CN110163374B - Fault diagnosis reasoning system based on Word general configuration - Google Patents
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Abstract
The invention discloses a fault diagnosis reasoning system based on Word general configuration, which comprises an interaction layer, an algorithm layer, a data layer and a support layer, wherein the support layer comprises a rule base, a quality case base, a system database and a server, the data layer comprises rule data, case data, engineering data, user authority data, fact data and a Spring frame, the algorithm layer comprises a forward reasoning module, a reverse reasoning module, a fault tree picture generation module, a reasoning prompt module and a document generation module, the rule base comprises a data analysis rule table and a fault information rule table, and cause-effect relationships from reasons to faults and rule weight values of the cause-effect relationships are defined in the fault information rule table. According to the invention, the ground-air missile fault diagnosis information is configured in the external Word document, and multi-type fault diagnosis is realized through external file configuration.
Description
Technical Field
The invention relates to a fault diagnosis reasoning software of a ground-air missile testing system based on Word general configuration.
Background
With the improvement of the complexity of the product and the improvement of the maintenance requirement, whether the original data is correctly changed into the bottom data or not is judged, whether the trend is normal or not is judged, and whether the problem is rapidly checked or not is judged. The requirements for the test system are also changed from meeting the test function to deep analysis of data and rapid localization of faults.
When the problems in the test site are checked at present, the following problems exist:
a) when the test fails, a unified and standard troubleshooting flow does not exist, and the problems of failure site damage and failure troubleshooting difficulty are easily caused;
b) when a fault occurs, a reliable diagnosis tool is not available on an operation site, and the bottom layer data analysis needs to be imported into an internal network for shunting and drawing under a Windows system, so that the working efficiency is influenced;
c) when the cable problem appears, need look over the paper drawing, consuming time and wasting power influences the production progress.
The traditional fault diagnosis system needs fault experts and software designers to finish the fault diagnosis together, has low development efficiency and weak universality, and therefore, researches the general fault diagnosis reasoning software based on the expert knowledge base.
Disclosure of Invention
Aiming at the problems existing in the traditional fault diagnosis, the invention configures the ground-air missile fault diagnosis information in an external Word document, and realizes the fault diagnosis of multiple types through the external document configuration.
The technical scheme of the invention is as follows:
a fault diagnosis reasoning system based on Word general configuration comprises an interaction layer, an algorithm layer, a data layer and a support layer, wherein the support layer comprises a rule base, a quality case base, a system database and a server, the data layer comprises rule data, case data, engineering data, user authority data, fact data and a Spring framework, the algorithm layer comprises a forward reasoning module, a reverse reasoning module, a fault tree picture generating module, a reasoning prompting module and a document generating module, the rule base comprises a data analysis rule table and a fault information rule table, and cause-effect relations from reasons to faults and rule weight values of the cause-effect relations are defined in the fault information rule table.
The interaction layer is deployed into a network version or a single machine version through ExtJs and Swing frameworks.
The system performs the following steps: firstly, inputting a fault phenomenon; secondly, fact management, namely listing all possible fault sources according to fault phenomena and stored rules; and thirdly, reasoning forwards or backwards to find the reason and the solution causing the fault source.
And in the first step, the fault phenomenon is not input, but the fact test data information and the rule data information are input and read, and the analysis rule is called to analyze the fact test data to obtain the fault phenomenon.
The forward reasoning module is used for realizing the following steps: a) reading fact test data information and rule data information, calling an analysis rule to analyze the fact test data, and searching a fault source; b) arranging fault sources from large to small according to a mode of weight multiplied by certainty, and popping up a rule that an interface prompts the abnormal fact item by item; c) the user is prompted with 3 options: if yes, no and uncertain, when the user selects 'yes', the software automatically searches and matches the next layer of the fault tree; if no, searching and matching are carried out on the same layer of the fault tree; when the 'uncertain' is selected, entering the next layer of the fault tree, when the fault source is not found in the next layer, returning the item-by-item prompt of the previous layer, and updating the weight, wherein the new weight = the times of the weight x (1 +/-growth rate); d) when the fault point is found or all possible fault rules are checked, the checking is finished; e) updating the newly obtained weight value to the fault rule table to replace the original weight value.
In the step b, an analysis rule is called to analyze the test data, or a hardware resource field test analysis is called, the certainty factor of a normal fault source of the test data is set to 0, the fault source is automatically deleted, and the abnormal condition is not prompted; and for other fault sources which cannot be eliminated, arranging the rules of the fault sources from large to small according to the mode of weight multiplied by the certainty factor, and prompting a user.
The reverse reasoning module is used for realizing the following steps: a) listing all possible faults causing the faults according to the found fault sources, and listing all possible fault rules and root nodes according to the rule weight sequence; b) prompting process, listing corresponding rule checking method and processing method, informing user how to confirm the fault and how to eliminate the fault; c) repeating the step b according to the selection of the user, and updating the weight, wherein the new weight = weight x (1 +/-growth rate)Number of timesUntil the fact base and the root node of the possible rule are not changed any more, reasoning is finished; d) and updating the newly solved weight to a fault rule table to replace the original weight.
The invention has the beneficial effects that: and configuring the ground-air missile fault diagnosis information in an external Word document, and realizing multi-type and multi-type fault diagnosis through external file configuration. The fault expert stores knowledge, rules and analysis methods in Word documents, and the fault diagnosis reasoning software carries out automatic forward and backward reasoning according to the information. The fault diagnosis reasoning software can also carry out reasoning and learning according to external quality cases and diagnosis cases, so that the reasoning result tends to be accurate. .
Description of the drawings:
FIG. 1 is a schematic diagram of the system of the present invention.
Fig. 2 is a schematic structural diagram of a functional module according to the present invention.
FIG. 3 is a schematic diagram of a fault rule table.
Fig. 4 is a generated tree diagram.
Fig. 5 is a partial interface diagram of the software.
Detailed Description
The invention relates to a fault diagnosis reasoning system of an air-ground missile test system based on Word general configuration, which is realized by the following steps:
a) and the algorithm, data and support of the single machine version and the network version are designed into a universal layer through architecture layering. The method is characterized in that the method is deployed into a network version and a single machine version through ExtJs and Swing frameworks, so that the operation of a set of software kernel in two environments is realized;
b) defining the rule base content and the detection and troubleshooting method thereof in Word to realize the external configuration of the inference rule; the inference process supports multiple rule files. Each equipment matching unit on the missile can submit a rule base thereof, and the software realizes the hierarchical reasoning of the faults according to the rule bases;
c) the software running framework adopts spring and hibernate to realize the external configurable characteristics of a software kernel and a database;
d) the framework and the development tool selected by the system are compatible with a Linux system, the framework is an open-source framework, the mysql database is transplanted to a domestic gold warehouse, a dreams and other databases through the external configuration of the database, and the capability of seamless transplantation to a domestic autonomous controllable platform is achieved.
The system is divided into a supporting layer, a data layer, an algorithm layer and an interaction layer. The support layer comprises a rule base, a quality case base, a system database and a server, the data layer comprises rule data, case data, engineering data, user authority data, fact data and a Spring framework, the algorithm layer comprises a forward reasoning module, a reverse reasoning module, a fault tree picture generating module, a reasoning prompting module and a document generating module, and a rule table in the rule base defines cause-effect relationships from reasons to faults and rule weights of the cause-effect relationships. The interaction layer is deployed into a network version or a single machine version through ExtJs and Swing frameworks. The software operation process comprises a management mode and a fault reasoning mode. In the management mode, the method mainly performs knowledge rule management, system management, quality case management and engineering management. In the fault reasoning mode, test data analysis, fact management, forward reasoning and reverse reasoning, reasoning prompt, fault tree picture generation and document generation are mainly carried out. And storing knowledge rule information and a data analysis method in a Word document, and constructing an expert knowledge rule according to the content of the knowledge rule information and the data analysis method. And when the fault is diagnosed, performing data analysis according to a defined data analysis method to obtain fault information. And reasoning the fault information according to rules to form a reasoning result.
The data analysis rule table defines data file names, processing methods, judgment criteria, judgment conditions, fault tolerance criteria and corresponding knowledge rule information. By configuring the table externally, the generalization of data analysis is realized. And analyzing the obtained test data through the rules in the data analysis table to find whether the fault exists. For example, for XXXX _ d.bin files (test data), call the cxxxxxjudgyaocebinhandle interface, read, calculate the cumulative sum. When the sum is accumulated correctly, the 'modulus flight digital quantity interpretation' is set to be correct, otherwise, the 'modulus flight digital quantity interpretation' is set to be wrong. When the analysis result of the 'model flight digital quantity interpretation' is correct, the software sets the certainty factor of the fault source to 0, automatically deletes the fault source and does not prompt the abnormal condition. Bin file represents a 16-system data communication file for product testing, and by means of the file, whether a certain part in a product has a fault or not and whether a certain product is normal or not can be analyzed, and the cxxxxxjudgyaocebibandler is an interface for analyzing the file. This interface is configured in the Word document. For example, we need to change the XXXX _ d.bin analysis and change it to another interface for analysis, and we only need to replace "cxxxjudgyaocebinhandle" with a new name in the Word document.
The fault information table defines extension parameters such as fault types, fault names, aliases, phenomena, detection methods, processing methods and the like, and is used for calling external detection methods. The cause-effect relationship from the cause to the fault, and the certainty factor, the weight value and the growth rate information of the rule are defined in the fault rule table and are used for establishing the priority among the rules. The certainty degree indicates the probability of occurrence of a failure, which inevitably occurs as 100 and does not occur as 0. The weight value represents a prioritization of troubleshooting of multiple failure sources. New weight = weight x (1 + -growth rate)Number of timesThe weight is increased when the source of the fault is determined, and decreased otherwise. Finally, the software sorts the fault sources from large to small according to the mode of the weight multiplied by the certainty factor, and carries out troubleshooting analysis. The certainty factor and the growth rate are initially specified by engineering technicians at the initial stage of defining the troubleshooting rule, and the weight value is exponentially increased or decreased according to the growth rate to realize the dynamic adjustment of the analysis sequence.
The user can select forward reasoning or backward reasoning, and the forward reasoning step is as follows:
a) reading fact information, knowledge and rule information;
b) according to the fact information, popping up an interface to prompt a possible rule which may cause the abnormal fact, and gradually prompting; for example: the fault information is that the uncontrolled instrument response waveform does not exist, all reasons of the uncontrolled instrument response waveform does not exist are found out, the reasons are gradually recurred as results until the reasons can not be subdivided, and finally, a tree-shaped rule shown in fig. 4 is formed;
c) the software calls the analysis rule in fig. 3 to analyze the test data, or calls the hardware resource field test analysis. As in fig. 3, for XXXX _ d.bin files, the cxxxxxjudgyaocebinhandle interface is invoked, and the cumulative sum is read and calculated. When the sum is accumulated correctly, the 'modulus flight digital quantity interpretation' is set to be correct, otherwise, the 'modulus flight digital quantity interpretation' is set to be wrong. When the analysis result of the 'model flight digital quantity interpretation' is correct, the software sets the certainty factor of the fault source to be 0, automatically deletes the fault source and does not prompt the abnormal condition;
d) and for other fault sources which cannot be eliminated, arranging the rules of the fault sources from large to small according to the mode of weight multiplied by the certainty factor, and prompting a user. In the prompting process, a detection method, a processing method and a schematic diagram in the fault information table are displayed on an interface, so that the teaching function of a user is realized; the detection method informs a user of equipment and operation steps required for checking the fault, and the processing method informs the user of a repair measure for the fault; the user carries out detection and repair operations according to the detection method and the processing method;
e) in the troubleshooting process, the user is prompted with 3 options: yes, no and uncertain. The user selects 'yes' when the fault is confirmed by the detection method, selects 'no' when the fault is not confirmed by the user, and can select 'uncertain' if the fault point cannot be determined by the current detection method. When the user selects 'yes', the software automatically searches and matches the next layer of the fault tree; if no, searching and matching are carried out on the same layer of the fault tree; when the selection is uncertain, entering the next layer of the fault tree, and returning to the previous layer for item-by-item prompt when the next layer does not find a fault source;
f) gradually prompting according to user selection and investigation until a root node of the rule is found; after the user operates, the corresponding certainty and weight of the fault source can be dynamically changed, and the software repeatedly enters the d) adjusting sequence; when all fault sources of the fault tree shown in fig. 4 are checked or the user manually exits halfway (for example, the user only needs to check the fault point that the simulation group a consumed current pulse impact does not exist, and does not need to check downwards again), the fault checking is completed;
g) and updating the newly calculated weight to the fault rule table, replacing the original weight, and automatically storing the file of the fault rule table. The updated weight value is used when the software is used next time, and the purpose of self-learning of the diagnosis system is achieved.
The fault diagnosis reasoning software reverse reasoning steps are as follows:
a) reading fact information, knowledge and rule information;
b) analyzing the rule base, listing all possible faults causing the faults, and listing root nodes of all possible rules according to the rule weight sequence;
c) in the prompting process, listing a corresponding rule checking method and a corresponding rule processing method, informing a user how to confirm the fault and how to eliminate the fault;
d) gradually recursing to b) according to confirmation and exclusion of the user to the facts and the rules until the root nodes of the fact base and the possible rules are not changed any more, and finishing reasoning;
e) and updating the reasoning result into the weight of the rule base according to the growth rate and the analysis result to achieve the purpose of self-learning of the diagnosis system.
After the reasoning work is finished, the software generates the fault tree into a fault tree picture in a jpg format, and generates a fault analysis report document in a Word format as a character record for troubleshooting in the reasoning process.
Claims (6)
1. A fault diagnosis inference system based on Word general configuration comprises an interaction layer, an algorithm layer, a data layer and a support layer, and is characterized in that the support layer comprises a rule base, a quality case base, a system database and a server, the data layer comprises rule data, case data, engineering data, user authority data, fact data and a Spring frame, the algorithm layer comprises a forward inference module, a reverse inference module, a fault tree picture generation module, an inference prompt module and a document generation module, the rule base comprises a data analysis rule table and a fault information rule table, cause-effect relationships from reasons to faults and rule weights of the cause-effect relationships are defined in the fault information rule table, and the forward inference module is used for realizing the following steps: a) reading fact data information and rule data information, calling an analysis rule to analyze the fact data, and searching a fault source; b) arranging fault sources from large to small according to a mode of weight multiplied by certainty, and popping up a rule that an interface prompts the abnormal fact item by item; c) the user is prompted with 3 options: if yes, no and uncertain, when the user selects 'yes', the software automatically searches and matches the next layer of the fault tree; if no, searching and matching are carried out on the same layer of the fault tree; when the selection is 'uncertain', the next layer of the fault tree is enteredWhen the next layer does not find the fault source, the next layer returns to the previous layer for item-by-item prompt, and the weight is updated, wherein the new weight = the weight x (1 +/-growth rate)Number of times(ii) a d) When the fault point is found or all possible fault rules are checked, the checking is finished; e) and updating the newly solved weight to a fault rule table to replace the original weight.
2. The fault diagnosis reasoning system based on Word general configuration as claimed in claim 1, wherein: the interaction layer is deployed into a network version or a single machine version through ExtJs and Swing frameworks.
3. The fault diagnosis reasoning system based on Word general configuration as claimed in claim 1, wherein: the system performs the following steps: firstly, inputting a fault phenomenon; secondly, fact management, namely listing all possible fault sources according to fault phenomena and stored rules; and thirdly, reasoning forwards or backwards to find the reason and the solution causing the fault source.
4. The fault diagnosis reasoning system based on Word general configuration as claimed in claim 3, wherein: and in the first step, the fault phenomenon is not input, but the fact data information and the rule data information are input and read, and the analysis rule is called to analyze the fact data to obtain the fault phenomenon.
5. The fault diagnosis reasoning system based on Word general configuration as claimed in claim 4, wherein: in the step b, an analysis rule is called to analyze the test data, or a hardware resource field test analysis is called, the certainty factor of a normal fault source of the test data is set to 0, the fault source is automatically deleted, and the abnormal condition is not prompted; and for other fault sources which cannot be eliminated, arranging the rules of the fault sources from large to small according to the mode of weight multiplied by the certainty factor, and prompting a user.
6. The fault-diagnosis reasoning system based on Word general configuration as claimed in claim 3, wherein the backward reasoning module is for implementingThe following steps are performed: a) listing all possible faults causing the faults according to the found fault sources, and listing all possible fault rules and root nodes according to the rule weight sequence; b) prompting process, listing corresponding rule checking method and processing method, informing user how to confirm the fault and how to eliminate the fault; c) repeating the step b according to the selection of the user, and updating the weight, wherein the new weight = weight x (1 +/-growth rate)Number of timesUntil the fact base and the root node of the possible rule are not changed any more, reasoning is finished; d) and updating the newly solved weight to a fault rule table to replace the original weight.
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