CN115329475B - Part preparation method and equipment based on zoned multistage cryogenic treatment - Google Patents

Part preparation method and equipment based on zoned multistage cryogenic treatment Download PDF

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CN115329475B
CN115329475B CN202210837481.6A CN202210837481A CN115329475B CN 115329475 B CN115329475 B CN 115329475B CN 202210837481 A CN202210837481 A CN 202210837481A CN 115329475 B CN115329475 B CN 115329475B
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王新云
丁华平
唐学峰
牛勇
邓磊
龚攀
张茂
金俊松
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Huazhong University of Science and Technology
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Abstract

The invention belongs to the technical field of cryogenic treatment, and discloses a part preparation method and equipment based on zoned multistage cryogenic treatment, wherein the method comprises the following steps: (1) Establishing a nonlinear mapping relation between multistage cryogenic process parameters, microstructure and performance through a neural network; (2) Dividing the target part into a plurality of subareas, and reversely pushing out multistage cryogenic treatment parameters required by each subarea so as to obtain a series of corresponding cryogenic process parameter distribution combinations in the target part; (3) Performing high-throughput numerical simulation on the zoned multistage cryogenic treatment process to determine optimal cryogenic treatment parameter combinations of different areas inside the target part; (4) And carrying out independent sub-region cryogenic treatment on the part to be treated to obtain the target part. The invention solves the technical problems of low applicability and complex process of the deep cooling treatment of the parts in the prior art.

Description

Part preparation method and equipment based on zoned multistage cryogenic treatment
Technical Field
The invention belongs to the technical field related to cryogenic treatment, and particularly relates to a part preparation method and equipment based on zoned multistage cryogenic treatment.
Background
The weight of lightweight structural parts such as blisks, turbine disks and the like can be reduced by about 30%, and the thrust-weight ratio and the use reliability of the engine are improved. The blisk and turbine disk parts have larger temperature gradient and stress gradient along the radial direction, different areas have different requirements on material performance, the blade emphasizes to have excellent high-cycle fatigue resistance, and the disk body emphasizes to have high-temperature creep resistance and damage tolerance performance. The spoke working temperature of the turbine disk is relatively low, and the fine grain structure better meets the requirements of high yield strength and low cycle fatigue performance of the spoke; the temperature of the disc edge is relatively high, the coarse grain structure has high creep and damage tolerance performance, and microcracks possibly occurring in the mortises can be avoided. In order to further develop the performance potential of parts such as blisks and the like, proper alloy materials and tissue states are selected according to the actual service environments of different areas of the parts, so scientists propose design ideas of dual-performance blisks and turbine discs, break through the inertia thinking that the traditional hot processing technology pursues uniform tissue, and develop a series of single-alloy dual-performance or dual-alloy gradient structure parts with gradient microstructure characteristics.
The manufacturing methods of the present gradient structure metal parts, in particular to the representative double-performance blisk, turbine disk and other parts mainly comprise a welding method, zoning temperature control forging and zoning temperature control heat treatment. The welding method can realize the connection of dissimilar materials, but the biggest problem is that the connection area often becomes a weak link of the whole component, which is an important hidden trouble for high-speed rotating parts of the aeroengine with high reliability and long service life. Compared with the partition temperature control forging process, the partition temperature control heat treatment process is adopted, so that stable and controllable temperature gradient is easier to form between the blade and the disc body, the required double structure is obtained, the process operation is relatively easy, and the consistency is good. After traditional heat treatment, the material still has certain defects, such as unstable structure after quenching, higher heat stress, tissue stress, uneven structure and the like, which can deteriorate the material performance and further influence the service life of the material. Generally, such problems are difficult to solve by a single heat treatment process, and the cryogenic treatment is an important additional process for heat treatment, so that the performance of the material after heat treatment can be effectively subjected to secondary optimization, and the method has a remarkable effect of prolonging the service life of the material.
The cryogenic treatment refers to the treatment of a material (or a workpiece) in a certain low-temperature (-130 ℃) environment by controlling the technological parameters such as the cryogenic treatment temperature, the temperature rise and fall speed, the heat preservation time, the treatment times and the like, so that the microstructure of the material is irreversibly transformed to different degrees, thereby achieving the purpose of improving the comprehensive performance. Researches show that the deep cooling treatment has remarkable modification effects on materials such as die steel, high-temperature alloy, titanium alloy, hard alloy, amorphous alloy, high-entropy alloy and the like, and has the effects of promoting transformation of retained austenite, refining grains, improving dislocation density, promoting formation of twin crystal and sub-crystal tissues, promoting phase transformation and carbide precipitation, promoting formation of textures and the like.
For gradient structural parts, the requirements of different parts on the structure, even the alloy types, are different, and the requirements for cryogenic treatment are greatly different. The typical cryogenic treatment method for such parts is to wrap a region which is not subjected to cryogenic treatment at a certain stage by using a heat insulating material, and often requires multiple steps, and the steps are complicated and have poor effects. The existing cryogenic treatment process and device are only suitable for single-material and uniform parts, and are difficult to meet the cryogenic requirements of different areas of parts with gradient structures such as a dual-performance impeller disc, a turbine disc and the like.
Disclosure of Invention
Aiming at the defects or improvement demands of the prior art, the invention provides a part preparation method and equipment based on zoned multistage cryogenic treatment, the preparation method obtains parts with corresponding tissue characteristics and performance distribution by controlling the temperature gradient field distribution in a sample in the multistage cryogenic treatment process, and the differential cryogenic treatment of different areas of the parts can be realized by optimizing the process parameters such as temperature, heat preservation time and the like in the multistage cryogenic treatment process, so that the target tissue and performance distribution are obtained, and the technical problems of low applicability and complex process for the cryogenic treatment of the parts in the prior art are solved.
In order to achieve the above object, according to one aspect of the present invention, there is provided a method for manufacturing a part based on zoned multistage cryogenic treatment, the method mainly comprising the steps of:
(1) Obtaining a tissue-performance evolution rule of a material component of a target part through a multistage cryogenic treatment experiment, and establishing a nonlinear mapping relation between multistage cryogenic process parameters and microstructure-performance through a neural network;
(2) Dividing the target part into a plurality of subareas according to the tissue performance distribution requirement of the target part, and reversely pushing out multistage cryogenic treatment parameters required by each subarea by combining the obtained nonlinear mapping relation, so as to obtain a series of cryogenic process parameter distribution combinations corresponding to the interior of the target part when the multistage cryogenic treatment target part is adopted;
(3) Carrying out high-flux numerical simulation on the zoned multistage cryogenic treatment process by combining the obtained cryogenic process parameter distribution combinations, and determining the cryogenic process parameter combination corresponding to the tissue performance distribution requirement of the temperature distribution or microstructure distribution closest to the target part in the numerical simulation as the optimal cryogenic process parameter combination of different areas inside the target part;
(4) And combining the geometric division area of the target part and the optimal cryogenic treatment parameter combination, and performing independent cryogenic treatment on the part to be treated in a partitioning manner to obtain the target part.
Further, the obtaining of the tissue-performance evolution law of the material composition of the target part comprises the following steps: setting orthogonal experiments or single-factor experiments in a preset cryogenic treatment parameter range by taking a material of a target part as an initial experimental object, carrying out multistage cryogenic treatment on the initial experimental object under different cryogenic treatment process parameter conditions, and carrying out microstructure characterization and performance test on a sample obtained by cryogenic treatment to obtain microstructure characteristic parameters and performance data in the sample under different cryogenic treatment parameter conditions, thereby obtaining a multistage cryogenic treatment process parameter-microstructure-performance database.
Further, multistage cryogenic treatment refers to a process in which a plurality of heat preservation and temperature rise processes are performed from an initial treatment temperature to a minimum treatment temperature; the microstructure characteristic parameters include one or more of grain size, dislocation density, retained austenite volume fraction, size of carbide phase, and volume fraction; the multistage cryogenic treatment process parameters comprise one or more of temperature, heat preservation time, temperature rising and falling speed and treatment times.
Further, the established nonlinear mapping relationship between the multistage cryogenic process parameter and the microstructure-performance comprises a cryogenic process parameter and microstructure relationship model, a microstructure-performance relationship model and a cryogenic process parameter and performance relationship model.
Further, each relation model is described by a BP neural network model with a plurality of hidden layers, wherein the establishment of the nonlinear mapping relation of the cryogenic process parameters and the microstructure comprises the following steps:
taking a set of cryogenic process parameters obtained by a multistage cryogenic treatment experiment as input, taking the obtained microstructure characteristic parameter set as output, constructing and training a BP neural network model containing multiple hidden layers, and selecting proper excitation functions for each hidden layer and output layer; optimizing the initial weight and threshold of the BP neural network by using a genetic algorithm to obtain the weight and threshold of the optimal individual; and assigning the obtained weight and threshold of the optimal individual to the BP neural network model, and updating the weight and threshold of each hidden layer by using an error back propagation algorithm in the training process until the cost function J is smaller than the set precision or the maximum iteration number is reached, and finishing the training.
Further to the bottom, the excitation functions of the hidden layers all select a logistic function, and the excitation functions of the output layers select a linear function g (x) =x.
Further, the initial weight and threshold of the BP neural network are optimized by adopting a genetic algorithm, and the method specifically comprises the following steps:
s1: firstly, determining the weight and the number of thresholds of a neural network according to a topological graph of the BP neural network model, and following the following formula:
Figure BDA0003749236780000041
wherein N is um Is weight valueThe total number of threshold values, i, represents the i-th layer neuron, H i The number of nodes for the i-th layer neuron;
s2: carrying out coding operation on a weight threshold value of the neural network by adopting a real number coding mode, initializing a population, randomly taking a value between (-1, 1) initial weight threshold values, and setting an adaptability function of the population as F1;
Figure BDA0003749236780000042
where F1 is the fitness value, ρ1 is the enhancement phase component predicted by the neural network using the initial weight and threshold, η1 is the enhancement phase volume fraction predicted by the neural network using the initial weight and threshold, δ1 is the enhancement phase average size predicted by the neural network using the initial weight and threshold, ρ 0 To enhance the phase composition expectancy, η 0 To enhance the phase volume fraction expectations, δ 0 Average size expectancy for the reinforcement phase;
s3: calculating fitness values of all individuals in the population, selecting the individuals with high fitness from the parents by using a roulette algorithm to perform selection operation, and generating next-generation individuals, wherein the probability of each selected individual follows the following formula:
Figure BDA0003749236780000051
wherein p is k Probability of being selected for kth individual, F k The fitness value of the kth individual, K is the total number of individuals in the population;
s4: the method comprises the steps of performing cross operation on individuals in a population, setting cross probability as pc, generating a random number, performing cross operation if the random number is smaller than the cross probability, randomly selecting two individuals and randomly selecting cross bits during cross, and performing cross operation according to the following formula:
Figure BDA0003749236780000052
wherein a is kj Is the real number of the kth chromosome at position j, a lj Is the real number of the first chromosome at the j position, and b is the random number between (0 and 1);
s5: the individual in the population is subjected to mutation operation, the mutation probability is set to be pm, if a random number is generated and is smaller than the mutation probability, the mutation operation is carried out, when the individual is mutated, the mutation operation is carried out by randomly selecting an individual and randomly selecting mutation positions, and the mutation operation is carried out according to the following formula:
Figure BDA0003749236780000053
/>
Figure BDA0003749236780000054
wherein a is ij Is the real number of the ith chromosome at the j bit, G is the current iteration number, f (G) is a variation factor, G max For maximum iteration number, a max Is a ij Upper limit of the value, a min Is a ij The lower limit of the value is that r and r' are random numbers between (0, 1);
s6: and (3) cycling the steps S3 to S5 until a satisfactory fitness value is obtained or a limited iteration number is reached, and outputting an optimal individual, namely the individual with the largest fitness value.
According to another aspect of the present invention, there is provided a part manufacturing apparatus based on a partitioned multistage cryogenic process, which manufactures a part using the part manufacturing method based on a partitioned multistage cryogenic process as described above; the apparatus is formed with a plurality of independent cryogenic treatment chambers, each capable of independently cryogenic treating a section of the part to be prepared.
Further, each cryogenic treatment chamber is respectively provided with an independent resistance heating wire, a temperature sensor, a cooling medium inlet and outlet pipe and a moving mechanism, so that each cryogenic treatment chamber can independently work to perform cryogenic treatment on a local area of a target part.
Further, the equipment further comprises a plurality of heat insulation plates, and the equipment is provided with a containing cavity, wherein the plurality of heat insulation plates are arranged in the containing cavity at intervals so as to divide the containing cavity into a plurality of independent cryogenic treatment chambers; the heat insulation plate is also used for bearing parts to be prepared; each heat insulating plate is connected with one moving mechanism, and the moving mechanism is used for driving the heat insulating plates to move so as to change the space size of the cryogenic treatment chambers at two sides of the heat insulating plates.
In general, compared with the prior art, the part preparation method and the equipment based on the zoned multistage cryogenic treatment mainly have the following beneficial effects:
1. according to the preparation method, the fact that microstructure and performance evolution of a metal material during cryogenic treatment directly depend on temperature field distribution in cryogenic treatment is utilized, gradient temperature field distribution required by multistage cryogenic treatment of a target part is reversely deduced according to microstructure and performance requirements in the target part, a geometric division scheme capable of obtaining the gradient temperature field distribution of the target is determined through numerical simulation, reversely deduced multistage cryogenic treatment parameters and geometric division scheme are finally adopted, the space of each chamber of a cryogenic treatment device is adjusted, and a cryogenic treatment program of each chamber is set, so that the target part is obtained.
2. Compared with the traditional modes of directly immersing in cooling media such as liquid nitrogen and the like, the multistage cooling mode is adopted, the heat shock to parts is small, cracks and deformation are not easy to generate in the treatment process, and the multistage cooling mode is suitable for thin-wall parts and brittle materials; meanwhile, aiming at the requirements of cryogenic treatment of different areas of the part, a partition cryogenic treatment mode is adopted, the micro-structure and mechanical property regulation and control of the whole part can be completed through one-time cryogenic treatment, the cryogenic treatment process of the part is obviously simplified, the treatment efficiency is improved, the micro-structure and mechanical property transition between different areas is good, the interface stress concentration in the part service process can be avoided, and the whole service life is prolonged.
3. According to the invention, firstly, orthogonal experiments or single factor experiments of multistage cryogenic treatment are carried out on material components of a target part to obtain microstructure and performance data of the target part under different cryogenic treatment parameters, then, the experimental data are used for establishing cryogenic treatment parameters such as temperature, heat preservation time, temperature rise and fall rate, treatment times and microstructure parameters such as grain size, dislocation density, volume fraction of retained austenite, volume fraction of precipitated phases of carbide and the like by utilizing a neural network technology, and the complex nonlinear mapping relation of performance parameters such as yield strength, room temperature plasticity, breaking strength, bending strength, hardness and the like can comprehensively reflect the cryogenic treatment parameters and the complex influence rule between microstructure and performance, help to reversely push the required gradient temperature field, optimize the process parameters, reduce the number of pre-experiments, and realize the rapid and intelligent formulation of the multistage cryogenic treatment process of the part in a partitioned area.
4. The equipment changes a single chamber of a traditional cryogenic device into a multi-chamber design, the temperature of each chamber is independently controlled, the space is flexible and adjustable, a heat insulation layer is arranged between the chambers, the cryogenic requirements of complex-shaped parts consisting of single alloy gradient tissues or multi-alloy tissues can be met, the cryogenic treatment process is obviously simplified, and the cryogenic treatment effect is good.
Drawings
FIG. 1 is a schematic flow chart of a part preparation method based on zoned multistage cryogenic treatment;
FIG. 2 is a schematic diagram of a part manufacturing apparatus based on zoned multi-stage cryogenic treatment according to an embodiment of the invention;
FIG. 3 is a cross-sectional view of the part preparation apparatus of FIG. 2 based on a zoned multi-stage cryogenic process;
FIG. 4 is a partial schematic view of the part preparation apparatus of FIG. 2 based on a zoned multi-stage cryogenic process;
FIG. 5 is a schematic view of the part preparation apparatus of FIG. 2 in an open and closed state based on a zoned multi-stage cryogenic process;
FIG. 6 is a schematic structural view of a part preparation apparatus based on zoned multi-stage cryogenic treatment according to another embodiment of the invention;
FIG. 7 is a cross-sectional view of the part preparation apparatus of FIG. 6 based on a zoned multi-stage cryogenic process;
FIG. 8 is a partial schematic view of the part preparation apparatus of FIG. 6 based on a zoned multi-stage cryogenic process;
FIG. 9 is a schematic view of the part preparation apparatus of FIG. 6 based on a zoned multistage cryogenic process in an open state.
The same reference numbers are used throughout the drawings to reference like elements or structures, wherein: the device comprises a 1-upper pipeline chamber, a 2-upper chamber, a 3-lower chamber, a 4-lower pipeline chamber, a 5-connecting mechanism, a 6-liquid nitrogen pipe, a 7-moving mechanism, an 8-heat insulation layer, a 9-resistance heating wire, a 10-thermocouple, a 11-plate-shaped gradient structure part, a 12-thermocouple signal wire, a 13-temperature control system, a 14-heat insulation plate and a 15-plate-shaped gradient structure part.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
Referring to fig. 1, the invention provides a part preparation method based on zoned multistage cryogenic treatment, which can realize flexible microstructure setting of parts, rapid optimization of performance zoning, better continuity of tissue performance among different zones, small thermal shock generated by multistage treatment, difficult cracking of parts in the treatment process and wide applicable part types and material ranges. The preparation method can prepare parts with gradient structures and uniform structures.
The invention provides a part preparation method based on zoned multistage cryogenic treatment, which mainly comprises the following steps:
obtaining a tissue-performance evolution rule of a material composition of a target part through a multistage cryogenic treatment experiment, and establishing a nonlinear mapping relation between multistage cryogenic process parameters and microstructure-performance through a neural network.
The tissue-performance evolution rule of the material composition of the target part is obtained through a multistage cryogenic treatment experiment, and the method specifically comprises the following steps: setting orthogonal experiments or single-factor experiments in a preset cryogenic treatment parameter range by taking a material of a target part as an initial experimental object, carrying out multistage cryogenic treatment on the initial experimental object under different cryogenic treatment process parameter conditions, and carrying out microstructure characterization and performance test on a sample obtained by cryogenic treatment to obtain microstructure characteristic parameters and performance data in the sample under different cryogenic treatment parameter conditions, thereby obtaining a multistage cryogenic treatment process parameter-microstructure-performance database.
Multistage cryogenic treatment refers to a process that undergoes several soak and soak processes from the initial process temperature to the minimum process temperature. The microstructure characteristic parameters include one or more of grain size, dislocation density, retained austenite volume fraction, size of carbide phase, and volume fraction. The multistage cryogenic treatment process parameters comprise one or more of temperature, heat preservation time, temperature rising and falling speed and treatment times. The performance data includes mechanical properties of the material, such as yield strength, breaking strength, electromagnetic properties, such as one or more of electrical conductivity, magnetic permeability, thermal conductivity.
The phase composition and dislocation density in the cryogenic sample are determined by X-ray diffraction analysis (XRD), and the grain size, the volume fraction of residual austenite, the size and the volume fraction of carbide phase and the like in the cryogenic sample are obtained by means of a metallographic microscope or a scanning electron microscope, EBSD and the like.
The nonlinear mapping relation between the cryogenic treatment process parameter and the microstructure-performance of the material composition of the target part comprises 3 relation models such as a cryogenic treatment process parameter and microstructure relation model, a microstructure-performance relation model, a cryogenic treatment process parameter and performance relation model and the like.
Each relation model is described by adopting a BP neural network model containing a plurality of hidden layers, wherein the establishment of the nonlinear mapping relation of the cryogenic process parameters and the microstructure comprises the following steps:
taking a set of cryogenic process parameters obtained by the multistage cryogenic treatment experiment as input, taking the obtained microstructure characteristic parameter set as output, constructing and training a BP neural network model containing multiple hidden layers, and selecting proper excitation functions for each hidden layer and output layer; optimizing the initial weight and threshold of the BP neural network by using a genetic algorithm to obtain the weight and threshold of the optimal individual; and assigning the obtained weight and threshold of the optimal individual to the BP neural network model, and updating the weight and threshold of each hidden layer by using an error back propagation algorithm in the training process until the cost function J is smaller than the set precision or the maximum iteration number is reached, and finishing the training.
The excitation functions of the hidden layers all select a logistic function, and the excitation functions of the output layers select a linear function g (x) =x.
Optimizing the initial weight and threshold of the BP neural network by adopting a genetic algorithm, and specifically comprising the following steps:
s1: firstly, determining the weight and the number of thresholds of a neural network according to a topological graph of the BP neural network model, and following the following formula:
Figure BDA0003749236780000101
wherein N is um I represents the i-th layer neuron, H, which is the total number of the weight and the threshold value i The number of nodes for the i-th layer neuron;
s2: carrying out coding operation on a weight threshold value of the neural network by adopting a real number coding mode, initializing a population, randomly taking a value between (-1, 1) initial weight threshold values, and setting an adaptability function of the population as F1;
Figure BDA0003749236780000102
where F1 is the fitness value, ρ1 is the enhancement phase component predicted by the neural network using the initial weight and threshold, η1 is the enhancement phase volume fraction predicted by the neural network using the initial weight and threshold, δ1 is the enhancement phase average predicted by the neural network using the initial weight and thresholdSize ρ 0 To enhance the phase composition expectancy, η 0 To enhance the phase volume fraction expectations, δ 0 Average size expectancy for the reinforcement phase;
s3: calculating fitness values of all individuals in the population, selecting the individuals with high fitness from the parents by using a roulette algorithm to perform selection operation, and generating next-generation individuals, wherein the probability of each selected individual follows the following formula:
Figure BDA0003749236780000103
wherein p is k Probability of being selected for kth individual, F k The fitness value of the kth individual, K is the total number of individuals in the population;
s4: the method comprises the steps of performing cross operation on individuals in a population, setting cross probability as pc, generating a random number, performing cross operation if the random number is smaller than the cross probability, randomly selecting two individuals and randomly selecting cross bits during cross, and performing cross operation according to the following formula:
Figure BDA0003749236780000111
wherein a is kj Is the real number of the kth chromosome at position j, a lj Is the real number of the first chromosome at the j position, and b is the random number between (0 and 1);
s5: the individual in the population is subjected to mutation operation, the mutation probability is set to be pm, if a random number is generated and is smaller than the mutation probability, the mutation operation is carried out, when the individual is mutated, the mutation operation is carried out by randomly selecting an individual and randomly selecting mutation positions, and the mutation operation is carried out according to the following formula:
Figure BDA0003749236780000112
Figure BDA0003749236780000113
wherein a is ij Is the real number of the ith chromosome at the j bit, G is the current iteration number, f (G) is a variation factor, G max For maximum iteration number, a max Is a ij Upper limit of the value, a min Is a ij The lower limit of the value is that r and r' are random numbers between (0, 1);
s6: and (3) cycling the steps S3 to S5 until a satisfactory fitness value is obtained or a limited iteration number is reached, and outputting an optimal individual, namely the individual with the largest fitness value.
Dividing the target part into a plurality of subareas according to the tissue performance distribution requirement of the target part, and reversely pushing out multistage cryogenic process parameters required by each subarea by combining the obtained nonlinear mapping relation, so as to obtain a series of cryogenic process parameter distribution combinations corresponding to the interior of the target part when the multistage cryogenic process target part is adopted.
And thirdly, carrying out high-flux numerical simulation on the zoned multistage cryogenic treatment process by combining the obtained cryogenic process parameter distribution combination, and determining the cryogenic process parameter combination corresponding to the tissue performance distribution requirement of the temperature distribution or microstructure distribution closest to the target part in the numerical simulation as the optimal cryogenic process parameter combination of different areas inside the target part.
The multi-stage cryogenic process is simulated by heat transfer or by heat transfer-microstructure coupling using commercially available numerical simulation software such as Deform, abaqus, ansys or Comsol.
And step four, combining the geometric division area of the target part and the optimal combination of the cryogenic treatment parameters, and performing independent cryogenic treatment on the part to be treated in a partitioning way to obtain the target part.
The invention is further described in detail in the following examples.
Example 1
The target part is a high-temperature alloy GH2132 dual-performance platy part, the working temperature of the middle part of the part is low, the size of a structural grain is required to be small, enough strength, creep resistance and fatigue resistance are ensured, the working temperature born by the edge part is high, a coarse grain structure is required, and the room temperature plasticity, creep resistance and fatigue expansion resistance are ensured. Therefore, different regions of the target plate-like part are required to have microstructure structures with different grain sizes so as to obtain corresponding mechanical properties. According to the actual service condition of the part, the target gradient structure part is divided into 4 characteristic areas, grains at the central part are of ultrafine grain structures, average grains are smaller than 1 mu m, edge parts are of coarse grain structures, average grain size is 100 mu m, and grain sizes of middle areas are gradually transited. Meanwhile, the Vickers hardness of the central part is not lower than 380HV, the room temperature tensile strength is not lower than 800MPa, the room temperature tensile plasticity is not lower than 20%, the Vickers hardness of the edge area is not lower than 300HV, the room temperature tensile strength is not lower than 500MPa, and the room temperature tensile plasticity is not lower than 40%. The zoned multistage cryogenic treatment method comprises the following steps:
(1) The tissue-performance evolution rule of the high-temperature alloy GH2132 is obtained through a multi-stage cryogenic treatment experiment, and the multi-stage cryogenic treatment process parameters are selected as temperatures, two-stage temperature curves comprising temperature T 1 And T 2 The microstructure parameters are selected as grain size, and the performance parameters are selected as vickers hardness, tensile strength and room temperature stretch plasticity. And a nonlinear mapping relation between multistage cryogenic process parameters and microstructure-performance is established through a BP neural network.
The cryogenic treatment temperature is set to be-50 ℃, -75 ℃, -100 ℃, -125 ℃, -150 ℃, -175 ℃, -196 ℃, the heat preservation time is unified to be 1h, the temperature rising and falling rate is 50 ℃/min, and the treatment frequency is 1. And determining the average grain size after the multistage cryogenic treatment by taking metallographic pictures after metallographic grinding and polishing, and counting the grain size distribution and the average grain size by using imageJ image software. Vickers Hardness was measured by a 430SVD vickers Hardness tester from Wilson Hardness, usa, under a load of 1kg, and 5 points were measured for each sample for Hardness, and the maximum and minimum values of the data were removed and averaged to obtain the Hardness of the sample. The stretched bar stock is a standard stretching sample with the diameter of 10mm, and specifically, room temperature quasi-static stretching experiments are carried out according to the requirements of GB/T228-2010 'room temperature stretching test method for metallic materials', and room temperature stretching strength and room temperature stretching plasticity data are counted.
And establishing a nonlinear mapping relation among temperature, grain size, vickers hardness, room temperature tensile strength and room temperature tensile plasticity through a BP neural network, and taking experimental data obtained by a pre-experiment as a training sample until ideal prediction precision is achieved.
(2) Dividing the target gradient structure plate-shaped part into 4 characteristic areas according to the actual service working condition of the part, and reversely pushing out multistage cryogenic treatment parameters required by each subarea by combining the obtained nonlinear mapping relation, so as to obtain a series of cryogenic process parameter distribution combinations in the multistage cryogenic treatment target part.
(3) And (3) combining the step (2) to obtain a series of cryogenic process parameter combinations in the target part, and performing high-throughput numerical simulation on the partitioned multistage cryogenic treatment process, wherein the numerical simulation adopts com software. And determining the combination of the parameters of the cryogenic treatment process corresponding to the tissue performance distribution requirement of the temperature distribution or microstructure distribution closest to the target part in numerical simulation as the optimal combination of the parameters of the cryogenic treatment of different areas in the target part. In this embodiment, parameters of the multistage cryogenic treatment of each sub-region are region I: t (T) 1 Is at-175 ℃, T 2 At-196 ℃, region ii: t (T) 1 Is at-150deg.C, T 2 -175 ℃, region iii: t (T) 1 At-125 ℃, T 2 -150 ℃, region iv: t (T) 1 Is at-100deg.C, T 2 Is-125 ℃. The temperature rising and reducing rate is unified to be 50 ℃/min, and the heat preservation time of each temperature stage is 1h.
(4) And (3) combining the geometric dividing region of the plate-shaped part with the target gradient structure and the optimal cryogenic treatment parameter combination determined in the step (3), adjusting the geometric space of each chamber of the multi-chamber zoned cryogenic device, and performing zoned independent cryogenic treatment on each chamber according to the optimal cryogenic treatment parameter determined in the step (3), thereby obtaining the plate-shaped part with the target gradient structure.
Example 2
The target part is a high-temperature alloy GH2132 dual-performance disc-shaped part, the working temperature of the middle part of the same part is low, the size of the structural grains is required to be small, enough strength, creep resistance and fatigue resistance are ensured, the working temperature born by the edge part is high, the coarse grain structure is required, and the room temperature plasticity, creep resistance and fatigue expansion resistance are ensured. Therefore, different regions of the target plate-like part are required to have microstructure structures with different grain sizes so as to obtain corresponding mechanical properties. According to the actual service condition of the part, the target gradient structure part is divided into 3 characteristic areas, grains at the central part are of ultrafine grain structures, average grains are smaller than 1 mu m, edge parts are of coarse grain structures, average grain size is 100 mu m, and grain sizes of middle areas are gradually transited. Meanwhile, the Vickers hardness of the central part is not lower than 380HV, the room temperature tensile strength is not lower than 800MPa, the room temperature tensile plasticity is not lower than 20%, the Vickers hardness of the edge area is not lower than 300HV, the room temperature tensile strength is not lower than 500MPa, and the room temperature tensile plasticity is not lower than 40%.
And pre-experiment to obtain experimental data samples, and training the neural network by utilizing the data samples until the ideal prediction precision is achieved. And (3) reversely pushing the multistage cryogenic treatment parameters of each region according to the nonlinear mapping relation between the technological parameters and the tissue-performance established by the neural network. Determining an optimal process parameter combination by combining high-throughput numerical simulation; and (3) performing cryogenic treatment on the target gradient structure part by using a zoned multistage cryogenic treatment device suitable for the disc-shaped part, and taking out the part after the treatment is finished to obtain the target gradient structure disc-shaped part with the gradient grain structure.
The invention also provides a part preparation device based on the partitioned multistage cryogenic treatment, which adopts the part preparation method based on the partitioned multistage cryogenic treatment to prepare the part. The apparatus is formed with a plurality of independent cryogenic treatment chambers, each capable of independently cryogenic treating a section of the part to be prepared.
Referring to fig. 2, 3, 4 and 5, the apparatus for preparing a part based on zoned multistage cryogenic treatment according to an embodiment of the present invention includes an upper pipeline chamber 1, an upper chamber 2, a lower chamber 3, a lower pipeline chamber 4, a connection mechanism 5, a liquid nitrogen pipe 6, a moving mechanism 7, a heat insulation layer 8, a resistance heating wire 9, a thermocouple 10, a thermocouple signal wire 12, a temperature control system 13 and a heat insulation plate 14.
The upper pipeline chamber 1, the upper chamber 2, the lower chamber 3 and the lower pipeline chamber 4 are sequentially connected together from top to bottom through a connecting mechanism 5, the upper pipeline chamber 1 is fixedly connected with the upper chamber 2, the lower chamber 3 is fixedly connected with the lower pipeline chamber 4, and the upper chamber 2 is rotatably connected with one side of the lower chamber 3. The upper pipeline chamber 1 and the lower pipeline chamber 4 are both box bodies, the upper chamber 2 and the lower chamber 3 are rectangular frames, and the structures and the sizes of the two are respectively corresponding to realize the closing.
The upper chamber 2 is formed with a first accommodating cavity, the lower chamber 3 is formed with a second accommodating cavity, and when the upper chamber 2 is abutted against the lower chamber 3 through rotation, the first accommodating cavity is communicated with the second accommodating cavity to form an accommodating cavity. The first accommodating cavity is internally provided with a plurality of heat insulation plates 14 at intervals, the second accommodating cavity is also provided with a plurality of heat insulation plates 14 at intervals, and the number and the positions of the heat insulation plates 14 in the first accommodating cavity correspond to the number and the positions of the heat insulation plates 14 in the second accommodating cavity respectively so as to divide the accommodating cavity into a plurality of independent cryogenic treatment chambers. The two opposite heat insulation boards 14 are respectively provided with a containing groove, the shape and the size of the two containing grooves are respectively corresponding to those of the corresponding area of the part to be prepared, and the clamping grooves are used for clamping the corresponding area of the part so as to facilitate the independent cryogenic treatment of the area. In the present embodiment, the part to be produced is a plate-like gradient structure part 11.
The liquid nitrogen pipe 6 is divided into an inlet pipe, an outlet pipe and branch pipes, the number of the inlet pipes and the number of the outlet pipes are the same, and the number of the inlet pipes and the number of the outlet pipes are the same as the number of the cryogenic treatment chambers. One ends of the inlet pipes extend into the upper pipeline chamber 1 and then are connected with the branch pipes, the branch pipes are n-shaped, and two ends of the branch pipes penetrate through the bottom plate of the upper pipeline chamber 1 and then extend into the corresponding cryogenic treatment chambers. One ends of the plurality of outlet pipes extend into the lower pipeline chamber 4 and then are connected with the branch pipes, and two ends of the branch pipes respectively penetrate through the bottom plate of the lower pipeline chamber 4 and then enter the cryogenic treatment chamber, so that the inlet pipe, the cryogenic treatment chamber and the outlet pipes are communicated.
The two ends of each cryogenic treatment chamber are symmetrically provided with a resistance heating wire 9 and a thermocouple 10 respectively. The inner wall of each cryogenic treatment chamber is paved with a heat insulation layer 8, and the heat insulation layer 8 can be a vacuum heat insulation plate, an aerogel felt, aluminum silicate fiber and the like; the inner walls are isolated by using sealing gaskets to cool the cooling medium of different cryogenic treatment chambers, the contact parts of the inner walls and the parts use conformal gaskets to ensure the tightness between the chambers, and the sealing gaskets can be gaskets with poor heat conductivity and good sealing effect such as rubber gaskets, asbestos gaskets and the like.
Each heat insulation plate 14 is respectively connected with a moving mechanism 7, and the moving mechanism 7 is used for supporting and driving the heat insulation plates 14 to move so as to change the space of the cryogenic treatment chambers at two sides of the heat insulation plates 14. The thermocouple 10 is connected to the temperature control system 13 through a thermocouple signal wire 12, and the temperature control system 13 is also connected to the resistance heating wire 9, a cooling medium supply system and an inlet pipe connected to the cooling medium supply system.
In this embodiment, the cooling medium may be liquid nitrogen, liquid helium or a mixed liquid or gas of the liquid nitrogen, the liquid helium and a medium such as alcohol, and the cooling medium is introduced into the cryogenic treatment chamber through a cooling pipe; the temperature sensors can be thermocouples and are symmetrically arranged at two ends of the gradient part to be subjected to the cryogenic treatment, and of course, the temperature sensors can also be of other types, the determination of the temperature of the cryogenic treatment chamber is the average value of temperature measured values of the two temperature sensors, and the temperature control system controls the temperature of the corresponding cryogenic treatment chamber by adjusting the electric heating power of the corresponding resistance heating wire and the flow of the cooling medium; the moving mechanism is responsible for adjusting the position of the heat-insulating inner wall between the chambers, flexibly adjusting the space size of each chamber and supporting and moving parts inside the deep cooling device.
Referring to fig. 6, 7, 8 and 9, another embodiment of the present invention provides a part manufacturing apparatus based on the zoned multistage cryogenic treatment, which is substantially the same as the part manufacturing apparatus based on the zoned multistage cryogenic treatment provided in the above embodiment, except for the shape of the heat insulation plate and the arrangement of the liquid nitrogen pipe. The part to be prepared in this embodiment is a disc-shaped gradient structure part 15, the heat insulation plates are correspondingly formed by arc-shaped sheets, two opposite ends of each arc-shaped sheet are overlapped and connected into a circle and then are respectively arranged in the first accommodating cavity and the second accommodating cavity, the heat insulation plates positioned in the first accommodating cavity are coaxially arranged, and the heat insulation plates positioned in the second accommodating cavity are coaxially arranged, so that the accommodating cavity is divided into a plurality of annular cryogenic treatment chambers. Wherein the size of the space of the corresponding cryogenic treatment chamber is changed by changing the size of the non-overlapping area at the two opposite ends of the arc-shaped sheet. The outlet pipe and the inlet pipe are respectively communicated with the corresponding cryogenic treatment chamber through the straight branch pipes.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (10)

1. The preparation method of the part based on the zoned multistage cryogenic treatment is characterized by comprising the following steps of:
(1) Obtaining a tissue-performance evolution rule of a material component of a target part through a multistage cryogenic treatment experiment, and establishing a nonlinear mapping relation between multistage cryogenic process parameters and microstructure-performance through a neural network;
(2) Dividing the target part into a plurality of subareas according to the tissue performance distribution requirement of the target part, and reversely pushing out multistage cryogenic treatment parameters required by each subarea by combining the obtained nonlinear mapping relation, so as to obtain a series of cryogenic process parameter distribution combinations corresponding to the interior of the target part when the multistage cryogenic treatment target part is adopted;
(3) Carrying out high-flux numerical simulation on the zoned multistage cryogenic treatment process by combining the obtained cryogenic process parameter distribution combinations, and determining the cryogenic process parameter combination corresponding to the tissue performance distribution requirement of the temperature distribution or microstructure distribution closest to the target part in the numerical simulation as the optimal cryogenic process parameter combination of different areas inside the target part;
(4) And combining the geometric division area of the target part and the optimal cryogenic treatment parameter combination, and performing independent cryogenic treatment on the part to be treated in a partitioning manner to obtain the target part.
2. The method for preparing the part based on the zoned multistage cryogenic treatment according to claim 1, wherein the method comprises the following steps: the acquisition of the tissue-performance evolution law of the material composition of the target part comprises the following steps: setting orthogonal experiments or single-factor experiments in a preset cryogenic treatment parameter range by taking a material of a target part as an initial experimental object, carrying out multistage cryogenic treatment on the initial experimental object under different cryogenic treatment process parameter conditions, and carrying out microstructure characterization and performance test on a sample obtained by cryogenic treatment to obtain microstructure characteristic parameters and performance data in the sample under different cryogenic treatment parameter conditions, thereby obtaining a multistage cryogenic treatment process parameter-microstructure-performance database.
3. The method for preparing the part based on the zoned multistage cryogenic treatment according to claim 2, wherein the method comprises the following steps: multistage cryogenic treatment refers to a process in which a plurality of heat preservation and temperature rise processes are carried out from an initial treatment temperature to a minimum treatment temperature; the microstructure characteristic parameters include one or more of grain size, dislocation density, retained austenite volume fraction, size of carbide phase, and volume fraction; the multistage cryogenic treatment process parameters comprise one or more of temperature, heat preservation time, temperature rising and falling speed and treatment times.
4. The method for preparing the part based on the zoned multistage cryogenic treatment according to claim 1, wherein the method comprises the following steps: the nonlinear mapping relation between the multistage cryogenic process parameters and the microstructure-performance comprises a cryogenic process parameter and microstructure relation model, a microstructure-performance relation model and a cryogenic process parameter and performance relation model.
5. The method for preparing the part based on the zoned multistage cryogenic treatment according to claim 4, wherein the method comprises the following steps: each relation model is described by adopting a BP neural network model containing a plurality of hidden layers, wherein the establishment of the nonlinear mapping relation of the cryogenic process parameters and the microstructure comprises the following steps:
taking a set of cryogenic process parameters obtained by a multistage cryogenic treatment experiment as input, taking the obtained microstructure characteristic parameter set as output, constructing and training a BP neural network model containing multiple hidden layers, and selecting proper excitation functions for each hidden layer and output layer; optimizing the initial weight and threshold of the BP neural network by using a genetic algorithm to obtain the weight and threshold of the optimal individual; and assigning the obtained weight and threshold of the optimal individual to the BP neural network model, and updating the weight and threshold of each hidden layer by using an error back propagation algorithm in the training process until the cost function J is smaller than the set precision or the maximum iteration number is reached, and finishing the training.
6. The method for preparing the part based on the zoned multistage cryogenic treatment according to claim 5, wherein the method comprises the following steps: the excitation functions of the hidden layers all select a logistic function, and the excitation functions of the output layers select a linear function g (x) =x.
7. The method for preparing the part based on the zoned multistage cryogenic treatment according to claim 5, wherein the method comprises the following steps: optimizing the initial weight and threshold of the BP neural network by adopting a genetic algorithm, and specifically comprising the following steps:
s1: firstly, determining the weight and the number of thresholds of a neural network according to a topological graph of the BP neural network model, and following the following formula:
Figure FDA0004101508430000031
wherein Num is the total number of weights and thresholds, i represents the i-th layer neuron, H i The number of nodes for the i-th layer neuron;
s2: carrying out coding operation on a weight threshold value of the neural network by adopting a real number coding mode, initializing a population, randomly taking a value between (-1, 1) initial weight threshold values, and setting an adaptability function of the population as F1;
Figure FDA0004101508430000032
where F1 is the fitness value, ρ1 is the enhancement phase component predicted by the neural network using the initial weight and threshold, η1 is the enhancement phase volume fraction predicted by the neural network using the initial weight and threshold, δ1 is the enhancement phase average size predicted by the neural network using the initial weight and threshold, ρ 0 To enhance the phase composition expectancy, η 0 To enhance the phase volume fraction expectations, δ 0 Average size expectancy for the reinforcement phase;
s3: calculating fitness values of all individuals in the population, selecting the individuals with high fitness from the parents by using a roulette algorithm to perform selection operation, and generating next-generation individuals, wherein the probability of each selected individual follows the following formula:
Figure FDA0004101508430000033
wherein p is k Probability of being selected for kth individual, F k The fitness value of the kth individual, K is the total number of individuals in the population;
s4: the method comprises the steps of performing cross operation on individuals in a population, setting cross probability as pc, generating a random number, performing cross operation if the random number is smaller than the cross probability, randomly selecting two individuals and randomly selecting cross bits during cross, and performing cross operation according to the following formula:
Figure FDA0004101508430000034
wherein a is kj Is the real number of the kth chromosome at position j, a lj Is the real number of the first chromosome at the j positionB is a random number between (0, 1);
s5: the individual in the population is subjected to mutation operation, the mutation probability is set to be pm, if a random number is generated and is smaller than the mutation probability, the mutation operation is carried out, when the individual is mutated, the mutation operation is carried out by randomly selecting an individual and randomly selecting mutation positions, and the mutation operation is carried out according to the following formula:
Figure FDA0004101508430000041
Figure FDA0004101508430000042
wherein a is ij Is the real number of the ith chromosome at the j bit, G is the current iteration number, f (G) is a variation factor, G max For maximum iteration number, a max Is a ij Upper limit of the value, a min Is a ij The lower limit of the value is that r and r' are random numbers between (0, 1);
s6: and (3) cycling the steps S3 to S5 until a satisfactory fitness value is obtained or a limited iteration number is reached, and outputting an optimal individual, namely the individual with the largest fitness value.
8. Part preparation equipment based on multistage cryogenic treatment of subregion, its characterized in that: the apparatus employs the partitioned multistage cryogenic treatment-based part preparation method of any one of claims 1 to 7 to prepare a part; the apparatus is formed with a plurality of independent cryogenic treatment chambers, each capable of independently cryogenic treating a section of the part to be prepared.
9. The partitioned multi-stage cryogenic treatment-based part preparation apparatus of claim 8, wherein: each cryogenic treatment chamber is respectively provided with an independent resistance heating wire, a temperature sensor, a cooling medium inlet and outlet pipe and a moving mechanism, so that each cryogenic treatment chamber can independently work to carry out cryogenic treatment on a local area of a target part.
10. The zoned multistage cryogenic treatment-based part preparation apparatus of claim 9, wherein: the equipment further comprises a plurality of heat insulation plates, wherein the equipment is provided with a containing cavity, and the plurality of heat insulation plates are arranged in the containing cavity at intervals so as to divide the containing cavity into a plurality of independent cryogenic treatment chambers; the heat insulation plate is also used for bearing parts to be prepared; each heat insulating plate is connected with one moving mechanism, and the moving mechanism is used for driving the heat insulating plates to move so as to change the space size of the cryogenic treatment chambers at two sides of the heat insulating plates.
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