CN116694919B - Optimization method and system for bearing bainite heat treatment process - Google Patents
Optimization method and system for bearing bainite heat treatment process Download PDFInfo
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- 229910001563 bainite Inorganic materials 0.000 title claims abstract description 54
- 238000000034 method Methods 0.000 title claims abstract description 52
- 238000010438 heat treatment Methods 0.000 title claims abstract description 33
- 230000008569 process Effects 0.000 title claims abstract description 27
- 238000005457 optimization Methods 0.000 title claims description 32
- 238000010791 quenching Methods 0.000 claims abstract description 149
- 230000000171 quenching effect Effects 0.000 claims abstract description 148
- 238000001354 calcination Methods 0.000 claims abstract description 145
- 238000001514 detection method Methods 0.000 claims abstract description 33
- 238000012545 processing Methods 0.000 claims abstract description 31
- 229910001566 austenite Inorganic materials 0.000 claims description 39
- 229910000831 Steel Inorganic materials 0.000 claims description 23
- 239000010959 steel Substances 0.000 claims description 23
- 238000003754 machining Methods 0.000 claims description 18
- 239000000463 material Substances 0.000 claims description 18
- 238000001816 cooling Methods 0.000 claims description 17
- 229910002651 NO3 Inorganic materials 0.000 claims description 16
- NHNBFGGVMKEFGY-UHFFFAOYSA-N Nitrate Chemical compound [O-][N+]([O-])=O NHNBFGGVMKEFGY-UHFFFAOYSA-N 0.000 claims description 16
- 229910001562 pearlite Inorganic materials 0.000 claims description 13
- 238000012216 screening Methods 0.000 claims description 11
- 238000003837 high-temperature calcination Methods 0.000 claims description 7
- 238000010276 construction Methods 0.000 claims description 6
- 238000013528 artificial neural network Methods 0.000 claims description 5
- 238000005279 austempering Methods 0.000 claims description 3
- 238000012372 quality testing Methods 0.000 claims 2
- 230000000694 effects Effects 0.000 abstract description 5
- 239000007769 metal material Substances 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 238000012549 training Methods 0.000 description 4
- 238000005255 carburizing Methods 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 150000003839 salts Chemical class 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 229910052804 chromium Inorganic materials 0.000 description 1
- 239000011651 chromium Substances 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 229910000734 martensite Inorganic materials 0.000 description 1
- 238000005496 tempering Methods 0.000 description 1
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D11/00—Process control or regulation for heat treatments
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D1/00—General methods or devices for heat treatment, e.g. annealing, hardening, quenching or tempering
- C21D1/18—Hardening; Quenching with or without subsequent tempering
- C21D1/19—Hardening; Quenching with or without subsequent tempering by interrupted quenching
- C21D1/20—Isothermal quenching, e.g. bainitic hardening
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- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D1/00—General methods or devices for heat treatment, e.g. annealing, hardening, quenching or tempering
- C21D1/34—Methods of heating
- C21D1/44—Methods of heating in heat-treatment baths
- C21D1/46—Salt baths
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D1/00—General methods or devices for heat treatment, e.g. annealing, hardening, quenching or tempering
- C21D1/62—Quenching devices
- C21D1/63—Quenching devices for bath quenching
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D9/00—Heat treatment, e.g. annealing, hardening, quenching or tempering, adapted for particular articles; Furnaces therefor
- C21D9/40—Heat treatment, e.g. annealing, hardening, quenching or tempering, adapted for particular articles; Furnaces therefor for rings; for bearing races
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21D—MODIFYING THE PHYSICAL STRUCTURE OF FERROUS METALS; GENERAL DEVICES FOR HEAT TREATMENT OF FERROUS OR NON-FERROUS METALS OR ALLOYS; MAKING METAL MALLEABLE, e.g. BY DECARBURISATION OR TEMPERING
- C21D2211/00—Microstructure comprising significant phases
- C21D2211/002—Bainite
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Abstract
The invention discloses a method and a system for optimizing a bearing bainite heat treatment process, which relate to the technical field of bearing processing, and the method comprises the following steps: basic information of a bearing to be processed is obtained, a calcination control parameter and a quenching control parameter are obtained in a matching mode, isothermal quenching is carried out according to the parameters, and a bearing sample is obtained; carrying out quality detection on a bearing sample according to the standard parameters of the bearing, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results; optimizing by taking the standard bearing quality parameter as the optimizing direction to obtain the optimized isothermal temperature and the optimized isothermal time; and carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time. The invention solves the technical problem of poor quality of bearing products caused by unreasonable arrangement of isothermal temperature and isothermal time of bainite heat treatment in the prior art, and achieves the technical effect of improving the quality of bearing products by optimizing isothermal temperature and isothermal time.
Description
Technical Field
The invention relates to the technical field of bearing processing, in particular to a method and a system for optimizing a bearing bainite heat treatment process.
Background
Bearings are an important component in contemporary mechanical devices. The main function of the bearing is to support the mechanical rotator, reduce the friction coefficient in the motion process and ensure the rotation precision, and the existing production and manufacture of the bearing mostly adopts two manufacturing processes, namely, high-carbon chromium bearing steel is adopted and a martensite quenching process is adopted, and the bearing has high hardness but insufficient toughness after heat treatment. The other is to adopt carburizing steel and the like to carry out carburizing, quenching and low-temperature tempering, the heat treatment process is complex, the time is long, the cost is high, and the service life is short. At present, a heat treatment process is adopted, and the problems of complex treatment process, long production period, high cost and energy consumption, poor product quality and the like exist.
Disclosure of Invention
The application provides an optimization method and system of a bearing bainite heat treatment process, which are used for solving the technical problem of poor quality of bearing products caused by unreasonable isothermal temperature and isothermal time settings of bainite heat treatment in the prior art.
In a first aspect of the present application, there is provided a method of optimizing a bearing bainite heat treatment process, the method comprising: obtaining basic information of a bearing to be processed, wherein the basic information comprises steel materials, workpiece sizes and workpiece shapes; constructing a bearing machining expert database, inputting the steel material, the workpiece size and the workpiece shape into the bearing machining expert database, and matching to obtain a calcination control parameter and a quenching control parameter, wherein the calcination control parameter comprises a calcination temperature and a calcination time, and the quenching control parameter comprises an isothermal temperature and an isothermal time; heating the bearing to be processed to an austenitic state according to the calcination control parameter control high-temperature calcination equipment to obtain an austenitic bearing; placing the austenitic bearing into a nitrate bath furnace, and carrying out isothermal quenching according to the quenching control parameters to obtain a bearing sample; carrying out quality detection on the bearing sample according to the bearing standard parameters, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results; optimizing in the optimized isothermal temperature interval and the optimized isothermal time interval by taking the standard bearing quality parameter as the optimizing direction to obtain the optimized isothermal temperature and the optimized isothermal time; and carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time.
In a second aspect of the present application, there is provided a system for optimizing a bearing bainite heat treatment process, the system comprising: the bearing basic information acquisition module is used for acquiring basic information of a bearing to be processed, wherein the basic information comprises steel materials, workpiece sizes and workpiece shapes; the control parameter acquisition module is used for constructing a bearing machining expert database, inputting the steel material, the workpiece size and the workpiece shape into the bearing machining expert database, and matching to obtain a calcination control parameter and a quenching control parameter, wherein the calcination control parameter comprises a calcination temperature and a calcination time, and the quenching control parameter comprises an isothermal temperature and an isothermal time; the austenite bearing acquisition module is used for heating the bearing to be processed to an austenite state according to the calcination control parameter control high-temperature calcination equipment to obtain an austenite bearing; the bearing sample obtaining module is used for placing the austenitic bearing into a nitrate bath furnace, and carrying out isothermal quenching according to the quenching control parameters to obtain a bearing sample; the optimized parameter interval acquisition module is used for carrying out quality detection on the bearing sample according to the bearing standard parameters, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results; the optimization parameter acquisition module is used for optimizing in the optimization isothermal temperature interval and the optimization isothermal time interval by taking the standard bearing quality parameter as an optimizing direction to obtain the optimization isothermal temperature and the optimization isothermal time; and the isothermal quenching module is used for carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the application provides an optimization method of a bearing bainite heat treatment process, which relates to the technical field of bearing processing, and obtains a calcination control parameter and a quenching control parameter by obtaining basic information of a bearing to be processed and matching, and uses the parameters for isothermal quenching to obtain a bearing sample; the quality detection is carried out on the bearing sample to obtain an optimized isothermal temperature interval and an optimized isothermal time interval, the optimization is carried out by taking the standard bearing quality parameter as the optimization direction to obtain an optimized isothermal temperature and an optimized isothermal time, and the bearing is subjected to isothermal quenching by using the optimized quenching parameter, so that the technical problem that the quality of the bearing product is poor due to unreasonable setting of the isothermal temperature and isothermal time of bainite heat treatment in the prior art is solved, and the technical effect of improving the quality of the bearing product by optimizing the isothermal temperature and isothermal time is realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an optimization method of a bearing bainite heat treatment process according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a bearing sample obtained in an optimization method of a bearing bainite heat treatment process according to an embodiment of the present application;
fig. 3 is a schematic flow chart of obtaining an optimized isothermal temperature interval and an optimized isothermal time interval in an optimization method of a bearing bainite heat treatment process according to the embodiment of the present application;
fig. 4 is a schematic diagram of an optimized system structure of a bainite heat treatment process for a bearing according to an embodiment of the present application.
Reference numerals illustrate: the device comprises a bearing basic information acquisition module 11, a control parameter acquisition module 12, an austenitic bearing acquisition module 13, a bearing sample acquisition module 14, an optimized parameter interval acquisition module 15, an optimized parameter acquisition module 16 and an isothermal quenching module 17.
Detailed Description
The application provides an optimization method of a bearing bainite heat treatment process, which is used for solving the technical problem of poor bearing product quality caused by unreasonable isothermal temperature and isothermal time settings of bainite heat treatment in the prior art.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
As shown in fig. 1, the application provides an optimization method of a bearing bainite heat treatment process, which comprises the following steps:
s100: obtaining basic information of a bearing to be processed, wherein the basic information comprises steel materials, workpiece sizes and workpiece shapes;
specifically, basic information of the bearing to be processed is obtained by looking up a specification or inquiring a manufacturer, wherein the basic information comprises steel grade required to be used, size of a workpiece, shape of the workpiece and the like, and the steel grade, the size of the workpiece, the shape of the workpiece and the like are used as reference data for bearing processing to be carried out subsequently.
S200: constructing a bearing machining expert database, inputting the steel material, the workpiece size and the workpiece shape into the bearing machining expert database, and matching to obtain a calcination control parameter and a quenching control parameter, wherein the calcination control parameter comprises a calcination temperature and a calcination time, and the quenching control parameter comprises an isothermal temperature and an isothermal time;
specifically, a plurality of past time historical bearing processing cases are collected, cases meeting the bearing quality standard are screened out, the historical bearing basic information to be processed, the historical calcining control parameters and the historical bearing calcining quality in the cases are extracted, and the bearing processing expert database is constructed through the historical bearing basic information to be processed, the historical calcining control parameters, the historical bearing calcining quality and the corresponding relation of the historical bearing calcining quality. Inputting the steel material, the workpiece size and the workpiece shape of the current bearing to be processed into the bearing processing expert database for matching to obtain the current bearing to be processed, wherein the calcining control parameters comprise calcining temperature and calcining time of the bearing to be processed, the calcining temperature is generally about 800 ℃, the quenching control parameters comprise isothermal temperature and isothermal time of the bearing to be processed according to the steel material, the isothermal temperature refers to a temperature value when isothermal quenching is carried out, the isothermal time refers to a duration of isothermal quenching is carried out, and the isothermal time is 30-60 minutes. The calcination control parameter and the quenching control parameter can be used as reference data for the subsequent calcination and quenching of the currently-processed bearing.
Further, step S200 of the embodiment of the present application further includes:
s210: the bearing machining expert library comprises a calcining machining module and a quenching machining module;
s220: based on big data, carrying out information inquiry by taking bearing calcination as an index condition to obtain a plurality of historical bearing basic information to be processed, a plurality of historical calcination control parameters and a plurality of historical bearing calcination results;
s230: the basic information of the historical bearing to be processed, the historical calcination control parameters and the historical bearing calcination result have a corresponding relation, and the basic information of the historical bearing to be processed comprises steel materials, workpiece sizes and workpiece shapes of the historical bearing to be processed;
s240: the historical calcination control parameters comprise historical calcination temperature and historical calcination time, and the historical bearing calcination result is represented by a bearing calcination quality coefficient;
s250: screening the historical bearing calcination results according to preset bearing calcination quality standard coefficients, and extracting the historical bearing basic information to be processed and the historical calcination control parameters corresponding to the historical bearing calcination results meeting the preset bearing calcination quality standard coefficients to obtain a historical bearing basic information set to be processed and a historical calcination control parameter set;
S260: and constructing the calcination processing module based on the corresponding relation among the set of the historical bearing basic information to be processed, the set of the historical calcination control parameters, the historical bearing basic information to be processed and the historical calcination control parameters.
Specifically, the bearing processing expert library consists of a calcining processing module and a quenching processing module, wherein the calcining processing module is used for matching corresponding calcining control parameters according to basic information of a bearing to be processed. The construction process of the calcining processing module can be as follows: and carrying out information query by using bearing calcination as an index condition in a big data retrieval mode to obtain a plurality of bearing calcination processing cases, extracting a plurality of historical bearing basic information to be processed, a plurality of historical calcination control parameters and a plurality of historical bearing calcination results in the cases, wherein the historical bearing basic information to be processed, the historical calcination control parameters and the historical bearing calcination results are in one-to-one correspondence, the historical bearing basic information to be processed comprises steel materials, workpiece sizes and workpiece shapes of the historical bearing to be processed, the historical calcination control parameters comprise historical calcination temperature and historical calcination time, and the historical bearing calcination results are represented by bearing calcination quality coefficients. Further, a professional presets a bearing calcination quality standard coefficient according to the use requirement of the bearing, the preset bearing calcination quality standard coefficient is used as a reference, the historical bearing calcination result is screened, the historical bearing calcination result reaching the preset bearing calcination quality standard coefficient is reserved, corresponding historical bearing basic information and historical calcination control parameters to be processed are extracted, the corresponding historical bearing basic information and historical calcination control parameter set to be processed are arranged, the historical bearing basic information set and the historical calcination control parameter set are used as construction data, the corresponding relation between the historical bearing basic information to be processed and the historical calcination control parameter is combined to construct the calcination processing module, and the corresponding calcination control parameters can be selected based on the basic information of the current bearing to be processed.
Further, step S210 of the embodiment of the present application further includes:
s211: based on big data, carrying out information inquiry by taking bearing quenching as an index condition to obtain a plurality of pieces of historical bearing basic information to be processed, a plurality of historical quenching control parameters and a plurality of historical bearing quenching results, wherein the historical quenching control parameters comprise isothermal temperature and isothermal time;
s212: the basic information of the historical bearing to be processed, the historical quenching control parameters and the historical bearing quenching result have corresponding relations;
s213: screening the historical bearing quenching results according to preset bearing quenching quality standard coefficients, and extracting the historical to-be-processed bearing basic information and the historical quenching control parameters corresponding to the historical bearing quenching results meeting the preset bearing quenching quality standard coefficients to obtain a historical to-be-processed bearing basic information set and a historical quenching control parameter set;
s214: and constructing the quenching processing module based on the corresponding relation among the set of the basic information of the historical bearing to be processed, the set of the historical quenching control parameters, the basic information of the historical bearing to be processed and the historical quenching control parameters.
Specifically, a big data retrieval mode is used, information inquiry is carried out by taking bearing quenching as an index condition, a plurality of bearing quenching processing cases are obtained, a plurality of historical bearing basic information to be processed, a plurality of historical quenching control parameters and a plurality of historical bearing quenching results in the cases are extracted, the historical quenching control parameters comprise isothermal temperature and isothermal time when quenching is carried out, and the historical bearing basic information to be processed, the historical quenching control parameters and the historical bearing quenching results are in one-to-one correspondence. Further, a professional presets a bearing quenching quality standard coefficient according to the use requirement of the bearing, the preset bearing quenching quality standard coefficient is used as a reference, the historical bearing quenching result is screened, the historical bearing quenching result reaching the preset bearing quenching quality standard coefficient is reserved, corresponding historical to-be-processed bearing basic information and historical quenching control parameters are extracted, the corresponding historical to-be-processed bearing basic information set and historical quenching control parameter set are arranged, the historical to-be-processed bearing basic information set and the historical quenching control parameter set are used as construction data, the corresponding relation between the historical to-be-processed bearing basic information and the historical quenching control parameters is combined to construct the quenching processing module, and the quenching processing module can be used for selecting corresponding quenching control parameters based on the basic information of the current to-be-processed bearing.
S300: heating the bearing to be processed to an austenitic state according to the calcination control parameter control high-temperature calcination equipment to obtain an austenitic bearing;
specifically, the above calcination control parameters obtained by matching in the bearing processing expert database are used to control the high-temperature calcination equipment to heat the bearing to be processed to the calcination temperature and keep the calcination for a period of time, and the bearing to be processed is heated to an austenite state, wherein the austenite state is a state in which austenite is formed when steel is heated to a critical point or above, and the austenite state has a great influence on the performance of the metal material. Generally, the higher the austenite content, the higher the strength and hardness of the metal material, but the toughness and plasticity are correspondingly reduced. Conversely, the lower the austenite content, the strength and hardness of the metal material will decrease, but the toughness and plasticity will increase accordingly. Therefore, in practical application, according to different requirements, the performance of the metal material can be adjusted by controlling the content and the distribution state of austenite in the metal material. The bearing in the austenitic state is an austenitic bearing.
S400: placing the austenitic bearing into a nitrate bath furnace, and carrying out isothermal quenching according to the quenching control parameters to obtain a bearing sample;
Specifically, the austenite bearing is placed in a nitrate bath furnace, the temperature of the nitrate bath furnace is controlled to carry out isothermal quenching according to the obtained quenching control parameters, the austenite is rapidly cooled to isothermal temperature at a cooling speed greater than a critical cooling speed, and then the austenite bearing is placed in the nitrate bath furnace to carry out bainite transformation. The nitrate bath furnace refers to an industrial furnace which uses molten salt liquid as a heating medium and immerses a workpiece in the salt liquid for heating. The cooled bainite is used as a bearing sample and can be used as a sample for subsequent bearing quality detection.
Further, as shown in fig. 2, step S400 of the embodiment of the present application further includes:
s410: cooling the austenitic bearing under the condition of room temperature, and when the temperature of the austenitic bearing meets the isothermal temperature, placing the austenitic bearing into a nitrate bath furnace for isothermal quenching;
s420: and when the isothermal quenching time meets the isothermal time, obtaining a bainite bearing after quenching, cooling the bainite bearing under the condition of room temperature, and obtaining a bearing sample after cooling.
Specifically, the austenite bearing is placed under the room temperature condition for cooling, when the temperature of the austenite bearing is cooled to the isothermal temperature, the austenite bearing is placed into a nitrate bath furnace, the temperature is kept at the isothermal temperature for quenching, when the isothermal quenching time is reached, the quenching of the austenite bearing is completed, the bainite bearing is obtained, the bainite bearing is placed under the room temperature condition for cooling, the cooled bainite bearing can be used as a bearing sample, and the bainite bearing can be used as a sample for subsequent bearing quality detection.
S500: carrying out quality detection on the bearing sample according to the bearing standard parameters, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results;
specifically, the quality detection is carried out on the bearing sample, the quality parameter of the sample bearing is obtained, the difference value of the bearing standard parameter and the quality parameter of the sample bearing is compared, the optimized difference value of the isothermal temperature interval and the isothermal time interval is calculated, and the optimized isothermal temperature interval and the optimized isothermal time interval are obtained through the difference value, so that the optimized isothermal temperature and the optimized isothermal time are selected.
Further, as shown in fig. 3, step S500 of the embodiment of the present application further includes:
s510: obtaining an isothermal temperature threshold and an isothermal time threshold of bearing quenching;
s520: carrying out microscopic image acquisition on the bearing sample to obtain a microscopic image of the bearing sample;
s530: extracting features of an austenite image, a lower bainite image, a grain image and a pearlite image in the microscopic image of the bearing sample to obtain an austenite image ratio, a lower bainite image ratio, a grain image and a pearlite image ratio;
S540: carrying out bearing sample quality detection according to the austenite image proportion, the lower bainite image proportion, the grain image and the pearlite image proportion to obtain a bearing sample quality detection result;
s550: and obtaining an optimized isothermal temperature interval and an optimized isothermal time zone based on the isothermal temperature threshold, the isothermal time threshold and the bearing sample quality detection result.
Specifically, the professional determines an isothermal temperature threshold of bearing quenching, i.e. the temperature interval of the bainite, generally between 260 ℃ and 400 ℃, and an isothermal time threshold, i.e. the isothermal quenching time of the bainite, generally between 30 and 60 minutes. And acquiring microscopic images of the bearing sample by using a digital microscope, extracting an austenite image, a lower bainite image, a grain image and a pearlite image in the microscopic images of the bearing sample, and calculating the ratio characteristics of the austenite image, the lower bainite image, the grain image and the pearlite image. And detecting the quality of the bearing sample by using the austenite image ratio, the lower bainite image ratio, the grain image and the pearlite image ratio, wherein the detection rule can be as follows: judging the contents of austenite and lower bainite according to the ratio of the austenite image and the ratio of the lower bainite image, if the ratio of the lower bainite image does not meet a threshold value, indicating that the lower bainite content is insufficient, keeping the isothermal quenching temperature unchanged, and increasing the isothermal quenching time; if pearlite images exist, the quenching temperature and the quenching time are required to be increased; if the grains in the image are too large, the isothermal temperature is too high or the isothermal time is too long. Further, according to the detection result of the bearing sample quality, the isothermal time required to be increased or decreased can be calculated, the optimized isothermal temperature interval and the optimized isothermal time interval can be determined by combining the isothermal temperature threshold and the isothermal time threshold, and by way of example, the isothermal time during quenching of the sample is assumed to be 45 minutes, the original isothermal time threshold is 30-60 minutes, and according to the detection result of the bearing sample quality, the isothermal time is required to be increased, and the optimized isothermal time threshold is 45-60 minutes. The optimized isothermal temperature interval and the optimized isothermal time interval can be used for selecting the optimized isothermal temperature and the optimized isothermal time.
S600: optimizing in the optimized isothermal temperature interval and the optimized isothermal time interval by taking the standard bearing quality parameter as the optimizing direction to obtain the optimized isothermal temperature and the optimized isothermal time;
in particular, the quality parameter of the standard bearing is used as the optimizing direction, an iterative optimizing mode is adopted, the optimizing isothermal temperature interval and the optimizing isothermal time interval are optimized,
further, step S600 of the embodiment of the present application further includes:
s610: setting a first optimized isothermal temperature and a first optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
s620: constructing a bearing quality analysis model based on a neural network, and inputting the first optimized isothermal temperature and the first optimized isothermal time into the bearing quality analysis model to obtain a first bearing quality analysis result;
s630: setting a second optimized isothermal temperature and a second optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
s640: inputting the second optimized isothermal temperature and the second optimized isothermal time into the bearing quality analysis model to obtain a second bearing quality analysis result;
S650: comparing the first bearing quality analysis result with the second bearing quality analysis result;
s660: setting the first optimized isothermal temperature and the first optimized isothermal time to be at the current optimal isothermal temperature and the current optimal isothermal time when the first bearing quality analysis result is larger than the second bearing quality analysis result, and discarding the second optimized isothermal temperature and the second optimized isothermal time;
s670: when the first bearing mass analysis result is smaller than the second bearing mass analysis result, setting the second optimized isothermal temperature and the second optimized isothermal time to be the current optimal isothermal temperature and the current optimal isothermal time, and discarding the first optimized isothermal temperature and the first optimized isothermal time;
s680: and continuously performing iterative optimization until a preset optimizing threshold is met, and outputting the optimized isothermal temperature and the optimized isothermal time.
Specifically, one isothermal temperature and isothermal time are randomly selected from the optimized isothermal temperature interval and the optimized isothermal time interval as a first optimized isothermal temperature and a first optimized isothermal time. And collecting the historical isothermal temperature, the historical isothermal time and the historical bearing quality analysis result in the past period (which can be half a year, one year and the like, and the specific time can be adaptively adjusted according to the actual situation), dividing the sample data label into a training data set, a verification data set and a test data set as sample data, constructing a bearing quality analysis model based on a BP neural network, performing supervision training by using the training data set, the verification data set and the test data set until convergence, outputting data meeting the preset accuracy, and finishing the training of the bearing quality analysis model. And inputting the first optimized isothermal temperature and the first optimized isothermal time into the bearing mass analysis model, and taking the output result as a first bearing mass analysis result. Further, randomly selecting a second optimized isothermal temperature and a second optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval, inputting the second optimized isothermal temperature and the second optimized isothermal time into the bearing quality analysis model, and taking the output result as a second bearing quality analysis result.
Further, comparing the first bearing mass analysis result with the second bearing mass analysis result, screening out a better mass analysis result, and illustratively, when the first bearing mass analysis result is larger than the second bearing mass analysis result, taking the first optimized isothermal temperature and the first optimized isothermal time as the current optimal isothermal temperature and the current optimal isothermal time, and discarding the second optimized isothermal temperature and the second optimized isothermal time. And similarly, performing iterative optimization continuously until the optimizing times meet a preset optimizing threshold, and outputting the current optimal isothermal temperature and the current optimal isothermal time as the optimal isothermal temperature and the optimal isothermal time, wherein the preset optimizing threshold is set by specialized personnel according to the bearing quality requirement precision.
S700: and carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time.
Specifically, the obtained optimized isothermal temperature and optimized isothermal time are used for carrying out isothermal quenching, firstly, a bearing to be processed is heated to an austenite state, the austenite is rapidly cooled to the optimized isothermal temperature at a cooling speed larger than a critical cooling speed, then the bearing is placed into a nitrate bath furnace for bainite transformation, the bearing is taken out after the isothermal quenching time meets the optimized isothermal time, the bainite bearing is placed under a room temperature condition for cooling, the bearing is obtained after cooling is completed, and the bearing is subjected to isothermal quenching by using the optimized isothermal temperature and the optimized isothermal time, so that the quality of a bearing product can be effectively improved.
In summary, the embodiment of the application has at least the following technical effects:
according to the application, basic information of a bearing to be processed is obtained, a calcination control parameter and a quenching control parameter are obtained by matching, and isothermal quenching is carried out according to the calcination control parameter and the quenching control parameter, so that a bearing sample is obtained; carrying out quality detection on a bearing sample according to the standard parameters of the bearing, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results; optimizing by taking the standard bearing quality parameter as the optimizing direction to obtain the optimized isothermal temperature and the optimized isothermal time; and carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time.
The technical effect of improving the quality of bearing products by optimizing isothermal temperature and isothermal time is achieved.
Example two
Based on the same inventive concept as the optimization method of the bearing bainite heat treatment process in the foregoing embodiment, as shown in fig. 4, the present application provides an optimization system of the bearing bainite heat treatment process, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. Wherein the system comprises:
a bearing basic information acquisition module 11, which is used for acquiring basic information of a bearing to be processed, wherein the basic information comprises steel materials, workpiece sizes and workpiece shapes;
A control parameter obtaining module 12, configured to construct a bearing processing expert database, input the steel material, the workpiece size, and the workpiece shape into the bearing processing expert database, and obtain calcination control parameters and quenching control parameters in a matching manner, where the calcination control parameters include a calcination temperature and a calcination time, and the quenching control parameters include an isothermal temperature and an isothermal time;
an austenite bearing acquisition module 13, which is used for heating the bearing to be processed to an austenite state according to the calcination control parameter control high-temperature calcination equipment to obtain an austenite bearing;
a bearing sample obtaining module 14, configured to put the austenitic bearing into a nitrate bath furnace, and perform isothermal quenching according to the quenching control parameters, to obtain a bearing sample;
the optimized parameter interval acquisition module 15 is used for carrying out quality detection on the bearing sample according to the bearing standard parameters, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results;
the optimization parameter obtaining module 16 is configured to obtain an optimized isothermal temperature and an optimized isothermal time by using a standard bearing quality parameter as an optimization direction and performing optimization in the optimized isothermal temperature interval and the optimized isothermal time interval;
And an austempering module 17 for austempering the bearing according to the optimized isothermal temperature and the optimized isothermal time.
Further, the system further comprises:
the historical calcining data acquisition module is used for carrying out information inquiry by taking bearing calcining as an index condition based on big data to obtain a plurality of pieces of historical basic information of the bearing to be processed, a plurality of historical calcining control parameters and a plurality of historical bearing calcining results;
the historical calcining data screening module is used for screening the calcining result of the historical bearing according to a preset bearing calcining quality standard coefficient, extracting the basic information of the bearing to be processed and the historical calcining control parameter corresponding to the calcining result of the historical bearing meeting the preset bearing calcining quality standard coefficient, and obtaining a basic information set of the bearing to be processed and a historical calcining control parameter set;
the calcination processing module construction module is used for constructing the calcination processing module based on the corresponding relation among the historical bearing basic information set to be processed, the historical calcination control parameter set, the historical bearing basic information to be processed and the historical calcination control parameter;
Further, the system further comprises:
the historical quenching data acquisition module is used for carrying out information inquiry by taking bearing quenching as an index condition based on big data to obtain a plurality of pieces of historical basic information of the bearing to be processed, a plurality of historical quenching control parameters and a plurality of historical bearing quenching results, wherein the historical quenching control parameters comprise isothermal temperature and isothermal time;
the historical quenching data screening module is used for screening the quenching results of the historical bearings according to preset bearing quenching quality standard coefficients, extracting the basic information of the bearings to be processed and the historical quenching control parameters corresponding to the quenching results of the historical bearings meeting the preset bearing quenching quality standard coefficients, and obtaining a basic information set of the bearings to be processed and a historical quenching control parameter set;
the quenching processing module construction module is used for constructing the quenching processing module based on the corresponding relation among the historical bearing basic information set to be processed, the historical quenching control parameter set, the historical bearing basic information to be processed and the historical quenching control parameter;
Further, the system further comprises:
the isothermal quenching module is used for cooling the austenitic bearing under the condition of room temperature, and when the temperature of the austenitic bearing meets the isothermal temperature, the austenitic bearing is placed into a nitrate bath furnace for isothermal quenching;
the bearing sample acquisition module is used for acquiring a bainite bearing after quenching when the isothermal quenching time meets the isothermal time, cooling the bainite bearing under the room temperature condition, and acquiring a bearing sample after cooling;
further, the system further comprises:
the isothermal threshold acquisition module is used for acquiring an isothermal temperature threshold and an isothermal time threshold of bearing quenching;
the bearing sample microscopic image acquisition module is used for acquiring microscopic images of the bearing samples to obtain microscopic images of the bearing samples;
the feature extraction module is used for extracting features of an austenite image, a lower bainite image, a grain image and a pearlite image in the microscopic image of the bearing sample to obtain an austenite image ratio, a lower bainite image ratio, a grain image and a pearlite image ratio;
The sample quality detection result acquisition module is used for carrying out bearing sample quality detection according to the austenite image ratio, the lower bainite image ratio, the grain image and the pearlite image ratio to obtain a bearing sample quality detection result;
the optimized isothermal interval obtaining module is used for obtaining an optimized isothermal temperature interval and an optimized isothermal time interval based on the isothermal temperature threshold, the isothermal time threshold and the bearing sample quality detection result;
further, the system further comprises:
the first optimized isothermal parameter setting module is used for setting a first optimized isothermal temperature and a first optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
the first bearing quality analysis result acquisition module is used for constructing a bearing quality analysis model based on a neural network, inputting the first optimized isothermal temperature and the first optimized isothermal time into the bearing quality analysis model, and obtaining a first bearing quality analysis result;
The second optimized isothermal parameter setting module is used for setting a second optimized isothermal temperature and a second optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
the second bearing quality analysis result acquisition module is used for inputting the second optimized isothermal temperature and the second optimized isothermal time into the bearing quality analysis model to obtain a second bearing quality analysis result;
the analysis result comparison module is used for comparing the first bearing quality analysis result with the second bearing quality analysis result;
the mass analysis result optimizing module is used for setting the current optimal isothermal temperature and the current optimal isothermal time of the first optimal isothermal temperature and the first optimal isothermal time when the mass analysis result of the first bearing is larger than the mass analysis result of the second bearing, and discarding the second optimal isothermal temperature and the second optimal isothermal time; when the first bearing mass analysis result is smaller than the second bearing mass analysis result, setting the second optimized isothermal temperature and the second optimized isothermal time to be the current optimal isothermal temperature and the current optimal isothermal time, and discarding the first optimized isothermal temperature and the first optimized isothermal time;
And the optimized isothermal parameter obtaining module is used for continuously carrying out iterative optimization until the optimized isothermal temperature and the optimized isothermal time are output when a preset optimizing threshold value is met.
It should be noted that the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.
The specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
Claims (5)
1. A method for optimizing a bearing bainite heat treatment process, the method comprising:
obtaining basic information of a bearing to be processed, wherein the basic information comprises steel materials, workpiece sizes and workpiece shapes;
constructing a bearing machining expert database, inputting the steel material, the workpiece size and the workpiece shape into the bearing machining expert database, and matching to obtain a calcination control parameter and a quenching control parameter, wherein the calcination control parameter comprises a calcination temperature and a calcination time, and the quenching control parameter comprises an isothermal temperature and an isothermal time;
heating the bearing to be processed to an austenitic state according to the calcination control parameter control high-temperature calcination equipment to obtain an austenitic bearing;
placing the austenitic bearing into a nitrate bath furnace, and carrying out isothermal quenching according to the quenching control parameters to obtain a bearing sample;
carrying out quality detection on the bearing sample according to the bearing standard parameters, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results;
optimizing in the optimized isothermal temperature interval and the optimized isothermal time interval by taking the standard bearing quality parameter as the optimizing direction to obtain the optimized isothermal temperature and the optimized isothermal time;
Carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time;
the method comprises the steps of constructing a bearing machining expert database, inputting the steel material, the workpiece size and the workpiece shape into the bearing machining expert database, and obtaining calcination control parameters and quenching control parameters in a matching way, and further comprises the following steps:
the bearing machining expert library comprises a calcining machining module and a quenching machining module;
based on big data, carrying out information inquiry by taking bearing calcination as an index condition to obtain a plurality of historical bearing basic information to be processed, a plurality of historical calcination control parameters and a plurality of historical bearing calcination results;
the basic information of the historical bearing to be processed, the historical calcination control parameters and the historical bearing calcination result have a corresponding relation, and the basic information of the historical bearing to be processed comprises steel materials, workpiece sizes and workpiece shapes of the historical bearing to be processed;
the historical calcination control parameters comprise historical calcination temperature and historical calcination time, and the historical bearing calcination result is represented by a bearing calcination quality coefficient;
screening the historical bearing calcination results according to preset bearing calcination quality standard coefficients, and extracting the historical bearing basic information to be processed and the historical calcination control parameters corresponding to the historical bearing calcination results meeting the preset bearing calcination quality standard coefficients to obtain a historical bearing basic information set to be processed and a historical calcination control parameter set;
Constructing the calcination processing module based on the corresponding relation among the historical bearing basic information set to be processed, the historical calcination control parameter set, the historical bearing basic information to be processed and the historical calcination control parameter;
the optimizing is performed in the optimized isothermal temperature interval and the optimized isothermal time interval by taking the standard bearing quality parameter as an optimizing direction, so as to obtain the optimized isothermal temperature and the optimized isothermal time, and the method further comprises the following steps:
setting a first optimized isothermal temperature and a first optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
constructing a bearing quality analysis model based on a neural network, and inputting the first optimized isothermal temperature and the first optimized isothermal time into the bearing quality analysis model to obtain a first bearing quality analysis result;
setting a second optimized isothermal temperature and a second optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
inputting the second optimized isothermal temperature and the second optimized isothermal time into the bearing quality analysis model to obtain a second bearing quality analysis result;
comparing the first bearing quality analysis result with the second bearing quality analysis result;
Setting the first optimized isothermal temperature and the first optimized isothermal time to be at the current optimal isothermal temperature and the current optimal isothermal time when the first bearing quality analysis result is larger than the second bearing quality analysis result, and discarding the second optimized isothermal temperature and the second optimized isothermal time;
when the first bearing mass analysis result is smaller than the second bearing mass analysis result, setting the second optimized isothermal temperature and the second optimized isothermal time to be the current optimal isothermal temperature and the current optimal isothermal time, and discarding the first optimized isothermal temperature and the first optimized isothermal time;
and continuously performing iterative optimization until a preset optimizing threshold is met, and outputting the optimized isothermal temperature and the optimized isothermal time.
2. The method as recited in claim 1, further comprising:
based on big data, carrying out information inquiry by taking bearing quenching as an index condition to obtain a plurality of pieces of historical bearing basic information to be processed, a plurality of historical quenching control parameters and a plurality of historical bearing quenching results, wherein the historical quenching control parameters comprise isothermal temperature and isothermal time;
The basic information of the historical bearing to be processed, the historical quenching control parameters and the historical bearing quenching result have corresponding relations;
screening the historical bearing quenching results according to preset bearing quenching quality standard coefficients, and extracting the historical to-be-processed bearing basic information and the historical quenching control parameters corresponding to the historical bearing quenching results meeting the preset bearing quenching quality standard coefficients to obtain a historical to-be-processed bearing basic information set and a historical quenching control parameter set;
and constructing the quenching processing module based on the corresponding relation among the set of the basic information of the historical bearing to be processed, the set of the historical quenching control parameters, the basic information of the historical bearing to be processed and the historical quenching control parameters.
3. The method of claim 2, wherein said placing said austenitic bearing in a nitrate bath furnace austempering in accordance with said quench control parameters to obtain a bearing sample, further comprises:
cooling the austenitic bearing under the condition of room temperature, and when the temperature of the austenitic bearing meets the isothermal temperature, placing the austenitic bearing into a nitrate bath furnace for isothermal quenching;
And when the isothermal quenching time meets the isothermal time, obtaining a bainite bearing after quenching, cooling the bainite bearing under the condition of room temperature, and obtaining a bearing sample after cooling.
4. The method of claim 1, wherein the quality testing of the bearing sample based on the bearing standard parameters, obtaining an optimized isothermal temperature interval and an optimized isothermal time interval based on the quality testing results, further comprises:
obtaining an isothermal temperature threshold and an isothermal time threshold of bearing quenching;
carrying out microscopic image acquisition on the bearing sample to obtain a microscopic image of the bearing sample;
extracting features of an austenite image, a lower bainite image, a grain image and a pearlite image in the microscopic image of the bearing sample to obtain an austenite image ratio, a lower bainite image ratio, a grain image and a pearlite image ratio;
carrying out bearing sample quality detection according to the austenite image proportion, the lower bainite image proportion, the grain image and the pearlite image proportion to obtain a bearing sample quality detection result;
and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval based on the isothermal temperature threshold, the isothermal time threshold and the bearing sample quality detection result.
5. An optimization system for a bearing bainite heat treatment process, the system comprising:
the bearing basic information acquisition module is used for acquiring basic information of a bearing to be processed, wherein the basic information comprises steel materials, workpiece sizes and workpiece shapes;
the control parameter acquisition module is used for constructing a bearing machining expert database, inputting the steel material, the workpiece size and the workpiece shape into the bearing machining expert database, and matching to obtain a calcination control parameter and a quenching control parameter, wherein the calcination control parameter comprises a calcination temperature and a calcination time, and the quenching control parameter comprises an isothermal temperature and an isothermal time;
the austenite bearing acquisition module is used for heating the bearing to be processed to an austenite state according to the calcination control parameter control high-temperature calcination equipment to obtain an austenite bearing;
the bearing sample obtaining module is used for placing the austenitic bearing into a nitrate bath furnace, and carrying out isothermal quenching according to the quenching control parameters to obtain a bearing sample;
The optimized parameter interval acquisition module is used for carrying out quality detection on the bearing sample according to the bearing standard parameters, and obtaining an optimized isothermal temperature interval and an optimized isothermal time interval according to quality detection results;
the optimization parameter acquisition module is used for optimizing in the optimization isothermal temperature interval and the optimization isothermal time interval by taking the standard bearing quality parameter as an optimizing direction to obtain the optimization isothermal temperature and the optimization isothermal time;
the isothermal quenching module is used for carrying out isothermal quenching on the bearing according to the optimized isothermal temperature and the optimized isothermal time;
the historical calcining data acquisition module is used for carrying out information inquiry by taking bearing calcining as an index condition based on big data to obtain a plurality of pieces of historical basic information of the bearing to be processed, a plurality of historical calcining control parameters and a plurality of historical bearing calcining results;
the historical calcining data screening module is used for screening the calcining result of the historical bearing according to a preset bearing calcining quality standard coefficient, extracting the basic information of the bearing to be processed and the historical calcining control parameter corresponding to the calcining result of the historical bearing meeting the preset bearing calcining quality standard coefficient, and obtaining a basic information set of the bearing to be processed and a historical calcining control parameter set;
The calcination processing module construction module is used for constructing the calcination processing module based on the corresponding relation among the historical bearing basic information set to be processed, the historical calcination control parameter set, the historical bearing basic information to be processed and the historical calcination control parameter;
the first optimized isothermal parameter setting module is used for setting a first optimized isothermal temperature and a first optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
the first bearing quality analysis result acquisition module is used for constructing a bearing quality analysis model based on a neural network, inputting the first optimized isothermal temperature and the first optimized isothermal time into the bearing quality analysis model, and obtaining a first bearing quality analysis result;
the second optimized isothermal parameter setting module is used for setting a second optimized isothermal temperature and a second optimized isothermal time in the optimized isothermal temperature interval and the optimized isothermal time interval;
the second bearing quality analysis result acquisition module is used for inputting the second optimized isothermal temperature and the second optimized isothermal time into the bearing quality analysis model to obtain a second bearing quality analysis result;
The analysis result comparison module is used for comparing the first bearing quality analysis result with the second bearing quality analysis result;
the mass analysis result optimizing module is used for setting the current optimal isothermal temperature and the current optimal isothermal time of the first optimal isothermal temperature and the first optimal isothermal time when the mass analysis result of the first bearing is larger than the mass analysis result of the second bearing, and discarding the second optimal isothermal temperature and the second optimal isothermal time; when the first bearing mass analysis result is smaller than the second bearing mass analysis result, setting the second optimized isothermal temperature and the second optimized isothermal time to be the current optimal isothermal temperature and the current optimal isothermal time, and discarding the first optimized isothermal temperature and the first optimized isothermal time;
and the optimized isothermal parameter obtaining module is used for continuously carrying out iterative optimization until the optimized isothermal temperature and the optimized isothermal time are output when a preset optimizing threshold value is met.
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