Online fatigue life evaluation method and device based on temperature fluctuation

Abstract

The invention provides an on-line fatigue life evaluation method and device based on temperature fluctuation, the device comprises a memory, a processor and a program stored in the memory and capable of running on the processor, and when the processor executes the program, the following steps are realized: S1, carrying out step S2; processing the stress-time relation and the temperature-time relation of the parts in the running process of the gas turbine by adopting an online cycle counting method to obtain related stress information of the parts; s2, constructing a fatigue life evaluation mathematical model based on temperature fluctuation; and S3, based on the related stress information of the part and the fatigue life model based on the temperature fluctuation, fatigue accumulated damage evaluation is carried out to obtain the fatigue damage life. According to the method, the load information of the gas turbine during working can be processed in real time, online fatigue life evaluation is carried out on the part according to the load condition, and then the residual life prediction of the part is realized.

Description

Technical Field

[0001] The invention relates to the technical field of fatigue life assessment, and in particular to an online fatigue life assessment method and device based on temperature fluctuation. Background Art

[0002] In recent years, predictive maintenance of equipment components based on working conditions has received increasing attention. It can reduce unnecessary costs caused by regular maintenance and can also evaluate the life of equipment components in real time, improving the economic efficiency of equipment operation while also taking into account stability. This predictive maintenance requires continuous evaluation of the damage of components based on their load information.

[0003] In order to timely evaluate the damage status of these components, it is necessary to identify the load spectrum in time and substitute it into the corresponding life model. Finite element calculation is a common damage assessment method, but the long calculation process limits its online application; in addition, traditional cycle counting methods, such as rain flow counting, horizontal cross counting, peak counting, etc., are all offline counting methods. Before counting, it is necessary to traverse the complete load information and reconstruct the load spectrum to identify the largest half-cycle and full cycle as much as possible. It also ignores the effect of the load action order on the life, and is not suitable for online situations. Most of the existing online cycle counting methods are improved based on the rain flow counting method, but no one takes the temperature information of stress into account when counting.

[0004] Fatigue refers to the process in which a material or structure fails under cyclic loads, and is one of the main failure mechanisms of turbomachinery. Domestic and foreign scholars have proposed a variety of prediction models for fatigue life calculation. Among them, the MC model is widely used in engineering practice due to its simple form. However, since this model is only applicable to the case of cyclic symmetrical loads and cannot consider the influence of average stress on fatigue life, its scope of application has certain limitations. In order to consider the influence of average stress on fatigue life, the modified Morrow model corrects the average stress value through the pseudo-tensile stress-strain curve. The SWT model believes that the influence of average stress on fatigue life is related to the maximum stress, and the product of maximum stress and maximum strain amplitude remains unchanged as the damage control parameter. However, none of the above models consider the influence of temperature changes on fatigue life.

[0005] It should be noted that the above introduction to the technical background is only for the convenience of providing a clear and complete description of the technical solutions of the present application and for the convenience of understanding by those skilled in the art. It cannot be considered that the above technical solutions are well known to those skilled in the art simply because they are described in the background technology section of the present application. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide an online fatigue life assessment method and device based on temperature fluctuation, so as to solve the problem that the fatigue life assessment process in the prior art does not take temperature changes into consideration, resulting in inaccurate assessment.

[0007] To achieve the above object and other related objects, the present invention provides an online fatigue life assessment method based on temperature fluctuation, characterized in that it comprises at least the following steps:

[0008] S1, using the online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components;

[0009] S2, construct a mathematical model for fatigue life assessment based on temperature fluctuation;

[0010] S3, performing fatigue accumulation damage assessment based on relevant force information of the component and the fatigue life model based on temperature fluctuation to obtain fatigue damage life.

[0011] Preferably, the relevant stress information of the component includes at least the maximum stress, stress amplitude and characteristic temperature of the cycle.

[0012] Preferably, the process of using the online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components includes the following process:

[0013] The stress-time relationship of the component is processed to obtain the extreme value pile;

[0014] Counting the cycle periods and determining the cycle stresses and cycle action time based on the extreme value pile; wherein the cycle stresses at least include the cycle maximum stress and stress amplitude; and the cycle action time at least includes the cycle duration;

[0015] The cycles are processed according to the stress amplitude of each cycle to obtain the effective cycles;

[0016] determining a characteristic temperature for each effective cycle based on a temperature-time relationship and a duration of said cycle;

[0017] Perform stress-strain conversion for asymmetric cyclic loading of effective cycles.

[0018] Preferably, the stress-time relationship is a plurality of flow points stored in a stress set; three consecutive flow points in the stress-time relationship of the component are calculated and judged to obtain a judgment result; and an extreme value stack is obtained according to the judgment result.

[0019] Preferably, the stress values ​​of the three consecutive flow points in the extreme value pile are σ 1 , σ2 , σ 3 , if (σ 1 -σ 2 )*(σ 2 -σ 3 )<0, then σ 2 As the extreme point, σ 2 Keep to the extreme value heap; if (σ 1 -σ 2 )*(σ 2 -σ 3 )>0, then σ 2 As a non-extreme point, 2 give up.

[0020] Preferably, four consecutive extreme value points are read from the extreme value stack, and the four consecutive extreme value points are processed and judged. When it is judged to be a full cycle, the cycle count is 1, and when it is judged to be a half cycle, the cycle count is 0.5.

[0021] Preferably, the characteristic temperature of the effective cycle is:

[0022] T e =maxT(t begin , t end )

[0023] Where, T e is the characteristic temperature of the effective cycle; t begin is the cycle start time; t end The end time of the cycle.

[0024] Preferably, performing stress-strain conversion on asymmetric cyclic loading comprises:

[0025] (1) First convert the asymmetric cyclic load into a symmetric cyclic load;

[0026] (2) performing stress-strain conversion on the cyclic load based on the characteristic temperature.

[0027] Preferably, constructing a mathematical model for fatigue life assessment based on temperature fluctuation includes:

[0028] Determine the mathematical model for low cycle fatigue life assessment at different known temperatures;

[0029] Based on the mathematical model for evaluating low-cycle fatigue life at different known temperatures, a mathematical model for evaluating low-cycle fatigue life at unknown temperatures is derived;

[0030] A fatigue life assessment mathematical model based on temperature fluctuation is obtained according to the low cycle fatigue life assessment mathematical model of different known temperatures and the low cycle fatigue life assessment mathematical model of each unknown temperature.

[0031] To achieve the above-mentioned purpose and other related purposes, the present invention also provides an online fatigue life assessment device based on temperature fluctuation, comprising a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of the above-mentioned online fatigue life assessment method based on temperature fluctuation are implemented.

[0032] As described above, the online fatigue life assessment method and device based on temperature fluctuation of the present invention have the following beneficial effects:

[0033] The present invention discloses an online fatigue life assessment method and device based on temperature fluctuations. The device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: using an online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components; constructing a fatigue life assessment mathematical model based on temperature fluctuations; and performing fatigue accumulation damage assessment based on the relevant force information of the components and the fatigue life model based on temperature fluctuations to obtain the fatigue damage life. The present invention takes the influence of temperature fluctuations on fatigue life into consideration, making the online calculation and assessment of the entire fatigue life more accurate, specifically processing the load information of the gas turbine during operation in real time, obtaining the stress-time relationship and the temperature-time relationship, and accurately performing online fatigue life assessment on its components according to their load conditions, thereby realizing the remaining life prediction of the components. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic flow chart of the online fatigue life assessment method based on temperature fluctuation of the present invention. DETAILED DESCRIPTION

[0035] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0036] It should be noted that the illustrations provided in this embodiment are only used to illustrate the basic concept of the present invention in a schematic manner. Therefore, the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0037] The present invention takes into account the impact of temperature fluctuations on fatigue life, specifically reflects temperature fluctuations in the online cycle counting part and the fatigue life model respectively, and combines the online cycle counting and fatigue life counting models, which can greatly improve the accuracy of online life assessment of components. The present invention can be applied to the fields of online fatigue life assessment of hot end components of gas turbines and aircraft engines, online fatigue life of power semiconductor solder joints, etc.

[0038] Method Example:

[0039] like Figure 1 The figure shows a flow chart of the online fatigue life assessment method based on temperature fluctuation of the present invention. Figure 1 The online fatigue life assessment method based on temperature fluctuation of the present invention is introduced in detail. The online fatigue life assessment method based on temperature fluctuation of the present invention at least comprises the following steps:

[0040] S1, using the online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components;

[0041] The embodiment of the present invention takes the entire working state of a certain type of gas turbine from start-up to full load to shutdown as an example, and uses its operating data to establish boundary conditions. Since there are an infinite number of transient points in the entire start-up-full load-shutdown process, typical transient points (points where the rotation speed suddenly changes, points where the vibration displacement suddenly changes, etc.) are taken for calculation. CFD is used to calculate the temperature field of each component based on the boundary conditions established with actual data, and the temperature information of each transient point is imported into ANSYS to calculate the stress conditions of each component; the dangerous sections and dangerous points of the components are determined based on the stress conditions of the components, and the load and temperature information of the dangerous positions are recorded; the load-temperature-time information of each dangerous position in the entire start-up-full load-shutdown process is traversed, and the load-temperature-time information of the dangerous position is processed to obtain the stress-time relationship and the temperature-time relationship.

[0042] The stress-time relationship and temperature-time relationship of the components during the operation of the gas engine of the present invention can be obtained at least by a proxy model method, a response surface method or a Kriging simulation method.

[0043] The online cycle counting method of the present invention is an online cycle counting method combining temperature fluctuation on the basis of a four-point online rain flow counting method.

[0044] In the present invention, the online cycle counting method is used to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components, including the following process:

[0045] S11, processing the stress-time relationship of the component to obtain an extreme value pile;

[0046] In the present invention, the stress-time relationship is a plurality of flow points stored in the stress set. In other words, the stress values ​​stored in the stress set in chronological order are defined as flow points. The maximum stress value and the minimum stress value circulating in a cycle are crucial for fatigue life calculation, and any intermediate data points between the maximum stress value and the minimum stress value that are not related to fatigue calculation can be deleted. Therefore, the stress extreme value identification is to retain only the data points with reversed direction / slope, which requires at least three flow points to meet the judgment and identification.

[0047] The three continuous flow points in the stress-time relationship of the component are calculated and judged to obtain the judgment result; and the extreme value pile is obtained according to the judgment result.

[0048] Assume that the stress values ​​of three consecutive flow points are σ 1 , σ 2 , σ 3 , if (σ 1 -σ 2 )*(σ 2 -σ 3 )<0, then σ 2 As the extreme point, σ 2 Keep to the extreme value heap; if (σ 1 -σ 2 )*(σ 2 -σ 3 )>0, then σ 2 As a non-extreme point, 2 give up.

[0049] Specifically, if (σ 1 -σ 2 )*(σ 2 -σ 3 )<0, then σ 2 is the extreme point; when σ 2 >σ 1 When 2 is the maximum point; when σ 2 <σ 1 When 2 is the minimum point; at this time, σ 2 Store it in the extreme value pile, continue to read new incoming flow points backwards, and re-identify. 1 -σ 2 )*(σ 2 -σ 3 )>0, then σ 2 is a non-extreme point; at this time, remove σ 2 , continue to read new incoming flow points backward and re-identify; use the above method until all incoming flow points are identified.

[0050] S12, counting the cycle periods and determining the stresses of the cycle and the cycle action time based on the extreme value stack; wherein the cycle includes a full cycle and a half cycle, the stresses of the cycle include the maximum stress of the cycle, the stress amplitude and the average stress, and the cycle action time includes the cycle start time, the cycle end time and the cycle duration;

[0051] In the embodiment of the present invention, at least 5 extreme value points are stored in the extreme value pile. The cyclic counting in the present invention is improved on the idea of ​​four-point online rain flow counting. Therefore, in order to ensure that the points read in each subsequent cyclic counting method processing are extreme value points, at least 5 extreme value points should be stored in the extreme value pile, that is, the fourth value is judged to be an extreme value according to the fifth value.

[0052] Four consecutive extreme value points are read from the extreme value pile, and the four consecutive extreme value points are processed and judged. When it is judged to be a full cycle, the cycle count is 1, and when it is judged to be a half cycle, the cycle count is 0.5.

[0053] The cycle counting of the full cycle and the determination of each stress and cycle action time of the cycle in the present invention are as follows:

[0054] Assume that the stress values ​​of the four consecutive extreme value points read from the extreme value pile are σ` 1 ,σ` 2 ,σ` 3 ,σ` 4 , let Δσ 1 =|σ` 1 -σ` 2 |,Δσ 2 =|σ` 2 -σ` 3 |,Δσ 3 =|σ` 3 -σ` 4 |.

[0055] If Δσ 2 <Δσ 1 And Δσ 2 <Δσ 3 , then it is considered that Δσ 2 It constitutes a full cycle, and the maximum stress σ of the full cycle max =max(σ` 2 ,σ` 3 ), stress amplitude Mean stress The loop count is 1, and the extreme point σ` is eliminated 2 and extreme point σ` 3 , retain the extreme point σ 1 and the extreme point σ 4 , continue to read new incoming flow points (i.e., extreme value points in the extreme value pile) backward and re-identify.

[0056] Based on the relationship between loading information and loading time in the full cycle, the cycle action time for online fatigue life assessment in the full cycle is:

[0057] Cycle start time t begin The calculation formula is:

[0058] t begin =t 2

[0059] Cycle end time t end The calculation formula is:

[0060]

[0061] Cycle duration t hol The calculation formula is:

[0062] t hold =t end -t begin

[0063] In the formula, σ` 1 ,σ` 2 ,σ` 3 ,σ` 4 is the stress value (extreme value) at the inflow point; t 1 ,t 2 ,t 3 ,t 4 is the time corresponding to the four inflow points.

[0064] The cycle counting of the half cycle and the determination of each stress and cycle action time of the cycle in the present invention are as follows:

[0065] Assume that the stress values ​​of the four consecutive extreme value points read from the extreme value pile are σ` 1 ,σ` 2 ,σ` 3 ,σ` 4 , let Δσ 1 =|σ` 1 -σ` 2 |,Δσ 2 =|σ` 2 -σ` 3 |,Δσ 3 =|σ` 3 -σ` 4 |.

[0066] If Δσ 1 >Δσ 2 >Δσ 3 , Δσ 2 >Δσ 1 >Δσ 3, Δσ 2 >Δσ 3 >Δσ 1 or Δσ 3 >Δσ 2 >Δσ 1 When Δσ 1 It constitutes a half cycle, and the maximum stress σ of this half cycle max =max(σ` 1 ,σ` 2 ), stress amplitude Mean stress The loop count is 0.5, and the point σ is removed 1 , retaining point σ 2 , σ 3 , σ 4 , continue to read new incoming flow points backward and re-identify.

[0067] Referring to the full cycle time matching method, the cycle action times for online fatigue life assessment in the half cycle case are:

[0068] Cycle start time t begin The calculation formula is:

[0069] t begin =t 1

[0070] Cycle end time t end The calculation formula is:

[0071] t end =t 2

[0072] Cycle duration t hold The calculation formula is:

[0073] t hold =t end -t begin

[0074] In the formula, σ` 1 ,σ` 2 ,σ` 3 ,σ` 4 is the stress value (extreme value) at the inflow point; t 1 ,t 2 ,t 3 ,t 4 is the time corresponding to the four inflow points.

[0075] S13, processing the cycles according to the stress amplitude of each cycle to obtain effective cycles;

[0076] The purpose of the invalid cycle elimination of the present invention is to remove the negligible invalid fluctuations in the damage accumulation, and its judgment needs to be defined by a threshold value k, which is affected by multiple variables such as the operating speed, output power, and engine structure, and the k value is different under different conditions. It should be noted that the determination of the threshold value k does not affect the method proposed by the present invention.

[0077] For the cycle determined in step S12, if the stress amplitude of the cycle is greater than the set threshold, it is determined to be a valid cycle. It is considered as a valid cycle and is retained; if the cycle stress amplitude Then determine that it is an invalid loop and eliminate the loop, where k is a constant.

[0078] S14, determining a characteristic temperature of each effective cycle based on a temperature-time relationship and a duration of the cycle;

[0079] The characteristic temperature in the present invention refers to the temperature that best represents the identified cycle temperature history. In order to make the fatigue life assessment conservative, the maximum temperature experienced in the entire process from the beginning to the end of the identified cycle is taken as the characteristic temperature of the cycle, that is, the characteristic temperature of the effective cycle is selected based on the cycle duration and the temperature-time relationship in the present invention:

[0080] T e =maxT(t begin , t end )

[0081] Where, T e is the characteristic temperature of the identified cycle; t begin is the cycle start time; t end The end time of the cycle.

[0082] S15, stress-strain conversion for asymmetric cyclic loading of effective cycles.

[0083] The present invention performs stress-strain conversion on asymmetric cyclic loads, including:

[0084] (1) First convert the asymmetric cyclic load into a symmetric cyclic load;

[0085] Specifically, the working process of actual equipment is complex and changeable, and the loads borne by the components are also irregular random loads. However, most material specimens are obtained under symmetrical cyclic loads. In order to reduce the error in fatigue life calculation, it is necessary to convert the asymmetrical cyclic load into the symmetrical cyclic load according to the Goodman curve of the material.

[0086] As another implementation method, if the influence of the mean stress is considered in the subsequent fatigue life assessment mathematical model, this step can be omitted.

[0087] After completing the asymmetric cycle conversion, the yield strength of the material at the characteristic temperature needs to be compared with the maximum stress in the identified cycle to determine whether the component has plastic yield. If plastic yield occurs, the fatigue life assessment mathematical model considering temperature fluctuations is used. If plastic yield does not occur, the SWT model is used.

[0088] The calculation steps of the cyclic plastic strain are as follows:

[0089] The maximum stress of the cycle σ max The material used for the component has a characteristic temperature T in the cycle e The yield strength σ p Compare; if the maximum stress of the cycle σ max Greater than the yield strength σ p , the component is considered to be plastically deformed and its plastic strain can be calculated. The Neuber criterion states that the relationship between the local notch response and the applied elastic load is as follows:

[0090]

[0091] In the formula, ε and o are the local strain amplitude and local stress amplitude, K_t is the fatigue notch coefficient, S is the elastic stress, and E is the elastic modulus.

[0092] For a cyclic process, the local notch response will follow a stress-strain curve, usually represented by the Ramberg-Osgood equation defined as:

[0093]

[0094] Where K is the strain hardening coefficient and n' is the strain hardening exponent; both are temperature-dependent.

[0095] The traditional off-line conversion method roughly replaces the stress range and strain range with stress amplitude and strain amplitude. The conversion relationship in the present invention is:

[0096]

[0097] The stress-strain curve of the present invention changes with the change of temperature. In order to ensure the accuracy of the conversion result, the characteristic temperature of the identified cycle is used as the reference temperature for selecting the stress-strain curve during conversion.

[0098] (2) performing stress-strain conversion on the cyclic load based on the characteristic temperature.

[0099] Specifically, the size of plastic strain has a crucial influence on the fatigue life of the material. Neuber method, Glinka method, etc. are used for stress-strain conversion, but the stress-strain curve is related to temperature. In order to ensure the accuracy of the conversion result, the characteristic temperature of the identified cycle is used as the reference temperature selected for the stress-strain curve during conversion. After the present invention performs stress-strain conversion, the plastic strain of the cycle and the total strain of the cycle can be obtained.

[0100] The relevant stress information of the cycle output component after online cycle counting in the present invention includes the maximum stress, stress amplitude, average stress, cycle start time, cycle end time, cycle duration, number of cycles, full cycle / half cycle, characteristic temperature of the cycle, plastic strain of the cycle, and total strain of the cycle during the cycle.

[0101] S2, construct a mathematical model for fatigue life assessment based on temperature fluctuation;

[0102] According to the low cycle fatigue test data of the material at different temperatures, the plastic strain range Δz pa , total strain range Δε a and the maximum stress σ max The influence of cyclic damage is taken into account, and f(T) is introduced to describe the influence of temperature change on fatigue life. A functional relationship between low-cycle fatigue life and plastic strain range, total strain range, maximum stress and characteristic temperature is established in a form similar to the CDA model, and a fatigue life model based on temperature fluctuation is obtained.

[0103] S21, determine the mathematical model for low cycle fatigue life assessment at different known temperatures;

[0104] The present invention first determines a physical model for low cycle fatigue life assessment; then, the physical model for low cycle fatigue life assessment is fitted using acquired low cycle fatigue test data to determine a mathematical model for low cycle fatigue life assessment at different known temperatures.

[0105] lg 2 N f =lgA+n 1 lgΔε pa +n 2 lgΔε a +n 3 lgσ max

[0106] In the formula, Δε pa is the plastic strain range, Δε a is the total strain range, σ max is the maximum stress, N f is the fatigue life at temperature f(T), n 1 、n 2 、n3 are coefficients respectively, and A is a constant based on temperature fluctuation.

[0107] In the embodiment of the present invention, a nickel-based high-temperature alloy is tested on an MTS hydraulic servo test machine at test temperatures of RT, 300°C, 400°C, 500°C, 600°C and 650°C, respectively. The alloy is loaded by axial displacement control and the total strain ratio R is controlled. ε =-1, the cyclic waveform is a triangular wave, and the strain amplitude is controlled to be cyclically loaded within the strain level range of 0.4% to 1.2%, until the test bar breaks. This step can fit a new low-cycle fatigue life assessment model for a nickel-based high-temperature alloy at RT, 300℃, 400℃, 500℃, 600℃, and 650℃.

[0108] When the component does not undergo plastic deformation, the present invention assumes the SWT model taking into account the total strain range Δε_a, the maximum stress σ_max, and the temperature fluctuation as a low-cycle fatigue life assessment model, which is expressed as follows:

[0109]

[0110] Wherein σ_f∧′ is the fatigue strength coefficient; b is the fatigue strength index; ε_f∧′ is the fatigue extension coefficient; and c is the fatigue extension index. σ_f∧′, E, b, ε_f∧′, and c in the formula are all functions of temperature. In order to consider the influence of temperature fluctuation on fatigue life, the present invention selects the above parameters according to the characteristic temperature of the identified cycle.

[0111] When a component undergoes plastic deformation, the present invention takes into account the influence of the plastic strain range Δε_pa, the total strain range Δε_a and the maximum stress σ_max on the cyclic damage, and introduces f(T) to describe a new model for the influence of temperature change on fatigue life, that is, the low-cycle fatigue life flat model is expressed as follows:

[0112] lg 2 N f =lgA+n 1 lgΔε pa +n 2 lgΔε a +n 3 lgσ max

[0113] In the formula, Δε pa is the plastic strain range, Δε a is the total strain range, σ max is the maximum stress, N f is the fatigue life at temperature f(T), n 1 、n 2 、n 3 are coefficients respectively, and A is a constant considering temperature correction.

[0114] The present invention constructs different low-cycle fatigue life models when the component undergoes plastic deformation and when the component does not undergo plastic deformation.

[0115] S22, deriving a mathematical model for evaluating low-cycle fatigue life at each unknown temperature based on the mathematical model for evaluating low-cycle fatigue life at different known temperatures;

[0116] The present invention utilizes the least square method to interpolate and extrapolate a low cycle fatigue life assessment model at various unknown temperatures.

[0117] S23, obtaining a fatigue life assessment mathematical model for the full temperature field according to the low-cycle fatigue life assessment mathematical model for different known temperatures and the low-cycle fatigue life assessment mathematical model for each unknown temperature, wherein the fatigue life assessment mathematical model for the full temperature field is a fatigue life assessment mathematical model based on temperature fluctuations.

[0118] S3, performing fatigue accumulation damage assessment based on relevant force information of the component and the fatigue life model based on temperature fluctuation to obtain fatigue damage life.

[0119] The characteristic temperature of the cycle, the plastic strain of the cycle, the maximum stress of the cycle, and the total strain of the cycle of the relevant force information of the component are input into the fatigue life model of temperature fluctuation, and the fatigue life of each cycle under the influence of temperature is output after calculation and processing of the fatigue life model of temperature fluctuation.

[0120] Assuming that N cycles can be identified in the entire working process of a component during the operation of a gas turbine, if at the n1th cycle, the low-cycle fatigue life calculation formula at this temperature can be obtained based on the characteristic temperature of the n1th cycle, and the load information under this cycle is brought into the low-cycle fatigue calculation formula at this temperature, it can be known that the material has experienced Nf1 cycles of failure. If the n1th cycle count is a full cycle, the damage to this component caused by the n1th cycle is 1\Nf1; if the n1th cycle count is a half cycle, the damage to this component caused by the n1th cycle is 0.5\Nf1. Then, according to the linear damage accumulation criterion, the damage caused by N cycles is added up separately, and the damage to this component caused by such a working process can be quantified.

[0121] Assuming that the component fails when the cumulative damage reaches 1, the remaining service life is calculated by subtracting the damage caused from 1. Then, a typical operating condition can be selected to tell the user how many cycles the component will take under the typical operating condition before failing, thereby realizing the remaining service life prediction of the component.

[0122] The result of remaining life prediction achieved after online fatigue life assessment using the method of the present invention is basically the same as the result of equivalent operating hours of the same process gas turbine, which shows that the present invention can improve the accuracy of life assessment by taking temperature fluctuations into consideration.

[0123] Device Example:

[0124] To achieve the above-mentioned purpose and other related purposes, the present invention provides an online fatigue life assessment device based on temperature fluctuation, comprising a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of the online fatigue life assessment method based on temperature fluctuation described in the claim are implemented.

[0125] The processor in the present invention can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc., and can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0126] Among them, the detailed process of the steps of the online fatigue life assessment method based on temperature fluctuation has been described in detail in the method embodiment and will not be repeated here.

[0127] In summary, the present invention proposes an online fatigue life assessment method and device based on temperature fluctuation, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: using an online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components; constructing a fatigue life assessment mathematical model based on temperature fluctuation; and performing fatigue accumulation damage assessment based on the relevant force information of the components and the fatigue life model based on temperature fluctuation to obtain fatigue damage life. The present invention mainly takes into account the influence of temperature changes on fatigue life, constructs the existing online four-point rain flow counting method and fatigue life model, and determines the characteristic temperature of the effective cycle based on the action time of the cycle, that is, fully considers the temperature and combines the rain flow counting with the fatigue life, and can process the load information of the gas turbine in real time during operation, and perform online fatigue life assessment on its components according to its load conditions, thereby realizing the remaining life prediction of the components. Therefore, the present invention effectively overcomes the various shortcomings in the prior art and has a high industrial utilization value.

[0128] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. An online fatigue life assessment method based on temperature fluctuation, characterized in that: At least the following steps are included: S1, using the online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components; S2, construct a mathematical model for fatigue life assessment based on temperature fluctuation; S3, performing fatigue accumulation damage assessment based on relevant force information of the component and the fatigue life model based on temperature fluctuation to obtain fatigue damage life.

2. The online fatigue life assessment method based on temperature fluctuation according to claim 1 is characterized in that: The relevant stress information of the component includes at least the maximum stress of the cycle, the stress amplitude and the characteristic temperature of the cycle.

3. The online fatigue life assessment method based on temperature fluctuation according to claim 2 is characterized in that: The process of using the online cycle counting method to process the stress-time relationship and temperature-time relationship of the components during the operation of the gas turbine to obtain the relevant force information of the components includes the following process: The stress-time relationship of the component is processed to obtain the extreme value pile; Counting the cycle periods and determining the cycle stresses and cycle action time based on the extreme value pile; wherein the cycle stresses at least include the cycle maximum stress and stress amplitude; and the cycle action time at least includes the cycle duration; The cycles are processed according to the stress amplitude of each cycle to obtain the effective cycles; determining a characteristic temperature for each effective cycle based on a temperature-time relationship and a duration of said cycle; Perform stress-strain conversion for asymmetric cyclic loading of effective cycles.

4. The online fatigue life assessment method based on temperature fluctuation according to claim 3 is characterized in that: The stress-time relationship is a plurality of flow points stored in a stress set; three consecutive flow points in the stress-time relationship of the component are calculated and judged to obtain a judgment result; and an extreme value pile is obtained according to the judgment result.

5. The online fatigue life assessment method based on temperature fluctuation according to claim 4 is characterized in that: Assume that the stress values ​​of the three consecutive inflow points in the extreme value pile are σ1, σ2, and σ3 respectively. If (σ1-σ2)*(σ2-σ3)<0, then σ2 is an extreme point and σ2 is retained in the extreme value pile; if (σ1-σ2)*(σ2-σ3)>0, then σ2 is a non-extreme point and σ2 is discarded.

6. The online fatigue life assessment method based on temperature fluctuation according to claim 3 is characterized in that: Four consecutive extreme value points are read from the extreme value pile, and the four consecutive extreme value points are processed and judged. When it is judged to be a full cycle, the cycle count is 1, and when it is judged to be a half cycle, the cycle count is 0.

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7. The online fatigue life assessment method based on temperature fluctuation according to claim 3 is characterized in that: Characteristic temperature of effective cycle: T e =maxT(t begin ,t end ) Where, T e is the characteristic temperature of the effective cycle; t begin is the cycle start time; t end The end time of the cycle.

8. The online fatigue life assessment method based on temperature fluctuation according to claim 3 is characterized in that: Stress-strain conversion for asymmetric cyclic loading includes: (1) First convert the asymmetric cyclic load into a symmetric cyclic load; (2) performing stress-strain conversion on the cyclic load based on the characteristic temperature.

9. The online fatigue life assessment method based on temperature fluctuation according to claim 3 is characterized in that: The mathematical model for fatigue life assessment based on temperature fluctuations includes: Determine the mathematical model for low cycle fatigue life assessment at different known temperatures; Based on the mathematical model for evaluating low-cycle fatigue life at different known temperatures, a mathematical model for evaluating low-cycle fatigue life at unknown temperatures is derived; A fatigue life assessment mathematical model based on temperature fluctuation is obtained according to the low cycle fatigue life assessment mathematical model of different known temperatures and the low cycle fatigue life assessment mathematical model of each unknown temperature.

10. An online fatigue life assessment device based on temperature fluctuation, characterized in that: The invention comprises a memory, a processor and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of the online fatigue life assessment method based on temperature fluctuation described in any one of claims 1 to 9 are implemented.

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