CN110543489B - Solid rocket engine reliability data analysis mining and application software tool - Google Patents
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Abstract
The invention relates to a solid rocket engine reliability data analysis mining and application software tool, which is divided into three layers, namely a basic platform layer, a data management layer and a data application layer, wherein the basic platform is a server layer and comprises an application server, a database server, a file server and an integrated interface; the data management layer is a database layer and has data management functions on basic information of an engine, reliability data of charge and internal heat insulation, reliability data of a spray pipe, reliability data of a shell and external heat insulation, and reliability data of an entire engine and a straight part; the data application layer is a user layer and is used for data query, reliability data analysis, reliability data two-dimensional graph display and reliability data three-dimensional graph display. The invention provides data support for the product quality pre-judgment of the engine, further improves the stability and consistency of the product quality, and lays a foundation for improving the capability of the solid rocket engine in various aspects such as fine management, accurate manufacturing, quality assurance, informatization management and the like.
Description
Technical Field
The invention relates to the technical field of solid rocket engines, in particular to a solid rocket engine reliability data analysis mining and application software tool.
Background
The reliability data is used as the source of the product quality information, reflects the real-time quality condition of the product, is the premise and the basis of the reliability management of modern enterprises, and the reliability data analysis and mining work becomes the basis and the key of the enterprises to effectively perform various reliability management activities. The reliability data statistical analysis can carry out scientific and accurate analysis and prediction on the current and future quality conditions of products or processes, the quality conditions of the products are controlled to be kept in a stable and controlled statistical balance state, the purposes of controlling and improving the quality of the products are finally achieved, and the data analysis mining is a basis and an important means for controlling the quality of data reaction.
The traditional enterprise reliability data collection generally adopts a manual recording mode, and the manual recording mode is low in collection speed, poor in instantaneity and low in precision, and is unfavorable for real-time dynamic management and control of product quality. To solve these problems, foreign scholars have made a great deal of research on reliability data acquisition theory and applications thereof. Along with the continuous development and the deep development of computer technology, the computer technology is promoted to the aspect of reliability data acquisition, and the reliability data acquisition theory and technology are greatly developed. A Krenzel studied a computer-aided acquisition system to assist in analyzing crisis conditions. Billo RE and the like research a data automatic acquisition system based on a code technology. The BEISSBARTH four-wheel aligner, full-automatic headlamp detector and the like in Germany have the advantages of high detection speed, high detection precision, integrated functions and the like, and effectively ensure the quality of products of modern enterprises. At present, many researchers abroad have conducted intensive research on integration, intellectualization and networking of reliability data acquisition technologies.
During the world war II, the statistical method is widely applied to the quality management of national enterprises such as America, english and the like. In order to ensure the quality of a large number of military supplies, the U.S. military is required to popularize a statistical quality control method for all the military supply factories, and the national standards such as ASAZ1.1 quality management guidelines and ASAZ1.2 control chart method for data analysis are formulated. Meanwhile, the united kingdom also sets out "national standards for statistical methods in BS600 industry standardization and quality control" applications. 20. In the last 80 th century, in order to cope with the challenges of high-quality water costs of products from Japanese enterprises, the United states Motorola corporation has created a well-known sigma reliability management concept and its corresponding reliability management system, and by adopting modern advanced statistical quality analysis control methods, the quality level of the products of the corporation is guaranteed to reach the six sigma standard, and the competitiveness of the enterprise in the international market is greatly improved. In addition, the data analysis mining bears a large amount of valuable knowledge information such as product structure composition, types, key reliability data indexes and the like, so that the data analysis mining is also a basis for supporting scientific research and is an important component of core competitiveness. For the above reasons, data analysis mining is increasingly important.
Compared with developed countries, china has a gap in technological level and reliability data analysis mining and application level, and particularly has a larger gap in basic condition. China has proposed the assumption of constructing national science and technology foundation condition platform in 2002, and is widely endorsed by the national institutes of leadership and related departments. After serious investigation and research, the advanced experience at home and abroad is summarized, and the framework and development target of the national science and technology foundation condition platform construction are creatively put forward. In order to effectively manage and analyze the product reliability data in a systematic way and fully mine potential values in the data, domestic universities, enterprises and scientific institutions research management, analysis and application technologies of the product reliability data in different industries, and a series of research results are obtained.
Yang Yang and the like of Beijing Shenzhou aerospace software technology limited company artificially promote the collection and management of reliability data of aerospace model products, propose the construction and management targets of the reliability data packages of the model products, establish the reliability data packages of the model products, can record, transmit, process and utilize the reliability data of the model products, is beneficial to the development of product engineering, improves the analysis, evaluation and improvement capability of the product data, and realizes the tracing and application of the reliability data of the whole life cycle of the model products. The method is characterized in that various reliability data generated in the whole life cycle process of the aero-engine are researched by the northwest industrial university He Chao and Li Jiang, the data information is subjected to classification analysis based on the constituent elements of the engine, the quality information is divided into product types, component types and part types, an aero-engine reliability data information system architecture is established, and the integrated management of the aero-engine reliability data from acquisition, classification and transmission to sharing is realized. Aiming at the problems of lack of unified data sources, difficult data tracking, poor design quality evaluation means and the like in the traditional reliability data management of radar structures, such as thirty-eighth institute Chen Dijiang of China electronic technology group company, a radar structure design quality comprehensive evaluation method is provided by analyzing and researching a radar equipment reliability data classification and system construction method and a reliability data tracking and transmission method based on multi-level and multi-element analysis, an integrated reliability data model supporting a prototype system for evaluating the design quality of radar equipment and improving the design and key parts of the radar equipment is established, and the improved design of the radar equipment structure is guided, so that the purposes of improving the design quality, reducing the maintenance cost and improving the quality control capability are achieved. The reliability data integration method facing the whole life cycle of the product is researched by Beijing aviation aerospace university Zheng Yuansheng and Wang Meiqing, a product whole life cycle reliability data mapping semantic library and an integration mapping model are constructed based on the ideas of extraction, conversion and transfer (ETL) of data, an integration subsystem QQ-DI facing the reliability data of the whole life cycle of the product is designed and developed on the basis, and for heterogeneous reliability data from the whole life cycle of the product, the system can realize statistical analysis and traceability facing the structure and organization structure of the product and automatic generation of a reliability data packet. Through analysis of research on product reliability data analysis mining and application of domestic universities, enterprises and scientific research institutions, analysis and application technology research of reliability data is developed in the research and development process of various industrial products in China, a corresponding reliability data model, a reliability data analysis and evaluation system, a system architecture and the like are initially constructed, and effective support is provided for quality characteristics and reliability of corresponding products. However, in the field of aerospace power systems, because of more data special for engines and insufficient importance of related reliability data, analysis and application technical research of the reliability data of corresponding products are not basically carried out at present, so that research on the reliability data analysis and mining technology of solid rocket engines is needed to be carried out.
During the development of solid rocket engines, a great amount of reliability data is accumulated. However, because the special data in the reliability data of the engine is very much, the pertinence is very strong, and the special of the solid engine is added, the existing general data analysis and mining method of the data is not applicable to the solid rocket engine, so that the existing engine has various reliability data, complex structure, scattered data, heterogeneous sources, large amount of idle data, mixed high-low value data and difficult distinction; and the data cannot be deeply analyzed and processed. Meanwhile, as data analysis mining is the basis and prerequisite of data engineering application, the lack of good data analysis mining software tools leads to low data application level of the existing engine, the actual problem of the engine cannot be solved by utilizing data guidance, and the data due value is not exerted. On one hand, the problems seriously obstruct the rapid development of the informatization technology and the digitization technology of the solid rocket engine, and on the other hand, the reliability data utilization rate of the solid rocket engine is low, which is unfavorable for the quality and reliability evaluation of the solid rocket engine.
Disclosure of Invention
The invention aims to solve the technical problem of providing a solid rocket engine reliability data analysis mining and application software tool to solve the problems of engine reliability data management, analysis mining based on a solid engine reliability data system.
In order to solve the existing technical problems, the invention adopts the following technical scheme: the solid rocket engine reliability data analysis mining and application software tool is divided into three layers of a basic platform layer, a data management layer and a data application layer, wherein the basic platform is a server layer and comprises an application server, a database server, a file server and an integrated interface, and provides platform functions of tree definition user management, authority setting, log management and parameter setting; the data management layer is a database layer and provides data management functions of importing, exporting and editing for basic information of an engine, charging and internal heat insulation reliability data, spray pipe reliability data, shell and external heat insulation reliability data and reliability data of the whole engine and straight parts; the data application layer is a user layer and is a visual tool and an operation interface which interact with a user and is used for including the reliability data application functions of data query, reliability data analysis, reliability data two-dimensional graph display and reliability data three-dimensional graph display.
In particular, the charge and inner adiabatic reliability data, the spray pipe reliability data, the shell and outer adiabatic reliability data and the reliability data of the whole engine and the straight parts of the engine can be further divided into product data, process data and fault data according to life cycle and application,
The product data are divided into engine design research and development data, production manufacturing data and test data, the engine design research and development data system is divided into engine basic data, design data, temporary technical data and calculation data, the basic data are divided into engine structure index data, engine performance index data, engine complete machine and part component main size data, engine performance parameter data, engine working environment data, engine matched data, part component replacement data, engine complete machine and part record data, data labels and whether excessive material generation special release data exist, the design class data are divided into engine drawing pattern data, engine design task data, technical condition data, research summary data, research and development transition evaluation data and characteristic analysis data, the temporary technical data are divided into technical problem processing data, temporary task work data, modification parameter data and modification production data, and the calculation class data are divided into conventional calculation data, simulation calculation class data and other calculation class data; the production and manufacturing data are divided into engine record data and process type data, wherein the engine record data are divided into part component measurement data, working procedure process record data and final assembly test record data, and the process type data are divided into process file data, process report data, process summary data, process analysis data and key process data; the test data are divided into engine development process test data, external field test data and other types of test data, the engine development process test data are divided into part and part assembly test scheme data, part and part assembly test record data, part and part assembly test result analysis data, complete machine test scheme data, complete machine test record data, complete machine test result analysis data and the like, the external field test data are divided into external field flight test data and external field refurbishment test data, and the other types of test data are improvement measure verification test data;
The process data are divided into comprehensive engine guarantee data and health monitoring detection data, wherein the comprehensive engine guarantee data are divided into guarantee data, examination and review data, outsourcing data, material use data and scientific and technical result data, and the health monitoring detection data are divided into engine performance parameter extremum data, engine structure parameter extremum data, engine health monitoring data and engine nondestructive detection data;
the fault type data are divided into typical fault and analysis data and one-to-three data of the engine, wherein the typical fault and analysis data are divided into typical fault data of the engine, fault analysis data and product quality improvement data, and the one-to-three data are divided into one-to-three data of the whole engine, one-to-three data of an engine combustion chamber, one-to-three data of an engine nozzle, one-to-three data of an engine shell and one-to-three data of an engine safety ignition device.
Particularly, the data general functions of the data management function and the data application function of the invention can also comprise data import, data export, data display, data query retrieval, data analysis, addition, editing and deletion, wherein the data import comprises a data import template and a data import verification function; the data display comprises BOM tree display and list display functions; the data analysis is to analyze the packaged reliability data, and is divided into mean value method packaging, minimum value method packaging, maximum value method packaging, power method packaging, square method packaging, fitting method packaging and interpolation method packaging.
In particular, the reliability data analysis of the present invention may also include mathematical operation analysis, data statistics analysis, envelope analysis, regression analysis, and neural network algorithms.
In particular, the data application layer of the present invention may further include a reliability index alarm function, which is divided into a reliability index definition and a risk early warning tree.
Particularly, the solid rocket engine reliability data analysis mining and application software tool can also comprise an algorithm plug and play support, and the algorithm plug and play support has editing management functions on the Python algorithm and parameters and return values thereof.
Particularly, the solid rocket engine reliability data analysis mining and application software tool can also comprise data security management, wherein the data security management comprises login management, access security control, data domain security setting and three-member management adopted by system manager authority.
Aiming at the problems that the reliability data storage types are various, the storage positions are distributed, the data amount is large, the management is irregular, the utilization rate is low, effective support cannot be provided for the research and development of the engine and the reliability improvement, and the like, the invention develops the research of the reliability data analysis, the mining and the application technology of the engine, and simultaneously develops an engine reliability data analysis and mining software tool by utilizing the research results.
The invention is based on a solid engine reliability data system, and aims to realize engine reliability data management, analysis and mining, and the software tool can perform functions of data storage and management, data visual display, reliability index early warning, algorithm plug and play, data dynamic table construction, data analysis, mining and the like of engine reliability data.
According to the invention, the reliability data of the solid rocket engine is taken as a research object, the actual engineering problem of the engine is taken as a main line, a set of highly targeted engine reliability data analysis and mining method and software tool are constructed, an engine reliability database is established, the internal connection and potential rules of various reliability data of the engine are deeply mined while the visualization of the engine data is realized, the data support is provided for the product quality pre-judgment of the engine, the product quality stability and consistency are further improved, and the foundation is laid for improving the capability of multiple aspects such as the fine management, the accurate manufacturing, the quality guarantee, the informatization management and the like of the solid rocket engine.
Advantageous effects
Aiming at the problems that the solid engine has various reliability data storage types, scattered storage positions, large data volume, irregular management, low utilization rate, incapability of providing effective support for engine research and development and reliability improvement and the like, the invention carries out engine reliability data analysis mining technology research and development of software tools thereof. The patent provides a set of software tools comprising engine reliability data management, analysis, excavation and application, and compared with the conventional general data analysis excavation software tools, the software tools have strong pertinence; the method comprises the steps of classifying and constructing a data system of the reliability of the engine, analyzing and mining the data, developing data application and software function modules, and the like, wherein a progressive mode is friendly to workers; meanwhile, the software also comprises the functions of data general function, data dynamic modeling, data analysis and mining method, data visual display, reliability index alarm, algorithm plug and play, data security design and the like, and is compatible with the current mainstream digital research and development mode, thus laying a very favorable foundation for subsequent data application work.
Drawings
FIG. 1 is a schematic diagram of an overall scheme for reliability data analysis mining and application research of a solid engine;
FIG. 2 is a schematic diagram of classification by data type and purpose;
FIG. 3 is a schematic diagram of reliability data analysis and mining technique research;
FIG. 4 is a schematic diagram of a reliability data visualization presentation technique;
FIG. 5 is a schematic diagram of mathematical operations;
FIG. 6 Python algorithm support schematic;
FIG. 7 is a schematic diagram of a reliability data analysis mining and application software system architecture;
FIG. 8 is a schematic diagram of a three-layer physical structure of a reliability data analysis mining software tool;
FIG. 9 is a software data management page diagram;
FIG. 10 software add-on master table interface diagram;
FIG. 11 is an edit and delete interface diagram of a master table;
FIG. 12 is a two-dimensional diagram showing an interface diagram;
FIG. 13 is a three-dimensional diagram showing interface diagram one;
FIG. 14 is a three-dimensional diagram showing interface diagram two;
FIG. 15 is a reliability pre-warning indicator definition interface diagram;
FIG. 16 is a schematic diagram of a risk early warning tree;
FIG. 17 is an algorithm custom and import interface diagram;
FIG. 18 audit log view interface diagram;
FIG. 19 is a schematic view of data import and export business process approval.
Detailed Description
The invention is further described below with reference to the drawings and examples.
The main content of the invention is an engine reliability data analysis mining software tool and a visualization thereof, and main construction ideas of a general scheme of the solid engine reliability data analysis mining and application research are shown in figure 1. The main development flow is as follows: according to the actual state of the engine, the life cycle of the engine is divided into different stages of design development, production and manufacture, test, after-sale use and the like, the type of reliability data in each stage is determined, and the reliability data is induced and carded; for different types of reliability data, carrying out reliability data management method researches based on different modes of file, database data transmission, distributed storage and the like, realizing distributed storage and management of the reliability data, carrying out quality control on the transmitted reliability data, detecting error reliability data, removing repeated reliability data and the like; utilizing the stored reliability data to develop analysis of the reliability data and research of mining technology, and improving analysis processing capacity of different types of reliability data; the method for safely controlling all data access in the architecture by adopting a network or system physical isolation mode is researched, and the top-layer design method is adopted to perform top-layer design on the reliability data analysis and application architecture in the whole life cycle of the solid engine, so that an engine reliability data analysis, mining and application software tool is formed.
1 reliability data classification and system
With the improvement of quality management level and the deepening of the understanding of quality of missile weaponry in recent years, new requirements are put on the construction of reliable data resources under new circumstances. The reliability data classification of the solid rocket engine and the construction of a system are carried out, so that on one hand, the urgent requirements of quality situation analysis and equipment quality comprehensive evaluation in the missile weapon equipment industry are met, the consistency of analysis and evaluation results and the actual performance of equipment is improved, and the scientificity of quality management decisions is ensured; on the other hand, the reliability data is fed back to the research and development processes such as design, production, test and the like, so that the reliability data is used for improving the quality of products and improving the development level.
The project adopts a method of 'structure division and type division' to carry out data system construction on the reliability data of the solid engine. The "split structure" is to classify the reliability data of the engine according to the product structure (generally, the data can be classified into the structure of the engine, the combustion chamber, the spray pipe, the safety ignition device, the thrust terminating mechanism, the self-destruction device, the ground equipment, the accessories and the like). The classification refers to dividing the reliability data of the engine into product data, process data and fault data (the product data is directly related to the quality of the product and comprises design, development, production, manufacturing, test data and the like), the process data mainly comprises comprehensive guarantee data and product health monitoring data, and the fault data relates to the quality improvement of the product and mainly comprises typical fault and analysis data, one-to-three data and the like of the engine.
The engine can be divided into an engine body, a combustion chamber, a spray pipe, a safety ignition device, a thrust stopping mechanism, a self-destruction device, ground equipment, accessories and the like according to the product structure.
The engine reliability data is divided into product data, process data and fault class data according to life cycle and usage. The engine reliability data system is classified according to data types and purposes and is shown in fig. 2.
(1) Product data
The product data includes engine design development data, manufacturing data, and test data.
1) Solid rocket engine design development data
The engine design development data system comprises engine basic data, design data, temporary technical data and calculation data.
The basic data is the basis of works such as engine design, production, renovation and reconstruction, outfield test and the like, whether the basic data is comprehensive, whether the inquiry is convenient and whether the data accurately relate to the aspects of daily work of the engine. The basic engine data comprise data of special conditions such as engine structural index data, engine performance index data, main size data of the whole engine and the components of the engine, engine performance parameter data, engine working environment data, engine matching data, component replacement data, history data of the whole engine and the components of the engine, data labels, special release of out-of-tolerance material substitution and the like.
Design data is a main basis for engine design, use, maintenance and other works, and is also one of important contents of an engine research and development data system. The design class data comprise the contents of engine drawing pattern data, engine design task data, technical condition data, development summary data, development transition evaluation data, characteristic analysis data and the like.
The temporary technical data is technical data which is additionally added in order to ensure the smooth progress of tasks in the production and use processes of the engine, and is an important supplement to design data. The temporary technical data comprise technical problem processing data (unqualified product processing list, question list and other problem processing files), temporary task work data (technical notice data, scheduling notice data, process notice data and the like), parameter changing data, production data modification and the like.
The calculation data is also one of important contents of an engine design research and development data system, and plays an important role in the processes of engine scheme design, batch production use, simulation modeling and the like. The calculation class data includes conventional calculation data (engine and component parameter calculation data, calculation results, calculation programs, calculation reports), simulation calculation class data, and other calculation class data.
2) Solid rocket engine production and manufacturing data
The solid rocket engine production and manufacturing data system comprises engine record data and process type data.
Recorded data refers to data extracted from original records during the production and manufacturing process of the engine. The record class data includes aspects such as part component measurement data, process record data, assembly test record data, and the like.
The process data is one of important contents of an engine production and manufacturing data system, and plays an important role in engine manufacturing, mass production and the like. The process type data comprises process file data, process report data, process summary data, process analysis data, key process data and the like.
3) Solid rocket engine test data
The solid rocket engine test data system comprises engine development process test data, outfield test data and other types of test data.
The machine development process test data comprise part (part assembly) test scheme data, part (part assembly) test record data, part (part assembly) test result analysis data, complete machine test scheme data, complete machine test record data, complete machine test result analysis data and the like.
The external field test data comprise external field flight test data (pre-admission review, pre-flight detection and post-flight data processing), external field refurbishment test data (decomposition work, detection work and reloading work) and the like.
Other types of test data should include: the improvement measures verify the content of the test data and the like.
(2) Process data system
The process data comprises comprehensive engine guarantee data and health monitoring data
The engine will use different full life cycle data to judge the actual state of the engine at different stages of the full life cycle. The engine quality data comprise the aspects of guarantee data, review and review data, outsourcing data, material use data, scientific and technical result data and the like.
The diagnosis data comprise the content of engine performance parameter extremum data, engine structure parameter extremum data, engine health monitoring data, engine nondestructive testing data (ultrasonic flaw detection negative film, accelerator flaw detection negative film) and the like.
(3) Fault data system
The fault data system comprises typical fault and analysis data of the engine and one-to-three data.
Typical fault and analysis data include: typical fault data of the engine, fault analysis data, product quality improvement data and the like.
The primary and secondary data include: the system comprises data of the whole engine, data of the engine combustion chamber, data of the engine nozzle, data of the engine casing, data of the engine safety ignition device, and the like.
2 reliability data analysis and mining technique
The reliability data analysis and mining of the solid rocket engine are key to the reliability data processing, a large amount of reliability data has no practical significance, and the data can only play a role by analyzing the data aiming at specific application states and converting the data into useful results. Because of the variety of solid rocket engine reliability data and multiple sources of heterogeneous, the traditional data analysis method is difficult to adapt to the engine reliability data analysis and application requirements. Based on the reliability data acquisition, storage and management technology research, the part effectively improves the inherent connection and potential rule capability of different types of reliability data of the mining engine by carrying out data analysis and mining method research such as classification cluster analysis, regression analysis, association rule analysis and the like, and provides effective data support for data application problems such as product performance trend analysis, quality early warning, fault differential investigation and the like. Reliability data analysis and mining technology research is shown in fig. 3.
(1) Conventional mathematical analysis and mining technology research on reliability data
The conventional mathematical analysis method of the engine reliability data is to analyze the engine reliability data by using a mature mathematical method, and the analysis method is the most-used, most-needed and most-widely-applied analysis mining method at present, and the conventional mathematical analysis method comprises the contents of mathematical operation analysis, data statistics analysis, two-dimensional graph analysis, envelope analysis, deviation analysis and the like. Through the conventional mathematical analysis mining technology, a large amount of simple and visual data can be provided for the aspects of engine design, production, manufacture, test, report writing and the like, and data support is provided for the smooth progress of daily development work of the engine.
(2) Dedicated reliability data analysis and mining technology research
In the general concept of reliability data, there are dedicated reliability data and general reliability data, respectively, and for solid rocket engines, key data affecting the quality of the solid rocket engines are basically engine-dedicated data (such as heat insulation layer bonding data, grain structural integrity data, propellant mechanical property data and the like). Therefore, research on engine-specific reliability data analysis mining technology is an important item of the present subject. The special reliability data analysis and mining method for the engine combines the characteristics of the engine, develops the analysis and mining of the special forming process and the special professional data of the engine, and is a summary and a continuation of the special reliability data analysis algorithm for the engine in the past.
(3) Reliability data classification cluster analysis and mining technology research
The engine reliability data classification cluster analysis method is to find out common characteristics and different points of one or more groups of data in a database, and divide the data into several categories according to similarity and difference, so that the similarity between the data in the same category is as large as possible, and the similarity between the data in different categories is as small as possible. The analysis mining method can be applied to aspects of engine batch management, general problem analysis, differential searching of faults or problems and the like.
(4) Reliability data association rule analysis and mining technology research
The engine reliability data association rule analysis method is based on that certain items in one data set can be caused to appear in the same kind of data set, and the aim is to find out the association and interrelationship hidden between the data. Through the analysis and mining technology, key factors influencing different working processes of the engine can be found out from a large amount of data, and data support is provided for positioning of engine products, analysis of test risks and production flight decisions.
3 reliability data application
(1) Reliability data early warning and evaluation technology research
And obtaining envelope ranges of engine material characteristics, structural dimensions, key part component main performance characterization parameters and the like through a reliability data envelope analysis function, thereby giving an engine reliability judgment criterion. Based on the analysis, the functions of mathematical operation analysis, data statistics analysis, two-dimensional graph analysis, envelope analysis, deviation analysis, data classification clustering analysis, regression analysis, association rule analysis and the like are used for obtaining the reliability data change trend and fluctuation rule, predicting the quality state of the engine according to the quality judgment rule, and providing a quality fluctuation early warning signal, thereby providing powerful technical support for improving the quality reliability, stability and consistency of the solid engine product, providing corresponding reference and basis for improving the capability of the solid engine design, process manufacture and the like, and solving the reliability data service, integration and application problems of the solid engine product performance trend analysis, quality early warning, fault difference investigation and the like.
(2) Reliability data visualization technology research
The solid rocket engine life cycle reliability data are mined and analyzed, and the data are displayed in a specific mode, so that a user can conveniently, intuitively and rapidly acquire the internal relation, potential rules and the like of the engine data. For traditional structured data, the data can be represented in the forms of direct data value display, data table display, various statistical graphic displays and the like, but the data is not structured, and the traditional display method is generally difficult to represent due to various types, multiple sources and heterogeneous and complex relationships, and a large number of data tables and a complex relationship diagram can lead users to feel confusing, and even mislead the users. By developing technical researches on visual data display such as computer graphics and image processing, conventional two-dimensional data graph display is performed, and the change trend of an internal unit of an engine model is displayed through color change, the capabilities of product performance trend analysis, quality early warning, fault differential investigation and the like can be effectively improved, and data support is provided for solving the technical problems encountered in the design, production, test, storage and flight of a solid rocket engine. The reliability data visual display technology is studied as shown in figure 1.
4 engine reliability data management, analysis and application tool design
Through comprehensive condensation and integrated reliability data classification, reliability data storage and management, reliability data analysis and mining, deep application of reliability data and other key technologies, solid engine reliability data management, analysis and application platform system architecture is systematically developed, functional module design and customization and other researches are conducted, a software platform capable of effectively supporting solid engine reliability data application is constructed, reliability data application research is conducted on the basis, and scientificity, effectiveness and rationality of the subject result are comprehensively verified.
(1) Running environment
Table 1 System hardware
Table 1 System software
(2) System architecture
The system architecture of engine reliability data analysis and application is divided into: the three layers of the basic platform layer, the data management layer and the data application layer are specifically described as follows:
and (3) a basic platform: a management software development platform (SUN) provides platform functions such as tree definition user management, authority setting, log management, parameter setting and the like;
the data management layer provides data management functions such as import, export, editing and the like for basic information of an engine, charging and inner heat insulation reliability data, spray pipe reliability data, shell and outer heat insulation reliability data, reliability data of the whole engine, direct parts and the like;
Data application layer: the reliability data application function specifically comprises the functions of data query, reliability data analysis, reliability data two-dimensional graph display, reliability data three-dimensional graph display and the like.
The architecture of the system is a mainstream B/S-based three-layer architecture, and the three-layer architecture can well realize an MCV (Model/Controller/View) design mode advocated in software engineering, namely, a database layer is used for realizing data storage (Model), a server layer is used for realizing business logic and business flow (Controller), and a user layer is used for realizing a data display function (View).
The three layers can be operated on different computers respectively.
The database layer adopts an international popular Oracle relational database. The Oracle database has strong data storage and query capacity, is suitable for mass data management, and has good stability and expandability;
the server layer mainly comprises an application server, a database server, a file server, an integrated interface and the like;
the user layer is mainly the visualization tools and the operation interface that interact with the user. See in particular figures 7-8.
(3) Data general function design
Data importation
A data importing template;
and carrying out custom development according to the provided data template, analyzing the data template, and carrying out data importing.
Data import checking;
when the data is imported, data verification is carried out, if a problem exists in the imported template, if a certain line lacks data, the importing is carried out the rollback, and the number of problem lines is printed and reported in the page.
Data export
The system supports exporting the reliability test data stored in the system in the forms of EXCEL, WORD and the like, storing the reliability test data locally, and only the data manager has the authority, and other people have no exporting authority.
Data presentation
BOM tree display;
the system is navigated by the multi-dimensional display data of the BOM tree, is convenient for a user to check, and comprises a product code number, a pattern code number and the like.
Displaying a list;
the reliability test data imported into the system will be presented in a tabulated situation.
Data query retrieval
Ordinary inquiry;
the system can provide a query area in the reliability data management page, the system displays the query condition defined by the background in the area, inputs query content, and can query by clicking the [ query ] button.
Advanced querying;
the method can be used for switching by clicking (advanced query) in a query area, and in the advanced query, a user can select a column to be queried by himself and configure a complex query expression by himself. After configuration is finished, clicking a button for inquiring, and inquiring can be performed. The configured query condition information system can be reserved, so that the next query is convenient.
Data analysis
The system provides a packaged reliability data analysis method, comprising:
packaging by a mean value method;
in the data management page, a certain data column is selected, a packaging method is clicked (mean value) and the system can automatically calculate the mean value of the data column;
packaging by a minimum value method;
in the data management page, a certain data column is selected, a packaging method of [ minimum ] is clicked, and the system can automatically calculate the minimum value of the data column;
packaging by a maximum value method;
in the data management page, a certain data column is selected, a packaging method is clicked (maximum value) and the system can automatically calculate the minimum value of the data column;
packaging by a power method;
selecting a certain data, clicking the [ power ] packaging method, and automatically calculating the power result of the data by the system.
Packaging by a squaring method;
and selecting a certain data, clicking the packaging method, and automatically calculating the evolution result of the data by the system.
Packaging by a fitting method;
and selecting a certain row of data, generating a line graph by the system, packaging by a click (fitting) method, and displaying the fitted line graph by the system.
Packaging by an interpolation method;
selecting a certain line of data, generating a line graph by the system, clicking a certain point on the line to perform interpolation operation, packaging by a clicking (interpolation) method, inputting a value to be inserted, and displaying the interpolated line graph by the system.
New addition of
The information list interface can check the applied filing reservation information; clicking [ detail ] to check application detailed information and auditing conditions; inputting inquiry conditions, clicking and screening;
editing of
The user can edit and modify the imported reliability data, select a certain piece of reliability data in the page, and click the [ edit ] button to modify the piece of reliability data. The function is controlled by the right, only the data manager has the editing function, other people have no editing and modifying right, the operation record can be reserved in the log, and the system manager can view the log.
Deletion of
The user can delete the imported reliability data, select a certain piece of reliability data in the page, and delete the piece of reliability data by clicking a [ delete ] button. The function is controlled by the authority, only the data manager has the deleting function, other people have no deleting authority, the operation record can be reserved in the log, and the system manager can view the log.
(4) Dynamic modeling of data
The function of dynamic modeling (dynamic data table building) of data is supported.
Dynamic building table
A series of input boxes can appear under the query condition, and the existing table can be queried by clicking the query after inputting corresponding data. Clicking an 'add' button to enter an interface of an add table on a custom table list page:
Adding fields
Clicking the "Add column" button to add individual fields to the data sheet and saving after the operation is completed.
Editing and deleting field information
Selecting a field to be edited, performing editing operation by double clicking, selecting and clicking a deletion button if the field to be edited is required to be deleted, and clicking a storage button to store after the operation is completed.
(5) Data analysis and mining method
Mathematical operation analysis
Mathematical analysis includes data analysis from the simplest and most basic functions (e.g., mean, maximum, minimum, power, square, sine, cosine, etc.) to complex functions (e.g., interpolation, differentiation, integration, convolution). The mathematical operation is shown in fig. 5.
Statistical analysis of data
The data statistical analysis comprises descriptive statistical analysis and hypothesis testing analysis.
Descriptive statistical analysis includes maximizing, minimizing, median, summing, and common variances and standard deviations. Hypothesis testing includes single sample t-test, multiple sample t-test, variance chi-square test.
Envelope analysis
For a large amount of data with complex changes, besides the analysis by adopting methods such as extremum comparison, algorithm formula and the like, historical data of the data can be collected for envelope analysis, and especially for military products with high reliability and service life requirements, the development trend of the electrical characteristics of the products can be mastered, and the data can be used as evidence for analyzing the overall performance of the products and preventing hidden danger of the products.
The envelope analysis process comprises the steps of defining parameters participating in envelope analysis, defining parameter operation rules, boundary precision and the like, selecting according to the model concerned by a user and the product code number, generating an envelope analysis result table of the product, and automatically extracting the upper limit and the lower limit of the envelope by the user according to historical success data.
Regression analysis
Regression analysis is a method for determining the quantitative relationship of interdependence between two or more variables, and has wide application. Depending on the type of relationship between the independent and dependent variables, linear regression and nonlinear regression can be classified. Such regression analysis is called a unary regression analysis in which only one independent variable and one dependent variable are included in terms of the number of independent variables and dependent variables, and is called a multiple regression analysis if two or more independent variables are included in the regression analysis. The partial least square regression method is a novel multivariate statistical data analysis method, mainly researches the regression modeling of multiple independent variables by using a multi-dependent variable, and is particularly effective when the internal of each variable is highly linearly related, and the system adopts the partial least square method for regression analysis.
Neural network algorithm
Neural networks provide a relatively efficient way to solve complexity problems, and can easily solve problems with a large number of parameters, commonly used for classification and regression.
A neural network may be structurally divided into an input layer, an output layer, and an hidden layer. Each node of the input layer corresponds to an independent variable, and the nodes of the output layer correspond to a target variable, and a plurality of nodes can be provided. Between the input layer and the output layer is an hidden layer, and the number of hidden layers and the number of nodes in each layer determine the complexity of the neural network. Each neuron of the hidden layer is an independent unit with similar structure, which receives the data transmitted from the previous layer, inputs the weight of the data into the nonlinear function, and finally transmits the output result of the nonlinear function to the output layer.
(6) Visual display of data
The visual display of the engine reliability data is divided into a two-dimensional map data display function and a three-dimensional map data display function.
Two-dimensional map data presentation
The system realizes the display of the reliability data two-dimensional graph through the integrated report design tool FineReport. The support data field is associated with the graphic form, and when the format and the content of the two-dimensional graph need to be changed, the modification of the template can be quickly realized.
Setting is carried out through a design tool FineReport, and for the same data, various two-dimensional graph displays such as a histogram, a pie chart, a line graph and the like can be supported.
(7) Reliability index alarm function
The reliability index alarm function comprises two parts: reliability index definition and risk early warning tree.
Reliability index definition
The system provides a reliability index definition function, supports a user to define the names, data sources (calculation methods), alarm threshold values (target values), index categories and the like of reliability indexes (such as reliability, failure degree, failure rate, service life, average service life and the like), and provides a function of inquiring the indexes according to the category and index names.
Risk early warning tree
Through the risk early warning tree, early warning information of the reliability index of the engine can be checked. The system builds a risk early warning tree according to the level, the system carries out graphical early warning on the target condition according to indexes in the system, can display the target condition with different colors according to the early warning level, and can be unfolded/folded in a level manner according to the requirement.
(8) Algorithm plug and play support
In addition to the basic mathematical analysis algorithms and reliability algorithms that have been supported in current systems, the system needs to provide plug and play support for the algorithms, i.e., the user can conveniently use custom algorithms in the system. At present, python is the most common programming language for data analysis and mining, and can construct various reliability algorithms to meet business requirements, so that the system realizes the plug and play of the algorithms through the support of the Python language, and the system transmits the algorithm names and parameters to the Python for reliability calculation and returns the results. The Python algorithm support is shown in fig. 6.
In order to realize convenient call of the system to the Python algorithm, the system also needs to support the editing management function of the Python algorithm and parameters and return values thereof.
9) Data security design
In order to ensure data security, a security design is carried out on a reliability data analysis application tool:
the system provides login management, and logs the IP address, login time and login person;
the system carries out safety control on access, provides a user interface related to the authority of the user, and only presents a menu and a button which are consistent with the authority of the user;
the system sets the security of the data field, namely which data records can be accessed by the user;
the authority of the system administrator adopts 'three-member management', which accords with national security regulations.
In order to ensure the data security, when the data is imported, exported and modified, corresponding approval processes are required to be carried out, and related operations must be provided with audit logs to prohibit operations such as import, export and modification without approval.
And the related user initiates a task application for importing, exporting and modifying, submits the task application to a related leader for auditing, if the lead auditing is passed, flows to the related user for operation, if the auditing is not passed, the related user refuses to an application node, and resubmisses the application according to the refused opinion.
The specific design and function are shown in fig. 7-19.
Claims (6)
1. The utility model provides a solid rocket engine reliability data analysis excavates and application software instrument, falls into three levels of basic platform layer, data management layer and data application layer, its characterized in that:
the basic platform layer is a server layer and comprises an application server, a database server, a file server and an integrated interface, and provides platform functions of tree definition user management, authority setting, log management and parameter setting;
the data management layer is a database layer and provides data management functions of importing, exporting and editing for basic information of an engine, charging and internal heat insulation reliability data, spray pipe reliability data, shell and external heat insulation reliability data and reliability data of the whole engine and straight parts;
the data application layer is a user layer and is a visual tool and an operation interface which interact with a user and is used for including the reliability data application functions of data query, reliability data analysis, reliability data two-dimensional graph display and reliability data three-dimensional graph display;
the charge and inner insulation reliability data, the spray pipe reliability data, the shell and outer insulation reliability data and the engine whole machine and direct parts reliability data are divided into product data, process data and fault data according to life cycle and usage,
The product data are divided into engine design research and development data, production manufacturing data and test data, the engine design research and development data system is divided into engine basic data, design data, temporary technical data and calculation data, the basic data are divided into engine structure index data, engine performance index data, engine complete machine and part component main size data, engine performance parameter data, engine working environment data, engine matched data, part component replacement data, engine complete machine and part record data, data labels and whether excessive material generation special release data exist, the design class data are divided into engine drawing pattern data, engine design task data, technical condition data, research summary data, research and development transition evaluation data and characteristic analysis data, the temporary technical data are divided into technical problem processing data, temporary task work data, modification parameter data and modification production data, and the calculation class data are divided into conventional calculation data, simulation calculation class data and other calculation class data; the production and manufacturing data are divided into engine record data and process type data, wherein the engine record data are divided into part component measurement data, working procedure process record data and final assembly test record data, and the process type data are divided into process file data, process report data, process summary data, process analysis data and key process data; the test data are divided into engine development process test data, external field test data and other types of test data, the engine development process test data are divided into part and part assembly test scheme data, part and part assembly test record data, part and part assembly test result analysis data, complete machine test scheme data, complete machine test record data and complete machine test result analysis data, the external field test data are divided into external field flight test data and external field trimming test data, and the other types of test data are improvement measure verification test data;
The process data are divided into comprehensive engine guarantee data and health monitoring detection data, wherein the comprehensive engine guarantee data are divided into guarantee data, examination and review data, outsourcing data, material use data and scientific and technical result data, and the health monitoring detection data are divided into engine performance parameter extremum data, engine structure parameter extremum data, engine health monitoring data and engine nondestructive detection data;
the fault type data are divided into typical fault and analysis data and one-to-three data of the engine, wherein the typical fault and analysis data are divided into typical fault data of the engine, fault analysis data and product quality improvement data, and the one-to-three data are divided into one-to-three data of the whole engine, one-to-three data of an engine combustion chamber, one-to-three data of an engine nozzle, one-to-three data of an engine shell and one-to-three data of an engine safety ignition device.
2. The solid rocket engine reliability data analysis mining and application software tool of claim 1, wherein: the data general functions of the data management function and the data application function comprise data import, data export, data display, data query and retrieval, data analysis, addition, editing and deletion, wherein the data import comprises a data import template and a data import verification function; the data display comprises BOM tree display and list display functions; the data analysis is to analyze the packaged reliability data, and is divided into mean value method packaging, minimum value method packaging, maximum value method packaging, power method packaging, square method packaging, fitting method packaging and interpolation method packaging.
3. The solid rocket engine reliability data analysis mining and application software tool of claim 1, wherein: the reliability data analysis includes mathematical operation analysis, data statistics analysis, envelope analysis, regression analysis and neural network algorithms.
4. The solid rocket engine reliability data analysis mining and application software tool of claim 1, wherein: the data application layer also comprises a reliability index alarm function, wherein the reliability index alarm function is divided into a reliability index definition and a risk early warning tree.
5. The solid rocket engine reliability data analysis mining and application software tool of claim 1, wherein: the solid rocket engine reliability data analysis mining and application software tool also comprises an algorithm plug and play support, and the algorithm plug and play support has an editing management function on the Python algorithm and parameters and return values thereof.
6. The solid rocket engine reliability data analysis mining and application software tool of claim 1, wherein: the solid rocket engine reliability data analysis mining and application software tool also comprises data security management, wherein the data security management comprises login management, access security control, data domain security setting and three-member management adopted by system administrator authority.
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