Tailings transport control method and apparatus, and electronic device and storage medium

Abstract

Disclosed in the present application are a tailings transport control method and apparatus, and an electronic device and a storage medium. The method comprises: separately acquiring weight values measured by a first weighbridge and a second weighbridge; on the basis of the weight values measured by the first weighbridge and the second weighbridge, calculating an actual load weight of a truck; acquiring a truck image captured in a truck washing region, and performing recognition on the truck image to determine whether the truck is a legitimate vehicle; when it is determined that the truck is a legitimate vehicle, sending a truck washing signal to the truck washing region, and updating a cumulative washing count of the truck for the day; and associating all the actual load weights of the truck for the day with the current cumulative washing count of the truck, in order to generate a tailings transport data chart of the truck. The present application solves the technical problems in the prior art of it not being possible to accurately acquire a daily tailings outward transport weight, and it not being convenient to acquire the transport status of each laterite nickel ore tailings transport truck.

Description

Tailings transportation control method and device, electronic equipment and storage medium TECHNICAL FIELD

[0001] The present application relates to the technical field of laterite nickel ore tailings transportation, in particular to a tailings transportation method and device, electronic equipment and storage medium. BACKGROUND

[0002] After the laterite nickel ore is treated by using the hydrometallurgy technology, tailings will be obtained, and the tailings also contain a large amount of valuable metal elements, so the tailings are generally treated separately.

[0003] At present, the treatment of the laterite nickel ore and the treatment of the tailings are generally carried out separately, that is, after the treatment of the laterite nickel ore is completed, the tailings are transported to other places for treatment. In the prior art, the tailings are generally transported to the tailings treatment point by a truck. Before the truck leaves the laterite nickel ore treatment point, the weight of the truck is detected by a weight indicator, and then a worker reads the weight indicator reading and records the total number of shipments for subsequent cost settlement. However, since the weight of the truck is not known before the truck passes through the weight indicator, the daily tailings shipment weight cannot be accurately calculated. Moreover, since the total number of shipments or the weight of the truck is generally counted only on the same day, the worker cannot know the specific transportation situation of each truck, which is not convenient for subsequent analysis of the truck fleet.

[0004] SUMMARY

[0005] The present application aims to overcome the above technical deficiencies and provide a tailings transportation control method and device, electronic equipment and storage medium, which can accurately obtain the daily tailings shipment weight and conveniently obtain the transportation situation of each laterite nickel ore tailings transportation truck.

[0006] To achieve the above technical purpose, the present application adopts the following technical scheme:

[0007] In a first aspect, the present application provides a tailings transportation control method, comprising the following steps:

[0008] Respectively obtaining the weight values measured by a first weight indicator and a second weight indicator, wherein the first weight indicator is used to measure the weight of the truck before loading, and the second weight indicator is used to measure the weight of the truck after loading;

[0009] Based on the weight values measured by the first weight indicator and the second weight indicator, the actual loading amount of the truck is calculated;

[0010] Obtaining the truck image photographed by a washing area, identifying the truck image to determine whether the truck is a legal vehicle;

[0011] when determining that the truck is a legal vehicle, sending a car washing signal to the car washing area, and updating the cumulative number of car washings of the truck on the day;

[0012] associating all actual loading amounts of the truck on the day with the current cumulative number of car washings of the truck to generate a tailings transportation data graph of the truck.

[0013] In some embodiments, the method further comprises:

[0014] When the truck finishes car washing, it is determined whether a truck exit signal sent by the access control system is received, and if not, the cumulative number of car washings of the truck on the day is locked until the truck exit signal is received.

[0015] In some embodiments, the method further comprises:

[0016] The truck image captured by the car washing area is obtained, and the truck image is processed to obtain a region of interest in the truck image, wherein the region of interest has a license plate of the truck.

[0017] After preprocessing the region of interest, the region of interest is input into a pre-established image recognition model to identify the license plate number of the truck.

[0018] Based on the license plate number of the truck, it is determined whether the truck is a legal vehicle.

[0019] In some embodiments, the preprocessing of the region of interest is performed in the following manner:

[0020] The region of interest is sequentially subjected to grayscale and binarization processing;

[0021] The region of interest after binarization processing is subjected to enhancement processing.

[0022] In some embodiments, the image recognition model is a deep learning model or a machine learning model.

[0023] In some embodiments, based on the license plate number of the truck, it is determined whether the truck is a legal vehicle, comprising:

[0024] In the pre-established license plate number library, it is determined whether the license plate number of the truck exists, if it exists, it is determined that the truck is a legal vehicle, otherwise it is determined that the truck is an illegal vehicle.

[0025] In some embodiments, the method further comprises:

[0026] When it is determined that the truck is an illegal vehicle, an alarm signal is output to the car washing area so that the car washing area gives an alarm prompt.

[0027] In a second aspect, the application further provides a tailings transportation control device, comprising:

[0028] a weight acquisition module configured to acquire weight values measured by a first weighbridge and a second weighbridge, respectively, wherein the first weighbridge is configured to measure the weight of the truck before loading, and the second weighbridge is configured to measure the weight of the truck after loading;

[0029] an actual weight calculation module configured to calculate the actual loading amount of the truck based on the weight values measured by the first weighbridge and the second weighbridge;

[0030] a vehicle judgment module configured to acquire a truck image captured by the car washing area, and identify the truck image to determine whether the truck is a legal vehicle;

[0031] a vehicle cumulative car washing frequency updating module configured to send a car washing signal to the car washing area and update the cumulative car washing frequency of the truck for the day when it is determined that the truck is a legal vehicle;

[0032] a tailings transportation data generation module configured to associate all actual loading amounts of the truck for the day with the current cumulative car washing frequency of the truck to generate tailings transportation data of the truck.

[0033] In a third aspect, the application further provides an electronic device, comprising a processor and a memory;

[0034] The memory has stored thereon a computer program which can be executed by the processor;

[0035] The processor implements the steps in the tailings transportation control method as described above when executing the computer program.

[0036] In a fourth aspect, the application further provides a computer readable storage medium, which stores one or more programs which can be executed by one or more processors to implement the steps in the tailings transportation control method as described above.

[0037] Compared with the prior art, the tailing transportation control method, device, electronic equipment and storage medium provided by the application first acquire weight values measured by a first load cell and a second load cell, respectively, wherein the first load cell is used to measure the weight of a truck before loading, and the second load cell is used to measure the weight of the truck after loading; then, based on the weight values measured by the first load cell and the second load cell, the actual loading amount of the truck is calculated; then, a truck image captured by a washing area is acquired, and the truck image is identified to determine whether the truck is a legal vehicle; then, when it is determined that the truck is a legal vehicle, a washing signal is sent to the washing area, and the cumulative washing frequency of the truck on the same day is updated; finally, all actual loading amounts of the truck on the same day are associated with the current cumulative washing frequency of the truck to generate a tailing transportation data graph of the truck. The application can accurately acquire the weight of the tailings actually loaded by the truck, and can also classify and count data of each vehicle to generate a tailing transportation data graph of the truck, so that the staff can know the specific transportation situation of each truck, thereby facilitating subsequent adjustment of the vehicle fleet. BRIEF DESCRIPTION OF DRAWINGS

[0038] FIG. 1 is a flowchart of a tailing transportation control method provided by an embodiment of the application;

[0039] FIG. 2 is a flowchart of step S130 in the tailing transportation control method provided by an embodiment of the application;

[0040] FIG. 3 is a schematic block diagram of a tailing transportation control device provided by an embodiment of the application;

[0041] FIG. 4 is a schematic block diagram of a computer device provided by an embodiment of the application. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical scheme and advantages of the application more clear, the application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application.

[0043] Please refer to FIG. 1, which is a flowchart of a tailing transportation control method provided by an embodiment of the application. The tailing transportation control method is applied to a server (which can also be understood as an upper computer), which is in communication connection with a first load cell, a second load cell, a shooting device of a washing area and a washing device of the washing area.

[0044] Please refer to FIG. 1, the method comprises steps S110-S150.

[0045] S110, acquire weight values measured by a first load cell and a second load cell, respectively, wherein the first load cell is used to measure the weight of a truck before loading, and the second load cell is used to measure the weight of the truck after loading.

[0046] In the embodiment, in order to avoid the problem that the truck weight statistics is inaccurate at present, after the truck enters the construction site, the empty truck weight of the truck is measured by the first loadometer, and then the weight of the truck after loading is measured by the second loadometer after the truck is fully loaded, so that the actual loading weight of the truck can be calculated by the two weight data, thereby avoiding the problem of relying on experience to estimate the weight.

[0047] S120, calculate the actual loading capacity of the truck based on the weight values measured by the first loadometer and the second loadometer.

[0048] In the embodiment, when the weight values measured by the first loadometer and the second loadometer are obtained, the actual loading capacity of the truck can be obtained according to the difference between the two measured weights.

[0049] S130, obtain the truck image shot by the car washing area, and identify the truck image to determine whether the truck is a legal vehicle.

[0050] In the embodiment, the construction site of hydrometallurgy is relatively dirty, and there is a lot of sludge, so the vehicle needs to be washed before it leaves the construction site. In the prior art, the car washing area generally keeps the faucet open, and directly flushes when the truck arrives, which undoubtedly wastes water resources, and some illegal vehicles may also come to wash the car, such as some vehicles that have not been registered, and in extreme cases, illegal vehicles may also come to pretend to transport tailings. Therefore, in order to avoid property loss, the application first determines the legality of the truck when it arrives at the car washing area, thereby avoiding the occupation of water resources by illegal vehicles or illegal use of tailings.

[0051] S140, when it is determined that the truck is a legal vehicle, a car washing signal is sent to the car washing area, and the cumulative car washing times of the truck on the same day are updated.

[0052] In the embodiment, since the truck will be washed every time it transports, the application embodiment records the number of car washes to represent the cumulative number of truck trips on the same day, thereby facilitating the staff to know the specific operation of each truck.

[0053] S150, associate all actual loading capacities of the truck on the same day with the current cumulative number of car washes of the truck to generate a tailings transportation data graph of the truck.

[0054] In the embodiment, in order to facilitate data analysis of a single truck, all actual loading capacities of the truck on the same day are associated with the number of truck trips, and are integrated in a tailings transportation data graph, so that the staff can easily know the transportation capacity of the truck every day, and then the whole truck fleet can be adjusted according to the data.

[0055] The embodiment of the application first acquires the weight values measured by the first and second load cells respectively, wherein the first load cell is used to measure the weight of the truck before loading, and the second load cell is used to measure the weight of the truck after loading; then, based on the weight values measured by the first and second load cells, the actual loading amount of the truck is calculated; then, the truck image captured by the washing area is acquired, and the truck image is identified to determine whether the truck is a legal vehicle; then, when it is determined that the truck is a legal vehicle, a truck washing signal is sent to the washing area, and the cumulative washing frequency of the truck on the same day is updated; finally, all the actual loading amounts of the truck on the same day are associated with the current cumulative washing frequency of the truck to generate a tail residue transportation data graph of the truck. The actual loading weight of the tail residue of the truck can be accurately obtained, and data classification and statistics can be performed on each vehicle to generate a tail residue transportation data graph of the truck, so that the specific transportation situation of each truck can be known by the staff, so as to facilitate subsequent adjustment of the vehicle fleet.

[0056] In some embodiments, the step S120 specifically comprises:

[0057] The weight value measured by the second load cell is subtracted from the weight value measured by the first load cell to obtain the actual loading amount of the truck.

[0058] In the embodiment, since the first load cell measures the empty truck weight and the second load cell measures the weight after loading, the actual loading amount of the truck can be directly obtained by the difference between the weights measured by the two load cells, thereby ensuring the accuracy of the data.

[0059] In some embodiments, referring to FIG. 2, the step S130 specifically comprises:

[0060] S131, acquiring the truck image captured by the washing area, processing the truck image to obtain a region of interest in the truck image, wherein the region of interest has the license plate of the truck;

[0061] S132, after preprocessing the region of interest, inputting the region of interest into a pre-established image recognition model to identify the license plate number of the truck;

[0062] S133, judging whether the truck is a legal vehicle based on the license plate number of the truck.

[0063] In the embodiment, in order to automatically determine whether the truck is illegal, the region of interest of the truck is first automatically identified, then the region of interest is preprocessed to enhance the region of interest, then the pre-trained complete image recognition model is used to identify the license plate number in the region of interest, and finally the vehicle illegal judgment is performed according to the identified license plate number.

[0064] In some embodiments, the manner of preprocessing the region of interest is:

[0065] gray-scale processing and binarization processing are sequentially performed on the region of interest;

[0066] enhancement processing is performed on the region of interest after the binarization processing.

[0067] In this embodiment, because the final recognition is generally a black license plate number, the color image can be converted into a gray-scale image, the image dimension is reduced, and the processing speed is improved. Next, the image elements are binarized to highlight the text to be recognized, which can improve the subsequent recognition rate. Second, the image is enhanced by contrast stretching, improving resolution, and other operations to enhance the contrast and clarity of the image, further improving the recognition rate.

[0068] In some embodiments, the image recognition model is a deep learning model or a machine learning model.

[0069] The machine learning model can include but is not limited to a linear regression model, a ridge regression model, a support vector regression model, a support vector machine, a decision tree, a fully connected neural network, a recurrent neural network, etc. The deep learning model can include but is not limited to a convolutional neural network, a fully convolutional neural network, a residual network, etc. In this embodiment, the image recognition model uses a fully convolutional neural network model, such as a V-Net neural network model, a SN neural network model, a MSN neural network model, etc.

[0070] In some embodiments, the step S133 specifically includes:

[0071] In the pre-established license plate number library, it is determined whether the license plate number of the truck exists. If it exists, the truck is determined to be a legal vehicle, otherwise the truck is determined to be an illegal vehicle.

[0072] In this embodiment, a license plate number library is pre-established, and the license plate numbers of legal vehicles are registered in the license plate number library. Therefore, after obtaining the license plate number of the truck, it is first determined whether the license plate exists in the license plate number library. If it exists, the truck is a legal vehicle, otherwise the truck is an illegal vehicle.

[0073] In some embodiments, the method further includes:

[0074] When the truck is determined to be an illegal vehicle, an alarm signal is output to the car washing area to make the car washing area issue an alarm prompt.

[0075] In the embodiment, when the truck is an illegal vehicle, an alarm signal is output to the car washing area to send an alarm prompt, such as an alarm sound, to prompt the staff to check the vehicle, so as to avoid illegal vehicles from entering the tailings and thus avoid unnecessary property losses.

[0076] In some embodiments, the method further comprises:

[0077] When the truck has finished washing, it is determined whether a truck exit signal sent by the access control system is received. If not, the cumulative number of truck washings of the truck on the day is locked until the truck exit signal is received.

[0078] In the embodiment, since manual measurement of the number of truck trips is currently used, some trucks may pass through the load detector and then directly pass through the load detector again without leaving the construction site. At this time, if the staff are unaware, false statistics may occur, which may cause economic losses. Therefore, in order to avoid such a situation, a truck exit detection mechanism is provided in the embodiment. That is, when the truck has finished washing, if it exits normally, the access control detection will be triggered. When the access control detects that the truck has exited, a truck exit signal is generated. Therefore, it can be determined that the truck has exited according to the truck exit signal. At this time, the next time the truck enters can be waited for. When the access control system has not detected that the truck has exited, the cumulative number of truck washings of the truck at present is frozen, that is, the cumulative number of truck trips of the truck on the day is frozen. At this time, even if the truck passes through the load detector again or is washed again, the cumulative number of truck washings cannot be updated. Until the access control system detects that the truck has exited, the cumulative number of truck trips of the truck on the day is unlocked. In this way, false statistics caused by the truck not leaving the construction site and passing through the load detector multiple times can be avoided.

[0079] It can be seen that the embodiment of the method can accurately obtain the actual weight of the tailings loaded by the truck, and can classify and count the data of each truck to generate a tailings transportation data graph of the truck, so that the staff can know the specific transportation situation of each truck, so as to adjust the truck fleet in the future.

[0080] The application also provides a tailings transportation control device for executing any of the embodiments of the tailings transportation control method, and the tailings transportation control device is applied to a host computer which is in communication connection with an engine control device. Specifically, please refer to FIG. 5, which is a schematic block diagram of the tailings transportation control device 100 provided by the application.

[0081] As shown in Figure 5, the tailings transportation control device 100 comprises a weight acquisition module 110, an actual weight calculation module 120, a vehicle judgment module 130, a vehicle cumulative washing frequency updating module 140 and a tailings transportation data generation module 150.

[0082] The weight acquisition module 110 is configured to acquire the weight values measured by the first and second load scales, respectively, wherein the first load scale is used to measure the weight of the truck before loading, and the second load scale is used to measure the weight of the truck after loading.

[0083] The actual weight calculation module 120 is configured to calculate the actual loading amount of the truck based on the weight values measured by the first and second load scales.

[0084] The vehicle judgment module 130 is configured to acquire the truck image captured by the washing area, identify the truck image, and determine whether the truck is a legal vehicle.

[0085] The vehicle cumulative washing frequency updating module 140 is configured to send a washing signal to the washing area when it is determined that the truck is a legal vehicle, and update the cumulative washing frequency of the truck on the same day.

[0086] The tailings transportation data generation module 150 is configured to associate all the actual loading amounts of the truck on the same day with the current cumulative washing frequency of the truck, so as to generate a tailings transportation data graph of the truck.

[0087] In this embodiment, first, the weight values measured by the first and second load scales are acquired, respectively, wherein the first load scale is used to measure the weight of the truck before loading, and the second load scale is used to measure the weight of the truck after loading; then, the actual loading amount of the truck is calculated based on the weight values measured by the first and second load scales; thereafter, the truck image captured by the washing area is acquired, the truck image is identified, and it is determined whether the truck is a legal vehicle; thereafter, when it is determined that the truck is a legal vehicle, a washing signal is sent to the washing area, and the cumulative washing frequency of the truck on the same day is updated; finally, all the actual loading amounts of the truck on the same day are associated with the current cumulative washing frequency of the truck, so as to generate a tailings transportation data graph of the truck. The actual loading weight of the tailings of the truck can be accurately acquired, and the data of each vehicle can be classified and counted, so as to generate a tailings transportation data graph of the truck, which facilitates the staff to know the specific transportation situation of each truck, so as to adjust the vehicle fleet subsequently.

[0088] It should be noted that the unit referred to in the present application refers to a series of computer program instruction segments capable of completing a certain function, and is more suitable for describing the execution process of tailings transportation control than the program. The specific implementation of each unit will be described in the corresponding method embodiment above, which will not be described here.

[0089] In some embodiments, the device further comprises an egress detection module configured to determine whether a truck egress signal sent by an access control system is received after the truck is washed, and if not, lock the cumulative number of times of washing the truck on the day until the truck egress signal is received.

[0090] In some embodiments, the actual weight calculation module 120 is specifically configured to:

[0091] Subtract the weight value measured by the first weighbridge from the weight value measured by the second weighbridge to obtain the actual loading amount of the truck.

[0092] In some embodiments, the vehicle determination module 130 is specifically configured to:

[0093] Obtain a truck image captured by a washing area, and process the truck image to obtain a region of interest in the truck image, wherein the region of interest has a license plate of the truck.

[0094] After preprocessing the region of interest, input the region of interest into a pre-established image recognition model to identify the license plate number of the truck.

[0095] Determine whether the truck is a legal vehicle based on the license plate number of the truck.

[0096] In some embodiments, the preprocessing of the region of interest is performed in the following manner:

[0097] The region of interest is sequentially subjected to grayscale processing and binary processing.

[0098] The region of interest after the binary processing is subjected to enhancement processing.

[0099] In some embodiments, the image recognition model is a deep learning model or a machine learning model.

[0100] In some embodiments, the determination of whether the truck is a legal vehicle based on the license plate number of the truck comprises:

[0101] Searching a pre-established license plate number database for whether the license plate number of the truck exists, and if so, determining that the truck is a legal vehicle, otherwise determining that the truck is an illegal vehicle.

[0102] In some embodiments, the device further comprises an alarm module configured to output an alarm signal to the washing area when it is determined that the truck is an illegal vehicle, so that the washing area issues an alarm prompt.

[0103] The tailings transportation control device can be implemented in the form of a computer program, which can run on an electronic device as shown in FIG. 6.

[0104] Referring to FIG. 6, FIG. 6 is a schematic block diagram of a computer device provided in an embodiment of the present application. The electronic device 500 is a host computer or a server.

[0105] Referring to FIG. 6, the electronic device 500 includes a processor 502, a storage and a network interface 505 connected through a device bus 501, wherein the storage can include a storage medium 503 and an internal storage 504.

[0106] The storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, can cause the processor 502 to perform the tailings transportation control method.

[0107] The processor 502 is configured to provide computing and control capabilities to support the operation of the entire electronic device 500.

[0108] The internal storage 504 provides an environment for the execution of the computer program 5032 in the storage medium 503, and the computer program 5032, when executed by the processor 502, can cause the processor 502 to perform the tailings transportation control method.

[0109] The network interface 505 is configured to perform network communication, such as providing transmission of data information, etc. Those skilled in the art can understand that the structure shown in FIG. 6 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the electronic device 500 to which the scheme of the present application is applied. The specific electronic device 500 can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0110] The processor 502 is configured to run the computer program 5032 stored in the storage to implement the tailings transportation control method disclosed in the embodiments of the present application.

[0111] Those skilled in the art can understand that the embodiment of the computer device shown in FIG. 6 does not constitute a limitation on the specific structure of the computer device. In other embodiments, the computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement. For example, in some embodiments, the computer device can only include a storage and a processor, and in such embodiments, the structure and function of the storage and the processor are consistent with those of the embodiment shown in FIG. 6, which will not be described here.

[0112] It should be understood that, in the embodiments of this application, the processor 502 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0113] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the tailings transportation control method disclosed in the embodiments of this application.

[0114] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Units with the same function may be grouped into one unit. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, or it may be an electrical, mechanical, or other form of connection.

[0116] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e., may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0117] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0118] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a storage medium. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that contributes to the present application, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for making an electronic device (which can be a personal computer, a background server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), magnetic disk or optical disk, and various program code storage media.

[0119] The specific embodiments of the present application described above do not constitute a limitation on the scope of protection of the present application. Any various other corresponding changes and modifications made according to the technical concept of the present application shall be included in the scope of protection of the claims of the present application.

Claims

1. A tailings transport control method, characterized by, The method comprises the following steps: respectively acquiring weight values measured by a first load cell and a second load cell, wherein the first load cell is used to measure the weight of the truck before loading, and the second load cell is used to measure the weight of the truck after loading; calculating the actual loading amount of the truck based on the weight values measured by the first load cell and the second load cell; acquiring a truck image captured by a washing area, and identifying the truck image to determine whether the truck is a legal vehicle; when it is determined that the truck is a legal vehicle, sending a washing signal to the washing area, and updating the cumulative washing frequency of the truck on the same day; associating all actual loading amounts of the truck on the same day with the current cumulative washing frequency of the truck to generate tailings transportation data of the truck.

2. The tailings transport control method of claim 1, wherein, Further comprising: after the truck is washed, determining whether a truck exit signal sent by an access control system is received, and if not, locking the cumulative washing frequency of the truck on the same day until the truck exit signal is received.

3. The tailings transport control method of claim 1, wherein, The step of acquiring a truck image captured by a washing area, and identifying the truck image to determine whether the truck is a legal vehicle comprises: acquiring a truck image captured by a washing area, and processing the truck image to obtain a region of interest in the truck image, wherein the region of interest has a license plate of the truck; after preprocessing the region of interest, inputting the region of interest into a pre-established image recognition model to identify the license plate number of the truck; based on the license plate number of the truck, determining whether the truck is a legal vehicle.

4. The tailings transport control method of claim 3, wherein, The preprocessing manner of the region of interest is: sequentially performing grayscale processing and binaryzation processing on the region of interest; performing enhancement processing on the region of interest after the binaryzation processing.

5. The tailings transport control method of claim 3, wherein, The image recognition model is a deep learning model or a machine learning model.

6. The tailings transport control method of claim 3, wherein, The step of determining whether the truck is a legal vehicle based on the license plate number of the truck comprises: searching a pre-established license plate number library to determine whether the license plate number of the truck exists, and if so, determining that the truck is a legal vehicle, otherwise, determining that the truck is an illegal vehicle.

7. The tailings transport control method of claim 1, wherein Further comprising: when it is determined that the truck is an illegal vehicle, outputting an alarm signal to the washing area to make the washing area give an alarm prompt.

8. A tailings transport control apparatus, characterized by, The method comprises: a weight acquisition module configured to respectively acquire weight values measured by a first load cell and a second load cell, wherein the first load cell is used to measure the weight of the truck before loading, and the second load cell is used to measure the weight of the truck after loading; an actual weight calculation module configured to calculate the actual loading amount of the truck based on the weight values measured by the first load cell and the second load cell; a vehicle determination module configured to acquire a truck image captured by a washing area, and identify the truck image to determine whether the truck is a legal vehicle; a vehicle cumulative washing frequency updating module configured to, when it is determined that the truck is a legal vehicle, send a washing signal to the washing area, and update the cumulative washing frequency of the truck on the same day; The tailings transportation data generation module is configured to associate all actual loading amounts of the truck on the same day with a current cumulative washing number of the truck to generate a tailings transportation data graph of the truck.

9. An electronic device, comprising: The tailings transportation control method comprises the following steps: a processor and a memory; the memory stores a computer program executable by the processor; the processor executes the computer program to implement the steps in the tailings transportation control method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The tailings transportation control method comprises the following steps: a processor and a memory; the memory stores a computer program executable by the processor; the processor executes the computer program to implement the steps in the tailings transportation control method according to any one of claims 1-7.

Images