CN110580052A - vehicle detection method, device and system - Google Patents
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Abstract
the embodiment of the application discloses a vehicle detection method, device and system. According to the technical scheme, the detection strategy corresponding to each vehicle model is stored in advance, when a certain vehicle is detected, the detection strategy corresponding to the vehicle is called according to the acquired vehicle information, the aircraft is guided according to the detection strategy, and the vehicle is detected. According to the method, the vehicles are detected according to the detection strategy, the detection strategy records key detection points and common fault points of each vehicle, the technical problem that the detection level of a detector is different due to different training levels of personnel and types of contacted vehicles in the detection method and the technical problem that unified detection technical specification standards cannot be really realized due to different detection levels in the prior art is solved, missing detection and false detection are effectively avoided, and the detection accuracy is improved. Meanwhile, the aircraft is adopted to collect information, and the detection process is not influenced by a field any more.
Description
Technical Field
the invention relates to the technical field of computers, in particular to a vehicle detection method, device and system.
background
With the increasing living standard, the automobile has become a common transportation tool in ordinary families. More and more consumers choose to buy one automobile to bring convenience to daily life. In recent years, with the development of economic society and the increase in the living standard of urban residents, vehicles have become a basic requirement for private use. In recent years, the rapid development of Chinese economy, the rapid increase of vehicle reserves, and the trading of used cars is more and more prosperous, and the used cars are usually carried out on a vehicle trading platform.
The vehicle transaction platform acquires the used-for-vehicle vehicles in a store or a personal hand, detects the used-for-vehicle vehicles, generates a detection report, and evaluates the acquisition price of the used-for-vehicle vehicles according to the detection report. Before the vehicle trading platform buys the used-for-vehicle, a detector can detect various performances of the used-for-vehicle, then a detection report is generated and sent to the vehicle trading platform, and the purchase price of the used-for-vehicle is evaluated according to the detection report.
Generally, in order to ensure the accuracy of a detection result and the detection process of a vehicle, the detection is finished in some specific places, however, most of the existing automobile detection is manual detection, detection levels of detection operators are different due to different personnel training levels and types of contacted vehicle types, a unified detection technical specification standard cannot be really realized, the accuracy of the detection result is difficult to ensure, and the development of an accurate detection method which is not influenced by places is particularly important.
disclosure of Invention
the invention aims to provide a vehicle detection method, a device and a system, which solve the technical problem that the accuracy of the detection result of the detection method shown in the prior art is difficult to ensure.
A first aspect of embodiments of the present application shows a vehicle detection method, including:
Obtaining vehicle information, and calling a detection strategy corresponding to the vehicle information, wherein the detection strategy comprises the following steps: a driving path, a detection process and a photographing position;
Guiding the aircraft to detect according to the detection strategy, and generating first acquisition information according to a detection result;
and analyzing the first acquisition information to generate a detection report.
Optionally, the step of obtaining vehicle information and invoking a detection policy corresponding to the vehicle information includes:
acquiring vehicle information, wherein the vehicle information comprises: the vehicle model, and, the license plate number;
traversing a vehicle type library, and judging whether the vehicle type exists in the vehicle type library or not;
if the vehicle model does not exist, a central background system is communicated, the central background system obtains the control authority of the aircraft, the aircraft is controlled to detect the vehicle, and meanwhile, a detection strategy corresponding to the vehicle model is generated;
storing the detection strategy;
and if so, calling a detection strategy corresponding to the vehicle model.
Optionally, the step of parsing the first collected information and generating the detection report includes:
Analyzing the first acquisition information and determining problem items;
Sending the problem item to a detection terminal, and calibrating and rechecking the terminal according to the problem item to generate second detection information;
And acquiring the second detection information, and generating a detection report based on the first acquisition information and the second detection information.
optionally, the step of parsing the first collected information and determining the question item includes:
Receiving the first acquisition information, wherein the first acquisition information comprises: picture information, sound information, exhaust gas detection information, and driving behavior information;
comparing the first acquisition information with standard information to generate a comparison result;
and determining the problem item according to the comparison result.
Optionally, the step of comparing the first collected information with the standard information to generate a comparison result includes:
acquiring the main axis of the tire according to the image information;
Calculating the inclination of the main axis of the tire to the horizontal plane;
And inputting the inclination into a model trained by a learning machine to generate a comparison result.
optionally, the step of guiding the aircraft to detect according to the detection strategy, and generating the first collected information according to the detection result includes:
Driving the aircraft to move based on the driving path, and starting the camera to shoot a local picture; or driving the aircraft to move, starting the camera to shoot a local picture, recording the position of the aircraft in real time, generating a control signal of the aircraft according to the position, and controlling the aircraft to pause, rotate and start; the control signal includes: pause signal, rotation signal, drive signal;
And splicing the local pictures to obtain first acquisition information.
A second aspect of the embodiments of the present application shows a vehicle detection apparatus, including:
the device comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring vehicle information and calling a detection strategy corresponding to the vehicle information, and the detection strategy comprises: a driving path, a detection process and a photographing position;
The first acquisition information generating unit is used for guiding the aircraft to detect according to the detection strategy and generating first acquisition information according to a detection result;
And the detection report generating unit is used for analyzing the first acquisition information and generating a detection report.
optionally, the obtaining unit includes:
a first acquisition unit that acquires vehicle information, the vehicle information including: the vehicle model, and, the license plate number;
The judging unit is used for traversing a vehicle type library and judging whether the vehicle type exists in the vehicle type library or not;
The communication unit is used for communicating the central background system if the central background system does not exist, the central background system obtains the control authority of the aircraft, controls the aircraft to detect the vehicle and simultaneously generates a detection strategy corresponding to the vehicle model;
a storage unit for storing the detection policy;
And the calling unit is used for calling the detection strategy corresponding to the vehicle model if the detection strategy exists.
Optionally, the detection report generating unit includes:
the problem item determining unit is used for analyzing the first acquisition information and determining a problem item;
The sending unit is used for sending the problem item to a detection terminal, and the terminal carries out calibration and rechecking according to the problem item to generate second detection information;
And the second detection information acquisition unit is used for acquiring the second detection information and generating a detection report based on the first acquisition information and the second detection information.
Optionally, the question item determination unit includes:
A first receiving unit, configured to receive the first acquisition information, where the first acquisition information includes: picture information, sound information, exhaust gas detection information, and driving behavior information;
the comparison unit is used for comparing the first acquisition information with standard information to generate a comparison result;
and the first question item determining unit is used for determining question items according to the comparison result.
optionally, the alignment unit comprises:
The tire main axis obtaining unit is used for obtaining the tire main axis according to the image information;
A calculation unit for calculating the inclination of the main axis of the tyre with a horizontal plane;
And the comparison result generating unit is used for inputting the inclination into a model trained by the learning machine to generate a comparison result.
optionally, the generating unit according to the first acquisition information includes:
the local picture shooting unit is used for planning a running path of the aircraft, driving the aircraft to move based on the running path and starting the camera to shoot a local picture; or driving the aircraft to move, starting the camera to shoot a local picture, recording the position of the aircraft in real time, generating a control signal of the aircraft according to the position, and controlling the aircraft to pause, rotate and start; the control signal includes: pause signal, rotation signal, drive signal;
and the splicing unit is used for splicing the local pictures to obtain first acquisition information.
A third aspect of embodiments of the present application shows a vehicle detection system, including:
The system comprises an aircraft, an application platform server connected with the aircraft, and a terminal connected with the application platform server;
the aircraft is used for collecting picture information, sound information, tail gas detection information and driving behavior information;
The application platform server is used for realizing the method shown in the embodiment of the application;
And the terminal is used for acquiring the second detection information.
optionally, the system further comprises: a central back-office system;
and the central background system is used for obtaining the control authority of the aircraft, controlling the aircraft to detect the vehicle and generating a detection strategy corresponding to the vehicle model.
according to the technical scheme, the embodiment of the application shows a vehicle detection method, device and system. According to the technical scheme, the detection strategy corresponding to each vehicle model is stored in advance, when a certain vehicle is detected, the detection strategy corresponding to the vehicle is called according to the acquired vehicle information, the aircraft is guided according to the detection strategy, and the vehicle is detected. According to the method, the vehicles are detected according to the detection strategy, the detection strategy records key detection points and common fault points of each vehicle, the technical problem that the detection level of a detector is different due to different training levels of personnel and types of contacted vehicles in the detection method and the technical problem that unified detection technical specification standards cannot be really realized due to different detection levels in the prior art is solved, missing detection and false detection are effectively avoided, and the detection accuracy is improved. Meanwhile, the aircraft is adopted to collect information, and the detection process is not influenced by a field any more.
drawings
in order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a block diagram illustrating a vehicle detection system in accordance with a preferred embodiment;
FIG. 2 is a flow chart illustrating operation of a vehicle detection system in accordance with a preferred embodiment;
FIG. 3 is a flow chart illustrating a method of vehicle detection in accordance with a preferred embodiment;
FIG. 4 is a detailed flowchart of step S101, shown in accordance with a preferred embodiment;
FIG. 5 is a detailed flowchart of step S103, shown in accordance with a preferred embodiment;
FIG. 6 is a detailed flowchart of step S103 shown in accordance with yet another preferred embodiment;
FIG. 7 is a detailed flowchart of step S103, shown in accordance with a preferred embodiment;
FIG. 8 is a block diagram illustrating the construction of a vehicle chassis in accordance with a preferred embodiment;
FIG. 9 is a detailed flowchart of step S102, shown in accordance with a preferred embodiment;
fig. 10 is a block diagram showing a configuration of a vehicle detecting apparatus according to a preferred embodiment.
Detailed Description
the technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
example 1:
a first aspect of the embodiments of the present application shows a vehicle detection system, please refer to fig. 1, the system includes:
an aircraft 31, an application platform server 32 connected with the aircraft 31, and a terminal 33 connected with the application platform server 32;
The embodiment of the application shows that the aircraft has a flight function and a land driving function, and the land driving function is adopted by the aircraft in the process of chassis detection.
the aircraft 31 is used for collecting picture information, sound information, tail gas detection information and driving behavior information;
the aircraft 31 is provided with a tail gas detection device (retractable and controllable): the automobile exhaust analyzer is used to detect the content indexes of various gas elements in automobile exhaust. The automobile exhaust analyzer is used for measuring and analyzing main components of CO, HC, CO2, NOX and O2 in automobile exhaust by using a non-spectroscopic infrared ray and an electrochemical sensor.
The audio acquisition module: advanced noise processing, echo processing and long-distance transmission driving circuits are integrated to adapt to projects with higher standards and special requirements, and the site is recorded and restored faithfully with high-fidelity tone quality and pictures. The device is used for collecting the noise of the part to be tested and interacting with a tester.
the audio playing module: the media player is powerful.
the video acquisition module: also known as computer cameras, computer eyes, electronic eyes, etc., is a video input device.
A wireless communication module: communication function: supporting GPRS and short message double-channel data transmission; supporting multi-center data communication; and remote parameter setting and program upgrading are supported. Comprises the following steps: bluetooth, WiFi, 4G, 5G and other mobile communication modules.
positioning module (GPS and/or beidou): the integrated circuit is formed by integrating an RF chip, a baseband chip and a core CPU and adding related peripheral circuits.
the central data processing module: computer systems have devices that interpret instructions, execute instructions, and control operations, among other important functions. Mainly comprises a controller and an arithmetic unit. The central processor is used for centralized control and typically comprises one or more processors, one or more memories and possibly also elements of the conversion device.
a flight control module: when wind occurs, the aileron elevator can automatically correct to the horizontal position, in other words, when a flight control plane is arranged and a user sails with an accelerator, the flight control plane can stably fly forwards without deflection even if the wind exists.
The distance measurement module: the range finder measures the distance between the lens and the object to be photographed and adjusts the light focusing point.
an illumination module: the intelligent lighting control system monitors and tracks power supply in real time by using advanced electromagnetic voltage regulation and electronic induction technology, automatically and smoothly regulates the voltage and current amplitude of a circuit, improves external power consumption caused by unbalanced load in the lighting circuit, improves power factor, reduces the working temperature of lamps and lines, and achieves the aim of optimizing power supply.
a horizontal module: also known as a level meter, is a common measuring tool for measuring small angles. In the mechanical industry and in instrument manufacturing, the device is used for measuring the inclination angle relative to the horizontal position, the flatness and the straightness of a guide rail of machine tool equipment, the horizontal position and the vertical position of equipment installation and the like.
An alarm module: the alarm is an electronic product which reminds or warns people of taking certain action in the form of sound, light, air pressure and the like in order to prevent or prevent the consequences caused by certain events.
Auscultation module: it is possible to determine with high sensitivity various mechanical noise sources and sound sources of obstacles in an operating apparatus which cannot be found by the human ear. The loss condition of the engine is diagnosed through the sound wave in the starting state of the engine.
the application platform server is used for realizing the method shown in the embodiment of the application;
the method is used for (1) obtaining vehicle information and calling a detection strategy corresponding to the vehicle information, wherein the detection strategy comprises the following steps: a driving path, a detection process and a photographing position;
firstly, a terminal collects the vehicle model and the license plate number of the vehicle, wherein the vehicle model can be generated according to the picture of the vehicle, or the picture information of the vehicle and the vehicle model corresponding to the picture information can be stored in advance before the vehicle is detected. Then matching the acquired picture with a stored picture to finally generate a vehicle model;
the terminal sends the vehicle information to an application platform server;
it is worth noting that the application platform server shown in the embodiment of the application is internally provided with a data storage server, and the data storage server is internally provided with a behavior library, a vehicle model library, an accident library, a graph library and a mechanical learning library; the behavior library stores detection strategies of vehicles detected in advance, wherein the detection strategies comprise: the method comprises the steps of shooting a vehicle model, wherein the vehicle model comprises a driving path of the aircraft, an image acquisition position, a shooting position and a detection flow aiming at the vehicle model.
(2) guiding the aircraft to detect according to the detection strategy, and generating first acquisition information according to a detection result;
(3) analyzing the first acquisition information to generate a detection report;
the first acquisition information comprises an appearance picture of the vehicle, or a chassis picture of the vehicle, or a skeleton picture, or sound of variable attributes of an engine, or tail gas of the vehicle.
please refer to fig. 2 for a specific detection process;
the method comprises the steps that the aircraft is controlled to take off or drive through a detection strategy, a tester can control the aircraft through voice, semantic analysis software such as science news is utilized to fly, and detection strategies generated by an application platform server can also be used for carrying out appearance shooting and frame detection around a vehicle to be detected, the aircraft transmits a shot video image of the vehicle to be detected to the application platform server through a wireless communication module (WiFi or Bluetooth), the application platform server traverses a vehicle type library function module to determine the vehicle type of the vehicle to be detected, carries out vehicle type identification on the vehicle, for example, identifies a gallop C200, then calls a behavior library function module, calls a detection strategy aiming at the gallop C200, and controls an unmanned plane to carry out corresponding detection steps according to the detection strategy. For example, when the step of appearance shooting is executed, the C200 is subjected to appearance shooting, a graphic library function module is called, the angle, the focus point, the position and the like of the vehicle appearance shooting are specified, and the aircraft is controlled to carry out the vehicle appearance shooting according to the requirements (multiple angles, the photo focus point and the shooting distance) specified by the graphic library; when the tail gas detection is executed, the aircraft is controlled to fly to the accessory of the exhaust funnel of the automobile, and the tail gas detection device is extended out for tail gas measurement; when display signals such as automobile headlights, tail lamps and steering lamps are detected, an unmanned person can follow a vehicle to be detected to record a video (the truth of detection data is ensured to be visible), and meanwhile, through the behavior library function module, the detection personnel can be supervised to carry out comprehensive test according to detection behaviors, so that the situations that the detection personnel leak and test troubles and the like when the former detection personnel carry out unmanned monitoring are avoided. Meanwhile, aiming at different vehicle types, an accident library function module can be called, the module stores the detection items of the vehicle type which often have faults, and the function module is called to remind a tester to detect the important test items or test points which often have faults, or directly control the aircraft to carry out video recording and photographing detection on the important test items or test points which often have faults.
in the process of detecting the vehicle chassis, the chassis detection methods shown in the prior art are used for various ditches, lifters, chassis inspection convex mirrors, fixed vehicle chassis detection devices and the like. And the trench is used for driving the vehicle to the trench, and the inspector stands in the trench to inspect the chassis of the vehicle. The lifter lifts the vehicle from ground to mid-air, and a detector can detect the vehicle chassis. The chassis inspection convex mirror is arranged at the bottom of the vehicle, and the inspector inspects the chassis by observing the convex mirror. A fixed vehicle chassis detection device needs to dig a pit on the ground and place the pit underground, and a camera is flush with the ground. The method needs a fixed place and has higher requirements on a test site;
The method shown in the embodiment of the application comprises the steps of collecting pictures of a vehicle chassis through an aircraft, comparing the collected pictures with a chassis picture corresponding to a new vehicle of the vehicle, and generating a chassis detection report according to a comparison result
the system is shown in the embodiment of the application, and the aircraft is led into the vehicle detection process, so that the vehicle detection process is not limited by a site;
it should be noted that the embodiments of the present application are only exemplary to illustrate the detection method using the chassis. In the practical application process, the appearance of the vehicle is detected, the chassis is detected, the skeleton and the invisible damage are detected, the circuit is detected, and the working condition is detected, the aircraft can be adopted to collect first collection information, so that the influence of a detection field is avoided in the whole detection process. The collection of the first collected information is completed in the process of moving the aircraft, and the detection efficiency is improved.
And the terminal is used for acquiring the second detection information.
In order to further improve the detection accuracy, the system provided by the application is provided with a terminal, and the terminal is used for calibrating and rechecking according to the problem item to generate second detection information.
the system shown in the embodiment of the application compares first acquisition information acquired by an aircraft with standard information to determine a problem item;
specifically, in the appearance detection process, the aircraft collects an appearance picture of a vehicle to be detected according to a detection strategy, then the collected appearance picture is compared with a standard picture of a new vehicle, if the collected appearance picture is different from the standard picture of the new vehicle, the position of the difference is determined to be a problem item, an application platform server sends the problem item to a terminal, and the terminal checks and rechecks the problem item;
the accuracy of the detection result can be improved by the problem item inspection and rechecking of the terminal;
for example, the following steps are carried out:
comparing the first collected information with the standard information, and displaying a comparison result, rubbing a right door of the vehicle, and determining the right door of the vehicle as a problem item;
And sending the problem item to a terminal, wherein the terminal finds that the rubbing of the right vehicle door is a repairable problem in the detection process, and the rubbing problem can be overcome through simple scrubbing.
the terminal generates second acquisition information through rechecking and checking;
and the application platform server generates a detection report through the first acquisition information and the second detection information, and guides the second-hand car trading platform to price the car.
the system shown in the embodiment of the application can improve the accuracy of the detection result by checking and rechecking the first acquired information through the terminal.
for some rare vehicles, detection strategies of relevant vehicles are not stored in the data storage service library, the aircraft is guided by the lack of the detection strategies to carry out detection, and false detection or missing detection can be caused due to the fact that detection key points are unknown according to European fault points in the detection process;
in order to solve the above problem, an embodiment of the present application shows that the system further includes: a central back-office system 34;
the central background system 34 is configured to obtain a control authority of the aircraft, control the aircraft to detect the vehicle, and generate a detection strategy corresponding to the vehicle model.
If the vehicle type does not exist in a vehicle type library in a data storage server or a newly-on-duty detector control terminal, field detectors can be connected with a central background system through a mobile detection device, the central background system is provided with a vehicle detection expert for monitoring, the vehicle detection expert can temporarily obtain the control right of the aircraft to directly control the aircraft, and simultaneously, the detection behaviors, fault points and detection flows of the vehicle are respectively stored in a vehicle type library function module, a behavior library function module, a graph library function module and an accident library function module in the data storage server, so that the machine learning experience is increased, and the detection of the same or similar vehicle types in the future is facilitated.
The system shown in the embodiment of the application introduces the aircraft into the detection equipment, and controls and adds the third person to call the visual angle display through the detection strategy and the evaluator, so that the circuit is more convenient to demonstrate and the dynamic detection is realized.
The aircraft can be used as a core auxiliary device and can be internally provided with a preloaded vehicle model library, the checking behavior of each type of vehicle, the checking auxiliary function of an evaluator, the standard checking behavior, the position positioning of the evaluator, the shooting light supplement and other extension functions, and the error rate is reduced.
The problem items are determined by comparing the information determined by the application platform server, so that the detection process of a detector can be standardized, and the position and the automatic assistance are used for carrying out image taking work of appearance and fixed detection. And the capability of automatically judging the vehicle condition and the damage. On vehicle electrical circuits and dynamic sensing.
Through professional evaluators for remote guidance and remote question answering, the quality of vehicle detection of the small public and the evaluators unfamiliar with the vehicle is improved.
example 2:
a second aspect of the embodiments of the present application shows a vehicle detection method, please refer to fig. 3, where the method includes:
S101, vehicle information is obtained, and a detection strategy corresponding to the vehicle information is called, wherein the detection strategy comprises the following steps: a driving path, a detection process and a photographing position;
firstly, a terminal collects vehicle information, wherein the vehicle information comprises: the vehicle model, and the license plate number of the vehicle or the picture of the vehicle; the picture of the vehicle comprises an appearance picture of the vehicle and a picture of a license plate number;
the application platform server shown in the embodiment of the application is internally provided with a data storage server, and the data storage server is internally provided with a behavior library, a vehicle model library, an accident library, a graph library and a mechanical learning library; the behavior library stores detection strategies of vehicles detected in advance, wherein the detection strategies comprise: in the photographing process, the traveling path of the aircraft, the position of image acquisition, the photographing position and the detection flow aiming at the vehicle type are respectively stored in a behavior library, a vehicle type library, an accident library, a graph library and a mechanical learning library.
the vehicle model can be generated according to a picture of the vehicle, or picture information of the vehicle and the vehicle model corresponding to the picture information can be stored in advance before the vehicle is detected. Then, matching is carried out according to the collected picture and the stored picture, and finally the vehicle model is generated;
the terminal sends the vehicle information to an application platform server;
The application platform server acquires vehicle information sent by the terminal;
s102, guiding the aircraft to detect according to the detection strategy, and generating first acquisition information according to a detection result;
After the vehicle model of the vehicle to be detected is determined, a detection strategy corresponding to the vehicle model is called, the aircraft is guided to collect first collection information according to the detection strategy, and the first collection information comprises appearance information, chassis information, skeleton information, circuit information, engine and gearbox information and working condition information of the vehicle.
s103, analyzing the first acquisition information to generate a detection report.
The first collected information is analyzed, for example: and comparing the first acquisition information with the standard information, and if the first acquisition information is consistent with the standard information, the performance of the vehicle is complete.
Or identifying whether the first collected information has defects through an image identification technology.
in practical applications, all methods that can evaluate the vehicle through the first collected information are within the scope of the method shown in the embodiment of the present application, and the space is not always listed herein because of limited space.
for example, if it is recognized that the driver C200 is present, the behavior library function module is called to call a detection policy for the driver C200, and the corresponding detection step is performed by controlling the robot according to the detection policy. For example, when the appearance shooting step is executed, the appearance shooting is carried out on the C200, a graphic library function module is called (the angle, the focus point, the position and the like of the vehicle appearance shooting are specified), and the aircraft is controlled to carry out the vehicle appearance shooting according to the requirements (multiple angles, the photo focus point and the shooting distance) specified by the graphic library; when the tail gas detection is executed, the aircraft is controlled to fly to the accessory of the exhaust funnel of the automobile, and the tail gas detection device is extended out for tail gas measurement; when display signals such as automobile headlights, tail lamps and steering lamps are detected, an unmanned person can record a video along with the vehicle to be detected, and therefore the reality and the visibility of detection data are guaranteed.
the method shown in the embodiment of the application stores the detection strategy of each vehicle in advance, then calls the detection strategy corresponding to the vehicle model according to the vehicle model of the vehicle, and guides the aircraft to detect according to the detection strategy. According to the technical scheme, the detection strategy corresponding to each vehicle model is stored in advance, when a certain vehicle is detected, the detection strategy corresponding to the vehicle is called according to the acquired vehicle information, the aircraft is guided according to the detection strategy, and the vehicle is detected. According to the method, the vehicles are detected according to the detection strategy, the detection strategy records key detection points and common fault points of each vehicle, the technical problem that the detection level of a detector is different due to different training levels of personnel and types of contacted vehicles in the detection method and the technical problem that unified detection technical specification standards cannot be really realized due to different detection levels in the prior art is solved, missing detection and false detection are effectively avoided, and the detection accuracy is improved. Meanwhile, the aircraft is adopted to collect information, and the detection process is not influenced by a field any more.
the behavior specifications of a inspector can be tracked and reminded according to the camera on the aircraft; recording the vehicle condition during detection; the situation that naked eyes cannot distinguish easily is solved by comparing the data of the picture shot on site with the new car picture in the database; and identifying the vehicle type, the year, the driving license and the like. Through continuous detection of the same vehicle type, data experience is accumulated, and more detection room workload is replaced.
Example 3:
for some rare vehicles, the data storage service library does not store detection strategies of related vehicles, the detection strategies are lacked to guide the aircraft to detect, and false detection or missing detection is possibly caused by the fact that detection key points or fault points are not known in the detection process;
In order to solve the above technical problem, an embodiment of the present application illustrates a method for generating a rare vehicle detection strategy, and specifically, please refer to fig. 4;
Embodiment 3 has similar steps as embodiment 2, and the only difference is that in the technical solution shown in embodiment 2, the step of acquiring the vehicle information and invoking the detection strategy corresponding to the vehicle information includes:
S1011 acquires vehicle information, the vehicle information including: the vehicle model, and, the license plate number;
some rare vehicle data storage servers have no records of relevant vehicles in advance.
The terminal shoots the vehicle to be detected in advance, wherein the shooting is carried out on the appearance and the license plate number of the vehicle roughly.
determining the vehicle model according to the appearance of the vehicle;
or the terminal directly acquires the vehicle model;
s1012, traversing a vehicle type library, and judging whether the vehicle type exists in the vehicle type library or not;
S1013, if the vehicle model does not exist, communicating a central background system, wherein the central background system acquires the control authority of the aircraft, controls the aircraft to detect the vehicle, and generates a detection strategy corresponding to the vehicle model;
s1014, storing the detection strategy;
if the vehicle model does not exist in a new on-duty detector control terminal or a vehicle model library in the data storage server, field detectors can be connected with the central background system through the mobile detection device to communicate the central background system with the application platform server, the central background system is monitored by a vehicle detection expert, the vehicle detection expert can temporarily obtain a control right item of the aircraft to directly control the aircraft to complete detection of the vehicle, and simultaneously, detection behaviors, fault points and detection processes of the vehicle are respectively stored in a vehicle model library function module, a behavior library function module, a graph library function module and an accident library function module in the data storage server, so that machine learning experience is increased, and detection of the same or similar vehicle models is facilitated later.
and S1015, if so, calling a detection strategy corresponding to the vehicle model.
Through professional evaluators remote guidance and remote question answering, the quality of vehicle detection of the small and popular vehicles and the quality of vehicle detection which are unfamiliar to evaluators are improved.
according to the technical scheme shown in the embodiment of the application, a part of simple and repeated work is replaced by an aircraft form, the difficult problem encountered by a field inspector at that time can be timely transmitted to a high-level inspector at headquarters in real time through sound and images, and the problem can be solved on site.
example 4:
in order to further improve the accuracy of the detection result of the method in the embodiment of the present application, a method for verifying the collected information and attaching the collected information is shown in the embodiment of the present application, and specifically, refer to fig. 5;
the technical solution shown in embodiment 4 has similar steps to the technical solution shown in embodiment 2, and the only difference is that the step of analyzing the first collected information and generating the detection report in the technical solution shown in embodiment 2 includes:
S10311, analyzing the first acquisition information, and determining problem items;
the first acquisition information comprises an appearance picture of the vehicle, a chassis picture of the vehicle, a skeleton picture, sound of an engine gearbox and tail gas of the vehicle.
analyzing the first acquisition information, comparing the first acquisition information acquired by the aircraft with the standard information, and determining a problem item;
Specifically, in the appearance detection process, the aircraft collects an appearance picture of a vehicle to be detected according to a detection strategy, then the collected appearance picture is compared with a standard picture of a new vehicle, and if the collected appearance picture is different from the standard picture of the new vehicle, the position of the difference is determined as a problem item; comparing the collected sound of the engine gearbox with the standard sound of a new vehicle, and if the difference exists, determining the difference as a problem item;
the application platform server sends the problem item to a terminal, and the terminal verifies and rechecks the problem item;
S10312, sending the problem item to a detection terminal, and calibrating and rechecking the terminal according to the problem item to generate second detection information;
comparing the first collected information with the standard information, and displaying a comparison result, rubbing a right door of the vehicle, and determining the right door of the vehicle as a problem item;
the application platform server sends the problem item to the terminal, and the terminal finds that rubbing of the right vehicle door is a repairable problem in the detection process, and the rubbing problem can be overcome through simple scrubbing.
the terminal generates second acquisition information according to the rechecking and checking results and sends the second acquisition information to the application platform server;
the application platform server generates a detection report according to the first acquisition information and the second acquisition information;
S10313, acquiring the second detection information, and generating a detection report based on the first acquisition information and the second detection information.
according to the technical scheme, firstly, a part of simple and repeated work is replaced by an aircraft form to generate first acquisition information, if the first acquisition information has a problem item, the problem item is sent to a terminal, the terminal rechecks the problem item and checks the problem item to finally obtain second acquisition information, and a detection report is generated based on the first acquisition information and the second detection information. According to the method, the problem item is rechecked and verified through the terminal, so that on one hand, the accuracy of the detection result can be improved, and on the other hand, the terminal only detects the problem item, so that the detection efficiency is improved.
example 5:
in order to further improve the detection efficiency, the embodiment of the present application shows a method for determining a problem item, specifically, please refer to fig. 6;
the technical solution shown in embodiment 5 has similar steps to the technical solution shown in embodiment 2, and the only difference is that the step of analyzing the first collected information and determining the problem item in the technical solution shown in embodiment 2 includes:
s10321 receives the first acquisition information, which includes: picture information, sound information, exhaust gas detection information, and driving behavior information;
s10322, comparing the first acquisition information with standard information to generate a comparison result;
specifically, in the appearance detection process, the aircraft collects picture information of the vehicle to be detected according to a detection strategy, wherein the picture information comprises: an appearance picture, the appearance picture comprising: the shape picture, chassis picture and skeleton picture of the vehicle;
then comparing the acquired appearance picture with a standard picture of a new car, if the acquired appearance picture is different from the standard picture of the new car, determining the position of the difference as a problem item, sending the problem item to a terminal by an application platform server, and verifying and rechecking the problem item by the terminal;
s10323, according to the comparison result, the question item is determined.
According to the technical scheme shown in the embodiment of the application, the vehicle model is determined, and meanwhile, the standard information corresponding to the vehicle model is called, wherein the standard information comprises: standard pictures, standard video, and standard audio; and then, determining the problem item by comparing the first acquisition information with the standard information.
the whole problem item determination process only needs to adopt comparison of the first acquisition information and the standard information, the whole program is simple, and the detection efficiency is further improved.
Example 6:
the damage assessment of the skeleton is based on human eye recognition analysis, the experience level of each person is uneven, and the detection quality is difficult to guarantee.
In order to solve the above problems, the embodiments of the present application illustrate a problem item determination method of a skeleton damage; specifically, please refer to fig. 7;
the embodiment 6 and the technical solution shown in the embodiment 5 have similar steps, and the only difference is that the step of comparing the first collected information with the standard information in the technical solution shown in the embodiment 5 to generate the comparison result includes the following steps:
S103221, acquiring a tire main axis according to the image information;
S103222 calculating an inclination of the tire main axis to a horizontal plane;
specifically, referring to FIG. 8, the principal axes X-1, X-2, and Y of the tires of the vehicle are determined from the images taken by the aircraft;
Then respectively calculating the inclination of the x-1, the x-2 and the Y with the horizontal plane;
s103223, inputting the inclination into a model trained by a learning machine, and generating a comparison result.
The technical scheme shown in the embodiment of the application is that a large amount of gradients and vehicle accidents are input into a computer in advance, and then models of the gradients and the vehicle accidents are constructed;
and then inputting the inclination of the vehicle to be tested into a model trained by a learning machine, and determining whether the vehicle has an accident or not.
The method that this application embodiment shows, frame through aircraft detection device detects, can shoot with the accurate angle of standard, then pass front tire figure and skeleton image back application platform server, call failure assessment function module, this module can compare the image that newly shoots and the standard image when this motorcycle type newly leaves the factory, the slope degree of analysis skeleton deformation degree or tire main axis and horizontal ground, the model that comes out through machine learning judges whether the vehicle that awaits measuring takes place overweight accident, or the damage degree that the evaluation accident caused, be convenient for vehicle pricing.
example 7:
The chassis inspection methods shown in the prior art are used for various ditches, lifters, chassis inspection convex mirrors, fixed vehicle chassis inspection devices, and the like. And the trench is used for driving the vehicle to the trench, and the inspector stands in the trench to inspect the chassis of the vehicle. The lifter lifts the vehicle from ground to mid-air, and a detector can detect the vehicle chassis. The chassis inspection convex mirror is arranged at the bottom of the vehicle, and the inspector inspects the chassis by observing the convex mirror. A fixed vehicle chassis detection device needs to dig a pit on the ground and place the pit underground, and a camera is flush with the ground. The method needs a fixed place, has high requirements on a test site, is not easy to carry, and has low detection efficiency.
to solve the above problems, the present embodiment shows a chassis inspection method, specifically please refer to fig. 9;
embodiment 7 has similar steps to the solutions shown in any of embodiments 2 to 6, and the only difference is that in the solutions shown in embodiments 2 to 6, the aircraft is guided to be detected according to the detection strategy, and the step of generating the first collected information according to the detection result includes:
S1021, driving the aircraft to move based on the driving path, and starting the camera to shoot a local picture; or driving the aircraft to move, starting the camera to shoot a local picture, recording the position of the aircraft in real time, generating a control signal of the aircraft according to the position, and controlling the aircraft to pause, rotate and start; the control signal includes: pause signal, rotation signal, drive signal;
In order to ensure that the aircraft successfully acquires the picture of the vehicle chassis in the detection process, the method disclosed by the embodiment of the application ensures that the aircraft is always positioned at the bottom of the vehicle.
In order to ensure that the aircraft is always positioned at the bottom of the vehicle, the embodiment of the application shows two technical solutions:
firstly, by designing a running path in advance and then driving an aircraft, the aircraft is always positioned at the bottom of the vehicle according to the running path. In the moving process of the aircraft, a camera is adopted to shoot a local picture of the vehicle chassis.
secondly, the aircraft is driven firstly, the position of the aircraft is obtained in real time in the moving process of the aircraft, and the method for obtaining the position of the aircraft in real time can be a radar positioning mode, a GPS (global positioning system), a base station positioning mode, a WiFi (wireless fidelity) AP (access point) positioning mode and a Bluetooth positioning mode (iBeacon).
specifically, if the position of the aircraft is found to be far away from the bottom of the vehicle in the positioning process, the aircraft is controlled to pause or turn.
In the moving process of the aircraft, a camera is adopted to shoot a local picture of a vehicle chassis;
s1022, the local pictures are spliced to obtain first acquisition information.
the local pictures are spliced, and the splicing mode can be performed according to the time of picture acquisition, for example: and acquiring a local picture every 5s, wherein the splicing mode is that the local picture acquired in the 1 st s is connected with the local picture acquired in the 5 th s, connected with the local picture acquired in the 10 th s and connected with the local picture acquired in the 15 th s, and sequentially spliced downwards.
the picture stitching techniques shown in the prior art can be applied to the technical solutions shown in the embodiments of the present application, and herein, because of limited space, the description is not an example.
according to the method, the driving path of the aircraft is planned, or the position of the aircraft is obtained in real time, the control signal is generated according to the position, the aircraft is controlled to move, the aircraft is guaranteed to be located at the bottom of the vehicle all the time, in the moving process of the aircraft, the camera collects the local pictures of the vehicle chassis in real time, the vehicle chassis pictures are obtained through splicing of the local pictures, and the chassis performance of the vehicle is detected according to the vehicle chassis pictures. According to the method, in the process of detecting the vehicle chassis, the limitation of a field is avoided, the collection of pictures is completed in the process of moving the vehicle chassis through the aircraft, and the detection efficiency is improved.
the aircraft continuously shoots local images of the chassis by using the overhead camera in the motion process. And each picture has position information during shooting, and the panoramic picture of the chassis is preliminarily spliced by using the position information and the camera parameters. However, in consideration of errors in positioning and navigation, if a high-quality panoramic image needs to be obtained, rotation and translation fine adjustment needs to be performed on the image according to feature matching in adjacent images, so that a panoramic image with pixel accuracy is obtained.
and scanning the periphery by using an overhead laser radar under the chassis of the vehicle. The four tires have distinct geometric features under lidar scanning results that can be used as markers to determine the position of the aircraft relative to the vehicle. The planning of the aircraft path is realized in a straight line travel + 90-degree pivot turning mode, and the deviation possibly caused by complex paths such as differential turning is avoided.
The aircraft continuously shoots local images of the chassis by using the overhead camera in the motion process. And each picture has position information during shooting, and the panoramic picture of the chassis is preliminarily spliced by using the position information and the camera parameters. However, in consideration of errors in positioning and navigation, if a high-quality panoramic image needs to be obtained, rotation and translation fine adjustment needs to be performed on the image according to feature matching in adjacent images, so that a panoramic image with pixel accuracy is obtained.
Example 8:
Please refer to fig. 10;
A third aspect of the embodiments of the present application shows a vehicle detection apparatus, including:
The obtaining unit 21 is configured to obtain vehicle information, and invoke a detection policy corresponding to the vehicle information, where the detection policy includes: a driving path, a detection process and a photographing position;
the first acquisition information generating unit 22 is used for guiding the aircraft to detect according to the detection strategy and generating first acquisition information according to the detection result;
and a detection report generating unit 23, configured to analyze the first acquisition information and generate a detection report.
Optionally, the obtaining unit includes:
a first acquisition unit that acquires vehicle information, the vehicle information including: the vehicle model, and, the license plate number;
The judging unit is used for traversing a vehicle type library and judging whether the vehicle type exists in the vehicle type library or not;
The communication unit is used for communicating the central background system if the central background system does not exist, the central background system obtains the control authority of the aircraft, controls the aircraft to detect the vehicle and simultaneously generates a detection strategy corresponding to the vehicle model;
a storage unit for storing the detection policy;
And the calling unit is used for calling the detection strategy corresponding to the vehicle model if the detection strategy exists.
Optionally, the detection report generating unit includes:
the problem item determining unit is used for analyzing the first acquisition information and determining a problem item;
the sending unit is used for sending the problem item to a detection terminal, and the terminal carries out calibration and rechecking according to the problem item to generate second detection information;
And the second detection information acquisition unit is used for acquiring the second detection information and generating a detection report based on the first acquisition information and the second detection information.
optionally, the question item determination unit includes:
A first receiving unit, configured to receive the first acquisition information, where the first acquisition information includes: picture information, sound information, exhaust gas detection information, and driving behavior information;
the comparison unit is used for comparing the first acquisition information with standard information to generate a comparison result;
and the first question item determining unit is used for determining question items according to the comparison result.
Optionally, the alignment unit comprises:
the tire main axis obtaining unit is used for obtaining the tire main axis according to the image information;
a calculation unit for calculating the inclination of the main axis of the tyre with a horizontal plane;
and the comparison result generating unit is used for inputting the inclination into a model trained by the learning machine to generate a comparison result.
optionally, the generating unit according to the first acquisition information includes:
the local picture shooting unit is used for planning a running path of the aircraft, driving the aircraft to move based on the running path and starting the camera to shoot a local picture; or driving the aircraft to move, starting the camera to shoot a local picture, recording the position of the aircraft in real time, generating a control signal of the aircraft according to the position, and controlling the aircraft to pause, rotate and start; the control signal includes: pause signal, rotation signal, drive signal;
and the splicing unit is used for splicing the local pictures to obtain first acquisition information.
other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
it will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (14)
1. A vehicle detection method, characterized in that the method comprises:
Obtaining vehicle information, and calling a detection strategy corresponding to the vehicle information, wherein the detection strategy comprises the following steps: a driving path, a detection process and a photographing position;
guiding the aircraft to detect according to the detection strategy, and generating first acquisition information according to a detection result;
and analyzing the first acquisition information to generate a detection report.
2. the method of claim 1, wherein the step of obtaining vehicle information and invoking a detection strategy corresponding to the vehicle information comprises:
acquiring vehicle information, wherein the vehicle information comprises: the vehicle model, and, the license plate number;
traversing a vehicle type library, and judging whether the vehicle type exists in the vehicle type library or not;
If the vehicle model does not exist, a central background system is communicated, the central background system obtains the control authority of the aircraft, the aircraft is controlled to detect the vehicle, and meanwhile, a detection strategy corresponding to the vehicle model is generated;
Storing the detection strategy;
and if so, calling a detection strategy corresponding to the vehicle model.
3. the method of claim 1, wherein the step of parsing the first collected information to generate a detection report comprises:
Analyzing the first acquisition information and determining problem items;
sending the problem item to a detection terminal, and calibrating and rechecking the terminal according to the problem item to generate second detection information;
and acquiring the second detection information, and generating a detection report based on the first acquisition information and the second detection information.
4. The method of claim 3, wherein the step of parsing the first collected information to determine the problem item comprises:
Receiving the first acquisition information, wherein the first acquisition information comprises: picture information, sound information, exhaust gas detection information, and driving behavior information;
comparing the first acquisition information with standard information to generate a comparison result;
and determining the problem item according to the comparison result.
5. the method of claim 4, wherein the step of comparing the first collected information with the standard information to generate a comparison result comprises:
Acquiring the main axis of the tire according to the image information;
calculating the inclination of the main axis of the tire to the horizontal plane;
and inputting the inclination into a model trained by a learning machine to generate a comparison result.
6. The method of claim 1, wherein the step of directing aircraft inspection according to the inspection strategy and generating first collected information according to inspection results comprises:
driving the aircraft to move based on the driving path, and starting the camera to shoot a local picture; or driving the aircraft to move, starting the camera to shoot a local picture, recording the position of the aircraft in real time, generating a control signal of the aircraft according to the position, and controlling the aircraft to pause, rotate and start; the control signal includes: pause signal, rotation signal, drive signal;
And splicing the local pictures to obtain first acquisition information.
7. a vehicle detection apparatus, characterized in that the apparatus comprises:
the device comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring vehicle information and calling a detection strategy corresponding to the vehicle information, and the detection strategy comprises: a driving path, a detection process and a photographing position;
The first acquisition information generating unit is used for guiding the aircraft to detect according to the detection strategy and generating first acquisition information according to a detection result;
and the detection report generating unit is used for analyzing the first acquisition information and generating a detection report.
8. The apparatus of claim 7, wherein the obtaining unit comprises:
A first acquisition unit that acquires vehicle information, the vehicle information including: the vehicle model, and, the license plate number;
the judging unit is used for traversing a vehicle type library and judging whether the vehicle type exists in the vehicle type library or not;
the communication unit is used for communicating the central background system if the central background system does not exist, the central background system obtains the control authority of the aircraft, controls the aircraft to detect the vehicle and simultaneously generates a detection strategy corresponding to the vehicle model;
a storage unit for storing the detection policy;
And the calling unit is used for calling the detection strategy corresponding to the vehicle model if the detection strategy exists.
9. the apparatus of claim 7, wherein the detection report generating unit comprises:
The problem item determining unit is used for analyzing the first acquisition information and determining a problem item;
The sending unit is used for sending the problem item to a detection terminal, and the terminal carries out calibration and rechecking according to the problem item to generate second detection information;
and the second detection information acquisition unit is used for acquiring the second detection information and generating a detection report based on the first acquisition information and the second detection information.
10. the apparatus of claim 9, wherein the problem item determination unit comprises:
a first receiving unit, configured to receive the first acquisition information, where the first acquisition information includes: picture information, sound information, exhaust gas detection information, and driving behavior information;
The comparison unit is used for comparing the first acquisition information with standard information to generate a comparison result;
and the first question item determining unit is used for determining question items according to the comparison result.
11. The apparatus of claim 10, wherein the alignment unit comprises:
the tire main axis obtaining unit is used for obtaining the tire main axis according to the image information;
A calculation unit for calculating the inclination of the main axis of the tyre with a horizontal plane;
And the comparison result generating unit is used for inputting the inclination into a model trained by the learning machine to generate a comparison result.
12. The apparatus of claim 7, wherein the means for generating according to the first acquisition information comprises:
the local picture shooting unit is used for planning a running path of the aircraft, driving the aircraft to move based on the running path and starting the camera to shoot a local picture; or driving the aircraft to move, starting the camera to shoot a local picture, recording the position of the aircraft in real time, generating a control signal of the aircraft according to the position, and controlling the aircraft to pause, rotate and start; the control signal includes: pause signal, rotation signal, drive signal;
And the splicing unit is used for splicing the local pictures to obtain first acquisition information.
13. a vehicle detection system, characterized in that the system comprises:
The system comprises an aircraft, an application platform server connected with the aircraft, and a terminal connected with the application platform server;
the aircraft is used for collecting picture information, sound information, tail gas detection information and driving behavior information;
An application platform server for implementing the method of any one of claims 1 to 6;
and the terminal is used for acquiring the second detection information.
14. The system of claim 13, further comprising: a central back-office system;
and the central background system is used for obtaining the control authority of the aircraft, controlling the aircraft to detect the vehicle and generating a detection strategy corresponding to the vehicle model.
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