CN117766079A - Material degradation evaluation method based on indentation detection - Google Patents
Material degradation evaluation method based on indentation detection Download PDFInfo
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Abstract
A texture degradation evaluation method based on indentation detection comprises the following steps: 1) And establishing a material degradation database, wherein the material degradation database is used for collecting degradation type data and degradation degree data of the material. The invention establishes the material degradation evaluation method based on indentation detection, realizes the evaluation of the material degradation degree by only relying on nondestructive detection data, can be used for on-site evaluation of the degradation degree of the in-service equipment pipeline, further judges the applicability of the in-service equipment pipeline, and has the advantages of improved efficiency and reduced cost; meanwhile, the method is suitable for evaluating various material degradation types related to mechanical property changes, and can automatically judge the material degradation types according to input information, and clearly check parameters; the technology can effectively accumulate material degradation information data, continuously improve and optimize an evaluation model through the continuous accumulation of the data and a model retraining mechanism, and evaluate the material degradation degree by using the technology, wherein the reliability of the result is higher.
Description
Technical Field
The invention relates to the technical field of material detection, in particular to a material degradation evaluation method based on indentation detection.
Background
In recent years, when equipment of the refining device fails, serious losses are caused once failure leakage occurs, so that advanced prediction of failure risk of the refining device is more and more important. The service environment of the refining equipment is complex, the failure types are numerous, and many corrosion failure mechanisms are accompanied by material degradation, but the evaluation of the material degradation degree generally requires destructive sampling and complex tests, and the evaluation of the material degradation degree by using nondestructive detection data has a certain difficulty. The existing nondestructive detection means can only perform qualitative analysis on thickness loss, existing cracks, defects and the like, cannot directly measure residual strength and the like, and cannot characterize the quality degradation degree, so that the limitation is large.
The material quality is often accompanied with the change of mechanical properties, so that the severity of the material quality degradation can be characterized to a certain extent by the change of mechanical properties. The traditional mechanical property detection method needs to destroy and sample, and the complex test is only suitable for laboratory conditions. At present, related researches on the mechanical properties of materials detected by an indentation method are also carried out at home and abroad, but the indentation detection data has a certain deviation from the traditional mechanical property detection and a certain distance from the specific industry, so that the indentation detection method needs to be further researched.
Disclosure of Invention
The invention aims to provide a material degradation evaluation method based on indentation detection, which is used for evaluating the degradation degree of a material by only using nondestructive detection data, and can be used for on-site evaluation of the degradation degree of a pipeline of in-service equipment, and has the advantages of improved efficiency and reduced cost.
The invention solves the technical problems, and adopts the following technical scheme: a texture degradation evaluation method based on indentation detection comprises the following steps:
1) Establishing a material degradation database, wherein the material degradation database is used for collecting degradation type data and degradation degree data of materials;
2) Establishing a characteristic parameter mode of inputting a material degradation type into a material degradation database by a degradation material and a degradation index characterization method/principle;
3) Constructing an evaluation model for evaluating the material degradation type according to an artificial neural network method;
4) Training the evaluation model in the step 3);
5) Establishing a material degradation evaluation flow based on the trained evaluation model, and further training an optimized evaluation model when the model evaluation result and the expert evaluation result are inconsistent; when the material degradation degree exceeds the expected level, the device reminds timely maintenance and replacement, and avoids safety accidents and unplanned shutdown.
As a further optimization of the material degradation evaluation method based on indentation detection according to the present invention, the degradation class data in 3) includes a material degradation class, a mechanism, an affected material, a generation site, a detection method, and a characteristic parameter associated with each material degradation class.
As a further optimization of the material degradation evaluation method based on indentation detection, the characteristic parameters comprise occurrence temperature, mechanical property change and metallographic phase change.
As a further optimization of the material degradation assessment method based on indentation detection of the present invention, the material degradation classification includes creep, grain growth, spheroidization, graphitization, decarburization, carburization, nitriding, sigma phase embrittlement, embrittlement at 475 ℃ and tempering embrittlement.
As further optimization of the material degradation evaluation method based on indentation detection, the degradation degree data comprise the service start time, the initial mechanical property, the initial indentation test data, the initial metallographic feature, the time, the traditional mechanical property, the metallographic feature, the indentation test data, the residual service life and the material degradation index of the material service environment.
As a further optimization of the indentation detection-based material degradation evaluation method, the traditional mechanical properties comprise hardness, tensile strength, creep resistance and toughness.
As a further optimization of the material degradation evaluation method based on indentation detection, the evaluation model in the step 3) comprises a traditional mechanical property and material degradation degree relation model, an indentation test data and traditional mechanical property relation model and an indentation test data and material degradation degree corresponding relation model.
As a further optimization of the texture degradation evaluation method based on indentation detection, the input of the traditional mechanical property and texture degradation degree relation model is the traditional mechanical property, and the output is the texture degradation degree.
As a further optimization of the indentation detection-based material degradation evaluation method of the present invention, the conventional mechanical properties include tensile strength, yield strength, impact toughness and creep property, and the degree of material degradation includes a metallographic grade, a residual life and a degradation index.
As a further optimization of the material degradation evaluation method based on indentation detection, the indentation test data and the traditional mechanical property relation model are input into the indentation test data, and output into the traditional mechanical property data.
As a further optimization of the material degradation evaluation method based on indentation detection, the corresponding relation model of indentation test data and the material degradation degree is input as indentation test data, and output as the material degradation degree.
As a further optimization of the texture degradation evaluation method based on indentation detection, the construction of the evaluation model in the step 3) adopts a BP algorithm.
The invention has the following beneficial effects:
1. the invention establishes the material degradation evaluation method based on indentation detection, realizes the evaluation of the material degradation degree by only relying on nondestructive detection data, can be used for on-site evaluation of the degradation degree of the in-service equipment pipeline, further judges the applicability of the in-service equipment pipeline, and has the advantages of improved efficiency and reduced cost;
2. the method is suitable for evaluating various material degradation types related to mechanical property changes, and can automatically judge the material degradation types according to input information, and clearly check parameters;
3. the technology can effectively accumulate material degradation information data, continuously improve and optimize an evaluation model through the continuous accumulation of the data and a model retraining mechanism, and evaluate the material degradation degree by using the technology, wherein the reliability of the result is higher.
Drawings
FIG. 1 is a schematic diagram of a material degradation evaluation process according to the present invention;
FIG. 2 is a table of creep deterioration index correspondence references in the examples;
FIG. 3 is a schematic diagram of an artificial neural network of an evaluation model in the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
The invention provides a material degradation evaluation method based on indentation detection, which only evaluates the material degradation degree by means of nondestructive detection data, can be used for on-site evaluation of the degradation degree of in-service equipment pipelines, further judges the applicability of the material degradation evaluation method, and has the advantages of improved efficiency and reduced cost. The method and the system can carry out nondestructive testing on the pipeline material of the in-service equipment of the enterprise, evaluate the degradation degree of the pipeline material, predict the service life, judge that the pipeline material needs to be replaced in time, assist a manager to make a maintenance plan, avoid unplanned downtime and safety risks caused by material damage failure, and improve the economic and social benefits of the enterprise.
The evaluation method comprises the following steps:
1) Establishing a material degradation database, wherein the material degradation database is used for collecting degradation type data and degradation degree data of materials; the data support is provided for the construction of a subsequent evaluation model by collecting degradation types and degradation degrees of different materials;
the degradation class data comprises degradation classes, mechanisms, influencing materials, occurrence parts, detection methods and characteristic parameters related to each material degradation class; wherein the characteristic parameters comprise occurrence temperature, mechanical property change and metallographic phase change; classification of material degradation including creep, grain growth, spheroidization, graphitization, decarburization, carburization, nitriding, sigma phase embrittlement, 475 ℃ embrittlement, tempering embrittlement;
the degradation degree data comprise material service environment service start time, initial mechanical properties, initial indentation test data, initial metallographic features, time, traditional mechanical properties, metallographic features, indentation test data, residual service life and material degradation indexes, wherein the traditional mechanical properties comprise hardness, tensile strength, creep resistance and toughness;
2) Establishing a characteristic parameter mode of inputting a material degradation type into a material degradation database by a degradation material and a degradation index characterization method/principle; according to the comparison and analysis of the input information data and the data in the material degradation database, the material degradation type can be automatically judged, and then the indentation detection parameters are clearly required to be developed;
wherein the material characteristic parameters mainly comprise: a) Conventional mechanical properties such as room temperature and high temperature tensile properties, etc.; b) High temperature long term performance, such as high temperature endurance strength, high temperature creep performance, material L-M curve: c) The microstructure features such as grain size, crystal form ratio (e.g., columnar and equiaxed crystal ratio), carbide type, morphology and distribution, creep voids and cracks, and the like; d) Physical properties, namely modulus of elasticity, poisson's ratio, coefficient of linear expansion, specific heat capacity, thermal conductivity, etc.;
material degradation index: in principle, the range is 0 to 1. The 0 indicates no degradation, the 1 indicates material failure/service life exhaustion caused by degradation, and the determination of the material degradation index is respectively determined according to the degradation type;
3) Constructing an evaluation model for evaluating the material degradation type according to an artificial neural network method; the evaluation model comprises a traditional mechanical property and material degradation degree relation model, indentation test data and traditional mechanical property relation model and an indentation test data and material degradation degree corresponding relation model;
the input of the traditional mechanical property and material degradation degree relation model is the traditional mechanical property, and the output is the material degradation degree. Traditional mechanical properties include tensile strength, yield strength, impact toughness and creep properties, and the degree of material degradation includes metallurgical grade, residual life and degradation index. The indentation test data and the traditional mechanical property relation model are input into the indentation test data, and output into the traditional mechanical property data. The corresponding relation model of the indentation test data and the material degradation degree is input as the indentation test data and output as the material degradation degree;
in the step, an artificial neural network method is shown in fig. 3, and a BP algorithm is specifically adopted to construct an evaluation model;
4) Training the evaluation model in the step 3); and respectively training to obtain three relation models of a certain degradation type. (the selected BP neural network has an input layer, an hidden layer and an output layer 3-layer structure). As a multilayer feedforward neural network, the system is mainly characterized by forward signal transmission and reverse error transmission. The input signals are processed layer by layer through the input layer by the hidden layer and output through the output layer. If the output value does not reach the expected value, the error between the output value and the expected value is reversely propagated, the weight and the threshold value of the network are adjusted according to the error, the error is reduced through repeated iteration until the error is reduced to the allowable value, and then the neural network training is completed;
5) Establishing a material degradation evaluation flow based on the trained evaluation model, wherein the evaluation flow is shown in fig. 2, and further training an optimized evaluation model when the model evaluation result and the expert evaluation result are inconsistent; when the material degradation degree exceeds the expected level, the device reminds timely maintenance and replacement, and avoids safety accidents and unplanned shutdown.
The following is a specific embodiment developed according to the above evaluation method, and the evaluation establishment procedure is developed according to the evaluation method established by creep of one of the material degradation types:
1. database creation and data collection
(1) Material degradation class library
The following information is recorded as one piece in the material degradation class library.
1) Degradation category: creep (creep)
2) Definition: refers to a process in which a high temperature device or a high temperature part of the device is slowly plastically deformed over time under a load below a yield stress. Creep deformation causes the actual load-bearing cross-section of the component to shrink, the stress to rise, and eventually a different form of fracture to occur.
3) The mechanism is as follows: a) Creeping along crystal; b) And (5) crystal penetration creep.
4) Morphology: a) The initial stages of creep damage are generally characterized by no significant features, but can be identified by scanning electron microscope observation. Creep voids appear at grain boundaries, forming microcracks in the middle and later stages, and then macrocracks. b) The material with better plasticity can observe obvious creep deformation before stress fracture, while the material with poorer plasticity has no obvious creep deformation before stress fracture. At operating temperatures well above the creep temperature threshold, significant bulging, elongation, etc. deformations are typically observed, with the amount of deformation being primarily dependent on the combination of the three materials, temperature, and stress levels. C) The parts with high temperature and concentrated stress in the pressure-bearing equipment are easy to creep, especially in the structure discontinuous parts such as tee joints, connecting pipes, defects, welded joints and the like.
4) Influence factors: material, stress, temperature.
a) The main influencing factors of the creep deformation rate are materials, stress and temperature, and the damage rate (or strain rate) is sensitive to the stress and the temperature, for example, the service temperature of the alloy is increased by 12 ℃, or the stress is increased by 15%, so that the residual service life of the alloy can be shortened by more than half.
b) Temperature: at the creep threshold temperature, no creep deformation generally occurs. Above the temperature threshold, creep damage may occur. The life of the metal component is hardly affected by equipment that is in service at the threshold temperature, even if the stress near the crack tip is high.
c) Stress: the higher the stress level, the greater the creep deformation rate and the shorter the time to stress rupture.
d) Creep toughness: materials with low creep toughness deform little or no significant deformation when creep occurs. Generally, materials with high tensile strength, welded joint locations, and coarse-grain materials have lower creep toughness and are more likely to undergo stress cracking.
5) Influence the material quality: all metallic materials
6) The occurrence part is as follows: a) Above the creep temperature threshold, pressure-bearing equipment such as a catalytic reformer hot wall hydrogenation reactor and a heating furnace tube, a hydrofining device heating furnace tube, a hydrocracking device heating furnace tube, a catalytic cracking device hot wall hydrogenation reactor, a fractionating tower and a regenerator internals, a cracking furnace tube of an ethylene cracking device, a coking furnace tube and a coke tower of a delayed coking device, a high-temperature flue gas pipeline and the like are operated;
b) The dissimilar steel welded joint is easy to creep in a welding joint heat affected zone and a local high-stress zone, and a long welding joint of a connecting pipe welding joint heat affected zone and a catalytic reforming reactor can have low creep ductility failure;
c) Other equipment operating at high temperatures, such as furnace tubes, tube holders, tube hangers in heating furnaces, and main steam lines of boilers, and components within the furnaces, are sensitive.
7) The detection mode is as follows:
a) The method is characterized in that an infrared monitoring method is adopted in the in-service equipment to observe whether overheat exists or not, visual detection and thickness measurement are carried out on the part suspected to be overheated and the part with complex stress state when the in-service equipment is stopped, and when obvious deformation exists, surface magnetic powder detection or penetration detection can be carried out to confirm whether cracking exists, if necessary, the damage degree can be analyzed through metallographic examination, even micro damage or destructive sampling test can be carried out, and the high-temperature mechanical property of the material can be tested;
b) The equipment is made of chromium-molybdenum alloy and operated above the creep temperature threshold or the welded joint of the equipment with the operation temperature close to the creep threshold, visual detection is carried out on the welded joint to confirm whether bulge, cracking, sagging and arc bending exist or not, surface magnetic powder detection or penetration detection is carried out at intervals of a certain period (2 years to 4 years), ultrasonic transverse wave detection is supplemented to the equipment with longer operation period (more than or equal to 8 years), and the part with defects or repaired parts during manufacturing is used as a detection key area;
c) Visual inspection and deformation measurement: visually detecting whether bulge, cracking, sagging and arc bending exist, checking whether diameter increase exists for large-diameter (more than or equal to 3.5 m) equipment by using a laser distance measuring instrument, checking whether diameter increase exists for non-large-diameter equipment by using a laser distance measuring instrument, a creep measuring ruler and a gauge, or setting mark points on the surface and measuring whether the mark distance is increased;
d) Wall thickness is measured where wall thickness reduction is most likely to occur.
2. Method for establishing material degradation input characteristic parameter and degradation index characterization method/principle
(1) The characteristic parameters include environmental characteristic parameters and performance characteristic parameters
1) The environmental characteristic parameters include a) material: the creep temperature and the creep toughness of the related materials; b) Operating temperature: whether the operating temperature is above the material creep threshold; c) The parts are as follows: a part dictionary has occurred.
2) The performance characteristic parameters include a) tensile strength: lowering; b) Creep resistance: lowering; c) Metallography: there is degradation; d) Cracking: may be present.
(2) Method for determining the characterization of creep material degradation index
1) The degradation state is characterized by a metallographic method, the degradation index is further determined, the creep damage grade can be classified into 5 grades from the initiation of isolated holes to the expansion of microcracks according to the difference of microstructures and damage forms, and the inspection of the creep holes is carried out according to the specification of DL/T884.
2) The degradation state is characterized by using the creep life evaluation, one or more creep life evaluation methods (an isotherm extrapolation method, an L-M parameter method, a theta parameter method and the like can be adopted, but the evaluation method is not limited to the method, and can refer to NB/T10617) for evaluating the residual creep life, obtaining a cumulative life fraction (1-residual creep life/initial creep life), and further determining the creep degradation index (shown in fig. 2) according to the cumulative life fraction.
3. Modeling and training
For creep degradation types, three artificial neural network evaluation models are established: 1) A traditional mechanical property and creep degradation degree relation model; 2) Indentation test data and traditional mechanical property relation model; 3) And (5) an indentation test data and creep degradation degree corresponding relation model.
1) The relation model of the traditional mechanical property and the creep degradation degree is input into the traditional mechanical property (according to creep characteristic parameters, the mechanical property related to creep is mainly high-temperature long-term performance and conventional mechanical property), and output into the creep degradation degree related parameters (including but not limited to metallographic grade, residual life and degradation index);
2) The indentation test data and the traditional mechanical property relation model are input into indentation test data (mechanical property values obtained by indentation test, including but not limited to hardness, yield strength, tensile strength, fracture toughness, residual stress, load-indentation depth data set and the like), and output into traditional mechanical property data;
3) The corresponding relation model of the indentation test data and the creep degradation degree is input as the indentation test data and output as the creep degradation degree.
And respectively training three relation models of the creep degradation type by utilizing the data related to the creep degradation of the database.
4. Performing field assessment using an established model
During the shutdown period of the device, indentation detection can be performed on the parts such as the furnace tube of the hydrogen production reformer according to the material degradation evaluation flow, as shown in fig. 1, so as to evaluate the material degradation degree.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes and modifications may be made by one skilled in the art within the scope of the claims without affecting the spirit of the invention.
Claims (12)
1. The material degradation evaluation method based on indentation detection is characterized by comprising the following steps:
1) Establishing a material degradation database, wherein the material degradation database is used for collecting degradation type data and degradation degree data of materials;
2) Establishing a characteristic parameter mode of inputting a material degradation type into a material degradation database by a degradation material and a degradation index characterization method/principle;
3) Constructing an evaluation model for evaluating the material degradation type according to an artificial neural network method;
4) Training the evaluation model in the step 3);
5) Establishing a material degradation evaluation flow based on the trained evaluation model, and further training an optimized evaluation model when the model evaluation result and the expert evaluation result are inconsistent; when the material degradation degree exceeds the expected level, the device reminds timely maintenance and replacement, and avoids safety accidents and unplanned shutdown.
2. The method for evaluating the quality degradation based on indentation detection as claimed in claim 1, wherein: the degradation class data in 3) includes a material degradation class, a mechanism, an affected material, a generation site, a detection method, and a characteristic parameter associated with each material degradation class.
3. The method for evaluating the quality degradation based on indentation detection as claimed in claim 2, wherein: the characteristic parameters comprise occurrence temperature, mechanical property change and metallographic phase change.
4. The method for evaluating the quality degradation based on indentation detection as claimed in claim 2, wherein: the material degradation classification includes creep, grain growth, spheroidization, graphitization, decarburization, carburization, nitriding, sigma phase embrittlement, embrittlement at 475 ℃ and tempering embrittlement.
5. The method for evaluating the quality degradation based on indentation detection as claimed in claim 1, wherein: the degradation degree data comprise material service environment service start time, initial mechanical property, initial indentation test data, initial metallographic feature, time, traditional mechanical property and metallographic feature, indentation test data, residual service life and material degradation index.
6. The method for evaluating texture deterioration based on indentation detection as claimed in claim 5, wherein: the conventional mechanical properties include hardness, tensile strength, creep resistance and toughness.
7. The method for evaluating the quality degradation based on indentation detection as claimed in claim 1, wherein: the evaluation model in the step 3) comprises a traditional mechanical property and material degradation degree relation model, an indentation test data and traditional mechanical property relation model and an indentation test data and material degradation degree corresponding relation model.
8. The method for evaluating texture deterioration based on indentation detection as claimed in claim 7, wherein: the input of the traditional mechanical property and material degradation degree relation model is the traditional mechanical property, and the output is the material degradation degree.
9. The method for evaluating the quality degradation based on indentation detection as claimed in claim 8, wherein: the traditional mechanical properties comprise tensile strength, yield strength, impact toughness and creep property, and the material degradation degree comprises metallographic grade, residual life and degradation index.
10. The method for evaluating texture deterioration based on indentation detection as claimed in claim 7, wherein: the indentation test data and the traditional mechanical property relation model are input into the indentation test data, and output into the traditional mechanical property data.
11. The method for evaluating texture deterioration based on indentation detection as claimed in claim 7, wherein: the corresponding relation model of the indentation test data and the material degradation degree is input as the indentation test data, and output as the material degradation degree.
12. The method for evaluating the quality degradation based on indentation detection as claimed in claim 1, wherein: the artificial neural network method in the step 3) is a BP algorithm.
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| CN118882367A (en) * | 2024-09-29 | 2024-11-01 | 合肥巨阙电子有限公司 | A Fault Prediction and Early Warning System for Aging Furnace |
| CN118882367B (en) * | 2024-09-29 | 2024-12-20 | 合肥巨阙电子有限公司 | A Fault Prediction and Early Warning System for Aging Furnace |
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