Complex system residual life modeling method based on fault tree and degradation trajectory and related equipment

Abstract

The embodiment of the invention provides a complex system residual life modeling method based on a fault tree and a degradation track and related equipment, and relates to the technical field of complex system residual life evaluation, and the method comprises the steps: building a fault tree with a complex system failure as a top event; performing degradation modeling on each bottom event in the fault tree to obtain a degradation model of all bottom events; and combining the fault tree with the degradation models of all the bottom events, and establishing a residual life model of the complex system. According to the technical scheme, the fault tree and the degradation track method are combined, the residual life prediction model of the complex system is established, the model can dynamically sense the health condition of the system, technical support is provided for preventive maintenance, and therefore the safety and reliability of the system are improved.

Description

Technical Field

[0001] The present application relates to the technical field of complex system remaining life assessment, and in particular to a complex system remaining life modeling method based on fault trees and degradation trajectories and related equipment. Background Art

[0002] Although the existing fault diagnosis technology can improve the safety and reliability of equipment to a certain extent, the process fault diagnosis adopts a shutdown inspection and maintenance system. Excessive maintenance and insufficient maintenance will cause great economic losses. Predictive maintenance realizes the transformation from planned maintenance to condition-based maintenance, improves the reliability of the system and reduces the maintenance cost of the entire life cycle. Remaining life prediction is to estimate the remaining life of the system or equipment based on the extraction of early fault features and trend analysis, so as to provide a decision-making basis for fault diagnosis and predictive maintenance. The remaining life assessment model is a model that predicts the remaining service life of a device or system at a certain point in the future. This model is usually based on the equipment's operating history data and performance degradation data. It predicts the remaining life by analyzing the performance degradation and wear of the equipment.

[0003] With the high integration of systems and the complexity of operating environments, the reliability of complex systems reflects the characteristics of complex structures, diverse failure modes, and nonlinear operating conditions. The advancement of science and technology has greatly improved the reliability of products. Therefore, it is extremely difficult to observe the end-of-life data of products in a natural state. As a second choice, we can model by observing the degradation data of core components. Specifically, the remaining life assessment model can be analyzed and modeled based on the key performance indicators of components, such as temperature, pressure, vibration, etc. These indicators can reflect the operating status and health of the equipment, and then predict the remaining service life of the equipment.

[0004] There are two types of existing remaining life modeling: one is based on statistical analysis modeling, and the other is based on deep learning modeling. However, both have certain shortcomings.

[0005] For example, the modeling method based on statistical analysis has the problem that the correlation of multiple failure modes cannot be measured. The modeling method based on deep learning has sample size limitations, the neural network is unable to explain its own reasoning process and reasoning basis and the significance of its stored knowledge, the neural network uses knowledge and expresses knowledge in a single way, the neural network can only use numerical knowledge, and the neural network can only simulate intelligent activities at the human sensory level. Summary of the invention

[0006] The embodiments of the present application provide a complex system remaining life modeling method and related equipment based on fault trees and degradation trajectories to solve the technical problems existing in the prior art.

[0007] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0008] According to a first aspect of an embodiment of the present application, a method for modeling the remaining life of a complex system based on a fault tree and a degradation trajectory is provided, comprising:

[0009] Establish a fault tree with complex system failure as the top event;

[0010] Performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events;

[0011] The fault tree is combined with the degradation models of all bottom events to establish a remaining life model for the complex system.

[0012] In some embodiments of the present application, based on the above solution, the establishment of a fault tree with the failure of a complex system as the top event includes:

[0013] Take the failure of complex system as the top event of the fault tree;

[0014] Taking the top event as a starting point, the intermediate events and the bottom events of the fault tree are determined, and the intermediate events and the bottom events are connected according to the causal relationship between the intermediate events and the bottom events to form a complete fault tree.

[0015] In some embodiments of the present application, based on the above solution, after establishing the fault tree, the method further includes:

[0016] The structure function method is used to solve the minimum cut set of the fault tree.

[0017] In some embodiments of the present application, based on the above solution, the method of using the structure function method to solve the minimum cut set of the fault tree includes:

[0018] Assume that the expression of the minimum cut set K of the fault tree is:

[0019] K=x1x2…x m ;

[0020] Based on the expression of the minimum cut set K of the fault tree, the expression of the top event T of the fault tree is obtained:

[0021] T=K1+K2+…+K j +…+K n ;

[0022] Calculate the occurrence probability q of the minimum cut set of the fault tree according to the probability formula of independent events k :

[0023]

[0024] The probability of occurrence q(T) of the top event of the fault tree is calculated according to the probability formula of independent events:

[0025]

[0026] Among them, x represents the bottom event, m represents the number of bottom events, K represents the minimum cut set of the fault tree, and n represents the number of top events.

[0027] In some embodiments of the present application, based on the above solution, performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events includes:

[0028] Collecting observation data of product performance degradation, wherein the observation data includes a time point and a corresponding performance degradation amount;

[0029] Preprocess the collected observation data;

[0030] Based on the characteristics of the observed data and the purpose of modeling, a suitable degradation trajectory model or random process model is selected for degradation modeling, and model parameters are estimated.

[0031] In some embodiments of the present application, based on the above scheme, in the process of degradation modeling, the Wiener process is used to fit the degradation amount to obtain the failure threshold ξ, where X(t) represents the performance degradation measurement value of the product at time t, and the degradation trajectory is expressed as follows:

[0032]

[0033] Where u represents the drift coefficient of the Wiener process, σ represents the diffusion coefficient of the Wiener process, η represents the mean value of u, and τ(t) represents the function of time t.

[0034] In some embodiments of the present application, based on the above scheme, the model parameters include:

[0035] The product life Y is the time when the performance degradation X(t) first reaches the failure threshold ξ, and the formula is as follows:

[0036] Y=inf(t|X(t)≥ξ,t>0);

[0037] The distribution function F of the product life Y Y (t), the formula is as follows:

[0038]

[0039] Here, e represents a natural constant.

[0040] In some embodiments of the present application, based on the above scheme, the distribution function F of the remaining life model of the complex systemT (t) is:

[0041]

[0042]

[0043] Where K represents the minimum cut set of the fault tree;

[0044] The remaining life at any time t is estimated as:

[0045]

[0046] Among them, f T (t+x) is F T (t) Derivative.

[0047] According to a second aspect of an embodiment of the present application, a complex system remaining life modeling device based on a fault tree and a degradation trajectory is provided, comprising:

[0048] Establishment unit for establishing fault tree with failure of complex system as top event;

[0049] A modeling unit, used for performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events;

[0050] The combining unit is used to combine the fault tree with the degradation models of all bottom events to establish a remaining life model of the complex system.

[0051] According to a third aspect of an embodiment of the present application, there is provided an electronic device, including: a memory and a processor;

[0052] The memory is used to store computer instructions;

[0053] The processor is used to call the computer instructions stored in the memory so that the electronic device executes the method as described in the first aspect.

[0054] The technical solution of the present application, combining the fault tree and degradation trajectory methods, establishes a remaining life prediction model for complex systems. The model can dynamically sense the health status of the system and provide technical support for preventive maintenance, thereby improving the safety and reliability of the system.

[0055] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0057] Figure 1 A flow chart of a method for modeling the remaining life of a complex system based on a fault tree and degradation trajectory according to an embodiment of the present application is shown;

[0058] Figure 2 A block diagram of a complex system remaining life modeling device based on a fault tree and degradation trajectory according to an embodiment of the present application is shown;

[0059] Figure 3 A block diagram of an electronic device according to an embodiment of the present application is shown;

[0060] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0061] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0062] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0063] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0064] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0065] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] Some embodiments of the present application will be described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments may be combined with each other.

[0067] See also Figure 1 , shows a flow chart of a method for modeling the remaining life of a complex system based on a fault tree and degradation trajectory according to an embodiment of the present application.

[0068] like Figure 1 As shown, a complex system remaining life modeling method based on fault tree and degradation trajectory is presented, and the method includes steps S100 to S300.

[0069] refer to Figure 1 , step S100, establishing a fault tree with the complex system failure as the top event.

[0070] It can be understood that the top event is the top-level event in the fault tree analysis, that is, the most undesirable fault state or accident in the system under study. It is the goal and research object of the entire fault tree analysis.

[0071] In some feasible embodiments, based on the above solution, establishing a fault tree with the failure of the complex system as the top event includes:

[0072] Take the failure of complex system as the top event of the fault tree;

[0073] Taking the top event as a starting point, the intermediate events and the bottom events of the fault tree are determined, and the intermediate events and the bottom events are connected according to the causal relationship between the intermediate events and the bottom events to form a complete fault tree.

[0074] The intermediate events can be understood as the trunk of the fault tree, while the bottom events can be understood as the branches of the fault tree. In the specific process of establishing the fault tree, the top events and the intermediate events can be represented by rectangular symbols, and the bottom events can be represented by circular symbols. The causal relationships between them can be connected with corresponding logical symbols to form a complete fault tree.

[0075] In some feasible embodiments, based on the above solution, after establishing the fault tree, the method further includes:

[0076] The structure function method is used to solve the minimum cut set of the fault tree.

[0077] In some feasible embodiments, based on the above solution, the method of using the structure function method to solve the minimum cut set of the fault tree includes:

[0078] Assume that the expression of the minimum cut set K of the fault tree is:

[0079] K=x1x2…x m ;

[0080] Based on the expression of the minimum cut set K of the fault tree, the expression of the top event T of the fault tree is obtained:

[0081] T=K1+K2+…+K j +…+K n ;

[0082] Calculate the occurrence probability q of the minimum cut set of the fault tree according to the probability formula of independent events k :

[0083]

[0084] Where q1q2…q m is the bottom event x1x2…x in the cut set K m The probability of occurrence;

[0085] The probability of occurrence q(T) of the top event of the fault tree is calculated according to the probability formula of independent events:

[0086]

[0087] Among them, x represents the bottom event, m represents the number of bottom events, K represents the minimum cut set of the fault tree, and n represents the number of top events.

[0088] It can be understood that, since the bottom events in the minimum cut set of the fault tree are independent events, the occurrence probability of the minimum cut set in this embodiment is calculated according to the probability formula of independent events.

[0089] Continue to refer Figure 1, step S200, performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events.

[0090] In some feasible embodiments, based on the above solution, performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events includes:

[0091] Collecting observation data of product performance degradation, wherein the observation data includes a time point and a corresponding performance degradation amount;

[0092] Preprocess the collected observation data;

[0093] Based on the characteristics of the observed data and the purpose of modeling, a suitable degradation trajectory model or random process model is selected for degradation modeling, and model parameters are estimated.

[0094] For example, in the process of collecting observation data, X(t ij ) identifies product i at time t ij The measured value is ΔX(t ij )=X(t ij )-X(t ij-1 ),Δτ(t ij )=τ(t ij )-τ(t ij-1 ).

[0095] Exemplarily, preprocessing includes cleaning, denoising, interpolation, etc., aiming to improve data quality.

[0096] It should be noted that, in this embodiment, the model parameters are estimated using methods such as regression analysis and maximum likelihood estimation.

[0097] In some feasible embodiments, based on the above scheme, in the process of degradation modeling, the Wiener process is used to fit the degradation amount to obtain the failure threshold ξ, where X(t) represents the performance degradation measurement value of the product at time t, and the degradation trajectory is expressed as follows:

[0098]

[0099] Where u represents the drift coefficient of the Wiener process, σ represents the diffusion coefficient of the Wiener process, η represents the mean value of u, and τ(t) represents the function of time t.

[0100] In some feasible embodiments, based on the above scheme, the model parameters include:

[0101] The product life Y is the time when the performance degradation X(t) first reaches the failure threshold ξ, and the formula is as follows:

[0102] Y=inf(t|X(t)≥ξ,t>0);

[0103] The distribution function F of the product life Y Y (t), the formula is as follows:

[0104]

[0105] Here, e represents a natural constant.

[0106] Continue to refer Figure 1 , step S300, combining the fault tree and the degradation models of all bottom events to establish a remaining life model of the complex system.

[0107] It can be understood that the established fault tree is equivalent to the structural framework of the system, and the established degradation model is the actual content in the framework. Combining the structural framework with the actual content will result in the final remaining life model.

[0108] In some feasible embodiments, based on the above scheme, the distribution function F of the remaining life model of the complex system is T (t) is:

[0109]

[0110] Where K represents the minimum cut set of the fault tree;

[0111] The remaining life at any time t is estimated as:

[0112]

[0113] Among them, f T (t+x) is F T (t) Derivative.

[0114] In summary, the method provided in the embodiment of the present application combines the fault tree and degradation trajectory methods to establish a remaining life prediction model for a complex system, which can dynamically perceive the health status of the system and provide technical support for preventive maintenance, thereby improving the safety and reliability of the system.

[0115] The method provided in the embodiment of the present application carries out remaining life modeling on the basis of establishing a fault tree of a complex system, fully considering the structural mechanism of the complex system, and the model is more accurate.

[0116] The following describes an embodiment of the device of the present application, which can be used to implement a complex system remaining life modeling method based on a fault tree and degradation trajectory in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the above method of the present application.

[0117] Reference Figure 2As shown, according to an embodiment of the present application, a complex system remaining life modeling device 200 based on a fault tree and a degradation trajectory includes:

[0118] A building unit 201 is used to build a fault tree with a complex system failure as a top event;

[0119] A modeling unit 202, configured to perform degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events;

[0120] The combining unit 203 is used to combine the fault tree with the degradation models of all bottom events to establish a remaining life model of the complex system.

[0121] like Figure 3 As shown, an embodiment of the present application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, the steps of the above-mentioned method for modeling the remaining life of a complex system based on a fault tree and a degradation trajectory are implemented.

[0122] Since the electronic device introduced in this embodiment is a device used to implement a complex system remaining life modeling device based on fault trees and degradation trajectories in an embodiment of the present application, based on the method introduced in the embodiment of the present application, technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0123] During the specific implementation process, when the computer program 311 is executed by a processor, any implementation method in the embodiments corresponding to the first aspect can be implemented.

[0124] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0125] It should be noted that Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0126] like Figure 4As shown, the computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In the RAM 403, various programs and data required for system operation are also stored. The CPU 401, ROM 402 and RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0127] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0128] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 409, and / or installed from a removable medium 411. When the computer program is executed by a central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0129] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0130] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0131] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0132] As another aspect, the present application further provides a computer program product or a computer program, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes a complex system remaining life modeling method based on a fault tree and a degradation trajectory described in the above embodiment.

[0133] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements a complex system remaining life modeling method based on a fault tree and a degradation trajectory described in the above embodiment.

[0134] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0135] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0136] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary techniques in the art that are not disclosed in the present application. It should be understood that the present application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A complex system residual life modeling method based on fault tree and degradation trajectory, characterized in that: include: Establish a fault tree with complex system failure as the top event; Performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events; The fault tree is combined with the degradation models of all bottom events to establish a remaining life model for the complex system.

2. The method according to claim 1, characterized in that The fault tree is established with the failure of the complex system as the top event, including: Take the failure of complex system as the top event of the fault tree; Taking the top event as a starting point, the intermediate events and the bottom events of the fault tree are determined, and the intermediate events and the bottom events are connected according to the causal relationship between the intermediate events and the bottom events to form a complete fault tree.

3. The method according to claim 2, characterized in that After the fault tree is established, it also includes: The structure function method is used to solve the minimum cut set of the fault tree.

4. The method according to claim 3, characterized in that: The method of using the structure function method to solve the minimum cut set of the fault tree includes: Assume that the expression of the minimum cut set K of the fault tree is: K=x1x2…x m ; Based on the expression of the minimum cut set K of the fault tree, the expression of the top event T of the fault tree is obtained: T=K1+K2+…+K j +…+K n ; Calculate the occurrence probability q of the minimum cut set of the fault tree according to the probability formula of independent events k : The probability of occurrence q(T) of the top event of the fault tree is calculated according to the probability formula of independent events: Among them, x represents the bottom event, m represents the number of bottom events, K represents the minimum cut set of the fault tree, and n represents the number of top events.

5. The method according to claim 4, characterized in that The step of performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events includes: Collecting observation data of product performance degradation, wherein the observation data includes a time point and a corresponding performance degradation amount; Preprocess the collected observation data; Based on the characteristics of the observed data and the purpose of modeling, a suitable degradation trajectory model or random process model is selected for degradation modeling, and model parameters are estimated.

6. The method according to claim 5, characterized in that In the process of degradation modeling, the Wiener process is used to fit the degradation amount and obtain the failure threshold ξ. X(t) represents the performance degradation measurement value of the product at time t. The degradation trajectory is expressed as follows: Where u represents the drift coefficient of the Wiener process, σ represents the diffusion coefficient of the Wiener process, η represents the mean value of u, and τ(t) represents the function of time t.

7. The method according to claim 6, characterized in that The model parameters include: The product life Y is the time when the performance degradation X(t) first reaches the failure threshold ξ, and the formula is as follows: Y=inf(t|X(t)≥ξ,t>0); The distribution function F of the product life Y Y (t), the formula is as follows: Here, e represents a natural constant.

8. The method according to claim 7, characterized in that The distribution function F of the remaining life model of the complex system T (t) is: Where K represents the minimum cut set of the fault tree; The remaining life at any time t is estimated as: Among them, f T (t+x) is F T (t) Derivative.

9. A complex system residual life modeling device based on fault tree and degradation trajectory, characterized in that: include: Establishment unit for establishing fault tree with failure of complex system as top event; A modeling unit, used for performing degradation modeling on each bottom event in the fault tree to obtain degradation models of all bottom events; The combining unit is used to combine the fault tree with the degradation models of all bottom events to establish a remaining life model of the complex system.

10. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer instructions; The processor is used to call the computer instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-8.

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