CN109002421B - Muck truck transportation earth square number statistical method, muck truck transportation earth square number statistical system, muck truck transportation earth square number statistical server and storage medium - Google Patents
Muck truck transportation earth square number statistical method, muck truck transportation earth square number statistical system, muck truck transportation earth square number statistical server and storage mediumDownload PDFInfo
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Abstract
Description
Technical Field
The invention relates to the technical field of muck transportation management, in particular to a muck truck transportation earth square number statistical method, a muck truck transportation earth square number statistical system, a background server and a computer readable storage medium.
Background
The slag car, also called as a soil pulling car and a slag transport car, is not specific to which car, but refers to a truck for transporting building materials such as sand and stone.
The existing muck truck transport earth square number adopts a manual statistics mode, manual statistics is mostly judged through artificial subjective experience, the existing mode of earth square number statistics needs manpower firstly, unfairness or statistics errors possibly exist secondly, time and labor are consumed thirdly, and data statistics management is inconvenient.
Disclosure of Invention
The invention mainly aims to provide a method and a system for counting the number of earth transportation parties of a muck truck, a background server and a computer readable storage medium, and aims to solve the technical problem of how to realize automatic counting of the number of earth transportation parties of the muck truck.
In order to achieve the purpose, the invention provides a method for counting the earth transportation square number of a muck truck, which comprises the following steps:
when the muck truck transports muck and enters a field, acquiring a license plate image and a rear carriage image of the entering muck truck by using image acquisition equipment;
identifying license plate numbers of license plate images of the entering muck trucks, and determining entering cars and entering time thereof; comparing the image characteristics of the rear compartment image of the incoming muck truck with the characteristic database to determine a first earth number carried by the incoming muck truck;
when the muck truck unloads muck and leaves the field, acquiring a license plate image and a rear carriage image of the left muck truck by using image acquisition equipment;
identifying license plate numbers of license plate images of the discharged muck trucks, and determining discharged trucks and the discharge time thereof; comparing the image characteristics of the rear compartment image of the outgoing residue soil vehicle with the characteristic database to determine a second earth number carried by the outgoing vehicle;
and determining the actual carrying earth number of the muck vehicle in the same transport vehicle number based on the first earth number and the second earth number of the same muck vehicle, and generating a statistical record of the carrying earth number of the muck vehicle.
Optionally, the statistical method for the number of earth transportation squares of the muck truck further includes:
before image feature comparison, taking images of the back compartments of the muck trucks under different carrying earthwork numbers as learning samples, and performing feature training by adopting a machine learning algorithm to obtain corresponding image features of the back compartments under different carrying earthwork numbers and form a feature database;
and when image characteristics are compared, extracting image characteristics of the image of the rear compartment of the muck truck collected on site and comparing the image characteristics with the characteristic database so as to determine the carrying earth volume of the current muck truck.
Optionally, the statistical method for the number of earth transportation squares of the muck truck further includes:
when the muck truck transports muck and enters a field, collecting the carrying weight of the slag truck entering the field through a weighbridge;
determining the type of the residue soil carried by the incoming residue soil truck based on the carrying weight and the carrying earthwork number of the incoming residue soil truck, wherein the type of the residue soil comprises rocks and silt;
and when the type of the residue carried by the entering residue soil vehicle is rock, correcting the carrying earth volume of the entering residue soil vehicle based on a preset earth volume correction coefficient and carrying weight.
Optionally, the preset manner of the earthwork correction coefficient includes:
the method comprises the steps of obtaining the carrying weight and the carrying earthwork number of each transport train number of the same entering muck vehicle for transporting rocks, and setting an earthwork correction coefficient based on the following formula:
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, bi The number of the carrying earthwork of the ith approach transportation is shown, and n is the total number of the approach transportation vehicles.
Optionally, the correcting the number of the carrying earthwork of the incoming muck truck based on a preset earthwork correction coefficient and a carrying weight includes:
calculating the theoretical carrying earth number of each transport train number of the incoming muck truck based on the following formula, and judging whether the difference value between the theoretical carrying earth number and the incoming carrying earth number exceeds a preset error rate or not;
if yes, correcting the carrying earth number of the muck truck entering the field according to the theoretical carrying earth number, otherwise, not correcting;
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, Bi And the theoretical carrying earth volume of the ith approach transportation is shown.
Further, in order to achieve the above object, the present invention further provides a background server, where the background server includes a memory, a processor, and a muck truck transportation earth square number statistical program stored in the memory and capable of running on the processor, and the muck truck transportation earth square number statistical program, when executed by the processor, implements the steps of the muck truck transportation earth square number statistical method according to any one of the above mentioned steps.
Further, in order to achieve the above object, the present invention further provides a muck truck transportation earth square number statistical system, including: the image acquisition equipment and the background server are used for acquiring images;
the image acquisition device is configured to: and acquiring license plate images and rear carriage images of the incoming and outgoing muck trucks and uploading the images to the background server.
Optionally, the muck truck transportation earth square number statistical system further includes: a weighbridge scale;
the weighbridge is used for: and collecting the carrying weight of the entering muck truck and uploading the carrying weight to the background server.
Further, in order to achieve the above object, the present invention further provides a computer readable storage medium, wherein the computer readable storage medium stores a muck truck transporting earth square number statistical program, and when the muck truck transporting earth square number statistical program is executed by a processor, the step of the muck truck transporting earth square number statistical method according to any one of the above mentioned steps is implemented.
In the invention, the license plate image and the rear compartment image of the muck car can be automatically collected through the image collecting equipment, and the license plate number identification is carried out on the license plate image so as to determine the vehicles entering and leaving the yard and the time of entering and leaving the yard; comparing the image characteristics of the rear compartment image of the muck truck with a characteristic database to further determine the number of earthwork carried by the muck truck; and determining the actual carrying earth number of the muck vehicle in the same transport vehicle number based on the earth number of the same muck vehicle when the same muck vehicle enters and exits, and generating a statistical record of the transport earth number of the muck vehicle. The whole process is automatically completed by machine equipment without manual participation, the automatic statistics of the amount of the earth transported by the muck is realized, and the complexity and the low efficiency of manual statistics are avoided.
Drawings
Fig. 1 is a schematic structural diagram of a hardware operating environment of a device according to an embodiment of the present invention;
FIG. 2 is a scene schematic diagram of an embodiment of a muck truck transporting earth number statistical system of the invention;
FIG. 3 is a schematic view of a scene of another embodiment of the statistical system for the number of earth transported by the muck truck according to the invention;
fig. 4 is a flow chart of an embodiment of the statistical method for the earth transportation square number of the muck truck.
The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a background server.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a hardware operating environment of a device according to an embodiment of the present invention.
As shown in fig. 1, the backend server may include: aprocessor 1001, such as a CPU, acommunication bus 1002, auser interface 1003, anetwork interface 1004, and amemory 1005. Thecommunication bus 1002 is used to implement connection communication among these components. Theuser interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and theoptional user interface 1003 may also include a standard wired interface, a wireless interface. Thenetwork interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). Thememory 1005 may be a high-speed RAM memory or a non-volatile memory such as a disk memory. Thememory 1005 may alternatively be a memory device separate from theprocessor 1001 described above. It should be noted that theprocessor 1001 is installed in the backend server in an embedded chip manner.
Those skilled in the art will appreciate that the hardware configuration of the back-end server shown in fig. 1 does not constitute a limitation of the back-end server, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, amemory 1005, which is a kind of computer-readable storage medium, may include therein an operating system, a network communication module, a user interface module, and a muck truck transport earth square statistic program. The operating system is a program for managing and controlling background servers and software resources, and supports the operation of a network communication module, a user interface module, a muck truck earth transportation square number counting program and other programs or software; the network communication module is used to manage and control thenetwork interface 1004; the user interface module is used to manage and control theuser interface 1003.
In the hardware structure of the background server shown in fig. 1, thenetwork interface 1004 is mainly used for connecting to the system background and performing data communication with the system background; theuser interface 1003 is mainly used for connecting a front-end device (user side) and performing data communication with the front-end device; the background server calls the muck truck transportation earth square number statistical program stored in thememory 1005 through theprocessor 1001, and executes the following operations:
when the muck truck transports muck and enters a field, acquiring a license plate image and a rear carriage image of the slag truck entering the field through image acquisition equipment;
identifying license plate numbers of license plate images of the incoming muck cars, and determining incoming vehicles and incoming time thereof; comparing the image characteristics of the rear compartment image of the incoming muck truck with the characteristic database to determine a first earth number carried by the incoming muck truck;
when the muck truck unloads muck and leaves the field, acquiring a license plate image and a rear carriage image of the left muck truck by using image acquisition equipment;
carrying out license plate number recognition on the license plate image of the outgoing muck car, and determining the outgoing vehicles and the outgoing time thereof; comparing the image characteristics of the rear compartment image of the outgoing residue soil vehicle with the characteristic database to determine a second earth number carried by the outgoing vehicle;
and determining the actual carrying earth number of the muck truck in the same transport vehicle number based on the first earth number and the second earth number of the same muck truck, and generating a statistical record of the carrying earth number of the muck truck.
Further, the background server calls the muck truck transporting earth number statistic program stored in thememory 1005 through theprocessor 1001 to further perform the following operations:
before image feature comparison, taking images of the back compartments of the muck trucks under different carrying earthwork numbers as learning samples, and performing feature training by adopting a machine learning algorithm to obtain corresponding image features of the back compartments under different carrying earthwork numbers and form a feature database;
and when image characteristics are compared, extracting image characteristics of the image of the rear compartment of the muck truck collected on site and comparing the image characteristics with the characteristic database so as to determine the carrying earth volume of the current muck truck.
Further, the background server calls the muck truck transporting earth number statistic program stored in thememory 1005 through theprocessor 1001 to further perform the following operations:
when the muck truck transports muck and enters a field, collecting the carrying weight of the slag truck entering the field through a weighbridge;
determining the type of the residue soil carried by the incoming residue soil truck based on the carrying weight and the carrying earthwork number of the incoming residue soil truck, wherein the type of the residue soil comprises rocks and silt;
and when the type of the slag carried by the entering slag car is rock, correcting the carrying earthwork number of the entering slag car based on a preset earthwork correction coefficient and carrying weight.
Further, the backend server invokes the muck truck transportation earth number statistical program stored in thememory 1005 through theprocessor 1001 to further perform the following operations:
the method comprises the steps of obtaining the carrying weight and the carrying earthwork number of each transport train number of the same entering muck vehicle for transporting rocks, and setting an earthwork correction coefficient based on the following formula:
wherein K representsCoefficient of earth correction, ai Representing the carrying weight of the i-th approach transport, bi The number of the carrying earthwork of the ith approach transportation is shown, and n is the total number of the approach transportation vehicles.
Further, the backend server invokes the muck truck transportation earth number statistical program stored in thememory 1005 through theprocessor 1001 to further perform the following operations:
calculating the theoretical carrying earth number of each transport train number of the incoming muck truck based on the following formula, and judging whether the difference value between the theoretical carrying earth number and the incoming carrying earth number exceeds a preset error rate or not;
if yes, correcting the number of the earth-carrying vehicles entering the field by the theoretical number of the earth-carrying vehicles, otherwise, not correcting;
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, Bi And the theoretical carrying earth volume of the ith approach transportation is shown.
Referring to fig. 2, fig. 2 is a scene schematic diagram of an embodiment of a statistical system for earth transportation of a muck truck according to the present invention.
In this embodiment, the muck truck transport earth square number statistical system includes: and the image acquisition equipment and the background server are in communication connection in a wired or wireless mode.
In this embodiment, the image capturing device may be an integrally formed rod-shaped shooting device, or may be a device composed of a column rod and a high-altitude camera. The image acquisition equipment is deployed at a vehicle entrance and exit of a construction site, and the background server can be deployed at the vehicle entrance and exit or at other remote positions, such as a remote construction party management center. The image acquisition equipment is used for acquiring license plate images and rear compartment images of the incoming and outgoing muck trucks and uploading the license plate images and the rear compartment images to the background server;
the background server is used for carrying out license plate number recognition on license plate images of the incoming and outgoing muck cars and determining incoming and outgoing vehicles and incoming and outgoing time of the incoming and outgoing vehicles; comparing the image characteristics of the rear compartment image of the in-out slag car with the characteristic database to determine the number of earthwork carried by the in-out slag car; and determining the actual carrying earth number of the muck truck in the same transport train number based on the earth number carried by the vehicles entering and leaving the field, and generating a statistical record of the carrying earth number of the muck truck.
Referring to fig. 3, fig. 3 is a functional architecture diagram of another embodiment of the statistical system for the earth transportation power of the muck truck according to the present invention.
In this embodiment, the statistics system for the number of earth transportation squares of the muck truck further includes: a weighbridge.
In the embodiment, the weighbridge scale is arranged at a vehicle inlet and a vehicle outlet of a construction site and used for collecting the carrying weight of the incoming muck truck and uploading the carrying weight to the background server. The loadometer establishes communication connection with the background server in a wired or wireless mode.
In this embodiment, because the dregs type of dregs car transportation is mainly silt, rock, and under equal volume, rock weight far surpasses silt, consequently introduce the dregs type that the earth pound title not only can simply judge the dregs car transportation fast, but also can further revise the transportation square of irregular rock, promote statistical result's accuracy fairness.
Based on the background server and the software and hardware architecture of the muck truck transporting and earth transporting square number statistical system, the following embodiments of the muck truck transporting and earth transporting square number statistical method are provided.
Referring to fig. 4, fig. 4 is a schematic flow chart of an embodiment of the statistical method for the earth transportation number of the muck truck of the present invention. In this embodiment, the statistical method for the number of earth transportation squares of the muck truck includes the following steps:
step S10, when the muck truck transports muck and enters a field, acquiring a license plate image and a rear carriage image of the entering muck truck through image acquisition equipment;
s20, identifying license plate numbers of license plate images of the entering muck trucks, and determining entering cars and entering time thereof; comparing the image characteristics of the rear compartment image of the incoming muck truck with the characteristic database to determine a first earth volume carried by the incoming muck truck;
in the embodiment, the image acquisition equipment automatically detects whether the entering muck truck exists or not based on the image characteristic change of the monitoring area, and if the entering muck truck exists, the image of the license plate number and the image of the rear compartment of the entering muck truck are acquired and uploaded to a background server for processing;
and the background server identifies the license plate number of the image of the incoming muck car uploaded by the image acquisition equipment and determines the incoming vehicle and the incoming time thereof, wherein the background server can also obtain the incoming time of the muck car based on the generation time of the license plate image.
And the background server compares the image characteristics of the rear compartment image of the incoming slag car with the characteristic database, and further determines the number of earthworms (namely the first number of earthworms) carried by the incoming car. The characteristic database stores corresponding rear carriage image characteristics under different carrying earth volume, and the earth volume of the muck truck carrying the muck can be determined through image characteristic comparison.
S30, when the muck truck unloads muck and leaves, acquiring a license plate image and a rear carriage image of the muck truck leaving the field through image acquisition equipment;
s40, identifying license plate numbers of license plate images of the discharged muck cars, and determining discharged vehicles and the discharge time of the discharged vehicles; comparing the image characteristics of the rear compartment image of the outgoing residue soil vehicle with the characteristic database to determine a second earth number carried by the outgoing vehicle;
in the embodiment, the image acquisition equipment automatically detects whether the discharged muck car exists or not based on the image characteristic change of the monitoring area, and acquires the license plate number image and the rear carriage image of the discharged muck car and uploads the license plate number image and the rear carriage image to the background server for processing if the discharged muck car exists;
and the background server identifies the license plate number of the image of the discharged muck truck uploaded by the image acquisition equipment and determines the discharged muck truck and the entering time of the discharged muck truck, wherein the background server can also obtain the discharging time of the muck truck based on the generation time of the license plate image.
And the background server compares the image characteristics of the rear compartment image of the outgoing residue soil vehicle with the characteristic database, and further determines the number of earthworms carried by the outgoing vehicle (namely the second number of earthworms). The characteristic database stores corresponding rear carriage image characteristics under different carrying earth volume, and the earth volume of the muck truck carrying the muck can be determined through image characteristic comparison.
And S50, determining the actual carrying earth number of the muck truck in the same transport vehicle number based on the first earth number and the second earth number of the same muck truck, and generating a statistical record of the transport earth number of the muck truck.
In this embodiment, to avoid the problem of incomplete unloading of the muck truck, the background server further acquires the images of the rear compartment of the muck truck leaving the yard, so as to determine the actual number of muck trucks (i.e., the difference between the first number of earthwork and the second number of earthwork) transported by the muck truck based on the respective corresponding number of earthwork entering the yard and leaving the yard.
In this embodiment, in order to facilitate the manager to separately manage the operation conditions of the respective muck trucks, the background server further generates a statistical record of the number of earth transportation of each muck truck.
For example, the earth number statistical record includes the license plate number of each muck car, the entering time and entering earth number corresponding to each transportation of the same muck car, the leaving time and leaving earth number, the actual carrying earth number, and the total earth number of the same muck car for each day/week/month transportation.
In the embodiment, the license plate image and the rear compartment image of the muck car can be automatically collected through the image collecting device, and the license plate number of the license plate image is identified, so that the vehicles entering and leaving the yard and the time of entering and leaving the yard are determined; comparing the image characteristics of the rear compartment image of the muck truck with a characteristic database to further determine the number of earthwork carried by the muck truck; and determining the actual carrying earth number of the muck truck in the same transport vehicle number based on the earth number of the same muck truck when the same muck truck enters and exits, and generating a statistical record of the carrying earth number of the muck truck. The whole process is automatically completed by machine equipment without manual participation, so that the automatic statistics of the earth volume of muck transportation is realized, and the complexity and the low efficiency of manual statistics are avoided.
Further, in an embodiment, in order to facilitate determining the number of earthwork carried by the slag car, the embodiment identifies the number of earthwork carried by the slag car by using an image feature comparison method, and the specific implementation process includes:
(1) Before image feature comparison, taking images of the back compartments of the muck trucks under different carrying earthwork numbers as learning samples, and performing feature training by adopting a machine learning algorithm to obtain corresponding image features of the back compartments under different carrying earthwork numbers and form a feature database;
(2) And when image characteristics are compared, extracting image characteristics of the image of the rear compartment of the muck truck acquired on site and comparing the image characteristics with the characteristic database so as to determine the carrying earthwork number of the current muck truck.
In the embodiment, images of the rear compartment of the muck truck under different carrying earthwork numbers are collected in advance to serve as machine learning samples, feature training is performed by adopting a machine learning algorithm, such as an HOG feature learning algorithm, a Sift/Surf feature learning algorithm and the like, so that the image features of the rear compartment corresponding to different carrying earthwork numbers are obtained, and a feature database is formed.
In this embodiment, when image feature comparison is performed, only image features of images of a rear compartment of the muck truck acquired on site need to be extracted and compared with the feature database, and the number of the carried earthwork corresponding to the images of the rear compartment in the database with the highest image feature matching degree is determined as the number of the earthwork carried by the current muck truck.
Further, based on the above embodiment, in this embodiment, the statistical method for the number of earth transportation squares of the muck truck further includes the following processing procedures:
(1) When the muck truck transports muck and enters a field, the carrying weight of the slag truck entering the field is collected through a weighbridge scale; determining the type of the residue soil carried by the incoming residue soil truck based on the carrying weight and the carrying earthwork number of the incoming residue soil truck, wherein the type of the residue soil comprises rocks and silt;
in this embodiment, a large error may exist in the statistics of the number of earth and dregs in consideration of the different types of the earth and dregs to be transported, and therefore, the number of earth and dregs needs to be corrected.
In this embodiment, the amount of the unearthed clean muck is very small when the muck truck leaves the field, and therefore, the amount of the unearthed clean muck can be ignored. Therefore, the present embodiment corrects only the number of earth and slag squares carried by the vehicle at the time of entry.
The background server can determine the type of the muck carried by the muck truck based on the weight and the volume of the muck, for example, the weight of rock muck is far larger than that of silt muck under the condition of similar volume.
(2) And when the type of the slag carried by the entering slag car is rock, correcting the carrying earthwork number of the entering slag car based on a preset earthwork correction coefficient and carrying weight.
In the embodiment, the carrying earth number of the incoming muck truck is corrected through the preset square correction coefficient and the carrying weight, so that the actual carrying earth number is indirectly corrected.
Optionally, in an embodiment, the earthwork correction coefficient is specifically set by the following method:
the method comprises the steps of obtaining the carrying weight and the carrying earthwork number of each transport vehicle number of the same entering muck vehicle for transporting rocks, and setting an earthwork correction coefficient based on the following formula:
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, bi The number of the carrying earthwork of the ith approach transportation is shown, and n is the total number of the approach transportation vehicles.
The carrying weight is acquired by the wagon balance collection, and the carrying earth volume is acquired by image feature matching.
For example, muck truck a transports rock three times a day, the transport being as follows: the weight of the first-time entering transportation rock is 10, the number of earthwork is 4, the weight of the second-time entering transportation rock is 12, the number of earthwork is 6, the weight of the third-time entering transportation rock is 11, the number of earthwork is 5, and then the earthwork correction coefficient K is 2.2.
In this embodiment, the earthwork correction coefficient is set with reference to data of all transport vehicle numbers of the same vehicle, and the earthwork correction coefficient can be adapted to actual transport data, so that fairness of data operation results is improved, and disputes are avoided.
Further optionally, in an embodiment, the number of earth-moving objects is modified based on the following specific manner:
calculating the theoretical carrying earth number of each transport train number of the incoming muck truck based on the following formula, and judging whether the difference value between the theoretical carrying earth number and the incoming carrying earth number exceeds a preset error rate or not;
if yes, correcting the number of the earth-carrying vehicles entering the field by the theoretical number of the earth-carrying vehicles, otherwise, not correcting;
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, Bi And the theoretical carrying earth volume of the ith approach transportation is shown.
In this embodiment, when the muck is loaded on the muck truck, it is difficult to regularly arrange irregular muck such as rocks, so that it is difficult to absolutely fair the statistical result, and therefore, this embodiment allows a certain error rate, for example, an error below 10% is acceptable.
In this embodiment, the number of earth and slag squares carried by the earth and slag car is corrected based on the above equations 1 and 2.
For example, muck truck a transports rock three times a day, the transport being as follows: when the weight of the first-time approach transportation rock is 10 and the number of earths is 4, the weight of the second-time approach transportation rock is 12 and the number of earths is 6, and the weight of the third-time approach transportation rock is 11 and the number of earths is 5, the earth correction coefficient K is 2.2 based on the above formula 1.
Based on the formula 2, the theoretical carrying earth number of the muck truck for the first time of entering the field is 4.55, the theoretical carrying earth number of the second time of entering the field is 5.45, the theoretical carrying earth number of the third time of entering the field is 5, and the error rate calculation shows that the error rate between the theoretical carrying earth number and the earth number of the first time of entering the field only reaches 10%, so that the theoretical carrying earth number of 4.55 is taken as the carrying earth number of the muck truck for the current entering the field.
The invention also provides a computer readable storage medium.
In this embodiment, the computer-readable storage medium stores a muck truck transporting earth square number statistical program, and the muck truck transporting earth square number statistical program, when executed by the processor, implements the steps of the muck truck transporting earth square number statistical method described in any one of the above embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM) and includes several instructions for enabling a terminal (which may be a mobile phone, a computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
The present invention is described in connection with the accompanying drawings, but the present invention is not limited to the above embodiments, which are only illustrative and not restrictive, and those skilled in the art can make various changes without departing from the spirit and scope of the invention as defined by the appended claims, and all changes that come within the meaning and range of equivalency of the specification and drawings that are obvious from the description and the attached claims are intended to be embraced therein.
Claims (4)
1. The statistical method for the number of earth transportation squares of the muck truck is characterized by comprising the following steps of:
when the muck truck transports muck and enters a field, acquiring a license plate image and a rear carriage image of the entering muck truck by using image acquisition equipment;
identifying license plate numbers of license plate images of the incoming muck cars, and determining incoming vehicles and incoming time thereof; comparing the image characteristics of the rear compartment image of the incoming muck truck with the characteristic database to determine a first earth number carried by the incoming muck truck;
when the muck truck unloads muck and leaves the field, acquiring a license plate image and a rear carriage image of the left muck truck by using image acquisition equipment;
identifying license plate numbers of license plate images of the discharged muck trucks, and determining discharged trucks and the discharge time thereof; comparing the image characteristics of the rear compartment image of the outgoing residue soil vehicle with the characteristic database to determine a second earth number carried by the outgoing vehicle;
determining the actual carrying earthwork number of the muck vehicle in the same transport vehicle number based on the first earthwork number and the second earthwork number of the same muck vehicle, and generating a statistical record of the carrying earthwork number of the muck vehicle, wherein when the muck vehicle carries muck to enter a field, the carrying weight of the muck vehicle entering the field is acquired through a weighbridge, and the muck type carried by the muck vehicle entering the field is determined based on the carrying weight and the carrying earthwork number of the muck vehicle entering the field, wherein the muck type comprises rock and silt, and when the muck type carried by the muck vehicle entering the field is rock, the carrying earthwork number of the muck vehicle entering the field is corrected based on a preset earthwork correction coefficient and the carrying weight;
the preset mode of the earthwork correction coefficient comprises the following steps:
the method comprises the steps of obtaining the carrying weight and the carrying earthwork number of each transport train number of the same entering muck vehicle for transporting rocks, and setting an earthwork correction coefficient based on the following formula:
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, bi Carrying earthwork representing i-th approach transportationThe number n represents the total number of the entering transport vehicles;
the correction of the carrying earthwork number of the incoming slag-soil vehicle based on the preset earthwork correction coefficient and the carrying weight comprises the following steps:
calculating the theoretical carrying earth number of each transport train number of the incoming muck truck based on the following formula, and judging whether the difference value between the theoretical carrying earth number and the incoming carrying earth number exceeds a preset error rate or not;
if yes, correcting the number of the earth-carrying vehicles entering the field by the theoretical number of the earth-carrying vehicles, otherwise, not correcting;
wherein K represents an earth correction coefficient, ai Representing the carrying weight of the i-th approach transport, Bi Representing the theoretical carrying earth volume of the ith approach transportation;
the statistical method for the number of earth transportation squares of the muck truck further comprises the following steps:
before image feature comparison, taking images of the rear compartment of the muck truck under different carrying earthwork numbers as learning samples, carrying out feature training by adopting a machine learning algorithm to obtain corresponding rear compartment image features under different carrying earthwork numbers, and forming a feature database;
and when image characteristics are compared, extracting image characteristics of the image of the rear compartment of the muck truck acquired on site and comparing the image characteristics with the characteristic database so as to determine the carrying earthwork number of the current muck truck.
2. A backend server, characterized in that the backend server comprises a memory, a processor and a muck truck transporting earth square statistic program stored on the memory and operable on the processor, wherein the muck truck transporting earth square statistic program when executed by the processor implements the steps of the muck truck transporting earth square statistic method according to claim 1.
3. The utility model provides a dregs car transportation earth side's number statistical system which characterized in that, dregs car transportation earth side's number statistical system includes: the image acquisition device and the background server of claim 2;
the image acquisition device is configured to: collecting license plate images and rear compartment images of the incoming and outgoing muck cars and uploading the images to the background server;
the muck truck transportation earth square number statistical system further comprises: a loadometer scale;
the weighbridge is used for: and collecting the carrying weight of the entering muck truck and uploading the carrying weight to the background server.
4. A computer-readable storage medium, wherein the computer-readable storage medium has stored thereon a muck truck transport earthwork statistical program, which when executed by a processor, implements the steps of the muck truck transport earthwork statistical method of claim 1.
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