KR100716902B1 - Metal Damage Assessment System and Metal Damage Assessment Method Using The Same - Google Patents

Abstract

The present invention relates to a metal damage assessment system and a metal damage assessment method using the same, and more particularly, computer image processing for the degree of damage of metal tissues in place of the conventional metal damage evaluation methods evaluated based on visual observation. By developing and using a system for quantitative analysis using a device, the present invention relates to a metal damage evaluation system capable of improving the objectivity and reliability of damage evaluation and ensuring accuracy, and a method for assessing metal damage using the same.

Metal damage assessment system, grain deformation method, tissue preparation method, precipitate inspection method, grain boundary method

Description

The damage evaluation system of metal and the damage evaluation method of metal using the same}

1 is a block diagram of a metal structure damage evaluation system according to an embodiment of the present invention

Figure 2a is an algorithm of the metal damage evaluation method by the grain deformation method of metal damage evaluation method according to the present invention

2B is a screen diagram in which the algorithm of FIG. 2A is implemented on a computer.

Figure 3a is an algorithm of the metal damage evaluation method by the metal structure damage evaluation method or the precipitate inspection method of the metal structure damage evaluation method according to the present invention

3B is a screen diagram of a computer implemented algorithm using the tissue contrast method of FIG. 3A.

3C is a screen diagram of a computer implemented algorithm of the precipitate inspection method of FIG. 3A.

Figure 4a is an algorithm of the metal damage evaluation method by the grain boundary method of the metal damage evaluation method according to the present invention

4B is a screen diagram in which the algorithm of FIG. 4A is implemented on a computer.

<Description of Symbols for Main Parts of Drawings>

10-Input Module 20-Image Processing Module

30-Metallographic Database 40-Metallographic Evaluation Module

50-output module 100-metal damage assessment system

S210, S310, S410-Image input step

S220, S320, S420-Image Cleaning Step

S230, S330, S430-data conversion stage

S250, S340-Measuring stage

S260, S350, S450-Evaluation Level

S270, S360, S460-Output Stage

The present invention relates to a metal damage assessment system and a metal damage assessment method using the same, and more particularly, computer image processing for the degree of damage of metal tissues in place of the conventional metal damage evaluation methods evaluated based on visual observation. By developing and using a system for quantitative analysis using a device, the present invention relates to a metal damage evaluation system capable of improving the objectivity and reliability of damage evaluation and ensuring accuracy, and a method for assessing metal damage using the same.

Thermal power plants and chemical plant facilities operating in Korea are used for a long time under high temperature and high pressure operating conditions. Therefore, it is essential to secure safety by evaluating the deterioration and the degree of damage. The materials used to manufacture power plants and petrochemical machinery are designed to be used at high temperatures, but when used at high temperatures for a long time, the material strength drops below the design strength, providing a cause of damage. In addition, mechanical damages due to thermal stress and high pressure stress caused by start-up also accumulate inside the material and damage the equipment when certain standards are reached. Therefore, in order to secure the stability of the equipment, accurate deterioration degree and damage assessment should be performed for materials whose strength decreases with long-term use at high temperatures.

Factors that cause material deterioration include high temperature operating conditions, excessive operating time, load conditions, and corrosion of machinery. In general, these factors work in combination to promote deterioration of equipment. Especially in the case of thermal power plants, the deterioration of the mechanical equipment due to material deterioration is prominent in steam boiler pipes, headers, tubes and steam turbine rotors, casings, blades, etc. There is a need for securing standardization techniques for evaluation.

At present, the damage evaluation of materials used at high temperature uses a method of surface replication of a damaged material on a plastic film, followed by visual observation through a microscope. This evaluation method can vary greatly according to the individual's ability and experience, so a systematic and objective damage diagnosis system is required, and it is necessary to accurately evaluate the damage of metal tissue using quantitative analysis method.

The technology for evaluating the remaining life of equipment operating in high temperature environment is actively progressed in US EPRI and developed countries, and has been applied to technology development and power plants since 1993 in Korea. The damage assessment of metal tissues, which is an important criterion for evaluating the life of power plants and petrochemical plants, is evaluated after visual observation of specimens and surface coatings of metal tissues through optical and electron microscopes. Rely entirely on knowledge and experience. In order to ensure the accuracy of the damage assessment, only those who have been in the metal damage assessment field for more than 10 years can evaluate it. Despite the fact that the evaluation results must be reproducible, evaluation is made by the difference in evaluation methods and skills among professional evaluators. There is a difference in the results. Therefore, more objective and credible evaluation is urgently needed from the point of view of the facility operator who needs to invest hundreds of billions to billions of dollars in the maintenance and replacement of damaged equipment to prevent breakage.

The present invention has been made to solve the above problems, and in particular, a system for quantitatively analyzing the damage of metal tissue using a computer image processing device in place of the existing metal damage evaluation method which was evaluated based on visual observation. The purpose of this study is to provide a metal damage assessment system and a metal damage assessment method using the same, which can improve the objectivity and reliability of the damage assessment and ensure accuracy.

In order to solve the above problems, the metal tissue damage evaluation system of the present invention includes an input module for inputting an image observed by at least one of an optical microscope and an electron microscope, or a scanned metal texture photograph; An image processing module for automatically or manually measuring characteristics of the metal texture input by the input module using an image processing apparatus; A metal structure database in which the shape change of the metal structure according to the mechanism and process of deterioration of the metal material used at a high temperature, and the standard structure of the steady state metal material and the damage evaluation result of the metal structure are stored; A metal texture evaluation module for analyzing and evaluating metal textures by comparing the characteristics of metal textures measured by the image processing module with data stored in the metal texture database by a metal texture evaluation algorithm; And an output module for outputting a result evaluated by the metallographic evaluation module.

At this time, the image processing module analyzes the long axis and short axis measurement and distribution of grains, measures the number of grain boundary pores in a specific cross section of the metal material, or the area ratio or carbide occupied by carbide present in the metal structure. It may be performed to measure the degree of circularization, to measure the gap and dispersion between carbides, or to measure the size and the distance between the precipitates in the metal structure.

In addition, the metal structure damage evaluation method according to the present invention comprises an image input step of inputting an image of the metal texture; A data conversion step of converting an image input through the image input step into binary data; A measurement step of measuring numerical values representing characteristics of the metal structure damaged by the data converted through the data conversion step; An evaluation step of analyzing the quantified value through the measuring step and diagnosing the degree of creep damage by comparing with a standard tissue; And an output step of outputting the result of the evaluation step to an output means including an image or a printed matter.

In addition, the metal structure damage evaluation method according to the present invention may further comprise an image cleaning step of cleaning the image input through the image input step to the image of the metal texture including the grain boundary using a plurality of filters. have.

In addition, the metal structure damage evaluation method according to the present invention further includes an extraction step for extracting the crystal grains transformed into the data converted through the data conversion step, the measuring step is to measure the long axis and short axis of the crystal grains and It may be a metal structure damage evaluation method by the grain modification method to be prepared.

In addition, the metal damage assessment method according to the present invention is the step of measuring the area ratio or the degree of carbide rounding occupied by the carbide (carbide) present in the metal structure, or measuring the gap and dispersion between carbides It may be a metal tissue damage evaluation method by a tissue preparation method characterized in that.

In addition, the metal damage assessment method according to the invention may be a metal damage assessment method by the precipitate inspection method, characterized in that the step of measuring the size and the distance between the precipitates present in the metal structure.

In addition, the metal damage assessment method according to the present invention may be a metal damage assessment method by the grain boundary method, characterized in that the measuring step is to measure the number of pores generated in the grain boundary of the metal structure.

In addition, the metal damage assessment method according to the present invention performs the evaluation by the above steps for each of the grain deformation method, tissue contrast method, precipitate inspection method and grain boundary method, each of the results calculated by the four evaluation methods The method may be a method of evaluating a comprehensive damage degree of a metal structure by adding a weight to and then combining the evaluation results in which the weight is reflected.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

First, a metal structure damage evaluation system according to an embodiment of the present invention will be described. Figure 1 shows the configuration of a metal structure damage evaluation system according to an embodiment of the present invention.

In the metal tissue damage evaluation system 100 according to the embodiment of the present invention, referring to FIG. 1, the input module 10, the image processing module 20, the metal texture database 30, and the metal texture evaluation module 40 are described. And an output module 50.

The input module 10 is a portion in which an image observed by a metal microscope or an electron microscope is directly input or a scanned metallographic image is input. In this case, the input module 10 first obtains a replica by replicating a damaged part of a material from a field facility using a plastic film, and observes the replica through a light microscope and / or an electron microscope. You get a picture of the organization. Thereafter, the tissue picture is stored in the metallographic database 40 to be used in the image processing module 20. On the other hand, the input module 10, instead of observing the replicate tissue through a microscope to input the metal damage assessment system 100, if there is a tissue picture of the metal tissue to be evaluated by scanning such a tissue picture Of course, the metal damage assessment system 100 may be input. In addition, the input module 10 may be used to directly collect a small amount of the specimen from the field equipment to be evaluated instead of using the replication tissue.

The image processing module 20 is a portion for automatically or manually measuring the characteristics of the metal texture input by the input module 10 using an image processing apparatus. At this time, the image processing module 20 analyzes the long axis and short axis measurement and distribution of grains, measures the number of grain boundary pores in a specific cross section of the metal material, or the area occupied by carbides present in the metal structure. It is formed to measure the degree or degree of rounding of carbides, to measure the gap and dispersion between carbides, or to measure the size and the distance between precipitates in the metal structure. In addition, the image processing module 20 may perform an operation of cleaning an image of a metal texture including grain boundaries by using a plurality of filters on the image input by the input module 10. At this time, the cleaning operation may be performed using a median filter to sharpen grain boundaries and precipitates. The cleaning operation clearly reveals the contrast within the grains of the metal structure and the grain boundaries, and measures specific values of grain boundaries, precipitates, pores, and the like. In addition, the image processing module 20 may convert the cleaned image data into binary data and convert the image data into data that a computer can understand and work with.

The metallographic database 30 is a portion in which the shape change of the metallographic structure according to the mechanism and the process of deterioration of the metallized material used at high temperature, and the results of damage assessment of the metallographic structure and the standard structure of the metallographic material are stored. That is, the metallographic database 30 stores data on the standard tissue in a normal state for the damage evaluation of the metallographic structure, and the result evaluated by the metallographic evaluation module 40 is stored so that such data are needed. It's built to be accessible anytime. The data on the standard tissues are compared with the data on the damaged tissues and serve as a basis for calculating the degree of damage of the metal structure to be evaluated, and the data on the evaluation results are referred to when evaluation of other specimens is made later. It will be used as data.

The metal structure evaluation module 40 analyzes the metal structure by comparing the characteristics of the metal structure measured by the image processing module 20 with data stored in the metal structure database 30 by a metal structure evaluation algorithm. It is part of the evaluation. The metal texture evaluation algorithm analyzes a characteristic factor for evaluating the damage degree of the metal structure by the expert and evaluates the damage degree through data numerically quantified by the image processing module 20. The evaluation method used in the metal structure evaluation module 40 includes a damage evaluation method by a grain deformation method, a damage evaluation method by a tissue contrast method, a damage evaluation method by a precipitation inspection method, a damage evaluation method by a grain boundary method, and the like. have. Hereinafter, the four metal tissue damage evaluation methods will be described in sequence.

In the damage evaluation method using the grain modification method, the damage of the metal structure is evaluated by quantifying the degree of deformation of the grains to diagnose creep damage. Low-flammable materials, such as welds or stainless steel, which have a high grain strength and are difficult to deform in the grain, are deformed at grain boundaries. Therefore, pores are generated in the grain boundaries from about half of the life. The degree can be diagnosed. However, high-combustibility materials, such as chromium-molybdenum (Cr-Mo) steel, which tend to deform crystal grains, make pores first appear at the end of their lifespan, thereby making life assessment difficult by measurement of pores difficult. Therefore, the high ductility material calculates the degree of deformation of the grains by comparing the long and short axis lengths and the distribution of the grains measured by the image processing module 20 with the standard tissues stored in the metallographic database 30. Damage will be assessed.

The damage assessment method using the tissue contrast method is a method applying the theory that carbides existing in the metal tissues aggregate with each other to reduce the area occupied within the tissues due to long-term use at high temperatures and deteriorated tissues. The damage assessment method using the tissue contrast method evaluates the degree of damage by comparing the area ratio occupied by carbide in the tissue obtained by surface replication through the input module 10 and the area ratio occupied by carbide in the standard tissue. At this time, the carbide is clearly displayed in black during image processing by the image processing module 20, so that it is clearly distinguished from other parts.

The damage evaluation method using the precipitate inspection method evaluates the use temperature of the material and the degree of damage by using the distance between the precipitates and the size of the precipitates measured by the image processing module 20. Creep strength is influenced by finely dispersed precipitates, and the metal material causes transformation and coarsening of precipitates when used for a long time at high temperature. Therefore, the size of the precipitate or the distance between the precipitates can be utilized as a damage assessment tool. Damage assessment by the precipitate inspection method is to use the following [Equation 1] and [Equation 2].

[Equation 1] d ³  = Kt

(d is mean diameter of precipitate, t is operating time, K is proportional constant)

[Equation 2] ln  K = 5.99 × 10 ^-2 T + ln  (3.25 × 10 ^-42 )

(T is absolute temperature)

[Equation 1] quantitatively shows the relationship between the average diameter of the precipitate and the operating time of the facility. In addition, [Equation 2] quantitatively shows the relationship between the absolute temperature and the proportional constant in which the equipment is operated. Therefore, when the average diameter of the precipitate is measured through the image processing module 20 and the time the facility is operated up to now is calculated, the absolute temperature of the facility being operated is calculated. Using the calculated absolute temperature, the size of the precipitate and the distance between the precipitates it is possible to evaluate the damage of the metal structure.

The damage evaluation method using the grain boundary pore method is a method of measuring damage by measuring pores generated in grain boundaries of metal structures when creep damage occurs. At this time, the method of measuring the pores may be used the A-Parameter method, which is a method of quantitatively indicating the number of pores generated in the grain boundary to evaluate the damage. Since the A-Parameter method is well known to those skilled in the art, a detailed description thereof will be omitted.

The output module 50 is a part for outputting the result evaluated by the metallographic evaluation module 40, which may be output by a display method such as a monitor, or may be output by printed matter. Here, the output method of the output module 50 is not limited.

Next, the metal structure damage evaluation method according to the present invention will be described.

FIG. 2A illustrates an algorithm of a metal damage evaluation method by a grain deformation method of a metal damage evaluation method according to the present invention, and FIG. 2B illustrates a screen on which a computer of the algorithm of FIG. 2A is implemented. FIG. 3A illustrates an algorithm of a metal damage evaluation method using a tissue contrast method or a metal damage evaluation method using a precipitate inspection method among metal damage evaluation methods according to the present invention, and FIG. 3B is an algorithm based on the tissue contrast method shown in FIG. 3A. The screen implemented on this computer is shown, and FIG. 3C shows the screen implemented on the computer by the algorithm according to the precipitate inspection method of FIG. 3A. Figure 4a shows an algorithm of the metal damage assessment method by the grain boundary method of the metal damage damage method according to the present invention, Figure 4b shows a screen in which the algorithm of Figure 4a is implemented on a computer.

The method for evaluating metal structure damage (hereinafter, referred to as a first method) by the grain deformation method, referring to FIG. 2A, an image input step S210, a data conversion step S230, a measurement step S250, and an evaluation step It includes the step (S260) and the output step (S270). In addition, the first method may further include an image cleaning step S220 and a color extraction step S240.

The image input step S210 may be performed by the input module 10. The image input step S210 is a step in which an image observed by an optical microscope and / or an electron microscope is directly input to a wound wound device, or a scanned metallographic image is input to an image processing device. In addition, the image input step (S210) as described above may be observed by a microscope to extract the specimen directly from the facility. The image input through the image input step S210 is passed to the image cleaning step S220 for clear contrast.

The image cleaning step S220 may be performed by the image processing module 20. The image cleaning step S220 includes a grain boundary using a plurality of filters on the image input from the image input step S210. This is the step of cleaning the image of the metallization. At this time, the cleaning operation may be performed using a median filter to sharpen grain boundaries and precipitates. In the image cleaning step (S220), referring to FIG. 2B, a tissue picture before performing a cleaning operation is displayed in a source image window in the upper left of the screen, and a tissue after performing the cleaning operation in a threshold image window in the lower left of the screen. The picture will appear. In addition, the image cleaning step (S220) can adjust the color or brightness of the cleaned screen through the HISTOGRAM on the upper right of the screen. The minimum value (min) and the maximum value (max) at the bottom of the HISTOGRAM are the minimum brightness and the maximum brightness of the cleaned screen. By the cleaning, the contrast within the grains and grain boundaries of the metal structure is clearly revealed, so that specific values of grain boundaries, precipitates, pores, etc. are measured in the measuring step S250.

The data conversion step S230 may be performed by the image processing module 20. The data conversion step S230 is a step of converting the image data cleaned through the image cleaning step S220 into binary data and converting the image data into data that a computer can understand and work with.

The color extraction step S240 may be performed by the image processing module 20. The extraction step (S240) is a step of extracting the crystal grains modified using the data converted through the data conversion step (S230). In order to evaluate the degree of deformation of grains, it is convenient to distinguish between grains of normal tissue and damaged grains. However, in some cases, the extraction step (S240) may be made collectively prior to the measurement of the size of the crystal grains in the measurement step (S250). In the extracting step (S240), referring to FIG. 2B, the number of found crystal grains is displayed in the Particle Information column at the bottom right of the screen.

The measuring step S250 may be performed by the image processing module 20. The measuring step (S250) is a step of measuring the long axis and short axis of the crystal grains and creating a distribution chart, which is a basis for analyzing how much deformation occurred in which direction by measuring the length of the long axis and short axis of the crystal grains. to be. In addition, the measurement step (S250) is a distribution chart is created through the length of the long axis and short axis of the measured grains, the evaluation step (S260) is a step that can be compared to the degree of distribution of the standard tissue. In the measuring step (S250), referring to Figure 2b, the ratio between the long axis and the short axis relative to the standard tissue is shown in the Orientation Histogram column on the bottom right of the screen. In addition, in the measuring step (S250), the Life Rraction (life ratio) is calculated at the bottom of the Orientation Histogram so that the ratio of the remaining life to the total life is expressed in the form of a percentage (%).

The evaluation step (S260) may be performed in the metal structure evaluation module 40. The evaluation step (S260) is a step of diagnosing the degree of creep damage by analyzing the numerical value quantified through the measurement step (S250), that is, the length and distribution of the major and minor axes of the crystal grains and comparing them with the standard tissue. Content evaluated through the evaluation step (S260) is a basis for evaluating the degree of deterioration of the facility, it is possible to calculate the repair time or replacement time of the facility according to the result. In the evaluation step (S260), referring to Figure 2b, the evaluation result is confirmed through the assessment on the lower right of the screen.

The output step S270 may be performed by the output module 50. The output step (S270) is a part for outputting the result evaluated by the evaluation step (S260), it may be output by a display method such as a monitor, and may be output as a print as described above.

The metal tissue damage evaluation method (hereinafter referred to as the second method) by the tissue contrast method and the metal structure damage evaluation method (hereinafter referred to as the third method) by the precipitate inspection method are referred to as FIG. It includes a step S310, a data conversion step S330, a measurement step S340, an evaluation step S350, and an output step S360. In addition, the second method or the third method may further comprise an image cleaning step (S320). Since the image input step S310, the data conversion step S330 and the output step S360 are similar to the first method, detailed description thereof will be omitted. Since the second method and the third method are performed through similar steps, they will be described here for convenience.

In the image cleaning step (S320) of the second method or the third method, the image input from the image input step (S310) is performed using a plurality of filters to clean an image of a metal structure including grain boundaries. As such, the cleaning operation may be performed using a median filter to sharpen precipitates, including grain boundaries and carbides. In the image cleaning step (S320) of the second method, referring to FIG. 3B, a tissue photograph before performing a cleaning operation is displayed in a source image window in the upper left of the screen, and the filter-processed image window in the lower left of the screen is displayed. The organization picture after the cleaning operation is displayed. Since the carbides appear black in image processing, it is easy to calculate the area ratio of carbides to the entire tissue. In addition, in the image cleaning step S320 of the third method, referring to FIG. 3C, a picture of the entire tissue including the precipitate before the cleaning operation is displayed in the Source Image window on the upper left of the screen. In the Threshold Image window, a tissue photograph after the cleaning operation is displayed. The function of the HISTOGRAM column on the upper right side of the screen is the same as that described in the first method.

The measuring step (S340) in the second method is a step of measuring the area ratio occupied by the carbide (carbide) existing in the metal structure or the degree of rounding of the carbide, or the gap and dispersion between the carbides. In the measuring method (S340) of the second method, referring to FIG. 3B, a contrast ratio indicating a area of measurement (Region of Interest) and the proportion of carbides in the total area in the Analysis Report column at the bottom right of the screen. And Class will appear. In addition, referring to FIG. 3C, the measurement step (S340) of the third method includes a distance nearest neighbor, a life fraction and a spheroidization rate in the Analysis Report column at the bottom right of the screen. The measurement results are displayed in the (Sph. Rate) column.

The evaluation step (S350) in the second method is to analyze the numerical value quantified through the measurement step (S340), that is, the area ratio of carbides, the degree of carbide rounding, the gap and dispersion between carbides and compared with the standard structure This step is to diagnose the degree of creep damage. Evaluation step (S350) in the third method is to evaluate the degree of damage through the remaining life of the facility using the size of the precipitates, the distance between the precipitates and the life ratio measured in the measurement step (S340). The size of the precipitate and the distance between the precipitates are closely related to each other. The larger the precipitate, the greater the distance between the precipitates. The remaining life is calculated through [Equation 1] and [Equation 2]. The content evaluated through the evaluation step (S350) in the second method or the third method is based on the evaluation of the degree of deterioration of the facility. As a result, it is possible to calculate the time of repair or replacement of the equipment. In the evaluation step S350 of the second method or the third method, referring to FIG. 3B or 3C, the evaluation result is confirmed through an evaluation at the bottom right of the screen.

For the metal structure damage evaluation method (hereinafter referred to as a fourth method) by the grain boundary method, referring to FIG. 4A, an image input step S410, a data conversion step S430, and an A-parameter calculation step S440. And an evaluation step (S450) and an output step (S460). In addition, the fourth method may further include an image cleaning step (S420). The image input step (S410), data conversion step (S430), and output step (S460) are similar to the first method, and thus detailed description thereof will be omitted.

The image cleaning step S420 is a step of cleaning an image of a metal structure including grain boundaries and pores using the image input from the image input step S410 using a plurality of filters, and the cleaning operation is performed as a grain boundary. And cleaning may be performed using a median filter to sharpen the pores generated in the grain boundary. In the image cleaning step (S420), referring to FIG. 3C, the tissue picture before cleaning in the Source Image window on the upper left of the screen is shown in the Threshold Image window on the lower left of the screen. The function of the HISTOGRAM column is the same as described in the first method.

The A-parameter calculation step (S440) is a step for quantitatively indicating the number of pores generated in the grain boundary. The A-parameter calculation step S440 is a step corresponding to the measurement steps S250 and S340 of the first to third methods. In the A-parameter calculation step (S440), referring to FIG. 4B, an example of A-parameter calculation in the grain boundary method is shown in an explanation sheet on the upper right side of the screen. In addition, a predetermined inspection rule is displayed at the bottom right of the screen. A-Parameter is calculated according to the following rules. Rule 1 is to observe only between the first boundary triplet on both the straight line and the intersection. If the grain boundary extends beyond the field of view, the point of departure is the triple point. Rule 2 is that if one or more pores or microcracks are present at the observed boundary (including triple points), they are classified as damaged, otherwise they are classified as intact. Rule 3 states that when multiple intersections exist at the same boundary, each counts, and damage is determined by the state of the entire observed boundary. Rule 4 states that the intersection with the triple point is counted as one, and the damage is taken predominantly in consideration of the damage condition of the three boundary points. The A-parameter calculation step (S440) is performed by the four rules as described above, and the result is an undamaged grain boundary (N_U), a damaged grain boundary (N_D), and a total grain boundary (N) in the CAVITY test column at the upper left of the screen. ) And the A-parameter value (A).

The evaluation step (S450) is a step of diagnosing the degree of creep damage by analyzing the A-Parameter value calculated through the A-Parameter calculation step (S440) and comparing with the standard tissue. Content evaluated through the evaluation step (S450) is the basis for evaluating the degree of deterioration of the facility, it is possible to calculate the repair time or replacement time of the facility according to the result.

In addition, the metal damage evaluation method is to perform the evaluation by each step of the first to fourth methods individually, weight each of the results calculated by the four evaluation methods and then the metal weights by combining the weights It may be done to assess the overall degree of damage to the tissue. For example, in the case of low ductility materials such as welds or stainless steel, the assessment of the overall damage degree gives a relatively low weight to the results of the first method, an intermediate weight to the results of the second and third methods, This can be achieved by giving a relatively high weight to the result of the fourth method. In addition, for high ductility materials such as chromium-molybdenum steel, the assessment of the overall damage degree gives a relatively high weight to the results of the first method, the second and third methods give an intermediate weight to the results, and the fourth This can be done by giving a relatively low weight to the result of the method. The comprehensive damage degree calculated in this way can be improved in accuracy and reliability compared to the damage degree calculated by one evaluation method.

As described above, the present invention is not limited to the specific preferred embodiments described above, and any person having ordinary skill in the art to which the present invention pertains without departing from the gist of the present invention claimed in the claims. Various modifications are possible, of course, and such changes are within the scope of the claims.

According to the metal damage assessment system according to the present invention and the metal damage assessment method using the same, not only provides a quantitative tissue deterioration analysis data through a system that can systematically analyze the metal damage assessment and associated mechanical equipment By providing evaluation data on the remaining life of the system, it is effective to maximize the work efficiency of field workers and improve the reliability of the evaluation results. In addition, there is an effect that can enable the operation of the plant to plan the efficient operation and long life of the plant, and comprehensively evaluate the reliability and economic efficiency.

Specifically, the accuracy of the evaluation results is improved by systematically and objectively organizing the process of damage assessment of metal structures to provide highly reliable data. It can prevent the damage of equipment at an early stage. Third, it can prevent human loss and property damage caused by the damage of equipment. Fourth, by predicting and repairing equipment according to the accurate evaluation result, it reduces downtime and extends operation time. Finally, it is effective to greatly improve the efficiency of maintenance by accurately presenting equipment inspection and replacement time to equipment managers.

Claims (9)

An input module for inputting an image observed by at least one of an optical microscope and an electron microscope, or inputting a scanned metallographic photograph; An image processing module for automatically or manually measuring characteristics of the metal texture input by the input module using an image processing apparatus; A metal structure database in which the shape change of the metal structure according to the mechanism and process of deterioration of the metal material used at a high temperature, and the standard structure of the steady state metal material and the damage evaluation result of the metal structure are stored; A metal texture evaluation module for analyzing and evaluating metal textures by comparing the characteristics of metal textures measured by the image processing module with data stored in the metal texture database by a metal texture evaluation algorithm; And It comprises an output module for outputting the result evaluated by the metal structure evaluation module, The image processing module measures the long and short axis of grains and makes a distribution map, measures the number of grain boundary pores in a specific cross section of the metal material, or circularizes the area ratio or carbide occupied by carbide present in the metal structure. Tasks including measuring the degree, measuring the gaps and dispersions between carbides, measuring the size and distance between precipitates present in the metal structure, or measuring the number of cavities generated in the grain boundaries of the metal structure Metal damage assessment system, characterized in that to carry out. delete An image input step of inputting an image of a metal structure; An image cleaning step of cleaning the image input through the image input step with an image of a metal structure including grain boundaries using a plurality of filters; A data conversion step of converting an image input through the image input step into binary data; An extraction step of extracting the crystal grains transformed into the data converted through the data conversion step; A measurement step of measuring numerical values representing characteristics of the metal structure damaged by the data converted through the data conversion step; An evaluation step of analyzing the quantified value through the measuring step and diagnosing the degree of creep damage by comparing with a standard tissue; And And an output step of outputting the result of the evaluation step to an output means including an image or printed matter. The measuring step measures the long axis and short axis of the crystal grains and prepare a distribution chart, The measuring step is to measure the area ratio occupied by the carbide (carbide) present in the metal structure or the degree of rounding of the carbide, or to measure the gap and dispersion between carbides, The measuring step measures the size and the distance between the precipitates present in the metal structure, The measuring step is a metal structure damage evaluation method by the grain boundary method, characterized in that for measuring the number of pores (cavity) generated in the grain boundary of the metal structure. delete delete delete delete delete The method of claim 3, The metal damage evaluation method is evaluated by each step for each of the grain deformation method, tissue contrast method, precipitate inspection method and grain boundary method, and weighted to each of the results calculated by the four evaluation methods A method of evaluating the overall damage of metal structures by combining the evaluation results that reflect the weights.

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