CN113448303A - Vehicle fault diagnosis method and system - Google Patents
Vehicle fault diagnosis method and systemDownload PDFInfo
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- CN113448303A CN113448303ACN202010229763.9ACN202010229763ACN113448303ACN 113448303 ACN113448303 ACN 113448303ACN 202010229763 ACN202010229763 ACN 202010229763ACN 113448303 ACN113448303 ACN 113448303A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0262—Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
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Abstract
Translated fromChinese
Description
Technical Field
The invention relates to the technical field of vehicle fault diagnosis, in particular to a vehicle fault diagnosis method and a vehicle fault diagnosis system.
Background
At present, vehicle faults are processed in the field of vehicle electronic after-sale maintenance mostly by means of experience and tools of people, and the tools are only limited to be used for fault maintenance by maintenance personnel through a maintenance help manual after fault codes of vehicles are acquired. At present, a maintenance help manual integrates an electrical appliance wiring harness schematic diagram, a part position diagram, a disassembly process and a fault setting condition to form a document according to possible reasons of faults through engineers, and the process is time-consuming and labor-consuming and is not easy to update and maintain.
In addition, at present, the remote diagnosis of the vehicle is only limited to the remote control of the remote equipment through remote control software, and is not the diagnosis of a vehicle by a direct remote person. Although vehicle remote fault diagnosis at home and abroad is applied to a vehicle Telematics system, the current vehicle remote fault diagnosis is only limited to acquisition of diagnostic fault code information and control of some simple functions, cannot perform more processing on vehicle diagnosis, cannot be used in association with other diagnostic data and design data, does not research a fault diagnosis model, and is rarely involved in vehicle fault statistics. At present, Telematics-based vehicle remote diagnosis is to finish acquisition of fault codes through a vehicle-mounted data acquisition system, then upload the fault codes to a server background, and send the fault codes to a client APP for display, wherein the fault codes can only realize simple fault display and reminding, the fault codes cannot be classified, and an intelligent fault processing flow is not formed.
Disclosure of Invention
The invention aims to provide a vehicle fault diagnosis method and a vehicle fault diagnosis system, so that faults are classified and processed, and an intelligent fault processing flow is formed, so that the real-time performance and convenience of vehicle fault diagnosis are improved.
In a first aspect, an embodiment of the present invention provides a vehicle fault diagnosis method, including:
generating a vehicle diagnosis request according to diagnosis request information uploaded by a client, and sending the vehicle diagnosis request to a vehicle to be diagnosed; the vehicle diagnosis request comprises information of a functional unit to be diagnosed of a target vehicle electrical system;
receiving vehicle diagnostic information uploaded by the target vehicle; the vehicle diagnosis information is state information corresponding to a functional unit to be diagnosed of the target vehicle;
judging whether the functional unit to be diagnosed has a fault according to the vehicle diagnosis information, if so, generating corresponding fault information, determining one or more fault nodes according to the fault information and a preset vehicle electrical system topological structure, judging a fault type according to the one or more fault nodes, executing a corresponding diagnosis analysis strategy according to the fault type, and generating a fault maintenance guide;
issuing the trouble shooting guide to the target vehicle; the trouble shooting guide is used for guiding the execution unit of the target vehicle to carry out trouble shooting.
Preferably, the vehicle diagnosis information includes a real vehicle bus signal, a real vehicle diagnosis data stream, and real vehicle fault code information corresponding to the functional unit to be diagnosed;
judging whether the functional unit to be diagnosed has a fault according to the vehicle diagnosis information, and specifically comprising the following steps:
judging whether a current fault code is generated according to the real vehicle fault code information;
if the current fault code is generated, acquiring a reference bus signal and a reference diagnosis data stream corresponding to the fault code from a database according to the fault code, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generating corresponding fault information when the fault occurs;
and if no current fault code is generated, judging whether the vehicle diagnosis information has real vehicle fault phenomenon information, if so, judging whether a fault occurs according to the real vehicle fault phenomenon information, and generating corresponding fault information when the fault occurs.
Preferably, the determining whether a fault occurs according to the real vehicle fault phenomenon information specifically includes:
judging whether a fault indicator lamp corresponding to the functional unit to be diagnosed is turned on or not according to the real vehicle fault phenomenon information;
if the real vehicle diagnostic data stream is lightened, acquiring a fault condition corresponding to the lightening of a fault indicator lamp, acquiring a reference bus signal and a reference diagnostic data stream corresponding to the fault condition from a database, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnostic data stream and the reference diagnostic data stream, and generating corresponding fault information when the fault occurs;
and if the fault indicator lamp corresponding to the functional unit to be diagnosed is not lighted, acquiring a fault keyword according to the fault phenomenon, retrieving the database according to the fault keyword to obtain a corresponding vehicle unit, judging that the vehicle unit has a fault, and generating corresponding fault information when the fault is judged to occur.
Preferably, the vehicle electrical system topology comprises a plurality of subsystems, and each subsystem is composed of several parts and a harness loop; the multiple subsystems are respectively a vehicle body electronic system, a power electronic system, an air conditioning system, a chassis electric control system, an information interaction system, an active and passive safety system and a new energy electric control system;
determining a fault type according to the one or more fault nodes, specifically comprising:
querying whether one or more preset fault nodes corresponding to the one or more fault nodes exist in a database, wherein if the one or more fault nodes all have corresponding preset fault nodes, the fault type is a first fault type; and if at least one fault node does not have a corresponding preset fault node, the fault type is a second fault type.
Preferably, executing a corresponding diagnostic analysis strategy according to the fault type specifically includes:
for the fault of the first fault type, acquiring corresponding fault maintenance guidance according to one or more fault nodes; each preset fault node is provided with a corresponding fault maintenance guide;
for the fault of the second fault type, processing vehicle diagnosis information by using an intelligent fault diagnosis model based on machine learning, extracting characteristic information of the vehicle diagnosis information, and obtaining corresponding fault maintenance guidance according to the characteristic information; the preset fault analysis model is used for training and learning the vehicle diagnosis information of a plurality of fault cases in advance through a machine learning algorithm.
In a second aspect, an embodiment of the present invention provides a vehicle fault diagnosis system, including:
the diagnosis request generation unit is used for generating a vehicle diagnosis request according to the diagnosis request information uploaded by the client and sending the vehicle diagnosis request to a vehicle to be diagnosed; the vehicle diagnosis request comprises information of a functional unit to be diagnosed of a target vehicle electrical system;
the signal receiving unit is used for receiving vehicle diagnosis information uploaded by the target vehicle;
the vehicle diagnosis information is state information corresponding to a functional unit to be diagnosed of the target vehicle;
the fault diagnosis unit is used for judging whether the functional unit to be diagnosed has faults or not according to the vehicle diagnosis information, if so, generating corresponding fault information, determining one or more fault nodes according to the fault information and a preset topological structure of a vehicle electrical system, judging fault types according to the one or more fault nodes, executing corresponding diagnosis analysis strategies according to the fault types, and generating fault maintenance guidance; and
the signal sending unit is used for sending the fault maintenance guide to the target vehicle; the trouble shooting guide is used for guiding the execution unit of the target vehicle to carry out trouble shooting.
Preferably, the vehicle diagnosis information includes a real vehicle bus signal, a real vehicle diagnosis data stream, and real vehicle fault code information corresponding to the functional unit to be diagnosed;
the fault diagnosis unit specifically comprises:
the first judging unit is used for judging whether a current fault code is generated according to the real vehicle fault code information;
the second judgment unit is used for acquiring a reference bus signal and a reference diagnosis data stream corresponding to the fault code from a database according to the fault code when the current fault code is generated, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generating corresponding fault information when the fault occurs; when no current fault code is generated, judging whether the vehicle diagnosis information has real vehicle fault phenomenon information, if so, judging whether a fault occurs according to the real vehicle fault phenomenon information, and generating corresponding fault information when judging that the fault occurs;
the third judging unit is used for judging whether the vehicle diagnosis information has real vehicle fault phenomenon information or not when no current fault code is generated, and judging whether a fault indicator lamp corresponding to the functional unit to be diagnosed is turned on or not according to the real vehicle fault phenomenon information if the real vehicle fault phenomenon information exists;
the fault type determining unit is used for determining one or more fault nodes according to the fault information and a preset vehicle electrical system topological structure; and
and the fault type determining unit is used for determining the corresponding fault type of the one or more fault nodes according to the one or more fault nodes.
Preferably, the third determination unit is specifically configured to:
when the fault indicator lamp is turned on, the third judging unit acquires a fault condition corresponding to the turning-on of the fault indicator lamp, acquires a reference bus signal and a reference diagnosis data stream corresponding to the fault condition from a database, judges whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generates corresponding fault information when the fault occurs;
when the fault indicator lamp is not lightened, the third judging unit obtains a fault keyword according to the fault phenomenon, obtains a corresponding vehicle unit according to the fault keyword search database, judges that the vehicle unit has a fault, and generates corresponding fault information when the fault is judged to occur.
Preferably, the vehicle electrical system topology comprises a plurality of subsystems, and each subsystem is composed of several parts and a harness loop; the multiple subsystems are respectively a vehicle body electronic system, a power electronic system, an air conditioning system, a chassis electric control system, an information interaction system, an active and passive safety system and a new energy electric control system;
the fault type determining unit is specifically configured to query whether one or more preset fault nodes corresponding to the one or more fault nodes exist in a database, and if the one or more fault nodes all have corresponding preset fault nodes, the fault type is a first fault type; and if at least one fault node does not have a corresponding preset fault node, the fault type is a second fault type.
Preferably, the fault diagnosis unit further includes a diagnosis analysis unit, configured to:
for the fault of the first fault type, acquiring corresponding fault maintenance guide according to the fault node; each preset fault node is provided with a corresponding fault maintenance guide;
for the fault of the second fault type, processing vehicle diagnosis information by using an intelligent fault diagnosis model based on machine learning, extracting characteristic information of the vehicle diagnosis information, and obtaining corresponding fault maintenance guidance according to the characteristic information; the preset fault analysis model is used for training and learning the vehicle diagnosis information of a plurality of fault cases in advance through a machine learning algorithm.
The technical scheme at least has the following advantages: the state information corresponding to the functional unit to be diagnosed of the target vehicle is collected to be used as vehicle diagnosis information, the technical means of the technical scheme is utilized to carry out fault judgment and fault type judgment on the vehicle diagnosis information, and finally corresponding fault maintenance guide is obtained by adopting a corresponding fault diagnosis strategy according to the fault type and is used for carrying out automatic maintenance on a vehicle execution unit so as to eliminate the fault. Therefore, the automatic generation of the fault classification and fault maintenance guide of the vehicle is realized, the processing capacity of vehicle fault diagnosis is improved, and the real-time performance and the convenience of vehicle fault diagnosis are improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a vehicle fault diagnosis method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of fault information association according to an embodiment of the present invention.
Fig. 3 is a block diagram of a vehicle fault diagnosis system according to another embodiment of the present invention.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
In addition, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present invention. It will be understood by those skilled in the art that the present invention may be practiced without some of these specific details. In some instances, well known means have not been described in detail so as not to obscure the present invention.
An embodiment of the present invention provides a vehicle fault diagnosis method, which can be applied to servers in an internet of vehicles, and the method of the embodiment is executed by one or more servers, fig. 1 is a flowchart of the vehicle fault diagnosis method of the embodiment, and referring to fig. 1, the method of the embodiment includes steps S101 to S104:
step S101, generating a vehicle diagnosis request according to diagnosis request information uploaded by a client, and sending the vehicle diagnosis request to a vehicle to be diagnosed; the vehicle diagnosis request comprises information of a functional unit to be diagnosed of a target vehicle electrical system;
specifically, the user operates through the client, generates and uploads the diagnosis request information to the server, and the diagnosis request information may include diagnosis types, target vehicle information to be diagnosed, target vehicle electrical system information, functional unit information, and the like.
Step S102, vehicle diagnosis information uploaded by the target vehicle is received; the vehicle diagnosis information is state information corresponding to a functional unit to be diagnosed of the target vehicle;
specifically, after the vehicle receives the diagnosis request information sent by the server, the vehicle state information required by the current diagnosis request is acquired through a data acquisition system of the vehicle, and the vehicle diagnosis information is obtained by summarizing and fed back to the server.
Step S103, judging whether the functional unit to be diagnosed has a fault or not according to the vehicle diagnosis information, if so, generating corresponding fault information, determining one or more fault nodes according to the fault information and a preset topological structure of a vehicle electrical system, judging according to the one or more fault nodes, executing a corresponding diagnosis analysis strategy according to the fault type, and generating a fault maintenance guide;
specifically, after receiving vehicle diagnosis information uploaded by a vehicle, the server performs fault judgment according to the vehicle diagnosis information based on a preset control strategy, and determines why the type of the fault is specific when the fault is found, and according to different fault types, the method of the embodiment presets different diagnosis and analysis strategies and generates fault maintenance guidance.
Step S104, issuing the fault maintenance guide to the target vehicle; the trouble shooting guide is used for guiding the execution unit of the target vehicle to carry out trouble shooting.
Specifically, the fault maintenance guide comprises instructions/information for guiding the vehicle to carry out diagnosis maintenance, and the related execution unit of the vehicle can generate corresponding diagnosis maintenance instructions according to the fault maintenance guide to carry out automatic diagnosis maintenance on the vehicle so as to eliminate vehicle faults.
The method realizes the automatic generation of the fault classification and the fault maintenance guide of the vehicle, improves the processing capacity of vehicle fault diagnosis, improves the real-time performance and the convenience of vehicle fault diagnosis, and avoids the condition that the vehicle maintenance process is too dependent on the experience of people.
In a specific embodiment, the vehicle diagnosis information includes a real vehicle bus signal, a real vehicle diagnosis data stream, and real vehicle fault code information corresponding to the functional unit to be diagnosed; specifically, the vehicle adopts a CAN bus network to transmit internal signals, the state signals of all functional units are all reflected in the CAN bus network, and bus signals CAN be obtained through the CAN bus network; the diagnostic data stream refers to data memorized in an Electronic Control Unit (ECU), truly reflects the working voltage and state of each sensor and actuator, can be used as the basis of vehicle fault diagnosis, is convenient for maintenance personnel to know the working state of the vehicle at any time and diagnose the fault of the vehicle in time. Generally, any fault code of the vehicle is set with certain conditions, and when the self-diagnosis system detects that some signal or signals exceed the set conditions, the ECU determines the fault code.
Wherein, the step S103 specifically includes the following steps S201 to S203:
step S201, judging whether a current fault code is generated according to the vehicle diagnosis information;
specifically, the fault code refers to code information reflected by ECU analysis after a vehicle has failed. The fault code type comprises a historical fault code and a current fault code, the historical fault code refers to a fault code which is generated by a fault which occurs in the past but does not occur currently and is not yet clear, and the current fault code refers to a fault which does exist currently. The current fault code can be determined by clearing the fault code, and for the historical fault code, the current fault code will not appear after clearing, but the current fault code still exists due to the fault, and therefore the current fault code still appears after clearing, that is, the current fault code cannot be cleared, so that whether the real vehicle fault code information has the current fault code can be determined.
Step S202, if a current fault code is generated, acquiring a reference bus signal and a reference diagnosis data stream corresponding to the fault code from a database according to the fault code, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generating corresponding fault information when the fault occurs;
specifically, the CAN ID in the vehicle bus data CAN indicate which ECU has sent the message, and the fault code information collected in addition is also stored in the corresponding ECU, so that the ECU sending the CAN message or the ECU storing the fault code. Therefore, when the vehicle diagnosis information includes a fault code, it indicates that a fault occurs, but the fault may also be a false report, that is, no fault actually occurs, and therefore further determination is needed, a normal operating parameter value corresponding to the ECU can be quickly found according to the fault code, the reference bus signal and the reference diagnosis data stream are parameter value ranges corresponding to the normal operation of the vehicle, and whether a fault occurs can be determined by comparing the actual vehicle bus signal with the reference bus signal, the actual vehicle diagnosis data stream with the reference diagnosis data stream.
Step S203, if no current fault code is generated, judging whether the vehicle diagnosis information has real vehicle fault phenomenon information, if so, judging whether a fault occurs according to the real vehicle fault phenomenon information, and generating corresponding fault information when judging that the fault occurs.
Specifically, when the vehicle diagnosis information does not include the fault code, it is impossible to quickly determine which part of the units has the fault, and the further determination can be made through fault phenomenon information, where the fault phenomenon refers to a general electrical fault on the vehicle, and can be expressed as fault phenomenon information through language or direct bus data, such as that a fault indicator lamp on an instrument is on or information input by a user, such as that a headlight is not on or the like. Therefore, it is possible to determine whether or not the vehicle has failed based on the failure phenomenon information, and generate corresponding failure information when it is determined that the vehicle has failed.
In a specific embodiment, the step S203 specifically includes the following steps S301 to S303:
step S301, judging whether a fault indicator lamp corresponding to the functional unit to be diagnosed is turned on or not according to the real vehicle fault phenomenon information;
specifically, there are many types of fault indicators for vehicles, and when a functional unit of a vehicle has a fault, the corresponding ECU sends a fault signal to the corresponding fault indicator to turn on the fault indicator to indicate the fault, but the fault indicator may be a false alarm, that is, no fault actually occurs, and therefore further determination is required.
Step S302, if a fault indicator lamp corresponding to the functional unit to be diagnosed is turned on, acquiring a fault condition corresponding to the turned-on fault indicator lamp, acquiring a reference bus signal and a reference diagnosis data stream corresponding to the fault condition from a database, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generating corresponding fault information when the fault occurs.
Specifically, since a fault condition is determined to be a fault if a certain state value exceeds a set value range, for example, a corresponding reference bus signal and a reference diagnostic data stream can be found according to the fault condition, and compared with an actual bus signal and an actual diagnostic data stream for analysis, whether the fault condition is satisfied is determined, and finally whether the fault is determined.
Step S303, if the fault indicator lamp corresponding to the functional unit to be diagnosed is not lighted, obtaining a fault keyword according to the fault phenomenon, retrieving a database according to the fault keyword to obtain a corresponding vehicle unit, and judging that the vehicle unit has a fault.
Specifically, the fault phenomenon information is information describing a fault, corresponding keywords can be extracted according to the fault phenomenon information, corresponding functional units are retrieved according to the keywords, and the fault is determined.
In a specific embodiment, wherein the vehicle electrical system topology comprises a plurality of subsystems, and each subsystem is composed of a number of parts and a harness loop; the multiple subsystems are respectively a vehicle body electronic system, a power electronic system, an air conditioning system, a chassis electric control system, an information interaction system, an active and passive safety system and a new energy electric control system;
in particular, according to the vehicle electrical system topology described above, it can be determined which parts or harness loops are faulty, i.e., those nodes of the vehicle electrical system topology are faulty nodes. The types of the parts can be divided into faults of an actuator, a sensor, an input/output and a controller, and the like, a wiring harness loop has open-circuit and short-circuit faults, and the number and the positions of fault nodes are further determined according to a pre-designed topological structure of the vehicle electrical system in the step.
The parts are subdivided according to the part numbers or part assembly numbers of the actual BOM system, the loop numbers in each system are listed according to the requirement of harness design in a harness loop, and two types of faults, namely open-circuit faults and short-circuit faults, exist under each harness loop. The information about each fault includes the following items: diagnosing fault information, data streams, bus signal values and fault phenomena and possible fault locations or components. After the system is classified, each electrical part, each loop, which fault codes are associated, and which bus signals have a corresponding relationship, and these signals can give reference values in the ON gear state from the design end, as shown in fig. 2.
For example, a BCS (brake control system ECU) fault code U101286 receives a front left wheel speed signal from the BCS that is invalid. First, the fault code exists in the BCS, so the part number of the BCS is 8085003ATN0100/8085003ATN0000, and the part number of the BCS belongs to the chassis electric control system in 7 major systems. The wiring harness loop related to the fault code comprises a left front wheel speed sensor related loop, a power supply loop, a CAN loop and the sensor. From the wiring harness schematic diagram, loop numbers BR 021A, BR 021B, BR022A, BR022B are known, and these loops are all associated with fault codes U101286. Meanwhile, according to DBC, the CANID of the left front wheel speed signal is 0x26C, and the name of the wheel speed signal is
BCS _ FRWheelSpd (13 bits in total from Bit4-Bit0 to Byte5 of Byte 4) and BCS _ FRWheelSpdVD (Bit 7 of Byte 4). Thus, fault code dependent loops, parts and bus signals are correlated in the data model.
For example, a wire harness loop is in what range the value of the bus signal is in when open and in what range when open. Different local breaks can cause different situations.
TABLE 1 subsystem Classification examples
In this embodiment, the determining the fault type corresponding to the one or more faulty nodes according to the one or more faulty nodes specifically includes:
querying whether one or more preset fault nodes corresponding to the one or more fault nodes exist in a database, wherein if the one or more fault nodes all have corresponding preset fault nodes, the fault type is a first fault type; and if at least one fault node does not have a corresponding preset fault node, the fault type is a second fault type.
Specifically, different diagnostic analysis strategies are employed according to different fault types to improve the efficiency of the diagnostic process.
In a specific embodiment, the step S103 further includes the following steps S501 to S503:
s501, for the fault of the first fault type, acquiring a corresponding fault maintenance guide according to a fault node; each preset fault node is provided with a corresponding fault maintenance guide;
specifically, the first fault type is a known fault, and there is a corresponding fault case, and the fault case matching with the known fault type can be found by searching the case base according to the relevant information of the fault, and each fault case has a corresponding fault maintenance guide. The types of the parts can be divided into faults of an actuator, a sensor, an input/output and a controller, and the like, and the wiring harness loop has faults of open circuit and short circuit.
Step S502, for the fault of the second fault type, processing vehicle diagnosis information by using an intelligent fault diagnosis model based on machine learning, extracting characteristic information of the vehicle diagnosis information, and obtaining corresponding fault maintenance guidance according to the characteristic information; the preset fault analysis model is used for training and learning the vehicle diagnosis information of a plurality of fault cases in advance through a machine learning algorithm.
Specifically, when the fault of the second fault type is an unknown fault situation and no corresponding fault maintenance guide exists, the data such as the bus signal, the diagnostic data stream, the fault phenomenon information and the like are used as model input by using a fault analysis model trained in advance, the characteristic information of various data is extracted, and intelligent prediction is performed according to the characteristic information to generate the corresponding fault maintenance guide.
It can be understood that machine learning-based intelligent fault diagnosis is currently applied in various fields, and this embodiment is intended to diagnose unknown complex faults using related technologies.
As shown in fig. 3, another embodiment of the present invention provides a vehicle fault diagnosis system, including:
the diagnosisrequest generating unit 1 is used for generating a vehicle diagnosis request according to diagnosis request information uploaded by a client and sending the vehicle diagnosis request to a vehicle to be diagnosed; the vehicle diagnosis request comprises information of a functional unit to be diagnosed of a target vehicle electrical system;
thesignal receiving unit 2 is used for receiving vehicle diagnosis information uploaded by the target vehicle; the vehicle diagnosis information is state information corresponding to a functional unit to be diagnosed of the target vehicle;
thefault diagnosis unit 3 is used for judging whether the functional unit to be diagnosed has a fault according to the vehicle diagnosis information, if so, generating corresponding fault information, determining one or more fault nodes according to the fault information and a preset topological structure of a vehicle electrical system, judging a fault type according to the one or more fault nodes, executing a corresponding diagnosis analysis strategy according to the fault type, and generating a fault maintenance guide; and
the signal sending unit 4 is used for sending the fault maintenance guide to the target vehicle; the trouble shooting guide is used for guiding the execution unit of the target vehicle to carry out trouble shooting.
In a specific embodiment, the vehicle diagnosis information includes a real vehicle bus signal, a real vehicle diagnosis data stream, and real vehicle fault code information corresponding to the functional unit to be diagnosed;
thefault diagnosis unit 3 specifically includes:
afirst determination unit 31, configured to determine whether a current fault code is generated according to the real vehicle fault code information;
a second determiningunit 32, configured to, when a current fault code is generated, obtain a reference bus signal and a reference diagnostic data stream corresponding to the fault code from a database according to the fault code, determine whether a fault occurs according to a comparison result between the real vehicle bus signal and the reference bus signal and a comparison result between the real vehicle diagnostic data stream and the reference diagnostic data stream, and generate corresponding fault information when it is determined that a fault occurs;
a third determiningunit 33, configured to determine whether there is real vehicle fault phenomenon information in the vehicle diagnosis information when no current fault code is generated, and if there is real vehicle fault phenomenon information, determine whether a fault indicator corresponding to the functional unit to be diagnosed is turned on according to the real vehicle fault phenomenon information; wherein: when the fault indicator lamp is turned on, the third judging unit acquires a fault condition corresponding to the turning-on of the fault indicator lamp, acquires a reference bus signal and a reference diagnosis data stream corresponding to the fault condition from a database, judges whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generates corresponding fault information when the fault occurs; when the fault indicator lamp is not lightened, the third judging unit obtains a fault keyword according to the fault phenomenon, obtains a corresponding vehicle unit according to the fault keyword retrieval database, judges that the vehicle unit has a fault, and generates corresponding fault information when the fault is judged to occur;
a faulttype determining unit 34, configured to determine one or more fault nodes according to the fault information and a preset topology of the vehicle electrical system; and
and a faulttype determining unit 35, configured to determine a fault type corresponding to the one or more faulty nodes according to the one or more faulty nodes.
In a particular embodiment, the vehicle electrical system topology includes a plurality of subsystems, and each subsystem is comprised of a number of parts and a harness loop; the multiple subsystems are respectively a vehicle body electronic system, a power electronic system, an air conditioning system, a chassis electric control system, an information interaction system, an active and passive safety system and a new energy electric control system;
the faulttype determining unit 35 is specifically configured to query whether one or more preset fault nodes corresponding to the one or more fault nodes exist in the database, and if the one or more fault nodes all have corresponding preset fault nodes, the fault type is a first fault type; and if at least one fault node does not have a corresponding preset fault node, the fault type is a second fault type.
In an embodiment, thefault diagnosis unit 3 further includes adiagnosis analysis unit 36, configured to:
for the fault of the first fault type, acquiring corresponding fault maintenance guide according to the fault node; each preset fault node is provided with a corresponding fault maintenance guide;
for the fault of the second fault type, processing vehicle diagnosis information by using an intelligent fault diagnosis model based on machine learning, extracting characteristic information of the vehicle diagnosis information, and obtaining corresponding fault maintenance guidance according to the characteristic information; the preset fault analysis model is used for training and learning the vehicle diagnosis information of a plurality of fault cases in advance through a machine learning algorithm.
The above-described system embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
It should be noted that the system described in the foregoing embodiment corresponds to the method described in the foregoing embodiment, and therefore, portions of the system described in the foregoing embodiment that are not described in detail can be obtained by referring to the content of the method described in the foregoing embodiment, and details are not described here.
Also, the vehicle failure diagnosis system according to the above embodiment may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A vehicle fault diagnosis method characterized by comprising:
generating a vehicle diagnosis request according to diagnosis request information uploaded by a client, and sending the vehicle diagnosis request to a vehicle to be diagnosed; the vehicle diagnosis request comprises information of a functional unit to be diagnosed of a target vehicle electrical system;
receiving vehicle diagnostic information uploaded by the target vehicle; the vehicle diagnosis information is state information corresponding to a functional unit to be diagnosed of the target vehicle;
judging whether the functional unit to be diagnosed has a fault according to the vehicle diagnosis information, if so, generating corresponding fault information, determining one or more fault nodes according to the fault information and a preset vehicle electrical system topological structure, judging a fault type according to the one or more fault nodes, executing a corresponding diagnosis analysis strategy according to the fault type, and generating a fault maintenance guide;
issuing the trouble shooting guide to the target vehicle; the trouble shooting guide is used for guiding the execution unit of the target vehicle to carry out trouble shooting.
2. The vehicle failure diagnosis method according to claim 1,
the vehicle diagnosis information comprises a real vehicle bus signal, a real vehicle diagnosis data stream and real vehicle fault code information corresponding to the functional unit to be diagnosed;
judging whether the functional unit to be diagnosed has a fault according to the vehicle diagnosis information, and specifically comprising the following steps:
judging whether a current fault code is generated according to the real vehicle fault code information;
if the current fault code is generated, acquiring a reference bus signal and a reference diagnosis data stream corresponding to the fault code from a database according to the fault code, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generating corresponding fault information when the fault occurs;
and if no current fault code is generated, judging whether the vehicle diagnosis information has real vehicle fault phenomenon information, if so, judging whether a fault occurs according to the real vehicle fault phenomenon information, and generating corresponding fault information when the fault occurs.
3. The vehicle fault diagnosis method according to claim 2, wherein determining whether a fault occurs according to the real vehicle fault phenomenon information specifically includes:
judging whether a fault indicator lamp corresponding to the functional unit to be diagnosed is turned on or not according to the real vehicle fault phenomenon information;
if the real vehicle diagnostic data stream is lightened, acquiring a fault condition corresponding to the lightening of a fault indicator lamp, acquiring a reference bus signal and a reference diagnostic data stream corresponding to the fault condition from a database, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnostic data stream and the reference diagnostic data stream, and generating corresponding fault information when the fault occurs;
and if the fault indicator lamp corresponding to the functional unit to be diagnosed is not lighted, acquiring a fault keyword according to the fault phenomenon, retrieving the database according to the fault keyword to obtain a corresponding vehicle unit, judging that the vehicle unit has a fault, and generating corresponding fault information when the fault is judged to occur.
4. The vehicle fault diagnosis method according to any one of claims 1 to 3, wherein the vehicle electrical system topology includes a plurality of subsystems, and each subsystem is composed of a number of parts and a harness loop; the multiple subsystems are respectively a vehicle body electronic system, a power electronic system, an air conditioning system, a chassis electric control system, an information interaction system, an active and passive safety system and a new energy electric control system;
determining a fault type according to the one or more fault nodes, specifically comprising:
querying whether one or more preset fault nodes corresponding to the one or more fault nodes exist in a database, wherein if the one or more fault nodes all have corresponding preset fault nodes, the fault type is a first fault type; and if at least one fault node does not have a corresponding preset fault node, the fault type is a second fault type.
5. The vehicle fault diagnosis method according to claim 4, wherein the corresponding diagnosis and analysis strategy is executed according to the fault type, and specifically comprises:
for the fault of the first fault type, acquiring corresponding fault maintenance guidance according to one or more fault nodes; each preset fault node is provided with a corresponding fault maintenance guide;
for the fault of the second fault type, processing vehicle diagnosis information by using an intelligent fault diagnosis model based on machine learning, extracting characteristic information of the vehicle diagnosis information, and obtaining corresponding fault maintenance guidance according to the characteristic information; the preset fault analysis model is used for training and learning the vehicle diagnosis information of a plurality of fault cases in advance through a machine learning algorithm.
6. A vehicle fault diagnosis system characterized by comprising:
the diagnosis request generation unit is used for generating a vehicle diagnosis request according to the diagnosis request information uploaded by the client and sending the vehicle diagnosis request to a vehicle to be diagnosed; the vehicle diagnosis request comprises information of a functional unit to be diagnosed of a target vehicle electrical system;
the signal receiving unit is used for receiving vehicle diagnosis information uploaded by the target vehicle; the vehicle diagnosis information is state information corresponding to a functional unit to be diagnosed of the target vehicle;
the fault diagnosis unit is used for judging whether the functional unit to be diagnosed has faults or not according to the vehicle diagnosis information, if so, generating corresponding fault information, determining one or more fault nodes according to the fault information and a preset topological structure of a vehicle electrical system, judging fault types according to the one or more fault nodes, executing corresponding diagnosis analysis strategies according to the fault types, and generating fault maintenance guidance; and
the signal sending unit is used for sending the fault maintenance guide to the target vehicle; the trouble shooting guide is used for guiding the execution unit of the target vehicle to carry out trouble shooting.
7. The vehicle failure diagnostic system according to claim 6,
the vehicle diagnosis information comprises a real vehicle bus signal, a real vehicle diagnosis data stream and real vehicle fault code information corresponding to the functional unit to be diagnosed;
the fault diagnosis unit specifically comprises:
the first judging unit is used for judging whether a current fault code is generated according to the real vehicle fault code information;
the second judgment unit is used for acquiring a reference bus signal and a reference diagnosis data stream corresponding to the fault code from a database according to the fault code when the current fault code is generated, judging whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generating corresponding fault information when the fault occurs; when no current fault code is generated, judging whether the vehicle diagnosis information has real vehicle fault phenomenon information, if so, judging whether a fault occurs according to the real vehicle fault phenomenon information, and generating corresponding fault information when judging that the fault occurs;
the third judging unit is used for judging whether the vehicle diagnosis information has real vehicle fault phenomenon information or not when no current fault code is generated, and judging whether a fault indicator lamp corresponding to the functional unit to be diagnosed is turned on or not according to the real vehicle fault phenomenon information if the real vehicle fault phenomenon information exists;
the fault type determining unit is used for determining one or more fault nodes according to the fault information and a preset vehicle electrical system topological structure; and
and the fault type determining unit is used for determining the corresponding fault type of the one or more fault nodes according to the one or more fault nodes.
8. The vehicle failure diagnosis system according to claim 7, wherein the third determination unit is specifically configured to:
when the fault indicator lamp is turned on, the third judging unit acquires a fault condition corresponding to the turning-on of the fault indicator lamp, acquires a reference bus signal and a reference diagnosis data stream corresponding to the fault condition from a database, judges whether a fault occurs according to a comparison result of the real vehicle bus signal and the reference bus signal and a comparison result of the real vehicle diagnosis data stream and the reference diagnosis data stream, and generates corresponding fault information when the fault occurs;
when the fault indicator lamp is not lightened, the third judging unit obtains a fault keyword according to the fault phenomenon, obtains a corresponding vehicle unit according to the fault keyword search database, judges that the vehicle unit has a fault, and generates corresponding fault information when the fault is judged to occur.
9. The vehicle malfunction diagnosis system according to any one of claims 6 to 7,
the vehicle electrical system topology comprises a plurality of subsystems, and each subsystem consists of a plurality of parts and a wiring harness loop; the multiple subsystems are respectively a vehicle body electronic system, a power electronic system, an air conditioning system, a chassis electric control system, an information interaction system, an active and passive safety system and a new energy electric control system;
the fault type determining unit is specifically configured to query whether one or more preset fault nodes corresponding to the one or more fault nodes exist in a database, and if the one or more fault nodes all have corresponding preset fault nodes, the fault type is a first fault type; and if at least one fault node does not have a corresponding preset fault node, the fault type is a second fault type.
10. The vehicle fault diagnosis system according to claim 9, wherein the fault diagnosis unit further includes a diagnosis analysis unit configured to:
for the fault of the first fault type, acquiring corresponding fault maintenance guide according to the fault node; each preset fault node is provided with a corresponding fault maintenance guide;
for the fault of the second fault type, processing vehicle diagnosis information by using an intelligent fault diagnosis model based on machine learning, extracting characteristic information of the vehicle diagnosis information, and obtaining corresponding fault maintenance guidance according to the characteristic information; the preset fault analysis model is used for training and learning the vehicle diagnosis information of a plurality of fault cases in advance through a machine learning algorithm.
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