CN114115192A - Base level intelligent guarantee auxiliary system for airborne equipment - Google Patents
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- 238000003745 diagnosis Methods 0.000 claims abstract description 86
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- 238000012360 testing method Methods 0.000 claims abstract description 56
- 238000012423 maintenance Methods 0.000 claims abstract description 46
- 230000002452 interceptive effect Effects 0.000 claims abstract description 25
- 238000011161 development Methods 0.000 claims abstract description 15
- 238000007726 management method Methods 0.000 claims description 54
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- 238000012216 screening Methods 0.000 claims description 3
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- 238000013523 data management Methods 0.000 claims description 2
- 230000002567 autonomic effect Effects 0.000 abstract description 2
- 238000002955 isolation Methods 0.000 abstract description 2
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0262—Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24065—Real time diagnostics
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Abstract
The application provides a base level intelligent guarantee auxiliary system for airborne equipment, belongs to the technical field of maintenance and guarantee, and particularly comprises a management development platform and a browsing operation platform; the management development platform comprises a training data compiling management module and a knowledge case compiling management module, wherein a training database is stored in the training data compiling management module, and a maintenance database is stored in the knowledge case compiling management module; the browsing and operating platform comprises a guarantee training autonomous learning module and a fault diagnosis interactive reasoning module, the guarantee training autonomous learning module acquires training information from a training database and is used for assisting personnel in learning, and the fault diagnosis interactive reasoning module acquires fault diagnosis resources from a maintenance database and assists the personnel in maintenance. Through the processing scheme of this application, help maintenance support personnel to realize the quick location and the accurate isolation of trouble to the maintenance support personnel of being convenient for carry out autonomic training study and post knowledge test.
Description
Technical Field
The application relates to the field of maintenance support, in particular to an airborne equipment-oriented base level intelligent support auxiliary system.
Background
The requirements for ensuring the base level of the airborne equipment are increased day by day, and the complexity and the assembly difficulty of the airborne equipment are increased more and more, so that the requirements for the capability of the ensuring personnel are increased more and more. At present, common fault diagnosis Test methods for airborne Equipment include power-on self Test (BIT), periodic BIT, maintenance BIT, Automatic Test Equipment (ATE), manual Test, manual troubleshooting and the like. Particularly, in the epidemic situation protection period, the personnel circulation is inconvenient, and the problem is more prominent. The matched paper maintenance manual or electronic technical data lacks the capabilities of fault diagnosis assistance and guarantee training and is difficult to meet the use requirements of basic security personnel.
Disclosure of Invention
In view of this, the application provides a basic level intelligent security auxiliary system towards airborne equipment, has solved the problem among the prior art, helps the maintenance support personnel to realize the quick location and the accurate isolation of trouble to the maintenance support personnel of being convenient for carry out autonomic training study and post knowledge test.
The application provides a base level intelligent security auxiliary system towards airborne equipment adopts following technical scheme:
a base level intelligent guarantee auxiliary system facing to airborne equipment comprises a management development platform and a browsing operation platform;
the management development platform comprises a training data compiling management module and a knowledge case compiling management module, wherein a training database is stored in the training data compiling management module, and a maintenance database is stored in the knowledge case compiling management module;
the browsing and operating platform runs on portable maintenance auxiliary equipment and comprises a guarantee training autonomous learning module and a fault diagnosis interactive reasoning module, the guarantee training autonomous learning module acquires training information from a training database in the training data compiling and managing module and is used for assisting equipment to guarantee maintenance personnel to carry out post knowledge learning, the fault diagnosis interactive reasoning module acquires fault diagnosis resources from a maintenance database in the knowledge case compiling and managing module and assists the equipment to guarantee the maintenance personnel to maintain the equipment.
Optionally, the training data compiling and managing module includes an examination question bank data managing unit, a training information compiling unit and an examination result analyzing unit.
Optionally, the guarantee training autonomous learning module includes a virtual training unit, a knowledge retrieval unit, an online examination unit, and an autonomous examination marking unit.
Optionally, the knowledge case compiling and managing module includes a fault tree drawing unit, an automatic rule generating unit, a knowledge base managing unit, a diagnosis case entering unit and a case base managing unit, the fault tree model is established with the assistance of a computer, the production rule is automatically generated according to the node information in the fault tree model, and the diagnosis case entering unit models the elements of the diagnosis case.
Optionally, the fault diagnosis interactive reasoning module includes an interactive reasoning unit, a fault tree analysis and case reasoning fusion diagnosis unit and a fault information statistics unit, the interactive reasoning unit inputs fault phenomena or is equipped with a fault code output by self-detection through a human-computer interaction interface, the interactive reasoning unit automatically reads and analyzes an offline diagnosis resource data packet downloaded in advance, a diagnosis conclusion is obtained through fault tree analysis and case reasoning fusion diagnosis algorithm reasoning, and corresponding maintenance guidance is provided.
Optionally, the fault diagnosis interactive reasoning module includes a new fault recording module, the equipment ensures that maintenance personnel records and stores new faults and/or unsolved faults to the new fault recording module, the management and development platform obtains new faults and/or unsolved fault records from the browsing and running platform, and after the faults are resolved through expert analysis, the fault analysis and resolution method is added to the knowledge case compilation and management module.
Optionally, the management platform obtains the examination result from the autonomous learning module for guarantee training, and the administrator analyzes the examination result and makes the targeted training.
Optionally, the online testing unit operating step includes:
logging in an examination interface, and selecting examination subjects and difficulty coefficients;
automatically screening test questions meeting conditions from a test question numbering library of the training information according to the selected test subjects and the difficulty system to form a test question numbering library to be selected;
randomly selecting test question numbers of different types from a test question number library to be selected according to the value proportions of the blank filling questions, the single-item selection questions, the multiple-item selection questions and the judgment questions;
carrying out repeatability verification on the extracted test question numbers;
if the extracted test question numbers are not repeated, reading corresponding test question information from the test question library according to the test question numbers to generate test papers;
if the test question numbers are repeated, the selection is carried out again from the test question number library to be selected.
Optionally, the operation step of the fault tree analysis and case reasoning fusion diagnosis unit includes:
acquiring fault information including fault phenomena or fault codes output by equipment self-detection;
firstly, diagnosing fault information by adopting a fault tree diagnosis algorithm;
if the fault tree diagnosis algorithm is successfully diagnosed, the diagnosis information is saved, and a diagnosis case base is updated;
if the diagnosis of the fault tree diagnosis algorithm fails, it indicates that the current expert knowledge base is not complete enough, a certain bottom event in the fault tree is a real fault reason but does not appear in the current fault tree, or an undetected bottom event exists, new event content needs to be added, and at the moment, a case matching algorithm is used for diagnosis;
if the case matching algorithm is successfully diagnosed, updating the relevant fault tree model and the expert knowledge base;
if the case matching algorithm fails to diagnose, it indicates that no case matched with the case exists in the current diagnosis case base, and prompts that manual diagnosis needs to be participated in, and the fault information is stored for subsequently updating the diagnosis case base and the expert knowledge base.
Optionally, the management development platform and the browsing operation platform both further include a data security management module, and the data security management module implements user login, role management and information security guarantee functions.
To sum up, the application comprises the following beneficial technical effects:
1. according to the invention, fault diagnosis and maintenance auxiliary guidance can be timely carried out in the base level guarantee maintenance process, and the outfield maintenance guarantee efficiency is improved;
2. the invention processes the complex fault diagnosis work by an intelligent system, reduces the capability requirement on basic-level maintenance support personnel and the dependence on technical experts, and saves the labor cost of maintenance support;
3. the invention provides a good man-machine interaction mode, which is convenient for ensuring maintenance personnel to carry out autonomous training, learning and knowledge testing at any time and any place, can reduce the learning cost and shorten the training period;
4. the invention can completely record the field information and the diagnosis process of the outfield fault, and is convenient for the research personnel to analyze the fault reason and improve the technology after the incident;
5. the portable outdoor maintenance system has good portability, can be used in a severe outdoor maintenance environment, enables maintenance personnel not to carry or frequently browse technical data of equipment, and improves the convenience of maintenance guarantee.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a base-level intelligent security assistance system in the present application.
Fig. 2 is a schematic structural diagram of a training data compiling management module and a guarantee training autonomous learning module in the present application.
Fig. 3 is a schematic flow chart of the operation of the online testing unit in the present application.
Fig. 4 is a schematic structural diagram of a knowledge case compilation management module and a fault diagnosis interactive reasoning module in the application.
Fig. 5 is a schematic view of an operation flow of the fault tree analysis and case reasoning fusion diagnosis unit of the present application.
Detailed Description
The embodiments of the present application will be described in detail below with reference to the accompanying drawings.
The following description of the embodiments of the present application is provided by way of specific examples, and other advantages and effects of the present application will be readily apparent to those skilled in the art from the disclosure herein. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. The present application is capable of other and different embodiments and its several details are capable of modifications and/or changes in various respects, all without departing from the spirit of the present application. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the present application, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present application, and the drawings only show the components related to the present application rather than the number, shape and size of the components in actual implementation, and the type, amount and ratio of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
The embodiment of the application provides a base level intelligent security auxiliary system for airborne equipment.
As shown in fig. 1, the base-level intelligent security assistance system for onboard equipment includes a management development platform and a browsing operation platform.
The management development platform and the browsing operation platform both further comprise data security management modules, and the data security management modules realize functions of user login, role management and information security guarantee. The data security management module is used as a primary interface for logging in the intelligent maintenance auxiliary system, is respectively integrated on the management development platform and the browsing operation platform, adopts multi-level user management and multi-level information management, adopts a dynamic management mode for user logging and database logging, and ensures data security for long-term use.
The management development platform comprises a training data compiling and management module and a knowledge case compiling and management module, wherein a training database is stored in the training data compiling and management module, and a maintenance database is stored in the knowledge case compiling and management module.
As shown in fig. 2, the training data preparation management module includes a question bank data management unit, a training information preparation unit, and an examination result analysis unit. The training data compiling management module exchanges data and calls a system with the equipment guarantee training database through client software, the exchanged data comprise training information, test question resources, examination result information and the like, and functions of managing the test question database data, compiling the training information and analyzing the examination results are provided for administrators and instructors.
And the management platform acquires the examination scores from the autonomous learning module for guaranteeing training, and an administrator analyzes the examination scores and formulates targeted training.
As shown in fig. 4, the knowledge case compiling and managing module includes a fault tree drawing unit, a rule automatic generating unit, a knowledge base managing unit, a diagnosis case entering unit and a case base managing unit, a fault tree model is established with the aid of a computer, a production rule is automatically generated according to node information in the fault tree model, and the diagnosis case entering unit models elements of the diagnosis case. The method mainly provides functions of fault tree drawing, rule automatic generation, knowledge base management, diagnosis case entry and case base management for management personnel and diagnosis experts; by simulating the thinking mode of human experts, taking artificial intelligence technology and computer technology as the basis and taking a knowledge base and an inference machine as the core, the coverage range of a fault mode is expanded, the fault modes corresponding to methods such as BIT, artificial test, manual troubleshooting and the like are covered, and corresponding maintenance guidance is provided, so that the defect of BIT capability of the equipment is made up.
The knowledge case compiling and managing module is used for managing and maintaining the expert knowledge base and the diagnosis case base, establishing an accurate and comprehensive fault tree model with the aid of a computer, automatically generating production rules according to node information in the fault tree model, supporting element modeling of diagnosis cases and inputting of newly added diagnosis cases, and enriching the expert knowledge base and the diagnosis case base.
Browse the operation platform and move on portable maintenance auxiliary assembly, portable maintenance auxiliary assembly adopts an organic whole to dress formula structure, carries out the totally enclosed design, and inside electrical component mainly has LCD screen, mainboard, storage module, lithium electricity module, interface function module to constitute, and intercommunication between each module forms handheld quick-witted inside electrical connection, realizes relevant function.
The browsing and operating platform comprises a guarantee training autonomous learning module and a fault diagnosis interactive reasoning module, wherein the guarantee training autonomous learning module acquires training information from a training database in the training data compiling and managing module and is used for assisting equipment to guarantee maintenance personnel to carry out post knowledge learning, the fault diagnosis interactive reasoning module acquires fault diagnosis resources from a maintenance database in the knowledge case compiling and managing module and assisting the equipment to guarantee the maintenance personnel to maintain equipment.
As shown in fig. 2, the guarantee training autonomous learning module includes a virtual training unit, a knowledge retrieval unit, an online examination unit, and an autonomous scoring unit. The self-learning module for ensuring training mainly obtains three-dimensional dynamic training resources in an airborne equipment ensuring training database for disassembling and assembling complex components of equipment and typical fault maintenance process, realizes the information retrieval function of the training resources, supports random automatic generation of examination paper based on the airborne equipment ensuring training database, has the automatic paper marking function, and can give scores and correct answers of examinees in time.
The question types provided by the automatically generated examination papers mainly take objective questions as main subjects, and comprise blank filling questions, single-item selection questions, multiple-item selection questions and judgment questions. As shown in fig. 3, the specific steps of the online test unit operation include:
and logging in an examination interface, and selecting examination subjects and difficulty coefficients.
And automatically screening test questions meeting the conditions from a test question numbering library of the training information according to the selected test subjects and the difficulty system to form a test question numbering library to be selected.
And randomly selecting test question numbers of different types from the test question number library to be selected according to the value proportions of the blank filling questions, the single-item selection questions, the multiple-item selection questions and the judgment questions.
And carrying out repeatability verification on the extracted test question numbers.
And if the extracted test question numbers are not repeated, reading corresponding test question information from the test question library according to the test question numbers to generate test papers.
If the test question numbers are repeated, the selection is carried out again from the test question number library to be selected.
As shown in fig. 4, the fault diagnosis interactive reasoning module includes an interactive reasoning unit, a fault tree analysis and case reasoning fusion diagnosis unit and a fault information statistic unit, the interactive reasoning unit inputs fault phenomena or fault codes output by self-detection through a human-computer interaction interface, the interactive reasoning unit automatically reads and analyzes offline diagnosis resource data packets downloaded in advance, and a diagnosis conclusion is obtained through fault tree analysis and case reasoning fusion diagnosis algorithm reasoning, and corresponding maintenance guidance is provided. The method mainly provides interactive Reasoning, Fault Tree Analysis (FTA) and Case Based Reasoning (CBR) fusion diagnosis and Fault information statistics functions for the security personnel.
The fault diagnosis interactive reasoning module comprises a new fault recording module, equipment ensures that maintenance personnel record new faults and/or unsolved faults to the new fault recording module and store the new faults and/or unsolved faults, the management and development platform obtains the new faults and/or unsolved fault records from the browsing and operating platform, and after the faults are resolved through expert analysis, fault analysis and resolution methods are added to the knowledge case compiling and managing module.
As shown in fig. 5, the operation steps of the fault tree analysis and case reasoning fused diagnosis unit include:
and acquiring fault information including fault phenomena or fault codes of equipment self-detection output.
Firstly, fault information is diagnosed by adopting a fault tree diagnosis algorithm.
If the fault tree diagnosis algorithm is successfully diagnosed, the diagnosis information is saved, and the diagnosis case base is updated.
If the diagnosis of the fault tree diagnosis algorithm fails, it indicates that the current expert knowledge base is not complete enough, a certain bottom event in the fault tree is a real fault reason but does not appear in the current fault tree, or an undetected bottom event exists, new event content needs to be added, and at this time, a case matching algorithm is used for diagnosis.
And if the case matching algorithm is successfully diagnosed, updating the relevant fault tree model and the expert knowledge base.
If the case matching algorithm fails to diagnose, it indicates that no case matched with the case exists in the current diagnosis case base, and prompts that manual diagnosis needs to be participated in, and the fault information is stored for subsequently updating the diagnosis case base and the expert knowledge base.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A base level intelligent guarantee auxiliary system facing to airborne equipment is characterized by comprising a management development platform and a browsing operation platform;
the management development platform comprises a training data compiling management module and a knowledge case compiling management module, wherein a training database is stored in the training data compiling management module, and a maintenance database is stored in the knowledge case compiling management module;
the browsing and operating platform runs on portable maintenance auxiliary equipment and comprises a guarantee training autonomous learning module and a fault diagnosis interactive reasoning module, the guarantee training autonomous learning module acquires training information from a training database in the training data compiling and managing module and is used for assisting equipment to guarantee maintenance personnel to carry out post knowledge learning, the fault diagnosis interactive reasoning module acquires fault diagnosis resources from a maintenance database in the knowledge case compiling and managing module and assists the equipment to guarantee the maintenance personnel to maintain the equipment.
2. The system of claim 1, wherein the training data preparation and management module comprises a test question bank data management unit, a training information preparation unit and an examination result analysis unit.
3. The system of claim 1, wherein the support training autonomous learning module comprises a virtual training unit, a knowledge retrieval unit, an online examination unit and an autonomous scoring unit.
4. The system as claimed in claim 1, wherein the knowledge case compilation management module comprises a fault tree drawing unit, an automatic rule generation unit, a knowledge base management unit, a diagnosis case entry unit and a case base management unit, the fault tree model is established by computer assistance, production rules are automatically generated according to node information in the fault tree model, and the diagnosis case entry unit models elements of diagnosis cases.
5. The base-level intelligent support auxiliary system for the airborne equipment as claimed in claim 1, wherein the fault diagnosis interactive reasoning module comprises an interactive reasoning unit, a fault tree analysis and case reasoning fusion diagnosis unit and a fault information statistical unit, the interactive reasoning unit inputs fault phenomena or fault codes output by self-detection of the equipment through a human-computer interaction interface, the interactive reasoning unit automatically reads and analyzes offline diagnosis resource data packets downloaded in advance, and a diagnosis conclusion is obtained through reasoning of a fault tree analysis and case reasoning fusion diagnosis algorithm and corresponding maintenance guidance is provided.
6. The system as claimed in claim 1, wherein the fault diagnosis interactive reasoning module includes a new fault recording module, equipment maintenance personnel records and stores new faults and/or unsolved faults in the new fault recording module, the management and development platform obtains new faults and/or unsolved fault records from the browsing and operating platform, and after the faults are resolved through expert analysis, the fault analysis and resolution method is added to the knowledge case compilation management module.
7. The system of claim 1, wherein the management platform obtains examination results from the on-board equipment-oriented base level intelligent security assistance system, and administrators analyze the examination results to develop targeted training.
8. The on-board equipment-oriented base-level intelligent security assistance system of claim 3, wherein the online testing unit operating step comprises:
logging in an examination interface, and selecting examination subjects and difficulty coefficients;
automatically screening test questions meeting conditions from a test question numbering library of the training information according to the selected test subjects and the difficulty system to form a test question numbering library to be selected;
randomly selecting test question numbers of different types from a test question number library to be selected according to the value proportions of the blank filling questions, the single-item selection questions, the multiple-item selection questions and the judgment questions;
carrying out repeatability verification on the extracted test question numbers;
if the extracted test question numbers are not repeated, reading corresponding test question information from the test question library according to the test question numbers to generate test papers;
if the test question numbers are repeated, the selection is carried out again from the test question number library to be selected.
9. The on-board equipment-oriented base-level intelligent support auxiliary system as claimed in claim 5, wherein the operation step of the fault tree analysis and case reasoning fused diagnosis unit comprises:
acquiring fault information including fault phenomena or fault codes output by equipment self-detection;
firstly, diagnosing fault information by adopting a fault tree diagnosis algorithm;
if the fault tree diagnosis algorithm is successfully diagnosed, the diagnosis information is saved, and a diagnosis case base is updated;
if the diagnosis of the fault tree diagnosis algorithm fails, it indicates that the current expert knowledge base is not complete enough, a certain bottom event in the fault tree is a real fault reason but does not appear in the current fault tree, or an undetected bottom event exists, new event content needs to be added, and at the moment, a case matching algorithm is used for diagnosis;
if the case matching algorithm is successfully diagnosed, updating the relevant fault tree model and the expert knowledge base;
if the case matching algorithm fails to diagnose, it indicates that no case matched with the case exists in the current diagnosis case base, and prompts that manual diagnosis needs to be participated in, and the fault information is stored for subsequently updating the diagnosis case base and the expert knowledge base.
10. The base-level intelligent security assistance system for the onboard equipment as claimed in any one of claims 1 to 9, wherein the management development platform and the browsing operation platform each further comprise a data security management module, and the data security management module implements functions of user login, role management and information security.
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