Fault analysis method and device and processing equipment

Abstract

The invention provides a fault analysis method and device and processing equipment. The method comprises the following steps: acquiring a fault report; obtaining a subject keyword in the fault report as a target subject keyword; according to the target subject keyword, determining a subject corresponding to the generated fault as a target subject; and obtaining an analysis result of the fault according to the target subject.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of production lines, and more specifically, to a fault analysis method, device, and processing equipment. Background Art

[0002] In modern manufacturing, especially on highly automated production lines, system failures, equipment defects or product quality problems (i.e. "bugs") may cause production stoppages, quality degradation, and even affect the operation of the entire production chain. At present, traditional bug detection and analysis methods mainly rely on manual inspection or algorithmic tools in a single discipline, which often requires a lot of manpower and time. As the complexity of factory equipment increases, the analysis methods of a single discipline cannot effectively deal with interdisciplinary problems, resulting in inefficient bug solving. Summary of the invention

[0003] An objective of the embodiments of the present disclosure is to provide a fault analysis method, apparatus and processing equipment.

[0004] According to a first aspect of an embodiment of the present disclosure, a fault analysis method is provided, including:

[0005] Get fault reports;

[0006] Obtaining subject keywords in the fault report as target subject keywords;

[0007] According to the target subject keyword, determine the subject corresponding to the generated fault as the target subject;

[0008] An analysis result of the fault is obtained according to the target subject.

[0009] Optionally, obtaining a subject keyword in the fault report as a target subject keyword includes:

[0010] Extracting a fault statement describing the fault in the fault report according to preset fault keywords;

[0011] Obtain the subject keyword in the fault statement as the target subject keyword.

[0012] Optionally, the method further includes:

[0013] Determine the time when the fault occurs according to the fault report;

[0014] The fault statement is also extracted according to the fault occurrence time.

[0015] Optionally, the method further includes:

[0016] The analysis result is obtained according to the target subject keywords and the fault statement.

[0017] Optionally, determining the discipline corresponding to the generated fault as the target discipline according to the target discipline keyword includes:

[0018] Obtain a subject knowledge graph representing the relationship between subjects and subject keywords;

[0019] According to the subject knowledge graph, determining the similarity between the target subject keyword and the subject in the subject knowledge graph;

[0020] The subject having the highest similarity to the target subject keyword is determined as the target subject.

[0021] Optionally, the method further includes:

[0022] Obtain multiple preset subjects and multiple subject keywords corresponding to each subject;

[0023] The subject keywords are connected with corresponding subjects to obtain the subject knowledge graph.

[0024] Optionally, the method further includes:

[0025] A decision suggestion for resolving the fault is determined based on the target subject keyword.

[0026] Optionally, the method further includes:

[0027] The analysis results and / or the occurrence of a failure in the processing equipment are displayed.

[0028] According to a second aspect of the present disclosure, there is provided a fault analysis device, comprising:

[0029] A report acquisition module is used to acquire fault reports;

[0030] A keyword acquisition module, used to acquire subject keywords in the fault report as target subject keywords;

[0031] A subject determination module, used to determine the subject corresponding to the generated fault as the target subject according to the target subject keyword;

[0032] A result determination module is used to obtain the analysis result of the fault according to the target subject.

[0033] According to a third aspect of the present disclosure, a processing device is provided, comprising a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the method described in the first aspect of the present disclosure under the control of the computer program.

[0034] Through the embodiments of the present disclosure, the subject keywords in the fault report are obtained as the target subject keywords; according to the target subject keywords, the subject corresponding to the generated fault is determined as the target subject; and the fault analysis result is obtained according to the target subject. In this way, the fault report can be analyzed quickly and accurately, the target subject corresponding to the generated fault can be obtained, and the location and cause of the fault can be located more quickly, so that engineers of the target subject can solve the fault.

[0035] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0037] Figure 1 is a flow chart of a fault analysis method according to an embodiment of the present disclosure;

[0038] Figure 2 is a flowchart of an example of a fault analysis method according to an embodiment of the present disclosure;

[0039] Figure 3 is a block diagram of a fault analysis device according to an embodiment of the present disclosure;

[0040] Figure 4 is a block diagram of a processing device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0041] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0042] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0043] Technologies, methods and equipment known to persons of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods and equipment should be considered part of the specification.

[0044] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0045] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0046] <Method Example>

[0047] The present disclosure provides a fault analysis method, which can be implemented by processing equipment.

[0048] Figure 1 The figure is a flowchart of a fault analysis method according to an embodiment of the present disclosure.

[0049] like Figure 1 As shown, the method includes steps S1100 to S1400 as shown below:

[0050] Step S1100, obtaining a fault report.

[0051] In this embodiment, the fault report may be generated when a processing device fails. The failure of the processing device may be caused by a system failure, a device defect, or a product quality problem.

[0052] Furthermore, each time the processing equipment processes a product, if there is a system failure, equipment defect or product quality problem, a fault report corresponding to the current processing process will be generated.

[0053] In one example, when there is a system failure, equipment defect or product quality problem, the processing equipment may generate a folder at a specified location, and the name of the folder may indicate at least one of the generation time of the folder, information of the processing equipment, and information of the product processed by the processing equipment this time. The folder may include at least one of a log file (i.e., a log file), a csv file, a plist file, etc.

[0054] On this basis, all files in the folder generated by the processing equipment when there is a system failure, equipment defect or product quality problem can be used as a fault report.

[0055] In another example, when a system failure, equipment defect or product quality problem occurs, the processing equipment may generate a log file at a specified location, and the name of the log file may indicate at least one of the generation time of the folder, information about the processing equipment, and information about the product processed by the processing equipment. Then, the log file generated by the processing equipment when a system failure, equipment defect or product quality problem occurs may be used as a fault report.

[0056] Step S1200, obtaining subject keywords in the fault report as target subject keywords.

[0057] In this embodiment, multiple subjects and at least one subject keyword corresponding to each subject may be set in advance based on materials for distinguishing subjects, wherein the materials for distinguishing subjects may include maintenance logs, maintenance records, and historical fault reports of technicians.

[0058] In one embodiment of the present disclosure, all fault reports may be searched based on a plurality of pre-set subject keywords to obtain the subject keywords in the fault reports.

[0059] In another embodiment of the present disclosure, obtaining subject keywords in a fault report as target subject keywords may include: extracting a fault statement describing the fault in the fault report according to preset fault keywords; and obtaining subject keywords in the fault statement as target subject keywords.

[0060] In this embodiment, the fault keywords may be pre-set according to application scenarios or specific requirements. For example, the fault keywords may include error, failed, warning, etc.

[0061] Extracting fault sentences in the fault report according to the fault keyword may be extracting complete sentences including the fault keyword in the fault report, wherein the complete sentences include not only sentences including the fault keyword but also context sentences of the sentences.

[0062] Through this embodiment, the fault statement is extracted first, and then the target subject keywords are obtained from the fault statement. There is no need to search all the statements in the fault report, which can speed up the acquisition of the target subject keywords.

[0063] In one embodiment of the present disclosure, the method may further include: determining the fault occurrence time according to the fault report, and extracting the fault statement according to the fault occurrence time.

[0064] In this embodiment, the folder generated by the processing equipment when there is a system failure, equipment defect or product quality problem may include a file recording the time when the failure occurred, and the time when the failure occurred can be determined based on the file.

[0065] Furthermore, the fault report also records the generation time of all statements. Therefore, a complete statement containing the fault keyword can be searched from the statements whose generation time matches the fault occurrence time as the fault statement.

[0066] Through this embodiment, the fault statement in the fault report can be located more quickly according to the fault occurrence time, thereby shortening the analysis time of the fault report.

[0067] Step S1300, according to the target subject keyword, determine the subject corresponding to the generated fault as the target subject.

[0068] In one embodiment of the present disclosure, a plurality of disciplines and at least one discipline keyword corresponding to each discipline may be set in advance based on materials for distinguishing disciplines.

[0069] In this embodiment, one subject corresponding to all target subject keywords may be determined from a plurality of pre-set subjects as the target subject.

[0070] In one embodiment of the present disclosure, based on the target subject keywords, determining the subject corresponding to the generated fault as the target subject may include: obtaining a subject knowledge graph representing the relationship between the subject and the subject keywords; based on the subject knowledge graph, determining the similarity between the target subject keywords and the subjects in the subject knowledge graph; and determining the subject with the highest similarity to the target subject keywords as the target subject.

[0071] In this embodiment, since there may be a situation where a subject keyword corresponds to multiple subjects, one subject is determined as the target subject from multiple subjects based on the similarity between the target subject keyword and each subject in the subject knowledge graph. This can accurately determine the subject corresponding to the fault caused by the processing equipment this time, so that technicians can find engineers of the corresponding subject to handle the fault based on the determined target subject.

[0072] Specifically, the similarity between each subject keyword and the corresponding subject can be preset according to the relationship between the subject keyword and the subject, as the weight of the corresponding edge in the subject knowledge graph. When a subject keyword corresponds to multiple subjects, the similarity between the subject keyword and the corresponding multiple subjects can be equal or unequal, which can be set according to the actual situation.

[0073] On this basis, for each subject, the sum of the similarities between each target subject keyword and the subject can be determined; and the subject with the highest sum of similarities with all target keywords can be determined as the target subject.

[0074] This embodiment establishes an interdisciplinary knowledge graph to associate the domain knowledge of each discipline with actual data, so as to perform reasoning analysis between data in different fields, conduct a comprehensive collaborative analysis from the perspective of multiple disciplines, solve complex cross-domain problems, and quickly locate the root cause of the fault.

[0075] In one embodiment of the present disclosure, the method further includes: obtaining a plurality of preset disciplines and a plurality of discipline keywords corresponding to each discipline; and connecting the discipline keywords with the corresponding disciplines to obtain a discipline knowledge graph.

[0076] Through this embodiment, a subject knowledge graph can be constructed, so as to determine the target subject corresponding to the generated fault based on the subject knowledge graph and the target subject keywords.

[0077] Step S1400, obtaining the analysis result of the fault according to the target subject.

[0078] In one embodiment of the present disclosure, the target subject may be taken as the analysis result.

[0079] In another embodiment of the present disclosure, the analysis result may be obtained according to the target subject and a preset analysis template.

[0080] Through the embodiments of the present disclosure, the subject keywords in the fault report are obtained as the target subject keywords; according to the target subject keywords, the subject corresponding to the generated fault is determined as the target subject; and the fault analysis result is obtained according to the target subject. In this way, the fault report can be analyzed quickly and accurately, the target subject corresponding to the generated fault can be obtained, and the location and cause of the fault can be located more quickly, so that engineers of the target subject can solve the fault.

[0081] In one embodiment of the present disclosure, the method further includes: obtaining analysis results according to target subject keywords and fault statements.

[0082] In this embodiment, adding target discipline keywords and fault statements to the analysis results can facilitate engineers in the target discipline to locate the location and cause of the fault more quickly, improve fault resolution efficiency, and reduce the possibility of manual inspection and misjudgment.

[0083] In one embodiment of the present disclosure, the method may further include: storing the analysis results to facilitate technical personnel to view and trace back.

[0084] In one embodiment of the present disclosure, the method further includes: displaying analysis results and / or failure conditions of processing equipment.

[0085] In this embodiment, the failure occurrence of the processing equipment may be the number and / or probability of the failure of the processing equipment within a target statistical period. The target statistical period may be pre-set according to an application scenario or specific requirements. For example, the target statistical period may be one day or a complete process of continuously processing the same type of product.

[0086] By displaying the occurrence of faults in processing equipment, it is easy for technical personnel to solve the faults in a timely manner and avoid the expansion of the faults.

[0087] Furthermore, the processing equipment can also issue an alarm when a fault occurs, that is, when a fault report is generated, to remind technical personnel to handle it in time to avoid the expansion of the fault.

[0088] In one embodiment of the present disclosure, the method further includes: determining a decision suggestion for resolving the fault according to the target subject keyword.

[0089] In this embodiment, decision suggestions corresponding to a plurality of subject keyword combinations may be pre-set, and each subject keyword combination may include at least one subject keyword.

[0090] Furthermore, on the basis of obtaining the target subject keyword, the decision suggestion corresponding to the subject keyword combination with the highest similarity to the target subject keyword may be obtained as the decision suggestion for solving the fault.

[0091] Furthermore, the decision suggestion may be stored and / or displayed for reference by technicians.

[0092] This embodiment provides decision suggestions based on target subject keywords, which can provide technicians with optimal repair steps, reduce trial and error time, and reduce manual intervention.

[0093] In one embodiment of the present disclosure, a machine learning model may be pre-trained, and the fault report may be input into the machine learning model to obtain an analysis result. In other words, each step of the method of this embodiment may be implemented by a machine learning model.

[0094] In one embodiment of the present disclosure, technicians can score the obtained analysis results according to actual conditions, and iterate the machine learning model with analysis results with scores greater than or equal to a threshold and corresponding fault reports to improve the analysis accuracy of the machine learning model.

[0095] Figure 2 is a flowchart of an example of a fault analysis method according to an embodiment of the present disclosure.

[0096] like Figure 2 As shown, the method may include the following steps:

[0097] Step S2001, obtaining a fault report.

[0098] Step S2002, determining the fault occurrence time according to the fault report.

[0099] Step S2003: extracting the fault statement describing the fault in the fault report according to the preset fault keywords and the fault occurrence time.

[0100] Step S2004, obtaining the subject keyword in the fault statement as the target subject keyword.

[0101] Step S2005, obtaining a subject knowledge graph representing the relationship between subjects and subject keywords.

[0102] Step S2006, based on the subject knowledge graph, determine the similarity between the target subject keyword and the subject in the subject knowledge graph.

[0103] Step S2007, determining the subject with the highest similarity to the target subject keyword as the target subject.

[0104] Step S2008, obtaining the analysis result of the fault according to the target subject, target subject keywords and fault statement.

[0105] Step S2009, determining a decision suggestion for solving the fault according to the target subject keywords.

[0106] Step S2010, storing and displaying analysis results and decision recommendations.

[0107] <Device Example>

[0108] This embodiment provides a fault analysis device, such as Figure 3 As shown, the fault analysis device 3000 may include a report acquisition module 3100 , a keyword acquisition module 3200 , a subject determination module 3300 and a result determination module 3400 .

[0109] The report acquisition module 3100 is used to acquire fault reports.

[0110] The keyword acquisition module 3200 is used to acquire subject keywords in the fault report as target subject keywords.

[0111] The subject determination module 3300 is used to determine the subject corresponding to the generated fault as the target subject according to the target subject keyword.

[0112] The result determination module 3400 is used to obtain the analysis result of the fault according to the target subject.

[0113] In one embodiment of the present disclosure, the keyword acquisition module 3200 is used to:

[0114] Extracting a fault statement describing the fault in the fault report according to preset fault keywords;

[0115] Obtain the subject keyword in the fault statement as the target subject keyword.

[0116] In one embodiment of the present disclosure, the fault analysis device 3000 further includes:

[0117] A module for determining a fault occurrence time according to the fault report;

[0118] The keyword acquisition module 3200 is further configured to extract the fault statement according to the fault occurrence time.

[0119] In one embodiment of the present disclosure, the result determination module 3400 is further used to:

[0120] The analysis result is obtained according to the target subject keywords and the fault statement.

[0121] In one embodiment of the present disclosure, the subject determination module 3300 is used to:

[0122] Obtain a subject knowledge graph representing the relationship between subjects and subject keywords;

[0123] According to the subject knowledge graph, determining the similarity between the target subject keyword and the subject in the subject knowledge graph;

[0124] The subject having the highest similarity to the target subject keyword is determined as the target subject.

[0125] In one embodiment of the present disclosure, the fault analysis device 3000 further includes:

[0126] A module for obtaining a plurality of preset subjects and a plurality of subject keywords corresponding to each subject;

[0127] A module for connecting the subject keywords with the corresponding subjects to obtain the subject knowledge graph.

[0128] In one embodiment of the present disclosure, the fault analysis device 3000 further includes:

[0129] A module for determining a decision suggestion for resolving the fault based on the target subject keyword.

[0130] In one embodiment of the present disclosure, the fault analysis device 3000 further includes:

[0131] A module for displaying the analysis results and / or the occurrence of a fault in the processing equipment.

[0132] <Processing Equipment Example>

[0133] This embodiment provides a processing device. In one aspect, the processing device may include the aforementioned fault analysis device 3000 .

[0134] On the other hand, Figure 4As shown, the processing equipment 4000 may include a processor 4100 and a memory 4200, the memory 4200 is used to store a computer program, and the processor 4100 is used to control the processing equipment to execute the method of any embodiment of the present disclosure under the control of the computer program.

[0135] The processing equipment in this embodiment can be any equipment on the production line.

[0136] <Readable Storage Medium Embodiment>

[0137] This embodiment provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the method described in any method embodiment of the present disclosure is executed.

[0138] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0139] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0140] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0141] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0142] Various aspects of the present invention are described herein with reference to the flow charts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0143] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0144] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0145] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a part of a module, a program segment or an instruction, and a part of the module, a program segment or an instruction contains one or more executable instructions for realizing the specified logical function. 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 consecutive boxes 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 and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0146] Embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the marketplace, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A fault analysis method, characterized in that: include: Get fault reports; Obtaining subject keywords in the fault report as target subject keywords; According to the target subject keyword, determine the subject corresponding to the generated fault as the target subject; An analysis result of the fault is obtained according to the target subject.

2. The method according to claim 1, characterized in that The step of obtaining the subject keyword in the fault report as the target subject keyword includes: Extracting a fault statement describing the fault in the fault report according to preset fault keywords; Obtain the subject keyword in the fault statement as the target subject keyword.

3. The method according to claim 2, characterized in that The method further comprises: Determine the time when the fault occurs according to the fault report; The fault statement is also extracted according to the fault occurrence time.

4. The method according to claim 2, characterized in that: The method further comprises: The analysis result is obtained according to the target subject keywords and the fault statement.

5. The method according to claim 1, characterized in that The step of determining the subject corresponding to the generated fault as the target subject according to the target subject keyword includes: Obtain a subject knowledge graph representing the relationship between subjects and subject keywords; According to the subject knowledge graph, determining the similarity between the target subject keyword and the subject in the subject knowledge graph; The subject having the highest similarity to the target subject keyword is determined as the target subject.

6. The method according to claim 5, characterized in that The method further comprises: Obtain multiple preset subjects and multiple subject keywords corresponding to each subject; The subject keywords are connected with corresponding subjects to obtain the subject knowledge graph.

7. The method according to claim 1, characterized in that The method further comprises: A decision suggestion for resolving the fault is determined based on the target subject keyword.

8. The method according to claim 1, characterized in that The method further comprises: The analysis results and / or the occurrence of a failure in the processing equipment are displayed.

9. A fault analysis device, characterized in that: include: A report acquisition module is used to acquire fault reports; A keyword acquisition module, used to acquire subject keywords in the fault report as target subject keywords; A subject determination module, used to determine the subject corresponding to the generated fault as the target subject according to the target subject keyword; A result determination module is used to obtain the analysis result of the fault according to the target subject.

10. A processing equipment, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the method according to any one of claims 1 to 8 under the control of the computer program.

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