired vehicle weighing data;
a construction unit for constructing a probability distribution map of the vehicle weight;
the corresponding unit is used for traversing the value range of the vehicle weight in the vehicle weight probability distribution graph from left to right by using an odd-order sliding window to obtain a window center position vehicle weight and vehicle number ratio corresponding table in the window, wherein the vehicle number ratio in the window refers to the sum of the vehicle numbers corresponding to various vehicle weights contained in the window and the vehicle number ratio in the total number of the vehicles;
and the result acquisition unit is used for searching the first-appearing window vehicle number ratio peak value in the corresponding table according to the vehicle weight from small to large, and taking the vehicle weight at the window center position corresponding to the ratio peak value as the unloaded weight of the target vehicle type.
6. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
7. A terminal comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1-4 are implemented when the program is executed by the processor.
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| CN101303802A (en) * | 2008-06-26 | 2008-11-12 | 吉林大学 | Method and system for on-line automatically beforehand judgment of overloading wagon |
| CN103106116A (en) * | 2012-12-31 | 2013-05-15 | 国家计算机网络与信息安全管理中心 | Dynamic resource management method based on sliding window |
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| CN103106116A (en) * | 2012-12-31 | 2013-05-15 | 国家计算机网络与信息安全管理中心 | Dynamic resource management method based on sliding window |
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