Rule management method and device, equipment and storage medium

Abstract

The invention relates to the technical field of rule management, and discloses a rule management method, device and equipment and a storage medium, and the method comprises the steps: obtaining vehicle log information corresponding to a vehicle in real time, and determining vehicle fault log information from the real-time vehicle log information; according to the vehicle fault log information, determining a fault component corresponding to the vehicle, and an operation state and a fault phenomenon corresponding to the fault component; and updating a target rule tree in the rule engine based on the fault component, the running state and the fault phenomenon. According to the vehicle fault log information corresponding to the vehicle, the fault component corresponding to the vehicle and the operation state and the fault phenomenon of the fault component are determined, and the target rule tree in the rule engine is updated based on the fault component, the operation state and the fault phenomenon; therefore, the technical problem that rule management is difficult due to the fact that the scale of the fault rule in the vehicle is large in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of rule management, and in particular to a rule management method, device, equipment and storage medium. Background Art

[0002] As cars gradually develop towards intelligence and electrification, the amount of faults generated by cars and the amount of data involved are also gradually increasing. At this time, vehicle fault detection can be performed through vehicle data to ensure vehicle driving safety. In existing solutions, vehicle fault-related data can be matched with pre-established fault rules in the vehicle system to achieve vehicle fault detection. However, due to the large scale of fault rules in vehicles, it is difficult to track and maintain, which in turn makes rule management difficult.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a rule management method, device, equipment and storage medium, aiming to solve the technical problem in the prior art that rule management is difficult due to the large scale of fault rules in vehicles.

[0005] To achieve the above object, the present invention provides a rule management method, which includes:

[0006] Acquire vehicle log information corresponding to the vehicle in real time, and determine vehicle fault log information from the real-time vehicle log information;

[0007] Determine the fault component corresponding to the vehicle, the operating state and fault phenomenon corresponding to the fault component according to the vehicle fault log information;

[0008] A target rule tree in a rule engine is updated based on the faulty component, the operating status, and the fault phenomenon.

[0009] Optionally, the step of updating a target rule tree in a rule engine based on the faulty component, the operating state and the fault phenomenon comprises:

[0010] Determine the component name corresponding to the faulty component;

[0011] Searching for a target rule tree with the component name as a root node from a rule tree of a rule engine;

[0012] Matching the operating state and the fault phenomenon with the subnodes in the target rule tree;

[0013] If the match fails, the target rule tree is updated based on the running state and the fault phenomenon.

[0014] Optionally, after the step of updating the target rule tree in the rule engine based on the faulty component, the operating state and the fault phenomenon, the method further includes:

[0015] When a fault signal of a vehicle is detected, obtaining sound information and vibration information corresponding to the vehicle;

[0016] Acquiring vehicle image information of the vehicle from a preset vehicle image database, wherein the preset vehicle image database stores a global image of the vehicle collected in real time;

[0017] determining a target faulty component corresponding to the vehicle based on the sound information, the vibration information and the vehicle image information;

[0018] Target fault information corresponding to the vehicle is determined based on the target fault component and the updated target rule tree.

[0019] Optionally, the step of determining target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree includes:

[0020] Determine target component information corresponding to the target faulty component;

[0021] Performing semantic recognition on the target component information to obtain a target component name corresponding to the target faulty component;

[0022] Determine the current operating state and current fault phenomenon corresponding to the target faulty component;

[0023] Based on the target component name, the current operating state and the current fault phenomenon, target fault information corresponding to the vehicle is determined through an updated target rule tree.

[0024] Optionally, the step of determining target fault information corresponding to the vehicle through an updated target rule tree based on the target component name, the current operating state and the current fault phenomenon includes:

[0025] Matching the target component name with the name corresponding to the root node in the updated target rule tree;

[0026] If the match is successful, the current running state and the current fault phenomenon are matched with the subnodes in the updated target rule tree in sequence;

[0027] If the match is successful, the target root node is determined, and the target fault information corresponding to the vehicle is determined according to the fault identifier corresponding to the target root node.

[0028] Optionally, the step of determining a target faulty component corresponding to the vehicle based on the sound information, the vibration information and the vehicle image information includes:

[0029] Determine target image information corresponding to the abnormal area of ​​the vehicle based on the sound information, the vibration information and the vehicle image information;

[0030] Extracting component feature information corresponding to the abnormal area from the target image information;

[0031] Acquire standard component feature information corresponding to all components in the abnormal area;

[0032] comparing the component characteristic information with the standard component characteristic information;

[0033] Determining the matching degree between the component feature information and the standard component feature information according to the comparison result;

[0034] A target faulty component corresponding to the vehicle is determined from the abnormal area according to the matching degree.

[0035] Optionally, after the step of determining the target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree, the method further includes:

[0036] Determining a fault influencing factor according to the target fault information;

[0037] Determine whether the fault influencing factor is an environmental factor;

[0038] If so, obtain the current environment information and determine the fault resolution strategy based on the current environment information;

[0039] Fault resolution is performed on the vehicle according to the fault resolution strategy.

[0040] In addition, to achieve the above object, the present invention also provides a rule management device, the device comprising:

[0041] An information acquisition module, used to acquire vehicle log information corresponding to the vehicle in real time, and determine vehicle fault log information from the real-time vehicle log information;

[0042] An information determination module, used to determine the fault component corresponding to the vehicle, the operating state and fault phenomenon corresponding to the fault component according to the vehicle fault log information;

[0043] A rule updating module is used to update a target rule tree in a rule engine based on the faulty component, the operating state and the fault phenomenon.

[0044] In addition, to achieve the above objectives, the present invention also proposes a rule management device, which includes: a memory, a processor, and a rule management program stored in the memory and executable on the processor, wherein the rule management program is configured to implement the steps of the rule management method described above.

[0045] In addition, to achieve the above-mentioned purpose, the present invention further proposes a storage medium, on which a rule management program is stored, and when the rule management program is executed by a processor, the steps of the rule management method described above are implemented.

[0046] The present invention discloses real-time acquisition of vehicle log information corresponding to a vehicle, and determining vehicle fault log information from the real-time vehicle log information; determining faulty components corresponding to the vehicle, operating states and fault phenomena corresponding to the faulty components according to the vehicle fault log information; and updating a target rule tree in a rule engine based on the faulty components, operating states and fault phenomena; compared with the prior art, fault rules are large in scale and difficult to track and maintain, the present invention determines faulty components corresponding to the vehicle, operating states and fault phenomena corresponding to the vehicle according to the vehicle fault log information corresponding to the vehicle, and updates the target rule tree in the rule engine based on the faulty components, operating states and fault phenomena, thereby solving the technical problem in the prior art that rule management is difficult due to the large scale of fault rules in the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of the structure of a rule management device for a hardware operating environment involved in an embodiment of the present invention;

[0048] Figure 2 This is a flow chart of the first embodiment of the rule management method of the present invention;

[0049] Figure 3 This is a flow chart of a second embodiment of the rule management method of the present invention;

[0050] Figure 4 A schematic diagram of an updated target rule tree in the second embodiment of the rule management method of the present invention;

[0051] Figure 5 This is a flow chart of a third embodiment of the rule management method of the present invention;

[0052] Figure 6 It is a structural block diagram of the first embodiment of the rule management device of the present invention.

[0053] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0054] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0055] Reference Figure 1 , Figure 1 It is a schematic diagram of the structure of a rule management device for a hardware operating environment involved in an embodiment of the present invention.

[0056] like Figure 1 As shown, the rule management device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0057] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the rule management device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0058] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a rule management program.

[0059] exist Figure 1 In the rule management device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the rule management device of the present invention can be set in the rule management device, and the rule management device calls the rule management program stored in the memory 1005 through the processor 1001, and executes the rule management method provided by the embodiment of the present invention.

[0060] The embodiment of the present invention provides a rule management method, referring to Figure 2, Figure 2 It is a flowchart of the first embodiment of the rule management method of the present invention.

[0061] In this embodiment, the rule management method includes the following steps:

[0062] Step S10: Acquire vehicle log information corresponding to the vehicle in real time, and determine vehicle fault log information from the real-time vehicle log information.

[0063] It should be noted that the execution subject of the method of this embodiment can be a rule management device that manages the fault detection rules in the vehicle, or other rule management systems that can achieve the same or similar functions and include the rule management device. Here, the rule management method provided in this embodiment and the following embodiments is specifically described with a rule management system (hereinafter referred to as the system).

[0064] It should be noted that the above vehicle log information may be log information generated when the vehicle is driving. Correspondingly, the above vehicle fault log information may be log information when a fault occurs in the vehicle.

[0065] In practical applications, after the vehicle is started, the system will store the vehicle's log information in real time, including the log information when the vehicle is driving normally and the log information when the vehicle breaks down. Since the fault rules in the vehicle need to be managed in this embodiment, the vehicle fault log information when the vehicle breaks down can be screened in real time from all the log information of the vehicle. Specifically, all the log information of the vehicle can be vectorized, and a clustering method can be used to add labels to the vehicle log information, and then the labeled vehicle log information can be used to train a classification model, so that all the log information of the vehicle can be screened through the classification model to obtain the vehicle fault log information when the vehicle breaks down, thereby improving efficiency.

[0066] Step S20: determining the faulty component corresponding to the vehicle, the operating state and fault phenomenon corresponding to the faulty component according to the vehicle fault log information.

[0067] It should be understood that the above-mentioned faulty component may be a faulty component in the vehicle, such as an engine, a tire, a chassis, etc., and this embodiment does not impose any limitation on this.

[0068] It is understandable that the above-mentioned fault phenomenon may be a fault phenomenon presented by a faulty component in the vehicle, such as: insufficient tire pressure, engine failure, automatic engine shutdown, etc., and this embodiment does not limit this.

[0069] In actual applications, when a vehicle breaks down, the vehicle's fault log usually records information such as the time when the fault occurred, the faulty component, and the phenomenon of fault presentation and processing. Therefore, the system can directly obtain the faulty component corresponding to the vehicle's current fault, the corresponding operating status and fault phenomenon of the faulty component based on the vehicle's fault log.

[0070] Step S30: updating the target rule tree in the rule engine based on the faulty component, the operating status and the fault phenomenon.

[0071] It should be noted that the rule engine is a component embedded in the application. Most rule engines support rule implementation in simple scripting languages ​​and embedded development in general development languages. The rule engine separates business decisions from application code and uses predefined semantic modules to write business decisions. The application triggers the rule engine by submitting data or objects to the rule engine, which calls the corresponding rules and triggers the corresponding operations.

[0072] It should be noted that the target rule tree may be a pre-built tree storing the correspondence between faulty components, component operating states, and fault phenomena. Specifically, the target rule tree may store the correspondence between components running in the vehicle and their corresponding operating states, and possible fault phenomena in the operating states.

[0073] In this embodiment, the vehicle's faulty parts, operating status and fault phenomena can be matched with the target rule tree in the rule engine in turn. If the match is successful, it means that the target rule tree has high accuracy and does not need to be updated at this time; if the match fails, it means that the accuracy of the target rule tree is low. At this time, the fault phenomenon of the vehicle's faulty parts under this operating state can be updated to the target rule tree, thereby obtaining an updated target rule tree, so that the vehicle can be subsequently detected through the updated target rule tree, thereby improving the vehicle's fault detection accuracy.

[0074] Furthermore, the step S30 includes: determining the component name corresponding to the faulty component; searching for a target rule tree with the component name as the root node from the rule tree of the rule engine; matching the operating status and the fault phenomenon with the sub-nodes in the target rule tree; if the match fails, updating the target rule tree based on the operating status and the fault phenomenon.

[0075] It should be noted that the above-mentioned component names are the names of the vehicle's faulty components, such as: tires, engines, etc.

[0076] In this embodiment, since the rule trees in the rule engine are all tree structures established with the component name as the root node and the component's operating state and fault phenomenon as child nodes, if it is necessary to find the rule tree corresponding to the faulty component to perform vehicle fault detection, the component name of the faulty component can be determined first, and the rule tree with the component name as the root node can be found from all the rule trees in the rule engine, and the target rule tree determined by the rule tree can be determined at the same time. Then, the system can match the operating state of the faulty component and the fault phenomenon presented by the component in the operating state with the child nodes in the target rule tree to determine whether the target rule tree corresponding to the faulty component stores the phenomenon presented by this fault in the operating state. If the match is successful, it means that the target rule tree stores the phenomenon presented by this fault when the component is in the operating state, and the target rule tree does not need to be updated at this time; if the match fails, it means that the target rule tree does not record the phenomenon presented by this fault when the component is in the operating state, that is, it means that the target rule tree at this time is not accurate. Therefore, in order to achieve accurate identification of vehicle faults, the target rule tree can be updated based on the operating state and the fault phenomenon in the operating state. Specifically, the fault phenomenon that occurs this time in the running state can be updated to the target rule tree to obtain an updated target rule tree. At this time, the updated target rule tree is more comprehensive than the target rule tree before the update, thereby improving the fault detection accuracy of the vehicle. At the same time, since this embodiment can manage the fault rules in the vehicle through the rule tree in the rule engine, it reduces the management complexity and improves the rule management efficiency.

[0077] The present embodiment discloses real-time acquisition of vehicle log information corresponding to a vehicle, and determination of vehicle fault log information from the real-time vehicle log information; determination of faulty components corresponding to the vehicle, operating status and fault phenomena corresponding to the faulty components according to the vehicle fault log information; and updating of a target rule tree in a rule engine based on the faulty components, operating status and fault phenomena; compared with the prior art in which fault rules are large in scale and difficult to track and maintain, the present embodiment determines the faulty components corresponding to the vehicle, operating status and fault phenomena corresponding to the vehicle according to the vehicle fault log information corresponding to the vehicle, and updates the target rule tree in the rule engine based on the faulty components, operating status and fault phenomena, thereby solving the technical problem in the prior art in which rule management is difficult due to the large scale of fault rules in the vehicle.

[0078] refer to Figure 3 , Figure 3 It is a flowchart of the second embodiment of the rule management method of the present invention.

[0079] Based on the first embodiment, in order to perform fault detection when a vehicle fails to function and ensure driving safety, in this embodiment, after step S30, the method further includes:

[0080] Step S40: when a fault signal of the vehicle is detected, obtaining sound information and vibration information corresponding to the vehicle.

[0081] It should be noted that the above fault signal may be a signal triggered when a vehicle fails. In practical applications, when a vehicle fails, a corresponding fault signal may be triggered, and the system may detect the fault signal triggered by the vehicle.

[0082] It should be understood that the above-mentioned sound information may be the sound emitted by all running components in the vehicle, wherein the sound information in this embodiment may include the sound emitted by the vehicle's external components (such as the vehicle chassis, engine, etc.) and the vehicle's internal components (such as the air-conditioning outlet, vehicle audio, etc.) during the vehicle's driving, and this embodiment does not limit this. At the same time, the sound information in this embodiment may include but is not limited to sound intensity, sound frequency, etc.

[0083] It is understandable that the above vibration information may be the vibration emitted by all running components in the vehicle, wherein the sound information in this embodiment may include the vibration emitted by the external components of the vehicle (such as the vehicle chassis, engine, etc.) and the internal components of the vehicle (such as the air outlet of the air conditioner, the car audio, etc.) during the driving process of the vehicle, and this embodiment does not limit this. At the same time, the vibration information in this embodiment may include but is not limited to the vibration amplitude, vibration frequency, etc.

[0084] In practical applications, sound collection devices and vibration monitoring devices can be installed in advance at appropriate locations inside and outside the vehicle, so that when the vehicle is running, the sound collection devices and vibration monitoring devices can collect sound information and vibration information of all running parts of the vehicle in real time. Then, when the subsequent system detects a fault signal of the vehicle, it can directly obtain the sound information and vibration information of all running parts, thereby improving the fault detection efficiency.

[0085] Step S50: Acquire vehicle image information of the vehicle from a preset vehicle image database, wherein the preset vehicle image database stores a global image of the vehicle collected in real time.

[0086] It should be noted that the above-mentioned preset vehicle image database may be a database storing a global image of a vehicle, wherein the global image of the vehicle may include a global image of the interior of the vehicle, a global image of the top of the vehicle, and a global image of the bottom of the vehicle, etc. This embodiment does not impose any restrictions on this.

[0087] It should be understood that the above-mentioned vehicle image information may be image information of various operating components in the vehicle, wherein the operating components may include all operating components inside the vehicle, on the top of the vehicle and on the bottom of the vehicle, and this embodiment does not impose any limitation on this.

[0088] In this embodiment, the system can collect image information of all running parts in the vehicle in real time through the image acquisition device, and store all collected image information in a preset vehicle image database, so that when the vehicle fails later, the pre-collected image information can be directly obtained from the preset vehicle image database.

[0089] Step S60: determining a target faulty component corresponding to the vehicle based on the sound information, the vibration information and the vehicle image information.

[0090] It should be noted that the target faulty component mentioned above may be a faulty component in the vehicle.

[0091] In actual applications, the system can first preliminarily determine which area's components are faulty based on the vehicle's sound and vibration information, and then further determine which specific component in the area is faulty through the vehicle's image information, thereby determining the target faulty component corresponding to the vehicle.

[0092] Step S70: Determine target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree.

[0093] It can be understood that the above-mentioned target fault information may be information such as the reasons that may cause the target fault component to have the fault phenomenon in the corresponding operating state.

[0094] In actual applications, if the target fault component is found to be the engine of the vehicle according to the sound information, vibration information and image information corresponding to the vehicle, the operating state of the engine (including the operable state and the stopped operating state) can be determined at this time. If the engine is in the operable state, the fault phenomenon of the engine at this time can be determined, such as: the engine can rotate but does not ignite, the engine automatically shuts down during driving, and the engine can start but immediately shuts down. Then, according to the target fault component, the operating state of the component and the fault phenomenon, the target fault information of the fault component in the operating state with the fault phenomenon can be matched from the updated target rule tree in the rule engine, thereby realizing the fault detection of the vehicle.

[0095] Further, the step S70 includes: determining the target component information corresponding to the target faulty component; performing semantic recognition on the target component information to obtain the target component name corresponding to the target faulty component; determining the current operating state and current fault phenomenon corresponding to the target faulty component; based on the target component name, the current operating state and the current fault phenomenon, determining the target fault information corresponding to the vehicle through the updated target rule tree.

[0096] It should be understood that the above target component information may be relevant information of the target faulty component, such as the name, operating status, fault phenomenon, etc. of the target faulty component, which is not limited in this embodiment.

[0097] It is understandable that the above component name may be the name of the target fault component. Correspondingly, the above component additional information may be information such as the operating state and fault phenomenon of the target fault component, which is not limited in this embodiment.

[0098] In actual applications, the rule engine stores rule trees corresponding to all components in the vehicle. These rule trees are established with the component name corresponding to each component as the root node, the operating state corresponding to each component and the possible fault phenomenon in the operating state as the child node, and the leaf node can be the fault information corresponding to the fault phenomenon in the corresponding operating state. Figure 4 , Figure 4 FIG. 1 is a schematic diagram of an updated target rule tree in the second embodiment of the rule management method of the present invention. Figure 4 As shown, in order to accurately detect faults on the vehicle, the target component name, current operating status and current fault phenomenon corresponding to the target faulty component can be matched with the updated target rule tree to determine the target fault information corresponding to the vehicle.

[0099] Furthermore, the step of determining the target fault information corresponding to the vehicle through the updated target rule tree based on the target component name, the current operating status and the current fault phenomenon includes: matching the target component name with the name corresponding to the root node in the updated target rule tree; if the match is successful, matching the current operating status and the current fault phenomenon with the child nodes in the updated target rule tree in turn; if the match is successful, determining the target root node, and determining the target fault information corresponding to the vehicle according to the fault identifier corresponding to the target root node.

[0100] It should be noted that since the rule trees in the rule engine are all established with the component name as the root node, when performing fault detection on the vehicle through the updated target rule tree, the target component name of the target fault component of the vehicle must first be matched with the root node of the updated target rule tree to determine whether the updated target rule tree is the rule tree corresponding to the target fault component. If the match is successful, it means that the updated target rule tree is the rule tree corresponding to the target fault component. At this time, the additional information of the target fault component can continue to be matched with the updated target rule tree to achieve vehicle fault detection.

[0101] Specifically, after the target component name is successfully matched with the name corresponding to the root node in the updated target rule tree, the current operating state of the target fault component and the fault phenomenon presented at this time can be matched with the child nodes in the updated target rule tree, that is, the current operating state of the target fault component can be matched with the first child node directly connected to the root node in the updated target rule tree (i.e. Figure 4 If the match is successful, the fault phenomenon currently displayed by the target faulty component is matched with the second child node directly connected to the first child node that successfully matched in the updated target rule tree (i.e. Figure 4 The “fault phenomenon 1”, “fault phenomenon 2”, “fault phenomenon 3” and “fault phenomenon 4” in the vehicle are matched. If the match is successful, the fault information corresponding to the second sub-node that successfully matches is determined as the target fault information corresponding to the vehicle.

[0102] When a vehicle fault signal is detected, this embodiment determines the target fault component corresponding to the vehicle based on the sound information, vibration information and vehicle image information corresponding to the vehicle, and determines the target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree. Therefore, when a vehicle fault occurs, the rule tree can be used to perform rule matching to achieve vehicle fault detection, thereby improving the efficiency of vehicle fault detection and ensuring driving safety.

[0103] refer to Figure 5 , Figure 5 It is a flowchart of the third embodiment of the rule management method of the present invention.

[0104] Based on the above embodiments, in order to accurately determine the faulty component in the vehicle and improve the fault detection accuracy of the vehicle, in this embodiment, step S60 includes:

[0105] Step S601: Determine target image information corresponding to the abnormal area of ​​the vehicle based on the sound information, the vibration information and the vehicle image information.

[0106] It should be noted that the above abnormal area may be an area in the vehicle where a component failure may occur. In practical applications, since abnormal noise or vibration is usually emitted when a component fails, the system can first preliminarily determine the area where the abnormal noise or vibration exists based on the sound information and vibration information in the vehicle, and determine the area as an abnormal area.

[0107] It should be understood that the target image information may be image information of an abnormal area in the vehicle. In this embodiment, in order to accurately identify a faulty component in the abnormal area, the image information of the abnormal area may be extracted from all the image information of the vehicle to obtain the target image information.

[0108] Step S602: extracting component feature information corresponding to the abnormal area from the target image information.

[0109] It should be understood that the above-mentioned component characteristic information may be characteristic information corresponding to the components in the abnormal area, such as the state corresponding to the components in the abnormal area (such as tire pressure, whether the engine is rotating, etc.), and this embodiment does not limit this.

[0110] Step S603: Acquire standard component feature information corresponding to all components in the abnormal area.

[0111] It can be understood that the above-mentioned standard component characteristic information may be characteristic information of the component in the abnormal area when no failure occurs.

[0112] Step S604: Compare the component feature information with the standard component feature information.

[0113] Step S605: Determine the matching degree between the component feature information and the standard component feature information according to the comparison result.

[0114] It should be noted that the above-mentioned matching degree may be the matching degree between the component feature information and the standard component feature information.

[0115] Step S606: Determine a target faulty component corresponding to the vehicle from the abnormal area according to the matching degree.

[0116] It should be noted that the higher the degree of matching between component feature information and standard component feature information, the higher the similarity between the component feature information and the standard component feature information, that is, the higher the similarity between the current state of the component in the abnormal area and its state before the failure, the lower the possibility of failure of the component; if the lower the degree of matching between the component feature information and the standard component feature information, the lower the similarity between the component feature information and the standard component feature information, that is, the lower the similarity between the current state of the component in the abnormal area and its state before the failure, the higher the possibility of failure of the component.

[0117] In a specific implementation, the system can extract component feature information of all components in the abnormal area from the target image information corresponding to the abnormal area, and extract standard component feature information when the component is not faulty from the image information of all components in the abnormal area stored in the preset vehicle image database, and then compare the component feature information with the standard component feature information, and determine the degree of match between the component feature information and the standard component feature information based on the comparison result, so as to determine the target faulty component corresponding to the vehicle from the abnormal area according to the degree of match. Specifically, if the abnormal area is the area where the tire is located, the tire pressure of the tire at this time can be extracted from the target image information, and the tire pressure of the tire when it is not faulty can be determined, and the two tire pressures can be compared to determine the similarity between the current tire pressure and the normal tire pressure, so as to determine whether the vehicle tire is faulty, and then determine the target faulty component of the vehicle.

[0118] Furthermore, in order to perform fault processing after a fault is detected to ensure driving safety, after step S70, the method also includes: determining fault influencing factors based on the target fault information; judging whether there are environmental factors in the fault influencing factors; if so, obtaining current environmental information, and determining a fault resolution strategy based on the current environmental information; and performing fault processing on the vehicle according to the fault resolution strategy.

[0119] It should be noted that the above-mentioned fault influencing factors may be factors that cause vehicle faults, such as road factors, environmental factors, etc., which are not limited in this embodiment. Among them, environmental factors may be factors such as humidity and temperature in the environment when the vehicle is driving.

[0120] It should be noted that the above current environmental information may be information such as temperature and humidity in the current environment.

[0121] It is understandable that the above fault resolution strategy may be a strategy for resolving the current fault of the vehicle.

[0122] In actual applications, the system can determine the cause of the vehicle's current fault based on the vehicle's target fault information, and determine the influencing factors of the fault based on the cause of the current fault. At this time, it can be determined whether the influencing factors include environmental factors, that is, whether the current environment of the vehicle has an impact on the vehicle's current fault. If so, the fault resolution strategy can be determined based on the current environmental information of the vehicle, and the vehicle is fault-handled according to the fault resolution strategy. Specifically, if the component of the vehicle that has a fault this time is a tire, and the fault phenomenon is insufficient tire pressure, the vehicle's tire pressure may be insufficient due to the low temperature of the vehicle. Therefore, it can be determined that the influencing factors causing the vehicle's current fault include environmental factors. At this time, the environmental information of the vehicle's current environment can be obtained, that is, the temperature, humidity and other information of the vehicle's current environment can be obtained, and the solution strategy for this fault can be determined based on this information, such as driving to an area with a higher temperature, inflating the tires, etc., so as to handle the vehicle's fault according to the fault resolution strategy and ensure the vehicle's driving safety.

[0123] This embodiment determines the target image information of the abnormal area of ​​the vehicle based on the sound information, vibration information and vehicle image information of the vehicle, and compares the component feature information of the abnormal area with the standard component feature information, and determines the matching degree between the component feature information and the standard component feature information according to the comparison result, so as to determine the target faulty component of the vehicle from the abnormal area according to the matching degree, so as to accurately determine the faulty component in the vehicle and improve the fault detection accuracy of the vehicle. At the same time, this embodiment determines the fault influencing factors according to the target fault information, and when the fault influencing factors have environmental factors, determines the fault resolution strategy according to the current environmental information, and performs fault resolution on the vehicle according to the fault resolution strategy, so as to ensure the driving safety of the vehicle.

[0124] In addition, an embodiment of the present invention further provides a storage medium, on which a rule management program is stored. When the rule management program is executed by a processor, the steps of the rule management method described above are implemented.

[0125] Reference Figure 6 , Figure 6 It is a structural block diagram of the first embodiment of the rule management device of the present invention.

[0126] like Figure 6 As shown, the rule management device proposed in the embodiment of the present invention includes:

[0127] The information acquisition module 601 is used to acquire the vehicle log information corresponding to the vehicle in real time, and determine the vehicle fault log information from the real-time vehicle log information;

[0128] An information determination module 602 is used to determine the fault component corresponding to the vehicle, the operating state and fault phenomenon corresponding to the fault component according to the vehicle fault log information;

[0129] The rule updating module 603 is used to update the target rule tree in the rule engine based on the faulty component, the operating state and the fault phenomenon.

[0130] Furthermore, the rule updating module 603 is also used to determine the component name corresponding to the faulty component; search for a target rule tree with the component name as the root node from the rule tree of the rule engine; match the operating status and the fault phenomenon with the sub-nodes in the target rule tree; if the match fails, update the target rule tree based on the operating status and the fault phenomenon.

[0131] The rule management device of the present embodiment discloses real-time acquisition of vehicle log information corresponding to a vehicle, and determining vehicle fault log information from the real-time vehicle log information; determining faulty components corresponding to the vehicle, operating status and fault phenomena corresponding to the faulty components according to the vehicle fault log information; and updating a target rule tree in a rule engine based on the faulty components, operating status and fault phenomena; compared with the prior art, fault rules are large in scale and difficult to track and maintain, since the present embodiment determines the faulty components corresponding to the vehicle, operating status and fault phenomena corresponding to the vehicle according to the vehicle fault log information corresponding to the vehicle, and updates the target rule tree in the rule engine based on the faulty components, operating status and fault phenomena, it solves the technical problem in the prior art that rule management is difficult due to the large scale of fault rules in the vehicle.

[0132] Based on the above first embodiment of the rule management device of the present invention, a second embodiment of the rule management device of the present invention is proposed.

[0133] In this embodiment, the rule updating module 603 is also used to obtain the sound information and vibration information corresponding to the vehicle when a vehicle fault signal is detected; obtain the vehicle image information of the vehicle from a preset vehicle image database, and the preset vehicle image database stores a global image of the vehicle collected in real time; determine the target fault component corresponding to the vehicle based on the sound information, the vibration information and the vehicle image information; determine the target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree.

[0134] Furthermore, the rule updating module 603 is also used to determine the target component information corresponding to the target faulty component; perform semantic recognition on the target component information to obtain the target component name corresponding to the target faulty component; determine the current operating state and current fault phenomenon corresponding to the target faulty component; and based on the target component name, the current operating state and the current fault phenomenon, determine the target fault information corresponding to the vehicle through the updated target rule tree.

[0135] Furthermore, the rule updating module 603 is also used to match the target component name with the name corresponding to the root node in the updated target rule tree; if the match is successful, the current operating state and the current fault phenomenon are matched with the sub-nodes in the updated target rule tree in turn; if the match is successful, the target root node is determined, and the target fault information corresponding to the vehicle is determined according to the fault identifier corresponding to the target root node.

[0136] When a vehicle fault signal is detected, this embodiment determines the target fault component corresponding to the vehicle based on the sound information, vibration information and vehicle image information corresponding to the vehicle, and determines the target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree. Therefore, when a vehicle fault occurs, the rule tree can be used to perform rule matching to achieve vehicle fault detection, thereby improving the efficiency of vehicle fault detection and ensuring driving safety.

[0137] Based on the above-mentioned device embodiments, a third embodiment of the rule management device of the present invention is proposed.

[0138] In this embodiment, the rule updating module 603 is also used to determine the target image information corresponding to the abnormal area of ​​the vehicle based on the sound information, the vibration information and the vehicle image information; extract the component feature information corresponding to the abnormal area from the target image information; obtain the standard component feature information corresponding to all components in the abnormal area; compare the component feature information with the standard component feature information; determine the degree of matching between the component feature information and the standard component feature information according to the comparison result; and determine the target faulty component corresponding to the vehicle from the abnormal area according to the matching degree.

[0139] Furthermore, the rule updating module 603 is also used to determine the fault influencing factors according to the target fault information; determine whether the fault influencing factors include environmental factors; if so, obtain the current environmental information, and determine the fault resolution strategy according to the current environmental information; and perform fault processing on the vehicle according to the fault resolution strategy.

[0140] This embodiment determines the target image information of the abnormal area of ​​the vehicle based on the sound information, vibration information and vehicle image information of the vehicle, and compares the component feature information of the abnormal area with the standard component feature information, and determines the matching degree between the component feature information and the standard component feature information according to the comparison result, so as to determine the target faulty component of the vehicle from the abnormal area according to the matching degree, so as to accurately determine the faulty component in the vehicle and improve the fault detection accuracy of the vehicle. At the same time, this embodiment determines the fault influencing factors according to the target fault information, and when the fault influencing factors have environmental factors, determines the fault resolution strategy according to the current environmental information, and performs fault resolution on the vehicle according to the fault resolution strategy, so as to ensure the driving safety of the vehicle.

[0141] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0142] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0143] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0144] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A rule management method, characterized in that: The rule management method comprises: Acquire vehicle log information corresponding to the vehicle in real time, and determine vehicle fault log information from the real-time vehicle log information; Determine the fault component corresponding to the vehicle, the operating state and fault phenomenon corresponding to the fault component according to the vehicle fault log information; A target rule tree in a rule engine is updated based on the faulty component, the operating status, and the fault phenomenon.

2. The rule management method according to claim 1, characterized in that: The step of updating the target rule tree in the rule engine based on the faulty component, the operating state and the fault phenomenon comprises: Determine the component name corresponding to the faulty component; Searching for a target rule tree with the component name as a root node from a rule tree of a rule engine; Matching the operating state and the fault phenomenon with the subnodes in the target rule tree; If the match fails, the target rule tree is updated based on the running state and the fault phenomenon.

3. The rule management method according to claim 1, characterized in that: After the step of updating the target rule tree in the rule engine based on the faulty component, the operating state and the fault phenomenon, the method further includes: When a fault signal of a vehicle is detected, obtaining sound information and vibration information corresponding to the vehicle; Acquiring vehicle image information of the vehicle from a preset vehicle image database, wherein the preset vehicle image database stores a global image of the vehicle collected in real time; determining a target faulty component corresponding to the vehicle based on the sound information, the vibration information and the vehicle image information; Target fault information corresponding to the vehicle is determined based on the target fault component and the updated target rule tree.

4. The rule management method according to claim 3, characterized in that: The step of determining target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree comprises: Determine target component information corresponding to the target faulty component; Performing semantic recognition on the target component information to obtain a target component name corresponding to the target faulty component; Determine the current operating state and current fault phenomenon corresponding to the target faulty component; Based on the target component name, the current operating state and the current fault phenomenon, target fault information corresponding to the vehicle is determined through an updated target rule tree.

5. The rule management method according to claim 4, characterized in that: The step of determining target fault information corresponding to the vehicle through an updated target rule tree based on the target component name, the current operating state and the current fault phenomenon comprises: Matching the target component name with the name corresponding to the root node in the updated target rule tree; If the match is successful, the current running state and the current fault phenomenon are matched with the subnodes in the updated target rule tree in sequence; If the match is successful, the target root node is determined, and the target fault information corresponding to the vehicle is determined according to the fault identifier corresponding to the target root node.

6. The rule management method according to claim 3, characterized in that: The step of determining a target faulty component corresponding to the vehicle based on the sound information, the vibration information and the vehicle image information comprises: Determine target image information corresponding to the abnormal area of ​​the vehicle based on the sound information, the vibration information and the vehicle image information; Extracting component feature information corresponding to the abnormal area from the target image information; Acquire standard component feature information corresponding to all components in the abnormal area; comparing the component characteristic information with the standard component characteristic information; Determining the matching degree between the component feature information and the standard component feature information according to the comparison result; A target faulty component corresponding to the vehicle is determined from the abnormal area according to the matching degree.

7. The rule management method according to claim 3, characterized in that: After the step of determining the target fault information corresponding to the vehicle based on the target fault component and the updated target rule tree, the method further includes: Determining a fault influencing factor according to the target fault information; Determine whether the fault influencing factor is an environmental factor; If so, obtain the current environment information and determine the fault resolution strategy based on the current environment information; Fault resolution is performed on the vehicle according to the fault resolution strategy.

8. A rule management device, characterized in that: The device comprises: An information acquisition module, used to acquire vehicle log information corresponding to the vehicle in real time, and determine vehicle fault log information from the real-time vehicle log information; An information determination module, used to determine the fault component corresponding to the vehicle, the operating state and fault phenomenon corresponding to the fault component according to the vehicle fault log information; A rule updating module is used to update a target rule tree in a rule engine based on the faulty component, the operating state and the fault phenomenon.

9. A rule management device, characterized in that: The device comprises: a memory, a processor, and a rule management program stored in the memory and executable on the processor, wherein the rule management program is configured to implement the steps of the rule management method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a rule management program, and when the rule management program is executed by the processor, the steps of the rule management method according to any one of claims 1 to 7 are implemented.

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