KR20230046557A - Univesal remote vehicle diagnostic system and method - Google Patents

Abstract

The present invention relates to a universal remote vehicle diagnostic system and method, the system comprising a vehicle diagnostic relay device which collects sensor data for diagnosis of a vehicle to be diagnosed, acquired through a plurality of sensors provided in the vehicle to be diagnosed, in a state of being in communication with the vehicle to be diagnosed and generates diagnostic data to make the collected sensor data function as analysis data by a neural network; and a vehicle diagnostic server which receives the diagnostic data from the vehicle diagnostic relay device, applies the same to a pre-trained neural network model to diagnose the status of the vehicle to be diagnosed, and feeds back the diagnosis results to the vehicle diagnostic relay device. The universal remote vehicle diagnostic system and method of the present invention can present a universally applicable vehicle diagnosis topology that ensures objectivity in vehicle diagnosis methods and diagnosis results.

Description

Universal remote vehicle diagnosis system and method {UNIVESAL REMOTE VEHICLE DIAGNOSTIC SYSTEM AND METHOD}

The present invention relates to a universal remote vehicle diagnosis system and method, and more particularly, to a universal remote vehicle diagnosis system and method for performing vehicle diagnosis, failure prediction, and vehicle health management through a neural network. will be.

In general, when a breakdown occurs in a vehicle or a diagnosis is required, users visit a repair shop and have the vehicle inspected. The mechanic diagnoses the vehicle using the diagnostic device, proceeds with consultation, and delivers the vehicle to the user after servicing the vehicle. Hardware and software for diagnosing a vehicle are different for each vehicle vendor. Therefore, the mechanic has to purchase and manage diagnostic hardware and software for each vendor of the vehicle, and also has the hassle of managing hardware and software versions of the diagnostic device according to vehicle specifications whenever a new vehicle is released.

A method of performing vehicle fault diagnosis through OBD (On-Board Diagnostics) installed in the vehicle is performed by performing vehicle diagnosis based on DTC (Diagnostic Trouble Codes). In this case, since the fault diagnosis code can be acquired only after a vehicle failure occurs, the vehicle diagnosis method based on the fault diagnosis code has limitations limited to post-diagnosis after a fault occurs, and also the failure of a specific sensor and system occurs. Since it appears only in the problem, it is difficult to identify the cause of the failure. There are cases in which the cause of failure is specified according to the skill level of the mechanic, but in the method relying on the mechanic's personal experience, deviations occur in the vehicle diagnostic results, which makes it difficult to diagnose more objectively. Accordingly, even when vehicle diagnosis is performed using the same fault diagnosis code, since the analysis result is different for each mechanic, subsequent maintenance measures are different, making it difficult to objectively diagnose and repair the vehicle.

The background art of the present invention is disclosed in Korean Patent Publication No. 10-2017-0007074 (published on January 18, 2017).

The present invention has been devised to solve the above problems, and an object according to an aspect of the present invention is to eliminate the conventional problems caused by vehicle failure diagnosis methods and deviations in the diagnosis results by vehicle vendors and mechanics, An object of the present invention is to provide a general-purpose remote vehicle diagnosis system and method capable of securing objectivity in a vehicle diagnosis method and diagnosis result and presenting a more universally applicable vehicle diagnosis topology.

A vehicle diagnostic system according to an aspect of the present invention collects sensor data for diagnosis of a vehicle to be diagnosed, acquired through a plurality of sensors provided in the vehicle to be diagnosed, in a state of communication with the vehicle to be diagnosed, and a vehicle diagnostic relay device generating diagnostic data so that the collected sensor data functions as analysis data by a neural network; and a vehicle diagnostic server that receives the diagnosis data from the vehicle diagnostic relay device, applies the diagnostic data to a pre-learned neural network model, diagnoses the state of the vehicle to be diagnosed, and feeds back the diagnosis result to the vehicle diagnostic relay device. to be characterized

In the present invention, the vehicle diagnostic relay device is configured to be connected to OBD (On-Board Diagnostics) provided in the vehicle to be diagnosed, transmits a diagnosis request message for the diagnosis to the vehicle to be diagnosed, and sends a response message therefor. It is characterized in that it is configured to establish a communication connection with the vehicle to be diagnosed in a receiving manner.

In the present invention, the vehicle diagnosis relay device may be configured to perform the communication disconnection time when the response message is not received from the diagnosis target vehicle within a predefined communication disconnection time to function as a communication connection threshold time with the diagnosis target vehicle. It is characterized by increasing.

In the present invention, the vehicle diagnostic relay device collects the collected sensor data, Diagnostic Trouble Codes (DTCs) of the vehicle to be diagnosed, and location information of the vehicle diagnostic relay device, and collects the collected data. It is characterized in that the diagnosis data is generated and transmitted to the vehicle diagnosis server by a method of converting to data according to a transmission protocol for wireless transmission.

In the present invention, the neural network model is learned to identify the state of the vehicle as a class of input data through a neural network and is predefined in the vehicle diagnosis server, and the vehicle diagnosis server performs sensor data and fault diagnosis on the diagnosis data. Code is applied to the neural network model to generate status information of the engine, transmission, braking, steering, suspension, airbag, and electric system of the vehicle to be diagnosed as diagnosis result data.

In the present invention, the vehicle diagnosis server identifies parts required for maintenance of the vehicle to be diagnosed from the diagnosis result data derived by the neural network model, and obtains location information of the vehicle diagnosis relay device on the diagnosis data. Based on this, information of a repair shop capable of supplying the identified parts may be included in the diagnosis result data and transmitted to the vehicle diagnosis relay device.

In the present invention, the vehicle diagnostic relay device may increase the communication disconnection time when the diagnosis result data is not received from the vehicle diagnostic server within the communication disconnection time.

In the present invention, the vehicle diagnosis relay device transmits the diagnosis result data received from the vehicle diagnosis server to a mechanic terminal possessed by a mechanic of a corresponding service shop or a user terminal possessed by a user of the vehicle to be diagnosed, and The diagnosis result data is characterized in that it is used to update a fault diagnosis code of the vehicle to be diagnosed.

The present invention discloses a vehicle diagnosis relay device including a processor and a memory storing commands executed by the processor, and relaying between a vehicle diagnosis server and a vehicle diagnosis server for diagnosis of a vehicle to be diagnosed, wherein the processor comprises: In a state in which communication is connected to the vehicle to be diagnosed, sensor data for diagnosis of the vehicle to be diagnosed, which are acquired through a plurality of sensors provided in the vehicle to be diagnosed, are collected, and the collected sensor data is stored in a neural network (Neural Network). ) Generates diagnostic data to function as analysis data and transmits it to the vehicle diagnosis server, receives feedback from the vehicle diagnosis server and provides the diagnosis result data to the diagnosis target vehicle, The diagnosis result data of the vehicle may be generated in such a way that the condition of the vehicle to be diagnosed is diagnosed by applying the diagnosis data to a pre-learned neural network model.

Disclosed is a vehicle diagnosis server that includes a processor and a memory storing instructions executed by the processor, and diagnoses a vehicle to be diagnosed under the relay of a vehicle diagnosis relay device, wherein the processor includes the vehicle diagnosis relay device. The diagnostic data for diagnosis of the vehicle to be diagnosed, which is transmitted from, is applied to a pre-learned neural network model to diagnose the state of the vehicle to be diagnosed, and the diagnosis result is fed back to the vehicle diagnostic relay device, wherein the diagnostic data, In a state in which the vehicle to be diagnosed and the vehicle diagnostic relay device are connected in communication, sensor data for diagnosis of the vehicle to be diagnosed, acquired through a plurality of sensors provided in the vehicle to be diagnosed, function as analysis data by a neural network. Characterized in that it is created in a format for

A vehicle diagnosis method according to an aspect of the present invention relates to a sensor for diagnosing a vehicle to be diagnosed, acquired through a plurality of sensors provided in the vehicle to be diagnosed, in a state in which a vehicle diagnosis relay device is connected to the vehicle to be diagnosed by communication. collecting data; generating, by the vehicle diagnostic relay device, diagnostic data for allowing the collected sensor data to function as analysis data by a neural network; diagnosing a state of the vehicle to be diagnosed by a vehicle diagnosis server by receiving the diagnosis data from the vehicle diagnosis relay device and applying the data to a pre-learned neural network model; and feeding back, by the vehicle diagnosis server, a result of diagnosing the state of the vehicle to be diagnosed to the vehicle diagnosis relay device.

According to one aspect of the present invention, the present invention continuously collects sensor data at the system level of the vehicle, converts it into big data, trains a neural network model configured to diagnose the state of the vehicle based on the big data data, and then learns By performing vehicle diagnosis based on the neural network model, it is possible to predict failures along with vehicle diagnosis, away from post-failure maintenance based on diagnosis after failure, and to eliminate diagnostic deviations caused by vehicle vendors or mechanics, making it more objective and universal. An ideal vehicle diagnosis topology may be prepared.

1 and 2 are exemplary diagrams showing the structure of a vehicle diagnosis system according to an embodiment of the present invention.
3 is an exemplary view showing a transmission protocol of diagnostic data in a vehicle diagnostic relay device according to an embodiment of the present invention.
4 is a flowchart showing a method for diagnosing a vehicle according to an embodiment of the present invention.

Hereinafter, embodiments of a system and method for universal remote vehicle diagnosis according to the present invention will be described with reference to the accompanying drawings. In this process, the thickness of lines or the size of components shown in the drawings may be exaggerated for clarity and convenience of description. In addition, terms to be described later are terms defined in consideration of functions in the present invention, which may vary according to the intention or custom of a user or operator. Therefore, definitions of these terms will have to be made based on the content throughout this specification.

1 and 2 are exemplary diagrams showing the structure of a vehicle diagnostic system according to an embodiment of the present invention, and FIG. 3 is an exemplary diagram showing a transmission protocol of diagnostic data in a vehicle diagnostic relay device according to an exemplary embodiment of the present invention. am.

Referring to FIG. 1 , the vehicle diagnosis system according to the present embodiment may include a vehicle diagnosis relay device 200 and a vehicle diagnosis server 300, and each component includes processors 210 and 310 and a memory as sub-units thereof. (220, 320). The processors 210 and 310 function as a controller that controls the operation of the vehicle diagnostic relay device 200 and the vehicle diagnostic server 300, and is implemented as a central processing unit (CPU) or system on chip (SoC). It can be. The processors 210 and 310 may control a plurality of hardware or software components connected to the processors 210 and 310 by driving an operating system or an application, and may perform various data processing and operations. The processors 210 and 310 may be configured to execute at least one command stored in the memories 220 and 320 and store data resulting from the execution in the memories 220 and 320 .

As shown in FIG. 2 , the vehicle diagnosis relay device 200 is provided in a repair shop and functions as a device that relays the diagnosis target vehicle 100 and the vehicle diagnosis server 300 to diagnose the diagnosis target vehicle 100 . In addition, the vehicle diagnosis server 300 may be provided in a remote diagnosis center and function as a device for diagnosing the vehicle 100 to be diagnosed under the relay of the vehicle diagnosis relay device 200 . Referring to FIGS. 1 and 2 , the operation of the vehicle diagnosis system according to the present embodiment will be described in detail. The vehicle diagnosis relay device 200 communicates sensor data of the vehicle 100 to be diagnosed while being connected to the vehicle 100 to be diagnosed. is collected to generate diagnostic data for diagnosis of the vehicle 100 to be diagnosed, and the vehicle diagnostic server 300 receives the diagnostic data from the vehicle diagnostic relay device 200 and applies it to a pre-learned neural network model for diagnosis. It can operate to diagnose the condition of the target vehicle 100 . The diagnosis result data generated by the vehicle diagnosis server 300 is displayed on the expert terminal UT3 provided in the remote diagnosis center or fed back to the vehicle diagnosis relay device 200, and then the technician terminal possessed by the mechanic of the corresponding repair shop. UT2 or the user terminal UT1 possessed by the user of the vehicle 100 to be diagnosed can be displayed so that the mechanic and the user can check the diagnosis result.

Based on the above information, the vehicle diagnosis system according to the present embodiment will be described in detail, focusing on operations of the vehicle diagnosis relay device 200 and the vehicle diagnosis server 300 .

First, the vehicle diagnostic relay device 200 is a sensor for diagnosing the vehicle 100 to be diagnosed, which is acquired through a plurality of sensors provided in the vehicle to be diagnosed 100 while being connected to the vehicle 100 to be diagnosed. data can be collected.

Specifically, the vehicle diagnostic relay device 200 may be configured to be connected to OBD (On-Board Diagnostics) provided in the vehicle to be diagnosed 100 through a connector. Accordingly, the communication connection between the diagnosis target vehicle 100 and the vehicle diagnosis relay device 200 is such that a diagnosis request message for diagnosis is transmitted from the vehicle diagnosis relay device 200 to the diagnosis target vehicle 100 and a response message is received. may be established in a manner that is transmitted to the vehicle diagnostic relay device 200 .

Meanwhile, according to the OBD communication method, in a state in which the diagnosis target vehicle 100 and the vehicle diagnosis relay device 200 are connected, the vehicle diagnosis relay device 200 transmits a diagnosis request message through the OBD2 terminal to the diagnosis target vehicle 100. ), and the communication connection is disconnected if the response message is not received within a predefined communication connection disconnection time to function as a communication connection threshold time with the vehicle 100 to be diagnosed. Therefore, in order to prevent a situation in which the connection of the vehicle 100 to be diagnosed is not started even though the diagnosis is not started, the vehicle diagnosis relay device 200 in the present embodiment is configured to detect the vehicle 100 to be diagnosed within the communication disconnection time. When a response message is not received from the communication connection disconnection time can be operated to increase.

In a state where the communication connection between the diagnosis target vehicle 100 and the vehicle diagnosis relay device 200 is established and maintained through the above process, the vehicle diagnosis relay device 200 diagnoses based on the OBD of the diagnosis target vehicle 100. Sensor data may be collected from a plurality of sensors provided in the target vehicle 100 . A plurality of sensors provided in the vehicle 100 to be diagnosed include an engine system sensor (eg, an engine RPM sensor, an air flow sensor, an atmospheric pressure sensor, a manifold absolute pressure (MAP) sensor, a throttle position sensor, etc.), a shift system sensor ( Examples: Transmission fluid temperature sensor, pulse generator sensor, etc.), braking system sensors (eg brake pressure sensor, tire pressure sensor, etc.), steering system sensors (eg steering angle sensor, column torque sensor, etc.), suspension system sensors (eg car body attitude sensors, suspension pressure sensors, etc.), airbag system sensors (e.g. collision detection sensors, rollover detection sensors, etc.), and other electronic system sensors (e.g. navigation sensors, microphone noise canceling sensors, climate sensor's climate sensor, etc.). can include Each of these sensor data may be collected during temporary operation of the vehicle at the workshop.

When the sensor data is collected, the vehicle diagnostic relay device 200 may generate diagnostic data so that the collected sensor data functions as analysis data by a neural network. At this time, the vehicle diagnostic relay device 200 collects sensor data, Diagnostic Trouble Codes (DTCs) of the vehicle to be diagnosed 100, and location information of the vehicle diagnostic relay device 200, and transmits the collected data. Diagnosis data may be generated by converting data according to the TCP protocol for wireless transmission to the vehicle diagnosis server 300 .

Specifically, since the sensor data and fault diagnosis code of the vehicle 100 to be diagnosed correspond to data according to the vehicle communication interface (VCI) protocol, the vehicle diagnostic relay device 200 provides the sensor data and fault diagnosis code. And, the location information of the vehicle diagnostic relay device 200 is converted into data according to the TCP protocol for wireless transmission to the vehicle diagnostic server 300, and the converted data is transferred to the vehicle diagnostic server 300 through the TCP/IP wireless network. can be sent to 3 shows a transmission protocol of diagnostic data, and the vehicle diagnostic relay device 200 uses a physical layer, a data link layer, and an application layer among OSI 7 layers for diagnosis. The data may be transmitted to the vehicle diagnostic server 300, and the vehicle diagnostic server 300 may operate to perform a WebScan service that remotely analyzes the received diagnostic data.

When diagnostic data generated through the above process is transmitted from the vehicle diagnostic relay device 200 to the vehicle diagnostic server 300, the vehicle diagnostic server 300 applies the received diagnostic data to a pre-learned neural network model to be diagnosed. The condition of the vehicle 100 may be diagnosed.

Here, the neural network model may correspond to a deep learning model learned to identify a vehicle state as a class of input data through a neural network. In the vehicle diagnostic server 300, diagnostic data collected for diagnosing a plurality of vehicles during the past time period may be converted into big data and built into a database, and a neural network model for diagnosing the state of a vehicle based on such big data is deep learning It may be learned according to and predefined in the vehicle diagnosis server 300 . As described above, the sensor data of the diagnosis data may include sensor data of an engine system sensor, a transmission system sensor, a braking system sensor, a steering system sensor, a suspension system sensor, an airbag system sensor, and other electric system sensors. Accordingly, the vehicle The diagnosis server 300 applies sensor data and fault diagnosis codes on the diagnosis data to a neural network model, and as the diagnosis result data, state information of the engine, shift, braking, steering, suspension, airbag, and electric system of the vehicle 100 to be diagnosed. can be operated to generate

As a follow-up execution logic following the diagnosis logic of the vehicle 100 to be diagnosed by the neural network model, the vehicle diagnosis server 300 is required for maintenance of the vehicle 100 to be diagnosed from the diagnosis result data derived by the neural network model. Parts are identified, and based on location information of the vehicle diagnostic relay device 200 on the diagnosis data, information on repair shops capable of supplying the identified parts may be included in diagnosis result data and transmitted to the vehicle diagnostic relay device 200. . That is, the vehicle diagnosis server 300 may determine the location of other repair shops and parts inventory information in connection with the external system (ext1-3), and inventory of parts required for maintenance of the currently diagnosed diagnosis target vehicle 100. Maintenance of the vehicle 100 to be diagnosed at the repair shop by including the location of the repair shop near the location of the vehicle diagnostic relay device 200 as another repair shop with can proceed efficiently.

Meanwhile, when the OBD communication method is used, since the diagnosis result data generated through the above-described process must also be fed back to the vehicle diagnostic relay device 200 within the aforementioned communication disconnection time, the vehicle diagnostic relay device 200 is connected to the communication connection. When diagnosis result data is not received from the vehicle diagnosis server 300 within the release time, the communication connection release time may be increased. As a method, the vehicle diagnostic relay device 200 generates a delay signal (ping msg) and returns to the vehicle diagnostic relay device 200 from the vehicle diagnostic relay device 200 via the vehicle to be diagnosed 100 for a round trip. A method of extending a delay (RTD: Round Trip Delay) may be applied.

When the diagnosis result data is received from the vehicle diagnosis server 300, the vehicle diagnosis relay device 200 transmits the received diagnosis result data to the mechanic terminal UT2 possessed by the mechanic of the corresponding repair shop or the user of the vehicle 100 subject to diagnosis. may be transmitted to the user terminal UT1 possessed by the technician or the user to check the diagnosis result. In addition, diagnosis result data by the vehicle diagnosis server 300 may be used to update a fault diagnosis code of the vehicle 100 to be diagnosed.

FIG. 4 is a flowchart showing a vehicle diagnosis method according to an embodiment of the present invention. Referring to FIG. 4, the vehicle diagnosis method according to the present embodiment will be described. It is explained based on the composition of the structure.

First, the vehicle diagnostic relay device 200 is a sensor for diagnosing the vehicle 100 to be diagnosed, which is acquired through a plurality of sensors provided in the vehicle to be diagnosed 100 while being connected to the vehicle 100 to be diagnosed. Data is collected (S100). As described above, the vehicle diagnosis relay device 200 is configured to be connected to the OBD provided in the vehicle to be diagnosed 100, transmits a diagnosis request message for diagnosis to the vehicle to be diagnosed 100, and sends a response message thereto. It is configured to establish a communication connection with the vehicle 100 to be diagnosed in a receiving manner, and accordingly, in step S100, the vehicle diagnosis relay device 200 is predefined to function as a communication connection threshold time with the vehicle 100 to be diagnosed. If a response message is not received from the vehicle 100 to be diagnosed within the specified communication disconnection time, the communication disconnection time may be increased.

Subsequently, the vehicle diagnostic relay device 200 generates diagnostic data for the sensor data collected in step S100 to function as analysis data by the neural network (S200). In step S200, the vehicle diagnostic relay device 200 transmits the sensor data collected in step S100, diagnostic trouble codes (DTCs) of the vehicle 100 to be diagnosed, and location information of the vehicle diagnostic relay device 200. Data for diagnosis is created by collecting and converting the collected data into data according to the TCP protocol for wireless transmission.

Subsequently, the vehicle diagnosis server 300 receives diagnosis data from the vehicle diagnosis relay device 200 and applies the previously learned neural network model to diagnose the state of the vehicle 100 to be diagnosed (S300). The neural network model is learned to identify the state of the vehicle as a class of input data through the neural network and is predefined in the vehicle diagnostic server 300. Accordingly, in step S300, the vehicle diagnostic server 300 detects sensor data and failures on the diagnostic data. The diagnostic code is applied to the neural network model to generate state information of the engine, transmission, braking, steering, suspension, airbag, and electric system of the vehicle 100 to be diagnosed as diagnostic result data.

Next, the vehicle diagnosis server 300 feeds back the result of diagnosing the state of the vehicle 100 to be diagnosed to the vehicle diagnosis relay device 200 (S400). In step S400, the vehicle diagnostic server 300 identifies parts required for maintenance of the vehicle 100 subject to diagnosis from the diagnostic result data in step S300, and based on the location information of the vehicle diagnostic relay device 200 on the diagnostic data. , Information on repair shops capable of supplying the identified parts may be included in diagnosis result data and transmitted to the vehicle diagnosis relay device 200 (S400).

Subsequently, the vehicle diagnosis relay device 200 transfers the diagnosis result data received from the vehicle diagnosis server 300 to a mechanic terminal UT2 possessed by a mechanic of a corresponding service shop or a user terminal possessed by a user of the vehicle 100 subject to diagnosis. (UT1) (S500). In this case, the diagnosis result data may be used to update the fault diagnosis code of the vehicle 100 to be diagnosed.

In this way, the present embodiment continuously collects sensor data at the system level of the vehicle, transforms it into big data, trains a neural network model configured to diagnose the state of the vehicle based on the big data data, and then uses the learned neural network model based on the data. By performing vehicle diagnosis, it is possible to predict failure along with vehicle diagnosis, away from post-failure maintenance based on diagnosis after failure, and to eliminate diagnosis deviations caused by vehicle vendors or mechanics, a more objective and universal vehicle diagnosis topology can be created. can be provided.

Implementations described herein may be embodied in, for example, a method or process, an apparatus, a software program, a data stream, or a signal. Even if discussed only in the context of a single form of implementation (eg, discussed only as a method), the implementation of features discussed may also be implemented in other forms (eg, an apparatus or program). The device may be implemented in suitable hardware, software and firmware. The method may be implemented in an apparatus such as a processor, which is generally referred to as a processing device including, for example, a computer, microprocessor, integrated circuit, programmable logic device, or the like. Processors also include communication devices such as computers, cell phones, personal digital assistants ("PDAs") and other devices that facilitate communication of information between end-users.

Although the present invention has been described with reference to the embodiments shown in the drawings, it should be noted that this is only exemplary and various modifications and equivalent other embodiments are possible from those skilled in the art to which the technology pertains. will understand Therefore, the true technical protection scope of the present invention should be defined by the claims below.

1: vehicle diagnostic system
100: vehicle to be diagnosed
200: Vehicle diagnostic relay device
300: vehicle diagnosis server
210, 310: processor
220: 320: memory

Claims (11)

In a state of communication with the vehicle to be diagnosed, sensor data for diagnosis of the vehicle to be diagnosed, which are acquired through a plurality of sensors provided in the vehicle to be diagnosed, are collected, and the collected sensor data is transmitted to a neural network. a vehicle diagnostic relay device generating diagnostic data to function as analysis data by the vehicle; and
a vehicle diagnostic server that receives the diagnostic data from the vehicle diagnostic relay device, applies the diagnostic data to a pre-learned neural network model, diagnoses a state of the vehicle to be diagnosed, and feeds back the diagnosis result to the vehicle diagnostic relay device;
Vehicle diagnostic system comprising a.
According to claim 1,
The vehicle diagnostic relay device is configured to be connected to OBD (On-Board Diagnostics) provided in the vehicle to be diagnosed, transmits a diagnosis request message for the diagnosis to the vehicle to be diagnosed, and receives a response message therefor. A vehicle diagnosis system, characterized in that configured to establish a communication connection with the vehicle to be diagnosed.
According to claim 2,
The vehicle diagnostic relay device increases the communication connection disconnection time when the response message is not received from the diagnosis target vehicle within a predefined communication disconnection time to function as a communication connection critical time with the diagnosis target vehicle. Characterized vehicle diagnostic system.
According to claim 3,
The vehicle diagnostic relay device collects the collected sensor data, diagnostic trouble codes (DTCs) of the vehicle to be diagnosed, and location information of the vehicle diagnostic relay device, and wirelessly transmits the collected data. The vehicle diagnostic system, characterized in that for generating the diagnosis data by a method of converting into data according to the TCP protocol for transmission to the vehicle diagnosis server.
According to claim 4,
The neural network model is predefined in the vehicle diagnosis server by learning to identify the state of the vehicle as a class of input data through the neural network,
The vehicle diagnosis server applies sensor data and fault diagnosis codes of the diagnosis data to the neural network model, and as the diagnosis result data, state information of the engine, transmission, braking, steering, suspension, airbag, and electric system of the vehicle to be diagnosed. Vehicle diagnostic system characterized in that for generating.
According to claim 5,
The vehicle diagnosis server determines parts required for maintenance of the vehicle to be diagnosed from the diagnosis result data derived by the neural network model, and based on the location information of the vehicle diagnosis relay device on the diagnosis data, The vehicle diagnosis system, characterized in that the diagnosis result data is transmitted to the vehicle diagnosis relay device by including information on a repair shop capable of supplying the damaged parts.
According to claim 6,
The vehicle diagnostic relay device increases the communication disconnection time when the diagnosis result data is not received from the vehicle diagnostic server within the communication disconnection time.
According to claim 7,
The vehicle diagnosis relay device transmits the diagnosis result data received from the vehicle diagnosis server to a mechanic terminal possessed by a mechanic of a corresponding service shop or a user terminal possessed by a user of the vehicle to be diagnosed;
The diagnosis result data is used to update a fault diagnosis code of the vehicle to be diagnosed.
A vehicle diagnostic relay device including a processor and a memory storing commands executed by the processor, and relaying between the vehicle to be diagnosed and a vehicle diagnostic server for diagnosis of the vehicle to be diagnosed, comprising:
The processor collects sensor data for diagnosis of the vehicle to be diagnosed, acquired through a plurality of sensors included in the vehicle to be diagnosed, in a state of being communicatively connected to the vehicle to be diagnosed, and the collected sensor data is stored in a neural network. Diagnosis data for functioning as analysis data by (Neural Network) is generated and transmitted to the vehicle diagnosis server, and the diagnosis result data of the vehicle to be diagnosed is received as feedback from the vehicle diagnosis server and provided to the vehicle to be diagnosed,
The diagnosis result data of the vehicle to be diagnosed is generated in such a way that the condition of the vehicle to be diagnosed is diagnosed by applying the diagnosis data to a pre-learned neural network model.
A vehicle diagnostic server including a processor and a memory in which commands executed by the processor are stored, and diagnosing a vehicle to be diagnosed under the relay of a vehicle diagnostic relay device, comprising:
The processor diagnoses the condition of the vehicle to be diagnosed by applying diagnostic data for diagnosis of the vehicle to be diagnosed, which is transmitted from the vehicle diagnostic relay device, to a pre-learned neural network model, and transmits the diagnosis result to the vehicle diagnostic relay device. Feedback with
The diagnostic data is sensor data for diagnosis of the vehicle to be diagnosed, acquired through a plurality of sensors provided in the vehicle to be diagnosed, in a state in which communication is connected between the vehicle to be diagnosed and the vehicle diagnostic relay device. Characterized in that it is created in a format for functioning as analysis data, a vehicle diagnostic server.
collecting sensor data for diagnosis of the vehicle to be diagnosed, acquired through a plurality of sensors provided in the vehicle to be diagnosed, in a state in which the vehicle diagnostic relay device is connected to the vehicle to be diagnosed;
generating, by the vehicle diagnostic relay device, diagnostic data for allowing the collected sensor data to function as analysis data by a neural network;
diagnosing a state of the vehicle to be diagnosed by a vehicle diagnosis server by receiving the diagnosis data from the vehicle diagnosis relay device and applying the data to a pre-learned neural network model; and
feeding back, by the vehicle diagnosis server, a result of diagnosing the state of the vehicle to be diagnosed to the vehicle diagnosis relay device;
Vehicle diagnostic method comprising a.

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