Intelligent cabin fault analysis method, device and equipment and storage medium

Abstract

The invention discloses an intelligent cabin fault analysis method, device and equipment and a storage medium, and the method comprises the steps: starting a first thread to monitor a system fault in real time, and feeding back a daemon process to capture a field log when the system fault is monitored; after the daemon process finishes capturing the field log, a second thread is started to analyze a fault code in the field log, and a corresponding fault analysis function is matched; and the field log is analyzed again through the fault analysis function, and a fault generation reason and a fault coping strategy are obtained and broadcasted. According to the technical scheme provided by the embodiment of the invention, the fault analysis can be quickly completed, the fault generation reason can be fed back in time, and a fault coping strategy is provided for a user.

Description

Technical Field

[0001] This invention relates to the field of automotive intelligent cockpit technology, specifically to an intelligent cockpit fault analysis method, apparatus, device, and storage medium. Background Technology

[0002] The intelligent cockpit is one of the core carriers for the development of automotive intelligence and connectivity. By integrating technologies such as artificial intelligence, the Internet of Things, human-machine interaction, and display control, it upgrades the traditional car cockpit into an intelligent space that integrates "perception, interaction, service, and experience." Its core objective is to break down the information barriers between people and cars, and between cars and the environment, improve driving safety, ride comfort, and scenario adaptability, and even reconstruct the relationship between people and cars.

[0003] Because intelligent cockpits integrate multimodal interaction, intelligent display, and scenario-based services, they form complex intelligent systems. When encountering faults, they often involve multiple factors, including hardware, software, sensors, and the environment. Current technologies, when encountering system failures, can only save machine fault codes and logs online and send them back to the manufacturer's R&D department for analysis. This makes it impossible to understand the details of the fault in a timely manner or to quickly resolve the fault.

[0004] Therefore, there is an urgent need to propose a new method for analyzing intelligent cockpit faults, which can quickly analyze the causes of faults and provide emergency guidance services to users. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and storage medium for analyzing intelligent cockpit faults, aiming to help users solve the problem of not being able to understand the details of intelligent cockpit system faults in a timely manner and quickly resolve the faults when encountering faults during actual driving.

[0006] In a first aspect, the present invention provides a method for analyzing faults in an intelligent cockpit, comprising:

[0007] The first thread is activated to monitor system faults in real time, and when a system fault is detected, the daemon process is fed back to capture the on-site logs.

[0008] After the daemon process finishes capturing the field logs, it starts a second thread to parse the fault codes in the field logs and match the corresponding fault analysis functions.

[0009] The field logs are parsed again using the fault analysis function to obtain the cause of the fault and the fault response strategy, which are then broadcast.

[0010] Furthermore, before starting the first thread, the process also includes starting a daemon process;

[0011] The daemon process is used to start the first thread and the second thread;

[0012] The daemon process is also used to save the captured live logs to the first designated partition.

[0013] Furthermore, before starting the first thread, the following is also included:

[0014] Collect various fault types in the intelligent cockpit system, set corresponding fault codes for each fault type, and configure at least one fault analysis function for each fault code;

[0015] A fault database is constructed based on various fault types, fault codes, and fault analysis functions, and the fault database is stored in a second designated partition;

[0016] The fault parsing function is used to identify fault information in the field log and save the parsing results to the first designated partition.

[0017] Furthermore, the on-site logs captured by the daemon process and the parsing results parsed by the fault parsing function are packaged together to form a fault folder named with the fault code and the fault occurrence time.

[0018] The fault folder is sent back to the manufacturer to guide them in updating the fault database.

[0019] Furthermore, after the daemon process finishes capturing the on-site logs, the first thread continues to monitor system faults in real time.

[0020] Furthermore, after completing the parsing of the on-site logs, the second thread informs the user of the cause of the fault and the fault response strategy through on-screen text display and / or voice broadcast.

[0021] Furthermore, if the second thread cannot parse the fault code in the field log, the voice interaction function is activated to obtain user feedback information. The user feedback information and the field log are then sent back to the manufacturer for fault analysis, and the user is notified of the nearest after-sales service point for on-site repair.

[0022] Secondly, the present invention provides an intelligent cockpit fault analysis device, comprising:

[0023] The first process startup module is used to start the first thread to monitor system faults in real time, and when a system fault is detected, it will send a message to the daemon process to capture the on-site logs.

[0024] The second process startup module is used to start a second thread to parse the fault codes in the field logs and match the corresponding fault analysis functions after the daemon process finishes capturing the field logs.

[0025] The fault analysis and broadcasting module is used to further parse the field logs through the fault analysis function to obtain the cause of the fault and the fault response strategy for broadcasting.

[0026] Thirdly, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0027] At least one processor; and a memory communicatively connected to the at least one processor;

[0028] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the steps of the intelligent cockpit fault analysis method according to any embodiment of the present invention.

[0029] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute the steps of the intelligent cockpit fault analysis method of any embodiment of the present invention.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] The technical solution in this embodiment of the invention first activates a first thread to monitor system faults in real time, and when a system fault is detected, it sends a feedback to a daemon process to capture on-site logs. Then, after the daemon process finishes capturing on-site logs, a second thread is activated to parse the fault codes in the on-site logs and match them with the corresponding fault analysis functions. Finally, the on-site logs are parsed again using the fault analysis functions to obtain the cause of the fault and the fault response strategy, which is then broadcast. Through the solution in this embodiment of the invention, the cause of the fault can be analyzed in a timely manner and feedback can be provided to the user. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 A flowchart illustrating a method for analyzing faults in an intelligent cockpit, as provided in an embodiment of the present invention;

[0034] Figure 2 A fault analysis architecture block diagram provided in an embodiment of the present invention;

[0035] Figure 3 A block diagram of a daemon process architecture provided in an embodiment of the present invention;

[0036] Figure 4 This is a schematic diagram of the structure of an intelligent cockpit fault analysis device provided in an embodiment of the present invention;

[0037] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Before introducing the embodiments of the present invention, it should be noted that existing technologies can save machine fault codes and logs online and send them back to the manufacturer's R&D department for analysis. However, they have some drawbacks: First, the returned fault codes cannot be analyzed in real time to understand the fault currently encountered by the user, which is not conducive to the user understanding the fault in a timely manner and quickly resolving the problem; second, the returned information does not include on-site reproduction scenario information, which requires customer service personnel to conduct a second precise follow-up visit to obtain, which often cannot provide enough rich problem reproduction information for developers to analyze and locate the problem more efficiently.

[0040] Figure 1 This is a flowchart illustrating a smart cockpit fault analysis method provided in an embodiment of the present invention. This embodiment is applicable to situations where a system failure occurs in a smart cockpit. The method can be executed by a smart cockpit fault analysis device, which can be implemented in software and / or hardware and can be configured in an electronic device.

[0041] like Figure 1 As shown, the method specifically includes:

[0042] S1 starts the first thread to monitor system faults in real time, and when a system fault is detected, it sends a message to the daemon process to capture the on-site logs.

[0043] Before starting the first thread, the process also includes starting a daemon process. The daemon process is used to start the first and second threads, and also to save the captured live logs to the first designated partition.

[0044] Figure 2 A fault analysis architecture block diagram provided in an embodiment of the present invention, such as Figure 2 As shown, firstly, the daemon process is started, and the daemon process starts the first thread, which monitors for faults in real time. Then, when the first thread detects a fault, the daemon process starts the second thread, which completes the fault analysis and reports the fault result. Finally, the daemon process is shut down, and both the first and second threads are closed.

[0045] In some embodiments, the daemon process can be an after-sales service app, which runs in the background of the intelligent cockpit system. This reduces the need for numerous daemons, thereby lowering CPU and DDR resource consumption. Developing a single app service as the daemon process for the intelligent cockpit system eliminates the need for additional hardware design costs.

[0046] Figure 3 A daemon process architecture block diagram provided in an embodiment of the present invention, such as... Figure 3 As shown, the daemon process includes at least a first thread and a second thread, and the daemon process can start the first thread and the second thread.

[0047] Specifically, the after-sales service APP starts the first thread, thread1, which monitors the occurrence of system faults in the background in real time. Once a fault is triggered, the after-sales service APP promptly captures the on-site logs in the background and saves them to the first designated partition.

[0048] The on-site logs include basic logs such as logcat and kmsg, as well as specific fault log information such as hci, arnr, tombstone, app crash, dropbox, panic lastkmsg, and watchdog.

[0049] Before starting the first thread, the process also includes: collecting various fault types in the intelligent cockpit system, setting corresponding fault codes for each type of fault, configuring at least one fault analysis function for each fault code, constructing a fault database based on various fault types, fault codes, and fault analysis functions, and saving the fault database to a second designated partition.

[0050] The fault parsing function is used to identify fault information in the field log and save the parsing results to the first specified partition. The parsing results include the cause of the fault and the fault response strategy.

[0051] One of the core aspects of this invention is the collection of various potential faults and problems that the intelligent cockpit may encounter, forming a fault database stored within the intelligent cockpit system. When a fault occurs, based on real-time log information captured on-site, identifiable key information is parsed and matched against the fault type in the database. Then, the analyzed cause of the anomaly is communicated to the user via an app service.

[0052] In addition, the on-site logs captured by the daemon process and the parsing results parsed by the fault parsing function will eventually be packaged together to form a fault folder named after the fault code and the time of the fault occurrence; the fault folder will eventually be sent back to the manufacturer to guide the manufacturer to update the fault database.

[0053] The fault folder contains on-site logs and fault analysis results for all intelligent cockpit system failures, which can be used by manufacturers to further explore potential fault information and optimize and update the fault database.

[0054] S2: After the daemon process finishes capturing the live logs, it starts a second thread to parse the fault codes in the live logs and match them with the corresponding fault analysis functions.

[0055] In some embodiments, after the daemon process finishes capturing the live logs, the first thread continues to monitor system faults in real time.

[0056] Specifically, after the after-sales service app completes the collection of on-site logs, thread 1 continues to monitor system faults in the background in real time. Simultaneously, the after-sales service app starts a second thread, thread 2, which performs preliminary parsing of the collected on-site logs to extract fault codes. Then, based on the parsed fault codes, thread 2 retrieves at least one fault analysis function configured for the current fault code from the fault database.

[0057] S3 uses a fault analysis function to parse the field log again, obtains the cause of the fault and the fault response strategy, and broadcasts it.

[0058] Specifically, the second thread, thread2, calls the fault analysis function to parse the field log again, and after completing the parsing, saves the parsing result to the first designated partition. The parsing result and the field log are packaged together to form a fault folder named after the fault code and the time of the fault occurrence, and the fault folder is sent back to the manufacturer.

[0059] After parsing the on-site logs, the second thread (thread2) informs the user of the cause of the fault and the corresponding troubleshooting strategy through on-screen text display and / or voice broadcast. If the user is unable to communicate verbally, a text-based interface is provided for effective human-machine communication.

[0060] Simultaneously, the intelligent cockpit system activates its voice interaction function to inquire whether the on-site logs can be transmitted back to the manufacturer for further analysis by developers. This would facilitate the manufacturer's optimization and resolution of such faults, as well as the detection of unresolved fault information. The system also provides users with helpful tips for future use to prevent the recurrence of similar issues.

[0061] In some embodiments, if the second thread cannot parse the fault code in the field log, the voice interaction function is activated to obtain user feedback information. The user feedback information and the field log are then sent back to the manufacturer for fault analysis, and the user is notified of the nearest after-sales service point for on-site repair.

[0062] Specifically, if thread 2, while parsing the on-site logs, finds that it cannot pinpoint the cause of the fault in real time, there are two possibilities: first, the daemon process failed to capture the on-site logs containing fault information in a timely manner; second, the daemon process captured the on-site logs containing fault information, but this fault information was not recorded in the fault database. In this case, the intelligent cockpit system activates the voice interaction function to obtain a detailed reproduction process from the user. The obtained user feedback information is then compiled into a file and stored in the on-site log folder corresponding to this fault. The on-site logs and user feedback information are then sent back to the manufacturer for fault analysis. Since thread 2 has not identified the cause of the fault, the user can be informed of the nearest after-sales service point for on-site resolution via voice interaction.

[0063] The technical solutions in this invention aim to help users solve problems such as the inability to promptly understand fault details when encountering intelligent cockpit system malfunctions during actual use. A user-friendly intelligent after-sales service system alleviates user dissatisfaction, improves user experience, and guides users to provide more accurate anomaly reproduction information to developers, thereby improving problem-solving efficiency. Through the technical solutions in this invention, diagnosis and automatic analysis can be completed on the vehicle's in-vehicle system, and users can be promptly informed how to recover from the fault. For faults that cannot be recovered on-site, users are reminded of precautions for subsequent use and are advised to collect more comprehensive log information.

[0064] Figure 4 This is a schematic diagram of an intelligent cockpit fault analysis device provided in an embodiment of the present invention, as shown below. Figure 4 As shown, the device specifically includes:

[0065] The first process startup module 100 is used to start the first thread to monitor system faults in real time, and when a system fault is detected, it will send a message to the daemon process to capture the on-site logs.

[0066] The second process startup module 200 is used to start a second thread to parse the fault codes in the field logs and match the corresponding fault analysis functions after the daemon process finishes capturing the field logs.

[0067] The fault analysis and broadcasting module 300 is used to re-analyze the field logs through the fault analysis function to obtain the cause of the fault and the fault response strategy for broadcasting.

[0068] The technical solution in this embodiment of the invention, by establishing various modules and coordinating them to perform fault analysis, can promptly help users analyze the causes of the faults they encounter and provide constructive guidance on using the machine.

[0069] Figure 5This is a schematic diagram of the structure of an electronic device implementing the intelligent cockpit fault analysis method of this invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0070] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0071] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0072] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as intelligent cockpit fault analysis methods.

[0073] In some embodiments, the smart cockpit fault analysis method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the smart cockpit fault analysis method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the smart cockpit fault analysis method by any other suitable means (e.g., by means of firmware).

[0074] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0075] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0076] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0077] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0078] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0079] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0080] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0081] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing faults in an intelligent cockpit, characterized in that, include: The first thread is activated to monitor system faults in real time, and when a system fault is detected, the daemon process is fed back to capture the on-site logs. After the daemon process finishes capturing the field logs, it starts a second thread to parse the fault codes in the field logs and match the corresponding fault analysis functions. The field logs are parsed again using the fault analysis function to obtain the cause of the fault and the fault response strategy, which are then broadcast.

2. The method according to claim 1, characterized in that, Before starting the first thread, the following steps are also required: starting the daemon process; The daemon process is used to start the first thread and the second thread; The daemon process is also used to save the captured live logs to the first designated partition.

3. The method according to claim 1, characterized in that, Before starting the first thread, the following also applies: Collect various fault types in the intelligent cockpit system, set corresponding fault codes for each fault type, and configure at least one fault analysis function for each fault code; A fault database is constructed based on various fault types, fault codes, and fault analysis functions, and the fault database is stored in a second designated partition; The fault parsing function is used to identify fault information in the field log and save the parsing results to the first designated partition.

4. The method according to claim 3, characterized in that, Also includes: The on-site logs captured by the daemon process and the parsing results parsed by the fault parsing function are packaged together to form a fault folder named with the fault code and the fault occurrence time. The fault folder is sent back to the manufacturer to guide them in updating the fault database.

5. The method according to claim 1, characterized in that, Also includes: After the daemon process finishes capturing the on-site logs, the first thread continues to monitor system faults in real time.

6. The method according to claim 1, characterized in that, Also includes: After completing the parsing of the field logs, the second thread informs the user of the cause of the fault and the fault response strategy through on-screen text display and / or voice broadcast.

7. The method according to claim 1, characterized in that, Also includes: If the second thread cannot parse the fault code in the field log, the voice interaction function is activated to obtain user feedback information. The user feedback information and the field log are then sent back to the manufacturer for fault analysis. At the same time, the user is notified of the nearest after-sales service point for on-site repair.

8. A smart cockpit fault analysis device, characterized in that, The apparatus is configured to implement the method according to any one of claims 1-7, the apparatus comprising: The first process startup module is used to start the first thread to monitor system faults in real time, and when a system fault is detected, it will send a message to the daemon process to capture the on-site logs. The second process startup module is used to start a second thread to parse the fault codes in the field logs and match the corresponding fault analysis functions after the daemon process finishes capturing the field logs. The fault analysis and broadcasting module is used to further parse the field logs through the fault analysis function to obtain the cause of the fault and the fault response strategy for broadcasting.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the steps of the intelligent cockpit fault analysis method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the steps of the intelligent cockpit fault analysis method according to any one of claims 1-7.

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