An unmanned vehicle visual fault analysis method and system

Abstract

The application relates to a visual fault analysis method for an unmanned vehicle, which comprises the following steps: obtaining an SADT graph of the unmanned vehicle based on the component structure of the unmanned vehicle; performing fault mode, mechanism and influence analysis on the unmanned vehicle based on the SADT graph to obtain analysis results of the fault mode, mechanism and influence; constructing a system failure influence relationship graph based on the analysis results; and performing visual fault analysis on the unmanned vehicle based on the fault phenomenon of the unmanned vehicle and the system failure influence relationship graph. The system failure influence relationship graph of the unmanned vehicle is constructed, so that when the unmanned vehicle appears a fault, the fault of the unmanned vehicle can be analyzed based on the visual system failure influence relationship graph, direct causes of the fault are checked, fault causes corresponding to fault modes of all levels of lower levels which may cause the fault are checked, i.e. components directly causing the fault are checked, and components connected with the components causing the fault phenomenon which may cause the fault are checked, so that accurate and efficient fault analysis on the unmanned vehicle when the fault occurs is realized.

Description

Technical Field

[0001] This invention belongs to the field of unmanned vehicle technology, and in particular relates to a visual fault analysis method and system for unmanned vehicles. Background Technology

[0002] Autonomous vehicles are intelligent cars that use onboard sensor systems to perceive the road environment, automatically plan driving routes, and control the vehicle to reach predetermined destinations. Autonomous vehicles utilize onboard sensors to perceive the surrounding environment and, based on the perceived road, vehicle position, and obstacle information, control the vehicle's steering and speed, thereby enabling the vehicle to drive safely and reliably on the road.

[0003] When an autonomous vehicle system malfunctions, fault diagnosis and timely and effective identification of the cause of the malfunction are crucial for the safe and efficient operation of autonomous vehicles. Summary of the Invention

[0004] Based on the above analysis, the present invention aims to provide a method and system for visual fault analysis of unmanned vehicles, which utilizes functional failure influence diagrams and performance failure influence diagrams to perform visual fault analysis of unmanned vehicles, thereby improving the efficiency of unmanned vehicle fault analysis.

[0005] On the one hand, the present invention provides a visual fault analysis method for unmanned vehicles, which specifically includes the following steps:

[0006] The SADT diagram of the autonomous vehicle is obtained based on its component structure;

[0007] Based on the SADT diagram, a failure mode, mechanism, and impact analysis was performed on the unmanned vehicle to obtain the analysis results of failure modes, mechanisms, and impacts.

[0008] A system failure impact relationship diagram is constructed based on the analysis results;

[0009] Visualized fault analysis of unmanned vehicles is performed based on the relationship diagram between unmanned vehicle fault phenomena and system failure impact.

[0010] Furthermore, the system failure impact analysis diagram includes a functional failure impact relationship diagram and a performance failure impact relationship diagram.

[0011] Furthermore, the visualized fault analysis of the unmanned vehicle based on the fault phenomena and the system failure impact diagram includes:

[0012] Determine the corresponding failure mode based on the failure phenomenon of the autonomous vehicle.

[0013] Based on the aforementioned failure modes, corresponding failure mode nodes are obtained in the functional failure impact diagram or the performance failure impact diagram.

[0014] Fault analysis is performed based on the fault causes corresponding to the fault mode nodes and the fault causes corresponding to the lower-level fault modes at each level of the fault mode.

[0015] Furthermore, the construction of the system failure impact relationship graph based on the analysis results includes: constructing the system failure impact relationship graph with failure causes and failure modes as nodes and failure cause pointers and failure impact pointers as directed edges; wherein, the failure cause pointer represents the correspondence between failure causes and failure modes, and the failure impact pointer represents the lower-level failure mode triggering the higher-level failure mode.

[0016] Furthermore, the construction of the system failure impact diagram based on the analysis results also includes:

[0017] Using the fault cause of each fault mode as the source node and the fault mode as the target node, the relationship between each fault cause and the corresponding fault mode is presented by connecting them through directed edges pointing to the fault causes.

[0018] Using the lower-level fault mode as the source node and the higher-level fault mode as the target node, the relationships between the various fault modes are presented by connecting the directions of the fault influence through directed edges.

[0019] The ultimate target node is system failure;

[0020] Single-fault mode and multi-fault mode are marked to distinguish them in the diagram.

[0021] Furthermore, the SADT diagram of the autonomous vehicle obtained based on the vehicle's component structure includes:

[0022] Determine the functional inputs and outputs of each component of the autonomous vehicle and construct the SADT diagram for that component; where functional inputs include functional actions and functional requirements;

[0023] Based on the interrelationships of the functions and actions of each component, the SADT diagram of the autonomous vehicle system is obtained.

[0024] Furthermore, based on the SADT diagram, the failure mode, mechanism, and effects analysis of the unmanned vehicle yields the following results:

[0025] Identify the possible failure modes for each component; the failure modes include functional failure modes and performance failure modes.

[0026] The causes, mechanisms, and effects of each component's failure mode were identified.

[0027] Based on the SADT diagram, the failure modes of each component are confirmed to have a failure impact on the connecting components pointed to by the arrows in the SADT diagram.

[0028] On the other hand, the present invention also provides an unmanned vehicle visual fault analysis system, comprising:

[0029] The SADT module is used to obtain the SADT diagram of autonomous vehicles based on structured analysis and design methods.

[0030] The fault mode module is used to perform fault mode, mechanism and impact analysis on the unmanned vehicle based on the SADT diagram to obtain the analysis results of fault mode, mechanism and impact.

[0031] The system failure impact diagram module is used to construct a system failure impact diagram based on the analysis results.

[0032] The fault analysis module is used to perform visual fault analysis of unmanned vehicles based on the fault phenomena and the relationship diagram of the failure impact of the system.

[0033] Furthermore, the system failure impact diagram includes a functional failure impact diagram and a performance failure impact diagram.

[0034] Furthermore, the visualized fault analysis of the unmanned vehicle based on the fault phenomena and the system failure impact diagram includes:

[0035] Determine the corresponding failure mode based on the failure phenomenon of the autonomous vehicle.

[0036] Based on the aforementioned failure modes, the corresponding failure mode nodes are determined in the system failure impact relationship diagram.

[0037] Fault analysis is performed based on the fault causes corresponding to the fault mode nodes and the fault causes corresponding to the lower-level fault modes at each level of the fault mode.

[0038] The present invention can achieve at least one of the following beneficial effects:

[0039] By constructing a system failure impact diagram for autonomous vehicles (including functional and performance failure impact diagrams), faults can be analyzed intuitively and efficiently based on this visualized diagram. This allows for the identification of direct causes of the fault, as well as the identification of lower-level fault modes that may trigger it. Specifically, it identifies the directly faulty components and the components connected to them that may cause the fault. Therefore, the system failure impact diagram visually provides the influence relationships between different levels of fault modes, further mapping the fault influence relationships between components at each level. This provides an intuitive and efficient basis for visual fault analysis, effectively improving the efficiency of fault analysis.

[0040] By obtaining the SADT diagram of the autonomous vehicle based on its component structure, the functional requirements, functional actions, and functional outputs of each component of the autonomous vehicle can be clearly presented. It can also clearly show the functional influence relationship between each component, laying the foundation for further analysis of the failure modes, mechanisms, and effects of each component.

[0041] By performing failure mode, mechanism, and effect analysis on each component separately, the direct correlation between failure modes, failure causes, and failure effects of each component can be determined. By performing failure mode, mechanism, and effect analysis on each component directly based on the SADT diagram, the correlation between failure modes and failure effects of each component can be determined. This lays the foundation for constructing a system failure effect diagram for autonomous vehicles, which facilitates rapid and efficient failure analysis when an autonomous vehicle experiences a failure through visualization of the system failure effect diagram.

[0042] Other features and advantages of the invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained from what is particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0043] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0044] Figure 1 This is a flowchart of the unmanned vehicle visual fault analysis method according to an embodiment of the present invention;

[0045] Figure 2 This is a diagram showing the structure and function mapping of an autonomous vehicle system.

[0046] Figure 3 SADT diagram of autonomous vehicle components;

[0047] Figure 4 SADT diagram of the left motor component of the autonomous vehicle;

[0048] Figure 5 A SADT diagram showing the interrelationships between the functions of various components of an autonomous vehicle;

[0049] Figure 6 SADT diagram for autonomous vehicle system;

[0050] Figure 7 Diagram showing the impact of functional failures on autonomous vehicles;

[0051] Figure 8 This is a diagram showing the impact of performance-related failures on autonomous vehicles. Detailed Implementation

[0052] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0053] Method Implementation Examples

[0054] A specific embodiment of the present invention discloses a method for visual fault analysis of unmanned vehicles, which specifically includes the following steps:

[0055] Step S01: Obtain the SADT diagram of the autonomous vehicle based on its composition structure;

[0056] Step S02: Based on the SADT diagram, perform fault mode, mechanism and impact analysis on the unmanned vehicle to obtain the analysis results of fault mode, mechanism and impact;

[0057] Step S03: Construct a system failure impact relationship diagram based on the analysis results;

[0058] Step S04: Perform visual fault analysis of the unmanned vehicle based on the relationship diagram between the unmanned vehicle fault phenomena and the failure impact of the system.

[0059] Specifically, the structure of an autonomous vehicle includes a control unit, a drive unit, an execution unit, and a sensing unit.

[0060] Specifically, the main component of the control unit is the control motherboard, which is one of the most critical components in the autonomous drive control of unmanned vehicles. Its main function is to process data from sensors such as radar and cameras to complete upper-level control tasks such as data interaction, map building, path planning, target following, and autonomous obstacle avoidance, and to transmit control information to the lower-level drive unit.

[0061] Specifically, the drive unit includes components such as batteries and drive boards, which are used to provide energy to the vehicle and output electrical energy conversion signals to control the lower-level motor to achieve energy conversion.

[0062] Specifically, the execution unit includes components such as the vehicle frame, motor, transmission gears, and tracks, which are used for energy conversion and power output of the vehicle body.

[0063] Specifically, the sensing unit includes components such as radar, camera, attitude sensor, and encoder, which are used to sense the external environment, images, and information such as the vehicle's speed and position.

[0064] Specifically, the components and functions of the autonomous vehicle are shown in Table 1:

[0065] Table 1. Components and Functions of Autonomous Vehicles

[0066]

[0067]

[0068] Specifically, Figure 2 It demonstrates the structure and functional mapping relationship of the autonomous vehicle system.

[0069] Specifically, step S01, which involves obtaining the SADT diagram of the autonomous vehicle based on its structural composition, includes:

[0070] Determine the functional inputs and outputs (OF) of each component of the autonomous vehicle and construct its SADT diagram; where functional inputs include the having to do the function (HDF) and the requirement of the function (RF); such as Figure 3 As shown;

[0071] Based on the interrelationships of the functions and actions of each component, the SADT diagram of the autonomous vehicle system is obtained.

[0072] Specifically, functional actions include the specific movement or working state of a component, and functional requirements include environmental factors, parameter requirements, or the output of other functions. For example, Figure 4 The diagram shows the SADT of the left motor component of the autonomous vehicle, where HDF represents motor operation, RF represents power supply and control voltage ul from the drive board, and OF represents motor speed nl1.

[0073] Furthermore, to obtain the SADT diagram of an autonomous vehicle system, it is also necessary to consider the interrelationships of the functions and actions of various components. When the normal operation of one HDF is a prerequisite for the normal operation of another HDF, the output of the first HDF is called the input of the second HDF. Figure 5 The diagram shown is an SADT diagram illustrating the interrelationships between the functions of various components of an autonomous vehicle.

[0074] Furthermore, the SADT diagram of the autonomous vehicle system is as follows: Figure 6 As shown in Table 2, the functional requirements, functional actions, and functional outputs of each component are as follows:

[0075] Table 2. Meaning of Functional Requirements, Functional Actions, and Functional Outputs for Each Component

[0076]

[0077]

[0078] Specifically, in step S02, the failure mode, mechanism and effects analysis (FMMEA) results obtained by performing Failure Mode, Mechanism and Effects Analysis (FMMEA) on the unmanned vehicle based on the SADT diagram include:

[0079] Identify the possible failure modes for each component; the failure modes include functional failure modes and performance failure modes.

[0080] The causes, mechanisms, and effects of each component's failure mode were identified.

[0081] Based on the SADT diagram, the failure modes of each component are confirmed to have a failure impact on the connecting components pointed to by the arrows in the SADT diagram.

[0082] Specifically, a fault is a state in which a system cannot perform its intended function, and a fault criterion is a judgment value for determining whether a system constitutes a fault. The fault criteria of an autonomous vehicle system are closely related to its functional / performance indicators.

[0083] Specifically, the failure modes of each component include functional failure modes and performance failure modes.

[0084] Specifically, the main functional indicators of autonomous vehicles are motion functions, including forward, backward, turning, and obstacle avoidance. The autonomous vehicle is required to reach its destination from the starting point, and the final functional failure of the system is defined as the autonomous vehicle stopping.

[0085] Specifically, the performance indicators of unmanned vehicles include requirements for the real-time position error and speed error of the unmanned vehicle's running trajectory: maximum position error ≤ 8% × straight-line distance between the initial and final positions, maximum speed error ≤ 10% × target speed, and the final performance failure of the system is defined as unmanned vehicle yaw.

[0086] Furthermore, Table 3 provides the causes, mechanisms, and effects of failure modes for each component.

[0087] Table 3. Failure modes, causes, mechanisms, and effects of each component

[0088]

[0089]

[0090]

[0091]

[0092] Furthermore, based on the SADT diagram, the failure modes of each component are confirmed to have a failure impact on the connecting components pointed to by the arrows in the SADT diagram.

[0093] For example, based on the SADT diagram, the analysis results of the failure modes of the lithium battery on the connection components pointed to by the arrows are as follows: when the lithium battery has a functional failure, the whole vehicle stops supplying power, and the directly affected component is the drive board; when the battery has a performance degradation, due to insufficient voltage, the current decreases, which leads to a decrease in the speed of the DC motor, and the failure effect is reflected in the motor speed.

[0094] Specifically, step S03, which involves constructing a system failure impact diagram based on the analysis results, includes:

[0095] A system failure impact graph is constructed using fault causes and fault modes as nodes and fault cause pointers and fault impact pointers as directed edges. Here, the fault cause pointer represents the correspondence between fault causes and fault modes, and the fault impact pointer represents the lower-level fault mode triggering the higher-level fault mode.

[0096] Furthermore, taking the fault cause of each fault mode as the source node and the fault mode as the target node, the relationship between each fault cause and the corresponding fault mode is presented by connecting them through directed edges pointing to the fault causes.

[0097] Using the lower-level fault mode as the source node and the higher-level fault mode as the target node, the relationships between the various fault modes are presented by connecting the directions of the fault influence through directed edges.

[0098] The ultimate target node is system failure;

[0099] Single-fault mode and multi-fault mode are marked to distinguish them in the diagram.

[0100] Specifically, Figure 7 This is a functional failure impact diagram of an unmanned vehicle constructed for an embodiment of the present invention. Figure 8 This is a diagram illustrating the impact of performance-related failures of unmanned vehicles, constructed for an embodiment of the present invention.

[0101] Specifically, such as Figure 7 and Figure 8 As shown, the meanings of the numbers in the figure correspond one-to-one with the contents of Table 3. The meanings of different gray-scale nodes are indicated in the legend. Among them, component 1 (radar) and component 9 (motor) are multi-fault mode components, while other components are considered to have only one fault mode in the function and performance influence relationship diagram.

[0102] Specifically, step S04, based on the relationship diagram between the unmanned vehicle's fault phenomena and the system's failure impact, performs a visual fault analysis of the unmanned vehicle, including:

[0103] Determine the corresponding failure mode based on the failure phenomenon of the autonomous vehicle.

[0104] Based on the aforementioned failure modes, corresponding failure mode nodes are obtained in the functional failure impact diagram or the performance failure impact diagram.

[0105] Fault analysis is performed based on the fault causes corresponding to the fault mode nodes and the fault causes corresponding to the lower-level fault modes at each level of the fault mode.

[0106] Specifically, based on the fault symptoms, the corresponding fault modes can be determined through Table 3.

[0107] Furthermore, based on the aforementioned failure modes in Figure 7 or Figure 8 The corresponding fault mode nodes can be visualized in the image.

[0108] Furthermore, fault analysis is performed based on the fault causes corresponding to the fault mode nodes and the fault causes corresponding to the lower-level fault modes at each level of the fault mode.

[0109] For example, from Figure 7 The impact relationships of various fault modes show that faults in the radar, camera, and attitude sensor (1_1, 2_1, 3_1) all affect the signal output of the control board (4_1). As a key component for information processing and planning decisions, the control board's output commands affect the drive control signals of the lower-level drive boards. Conversely, as the power input and speed feedback signal receiver, the drive board's faults directly affect the motion execution actions of the lower-level execution units. Therefore, among the various components causing system functional failure (unmanned vehicle stopping, s1), the factors affecting the functional output of control board 4 and drive board 8 are the most numerous.

[0110] For example, from Figure 8 As can be seen, when the battery performance degrades, the signal transmission between the control board and the drive board is basically unaffected. However, due to the decrease in battery voltage and current, the DC motor speed slows down. The impact of battery performance degradation (5_2) is reflected in the motor (9_2). In addition, Figure 8 Node 11 in the figure represents severe motor vibration. As can be seen from the figure, it is both a fault caused by motor bearing wear (9_203) and one of the causes of camera image blur (2_2).

[0111] This embodiment discloses a visual fault analysis method for unmanned vehicles. By obtaining the SADT diagram of the unmanned vehicle based on its component structure, this embodiment can clearly present the functional requirements, functional actions, and functional outputs of each component of the unmanned vehicle, and can clearly present the functional influence relationship between each component, laying the foundation for further analysis of the fault modes, mechanisms, and effects of each component.

[0112] By performing failure mode, mechanism, and effect analysis on each component separately, the direct correlation between failure modes, failure causes, and failure effects of each component can be determined. By performing failure mode, mechanism, and effect analysis on each component directly based on the SADT diagram, the correlation between failure modes and failure effects of each component can be determined. This lays the foundation for constructing a system failure effect diagram for autonomous vehicles, which facilitates rapid and efficient failure analysis when an autonomous vehicle experiences a failure through visualization of the system failure effect diagram.

[0113] By constructing a system failure impact diagram for autonomous vehicles (including functional and performance failure impact diagrams), faults can be analyzed intuitively and efficiently based on this visualized diagram. This allows for the identification of direct causes of the fault, as well as the identification of lower-level fault modes that may trigger it. Specifically, it identifies the directly faulty components and the components connected to them that may cause the fault. Therefore, the system failure impact diagram visually provides the influence relationships between different levels of fault modes, further mapping the fault influence relationships between components at each level. This provides an intuitive and efficient basis for visual fault analysis, effectively improving the efficiency of fault analysis.

[0114] System Implementation Examples

[0115] An unmanned vehicle visualization fault analysis system includes an SADT module, a fault mode module, a system failure impact relationship diagram module, and a fault analysis module.

[0116] Specifically, the SADT module is used to obtain the SADT diagram of the autonomous vehicle based on structured analysis and design methods. The system provides a visual interface to present the SADT diagram of the autonomous vehicle, as well as an interactive operation interface.

[0117] Specifically, the Fault Mode and Effects (FMD) module is used to perform Fault Mode, Mechanism, and Effects (FMD) analysis on the autonomous vehicle based on the SADT diagram, obtaining the analysis results. The system provides a visual interface to present the analysis results in tables.

[0118] Specifically, the system failure impact diagram module is used to construct system failure impact diagrams based on the analysis results; this includes functional failure impact diagrams and performance failure impact diagrams. Specifically, the system provides a visual interface program for functional and performance failure impact diagrams, and provides related explanations for each component, failure mode, failure mechanism, failure cause, and failure impact associated with the diagrams.

[0119] Specifically, the fault analysis module is used to perform visualized fault analysis of the autonomous vehicle based on the fault phenomena and the system failure impact diagram. This includes determining the corresponding fault modes based on the fault phenomena; determining the corresponding fault mode nodes in the system failure impact diagram based on the fault modes; and performing fault analysis based on the fault causes corresponding to the fault mode nodes and the fault causes corresponding to the lower-level fault modes at each level of the fault mode. Specifically, the system provides a visualization interface that presents users with various information such as the fault modes and causes that may be associated with the fault phenomena in the system failure impact diagram.

[0120] Compared to existing technologies, the unmanned vehicle visualization fault analysis system provided in this embodiment first constructs an SADT diagram, which can clearly present the functional requirements, functional actions, and functional outputs of each component of the unmanned vehicle, as well as the functional influence relationships between each component. Then, by performing fault mode, mechanism, and impact analysis on the unmanned vehicle, the influence relationships between each component and the corresponding fault modes are obtained, laying the foundation for the system failure influence relationship diagram module to construct a system failure influence relationship diagram based on the analysis results.

[0121] This embodiment constructs functional failure impact diagrams and performance failure impact diagrams, presents them through a visual interface, and provides relevant explanations such as each component, each failure mode, failure mechanism, failure cause, and failure impact associated with the diagrams. It presents users with various information such as failure modes and failure causes that may be associated with the failure phenomenon in the system implementation impact diagrams. This allows users to intuitively and efficiently analyze the failure modes, failure causes, and failure components that may be associated with the failure phenomenon when an autonomous vehicle malfunctions.

[0122] It should be noted that the above embodiments are based on the same inventive concept, and the parts not described repeatedly can be used as references to each other.

[0123] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A visual fault analysis method for unmanned vehicles, characterized in that, Includes the following steps: Based on the component structure of the autonomous vehicle, a SADT diagram of the autonomous vehicle is obtained, which presents the various components of the autonomous vehicle. The functional requirements, actions, and outputs of the components are presented, showcasing the functional relationships between each component; the structure includes a control unit, a drive unit, an execution unit, and a sensing unit. Based on the SADT diagram, a failure mode, mechanism, and impact analysis was performed on the unmanned vehicle to obtain the analysis results of failure modes, mechanisms, and impacts. Based on the analysis results, a system failure impact diagram is constructed, which includes a functional failure impact diagram and a performance failure impact diagram. The construction of the system failure impact graph based on the analysis results includes: using failure causes and failure modes as nodes, and using cause pointing and failure impact as directed edges to construct the system failure impact graph; wherein, the cause pointing indicates the correspondence between failure causes and failure modes, and the failure impact indicates that the upper-level failure mode triggers the lower-level failure mode; using the failure cause of each failure mode as the source node and the failure mode as the target node, and connecting them through the cause pointing directed edges, the relationship between each failure cause and the corresponding failure mode is presented; using the upper-level failure mode as the source node and the lower-level failure mode as the target node, and connecting them through the failure impact directed edges, the relationship between each failure mode is presented; the system failure is the final target node; single failure modes and multiple failure modes are distinguished and marked in the graph; wherein, the final functional failure of the system is manifested as the unmanned vehicle stopping operation; the final performance failure of the system is manifested as the unmanned vehicle yawing; Visualized fault analysis of unmanned vehicles based on fault phenomena and the failure impact diagram of the system includes: determining the corresponding fault mode based on the fault phenomena of the unmanned vehicle; obtaining the corresponding fault mode node based on the fault mode in the functional failure impact diagram or performance failure impact diagram; and performing fault analysis based on the fault cause corresponding to the fault mode node and the fault cause corresponding to the fault modes at each level of the fault mode, that is, investigating the components that directly fail.

2. The visual fault analysis method according to claim 1, characterized in that, Place The SADT diagram of an autonomous vehicle, derived from its structural composition, includes: Determine the functional inputs and outputs of each component of the autonomous vehicle and construct the SADT diagram for that component; where functional inputs include functional actions and functional requirements; Based on the interrelationships of the functions and actions of each component, the SADT diagram of the autonomous vehicle system is obtained.

3. A visual fault analysis system for unmanned vehicles, characterized in that, include: The SADT module is used to obtain the SADT diagram of the autonomous vehicle based on its component structure, and to present it. The functional requirements, actions, and outputs of each component of the autonomous vehicle are described, and the functional relationships between these components are presented. The structure includes a control unit, a drive unit, an execution unit, and a sensing unit. The fault mode module is used to perform fault mode, mechanism and impact analysis on the unmanned vehicle based on the SADT diagram to obtain the analysis results of fault mode, mechanism and impact. The system failure impact diagram module is used to construct a system failure impact diagram based on the analysis results. The system failure impact diagram includes a functional failure impact diagram and a performance failure impact diagram. The construction of the system failure impact graph based on the analysis results includes: using failure causes and failure modes as nodes, and using cause pointing and failure impact as directed edges to construct the system failure impact graph; wherein, the cause pointing indicates the correspondence between failure causes and failure modes, and the failure impact indicates that the upper-level failure mode triggers the lower-level failure mode; using the failure cause of each failure mode as the source node and the failure mode as the target node, and connecting them through the cause pointing directed edges, the relationship between each failure cause and the corresponding failure mode is presented; using the upper-level failure mode as the source node and the lower-level failure mode as the target node, and connecting them through the failure impact directed edges, the relationship between each failure mode is presented; the system failure is the final target node; single failure modes and multiple failure modes are distinguished and marked in the graph; wherein, the final functional failure of the system is manifested as the unmanned vehicle stopping operation; the final performance failure of the system is manifested as the unmanned vehicle yawing; The fault analysis module is used to perform visualized fault analysis of unmanned vehicles based on fault phenomena and the system failure impact diagram. This includes: determining the corresponding fault mode based on the fault phenomena of the unmanned vehicle; obtaining the corresponding fault mode node in the functional failure impact diagram or performance failure impact diagram based on the fault mode; and performing fault analysis based on the fault cause corresponding to the fault mode node and the fault cause corresponding to the fault modes at each level of the fault mode, i.e., identifying the components that directly fail.

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