CN111730882B - Analysis and tracing system and method for autoclave molding process data - Google Patents
Analysis and tracing system and method for autoclave molding process data Download PDFInfo
- Publication number
- CN111730882B CN111730882B CN202010605243.3A CN202010605243A CN111730882B CN 111730882 B CN111730882 B CN 111730882B CN 202010605243 A CN202010605243 A CN 202010605243A CN 111730882 B CN111730882 B CN 111730882B
- Authority
- CN
- China
- Prior art keywords
- data
- analysis
- server
- temperature
- workpiece
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C70/00—Shaping composites, i.e. plastics material comprising reinforcements, fillers or preformed parts, e.g. inserts
- B29C70/04—Shaping composites, i.e. plastics material comprising reinforcements, fillers or preformed parts, e.g. inserts comprising reinforcements only, e.g. self-reinforcing plastics
- B29C70/28—Shaping operations therefor
- B29C70/54—Component parts, details or accessories; Auxiliary operations, e.g. feeding or storage of prepregs or SMC after impregnation or during ageing
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C70/00—Shaping composites, i.e. plastics material comprising reinforcements, fillers or preformed parts, e.g. inserts
- B29C70/04—Shaping composites, i.e. plastics material comprising reinforcements, fillers or preformed parts, e.g. inserts comprising reinforcements only, e.g. self-reinforcing plastics
- B29C70/28—Shaping operations therefor
- B29C70/30—Shaping by lay-up, i.e. applying fibres, tape or broadsheet on a mould, former or core; Shaping by spray-up, i.e. spraying of fibres on a mould, former or core
- B29C70/34—Shaping by lay-up, i.e. applying fibres, tape or broadsheet on a mould, former or core; Shaping by spray-up, i.e. spraying of fibres on a mould, former or core and shaping or impregnating by compression, i.e. combined with compressing after the lay-up operation
- B29C70/342—Shaping by lay-up, i.e. applying fibres, tape or broadsheet on a mould, former or core; Shaping by spray-up, i.e. spraying of fibres on a mould, former or core and shaping or impregnating by compression, i.e. combined with compressing after the lay-up operation using isostatic pressure
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C70/00—Shaping composites, i.e. plastics material comprising reinforcements, fillers or preformed parts, e.g. inserts
- B29C70/04—Shaping composites, i.e. plastics material comprising reinforcements, fillers or preformed parts, e.g. inserts comprising reinforcements only, e.g. self-reinforcing plastics
- B29C70/28—Shaping operations therefor
- B29C70/40—Shaping or impregnating by compression not applied
- B29C70/42—Shaping or impregnating by compression not applied for producing articles of definite length, i.e. discrete articles
- B29C70/44—Shaping or impregnating by compression not applied for producing articles of definite length, i.e. discrete articles using isostatic pressure, e.g. pressure difference-moulding, vacuum bag-moulding, autoclave-moulding or expanding rubber-moulding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Composite Materials (AREA)
- Mechanical Engineering (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Factory Administration (AREA)
Abstract
The invention discloses an analysis and tracing system and method for autoclave molding process data. The analysis tracing method comprises the steps of importing autoclave curing molding data and data such as molded surface curvature and porosity of a workpiece into a data analysis server, analyzing the data into format data, and storing the format data on a database server; and then, analyzing according to point inspection parameters preset in the application server, an algorithm in the data analysis server and a big data mathematical statistic model to obtain a point inspection report and a big data analysis result. The method has the advantages of convenient analysis process, reduced analysis difficulty, ensured accuracy of analysis results, improved production efficiency, reduced production cost and good practical value.
Description
Technical Field
The invention relates to an analysis and tracing system and method for autoclave molding process data.
Background
The autoclave molding process is widely adopted in the manufacturing process of a plurality of large-scale bearing structural members in the fields of aviation and aerospace. Autoclave curing is the key to ensure the quality of autoclave molded parts. The technological principle is that after heating to certain temperature, the blank is pressurized to ensure the product to be compacted, and this can exhaust air and volatile matter to the maximum and avoid extruding excessive resin. In the process, the heating and pressurizing procedures need to be determined by measuring the change of the viscosity, dielectric constant or reaction heat of the resin in the curing process.
The existing autoclave mainly processes a workpiece according to preset heating and pressurizing programs, and simultaneously records all data related to the workpiece in the autoclave through temperature and pressure sensors. Because of the strict requirements of the aviation and aerospace fields on the force-bearing structural member, inspection personnel or technical personnel are required to perform manual calculation and analysis on curing data to judge whether the curing of the workpiece meets the requirements or not, thereby judging whether the workpiece is qualified or not. However, since the autoclave curing generally requires more than 5 hours, and one data is recorded every minute, the data recorded by only a single temperature sensor and pressure sensor may be more than 300, while a large part generally requires more than 5 temperature sensors and more than 2 pressure sensors, and thus the curing data amount of the part can reach about 3000. Because the data volume of the curing data is large, calculation and point inspection items are more, two different inspectors are generally needed for comparison and verification through manual calculation and analysis, according to different proficiency levels, the time of about 1-3 hours is generally needed for single person calculation, and the total time of about 2-6 hours is needed, meanwhile, in the practical process, the situation of calculation errors often exists, a workpiece without a curing molding data quality point inspection table cannot enter the next procedure, and the production efficiency and the production cost are greatly restricted through the current production mode.
The temperature requirements and the pressure requirements of different types of workpieces are different, so that the analysis items and the parameter models of different workpieces have different requirements, the labor cost for training inspection personnel or technicians is high, and different analysis items, theoretical values and analysis methods of different workpieces cannot be well mastered in time. The existing manual calculation mode has higher requirement on the personal calculation capability of inspectors, and the situations of manual calculation errors and tampering cannot be fundamentally and effectively avoided.
The solidified molding data is stored in an unstructured form, and the traceability and secondary applicability of the solidified molding data are low. The quality data such as the profile, the porosity and the like of the same workpiece cannot be associated with different curing and molding data of the workpiece in a convenient and rapid manner, but the quality data such as the profile, the porosity and the like of the workpiece in the actual production process is associated with the actual processing data in the curing and molding process of the workpiece greatly.
Therefore, a system for analyzing, tracing and applying the autoclave molding process data quality is needed.
Disclosure of Invention
In order to solve the existing problems, the invention provides an analysis and tracing system and method for autoclave molding process data, which analyze autoclave curing molding data based on calculation and software so as to ensure the accuracy of an analysis result and the traceability and secondary applicability of the curing molding data. In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides an analysis and tracing system for autoclave molding process data, which comprises an FTP server, a data analysis server, a database server, other quality systems or equipment interfaces, an application server, a data analysis server, an application operation terminal, an identity verification terminal and an interface server, wherein the servers and the equipment are connected through the Internet of things, and corresponding application software and special software are deployed on each server.
The autoclave curing molding data is automatically generated in an excel format or txt format in an appointed directory of autoclave upper computer software, an FTP server automatically acquires a curing program data file from the directory in real time through a deployed software monitoring program, renames the file, copies the file to the appointed directory of the server and transmits the file to a data analysis server, data such as the molded surface curvature of a workpiece and the porosity of the workpiece are transmitted to the data analysis server through other quality systems or equipment, and the data analysis server analyzes the data into formatted data according to the data formats of different files and different service type data and different service model rules and stores the formatted data in a database server.
The application operation terminal is an entrance of system users such as inspectors and the like, is a display terminal and an interaction terminal of the system, performs logic operation according to a preset parameter model through the application server, and generates a point inspection report by one key.
The click report information generated by one key comprises: the part name, part FO number, production job number, shelf number, referenced specification number, leading thermocouple number, lagging thermocouple number, maximum temperature of the part, maximum temperature of the pressure relief, and the like.
The identity verification terminal is a fingerprint authentication terminal, the database server stores the basic information and the identity information of the user, and the authorized user can enter the system only after logging in the system and comparing the fingerprint information input by the fingerprint authentication terminal, so that the uniqueness of the identity information of the inspector is ensured, and the system can automatically watermark the serial number of the inspector into a point inspection report according to the identity information.
The data analysis server can preset a big data mathematical statistics model, has the characteristics of machine learning to a certain degree, provides rich algorithm types including classification, clustering, association rules and the like, and specifically comprises Adaboost classification, Bagging regression and the like.
The application server and the interface server have a data interaction relationship, the application server feeds back the point inspection result of the solidified and molded data to the interface server in real time, and the fed-back data includes but is not limited to: the method comprises the following steps of manufacturing part name, manufacturing part number, manufacturing part FO number, curing molding data number, production operation number, curing molding data starting time and finishing time, whether a point inspection result meets requirements or not, and an adopted point inspection parameter model and the like. And the interface server feeds back the serial number of the submitted workpiece and the state information of the submitted workpiece to the application server.
Secondly, the invention provides a method for analyzing and tracing the autoclave molding process data by using the system, which comprises the following steps:
(1) the FTP server automatically captures unstructured autoclave curing molding data in an excel or txt form in real time, renames the autoclave curing molding data and sends the autoclave curing molding data to the analysis server, and the analysis server performs analysis and formatting processing after acquiring the data and stores corresponding data in the database server; and meanwhile, after formatted or unformatted data such as the molded surface curvature of the workpiece, the porosity of the workpiece and the like acquired by the server through other quality systems or equipment are analyzed, the data are sorted, cleaned and formatted according to a set rule and then are stored in a database server. The whole process from the generation of the curing molding data to the formatting process cannot be interfered by manpower, so that the non-tamper property of the data source is ensured.
After the system receives, parses, formats and stores autoclave curing molding data, the system interface displays the basic information of the data, including furnace batch number, start time, end time, part number, production job number, etc., and provides links to open and view detailed data.
(2) The process technician or other authorized operators generalize and arrange different types of parts, and establish different point inspection parameter models, wherein one point inspection parameter model corresponds to one specification, one point inspection parameter model corresponds to a plurality of detection items, the system automatically generates unique point inspection parameter model numbers, each number corresponds to one type of finished piece, and the detection items of the point inspection parameter model generally comprise: the temperature rise rate, the temperature drop rate, the abnormal thermocouple judgment, the lead and lag thermocouple judgment, the maximum and minimum tank pressure, the highest pressure relief temperature, the highest workpiece temperature, the heat preservation temperature range and the heat preservation duration, the maximum back pressure in the atmosphere ventilation stage and the like.
The point inspection parameter model comprises inspection terms and corresponding theoretical value preset values, including but not limited to (taking a temperature rise stage as an example): the number of the point inspection parameter model, the corresponding standard number, the number of the detection item, the last time of setting, the setting person, the upper limit value and the lower limit value of the temperature interval in the temperature rising stage, the fixed value of the time interval and the like.
The operator can edit the detection item and the theoretical value in the point detection parameter model respectively, and can add, delete or modify the detection item and modify the corresponding theoretical value. After the point inspection parameter model is set, corresponding examination and approval are carried out through a workflow arranged in the system, the point inspection parameter model can take effect after being examined and approved step by step according to different authorities, and the point inspection parameter model is updated and stored in the database server.
(3) The method comprises the steps that after a process technician or a designated operator enters a system through an application operation terminal, a point inspection parameter model corresponding to a workpiece is selected, a one-key is clicked to generate a report and submit the report to an inspector, the inspector inputs an inspection conclusion after checking the workpiece, the system prompts that identity verification is needed after the report is submitted, after the inspector enters fingerprint information through an identity verification terminal, the system automatically judges the identity of the inspector, and a point inspection report with the serial number of the inspector is generated. Meanwhile, the system supports the graphical display of the data analysis result.
For the structured curing molding data, the structured profile curvature and the porosity data of the workpiece, the difference of the data such as the front and back actual temperature, pressure and the like in the multiple processing of the same workpiece, the profile curvature of the workpiece and the porosity of the workpiece are analyzed and compared through a big data mathematical statistical model, for example: influence of the heating and cooling rates on the porosity of the workpiece; the influence of different actual values of the heat preservation temperature and different heat preservation time on the curvature of the molded surface of the workpiece; the effect of the difference in pressure on the porosity of the part. Therefore, the theoretical value range can be continuously optimized, and the optimal solution of the temperature, the pressure and the time in the workpiece processing can be obtained.
The invention has the beneficial effects that:
the system analyzes the autoclave curing molding data and compares the autoclave curing molding data with a preset parameter model, whether the process treatment of the workpiece meets the standard requirement in the hot press molding process is judged, a process data quality analysis check report can be generated in a one-key mode within 5 seconds, data interaction is carried out with other production systems, the workpiece curing molding check result is fed back in real time, the difficulty of autoclave molding process curing data analysis is reduced, compared with a manual calculation mode, the whole process does not need human participation, the production waiting time of 2-6 hours can be reduced, the production efficiency is greatly improved, the production cost is reduced, and meanwhile, the accuracy and the tamper resistance of the analysis result are guaranteed.
The system has higher system flexibility, can meet the requirements of different part specifications, can add, delete and modify parameter models, and can adjust corresponding theoretical values according to the requirements, thereby being greatly suitable for generating part reports of different part types.
The method of the invention converts all curing molding data into structured data stored in the database through the computer system, can completely track any change of process parameters, restores the real production process, and realizes the storage, tracing and application of the curing process data.
For the structured curing molding data, the molded surface curvature of the workpiece and the porosity data of the workpiece, the optimal solution of the theoretical value of the workpiece can be obtained by a craftsman through an analysis model based on big data and a full-sample statistical technology, and the technological parameters are conveniently and continuously optimized.
Drawings
FIG. 1 is a schematic diagram of the analysis and traceability system and method of the autoclave molding process data according to the present invention;
FIG. 2 is an exemplary diagram of a click-through report generated by a key in the system of the present invention;
FIG. 3 is a graph of temperature rise of various thermocouples used in analyzing autoclave process curing data for a # 2 stringer workpiece on the left side of a vertical fin, in accordance with the present invention;
FIG. 4 is a graph of the cooling curve for each thermocouple for analysis of autoclave process curing data for the left side 2# stringer workpiece of the vertical tail.
Detailed Description
The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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 invention. The specific embodiment is as follows:
example 1
The embodiment is an analysis system of traceing back of autoclave shaping technology data, as shown in fig. 1, the system includes FTP server (1), data analysis server (2), database server (3), other quality system or equipment interface (4), application server (5), data analysis server (6), application operation terminal (7), authentication terminal (8) and interface server (9), these servers and equipment pass through internet of things and connect, and corresponding application software and special software have all been deployed on each server, other quality system or equipment interface (4) include three coordinate profile measurement data interface, porosity ultrasonic scanning data interface, thickness measurement data interface etc..
The method comprises the following steps that autoclave curing molding data related to a workpiece and recorded by a thermocouple and a pressure sensor in an autoclave are automatically generated in an excel format or a txt format in an appointed directory of upper computer software of the autoclave, an FTP server (1) automatically obtains a curing program data file from the directory in real time through a deployed software monitoring program, renames the file, copies the file to the appointed directory of the server and transmits the file to a data analysis server (2), and the data analysis server (2) analyzes the file into formatted data according to data formats of different files and data of different service types and different service model rules and stores the formatted data into a database server (3); meanwhile, unformatted data such as the profile curvature of the workpiece, the porosity of the workpiece and the like are also transmitted to the data analysis server (2) through other quality systems or equipment interfaces (4), and are analyzed into formatted data through the data analysis server (2) and stored in the database server (3); and the formatted data of the curvature of the molded surface of the manufactured part, the porosity of the manufactured part and the like are directly transmitted to a database server (3) through other quality systems or equipment interfaces (4).
The application operation terminal (7) described in this embodiment is an entrance for system users such as inspectors, and is also a display terminal and an interaction terminal of the system, and performs logical operation according to a preset parameter model through the application server (5), and generates a point inspection report by one key. As shown in fig. 2, the information content of the spot check report includes: the part name, part FO number, production job number, shelf number, referenced specification number, leading thermocouple number, lagging thermocouple number, maximum temperature of the part, maximum temperature of the pressure relief, and the like.
The identity verification terminal (8) is a fingerprint authentication terminal, the database server (3) stores the basic information and the identity information of the user, and the authorized user can enter the system only after logging in the system and comparing the fingerprint information input by the fingerprint authentication terminal, so that the uniqueness of the identity information of the inspector is ensured, and the system automatically watermarks the serial number of the inspector in a check report according to the identity information.
The data analysis server (6) described in this embodiment can preset a big data mathematical statistics model, has a certain degree of machine learning characteristics, and provides rich algorithm types including classification, clustering, association rules, and the like, specifically Adaboost classification, Bagging regression, and the like.
The application server (5) and the interface server (9) have a data interaction relationship, and the application server (5) feeds back the spot inspection result of the cured and molded data to the interface server (9) in real time and feeds back the spot inspection result to other systems such as MES (manufacturing execution system) for production, manufacturing and regulation. The data fed back includes, but is not limited to: the method comprises the following steps of (1) manufacturing part name, manufacturing part number, manufacturing part FO number, curing molding data number, production operation number, curing molding data starting time and finishing time, whether a point inspection result meets requirements, an adopted point inspection parameter model and the like; the interface server (9) feeds back the submitted part number and the state information thereof to the application server (5).
Example 2
This example is a method for analyzing and tracing autoclave molding process data using the system described in example 1,
(1) the FTP server automatically captures unstructured autoclave curing molding data stored in an appointed directory of autoclave upper computer software in an excel or txt form in real time, renames the autoclave curing molding data and sends the autoclave curing molding data to the analysis server, and the analysis server performs analysis and formatting processing after acquiring the autoclave curing molding data and stores corresponding data in the database server; and meanwhile, after formatted or unformatted data such as the molded surface curvature of the workpiece, the porosity of the workpiece and the like acquired by the server through other quality systems or equipment are analyzed, the data are sorted, cleaned and formatted according to a set rule and then are stored in a database server. The whole process from the generation of the curing molding data to the formatting process cannot be interfered by manpower, so that the non-tamper property of the data source is ensured.
After the system receives, parses, formats and stores autoclave curing molding data, the system interface displays the basic information of the data, including furnace batch number, start time, end time, part number, production job number, etc., and provides links to open and view detailed data.
The curing molding data include, but are not limited to: autoclave curing molding data furnace batch number, part number, curing molding data number, production operation number, curing molding data start time and end time, operator, thermocouple number, pressure gauge number, timestamp number and corresponding thermoelectric even number value, timestamp number and corresponding pressure gauge value and the like.
The curvature of the molded surface of the product and the porosity of the product include but are not limited to: the number of the workpiece, the name of the workpiece, the number of the production operation, operators for different inspection steps of the workpiece, the number of a coordinate system adopted by the measurement of the workpiece, the coordinate and curvature data of the selected detection point, the coordinate and porosity data of the selected detection point and the like.
(2) The process technician or other authorized operators induct and sort different types of parts, and establish different point inspection parameter models, wherein one point inspection parameter model corresponds to one specification, one point inspection parameter model corresponds to a plurality of detection items, the system automatically generates unique point inspection parameter model numbers, each number corresponds to one type of finished piece, and the detection items of the point inspection parameter model generally comprise: the temperature rise rate, the temperature drop rate, the abnormal thermocouple judgment, the lead and lag thermocouple judgment, the maximum and minimum tank pressure, the highest pressure relief temperature, the highest workpiece temperature, the heat preservation temperature range and the heat preservation duration, the maximum back pressure in the atmosphere ventilation stage and the like.
The point inspection parameter model comprises inspection terms and corresponding theoretical value preset values, including but not limited to (taking a temperature rise stage as an example): the number of the point inspection parameter model, the corresponding standard number, the number of the detection item, the last time of setting, the setting person, the upper limit value and the lower limit value of the temperature interval in the temperature rising stage, the fixed value of the time interval and the like.
The operator can edit the detection item and the theoretical value in the point detection parameter model respectively, and can add, delete or modify the detection item and modify the corresponding theoretical value. After the point inspection parameter model is set, corresponding examination and approval are carried out through a workflow built in the system, the point inspection parameter model can take effect after being examined and approved step by step according to different authorities, and the point inspection parameter model is updated and stored in the database server.
(3) The method comprises the steps that after a process technician or a designated operator enters a system through an application operation terminal, a point inspection parameter model inspection item corresponding to a workpiece is selected for analysis, a one-key is clicked to generate a report and submit the report to an inspector, the inspector inputs an inspection conclusion after checking the product, the system prompts that identity verification is needed after the report is submitted, and after the inspector inputs fingerprint information through an identity verification terminal, the system automatically judges the identity of the inspector and generates a point inspection report with the serial number of the inspector. Meanwhile, the system supports the graphical display of the data analysis result. Wherein:
the lead-lag thermocouple judgment is that a user inputs parameters for judging the temperature range and the temperature rise or temperature drop stage of the lead-lag thermocouple into a computer system according to needs, then data of thermocouple records which are pre-embedded in a hot-pressing tank and used for recording the temperature rise and temperature drop sequence of different parts of a workpiece are analyzed and processed by the computer system to generate an actual temperature rise and temperature drop curve of the corresponding part of the workpiece, and then the user judges the lead-lag thermocouple according to the temperature rise and temperature drop curve.
The heating and cooling rates of the workpiece are calculated and analyzed as follows: analyzing data recorded by each thermocouple in the introduced pressure tank by inputting analysis parameters in a computer system in advance, calculating the temperature rise and decrease rate of the temperature measured by each thermocouple, counting the maximum rate and the minimum rate, comparing the maximum rate and the minimum rate with preset conditions meeting requirements, judging whether the temperature is qualified, and separately recording the unqualified result.
The method for calculating the temperature rising and reducing rate comprises the following steps: the temperature value of the last recording period of the thermocouple-the temperature value of the initial recording period of the thermocouple-the time length of calculating the cooling rate; and the calculated temperature rising and reducing rates are stopped until the temperature measured by the thermocouple reaches the limit of the temperature rising and reducing range which is input into the computer system in advance.
And the temperature and time of the workpiece are judged to be qualified or not by the computer system analyzing the temperature data recorded by each introduced thermocouple according to the temperature range and time of the workpiece input in advance, calculating the temperature keeping time of data maintenance in the set temperature range, and comparing the temperature keeping time with the preset time.
The highest pressure relief temperature of the part is judged to be a preset pressure interval value and a required temperature value of the part, and the computer system calculates whether the temperature recorded by each thermocouple when the pressure of the autoclave is smaller than the lower limit of the pressure interval value is smaller than the required temperature value or not and gives a corresponding conclusion. The judgment of the highest pressure relief temperature of the workpiece further comprises the judgment of the reduction of the pressure value of the autoclave caused by the temperature reduction accompanied in the pressure relief process.
And judging the highest temperature of the workpiece as the highest recorded temperature value recorded by each thermocouple by the computer system to be compared with the preset highest theoretical temperature value, and judging whether the temperature is qualified or not.
And the maximum and minimum autoclave pressure judgment is that the computer system analyzes the related data recorded by the imported thermocouple and the pressure sensor to obtain the maximum and minimum autoclave pressures of the autoclave pressure value from the stage of starting temperature rise to finishing temperature drop, and the maximum and minimum autoclave pressures are compared with a preset theoretical autoclave pressure to judge whether the autoclave pressure is qualified.
Judging whether the maximum back pressure of the atmosphere introducing stage meets the requirement of the vacuum pressure of the workpiece in the curing process; specifically, a computer system analyzes relevant data recorded by a thermocouple and a pressure sensor to obtain a maximum vacuum pressure value and a minimum vacuum pressure value of a workpiece from the stage of starting temperature rise to the stage of finishing temperature drop, and compares the maximum vacuum pressure value and the minimum vacuum pressure value with a preset theoretical vacuum pressure value to judge whether the workpiece is qualified.
And judging the maximum back pressure of the workpiece in the cooling stage by a computer system according to the preset temperature interval of the cooling stage and the required theoretical range of the back pressure, and calculating and judging whether the back pressure range of the pressure sensor when the autoclave enters the cooling stage is in the required theoretical range of the pressure value or not by the computer system, and giving a corresponding conclusion.
For the structured solidification molding data, the structured profile curvature and the porosity data of the workpiece, the difference of the data such as the front and back actual temperature, pressure and the like in multiple processing of the same workpiece, the profile curvature of the workpiece and the porosity of the workpiece are analyzed and compared through a big data mathematical statistic model, for example: the influence of the heating and cooling rates on the porosity of the workpiece; the influence of different actual values of the heat preservation temperature and different heat preservation time on the curvature of the molded surface of the workpiece; the effect of the difference in pressure on the porosity of the part. Therefore, the theoretical value range can be continuously optimized, and the optimal solution of the temperature, the pressure and the time in the workpiece processing can be obtained.
Example 3
In this embodiment, the autoclave process curing data of the left 2# stringer of the vertical tail is analyzed by using the autoclave molding process data analysis and tracing system and method described in embodiments 1 and 2, and a one-key generation report part is selected for display and explanation. 6 thermocouples (numbered T2, T3, T7, T25, T26 and T27), 1 pressure sensor (numbered P1) and 2 vacuum pressure sensors (numbered VL7 and VL16) are shared in the curing and forming process of the autoclave process, and the recording period of each sensor is 1 minute; the specific analysis is as follows:
1) and (3) parameter model configuration:
the detection items and theoretical values are:
the temperature rise range is as follows: temperature rise calculation interval constant value of 55-174 ℃: the temperature rise rate is 0.5-3 ℃/Min within 10 minutes;
the cooling range is as follows: 174-60 ℃, and the cooling calculation interval constant value is as follows: the temperature reduction rate ranges from 0.5 to 3 ℃/Min within 10 minutes;
range of the holding temperature: 174-186 ℃ and the requirement of heat preservation duration: 120-390 minutes;
temperature range of lead-lag thermocouple: 60-174 ℃;
judging the maximum pressure relief temperature of the workpiece: the pressure range is 600 KPa-640 KPa, and the temperature value of the minute value reaching 600KPa for the first time is less than or equal to 60;
judging the highest temperature of the workpiece: less than or equal to 186;
judging the maximum and minimum tank pressure of the autoclave: temperature rise stage start temperature: 55 ℃, end temperature of cooling stage: 60 ℃, passing between predetermined maximum and predetermined minimum values for each pressure sensor value within this range, predetermined minimum: 600, predetermined maximum 650;
and (3) judging the maximum back pressure in the atmospheric stage: temperature rise stage start temperature: 55 ℃, end temperature of cooling stage: the values of the vacuum pressure sensors within this range between a predetermined maximum and a predetermined minimum are acceptable at 60 ℃, the predetermined minimum: 0, predetermined maximum: 34;
maximum backpressure in a cooling stage: end temperature of cooling stage: the maximum back pressure in the interval is less than or equal to 136kpa at the temperature of 60 ℃.
2) Judging a lead thermocouple and a lag thermocouple:
firstly, inputting the parameters for judging the temperature range (60-174 ℃) and the temperature rise or temperature fall stage of the leading and lagging thermocouples into a parameter model of a computer system, and generating an actual temperature rise and temperature fall curve of the corresponding part of the workpiece through analysis and processing of the computer system, as shown in fig. 3 and 4, the computer automatically judges the temperature rise and temperature fall curve to judge that the leading thermocouples are T26 and T2, and the lagging thermocouples are T25, T7, T3 and T27.
3) And (3) calculating the heating and cooling rates of the workpiece:
calculating the temperature rise rate: the temperature rise range is 55-174 ℃, and the temperature rise is divided into three stages, namely 55-150 ℃, 150-165 ℃ and 165-174 ℃. The temperature rise rate is calculated by taking the time length of rate calculation as 10 minutes as an example, and calculating the data recorded by the thermocouple T2, wherein the temperature recorded by the thermocouple T2 is 55.6 ℃ in the first minute of more than 55 ℃, the temperature recorded by the thermocouple T3556 in the 11 th minute is 72.9 ℃, and the temperature rise rate corresponding to the thermocouple T2 in the 10 minutes is as follows: (72.9 ℃ C. -55.6 ℃ C.)/10 ═ 1.73, and so on, and the calculation of the rate of temperature rise is cut off until the temperature recorded by the thermocouple is greater than 174 ℃. The specific record for each thermocouple is shown in table 1:
TABLE 1 temperature data recorded by each thermocouple for increasing and decreasing the temperature rate are as follows
4) And (3) judging the heat preservation temperature and time of the workpiece:
calculating the heat preservation temperature and time: the range of the heat preservation temperature is 174-186 ℃. The specific calculation method comprises the following steps: for example, the data shows that where thermocouple T2 recorded a temperature of 156 minutes at a time greater than 174 ℃ and a time less than 174 ℃ recorded a time of 329 minutes, thermocouple T2 corresponds to a soak time of: 329- "156" for 173 minutes, and so on. The holding temperature is continuously 5 first temperatures higher than 174 ℃ as the starting temperature, and is continuously 5 first temperatures lower than 174 ℃ as the cutoff temperature. The specific record for each thermocouple is shown in table 2:
TABLE 2 thermal insulation of each thermocouple recorded data as follows
5) Judging the maximum pressure relief temperature of the workpiece:
calculating the highest pressure relief temperature: the pressure recorded by the pressure sensor P1 is higher than 600KPa and normally between 600KPa and 640KPa, i.e. the pressure range is 600 KPa-640 KPa. The method for calculating the highest pressure relief temperature comprises the following steps: the data shows that the running time when the recorded pressure is less than 600KPa is 415 th minute of autoclave curing treatment, and the temperature of the thermocouple at the corresponding time is checked. For example, thermocouple T2 corresponds to a temperature of: 32 ℃ and so on. The maximum temperature at the time of pressure release is determined based on this, and is the maximum temperature among T2, T3, T7, T25, T26, and T27. The specific record for each thermocouple is shown in table 3:
TABLE 3 thermal insulation of the recorded data of each thermocouple as follows
6) Judging the highest temperature of the workpiece:
calculating the maximum temperature by computer system: the highest temperature in the recorded data of thermocouples such as T2, T3, T7, T25, T26, T27 was calculated. For example, thermocouple T2 has a maximum temperature of 180.3 deg.C, and so on. The specific record for each thermocouple is shown in table 4:
TABLE 4 thermal insulation of the recorded data of each thermocouple is as follows
7) Judging the maximum and minimum tank pressure of the autoclave:
calculating the maximum minimum tank pressure: the temperature rise starting temperature is 55 ℃, the temperature drop finishing temperature is 60 ℃, namely the maximum and minimum values of the pressure recorded by the P1 in the process that the T2, the T3, the T7, the T25, the T26 and the T27 are all greater than or equal to 55 ℃ after the temperature rise and are in the temperature drop stage until the temperature drop is less than 60 ℃ are calculated. Specific records of P1 are shown in table 5:
TABLE 5 maximum minimum tank pressure conditions reported by P1 as follows
8) And (3) judging the maximum back pressure in the atmospheric stage:
calculating the maximum back pressure in the atmospheric stage: the temperature rise starting temperature is 55 ℃, the temperature drop ending temperature is 60 ℃, namely, the temperature of T2, T3, T7, T25, T26 and T27 is calculated to be more than or equal to 55 ℃ after temperature rise, and the temperature drop stage is carried out until the maximum and minimum values of the pressure recorded by VL7 and VL16 are less than 60 ℃. Specific records of VL7, VL16 thermocouples are as in table 6:
TABLE 6 determination of maximum backpressure during venting phase as follows
9) Judging the maximum back pressure in the cooling stage:
maximum backpressure in a cooling stage: the system judges that the initial temperature of temperature reduction is 174 ℃ and the end temperature of temperature reduction is 60 ℃, namely, the maximum and minimum values of the pressure recorded by VL7 and VL16 in the process of 60 ℃ are obtained after the temperature reduction of T2, T3, T7, T25, T26 and T27 is started. Specific records of VL7, VL16 thermocouples are as in table 7:
TABLE 7 maximum backpressure determination at the cool down stage is as follows
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive. Furthermore, it should be understood that although the present specification describes embodiments, this does not include only one embodiment, and such description is for clarity only, and those skilled in the art should be able to make the specification as a whole, and the embodiments may be appropriately combined to form other embodiments understood by those skilled in the art.
Claims (7)
1. The utility model provides an analysis system of traceing back of autoclave shaping technology data which characterized in that: the system comprises an FTP server (1), a data analysis server (2), a database server (3), other quality systems or equipment interfaces (4), an application server (5), a data analysis server (6) and an application operation terminal (7) which are connected through the Internet of things;
the FTP server (1) is used for acquiring autoclave curing molding data and transmitting the autoclave curing molding data to the data analysis server (2);
the other quality system or equipment interface (4) is used for acquiring relevant data of the profile curvature and the porosity of the workpiece and transmitting the data to the data analysis server (2) or the database server (3); the device comprises a three-coordinate profile measurement data interface, a porosity ultrasonic scanning data interface and a thickness measurement data interface;
the data analysis server (2) is used for analyzing the received data into formatted data and storing the formatted data into the database server (3);
a point inspection parameter model is preset in the application server (5) and is used for analyzing the tank pressing curing molding data stored in the database server (3) and generating a point inspection report; the analysis items comprise a heating rate, a cooling rate, abnormal thermocouple judgment, leading and lagging thermocouple judgment, maximum and minimum tank pressure, a pressure relief maximum temperature, a workpiece maximum temperature, a heat preservation temperature range, heat preservation duration and maximum backpressure in an atmosphere introducing stage;
the data analysis server (6) is used for providing the algorithm type for the application server (5);
the application operation terminal (7) is used for man-machine interaction and operating the whole system;
the method for analyzing and tracing by adopting the analysis tracing system comprises the following steps:
1) data acquisition, processing and storage: acquiring autoclave curing molding data from a specified catalog of autoclave upper computer software automatically in real time through an FTP server (1) monitoring program, and acquiring related data of profile curvature and porosity of a workpiece through other quality systems or equipment interfaces (4); the data are analyzed and formatted by the data analysis server (2) and then stored in the database server (3);
2) presetting a point inspection model: counting the types of the workpieces, presetting a point inspection parameter model in an application server (5), and determining an analysis item;
3) point inspection and big data analysis: the application server (5) performs operation analysis on the formatted data stored in the database server (3) by adopting the algorithm type provided by the data analysis server (6) according to a preset point inspection model, and generates a point inspection report; meanwhile, carrying out big data analysis on the profile curvature, the porosity and other related data of the workpiece, and storing the analysis result in a database server (3);
the point inspection comprises leading and lagging thermocouple judgment, heating and cooling rate calculation analysis of a workpiece, temperature and time judgment of the workpiece, highest pressure relief temperature judgment of the workpiece, highest temperature judgment of the workpiece, maximum and minimum tank pressure judgment of an autoclave, maximum backpressure judgment of an atmosphere introducing stage and maximum backpressure judgment of a cooling stage of the workpiece;
the temperature rise and drop rate of the workpiece is calculated and analyzed as follows: analyzing data recorded by each thermocouple in an imported pressure tank by inputting analysis parameters in a computer system in advance, calculating the temperature rise and reduction rate of the temperature measured by each thermocouple, counting the maximum rate and the minimum rate, comparing the maximum rate and the minimum rate with preset conditions meeting the requirements, judging whether the temperature is qualified, and separately recording unqualified results;
the method for calculating the temperature rise and decrease rate comprises the following steps: the temperature value of the thermocouple in the last recording period is calculated; the calculated temperature rising and reducing rates are cut off until the temperature measured by the thermocouple reaches the limit of the temperature rising and reducing range which is input into the computer system in advance;
and the big data analysis is to analyze and compare the difference of the front and back actual temperature and pressure data of the same workpiece in multiple processing, the curvature of the molded surface of the workpiece and the porosity of the workpiece through a big data mathematical statistical model to obtain the optimal solution of the temperature, the pressure and the time in the processing of the workpiece.
2. The analysis traceability system of autoclave molding process data as set forth in claim 1, wherein: the system further comprises an identity authentication terminal (8) and an interface server (9), wherein the identity authentication terminal (8) is used for authorizing and authenticating user information of the system, the interface server (9) is in interactive connection with the application server (5), the serial number and the state information of the workpiece are fed back to the application server, and meanwhile, the point inspection result of the curing molding data is obtained from the application server (5).
3. The analysis traceability system of autoclave molding process data as set forth in claim 1, wherein: the autoclave curing molding data is curing program data automatically generated in a specified catalog of autoclave upper computer software in an excel format or a txt format.
4. The analysis traceability system of autoclave molding process data as set forth in claim 1, wherein: and the data analysis server (2) analyzes the data into formatted data according to the received data format and the service type and the service model rule.
5. The analysis traceability system of autoclave molding process data as set forth in claim 1, wherein: the data analysis server (6) is preset with a big data mathematical statistical model and has the characteristic of machine learning; the types of algorithms provided include classification, clustering and association rules.
6. The analysis traceability system of autoclave molding process data as set forth in claim 2, wherein: the identity verification terminal (8) is a fingerprint authentication terminal, and the authorized user information is stored on the database server (3).
7. The analysis and traceability system of the autoclave molding process data as claimed in claim 2, wherein: the point inspection result obtained by the interface server (9) from the application server (5) comprises a product name, a product number, a product FO number, a curing molding data number, a production job number, curing molding data start time and end time, whether the point inspection result meets the requirements or not and an adopted point inspection parameter model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010605243.3A CN111730882B (en) | 2020-06-29 | 2020-06-29 | Analysis and tracing system and method for autoclave molding process data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010605243.3A CN111730882B (en) | 2020-06-29 | 2020-06-29 | Analysis and tracing system and method for autoclave molding process data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111730882A CN111730882A (en) | 2020-10-02 |
| CN111730882B true CN111730882B (en) | 2022-06-14 |
Family
ID=72652168
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010605243.3A Active CN111730882B (en) | 2020-06-29 | 2020-06-29 | Analysis and tracing system and method for autoclave molding process data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111730882B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114648305A (en) * | 2022-03-25 | 2022-06-21 | 成都飞机工业（集团）有限责任公司 | System and method for correlating part manufacturing process data |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014012106A2 (en) * | 2012-07-13 | 2014-01-16 | Sourcefire, Inc. | Method and apparatus for retroactively detecting malicious or otherwise undesirable software as well as clean software through intelligent rescanning |
| CN104732022A (en) * | 2015-03-18 | 2015-06-24 | 南京航空航天大学 | Prediction method for composite microwave curing temperature field |
| CN105760555A (en) * | 2016-04-08 | 2016-07-13 | 浙江中烟工业有限责任公司 | Filter stick forming process quality analyzing and tracing system |
| CN109101632A (en) * | 2018-08-15 | 2018-12-28 | 中国人民解放军海军航空大学 | Product quality abnormal data retrospective analysis method based on manufacture big data |
| CN111299893A (en) * | 2019-11-25 | 2020-06-19 | 陕西海晨电子科技有限公司 | System for be used for gas pipeline crater quality analysis and trace back |
-
2020
- 2020-06-29 CN CN202010605243.3A patent/CN111730882B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014012106A2 (en) * | 2012-07-13 | 2014-01-16 | Sourcefire, Inc. | Method and apparatus for retroactively detecting malicious or otherwise undesirable software as well as clean software through intelligent rescanning |
| CN104732022A (en) * | 2015-03-18 | 2015-06-24 | 南京航空航天大学 | Prediction method for composite microwave curing temperature field |
| CN105760555A (en) * | 2016-04-08 | 2016-07-13 | 浙江中烟工业有限责任公司 | Filter stick forming process quality analyzing and tracing system |
| CN109101632A (en) * | 2018-08-15 | 2018-12-28 | 中国人民解放军海军航空大学 | Product quality abnormal data retrospective analysis method based on manufacture big data |
| CN111299893A (en) * | 2019-11-25 | 2020-06-19 | 陕西海晨电子科技有限公司 | System for be used for gas pipeline crater quality analysis and trace back |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111730882A (en) | 2020-10-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111730882B (en) | Analysis and tracing system and method for autoclave molding process data | |
| CN106872509A (en) | A kind of injection-molded item quality on-line detecting device and method based on infrared imaging | |
| CN110196265B (en) | Method for evaluating distribution stability of cut tobacco in cigarette branches in batch based on distribution probability | |
| CN111242464A (en) | Ceramic bathroom quality management method based on SPC | |
| CN117008557B (en) | Production control method and system for blending type interpenetrating network thermoplastic elastomer | |
| CN116228028B (en) | Application performance evaluation method and system for plastic bags | |
| CN111950577A (en) | Point inspection method and device | |
| CN115983721A (en) | Cable production quality data management system based on Internet of things big data | |
| CN117575624A (en) | Conductive adhesive traceability management system | |
| CN111428329A (en) | Model-based machine learning system | |
| CN109918704B (en) | Die forging die life prediction method based on finite element simulation | |
| CN117193178B (en) | Production process optimization control method and system for glass fiber composite board | |
| CN111795721A (en) | Real-time online detection method for autoclave curing data | |
| CN107340758A (en) | A kind of reliability of technology towards multistage manufacturing process is assessed and control method | |
| CN111445132B (en) | Data processing method, data processing system and computer storage medium | |
| CN116503025A (en) | Business work order flow processing method based on workflow engine | |
| CN115438033A (en) | Digital twin operation and maintenance data quality inspection method | |
| CN109878046B (en) | Injection molding production optimization method | |
| CN107480388A (en) | A kind of companding shaping method of predetermined design sized launches medicine | |
| CN117911412B (en) | Dimension detection method and system for caterpillar track section for engineering machinery | |
| CN104731955A (en) | Methods and systems for diagnostic standard establishment and intelligent diagnosis of wind generation set oil monitoring | |
| CN111798252B (en) | Forging quality traceability system | |
| CN116974788B (en) | Data processing method for analyzing wafer defects in real time | |
| CN113218880B (en) | Food material detection method of refrigerator, refrigerator and storage medium | |
| CN116821403B (en) | Intelligent operation and maintenance method and system for factory equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |