Titanium alloy structure detection and analysis method and system based on heat treatment

Abstract

The invention relates to the technical field of image processing, in particular to a titanium alloy structure detection and analysis method and system based on heat treatment, and the method comprises the steps: receiving a detection and analysis instruction, starting an image acquisition unit, obtaining a to-be-detected titanium alloy, carrying out heat treatment to obtain a cooled titanium alloy, carrying out polishing corrosion treatment to obtain a treated titanium alloy, and carrying out image acquisition; performing preprocessing to obtain a processed image set; performing image segmentation to obtain segmented images; collecting the segmented images to obtain a segmented image set; extracting crystal grain diameters, phase proportions and defect areas to obtain a crystal grain diameter set, a phase proportion set and a defect area set; and generating a correct analysis report or an error analysis report according to the average diameter, the average phase proportion and the average area of the crystal grains. The accuracy of titanium alloy structure detection can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a titanium alloy structure detection and analysis method and system based on heat treatment. Background Art

[0002] With the rapid development of information technology, tissue detection and analysis technology has been widely used in all walks of life. Accurate tissue detection and analysis has become a key technology for optimizing material performance and improving product quality. Titanium alloy, as an engineering material with excellent performance, its microstructure directly determines the mechanical properties, corrosion resistance and high-temperature stability of the material. Therefore, accurate detection and analysis of titanium alloy structure is of great significance to achieve high-quality manufacturing.

[0003] Traditional titanium alloy microstructure detection and analysis methods rely on manual observation and empirical judgment, which is not only time-consuming and easily affected by subjective factors, but also difficult to achieve large-scale, high-precision microstructure analysis. Therefore, how to improve the accuracy of titanium alloy microstructure detection is an important issue that needs to be solved urgently. Summary of the invention

[0004] The present invention provides a titanium alloy structure detection and analysis method and system based on heat treatment, the main purpose of which is to improve the accuracy of titanium alloy structure detection.

[0005] To achieve the above-mentioned purpose, the present invention provides a titanium alloy tissue detection and analysis method based on heat treatment, comprising: receiving a detection and analysis instruction, and starting a pre-confirmed image acquisition unit based on the detection and analysis instruction; obtaining a titanium alloy to be tested, and heat-treating the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time, and a preset cooling rate to obtain a cooled titanium alloy; performing polishing and corrosion treatment on the cooled titanium alloy to obtain a treated titanium alloy, performing an image acquisition operation on the treated titanium alloy based on the started image acquisition unit to obtain a collection image set, and pre-processing all the collection images in the collection image set to obtain a processed image set; extracting processed images from the processed image set in sequence, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set; extracting segmented images from the segmented image set in sequence, and performing feature extraction on the extracted segmented images, The grain diameter, phase ratio and defect area are obtained, and the grain diameter, phase ratio and defect area are collected respectively to obtain a grain diameter set, a phase ratio set and a defect area set; the average grain diameter, the average phase ratio and the average area are calculated respectively based on the grain diameter set, the phase ratio set and the defect area set; the average grain diameter, the average phase ratio and the average area are compared with the preset grain diameter threshold, the preset phase ratio threshold and the preset area threshold respectively; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

[0006] Optionally, the polishing and corrosion treatment of the cooled titanium alloy to obtain the treated titanium alloy includes: placing the cooled titanium alloy in a pre-acquired cleaning solution, setting a cleaning time, and performing a cleaning operation on the cooled titanium alloy based on the cleaning time and the cleaning solution to obtain a cleaned titanium alloy; obtaining a first sandpaper and a second sandpaper; calculating a grinding time, and performing a grinding operation on the cleaned titanium alloy using the first sandpaper, the grinding time, and a preset first-level grinding pressure to obtain a pre-polished titanium alloy; grinding the pre-polished titanium alloy using the second sandpaper, the grinding time, and a preset second-level grinding pressure to obtain a finely ground titanium alloy; and The fine-ground titanium alloy is polished with the obtained diamond suspension to obtain a preliminary polished titanium alloy, and the polishing completion of the preliminary polished titanium alloy is calculated; the polishing completion is compared with a preset completion threshold; when the polishing completion is less than the completion threshold, the fine-ground titanium alloy is updated with the preliminary polished titanium alloy, and the updated fine-ground titanium alloy is used to return to the above step of polishing the fine-ground titanium alloy based on the pre-acquired diamond suspension; when the polishing completion is greater than or equal to the completion threshold, the preliminary polished titanium alloy is confirmed as a polished titanium alloy; the polished titanium alloy is chemically corroded to obtain a treated titanium alloy.

[0007] Optionally, the calculating of the polishing time includes: setting a basic polishing time and a standard titanium alloy area, obtaining the titanium alloy area of ​​the cleaned titanium alloy, and calculating the polishing time based on the basic polishing time, the standard titanium alloy area and the titanium alloy area: ,in, Refers to the grinding time, Refers to the basic polishing time, Refers to the preset adjustment parameters, Refers to the titanium alloy area, Refers to the standard titanium alloy area.

[0008] Optionally, the image acquisition unit after startup performs an image acquisition operation on the processed titanium alloy to obtain a captured image set, including: setting a first acquisition multiple, a second acquisition multiple and a third acquisition multiple; performing an image acquisition operation on the processed titanium alloy based on the first acquisition multiple, the second acquisition multiple, the third acquisition multiple, the image acquisition unit and a preset number of acquisition times to obtain a first acquisition image set, a second acquisition image set and a third acquisition image set, wherein the first acquisition image set corresponds to the first acquisition multiple, the second acquisition image set corresponds to the second acquisition multiple, and the third acquisition image set corresponds to the third acquisition multiple; and collecting the first acquisition image set, the second acquisition image set and the third acquisition image set to obtain a acquisition image set.

[0009] Optionally, all acquired images in the acquired image set are preprocessed to obtain a processed image set, including: calculating a comprehensive noise level value based on the acquired image set, and setting a filtering standard deviation according to the comprehensive noise level value; performing a global denoising operation on all acquired images in the acquired image set according to the filtering standard deviation to obtain a global image set; setting a window size, and performing local denoising on the global image set based on the window size to obtain a processed image set.

[0010] Optionally, the calculation of the comprehensive noise level value based on the acquired image set includes: setting a regional horizontal value and a regional vertical value based on the acquired image set, and setting multiple detection areas according to the regional horizontal value and the regional vertical value; calculating the regional standard deviation of the multiple detection areas, and performing a mean calculation operation on the calculated regional standard deviation to obtain a regional mean; decomposing the acquired image set based on a preset discrete transformation method to obtain a high-frequency sub-band set; extracting high-frequency sub-bands from the high-frequency sub-band set in turn, and performing statistics on the extracted high-frequency sub-bands to obtain robust statistics, and aggregating the robust statistics to obtain a robust statistics set; performing a mean calculation operation on all robust statistics in the robust statistics set to obtain a statistic mean; and calculating the comprehensive noise level value based on the regional mean and the statistic mean.

[0011] Optionally, setting the filtering standard deviation according to the comprehensive noise level value includes: obtaining a low noise standard deviation and a low noise reference value, and calculating the filtering standard deviation based on the comprehensive noise level value, the low noise standard deviation and the low noise reference value: ,in, refers to the filtering standard deviation, refers to the low noise standard deviation, Refers to the comprehensive noise level value, Refers to the low noise reference value, Refers to the preset noise adjustment parameters.

[0012] Optionally, performing image segmentation on the extracted processed image to obtain a segmented image includes: obtaining the image grayscale mean of the processed image, setting a low grayscale parameter and a high grayscale parameter based on the image grayscale mean, wherein the low grayscale parameter is 0.4 times the image grayscale mean, and the high grayscale parameter is 1.6 times the image grayscale mean; performing edge detection using a pre-built edge detection algorithm, a low grayscale parameter, and a high grayscale parameter to obtain an edge contour set; and segmenting the processed image based on the edge contours in the edge contour set to obtain a segmented image.

[0013] Optionally, the feature extraction of the extracted segmented image to obtain the grain diameter, phase ratio and defect area includes: extracting the grain area based on the segmented image, marking the grain area based on a pre-built marking algorithm and the grain area to obtain a marked area set; extracting the marked area from the marked area set, and measuring the size of the extracted marked area to obtain an equivalent diameter, and collecting the equivalent diameters to obtain an equivalent diameter set; calculating the mean of all equivalent diameters in the equivalent diameter set to obtain the grain diameter; obtaining Related phase, general Related The phase is binarized to obtain a first pixel number and a second pixel number; a phase ratio is calculated based on the first pixel number and the second pixel number, a defect region is identified from the segmented image, and a defect area is calculated based on the defect region.

[0014] To achieve the above-mentioned purpose, the present invention also provides a titanium alloy tissue detection and analysis system based on heat treatment, comprising: an image acquisition module, which is used to receive a detection and analysis instruction, and start a pre-confirmed image acquisition unit based on the detection and analysis instruction; obtain a titanium alloy to be tested, and perform heat treatment on the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time and a preset cooling rate to obtain a cooled titanium alloy; perform polishing and corrosion treatment on the cooled titanium alloy to obtain a treated titanium alloy, perform image acquisition operation on the treated titanium alloy based on the started image acquisition unit to obtain a collection of collected images, and pre-process all collected images in the collection of collected images to obtain a collection of processed images; a feature extraction module, which is used to sequentially extract processed images from the collection of processed images, and perform image segmentation on the extracted processed images to obtain segmented images, and collect the segmented images to obtain a collection of segmented images; sequentially extract segmented images from the collection of segmented images, and perform feature extraction on the extracted segmented images, The grain diameter, phase ratio and defect area are obtained, and the grain diameter, phase ratio and defect area are respectively collected to obtain a grain diameter set, a phase ratio set and a defect area set; a mean calculation module is used to calculate the average grain diameter, average phase ratio and average area based on the grain diameter set, the phase ratio set and the defect area set; a report generation module is used to compare the average grain diameter, the average phase ratio and the average area with the preset grain diameter threshold, the preset phase ratio threshold and the preset area threshold respectively; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

[0015] In order to solve the above problems, the present invention also provides an electronic device, which includes: a memory storing at least one instruction; and a processor executing the instructions stored in the memory to implement the above-mentioned titanium alloy structure detection and analysis method based on heat treatment.

[0016] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned titanium alloy structure detection and analysis method based on heat treatment.

[0017] The present invention solves the problems described in the background technology. Firstly, a detection and analysis instruction is received, and an image acquisition unit is started based on the detection and analysis instruction. The image acquisition unit is automatically started by receiving the detection and analysis instruction, so as to realize automatic triggering of the detection process, reduce the possibility of errors in manual operation, and can quickly respond to detection needs, thereby improving the continuity and efficiency of the detection process; secondly, a heat treatment is performed on the titanium alloy to be tested based on the processing temperature, processing time and cooling rate. By presetting the processing temperature, processing time and cooling rate, the consistency of the heat treatment is ensured, and the deviation caused by parameter fluctuation is reduced; thirdly, the cooled titanium alloy is polished and corroded to obtain a treated titanium alloy. The polishing and corrosion treatments make the surface of the cooled titanium alloy smooth and reveal the real grain boundaries, phase boundaries and defects, thereby providing a reliable basis for subsequent image acquisition; thereafter, the collected image set is All the collected images in the method are preprocessed to obtain a processed image set, and the preprocessing steps include: global denoising and local denoising. By preprocessing the collected images, the noise in the collected images is effectively reduced, making the grain boundaries, phase boundaries and defects more obvious, and improving the accuracy of subsequent image segmentation and feature extraction; further, the processed images are segmented to obtain segmented images, and edge detection is performed using edge detection algorithms, low grayscale parameters and high grayscale parameters to obtain edge contour sets, and then image segmentation is performed based on the edge contour sets to obtain segmented images, which improves the accuracy and efficiency of image segmentation and provides a reliable basis for subsequent feature extraction; finally, feature extraction is performed on the segmented images to obtain grain diameter, phase ratio and defect area. Through feature extraction, the state of titanium alloy organization can be quantitatively described to provide accurate data. Therefore, the present invention can improve the accuracy of titanium alloy organization detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of a process for detecting and analyzing a titanium alloy structure based on heat treatment provided by an embodiment of the present invention; Figure 2 A functional module diagram of a titanium alloy structure detection and analysis system based on heat treatment provided by an embodiment of the present invention; Figure 3A schematic structural diagram of an electronic device for implementing the titanium alloy structure detection and analysis method based on heat treatment provided in one embodiment of the present invention.

[0019] Explanation of the reference numerals: 1. electronic device; 10. processor; 11. memory; 12. bus.

[0020] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0022] The embodiment of the present application provides a titanium alloy tissue detection and analysis method based on heat treatment. The execution subject of the titanium alloy tissue detection and analysis method based on heat treatment includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the titanium alloy tissue detection and analysis method based on heat treatment can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0023] Reference Figure 1 FIG. 1 is a flow chart of a method for detecting and analyzing titanium alloy tissue based on heat treatment according to an embodiment of the present invention. In this embodiment, the method for detecting and analyzing titanium alloy tissue based on heat treatment comprises: S1, receiving a detection and analysis instruction, and starting a pre-confirmed image acquisition unit based on the detection and analysis instruction.

[0024] Explainable, detection and analysis instructions refer to instructions issued manually for the detection and analysis of titanium alloy structure, titanium alloy structure includes: grain diameter, phase ratio and defect area. Grain diameter refers to the diameter of the grain in titanium alloy, phase ratio refers to phase and The area ratio of the phase, the defect area refers to the area of ​​the defective part in the titanium alloy, the defective part includes: defect holes and defect cracks, defect holes refer to the gaps formed in the titanium alloy due to gas inclusions in the molten state, insufficient filling or solidification shrinkage, the defect holes are round or elliptical, and their existence will weaken the local mechanical properties and become the initiation source of fatigue cracks, the diameter of the defect holes ranges from 5 microns to 20 microns, the defect cracks refer to the continuous rupture or separation defects that occur locally in the titanium alloy due to internal stress, uneven cooling during heat treatment, machining defects or external loads, the defect cracks are generally slender, and their existence will significantly reduce the fatigue resistance and fracture toughness, the width range of the defect cracks is: less than 1 micron, the length range of the defect cracks is: 10 microns to 50 microns, the image acquisition unit refers to the unit for image acquisition of the processed titanium alloy, optionally, the image acquisition unit includes a high-resolution optical microscope and a scanning electron microscope.

[0025] S2. Obtain a titanium alloy to be tested, and perform heat treatment on the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time, and a preset cooling rate to obtain a cooled titanium alloy.

[0026] It can be explained that the titanium alloy to be tested refers to the sample used for titanium alloy microstructure analysis, the treatment temperature refers to the temperature when the titanium alloy is heat treated, optionally, the treatment temperature is 900°C, the treatment time refers to the holding time when the titanium alloy is heat treated, optionally, the treatment time is 2 hours, the cooling rate refers to the cooling rate of the titanium alloy when the titanium alloy is heat treated, and heat treating the titanium alloy to be tested based on the preset treatment temperature, the preset treatment time and the preset cooling rate means first heating the titanium alloy to be tested based on the set treatment temperature, then keeping the titanium alloy warm according to the set treatment time, and finally cooling the titanium alloy according to the set cooling rate. The cooled titanium alloy refers to the titanium alloy to be tested after the heat treatment.

[0027] S3. Perform polishing and corrosion treatment on the cooled titanium alloy to obtain a processed titanium alloy, perform image acquisition operation on the processed titanium alloy based on the started image acquisition unit to obtain an acquired image set, and pre-process all acquired images in the acquired image set to obtain a processed image set.

[0028] It can be explained that the processed titanium alloy refers to the titanium alloy obtained after polishing and corrosion treatment of the cooled titanium alloy, the collected image set refers to the set composed of collected images, the collected image refers to the image obtained after image collection of the processed titanium alloy by using the image collection unit, the processed image set refers to the set composed of processed images, the processed image refers to the image obtained after preprocessing all the collected images in the collected image set, and preprocessing refers to the noise filtering operation.

[0029] In detail, the polishing and corrosion treatment of the cooled titanium alloy to obtain the treated titanium alloy includes: placing the cooled titanium alloy in a pre-acquired cleaning solution, setting a cleaning time, and performing a cleaning operation on the cooled titanium alloy based on the cleaning time and the cleaning solution to obtain a cleaned titanium alloy; obtaining a first sandpaper and a second sandpaper; calculating a grinding time, and performing a grinding operation on the cleaned titanium alloy using the first sandpaper, the grinding time, and a preset first-level grinding pressure to obtain a pre-polished titanium alloy; using the second sandpaper, the grinding time, and a preset second-level grinding pressure to grind the pre-polished titanium alloy to obtain a finely ground titanium alloy; based on the pre-acquired The fine-ground titanium alloy is polished with the obtained diamond suspension to obtain a preliminary polished titanium alloy, and the polishing completion of the preliminary polished titanium alloy is calculated; the polishing completion is compared with a preset completion threshold; when the polishing completion is less than the completion threshold, the fine-ground titanium alloy is updated with the preliminary polished titanium alloy, and the updated fine-ground titanium alloy is used to return to the above step of polishing the fine-ground titanium alloy based on the pre-acquired diamond suspension; when the polishing completion is greater than or equal to the completion threshold, the preliminary polished titanium alloy is confirmed as a polished titanium alloy; the polished titanium alloy is chemically corroded to obtain a treated titanium alloy.

[0030] It can be explained that the cleaning liquid refers to the liquid used to clean the cooled titanium alloy. Optionally, the cleaning liquid is an ethanol solution. The cleaning time refers to the time for cleaning the cooled titanium alloy. Optionally, the cleaning time is 5 minutes. The cleaned titanium alloy refers to the cooled titanium alloy cleaned by the cleaning liquid. The first sandpaper refers to the sandpaper used for the first grinding of the cleaned titanium alloy. Optionally, the first sandpaper is 240 mesh sandpaper. The second sandpaper refers to the sandpaper used for fine grinding of the preliminarily polished titanium alloy. Optionally, the second sandpaper is 600 mesh sandpaper. The grinding time refers to the time for grinding the cleaned titanium alloy calculated based on the area of ​​the titanium alloy. The primary grinding pressure refers to the pressure applied when grinding the cleaned titanium alloy using the first sandpaper. Optionally, the primary grinding pressure is 200 grams-force. The preliminarily polished titanium alloy refers to the titanium alloy obtained after grinding the cleaned titanium alloy using the first sandpaper. The secondary grinding pressure refers to the pressure applied when grinding the preliminarily polished titanium alloy using the second sandpaper. Optionally, the secondary grinding pressure is 150 grams-force. The finely ground titanium alloy refers to the titanium alloy obtained after the preliminary ground titanium alloy is polished with the second sandpaper, and the diamond suspension refers to the polishing medium used to polish the finely ground titanium alloy. Optionally, the diamond suspension is a diamond suspension with a particle size of 0.5 microns. The preliminary polished titanium alloy refers to the titanium alloy obtained after the finely ground titanium alloy is polished with the diamond suspension. The polishing completion of the preliminary polished titanium alloy is calculated as follows: ,in, Refers to the degree of polishing completion. Refers to the roughness before polishing. Refers to the roughness after polishing. Refers to the target roughness, refers to the current reflectivity, Refers to the target reflectivity.

[0031] It can be understood that the roughness before polishing refers to the surface roughness of the finely ground titanium alloy, and the surface roughness is measured by a roughness meter. The roughness after polishing refers to the surface roughness of the initially polished titanium alloy. The target roughness refers to the surface roughness set manually. Optionally, the target roughness is 0.1 microns. The current reflectivity refers to the reflection intensity of the surface of the initially polished titanium alloy, which is measured by a reflectivity meter. The target reflectivity refers to the reflection intensity corresponding to the target roughness. The polishing completion refers to the value used to determine whether the polishing of the finely ground titanium alloy is completed. The completion threshold refers to the threshold set manually for determining the polishing completion. Optionally, the completion threshold is 1. The polished titanium alloy refers to a titanium alloy whose polishing degree is greater than or equal to the completion degree threshold. Chemically corroding the polished titanium alloy refers to chemically corroding the polished titanium alloy using a pre-configured titanium alloy solvent and corrosion time. The corrosion time is the time for corroding the polished titanium alloy. The specific corrosion steps are: completely immersing the polished titanium alloy in the titanium alloy solvent. When the immersion time reaches the corrosion time, taking the polished titanium alloy out of the titanium alloy solvent and rinsing the polished titanium alloy with deionized water. The rinsing lasts for more than 1 minute to terminate the corrosion reaction. Optionally, the titanium alloy solvent is Kroll reagent, and the corrosion time is 15 to 20 seconds.

[0032] In detail, the calculation of the polishing time includes: setting a basic polishing time and a standard titanium alloy area, obtaining the titanium alloy area of ​​the cleaned titanium alloy, and calculating the polishing time based on the basic polishing time, the standard titanium alloy area and the titanium alloy area: ,in, Refers to the grinding time, Refers to the basic polishing time, Refers to the preset adjustment parameters, Refers to the titanium alloy area, Refers to the standard titanium alloy area.

[0033] Explanation: Basic grinding time refers to a fixed time set by humans for grinding cleaned titanium alloy. The basic grinding time is not affected by the titanium alloy area of ​​the cleaned titanium alloy and is a fixed time. Optionally, the basic grinding time is 3 minutes. Standard titanium alloy area refers to a titanium alloy area set by humans. The standard titanium alloy area is used as a reference scale so that Converted to a dimensionless ratio, the titanium alloy area refers to the area of ​​the cleaned titanium alloy surface, and the adjustment parameter refers to the parameter used to control The parameter that affects the grinding time. The larger the adjustment parameter, The greater the impact on the grinding time.

[0034] In detail, the image acquisition unit after startup performs an image acquisition operation on the processed titanium alloy to obtain a captured image set, including: setting a first acquisition multiple, a second acquisition multiple, and a third acquisition multiple; based on the first acquisition multiple, the second acquisition multiple, the third acquisition multiple, the image acquisition unit and a preset number of acquisition times, performs an image acquisition operation on the processed titanium alloy to obtain a first acquisition image set, a second acquisition image set, and a third acquisition image set, wherein the first acquisition image set corresponds to the first acquisition multiple, the second acquisition image set corresponds to the second acquisition multiple, and the third acquisition image set corresponds to the third acquisition multiple; and collects the first acquisition image set, the second acquisition image set, and the third acquisition image set to obtain a acquisition image set.

[0035] It can be explained that the first acquisition magnification refers to the magnification when the image of the processed titanium alloy is acquired, and the magnification refers to the magnification of the processed titanium alloy when the image is acquired. Optionally, the first acquisition magnification is 50 times. For example, the first acquisition magnification is 50 times, and the image of the processed titanium alloy is acquired by using the first acquisition magnification to obtain an image of the processed titanium alloy after being magnified 50 times. The second acquisition magnification refers to the magnification when the image of the processed titanium alloy is acquired. Optionally, the second acquisition magnification is 200 times. The third acquisition magnification refers to the magnification when the image of the processed titanium alloy is acquired. Optionally, the third acquisition magnification is 300 times. The number of acquisition times refers to the number of times the image of the processed titanium alloy is acquired. For example, if the number of acquisition times is 10, 10 images are acquired for the processed titanium alloy. The first acquired image set refers to a set composed of first acquired images, and the first acquired image refers to an acquired image obtained after image acquisition of the processed titanium alloy using the first acquisition magnification. The second acquired image set refers to a set composed of second acquired images, and the second acquired image refers to an acquired image obtained after image acquisition of the processed titanium alloy using the second acquisition magnification. The third acquired image set refers to a set composed of third acquired images, and the third acquired image refers to an acquired image obtained after image acquisition of the processed titanium alloy using the third acquisition magnification.

[0036] In detail, all the acquired images in the acquired image set are preprocessed to obtain a processed image set, including: calculating a comprehensive noise level value based on the acquired image set, and setting a filtering standard deviation according to the comprehensive noise level value; performing a global noise reduction operation on all the acquired images in the acquired image set according to the filtering standard deviation to obtain a global image set; setting a window size, and performing local denoising on the global image set based on the window size to obtain a processed image set.

[0037] It can be explained that the comprehensive noise level value refers to the value that combines the regional mean and the statistical mean to reflect the overall noise intensity of the collected image. The comprehensive noise level value calculated based on the regional mean and the statistical mean is as follows: ,in, Refers to the comprehensive noise level value, refers to the noise weight, refers to the regional mean, Refers to the mean of a statistic.

[0038] It can be explained that the noise weight refers to a parameter used to control the influence of the regional mean and the statistical mean on the comprehensive noise level value. The larger the noise weight, the greater the influence of the regional mean on the comprehensive noise level value. The filter standard deviation refers to the standard deviation of the Gaussian filter. The global image set refers to a set composed of global images. The global image refers to the image obtained after the collected image is globally denoised using the Gaussian filter and the filter standard deviation. Using the Gaussian filter to perform global denoising on the image is a prior art and will not be repeated here. The window size refers to the size of the median filter window. For example, 3×3 means that the window size is 3. The processed image set refers to a set composed of processed images. The processed image refers to the image obtained after the global image in the global image set is median filtered. Median filtering is a prior art and will not be repeated here.

[0039] In detail, the method of calculating the comprehensive noise level value based on the acquired image set includes: setting a regional horizontal value and a regional vertical value based on the acquired image set, and setting multiple detection areas according to the regional horizontal value and the regional vertical value; calculating the regional standard deviation of the multiple detection areas, and performing a mean calculation operation on the calculated regional standard deviation to obtain a regional mean; decomposing the acquired image set based on a preset discrete transformation method to obtain a high-frequency sub-band set; extracting high-frequency sub-bands from the high-frequency sub-band set in turn, and performing statistics on the extracted high-frequency sub-bands to obtain robust statistics, and aggregating the robust statistics to obtain a robust statistics set; performing a mean calculation operation on all robust statistics in the robust statistics set to obtain a statistical mean; and calculating the comprehensive noise level value based on the regional mean and the statistical mean.

[0040] It can be explained that the regional horizontal value refers to the length of the horizontal axis of the detection area, the regional vertical value refers to the length of the vertical axis of the detection area, the detection area refers to a matrix area constructed according to the regional horizontal value and the regional vertical axis, the regional standard deviation refers to the noise standard deviation in the detection area, the noise standard deviation refers to the parameter used to measure the degree of discreteness of the grayscale value in the collected image relative to the regional mean, and reflects the amplitude of the grayscale value fluctuation of the pixel points in the collected image. The regional mean refers to the mean of the regional standard deviations of all detection areas, the discrete transformation method refers to the discrete wavelet transform, the high-frequency subband set refers to the set composed of high-frequency subbands, the high-frequency subband refers to the high-frequency information obtained after the collected image is decomposed by the discrete wavelet transform, and the high-frequency subband includes the noise of the collected image, the robust statistic refers to the statistic of the noise in the high-frequency subband, the calculation of the robust statistic is an existing technology and will not be repeated here, the robust statistic set refers to the set composed of robust statistics, and the statistic mean refers to the average value obtained after the mean calculation of all robust statistics.

[0041] In detail, setting the filtering standard deviation according to the comprehensive noise level value includes: obtaining a low noise standard deviation and a low noise reference value, and calculating the filtering standard deviation based on the comprehensive noise level value, the low noise standard deviation and the low noise reference value: ,in, refers to the filtering standard deviation, refers to the low noise standard deviation, Refers to the comprehensive noise level value, Refers to the low noise reference value, Refers to the preset noise adjustment parameters.

[0042] It can be explained that the low noise standard deviation refers to the minimum standard deviation of filtering required to ensure the smoothness of the collected image under low noise conditions. For example, if the low noise standard deviation is 1 and the comprehensive noise level value is equal to the low noise reference value, the filter will filter with at least 1 pixel standard deviation to ensure the smoothness of the image. The low noise condition is that the comprehensive noise level value is less than or equal to the low noise reference value. The low noise reference value refers to the value used to judge the low noise condition. When the comprehensive noise level value is less than or equal to the low noise reference value, it is confirmed as a low noise condition. The noise adjustment parameter refers to the value used to control The parameter that affects the standard deviation of the filter. The larger the noise adjustment parameter, The greater the impact on the filtering standard deviation.

[0043] S4. Extracting processed images from the processed image set in sequence, performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set.

[0044] It can be explained that a segmented image refers to an image obtained after image segmentation is performed on a processed image, and a segmented image set refers to a set of segmented images.

[0045] In detail, the image segmentation of the extracted processed image to obtain a segmented image includes: obtaining the image grayscale mean of the processed image, setting a low grayscale parameter and a high grayscale parameter based on the image grayscale mean, wherein the low grayscale parameter is 0.4 times the image grayscale mean, and the high grayscale parameter is 1.6 times the image grayscale mean; performing edge detection using a pre-built edge detection algorithm, a low grayscale parameter, and a high grayscale parameter to obtain an edge contour set; and segmenting the processed image based on the edge contours in the edge contour set to obtain a segmented image.

[0046] Explanation: The grayscale mean of the image refers to the mean of the grayscale value of the processed image. The low grayscale parameter refers to a parameter set manually for filtering the gradient value of pixels in the processed image. The high grayscale parameter refers to a parameter set manually for filtering the gradient value of pixels in the processed image. When the gradient value of a pixel is greater than the high grayscale parameter, the pixel corresponding to the gradient value is confirmed as an edge. When the gradient value of a pixel is less than the low grayscale parameter, the pixel corresponding to the gradient value is confirmed as a non-edge. When the pixel between the high grayscale parameter and the low grayscale parameter is connected to the edge, it is confirmed as an edge. The edge detection algorithm refers to an algorithm used to detect the edge of the processed image. Optionally, the edge detection algorithm is the Canny edge detection algorithm. The edge contour set refers to a set composed of edge contours. The edge contour refers to a contour composed of edges. The segmented image refers to an image obtained after segmentation according to the edge contour.

[0047] S5. Extract segmented images from the segmented image set in sequence, and perform feature extraction on the extracted segmented images to obtain grain diameter, phase ratio and defect area, and collect the grain diameter, phase ratio and defect area respectively to obtain a grain diameter set, a phase ratio set and a defect area set.

[0048] Interpretable, phase ratio refers to the segmentation image The pixel area of ​​the phase The defect area refers to the area of ​​cracks and holes. Holes refer to voids with a diameter greater than 5 microns. Cracks refer to voids with a width less than 1 micron and a length greater than 10 microns. The grain diameter set refers to the set composed of grain diameters. The phase ratio set refers to the set composed of phase ratios. The defect area set refers to the set composed of defect areas.

[0049] In detail, the feature extraction of the extracted segmented image to obtain the grain diameter, phase ratio and defect area includes: extracting the grain area based on the segmented image, marking the grain area based on the pre-built marking algorithm and the grain area to obtain a marked area set; extracting the marked area from the marked area set, and measuring the size of the extracted marked area to obtain an equivalent diameter, and collecting the equivalent diameters to obtain an equivalent diameter set; calculating the mean of all equivalent diameters in the equivalent diameter set to obtain the grain diameter; obtaining Related phase, general Related Binarization is performed to obtain a first pixel number and a second pixel number; A phase ratio is calculated based on the first number of pixels and the second number of pixels, a defect region is identified from the segmented image, and a defect area is calculated based on the defect region.

[0050] Explainable, grain area refers to The area occupied by the phase grains, the marking algorithm refers to the 8-connectivity marking algorithm, the marked area set refers to the set composed of the marked areas, the marked area refers to the grain area marked by the marking algorithm, and the equivalent diameter refers to the diameter of the grain area. Related Phase Binarization The pixel points occupied by the phase are assigned a value of 1. The pixel points occupied by the phase are assigned a value of 0, which is convenient for calculating the first pixel number and the second pixel number. The equivalent diameter set refers to the set composed of equivalent diameters, the grain diameter refers to the average value of all equivalent means in the equivalent mean set, and the first pixel number refers to The number of pixels occupied by the phase, the second pixel number refers to The number of pixels occupied by the phase.

[0051] S6. Calculate the average grain diameter, average phase ratio and average area based on the grain diameter set, phase ratio set and defect area set.

[0052] It can be explained that the average grain diameter refers to the average value of all grain diameters in the grain diameter set, the average phase ratio refers to the average value of all phase ratios in the phase ratio set, and the average area refers to the average value of all defect areas in the defect area set.

[0053] S7, comparing the average grain diameter, average phase ratio and average area with a preset grain diameter threshold, a preset phase ratio threshold and a preset area threshold, respectively.

[0054] It can be explained that the grain diameter threshold, phase ratio threshold and area threshold refer to thresholds set artificially for determining the average grain diameter, average phase ratio and average area respectively.

[0055] S8. If it is confirmed that the average grain diameter, average phase ratio and average area are respectively less than or equal to the grain diameter threshold, phase ratio threshold and area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report.

[0056] It can be explained that the correct analysis report refers to the report generated when the average grain diameter, average phase ratio and average area are all less than or equal to the grain diameter threshold, phase ratio threshold and area threshold. The correct analysis report includes the average grain diameter, average phase ratio and average area, and marks that the titanium alloy structure is within the normal range.

[0057] S9. If it is confirmed that the average grain diameter, average phase ratio and average area are not less than or equal to the grain diameter threshold, phase ratio threshold and area threshold respectively, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

[0058] It can be explained that the error analysis report refers to the report generated when the average grain diameter, average phase ratio and average area are less than or equal to the grain diameter threshold, phase ratio threshold and area threshold. The error analysis report includes the average grain diameter, average phase ratio and average area, and marks that the titanium alloy structure is not within the normal range and the titanium alloy needs to be adjusted.

[0059] The present invention solves the problems described in the background technology. Firstly, a detection and analysis instruction is received, and an image acquisition unit is started based on the detection and analysis instruction. The image acquisition unit is automatically started by receiving the detection and analysis instruction, so as to realize automatic triggering of the detection process, reduce the possibility of errors in manual operation, and can quickly respond to detection needs, thereby improving the continuity and efficiency of the detection process; secondly, a heat treatment is performed on the titanium alloy to be tested based on the processing temperature, processing time and cooling rate. By presetting the processing temperature, processing time and cooling rate, the consistency of the heat treatment is ensured, and the deviation caused by parameter fluctuation is reduced; thirdly, the cooled titanium alloy is polished and corroded to obtain a treated titanium alloy. The polishing and corrosion treatments make the surface of the cooled titanium alloy smooth and reveal the real grain boundaries, phase boundaries and defects, thereby providing a reliable basis for subsequent image acquisition; thereafter, the collected image set is All the collected images in the method are preprocessed to obtain a processed image set, and the preprocessing steps include: global denoising and local denoising. By preprocessing the collected images, the noise in the collected images is effectively reduced, making the grain boundaries, phase boundaries and defects more obvious, and improving the accuracy of subsequent image segmentation and feature extraction; further, the processed images are segmented to obtain segmented images, and edge detection is performed using edge detection algorithms, low grayscale parameters and high grayscale parameters to obtain edge contour sets, and then image segmentation is performed based on the edge contour sets to obtain segmented images, which improves the accuracy and efficiency of image segmentation and provides a reliable basis for subsequent feature extraction; finally, feature extraction is performed on the segmented images to obtain grain diameter, phase ratio and defect area. Through feature extraction, the state of titanium alloy organization can be quantitatively described to provide accurate data. Therefore, the present invention can improve the accuracy of titanium alloy organization detection.

[0060] like Figure 2, which is a functional module diagram of a titanium alloy structure detection and analysis system based on heat treatment provided by an embodiment of the present invention.

[0061] The titanium alloy tissue detection and analysis system 100 based on heat treatment of the present invention can be installed in an electronic device. According to the functions to be implemented, the titanium alloy tissue detection and analysis system 100 based on heat treatment can include an image acquisition module 101, a feature extraction module 102, a mean calculation module 103 and a report generation module 104. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0062] The image acquisition module 101 is used to receive the detection and analysis instructions, and start the pre-confirmed image acquisition unit based on the detection and analysis instructions; obtain the titanium alloy to be tested, and perform heat treatment on the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time and a preset cooling rate to obtain a cooled titanium alloy; perform polishing and corrosion treatment on the cooled titanium alloy to obtain a treated titanium alloy, and perform image acquisition operations on the treated titanium alloy based on the started image acquisition unit to obtain a collection of collected images, and pre-process all collected images in the collection of collected images to obtain a processed image set; the feature extraction module 102 is used to sequentially extract processed images from the processed image set, and perform image segmentation on the extracted processed images to obtain segmented images, and collect the segmented images to obtain a segmented image set; sequentially extract segmented images from the segmented image set, and perform feature extraction on the extracted segmented images to obtain grain diameter, phase ratio and defect area, and collect them respectively; The grain diameter, phase ratio and defect area are collected to obtain a grain diameter set, a phase ratio set and a defect area set; the mean calculation module 103 is used to respectively calculate the average grain diameter, the average phase ratio and the average area based on the grain diameter set, the phase ratio set and the defect area set; the report generation module 104 is used to respectively compare the average grain diameter, the average phase ratio and the average area with a preset grain diameter threshold, a preset phase ratio threshold and a preset area threshold; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

[0063] In detail, the modules in the titanium alloy structure detection and analysis system 100 based on heat treatment in the embodiment of the present invention are used in the same manner as described above. Figure 1The same technical means as the titanium alloy structure detection and analysis method based on heat treatment described in the text can produce the same technical effects, so they will not be repeated here.

[0064] like Figure 3 , which is a schematic diagram of the structure of an electronic device for implementing a method for detecting and analyzing titanium alloy structure based on heat treatment provided by an embodiment of the present invention.

[0065] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a titanium alloy structure detection and analysis method program based on heat treatment.

[0066] Wherein, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 also includes an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the titanium alloy structure detection and analysis method program based on heat treatment, but also can be used to temporarily store data that has been output or is to be output.

[0067] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules (such as a titanium alloy structure detection and analysis method program based on heat treatment, etc.) stored in the memory 11, and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0068] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0069] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0070] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0071] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0072] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0073] The titanium alloy tissue detection and analysis method program based on heat treatment stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve: receiving the detection and analysis instruction, starting the pre-confirmed image acquisition unit based on the detection and analysis instruction; obtaining the titanium alloy to be tested, and heat-treating the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time and a preset cooling rate to obtain a cooled titanium alloy; performing polishing and corrosion treatment on the cooled titanium alloy to obtain a treated titanium alloy, performing image acquisition operations on the treated titanium alloy based on the started image acquisition unit to obtain a collection image set, pre-processing all the collected images in the collection image set to obtain a processed image set; extracting processed images from the processed image set in sequence, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set; extracting the segmented images from the segmented image set in sequence, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set; The extracted segmented image is subjected to feature extraction to obtain the grain diameter, phase ratio and defect area, and the grain diameter, phase ratio and defect area are respectively collected to obtain the grain diameter set, phase ratio set and defect area set; the average grain diameter, average phase ratio and average area are respectively calculated based on the grain diameter set, phase ratio set and defect area set; the average grain diameter, average phase ratio and average area are respectively compared with the preset grain diameter threshold, the preset phase ratio threshold and the preset area threshold; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

[0074] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0075] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0076] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor of an electronic device, it can achieve the following: receiving a detection and analysis instruction, and starting a pre-confirmed image acquisition unit based on the detection and analysis instruction; obtaining a titanium alloy to be tested, and heat-treating the titanium alloy to be tested based on a preset processing temperature, a preset processing time, and a preset cooling rate to obtain a cooled titanium alloy; performing a polishing and corrosion treatment on the cooled titanium alloy to obtain a processed titanium alloy, performing an image acquisition operation on the processed titanium alloy based on the started image acquisition unit to obtain a collected image set, and pre-processing all collected images in the collected image set to obtain a processed image set; extracting processed images from the processed image set in sequence, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set; extracting segmented images from the segmented image set in sequence, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set; extracting segmented images from the segmented image set in sequence, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set. The segmented image is used for feature extraction to obtain the grain diameter, phase ratio and defect area, and the grain diameter, phase ratio and defect area are respectively collected to obtain the grain diameter set, phase ratio set and defect area set; the average grain diameter, average phase ratio and average area are respectively calculated based on the grain diameter set, phase ratio set and defect area set; the average grain diameter, average phase ratio and average area are respectively compared with the preset grain diameter threshold, the preset phase ratio threshold and the preset area threshold; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

[0077] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation may have other division methods.

[0078] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0080] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A titanium alloy structure detection and analysis method based on heat treatment, characterized in that: The method comprises: receiving a detection and analysis instruction, and starting a pre-confirmed image acquisition unit based on the detection and analysis instruction; obtaining a titanium alloy to be tested, and performing a heat treatment on the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time and a preset cooling rate to obtain a cooled titanium alloy; performing a polishing and corrosion treatment on the cooled titanium alloy to obtain a treated titanium alloy, and performing an image acquisition operation on the treated titanium alloy based on the started image acquisition unit to obtain a collection image set, and pre-processing all the collection images in the collection image set to obtain a processed image set; sequentially extracting processed images from the processed image set, and performing image segmentation on the extracted processed images to obtain segmented images, and collecting the segmented images to obtain a segmented image set; sequentially extracting segmented images from the segmented image set, and performing feature extraction on the extracted segmented images to obtain grain diameter, phase ratio and defect area , respectively collect the grain diameter, phase ratio and defect area to obtain the grain diameter set, phase ratio set and defect area set; calculate the average grain diameter, average phase ratio and average area based on the grain diameter set, phase ratio set and defect area set; compare the average grain diameter, average phase ratio and average area with the preset grain diameter threshold, the preset phase ratio threshold and the preset area threshold respectively; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

2. The titanium alloy structure detection and analysis method based on heat treatment according to claim 1, characterized in that: The method of polishing and corroding the cooled titanium alloy to obtain the treated titanium alloy includes: placing the cooled titanium alloy in a pre-acquired cleaning solution, setting a cleaning time, and performing a cleaning operation on the cooled titanium alloy based on the cleaning time and the cleaning solution to obtain a cleaned titanium alloy; obtaining a first sandpaper and a second sandpaper; calculating a grinding time, and performing a grinding operation on the cleaned titanium alloy using the first sandpaper, the grinding time, and a preset first-level grinding pressure to obtain a pre-polished titanium alloy; grinding the pre-polished titanium alloy using the second sandpaper, the grinding time, and a preset second-level grinding pressure to obtain a finely ground titanium alloy; based on the pre-acquired The fine-ground titanium alloy is polished with a diamond suspension to obtain a preliminary polished titanium alloy, and the polishing completion of the preliminary polished titanium alloy is calculated; the polishing completion is compared with a preset completion threshold; when the polishing completion is less than the completion threshold, the fine-ground titanium alloy is updated with the preliminary polished titanium alloy, and the updated fine-ground titanium alloy is used to return to the above step of polishing the fine-ground titanium alloy based on the pre-acquired diamond suspension; when the polishing completion is greater than or equal to the completion threshold, the preliminary polished titanium alloy is confirmed as a polished titanium alloy; the polished titanium alloy is chemically corroded to obtain a processed titanium alloy.

3. The titanium alloy structure detection and analysis method based on heat treatment according to claim 2, characterized in that: The calculating of the grinding time includes: setting a basic grinding time and a standard titanium alloy area, obtaining the titanium alloy area of ​​the cleaned titanium alloy, and calculating the grinding time based on the basic grinding time, the standard titanium alloy area and the titanium alloy area: ,in, Refers to the grinding time, Refers to the basic polishing time, Refers to the preset adjustment parameters, Refers to the titanium alloy area, Refers to the standard titanium alloy area.

4. The titanium alloy structure detection and analysis method based on heat treatment according to claim 3, characterized in that: The method of performing an image acquisition operation on the processed titanium alloy based on the started image acquisition unit to obtain a captured image set includes: setting a first acquisition multiple, a second acquisition multiple and a third acquisition multiple; performing an image acquisition operation on the processed titanium alloy based on the first acquisition multiple, the second acquisition multiple, the third acquisition multiple, the image acquisition unit and a preset number of acquisition times to obtain a first acquisition image set, a second acquisition image set and a third acquisition image set, wherein the first acquisition image set corresponds to the first acquisition multiple, the second acquisition image set corresponds to the second acquisition multiple, and the third acquisition image set corresponds to the third acquisition multiple; and collecting the first acquisition image set, the second acquisition image set and the third acquisition image set to obtain a acquisition image set.

5. The titanium alloy structure detection and analysis method based on heat treatment according to claim 4, characterized in that: The method preprocesses all collected images in the collected image set to obtain a processed image set, including: calculating a comprehensive noise level value based on the collected image set, and setting a filtering standard deviation according to the comprehensive noise level value; performing a global noise reduction operation on all collected images in the collected image set according to the filtering standard deviation to obtain a global image set; setting a window size, and performing local denoising on the global image set based on the window size to obtain a processed image set.

6. The titanium alloy structure detection and analysis method based on heat treatment according to claim 5, characterized in that: The method for calculating the comprehensive noise level value based on the acquired image set includes: setting a regional horizontal value and a regional vertical value based on the acquired image set, and setting multiple detection areas according to the regional horizontal value and the regional vertical value; calculating the regional standard deviation of the multiple detection areas, and performing a mean calculation operation on the calculated regional standard deviation to obtain a regional mean; decomposing the acquired image set based on a preset discrete transformation method to obtain a high-frequency sub-band set; extracting high-frequency sub-bands from the high-frequency sub-band set in sequence, and performing statistics on the extracted high-frequency sub-bands to obtain robust statistics, and aggregating the robust statistics to obtain a robust statistics set; performing a mean calculation operation on all robust statistics in the robust statistics set to obtain a statistical mean; and calculating the comprehensive noise level value based on the regional mean and the statistical mean.

7. The titanium alloy structure detection and analysis method based on heat treatment according to claim 6, characterized in that: The setting of the filtering standard deviation according to the comprehensive noise level value includes: obtaining a low noise standard deviation and a low noise reference value, and calculating the filtering standard deviation based on the comprehensive noise level value, the low noise standard deviation and the low noise reference value: ,in, refers to the filtering standard deviation, refers to the low noise standard deviation, Refers to the comprehensive noise level value, Refers to the low noise reference value, Refers to the preset noise adjustment parameters.

8. The titanium alloy structure detection and analysis method based on heat treatment according to claim 7, characterized in that: The method of performing image segmentation on the extracted processed image to obtain a segmented image includes: obtaining an image grayscale mean value of the processed image, setting a low grayscale parameter and a high grayscale parameter based on the image grayscale mean value, wherein the low grayscale parameter is 0.4 times the image grayscale mean value, and the high grayscale parameter is 1.6 times the image grayscale mean value; performing edge detection using a pre-built edge detection algorithm, a low grayscale parameter, and a high grayscale parameter to obtain an edge contour set; and segmenting the processed image based on edge contours in the edge contour set to obtain a segmented image.

9. The titanium alloy structure detection and analysis method based on heat treatment according to claim 8, characterized in that: The method of extracting features from the extracted segmented image to obtain grain diameter, phase ratio and defect area includes: extracting grain regions based on the segmented image, marking the grain regions based on a pre-built marking algorithm and the grain regions to obtain a marked region set; extracting marked regions from the marked region set, measuring the size of the extracted marked regions to obtain equivalent diameters, and collecting the equivalent diameters to obtain an equivalent diameter set; calculating the mean of all equivalent diameters in the equivalent diameter set to obtain grain diameters; and obtaining Related phase, general Related The phase is binarized to obtain a first pixel number and a second pixel number; a phase ratio is calculated based on the first pixel number and the second pixel number, a defect region is identified from the segmented image, and a defect area is calculated based on the defect region.

10. A titanium alloy structure detection and analysis system based on heat treatment, characterized in that: The system includes: an image acquisition module, which is used to receive a detection and analysis instruction, and start a pre-confirmed image acquisition unit based on the detection and analysis instruction; obtain a titanium alloy to be tested, and perform heat treatment on the titanium alloy to be tested based on a preset treatment temperature, a preset treatment time and a preset cooling rate to obtain a cooled titanium alloy; perform polishing and corrosion treatment on the cooled titanium alloy to obtain a treated titanium alloy, and perform image acquisition operations on the treated titanium alloy based on the started image acquisition unit to obtain a collection of collected images, and pre-process all collected images in the collection of collected images to obtain a collection of processed images; a feature extraction module, which is used to sequentially extract processed images from the collection of processed images, and perform image segmentation on the extracted processed images to obtain segmented images, and collect the segmented images to obtain a collection of segmented images; sequentially extract segmented images from the collection of segmented images, and perform feature extraction on the extracted segmented images to obtain grain diameter, phase ratio and defect area , respectively collect the grain diameter, phase ratio and defect area to obtain the grain diameter set, phase ratio set and defect area set; the mean calculation module is used to calculate the average grain diameter, average phase ratio and average area based on the grain diameter set, phase ratio set and defect area set; the report generation module is used to compare the average grain diameter, average phase ratio and average area with the preset grain diameter threshold, the preset phase ratio threshold and the preset area threshold respectively; if it is confirmed that the average grain diameter, the average phase ratio and the average area are respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, a correct analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the correct analysis report; if it is confirmed that the average grain diameter, the average phase ratio and the average area are not respectively less than or equal to the grain diameter threshold, the phase ratio threshold and the area threshold, an error analysis report is generated, and the titanium alloy microstructure detection and analysis is completed based on the error analysis report.

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