CN117891235A - Multiple fault diagnosis method and device, electronic equipment and storage medium - Google Patents
Multiple fault diagnosis method and device, electronic equipment and storage medium Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 45
- 238000012545 processing Methods 0.000 claims abstract description 83
- 238000004088 simulation Methods 0.000 claims abstract description 75
- 238000004458 analytical method Methods 0.000 claims abstract description 34
- 238000012549 training Methods 0.000 claims description 10
- 238000012163 sequencing technique Methods 0.000 claims description 5
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- 238000005259 measurement Methods 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000013024 troubleshooting Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
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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
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0221—Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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Abstract
The invention provides a multiple fault diagnosis method, a multiple fault diagnosis device, electronic equipment and a storage medium, wherein the multiple fault diagnosis method comprises the following steps: when the alarm of triggering multiple fault signals by the engine is detected, acquiring vehicle end data of the engine ECU in a preset time period; classifying the vehicle-end data in a preset time period to obtain control signal information and processing data; performing simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal; the primary fault in the multiple fault signal is determined based on the processing data and the analog data. According to the invention, simulation analysis is carried out according to the vehicle end data in the preset time period set by the fault triggering time, so as to determine the simulation data corresponding to each repeated fault signal; and then processing is carried out based on the acquired processing data and the simulation data, and main faults in the multiple fault signals are determined, so that the fault diagnosis efficiency can be improved.
Description
Technical Field
The present invention relates to the field of engine fault processing technologies, and in particular, to a multiple fault diagnosis method, a multiple fault diagnosis device, an electronic device, and a storage medium.
Background
The engine ECU diagnosis of an engine fault often triggers multiple fault codes by a single cause, but the engine may not have multiple faults, that is, a false fault exists, so that an abnormal fault of the engine caused by the single cause needs to be determined from multiple faults, and the multiple fault troubleshooting process is tedious, time-consuming and high in cost.
At present, system fault reasons are usually checked one by one according to fault codes, and when a large number of related faults are reported, the checking work mainly depends on manual work according to manual flow and experience, so that the fault diagnosis efficiency in the checking process is lower.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a multiple fault diagnosis method, apparatus, electronic device, and storage medium, so as to solve the problem in the prior art that the fault diagnosis efficiency in the troubleshooting process is low.
In order to achieve the above object, the embodiment of the present invention provides the following technical solutions:
in a first aspect, an embodiment of the present invention shows a multiple fault diagnosis method, the method including:
when the alarm of triggering multiple fault signals of the engine is detected, acquiring vehicle end data of the engine ECU in a preset time period, wherein the preset time period is set based on the fault triggering time;
classifying the vehicle-end data in the preset time period to obtain control signal information and processing data;
performing simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal;
And processing based on the processing data and the simulation data, and determining a main fault in the multiple fault signals.
Optionally, the performing analog analysis on the control signal information to obtain analog data corresponding to each repeated fault signal includes:
Inputting a control signal and the fault signal in the control signal information into a preset engine physical model for each repeated fault signal in the multiple fault signals, wherein the preset engine physical model is based on historical sample data;
And carrying out simulation analysis on the control signals and the fault signals in the control signal information based on the preset engine physical model to obtain simulation data corresponding to each fault signal.
Optionally, the process of constructing the preset engine physical model based on the historical sample data includes:
Acquiring historical vehicle end data corresponding to multiple fault alarms in a historical preset time period;
Dividing historical vehicle-end data into historical control signal information and historical processing data, and taking the historical control signal information and the historical processing data as sample data;
and training a preset engine physical model based on the sample data.
Optionally, the performing analog analysis on the control signal information to obtain analog data corresponding to each repeated fault signal includes:
For each repeated fault signal, controlling the simulated engine to simulate based on the control signal in the control signal information and the fault signal;
And collecting processing data of the simulation engine under the simulation, and taking the processing data as simulation data.
Optionally, the determining the main fault in the multiple fault signal based on the processing data and the analog data includes:
Calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively;
and if the similarity degree larger than or equal to the preset threshold value exists, determining the fault signal of the similarity degree larger than or equal to the preset threshold value as a main fault.
Optionally, the determining the main fault in the multiple fault signal based on the processing data and the analog data includes:
Calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively;
sequencing the analog data corresponding to each repeated fault signal according to the sequence from large to small and the similarity degree of the analog data and the acquired processing data;
And determining a primary fault in the multiple fault signals based on the order of similarity.
A second aspect of an embodiment of the present invention shows a multiple fault diagnosis apparatus, the apparatus including:
The acquisition unit is used for acquiring vehicle end data of the engine ECU in a preset time period when the alarm of the engine triggering multiple fault signals is detected, wherein the preset time period is set based on the fault triggering time;
the classification processing unit is used for performing classification processing on the vehicle-end data in the preset time period to obtain control signal information and processing data;
the simulation analysis unit is used for carrying out simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal;
and the determining unit is used for processing based on the processing data and the simulation data and determining main faults in the multiple fault signals.
Optionally, the analog analysis unit is specifically configured to:
Inputting a control signal and the fault signal in the control signal information into a preset engine physical model for each repeated fault signal in the multiple fault signals, wherein the preset engine physical model is based on historical sample data;
And carrying out simulation analysis on the control signals and the fault signals in the control signal information based on the preset engine physical model to obtain simulation data corresponding to each fault signal.
A third aspect of the embodiment of the present invention shows an electronic device, where the electronic device is configured to execute a program, where the program executes the multiple fault diagnosis method according to the first aspect of the embodiment of the present invention.
A fourth aspect of the embodiment of the present invention shows a storage medium, where the storage medium includes a storage program, where the program, when executed, controls a device in which the storage medium is located to execute the multiple fault diagnosis method as shown in the first aspect of the embodiment of the present invention.
Based on the above-mentioned multiple fault diagnosis method, device, electronic equipment and storage medium provided by the embodiment of the invention, the method comprises the following steps: when the alarm of triggering multiple fault signals of the engine is detected, acquiring vehicle end data of the engine ECU in a preset time period, wherein the preset time period is set based on the fault triggering time; classifying the vehicle-end data in the preset time period to obtain control signal information and processing data; performing simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal; and processing based on the processing data and the simulation data, and determining a main fault in the multiple fault signals. In the embodiment of the invention, simulation analysis is carried out according to the vehicle end data in the preset time period set by the fault triggering time so as to determine the simulation data corresponding to each repeated fault signal; and then processing based on the acquired processing data and the simulation data, and determining main faults in the multiple fault signals, so that the fault diagnosis efficiency can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an architecture of an engine ECU and a server shown in an embodiment of the present invention;
FIG. 2 is a flow chart of a multiple fault diagnosis method according to an embodiment of the present invention;
FIG. 3 is a flow chart of another multiple fault diagnosis method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a multiple fault diagnosis apparatus according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the description of "first", "second", etc. in this disclosure is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implying an indication of the number of technical features being indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present invention.
In the present disclosure, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Referring to fig. 1, an architecture diagram of an engine ECU and a server according to an embodiment of the present invention is shown.
The engine ECU10 is connected to the server 20 through a cloud.
The engine ECU10 is connected with an engine at the vehicle end, and the engine ECU10 collects data of the engine in real time and sends the data to the server 20 through the cloud.
The process for realizing multiple fault diagnosis based on the architecture diagram comprises the following steps:
When detecting an alarm of triggering multiple fault signals by the engine, the server 20 acquires vehicle end data of the engine ECU10 within a preset time period, wherein the preset time period is set based on the fault triggering time; classifying the vehicle-end data in the preset time period to obtain control signal information and processing data; performing simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal; and processing based on the acquired processing data and the simulation data, and determining main faults in the multiple fault signals.
In the embodiment of the invention, simulation analysis is carried out according to the vehicle end data in the preset time period set by the fault triggering time so as to determine the simulation data corresponding to each repeated fault signal; and then processing based on the acquired processing data and the simulation data, and determining main faults in the multiple fault signals, so that the fault diagnosis efficiency can be improved.
Referring to fig. 2, a flow chart of a multiple fault diagnosis method according to an embodiment of the present invention is shown, where the method includes:
step S201: whether the engine receives the triggering multiple fault alarms or not is detected, and if yes, step S202 is executed.
Optionally, the engine ECU collects all data of the vehicle end in real time, and when the fault detection is triggered, all the collected data of the vehicle end are uploaded to the cloud end through the network based on the fault triggering instruction, and the cloud end performs calculation diagnosis of the physical model through the fault triggering, namely, the calculation diagnosis is sent to the server end, so that the server end can receive the data.
When no fault occurs, all data collected by the engine ECU in real time will not trigger multiple fault diagnosis of the physical model, directly store and analyze the data, and return to continue to execute step S201.
Step S202: and acquiring vehicle end data of the engine ECU in a preset time period, wherein the preset time period is set based on the fault triggering time.
In the specific implementation process of step S202, the server determines a preset time period according to the current fault triggering time, and selects vehicle end data collected by the engine ECU in the preset time period.
It should be noted that, the preset time period is n minutes before and after the current fault triggering time occurs, where n is preset by a technician according to the actual situation, for example, may be set to 10 minutes.
N is a positive integer greater than or equal to 2.
Further, the vehicle-end data includes control signals, fault signals, sensor measurement data, software calculation data in the engine ECU, and the like.
Step S203: and classifying the vehicle-end data in the preset time period to obtain control signal information and acquired processing data.
In the specific implementation step S203, the vehicle end data in the preset time period is traversed, and whether each data is an execution signal or fault state information of the control engine is sequentially determined, if yes, the control signal information is written into the data, and if not, the acquired processing data is written into the data.
That is, the control information includes control signals and fault signals, which directly act in the physical model variable parameters; the control signal is responsible for controlling an actuator of the engine and is used for representing the same running state as an actual engine, and the fault signal is responsible for being used as a basis for fault state injection and is used for representing the corresponding fault state of the engine.
The processing data is data detected by a sensor or software calculation data in the engine ECU.
Step S204: and carrying out simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal.
It should be noted that, in the specific implementation process of step S204, the method includes the following steps:
step S11: for each of the multiple fault signals, inputting the control signal in the control signal information and the fault signal into a preset engine physical model, wherein the preset engine physical model is based on historical sample data.
It should be noted that, the process of constructing the preset engine physical model based on the historical sample data includes:
Step S21: acquiring historical vehicle end data corresponding to multiple fault alarms in a historical preset time period;
Step S22: the historical vehicle-end data is divided into historical control signal information and historical processing data and used as sample data.
Step S23: and training a preset engine physical model based on the sample data.
In the specific implementation process of step S21 and step S23, the sample data is divided into a training set and a testing set; training the initial model based on the training set to obtain a trained initial model; performing simulation analysis on the initial model by using a test set to obtain preset data under each historical fault; judging whether preset data under each historical fault is consistent with the historical processing data in the test set, and if so, determining that an initial model obtained by current training is a preset engine physical model.
Optionally, if not, continuing to train the initial model based on the training set.
It should be noted that, the initial model may be constructed by a deep neural network algorithm or a machine learning algorithm.
In the embodiment of the invention, the preset engine physical model is obtained through training in the steps S21 to S23, the reliability of the fault signal is determined by comparing the deviation between the model simulation data and the vehicle-end transmission data according to the data in the fault occurrence period, namely the working condition of the corresponding fault signal restored by the control signal information, and the fault detection sequence is determined by sequencing the reliability to assist in troubleshooting.
Step S12: and carrying out simulation analysis on the control signals and the fault signals in the control signal information based on the preset engine physical model to obtain simulation data corresponding to each fault signal.
That is, the simulation is performed by the control signal and the fault state information, and the sensor measurement data and the software calculation data in the engine ECU under the control signal are determined at the fault signal.
In the specific implementation process of step S12, a physical model of the engine is preset to perform simulation analysis on the control signal in the control signal information and the fault signal, and the working condition corresponding to the fault signal is restored, so as to collect the measurement data of the sensor and the software calculation data in the engine ECU under the working condition of the fault signal, namely, the simulation data.
Step S205: and processing based on the acquired processing data and the simulation data, and determining main faults in the multiple fault signals.
It should be noted that there are various embodiments to embody the procedure of step S205.
A first embodiment comprises the steps of:
Step S31: and calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively.
Step S32: and comparing the similarity between the analog data corresponding to each repeated fault signal and the acquired processing data with a preset threshold, if the similarity is greater than or equal to the preset threshold, executing step S33, and if the similarity is less than the preset threshold, determining the fault signal with the similarity less than the preset threshold as a false fault signal.
It should be noted that the preset threshold is arbitrarily preset by the technology, for example, may be set to 95%.
Step S33: and determining the fault signals with the similarity degree larger than or equal to a preset threshold value as main faults.
In the embodiment of the invention, the false fault signal indicates that the fault alarm is false, namely the alarm reliability is negligible.
A second embodiment comprises the steps of:
step S41: and calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively.
Step S42: and sequencing the analog data corresponding to each repeated fault signal according to the sequence from big to small and the similarity degree of the analog data and the processing data.
Step S43: and determining a primary fault in the multiple fault signals based on the order of similarity.
In the specific implementation process of step S41 to step S43, the fault is checked in an auxiliary manner according to the order of the similarity from large to small, so as to determine whether each of the multiple fault signals is a main fault, and in general, the fault signal corresponding to the first similarity is the main fault in the multiple fault signals.
In the embodiment of the invention, simulation analysis is carried out according to the vehicle end data in the preset time period set by the fault triggering time so as to determine the simulation data corresponding to each repeated fault signal; and then processing the processing data and the simulation data to determine main faults in the multiple fault signals, so that the fault diagnosis efficiency can be improved.
Referring to fig. 3, a flow chart of another multiple fault diagnosis method according to an embodiment of the present invention is shown, where the method includes:
step S301: it is detected whether the engine ECU receives the trigger multiple failure alarm, and if so, step S302 is executed.
Step S302: and acquiring vehicle end data of the engine ECU in a preset time period, wherein the preset time period is set based on the fault triggering time.
Step S303: and classifying the vehicle-end data in the preset time period to obtain control signal information and processing data.
It should be noted that the implementation procedure for implementing steps S301 to S303 is the same as the implementation procedure for implementing steps S201 to S203 described above, and reference may be made to each other.
Step S304: and for each repeated fault signal, controlling the simulated engine to simulate based on the control signal in the control signal information and the fault signal.
The simulated engine refers to an engine having performance, model, function, and the like which are the same as those of a real engine.
In the specific implementation process of step S304, for each repeated fault signal, the control signal in the control signal information and the fault signal are sent to the analog engine, so as to control the analog engine to execute the control signal, so as to restore the change of the vehicle-end data when the control signal is executed under the fault signal.
Step S305: and collecting processing data of the simulation engine under the simulation, and taking the processing data as simulation data.
In the process of concretely implementing step S305, sensor measurement data corresponding to the simulated engine and software calculation data in the engine ECU, that is, processing data, are collected as simulation data in the simulation process.
Step S306: and processing based on the processing data and the simulation data, and determining a main fault in the multiple fault signals.
Note that, the implementation process of step S306 is the same as the implementation process of step S205 described above, and reference may be made to each other.
In the embodiment of the invention, simulation analysis is carried out according to the vehicle end data in the preset time period set by the fault triggering time so as to determine the simulation data corresponding to each repeated fault signal; and then processing the processing data and the simulation data to determine main faults in the multiple fault signals, so that the fault diagnosis efficiency can be improved.
Based on the multiple fault diagnosis method shown in the above embodiment of the present invention, the embodiment of the present invention correspondingly discloses a schematic structural diagram of a multiple fault diagnosis device, as shown in fig. 4, where the device includes:
An obtaining unit 401, configured to obtain, when an alarm of an engine triggering multiple fault signals is detected, vehicle end data of an engine ECU within a preset time period, where the preset time period is set based on a fault triggering time;
A classification processing unit 402, configured to perform classification processing on the vehicle-end data in the preset time period, so as to obtain control signal information and processing data;
the analog analysis unit 403 is configured to perform analog analysis on the control signal information to obtain analog data corresponding to each repeated fault signal;
a determining unit 404, configured to determine a main fault in the multiple fault signal based on the processing data and the analog data.
It should be noted that, the specific implementation process of each unit of the multiple fault diagnosis apparatus shown in the above embodiment of the present invention is the same as the specific implementation process of the multiple fault diagnosis method shown in the above embodiment, and can be referred to each other.
In the embodiment of the invention, simulation analysis is carried out according to the vehicle end data in the preset time period set by the fault triggering time so as to determine the simulation data corresponding to each repeated fault signal; and then processing the processing data and the simulation data to determine main faults in the multiple fault signals, so that the fault diagnosis efficiency can be improved.
Optionally, based on the multiple fault diagnosis apparatus shown in the foregoing embodiment of the present invention, the analog analysis unit 403 is specifically configured to:
Inputting a control signal and the fault signal in the control signal information into a preset engine physical model for each repeated fault signal in the multiple fault signals, wherein the preset engine physical model is based on historical sample data;
And carrying out simulation analysis on the control signals and the fault signals in the control signal information based on the preset engine physical model to obtain simulation data corresponding to each fault signal.
Optionally, the process of constructing the preset engine physical model based on the historical sample data includes:
Acquiring historical vehicle end data corresponding to multiple fault alarms in a historical preset time period;
Dividing historical vehicle-end data into historical control signal information and historical processing data, and taking the historical control signal information and the historical processing data as sample data;
and training a preset engine physical model based on the sample data.
Optionally, based on the multiple fault diagnosis apparatus shown in the foregoing embodiment of the present invention, the analog analysis unit 403 is specifically configured to:
For each repeated fault signal, controlling the simulated engine to simulate based on the control signal in the control signal information and the fault signal;
And collecting processing data of the simulation engine under the simulation, and taking the processing data as simulation data.
Optionally, based on the multiple fault diagnosis apparatus shown in the foregoing embodiment of the present invention, the determining unit 404 is specifically configured to:
Calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively;
and if the similarity degree larger than or equal to the preset threshold value exists, determining the fault signal of the similarity degree larger than or equal to the preset threshold value as a main fault.
Optionally, based on the multiple fault diagnosis apparatus shown in the foregoing embodiment of the present invention, the determining unit 404 is specifically configured to:
Calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively;
Sequencing the analog data corresponding to each repeated fault signal according to the sequence from big to small and the similarity degree of the analog data and the processing data;
And determining a primary fault in the multiple fault signals based on the order of similarity.
The embodiment of the invention also discloses an electronic device which is used for running a database storage process, wherein the multiple fault diagnosis method disclosed in the above figures 2 to 3 is executed when the database storage process is run.
The embodiment of the invention also discloses a storage medium which comprises a database storage process, wherein the equipment where the storage medium is controlled to execute the multiple fault diagnosis method disclosed in the figures 2 to 3 when the database storage process runs.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for a system or system embodiment, since it is substantially similar to a method embodiment, the description is relatively simple, with reference to the description of the method embodiment being made in part. The systems and system embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A multiple fault diagnosis method, the method comprising:
when the alarm of triggering multiple fault signals of the engine is detected, acquiring vehicle end data of the engine ECU in a preset time period, wherein the preset time period is set based on the fault triggering time;
classifying the vehicle-end data in the preset time period to obtain control signal information and processing data;
performing simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal;
And processing based on the processing data and the simulation data, and determining a main fault in the multiple fault signals.
2. The method of claim 1, wherein the performing analog analysis on the control signal information to obtain analog data corresponding to each heavy fault signal includes:
Inputting a control signal and the fault signal in the control signal information into a preset engine physical model for each repeated fault signal in the multiple fault signals, wherein the preset engine physical model is based on historical sample data;
And carrying out simulation analysis on the control signals and the fault signals in the control signal information based on the preset engine physical model to obtain simulation data corresponding to each fault signal.
3. The method of claim 2, wherein constructing the pre-set engine physical model based on the historical sample data comprises:
Acquiring historical vehicle end data corresponding to multiple fault alarms in a historical preset time period;
Dividing historical vehicle-end data into historical control signal information and historical processing data, and taking the historical control signal information and the historical processing data as sample data;
and training a preset engine physical model based on the sample data.
4. The method of claim 1, wherein the performing analog analysis on the control signal information to obtain analog data corresponding to each heavy fault signal includes:
For each repeated fault signal, controlling the simulated engine to simulate based on the control signal in the control signal information and the fault signal;
And collecting processing data of the simulation engine under the simulation, and taking the processing data as simulation data.
5. The method of claim 1, wherein said determining a primary fault in said multiple fault signal based on said processing data and analog data comprises:
Calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively;
and if the similarity degree larger than or equal to the preset threshold value exists, determining the fault signal of the similarity degree larger than or equal to the preset threshold value as a main fault.
6. The method of claim 1, wherein said determining a primary fault in said multiple fault signal based on said processing data and analog data comprises:
Calculating the similarity degree of the analog data corresponding to each repeated fault signal and the processing data respectively;
sequencing the analog data corresponding to each repeated fault signal according to the sequence from large to small and the similarity degree of the analog data and the acquired processing data;
And determining a primary fault in the multiple fault signals based on the order of similarity.
7. A multiple fault diagnosis apparatus, the apparatus comprising:
The acquisition unit is used for acquiring vehicle end data of the engine ECU in a preset time period when the alarm of the engine triggering multiple fault signals is detected, wherein the preset time period is set based on the fault triggering time;
the classification processing unit is used for performing classification processing on the vehicle-end data in the preset time period to obtain control signal information and processing data;
the simulation analysis unit is used for carrying out simulation analysis on the control signal information to obtain simulation data corresponding to each repeated fault signal;
and the determining unit is used for processing based on the processing data and the simulation data and determining main faults in the multiple fault signals.
8. The device according to claim 7, characterized in that said analog analysis unit is in particular adapted to:
Inputting a control signal and the fault signal in the control signal information into a preset engine physical model for each repeated fault signal in the multiple fault signals, wherein the preset engine physical model is based on historical sample data;
And carrying out simulation analysis on the control signals and the fault signals in the control signal information based on the preset engine physical model to obtain simulation data corresponding to each fault signal.
9. An electronic device for running a program, wherein the program, when run, performs the multiple fault diagnosis method according to any one of claims 1 to 6.
10. A storage medium comprising a storage program, wherein the storage medium is controlled to perform the multiple fault diagnosis method according to any one of claims 1 to 6 when the program is run.
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