CN116223224B - Method for detecting influence of curing agent on mechanical properties of product based on image processing - Google Patents
Method for detecting influence of curing agent on mechanical properties of product based on image processing Download PDFInfo
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Abstract
The invention relates to the technical field of curing effect detection of curing agents, in particular to a method for detecting the influence of the curing agents on the mechanical properties of products based on image processing, which comprises the following steps: preparing a plurality of groups of brittle insulating casting material fluid for standby; preparing a plurality of vessel containers; sequentially pouring an equal amount of brittle insulating castable fluid corresponding to the content of the anhydride curing agent into a corresponding vessel container, standing and waiting for the castable to solidify; forming molding casting blanks after the brittle insulating casting material fluid in each vessel container is completely shaped, and sequentially taking out each molding casting blank; forming detection samples, and sequentially detecting each detection sample; and obtaining the limit load resistance value corresponding to the batch detection samples. In the invention, an ultrasonic scanning imaging three-dimensional graph of internal characteristic distribution is also carried out on a detection sample prepared by a test, and the mechanical property of the model can be quantized rapidly and objectively by means of finite element analysis and parameter processing in three-dimensional software.
Description
Technical Field
The invention relates to the technical field of curing effect detection of curing agents, in particular to a detection method for realizing the influence of the curing agents on the mechanical properties of products based on image processing.
Background
The curing agent is a substance which can convert a soluble and fusible high molecular compound with a linear structure into an insoluble and infusible body structure, wherein the anhydride epoxy resin curing agent is an important variety with larger use amount and wider application in the curing agent, and can generate gas with pungent smell during curing; meanwhile, because the moisture absorption and decarbonation reaction are carried out, the anhydride in the curing agent absorbs the moisture in the air and reacts to generate free acid, so that the crosslinking density and the electrical property of the cured product are affected; the decarbonation reaction releases carbon dioxide and tends to form voids inside the cured product.
When anhydride epoxy resin curing agents are added into the castable, the situation that pores exist in the product formed after the castable of the power transmission electrical equipment is poured can be caused, if the number of the pores is too large, the normal functions of the similar castable power transmission electrical equipment can be affected, and even the serious situation can lead to the occurrence of power utilization accidents, wherein the performance of the ceramic insulator is obviously affected. Therefore, before the casting manufacturing of power transmission and transformation equipment (especially ceramic insulator products), the current adding proportion of the curing agent needs to be strictly controlled, and meanwhile, the curing effect and different influences on the products of the tested insulator products after the curing agents with different contents are added need to be detected.
At present, when the insulator casting product added with the curing agent is detected, the characteristics of surface appearance quality, hardness and the like are mainly detected to be used as indexes for reflecting the curing effect of the curing agent, but the mode of detecting the cured insulator casting product by utilizing surface observation and hardness test can not relatively objectively reflect the influence of the curing agent on the actual curing effect thereof, and the whole detection data has certain unilaterality.
Therefore, the invention develops a method for detecting the curing effect of the curing agent in the insulator casting by utilizing the detection of a plurality of parameters of the insulator casting test block cured by the curing agent, so as to better solve the problem that the detection mode for the curing effect of the curing agent in the insulator casting in the prior art is insufficient.
Disclosure of Invention
The invention aims to solve one of the technical problems, and adopts the following technical scheme: the method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing comprises the following steps:
s1: preparing a plurality of groups of brittle insulating casting material fluids for standby, wherein the content of an anhydride curing agent in each group of brittle insulating casting material fluids is used as a single variable, and the content of the anhydride curing agent in each group of brittle insulating casting material fluids is different;
The brittle insulating casting material fluid is a fluid material for preparing insulators, the content matching ratio of the rest components is controlled unchanged when the brittle insulating casting material fluid of each group is configured, the content of the curing agent is adjusted and changed, and the content of the curing agent in each group of brittle insulating casting material fluid is sequentially set as a%, b%, c%, d and e% according to the weight ratio;
s2: preparing a plurality of vessel containers;
s3: sequentially pouring an equal amount of brittle insulating castable fluid corresponding to the content of the anhydride curing agent into a corresponding vessel container, standing and waiting for the castable to solidify;
s4: forming molding casting blanks after the brittle insulating casting material fluid in each vessel container is completely shaped, and sequentially taking out each molding casting blank;
s5: cutting and grinding two end parts of each molded casting blank to form detection samples with the same size, and sequentially detecting each detection sample;
s6: acquiring external surface high-definition images of all detection samples to be detected, respectively expanding the external surface high-definition images to generate corresponding external surface high-definition expanded images, and analyzing to obtain external surface pore distribution conditions corresponding to all the detection samples;
S7: acquiring an ultrasonic scanning imaging three-dimensional image of the interior of each detection sample by utilizing high-frequency ultrasonic reflection, and reconstructing a sample reconstruction three-dimensional model identical to each ultrasonic scanning imaging three-dimensional image in modeling software according to each acquired ultrasonic scanning imaging three-dimensional image; wherein, the inside of the sample reconstruction three-dimensional model contains all theoretical mechanical parameters of the brittle material;
s8: and sequentially obtaining the maximum simulated anti-load value and the usable matching degree of the reconstructed three-dimensional model of each sample, and calculating to obtain the limit anti-load value corresponding to the batch detection samples.
In any of the above schemes, preferably, the specific steps of sequentially obtaining the maximum value of the simulated anti-load of the three-dimensional model reconstructed by each sample, simulating the available matching degree and calculating the limit anti-load value corresponding to the batch detection samples are as follows:
analyzing to obtain the pore distribution condition inside the reconstructed three-dimensional model of each sample and obtain the corresponding sample model porosity;
sequentially performing mechanical property simulation test on the three-dimensional model reconstructed by each sample, and respectively obtaining simulation anti-load maximum values corresponding to the detection samples under different curing agent contents;
carrying out real load record test on each detection sample of small batches corresponding to different curing agent contents in sequence, and obtaining the simulation available matching degree of the corresponding detection sample under the condition of different curing agent addition amounts;
The simulation available matching degree is led into calculation and is applicable to the detection of the limit load resistance of the same type of batch detection samples;
and obtaining the limit anti-load value corresponding to the batch detection samples by using the obtained simulation anti-load maximum value multiplied by the simulation available matching degree of the batch detection samples.
In any of the above-described aspects, it is preferable that each vessel container is a ring-column-shaped container, and the shape of the molded casting blank molded by the vessel container is a hollow column-shaped structure penetrating through the center.
In any of the above schemes, preferably, S6 further includes the following steps: and acquiring high-definition images of the inner surfaces of the center through cavities of the molded casting blanks, sequentially expanding the high-definition images to generate corresponding high-definition expanded images of the inner surfaces, and respectively analyzing to obtain the pore distribution conditions of the inner surfaces corresponding to the detection samples.
In any of the above schemes, preferably, the specific steps of sequentially performing the mechanical property simulation test on the reconstructed three-dimensional model of each sample include:
a1: the method comprises the steps of performing discretization on the characteristics inside a sample reconstruction three-dimensional model into a plurality of unit characteristics with the same size by utilizing finite element analysis;
a2: according to the analysis of the reconstructed three-dimensional model, the number of pore unit features and the pore position distribution are obtained, the overall transparency of the reconstructed three-dimensional model of the sample is improved, the color of the unit features representing the pores is deepened, and the distribution display of the pore unit features is realized;
A3: carrying out self-adaptive incremental loading on the sample reconstruction three-dimensional model in a single axis direction under boundary constraint conditions and load loading, realizing gradual failure of each unit feature, and simultaneously recording a loading load value corresponding to each unit feature failure;
a4: judging whether the three-dimensional model of the sample reconstruction still has bearing capacity or not after the current unit characteristics fail, and recording the total value of the current loading load when the three-dimensional model of the sample reconstruction does not have bearing capacity after all the unit characteristics fail, so as to obtain the maximum value of the simulation anti-loading of the current detection sample.
In any of the above schemes, preferably, the method of adaptive incremental loading is as follows: automatically adjusting load increment according to the preset material unit characteristic failure of the reconstructed three-dimensional model, and realizing that each loading guarantees that one unit characteristic fails to be destroyed by utilizing the maximum stress destruction criterion; and carrying out rigidity degradation treatment and unit feature hiding treatment on the failure destroyed unit features to obtain statistics of the number of the undelayed unit features, and continuously reloading through unbalanced iteration until all the unit features of the whole three-dimensional model lose bearing capacity.
In any of the above schemes, preferably, in step S6, the specific steps of obtaining the external surface high-definition images of each detection sample to be detected and respectively developing the external surface high-definition images to generate corresponding external surface high-definition developed images, and analyzing to obtain the external surface pore distribution condition corresponding to each detection sample include:
The image is unfolded at high definition on the outer surface to realize image bottom layer processing and background purification; the edge feature marking of the target image can be performed in advance in the processes of image bottom layer processing and background purifying processing, and then the image is subjected to binarization processing, so that the edge and the feature in the image can be more accurately identified by a later algorithm;
when each pore in the external surface high definition expanded image has depth and a non-straight hole, the pore appears to have isolated noise points and internal chroma spots on the picture;
further processing the image by using a mathematical morphology method, performing expansion operation on the binary image with the background removed, performing corrosion operation, and eliminating chromaticity spots in the pore image after multiple processing;
meanwhile, in order to eliminate isolated noise points in the image, the image is subjected to corrosion operation and then expansion operation by using open operation in mathematical morphology, and after multiple processing, the isolated noise points in the image are eliminated;
perfecting according to the edge feature marks of the target image, and calculating and detecting by using a gradient edge detection algorithm to obtain the edge contour of each accurate pore target feature;
And solving the area of each pore target characteristic according to the pore edge profile, and further obtaining the pore area ratio on the high-definition unfolded image of the outer surface, namely the pore ratio of the outer surface of the detection sample.
In any of the above schemes, preferably, the specific steps of obtaining the high-definition images of the inner surface of the central through cavity of each molded casting blank, sequentially expanding the high-definition images to generate corresponding high-definition expanded images of the inner surface, and respectively analyzing and obtaining the pore distribution condition of the inner surface corresponding to each detection sample include:
the image is developed in a high definition mode on the inner surface to realize image bottom layer processing and background purification; the edge feature marking of the target image can be performed in advance in the processes of image bottom layer processing and background purifying processing, and then the image is subjected to binarization processing, so that the edge and the feature in the image can be more accurately identified by a later algorithm;
in addition, when the bottom layer processing is carried out, the image noise reduction, denoising, enhancement and restoration are carried out, so that the identification degree of the image is improved;
when the picture is noise reduced, the noise in the signal is removed while the main characteristics of the original signal are kept as much as possible;
when noise is removed, a mode of median filtering and wiener filtering is adopted to overcome the problem of blurring caused by a linear filter to an image, and good edge characteristics are maintained while particle noise is effectively removed; meanwhile, the mean square error between the actual output obtained by multiplying the input signal by the response and the expected output is minimum;
The method comprises the steps of accurately positioning the target features before extracting the features, and carrying out position normalization operation on the target features, so that the extracted target pore features do not change along with the position and rotation angle changes of other objects in an image plane;
the size, the position and the gray level information of the image can be better known through feature extraction and description of the image processed at the bottom layer during image segmentation, the edge of the target object can be better modified, and each pore part is segmented, so that the accuracy of the extracted features of the target can be enhanced;
when each pore in the inner surface high definition expanded image has depth and a non-straight hole, the pore appears to have isolated noise points and internal chroma spots on the picture;
further processing the image by using a mathematical morphology method, performing expansion operation on the binary image with the background removed, performing corrosion operation, and eliminating chromaticity spots in the pore image after multiple processing;
meanwhile, in order to eliminate isolated noise points in the image, the image is subjected to corrosion operation and then expansion operation by using open operation in mathematical morphology, and after multiple processing, the isolated noise points in the image are eliminated;
Perfecting according to the edge feature marks of the target image, and calculating and detecting by using a gradient edge detection algorithm to obtain the edge contour of each accurate pore target feature;
and solving the area of each pore target characteristic according to the pore edge profile, and further obtaining the pore area occupation ratio on the high-definition unfolded image of the inner surface, namely the pore occupation ratio of the inner surface of the detection sample.
In any of the above schemes, preferably, the specific steps of sequentially performing real load record test on each test sample of small batches corresponding to different curing agent contents and obtaining the simulation available matching degree of the corresponding test sample under the condition of different curing agent addition amounts include:
placing all detection samples with the same curing agent content on a hydraulic pressure detector test platform one by one, wherein a high-precision load sensor is arranged on the hydraulic pressure detector test platform; the number of detection tests of the same curing agent content is 100 or more; the content gradient of the curing agent is at least 5 different content gradients, namely the number of detection samples of each curing agent content value is at least 100, and the total number of detection samples is more than or equal to 500;
Starting a hydraulic pressure detector and enabling a pressure disc of the hydraulic pressure detector to slowly realize unidirectional load loading, wherein in the loading process, the load is controlled to be gradually pressurized to a corresponding load value according to a number sequence of the loading load value corresponding to each unit characteristic failure obtained by recording in the step A3;
gradually observing the change of a load display value in signal connection with the high-precision load sensor, and simultaneously recording the front-view state change of the detection sample in the whole load pressurization process by a high-definition camera until the current detection test block is pressed to be completely invalid;
when the unidirectional load loading value reaches the loading load value corresponding to each unit feature failure obtained in the simulation process, keeping the current load unchanged and shooting and recording a high-definition side image of the current detection test block;
observing the morphological change of the appearance of the current detection sample compared with the appearance of the sample after the last loading when the corresponding loading load is applied by analyzing and processing the high-definition side images obtained by each shooting;
selecting a high-definition side image with morphological change in a detection sample, finding out a loading load value corresponding to the high-definition side image as an available value for accurately simulating an actual failure load, recording the number of the available values and obtaining the simulation matching degree of the current detection sample;
Repeating the steps to sequentially obtain the simulation matching degree of a plurality of other detection samples in the same batch;
the available matching degree of batch detection samples under the condition of the current curing agent content is obtained after the obtained simulation matching degrees are weighted and averaged;
and repeating the steps to obtain the available matching degree of the detection samples in the corresponding batch under the condition of the content of the rest curing agents.
Compared with the prior art, the invention has the following beneficial effects:
1. the detection method adopts a small sample batch detection mode to count the mechanical load resistance value of the sample prepared by the fluid material (brittle insulating castable fluid) of the insulator obtained when different curing agents are added, can be effectively applied to the rapid detection of large batches of like products, utilizes the early operation to acquire image data and model parameters in the detection process, can effectively ensure the detection efficiency, simultaneously avoids the tedious step of detecting the products one by one, can relatively objectively and relatively accurately reflect the performance of the whole same batch of products through the pre-arranged small sample test, and effectively realizes the programmed operation of product detection.
2. According to the invention, the preparation of samples is respectively carried out according to the proportion of the mixture ratio content of a plurality of common curing agents in the mixture ratio production of the insulator material, and the image acquisition of the inner surface and the outer surface is respectively carried out according to the prepared samples under the content state of each curing agent so as to achieve the purposes of calculating the surface pore distribution condition and indirectly reflecting the surface roughness; the surface quality of the insulator product in the similar formula state after production can be effectively reflected by analyzing the inner surface and the outer surface of the sample, so that the subsequent surface treatment process is convenient to arrange, and the aim of effectively improving the appearance quality of the product is fulfilled.
3. According to the invention, an ultrasonic scanning imaging three-dimensional graph of internal characteristic distribution is carried out on a detection sample prepared by a test, and meanwhile, a three-dimensional reconstruction is carried out on the detection sample to obtain a model, and the mechanical property of the model can be rapidly and objectively quantized by means of finite element analysis and parameter processing in three-dimensional software, so that the load resistance simulation result of the sample model can be effectively obtained on the premise of guaranteeing that a curing agent is used as a single variable, and the simulation result can be effectively evaluated by a small batch of actual tests of the sample, so that the real applicable available matching degree is obtained, and the available matching degree is convenient to be applied to mass production detection.
4. In order to ensure the accuracy of analysis results of actual surface features of a sample, the invention adopts a comprehensive mode of utilizing pre-edge analysis marks, median filtering and post-wiener filtering to ensure the quality and effect of pore feature analysis in the image during image processing, ensures the matching degree of the analysis results and the actual features, effectively reflects the surface quality of the prepared sample, is convenient for appointing an external surface process treatment plan of a subsequent product according to a detection result, and improves the rationality and the high efficiency of the whole product process treatment mode.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or features are generally identified by like reference numerals throughout the drawings. In the drawings, the elements or components are not necessarily drawn to scale.
FIG. 1 is a schematic flow chart of the present invention.
FIG. 2 is a flowchart of the steps of sequentially obtaining the maximum simulated load resistance value and the usable matching degree of the reconstructed three-dimensional model of each sample and calculating the ultimate load resistance value corresponding to the batch detection samples in the invention.
FIG. 3 is a flow chart of the mechanical property simulation test of each sample reconstructed three-dimensional model in sequence.
Detailed Description
Embodiments of the technical scheme of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and thus are merely examples, and are not intended to limit the scope of the present invention. The specific structure of the invention is shown in fig. 1-3.
Example 1: the method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing comprises the following steps:
S1: preparing a plurality of groups of brittle insulating casting material fluids for standby, wherein the content of an anhydride curing agent in each group of brittle insulating casting material fluids is used as a single variable, and the content of the anhydride curing agent in each group of brittle insulating casting material fluids is different;
the brittle insulating casting material fluid is a fluid material for preparing insulators, the content matching ratio of the rest components is controlled unchanged when the brittle insulating casting material fluid of each group is configured, the content of the curing agent is adjusted and changed, and the content of the curing agent in each group of brittle insulating casting material fluid is sequentially set as a%, b%, c%, d and e% according to the weight ratio;
the corresponding molded casting blank is prepared by selecting at least five groups of different curing agent content states of the current insulator product, wherein a%, b%, c%, d% and e% respectively represent the content proportion of a plurality of curing agents commonly used in the current insulator product, the corresponding values of a%, b%, c%, d% and e% are selected according to different product types, different comparison blanks are prepared by adopting the different curing agent content proportion modes, the influence of the curing agent on the mechanical property of the product can be better and more objectively reflected, and the whole detection result is more objective.
S2: preparing a plurality of vessel containers;
during use, each vessel container can be numbered, so that the corresponding experiment group can be identified conveniently, and the condition of confusion in the operation process is avoided.
S3: sequentially pouring an equal amount of brittle insulating castable fluid corresponding to the content of the anhydride curing agent into a corresponding vessel container, standing and waiting for the castable to solidify;
s4: forming molding casting blanks after the brittle insulating casting material fluid in each vessel container is completely shaped, and sequentially taking out each molding casting blank;
s5: cutting and grinding two end parts of each molded casting blank to form detection samples with the same size, and sequentially detecting each detection sample;
the purpose of carrying out end grinding treatment on each prepared molded casting blank is to prepare each molded casting blank into a sample with consistent external dimensions, so that the influence of other factors on the post-detection test result can be reduced as much as possible.
S6: acquiring external surface high-definition images of all detection samples to be detected, respectively expanding the external surface high-definition images to generate corresponding external surface high-definition expanded images, and analyzing to obtain external surface pore distribution conditions corresponding to all the detection samples;
The method has the advantages that the outer surface high-definition unfolding image is acquired, so that the outer surface of a sample product can be conveniently analyzed and detected in the later period, the surface quality of the prepared sample can be effectively reacted, the outer surface process treatment plan of the subsequent product can be conveniently designated according to the detection result, and the rationality and the high efficiency of the whole product process treatment mode are improved.
S7: acquiring an ultrasonic scanning imaging three-dimensional image of the interior of each detection sample by utilizing high-frequency ultrasonic reflection, and reconstructing a sample reconstruction three-dimensional model identical to each ultrasonic scanning imaging three-dimensional image in modeling software according to each acquired ultrasonic scanning imaging three-dimensional image; wherein, the inside of the sample reconstruction three-dimensional model contains all theoretical mechanical parameters of the brittle material;
according to the parameter result of the ultrasonic scanning imaging three-dimensional map, a sample can be obtained, and the reconstructed three-dimensional model adopts parameterized modeling to obtain the matching of the internal characteristics reflected by the ultrasonic scanning imaging three-dimensional map; meanwhile, material mechanical parameters or theoretical mechanical parameters of corresponding samples obtained by corresponding actual tests are set in a material list in the three-dimensional modeling analysis software, so that the later mechanical property simulation test is facilitated;
s8: and sequentially obtaining the maximum simulated anti-load value and the usable matching degree of the reconstructed three-dimensional model of each sample, and calculating to obtain the limit anti-load value corresponding to the batch detection samples.
In any of the above schemes, preferably, the specific steps of sequentially obtaining the maximum value of the simulated anti-load of the three-dimensional model reconstructed by each sample, simulating the available matching degree and calculating the limit anti-load value corresponding to the batch detection samples are as follows:
analyzing to obtain the pore distribution condition inside the reconstructed three-dimensional model of each sample and obtain the corresponding sample model porosity;
the sample model porosity of each set of samples can be used to provide the required parameters for subsequent simulation testing.
Sequentially performing mechanical property simulation test on the three-dimensional model reconstructed by each sample, and respectively obtaining simulation anti-load maximum values corresponding to the detection samples under different curing agent contents;
according to the simulation test result, the simulation anti-load maximum value can be obtained more accurately, and the obtained simulation anti-load maximum value also needs subsequent coefficient verification to obtain an available result which can be applied with more objective accuracy.
Carrying out real load record test on each detection sample of small batches corresponding to different curing agent contents in sequence, and obtaining the simulation available matching degree of the corresponding detection sample under the condition of different curing agent addition amounts;
the simulation available matching degree is led into calculation and is applicable to the detection of the limit load resistance of the same type of batch detection samples;
The result of simulating the available matching degree can be obtained by carrying out the real load record test, so that the available result can be obtained after the simulation test can be directly carried out during the subsequent actual detection.
And obtaining the limit anti-load value corresponding to the batch detection samples by using the obtained simulation anti-load maximum value multiplied by the simulation available matching degree of the batch detection samples.
The simulation load resistance maximum value is obtained through the mechanical property simulation test, the simulation available matching degree is obtained through the real load recording test, the result approaching to the real limit load resistance value can be obtained after the simulation load resistance maximum value and the real load recording test are multiplied, the error is in the allowable range, the error is regarded as the available limit load resistance value, therefore, the accurate mechanical property detection result can be obtained only by carrying out simple scanning on the product in the preamble and leading in a model for computer analysis when detecting a large quantity of products, the analysis and detection can be carried out on the batch products in different curing agent content states, the product detection efficiency is effectively improved, the products can be rapidly scanned one by one in practical application, the mechanical property of each product can be rapidly analyzed and obtained according to the actual distribution situation of the internal pores of the products after the scanning, and the defect caused by the probability spot check in the traditional detection result is overcome.
In any of the above-described aspects, it is preferable that each vessel container is a ring-column-shaped container, and the shape of the molded casting blank molded by the vessel container is a hollow column-shaped structure penetrating through the center.
In any of the above schemes, preferably, S6 further includes the following steps: and acquiring high-definition images of the inner surfaces of the center through cavities of the molded casting blanks, sequentially expanding the high-definition images to generate corresponding high-definition expanded images of the inner surfaces, and respectively analyzing to obtain the pore distribution conditions of the inner surfaces corresponding to the detection samples.
The water sample is prepared into a hollow columnar structure, a columnar annular sample structure can be prepared, the central inner surface of the inner ring can be realized by adopting a columnar annular detection sample, the detection range of the sample surface can be increased by detecting the inner surface and the outer surface of the center, and the pore distribution condition of the obtained product in the surface state can be better synthesized; the inner surface high-definition unfolding image is acquired, so that the inner surface of a sample product can be conveniently analyzed and detected in the later period, the surface quality of the prepared sample can be effectively reacted, the outer surface process treatment plan of the subsequent product can be conveniently designated according to the detection result, and the rationality and the high efficiency of the whole product process treatment mode are improved.
In any of the above schemes, preferably, the specific steps of sequentially performing the mechanical property simulation test on the reconstructed three-dimensional model of each sample include:
a1: the method comprises the steps of performing discretization on the characteristics inside a sample reconstruction three-dimensional model into a plurality of unit characteristics with the same size by utilizing finite element analysis;
a2: according to the analysis of the reconstructed three-dimensional model, the number of pore unit features and the pore position distribution are obtained, the overall transparency of the reconstructed three-dimensional model of the sample is improved, the color of the unit features representing the pores is deepened, and the distribution display of the pore unit features is realized;
the visual effect can be enhanced after the color of the unit characteristic representing the pore in the reconstructed three-dimensional model is deepened, the distribution condition of the internal pore characteristic is effectively observed through the model, and meanwhile, the collapse and failure process of the internal unit characteristic of the model on the display can be conveniently observed in the subsequent load loading process.
A3: carrying out self-adaptive incremental loading on the sample reconstruction three-dimensional model in a single axis direction under boundary constraint conditions and load loading, realizing gradual failure of each unit feature, and simultaneously recording a loading load value corresponding to each unit feature failure;
the self-adaptive incremental loading method comprises the following steps: automatically adjusting load increment according to the preset material unit characteristic failure of the reconstructed three-dimensional model, and realizing that each loading guarantees that one unit characteristic fails to be destroyed by utilizing the maximum stress destruction criterion; and carrying out rigidity degradation treatment and unit feature hiding treatment on the failure destroyed unit features to obtain statistics of the number of the undelayed unit features, and continuously reloading through unbalanced iteration until all the unit features of the whole three-dimensional model lose bearing capacity.
The process of real simulation model material failure can be achieved through a self-adaptive incremental loading mode, and the simulation load-resistant maximum value of the current sample can be obtained objectively.
A4: judging whether the three-dimensional model of the sample reconstruction still has bearing capacity or not after the current unit characteristics fail, and recording the total value of the current loading load when the three-dimensional model of the sample reconstruction does not have bearing capacity after all the unit characteristics fail, so as to obtain the maximum value of the simulation anti-loading of the current detection sample.
The method for verifying whether the whole model is completely pressurized and failed is to detect whether the load capacity of the three-dimensional model reconstructed by the sample is still standard, namely, when the whole model does not have the load capacity, the whole model can be considered to be completely failed, and the corresponding loading load value is the maximum value of the simulated anti-load which can be borne by the model under the simulated load state.
Example 2: compared with example 1, the method also comprises the following characteristics: in step S6, the specific steps of obtaining the external surface high-definition image of each detection sample to be detected and respectively developing the external surface high-definition image to generate a corresponding external surface high-definition developed image, and analyzing to obtain the external surface pore distribution condition corresponding to each detection sample include:
The image is unfolded at high definition on the outer surface to realize image bottom layer processing and background purification; the edge feature marking of the target image can be performed in advance in the processes of image bottom layer processing and background purifying processing, and then the image is subjected to binarization processing, so that the edge and the feature in the image can be more accurately identified by a later algorithm;
the method comprises the steps of accurately positioning the target features before extracting the features, and carrying out position normalization operation on the target features, so that the extracted target pore features do not change along with the position and rotation angle changes of other objects in an image plane;
the size, the position and the gray level information of the image can be better known through feature extraction and description of the image processed at the bottom layer during image segmentation, the edge of the target object can be better modified, and each pore part is segmented, so that the accuracy of the extracted features of the target can be enhanced;
when each pore in the external surface high definition expanded image has depth and a non-straight hole, the pore appears to have isolated noise points and internal chroma spots on the picture;
further processing the image by using a mathematical morphology method, performing expansion operation on the binary image with the background removed, performing corrosion operation, and eliminating chromaticity spots in the pore image after multiple processing;
Meanwhile, in order to eliminate isolated noise points in the image, the image is subjected to corrosion operation and then expansion operation by using open operation in mathematical morphology, and after multiple processing, the isolated noise points in the image are eliminated;
perfecting according to the edge feature marks of the target image, and calculating and detecting by using a gradient edge detection algorithm to obtain the edge contour of each accurate pore target feature;
and solving the area of each pore target characteristic according to the pore edge profile, and further obtaining the pore area ratio on the high-definition unfolded image of the outer surface, namely the pore ratio of the outer surface of the detection sample.
In any of the above schemes, preferably, in the process of obtaining the distribution condition of the pores on the outer surface corresponding to each detection sample through the analysis, the process of performing the bottom layer treatment comprises the steps of picture noise reduction, denoising, enhancement and restoration, so that the recognition degree of the image is improved;
when the picture is noise reduced, the noise in the signal is removed while the main characteristics of the original signal are kept as much as possible;
when noise is removed, a mode of median filtering and wiener filtering is adopted to overcome the problem of blurring caused by a linear filter to an image, and good edge characteristics are maintained while particle noise is effectively removed; meanwhile, the mean square error between the actual output obtained by multiplying the input signal by the response and the expected output is minimum, and specifically, the following formula is adopted:
;
Wherein,,an estimation function representing an original image, H (u, v) representing a degradation function, H T (u, v) represents a conjugate degenerate function, |H (u, v) | 2 =H T (u,v)×H(u,v);S n (u, v) represents the power spectrum of noise, S f (u, v) represents the power spectrum of the undegraded image; in addition, when the noise function S is unknown n (u, v) and S f The distribution of (u, v) can be adoptedThe following formula is used:
;
wherein G (u, v) is a predetermined constant.
In any of the above schemes, preferably, the specific steps of obtaining the high-definition images of the inner surface of the central through cavity of each molded casting blank, sequentially expanding the high-definition images to generate corresponding high-definition expanded images of the inner surface, and respectively analyzing and obtaining the pore distribution condition of the inner surface corresponding to each detection sample include:
the image is developed in a high definition mode on the inner surface to realize image bottom layer processing and background purification; the edge feature marking of the target image can be performed in advance in the processes of image bottom layer processing and background purifying processing, and then the image is subjected to binarization processing, so that the edge and the feature in the image can be more accurately identified by a later algorithm;
the method comprises the steps of accurately positioning the target features before extracting the features, and carrying out position normalization operation on the target features, so that the extracted target pore features do not change along with the position and rotation angle changes of other objects in an image plane;
The size, the position and the gray level information of the image can be better known through feature extraction and description of the image processed at the bottom layer during image segmentation, the edge of the target object can be better modified, and each pore part is segmented, so that the accuracy of the extracted features of the target can be enhanced;
when each pore in the inner surface high definition expanded image has depth and a non-straight hole, the pore appears to have isolated noise points and internal chroma spots on the picture;
further processing the image by using a mathematical morphology method, performing expansion operation on the binary image with the background removed, performing corrosion operation, and eliminating chromaticity spots in the pore image after multiple processing;
meanwhile, in order to eliminate isolated noise points in the image, the image is subjected to corrosion operation and then expansion operation by using open operation in mathematical morphology, and after multiple processing, the isolated noise points in the image are eliminated;
perfecting according to the edge feature marks of the target image, and calculating and detecting by using a gradient edge detection algorithm to obtain the edge contour of each accurate pore target feature;
and solving the area of each pore target characteristic according to the pore edge profile, and further obtaining the pore area occupation ratio on the high-definition unfolded image of the inner surface, namely the pore occupation ratio of the inner surface of the detection sample.
In any of the above schemes, preferably, in the process of obtaining the current distribution condition of the pores on the inner surface of the detection sample by the analysis, the bottom layer processing also comprises image noise reduction, denoising, enhancement and restoration, so that the recognition degree of the image is improved;
when the picture is noise reduced, the noise in the signal is removed while the main characteristics of the original signal are kept as much as possible;
when noise is removed, a mode of median filtering and wiener filtering is adopted to overcome the problem of blurring caused by a linear filter to an image, and good edge characteristics are maintained while particle noise is effectively removed; meanwhile, the mean square error between the actual output obtained by multiplying the input signal by the response and the expected output is minimized.
In any of the above schemes, preferably, the specific steps of sequentially performing real load record test on each test sample of small batches corresponding to different curing agent contents and obtaining the simulation available matching degree of the corresponding test sample under the condition of different curing agent addition amounts include:
placing all detection samples with the same curing agent content (the detection samples are actual sample products obtained through small-batch production, the sample products are the same as the formula and the preparation process of the detection samples corresponding to the curing agent content) on a hydraulic pressure detector test platform one by one, wherein a high-precision load sensor is arranged on the hydraulic pressure detector test platform; the number of detection tests of the same curing agent content is 100 or more; selecting at least 5 different content gradients of the curing agent of the currently detected product, namely at least 100 detection samples of each curing agent content value, wherein the total detection sample number is more than or equal to 500;
The real load record test designed at the position can be used for independently carrying out the test on the product batch corresponding to the content of a certain curing agent, the detection quantity of the product of the batch can be adjusted in advance according to the requirement when the sample is selected, at least 100 detection tests are ensured, and meanwhile, the expansion of the detection quantity of the sample can be carried out according to the actual condition so as to ensure the relative objectivity of the subsequent test result.
Starting a hydraulic pressure detector and enabling a pressure disc of the hydraulic pressure detector to slowly realize unidirectional load loading, wherein in the loading process, the load is controlled to be gradually pressurized to a corresponding load value according to a number sequence of the loading load value corresponding to each unit characteristic failure obtained by recording in the step A3;
gradually observing the change of a load display value in signal connection with the high-precision load sensor, and simultaneously recording the front-view state change of the detection sample in the whole load pressurization process by a high-definition camera until the current detection test block is pressed to be completely invalid;
the loading mode of the test change load is the same as that of the model, the loaded load value is loaded according to the corresponding load value obtained in the simulation test when each corresponding triggering unit feature fails, whether the current simulation load value is effective in the actual test is verified by observing the deformation of the actual product, and therefore the overall effective duty ratio is obtained through statistics according to the effective or ineffective quantity.
When the unidirectional load loading value reaches the loading load value corresponding to each unit feature failure obtained in the simulation process, keeping the current load unchanged and shooting and recording a high-definition side image of the current detection test block;
observing the morphological change of the appearance of the current detection sample compared with the appearance of the sample after the last loading when the corresponding loading load is applied by analyzing and processing the high-definition side images obtained by each shooting;
setting the size of the unit feature according to the requirement in a simulation test, so that the unit feature can directly react on the change of the external dimension when the unit feature fails; the change of the corresponding graph under the frame number before and after the observation of the change of the video frame number is taken as the basis for judging whether the appearance of the current detection test block changes or not, so as to judge whether the failure and collapse of the unit characteristic occur in the last loading process of the current test block.
Selecting a high-definition side image with morphological change in a detection sample, finding out a loading load value corresponding to the high-definition side image as an available value for accurately simulating an actual failure load, recording the number of the available values and obtaining the simulation matching degree of the current detection sample;
repeating the steps to sequentially obtain the simulation matching degree of a plurality of other detection samples in the same batch;
The available matching degree of batch detection samples under the condition of the current curing agent content is obtained after the obtained simulation matching degrees are weighted and averaged;
and repeating the steps to obtain the available matching degree of the detection samples in the corresponding batch under the condition of the content of the rest curing agents.
The available matching degree of each curing agent content can show the accurate probability of the result obtained by the product in the state when the simulation test is carried out, so that the product of the simulation detection result and the available matching degree can be used as the final detection result meeting the requirements.
According to the detection method for realizing the influence of the curing agent on the mechanical properties of the product based on image processing, the mechanical load resistance value of the sample prepared by the fluid material (brittle insulating castable fluid) of the insulator obtained when the adding contents of the curing agent are different is counted in a small sample batch detection mode, the method can be effectively applied to the rapid detection of large batches of like products, the image data and the model parameters are obtained by utilizing the early operation in the detection process, the detection efficiency can be effectively ensured, the complicated step of detecting the products one by one is avoided, the performance of the whole like products in the same batch can be objectively and relatively accurately reflected through the pre-arranged small sample test, and the programmed operation of the product detection is effectively realized; the preparation of samples is carried out on the proportion of the mixture ratio content of a plurality of curing agents which are common in the proportioning production of the insulator materials, and the image acquisition of the inner surface and the outer surface is carried out on the prepared samples under the content state of each curing agent so as to achieve the purposes of calculating the distribution condition of the surface pores and indirectly reflecting the surface roughness of the surface pores; the surface quality of the insulator product in the similar formula state after production can be effectively reflected by analyzing the inner surface and the outer surface of the sample, so that the subsequent surface treatment process is convenient to arrange, and the aim of effectively improving the appearance quality of the product is fulfilled; the ultrasonic scanning imaging three-dimensional graph of the internal characteristic distribution is also carried out on the detection sample prepared by the test, and meanwhile, the three-dimensional graph is subjected to three-dimensional reconstruction to obtain a model, and the mechanical property of the model can be rapidly and objectively quantified by means of finite element analysis and parameter processing in three-dimensional software, so that the load resistance simulation result of the sample model can be effectively obtained on the premise of guaranteeing that the curing agent is used as a single variable, the simulation result can be effectively evaluated by the actual test of a small batch of the sample, the true applicable available matching degree is obtained, and the available matching degree is convenient to be applied to mass production and detection; in order to ensure the accuracy of analysis results of actual surface features of a sample, the invention adopts a comprehensive mode of utilizing pre-edge analysis marks, median filtering and post-wiener filtering to ensure the quality and effect of pore feature analysis in the image during image processing, ensures the matching degree of the analysis results and the actual features, effectively reflects the surface quality of the prepared sample, is convenient for appointing an external surface process treatment plan of a subsequent product according to a detection result, and improves the rationality and the high efficiency of the whole product process treatment mode.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions; any alternative modifications or variations to the embodiments of the present invention will fall within the scope of the present invention for those skilled in the art.
The present invention is not described in detail in the present application, and is well known to those skilled in the art.
Claims (6)
1. The method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing is characterized by comprising the following steps of: the method comprises the following steps:
s1: preparing a plurality of groups of brittle insulating casting material fluids for standby, wherein the content of an anhydride curing agent in each group of brittle insulating casting material fluids is used as a single variable, and the content of the anhydride curing agent in each group of brittle insulating casting material fluids is different;
s2: preparing a plurality of vessel containers;
S3: sequentially pouring an equal amount of brittle insulating castable fluid corresponding to the content of the anhydride curing agent into a corresponding vessel container, standing and waiting for the castable to solidify;
s4: forming molding casting blanks after the brittle insulating casting material fluid in each vessel container is completely shaped, and sequentially taking out each molding casting blank;
s5: cutting and grinding two end parts of each molded casting blank to form detection samples with the same size, and sequentially detecting each detection sample;
s6: acquiring external surface high-definition images of all detection samples to be detected, respectively expanding the external surface high-definition images to generate corresponding external surface high-definition expanded images, and analyzing to obtain external surface pore distribution conditions corresponding to all the detection samples;
s7: acquiring an ultrasonic scanning imaging three-dimensional image of the interior of each detection sample by utilizing high-frequency ultrasonic reflection, and reconstructing a sample reconstruction three-dimensional model identical to each ultrasonic scanning imaging three-dimensional image in modeling software according to each acquired ultrasonic scanning imaging three-dimensional image;
s8: the method comprises the following specific steps of sequentially obtaining the maximum simulated anti-load value and the usable matching degree of the reconstructed three-dimensional model of each sample, and calculating to obtain the limit anti-load value corresponding to the batch detection samples:
Analyzing to obtain the pore distribution condition inside the reconstructed three-dimensional model of each sample and obtain the corresponding sample model porosity;
sequentially performing mechanical property simulation test on the three-dimensional model reconstructed by each sample, and respectively obtaining simulation anti-load maximum values corresponding to the detection samples under different curing agent contents;
carrying out real load record test on each detection sample of small batches corresponding to different curing agent contents in sequence, and obtaining the simulation available matching degree of the corresponding detection sample under the condition of different curing agent addition amounts;
the simulation available matching degree is led into calculation and is applicable to the detection of the limit load resistance of the same type of batch detection samples;
and obtaining the limit anti-load value corresponding to the batch detection samples by using the obtained simulation anti-load maximum value multiplied by the simulation available matching degree of the batch detection samples.
2. The method for detecting the influence of the curing agent on the mechanical properties of the product based on the image processing according to claim 1, wherein the method comprises the following steps: the container is a ring column container, and the shape of the molded casting blank molded and shaped by the container is a hollow column structure with a through center.
3. The method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing according to claim 2, wherein the method comprises the following steps: s6, further comprising the following steps: and acquiring high-definition images of the inner surfaces of the center through cavities of the molded casting blanks, sequentially expanding the high-definition images to generate corresponding high-definition expanded images of the inner surfaces, and respectively analyzing to obtain the pore distribution conditions of the inner surfaces corresponding to the detection samples.
4. The method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing according to claim 3, wherein the method comprises the following steps: the specific steps of sequentially carrying out mechanical property simulation test on the reconstructed three-dimensional model of each sample include:
a1: the method comprises the steps of performing discretization on the characteristics inside a sample reconstruction three-dimensional model into a plurality of unit characteristics with the same size by utilizing finite element analysis;
a2: according to the analysis of the reconstructed three-dimensional model, the number of pore unit features and the pore position distribution are obtained, the overall transparency of the reconstructed three-dimensional model of the sample is improved, the color of the unit features representing the pores is deepened, and the distribution display of the pore unit features is realized;
a3: carrying out self-adaptive incremental loading on the sample reconstruction three-dimensional model in a single axis direction under boundary constraint conditions and load loading, realizing gradual failure of each unit feature, and simultaneously recording a loading load value corresponding to each unit feature failure;
a4: judging whether the three-dimensional model of the sample reconstruction still has bearing capacity or not after the current unit characteristics fail, and recording the total value of the current loading load when the three-dimensional model of the sample reconstruction does not have bearing capacity after all the unit characteristics fail, so as to obtain the maximum value of the simulation anti-loading of the current detection sample.
5. The method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing according to claim 4, wherein the method comprises the following steps: the self-adaptive incremental loading method comprises the following steps:
according to the preset material unit characteristic failure triggering of the reconstructed three-dimensional model, automatically adjusting the load increment, and realizing that each loading guarantees that one unit characteristic fails to be destroyed by utilizing the maximum stress destruction criterion;
and carrying out rigidity degradation treatment and unit feature hiding treatment on the failed and destroyed unit features to obtain statistics of the number of the undelayed unit features, and continuously reloading through unbalanced iteration until all the unit features of the whole three-dimensional model lose bearing capacity.
6. The method for detecting the influence of the curing agent on the mechanical properties of the product based on image processing according to claim 5, wherein the method comprises the following steps: in step S6, the specific steps of obtaining the external surface high-definition image of each detection sample to be detected and respectively developing the external surface high-definition image to generate a corresponding external surface high-definition developed image, and analyzing to obtain the external surface pore distribution condition corresponding to each detection sample include:
the image is unfolded at high definition on the outer surface to realize image bottom layer processing and background purification;
Accurately positioning the target features before extracting the features, and performing position normalization operation of the target features;
eliminating chromaticity spots inside the pore image;
eliminating isolated noise points in the image;
perfecting according to the edge feature marks of the target image, and calculating and detecting by using a gradient edge detection algorithm to obtain the edge contour of each accurate pore target feature;
and solving the area of each pore target characteristic according to the pore edge profile, and further obtaining the pore area ratio on the high-definition unfolded image of the outer surface, namely the pore ratio of the outer surface of the detection sample.
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106770394A (en) * | 2017-02-16 | 2017-05-31 | 温州大学 | The three-dimensional appearance of metal welding seam internal flaw and the lossless detection method of stress characteristics |
CN107729596A (en) * | 2017-08-28 | 2018-02-23 | 上海工程技术大学 | A kind of method calculated for material damage |
AU2021102727A4 (en) * | 2021-05-21 | 2022-04-28 | Jain, Akshay Dr. | Method and system for determining heat affected zone during the laser beam drilling ofhybrid composite |
CN114861496A (en) * | 2022-05-05 | 2022-08-05 | 哈尔滨工业大学 | Concrete mesoscopic structure chloride ion erosion model based on cold region natural environment effect |
FR3121216A1 (en) * | 2021-03-24 | 2022-09-30 | Entreprise Generale Leon Grosse | Process for in situ determination of the mechanical characteristics of the concrete of a structure |
CN115148306A (en) * | 2022-05-20 | 2022-10-04 | 华东理工大学 | Method for predicting optimal dosage of additive in polyurethane material |
CN115630543A (en) * | 2022-10-06 | 2023-01-20 | 大连理工大学 | Three-dimensional finite element simulation method based on high-precision digital core reconstruction model |
CN115824743A (en) * | 2022-12-01 | 2023-03-21 | 华北水利水电大学 | Manufacturing method and simulation test method of high-transparency rock-like resin test piece |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US12050297B2 (en) * | 2020-09-11 | 2024-07-30 | Saudi Arabian Oil Company | Method and system for determining energy-based brittleness |
-
2023
- 2023-05-08 CN CN202310504718.3A patent/CN116223224B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106770394A (en) * | 2017-02-16 | 2017-05-31 | 温州大学 | The three-dimensional appearance of metal welding seam internal flaw and the lossless detection method of stress characteristics |
CN107729596A (en) * | 2017-08-28 | 2018-02-23 | 上海工程技术大学 | A kind of method calculated for material damage |
FR3121216A1 (en) * | 2021-03-24 | 2022-09-30 | Entreprise Generale Leon Grosse | Process for in situ determination of the mechanical characteristics of the concrete of a structure |
AU2021102727A4 (en) * | 2021-05-21 | 2022-04-28 | Jain, Akshay Dr. | Method and system for determining heat affected zone during the laser beam drilling ofhybrid composite |
CN114861496A (en) * | 2022-05-05 | 2022-08-05 | 哈尔滨工业大学 | Concrete mesoscopic structure chloride ion erosion model based on cold region natural environment effect |
CN115148306A (en) * | 2022-05-20 | 2022-10-04 | 华东理工大学 | Method for predicting optimal dosage of additive in polyurethane material |
CN115630543A (en) * | 2022-10-06 | 2023-01-20 | 大连理工大学 | Three-dimensional finite element simulation method based on high-precision digital core reconstruction model |
CN115824743A (en) * | 2022-12-01 | 2023-03-21 | 华北水利水电大学 | Manufacturing method and simulation test method of high-transparency rock-like resin test piece |
Non-Patent Citations (1)
Title |
---|
基于"AM-GoogLeNet + BP"联合数据驱动的混凝土细观模型压缩应力−应变曲线预测;刘溢凡等;《力学学报》;第55卷(第4期);第925-938页 * |
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