CN113779330A - Ultrasonic detection process parameter intelligent calculation system based on similarity measurement - Google Patents
Ultrasonic detection process parameter intelligent calculation system based on similarity measurement Download PDFInfo
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Abstract
The invention discloses an ultrasonic detection process parameter intelligent computing system based on similarity measurement, which comprises a process database, a server and a cloud end web application; the system comprises a process database, a server and a cloud end web application, wherein the process database is used for storing the existing ultrasonic detection process parameters, the server is used for analyzing and processing the existing ultrasonic detection process parameters, a machine learning model and the cloud end web application are constructed, and an intelligent process parameter calculation model can be obtained by training the machine learning model; and then the intelligent calculation model is transplanted to the web application, and a user can obtain the specific detection parameter process card of the workpiece by inputting necessary workpiece information and detection standards to the web application. The invention reduces the operation difficulty of ultrasonic detection, enables an inexperienced inspector to accurately carry out ultrasonic detection on the workpiece, and improves the reliability of ultrasonic detection of the workpiece; the web application of the invention also has the capability of secondary learning, and can optimize the intelligent calculation model at regular time and improve the accuracy of the specific detection parameters of the workpiece.
Description
Technical Field
The invention belongs to the technical field of deep learning and ultrasonic detection, and particularly relates to an ultrasonic detection process parameter intelligent calculation system based on similarity measurement.
Background
The ultrasonic detection is carried out by utilizing an ultrasonic technology, and is one of five conventional nondestructive detection methods; non-destructive inspection is a means of inspecting the surface and internal quality of a part under inspection without damaging the working condition of the workpiece or raw material.
The principle of ultrasonic detection is as follows: the transmission loss of the ultrasonic wave in the solid is small, the detection depth is large, and the ultrasonic wave can generate phenomena of reflection, refraction and the like on a heterogeneous interface, and particularly can not pass through a gas-solid interface. If there are defects (gas in the defect) or inclusions such as pores, cracks, or delamination in the metal, the ultrasonic waves are totally or partially reflected when they propagate to the interface between the metal and the defect. The reflected ultrasonic waves are received by the probe and processed by a circuit inside the instrument, and waveforms with different heights and certain intervals are displayed on a fluorescent screen of the instrument. The depth, position and shape of the defect in the workpiece can be judged according to the variation characteristics of the waveform.
In the practical application process, before ultrasonic detection is carried out, specific detection process parameters need to be determined according to workpiece information and detection standards, and then the workpiece can be detected according to the process parameters; the related domestic ultrasonic detection standards at present are JB/T4730.3, GB/T11345-1989, CB/T3559-2011 and the like, JB/T4730.3 is a relatively comprehensive standard, the latter two standards are welding seam detection standards, and other detection standards such as steel plates, casting and forging pieces and the like are also provided, so that a user can perform corresponding query according to needs; however, specific detection process parameters of the workpiece can be determined only through a large number of specific experiments, and for inspectors with insufficient experience, the workpiece is difficult to be accurately subjected to ultrasonic detection, so that the reliability of the ultrasonic detection result of the workpiece is low. Therefore, there is a need for an intelligent computing system that can determine specific inspection process parameters and generate a process card based on workpiece information and inspection criteria.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides an ultrasonic detection process parameter intelligent computing system based on similarity measurement.
In order to achieve the purpose, the invention adopts the technical scheme that:
an ultrasonic detection process parameter intelligent computing system based on similarity measurement comprises a process database, a cloud end web application and a server; the process database is used for storing the existing ultrasonic detection process parameters; the server is used for analyzing the ultrasonic detection process parameters, constructing a machine learning model and cloud end web application, and training the machine learning model to obtain an intelligent process parameter calculation model; and transplanting the intelligent calculation model of the process parameters to the cloud end web application, inputting necessary workpiece information and detection standards into the cloud end web application by a user, carrying out similarity measurement on data input by the user and the process parameters stored in a process database by a server, selecting a process card suitable for the detection requirement from the process database according to a measurement result, applying the process card to the cloud end web application, and providing the process card to the user through the cloud end web application.
Specifically, the ultrasonic detection process parameters stored in the process database include a plurality of types of workpiece information, detection standards corresponding to the various types of workpiece information, and specific detection parameter process cards.
Specifically, the training data of the machine learning model for training are ultrasonic detection process parameters stored in a process database; the method for training the machine learning model comprises one or more of weighted correlation calculation, data visualization analysis, a K-means clustering algorithm, a density-based clustering algorithm or an LDA algorithm.
Specifically, the cloud-side web application can be constructed through an existing web framework, and the existing web framework comprises a springboot framework or a flash framework.
Specifically, the cloud end web application is provided with a plurality of operation pages for human-computer interaction between a user and the server; the operation page at least comprises a user parameter input page, a process card return page and a user feedback page;
the user parameter input page is used for a user to input workpiece information and detection standards;
the process card return page is used for outputting the specific detection parameter process card corresponding to the workpiece;
the user feedback page is used for the user to feed back reasonable process parameters, and the user can submit the reasonable process parameters to a process database through the user feedback page in the process of ultrasonic detection to update the process parameters in the process database.
Specifically, the cloud-side web application has a secondary learning capability, and performs secondary learning training at regular time by using the updated process parameters in the process database to correct the process parameter intelligent calculation model and improve the accuracy of the specific detection parameter process card.
Specifically, the workpiece information at least comprises the material of the workpiece, the specification of a welding part, the form of a groove, a welding method, the width of a weld joint and postweld heat treatment; the detection standard at least comprises a detection technology grade, a detection temperature, a detection proportion and a qualified grade.
Compared with the prior art, the invention has the beneficial effects that: (1) according to the invention, the existing ultrasonic detection process parameters are collected and stored through the process database, the machine learning model and the cloud end web application are constructed through the server, the machine learning model is trained by utilizing the existing ultrasonic detection process parameters to obtain the intelligent process parameter calculation model, the calculation model is transplanted to the cloud end web application, and a user based on the cloud end web application can use a browser at any position with a network and input the information and detection standard of a workpiece to be detected, so that a specific detection parameter process card of the workpiece can be generated, the operation difficulty of ultrasonic detection is reduced, so that an inexperienced inspector can accurately perform ultrasonic detection on the workpiece, and the reliability of ultrasonic detection of the workpiece is improved; (2) the cloud web application is provided with a user feedback page, a user can submit existing reasonable technological parameters to a technological database through the user feedback page in the process of ultrasonic detection, the technological parameters in the technological database are updated, and the cloud web application can perform secondary learning training at regular time by using the updated technological parameters in the technological database so as to correct the technological parameter intelligent calculation model and improve the accuracy of a specific detection parameter technological card, so that the accuracy of ultrasonic detection of a workpiece is improved.
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FIG. 1 is a basic architecture diagram of an ultrasonic testing process parameter intelligent computing system based on similarity measurement according to the present invention.
Fig. 2 is a detailed architecture diagram of an ultrasonic testing process parameter intelligent computing system based on similarity measurement according to the present invention.
Fig. 3 is a flowchart of a method implemented by an intelligent calculation system for ultrasonic testing process parameters based on similarity measurement according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. 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.
As shown in fig. 1 to 3, the present embodiment provides an intelligent computing system for ultrasonic testing process parameters based on similarity measurement, which includes a process database, a cloud-end web application, and a server; the process database is used for storing the existing ultrasonic detection process parameters; the server is used for analyzing the ultrasonic detection process parameters, constructing a machine learning model and cloud end web application, and training the machine learning model to obtain an intelligent process parameter calculation model; and transplanting the intelligent calculation model of the process parameters to the cloud end web application, inputting necessary workpiece information and detection standards into the cloud end web application by a user, carrying out similarity measurement on data input by the user and the process parameters stored in a process database by a server, selecting a process card suitable for the detection requirement from the process database according to a measurement result, applying the process card to the cloud end web application, and providing the process card to the user through the cloud end web application.
Specifically, the ultrasonic detection process parameters stored in the process database include a plurality of kinds of workpiece information, detection standards corresponding to the various kinds of workpiece information, and specific detection parameter process cards;
further, the process database may be constructed to collect existing ultrasonic inspection process parameters via a web crawler or other methods.
Specifically, the training data of the machine learning model for training are ultrasonic detection process parameters stored in a process database; the method for training the machine learning model comprises one or more of weighted correlation calculation, data visualization analysis, a K-means clustering algorithm, a density-based clustering algorithm or an LDA algorithm.
In this embodiment, ultrasonic detection process parameter calculation of a weld is taken as an example, weighting correlation calculation is adopted, parameters such as material sound velocity (10, 10% difference each, similarity minus 1), attenuation (1), machining process (8), heat treatment process (2), grain size (6), groove angle (8, 5% difference each, similarity minus 1), workpiece thickness (8, 5% difference each, similarity minus 2) and the like of the weld are respectively given different weights, data in brackets is weight of corresponding parameters, a user inputs new weld parameters, weighting summation is carried out on parameters related to the weld input by the user and parameter similarity in a process library, namely correlation calculation is carried out, a plurality of process cards with the maximum correlation coefficient are taken and provided for the user, the user can directly adopt the process cards and can also make some modifications and be applied to a detection system for detection, meanwhile, the process cards modified by the user can be stored in the process card library, and the original data of the process card library is enriched.
Further, the ultrasonic detection parameters of the model need to be adjusted after the machine learning model is constructed; before training the machine learning model, data cleaning and feature preprocessing are required to be carried out on ultrasonic detection process parameters collected in the process database; the characteristic pretreatment specifically comprises the following steps: manually marking specific detection process parameters corresponding to each workpiece information in a process database; after workpiece information and detection standards are input into the machine learning model, the machine learning model can identify manually marked feature information (specific detection process parameters corresponding to workpieces) according to the input workpiece information and the detection standards; and after the training is finished, the model is required to be optimized.
Specifically, the cloud-side web application can be constructed through an existing web framework, and a corresponding html page (basic operation page) is established for the cloud-side web application, wherein the existing web framework comprises a spring boot framework or a flash framework.
Further, the operation page at least comprises a user parameter input page, a process card return page and a user feedback page;
the user parameter input page is used for a user to input workpiece information and detection standards;
the process card return page is used for outputting the specific detection parameter process card corresponding to the workpiece;
the user feedback page is used for the user to feed back reasonable process parameters, and the user can submit the reasonable process parameters to a process database through the user feedback page in the process of carrying out ultrasonic detection and update the process parameters in the process database;
when a user inputs reasonable workpiece information and detection standards on a user parameter input page and submits the workpiece information and the detection standards to the cloud end web application, the cloud end web application extracts data input by the user, calls a trained process parameter intelligent calculation model, inputs the extracted data into the model, and returns the generated process card to the page through the process card according to a calculation result of the model to be displayed for the user to refer to.
Specifically, the cloud web application has a secondary learning capability, and performs secondary learning training at regular time by using the updated process parameters in the process database to correct the process parameter intelligent calculation model and improve the accuracy of the specific detection parameter process card;
further, during the process of ultrasonic detection, the user may fill in the process card on the user feedback page and submit it to the web application, and the web application inputs the process card into the process database after verifying that it is valid.
Specifically, the workpiece information at least comprises the material of the workpiece, the specification of a welding part, the form of a groove, a welding method, the width of a weld joint and postweld heat treatment; the detection standard at least comprises a detection technology grade, a detection temperature, a detection proportion and a qualified grade.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. An ultrasonic detection process parameter intelligent computing system based on similarity measurement is characterized by comprising a process database, a cloud end web application and a server; the process database is used for storing the existing ultrasonic detection process parameters; the server is used for analyzing the ultrasonic detection process parameters, constructing a machine learning model and cloud end web application, and training the machine learning model to obtain an intelligent process parameter calculation model; and transplanting the intelligent calculation model of the process parameters to the cloud end web application, inputting necessary workpiece information and detection standards into the cloud end web application by a user, carrying out similarity measurement on data input by the user and the process parameters stored in a process database by a server, selecting a process card suitable for the detection requirement from the process database according to a measurement result, applying the process card to the cloud end web application, and providing the process card to the user through the cloud end web application.
2. The intelligent calculation system for ultrasonic testing process parameters based on similarity measurement according to claim 1, wherein the ultrasonic testing process parameters stored in the process database comprise a plurality of workpiece information, testing standards corresponding to the various workpiece information and specific testing parameter process cards.
3. The intelligent computing system for ultrasonic testing process parameters based on similarity measurement according to claim 1, wherein the training data for training the machine learning model is ultrasonic testing process parameters stored in a process database; the method for training the machine learning model comprises one or more of weighted correlation calculation, data visualization analysis, a K-means clustering algorithm, a density-based clustering algorithm or an LDA algorithm.
4. The intelligent computing system for ultrasonic detection process parameters based on similarity measurement according to claim 1, wherein the cloud-end web application can be constructed by an existing web framework, and the existing web framework comprises a springboot framework or a flash framework.
5. The intelligent computing system for ultrasonic detection process parameters based on similarity measurement according to claim 1, wherein the cloud-end web application is provided with a plurality of operation pages for human-computer interaction between a user and a server; the operation page at least comprises a user parameter input page, a process card return page and a user feedback page;
the user parameter input page is used for a user to input workpiece information and detection standards;
the process card return page is used for outputting the specific detection parameter process card corresponding to the workpiece;
the user feedback page is used for the user to feed back reasonable process parameters, and the user can submit the reasonable process parameters to a process database through the user feedback page in the process of ultrasonic detection to update the process parameters in the process database.
6. The ultrasonic testing process parameter intelligent computing system based on similarity measurement as claimed in claim 5, wherein the cloud web application has a secondary learning capability, and the cloud web application performs secondary learning training at regular time by using the process parameters updated in the process database to modify the process parameter intelligent computing model and improve the accuracy of the specific testing parameter process card.
7. The intelligent calculation system for ultrasonic detection process parameters based on similarity measurement according to claim 1, wherein the workpiece information at least comprises the material of the workpiece, the specification of the welding part, the form of a groove, the welding method, the width of a weld joint and the post-welding heat treatment; the detection standard at least comprises a detection technology grade, a detection temperature, a detection proportion and a qualified grade.
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