Material deterioration evaluation device

Abstract

To provide a material deterioration evaluation device and a material deterioration evaluation method that can respond to diversified apparatus operation and achieve high reliable evaluation.SOLUTION: A material deterioration evaluation device for evaluating embrittlement of an apparatus includes: an operation data acquisition section 20 that detects a state of the apparatus and acquires the state as operation data; an operation data storage section 40 that saves the operation data; a temperature evaluation section 50 that calculates a predetermined evaluation portion temperature of the apparatus on the basis of the operation data; an evaluation component material storage section 30 that stores material data of a material forming the apparatus and embrittlement estimation formulas; an embrittlement evaluation section 60 that calculates an embrittlement quantity of the material forming the apparatus on the basis of the evaluation portion temperature, the material data, and the embrittlement estimation formulas; a risk evaluation section 70 that calculates a damage risk of the material forming the apparatus on the basis of the embrittlement quantity; and a recommended maintenance time presentation section 80 that presents a recommended maintenance time of the apparatus on the basis of the damage risk.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] Embodiments of the present invention relate to a material degradation evaluation apparatus and a material degradation evaluation method.

Background Art

[0002] It is known that materials used in high-temperature environments deteriorate over time. For example, turbines, casings, control valves, pipes, etc., which are the main components of thermal power plants, are exposed to high-temperature environments by the inflowing steam, and material degradation such as softening and embrittlement occurs over time. Since these material degradations are also related to strength characteristics such as the tensile strength and yield strength of the members, in order to appropriately evaluate the damage and life associated with equipment operation, it is necessary to quantitatively grasp the amount of material degradation and perform maintenance management such as degradation evaluation and component replacement at appropriate times.

[0003] Embrittlement, which is one type of material degradation, is a cause of brittle fracture of equipment. Brittle fracture is a fracture that involves little plastic deformation and is a phenomenon in which a crack rapidly propagates and leads to fracture. For example, in a turbine shaft (hereinafter simply referred to as a rotor) that rotates at high speed in a high-temperature environment, centrifugal stress is generated in the rotor during operation. There are also cases where the toughness of the rotor material decreases due to embrittlement, leading to brittle fracture due to centrifugal stress.

[0004] Embrittlement not only causes such brittle fractures but also affects crack growth characteristics. It is known that crack growth occurs due to creep and metal fatigue. Creep is a phenomenon in which when a metal material is used in a temperature environment of about half of its melting point, permanent deformation gradually occurs over time even under a low stress below the yield strength of the metal material, cracks are generated and propagated, and fracture occurs. Fatigue is a phenomenon in which cracks are generated and propagated and lead to damage even under a stress that does not cause fracture under static loading, due to repeated occurrence.

[0005] As these damage evaluation methods, there is a method of predicting and evaluating the crack growth amount and evaluating the damage amount of the member from the allowable crack length. The crack growth rate can be evaluated in advance from a material strength test, but this crack growth rate is affected by the embrittlement of the material, and the crack growth rate increases as the material embrittles. Also, the allowable crack length becomes shorter as the material embrittles. From these facts, in the evaluation of crack growth damage due to creep or fatigue, an evaluation combined with the evaluation of the amount of embrittlement of the material is required.

[0006] It is known that the embrittlement of materials is affected by the use temperature, operation time, and the amount of impurity elements contained in the materials. Examples of equipment for which embrittlement evaluation is important include rotors and turbine casings. A rotor is a rotating shaft that transmits the rotational force received by the moving blades from the steam flow to the generator, and a turbine casing is a cover that surrounds this rotor. The steam flow passes between this turbine casing and the rotor, and the moving blades provided on the outer periphery of the rotor obtain rotational force from the steam flow. A plurality of stages of moving blades are arranged on the outer periphery of the rotor, and when these moving blades receive the steam flow, a rotational force is generated in the rotor. On the other hand, the steam that has flowed in at a high temperature consumes energy by passing through each stage of the moving blades, so the steam temperature decreases as it goes downstream. Therefore, in addition to being used in a high-temperature environment, the rotor and turbine casing in contact with this steam also have a temperature distribution within the same member. Due to this temperature distribution, the degree of embrittlement of each part within the same member is different.

[0007] Conventional thermal power generation is mainly based on base load operation, and it was often operated near the rated output where the plant efficiency is maximized. In such an operation case, the temperature and pressure at each part of the rotor and turbine casing are very clear because delicate evaluation and optimization were performed at the time of turbine design, and there are also few fluctuations during operation. Therefore, by opening the turbine at the time of plant shutdown and periodically performing embrittlement evaluation, the transition of the amount of embrittlement could be grasped relatively easily.

[0008] However, in recent years, due to the popularization of renewable energy, the opportunities for partial load operation in thermal power plants have been increasing. The increase in partial load operation leads to an increase in off-design operation, and turbine equipment is exposed to temperatures not assumed during design for long periods of time. As described above, embrittlement is affected by the operating temperature, so the embrittlement rate also changes with the variation of the operating temperature, making it difficult to appropriately grasp the trend of the embrittlement amount only by the regular embrittlement measurement during the shutdown of conventional plants.

[0009] In addition, the shutdown of the power plant and the opening of the steam turbine lead to an increase in power generation costs due to labor and time. Therefore, it is difficult to ensure a sufficient number of embrittlement evaluations due to cost constraints.

[0010] For these reasons, there is a need for an embrittlement evaluation method and an evaluation device that do not involve equipment shutdown and opening and consider the temperature changes during equipment operation. Although there have been examples of studying the embrittlement prediction of turbine rotor materials from operating temperature, time, and material data, most cases have verified embrittlement in the range of approximately 300 to 450°C, and the applicability in actual machines that require evaluation in a wider temperature range is unknown. Depending on the material, there are also examples where a peak in the embrittlement amount occurs at around 300 to 400°C when held at a constant temperature. However, when assuming a combination with crack propagation, for example, in creep crack propagation, the higher the temperature, the faster the crack propagation rate, and crack propagation evaluation in the temperature range exceeding 500°C is also assumed. That is, the damage evaluation site is not necessarily the maximum embrittlement site, and a embrittlement prediction method applicable up to a wider temperature range of 500°C or higher is required.

[0011] Damage assessment devices that have already collected and used operation data and combined it with material degradation evaluations such as embrittlement have also been proposed. In this device, the amount of embrittlement is estimated using a prediction formula obtained in advance from experimental data. However, it is widely known that there are variations in various material properties, and embrittlement is no exception. That is, statistical evaluations that take into account variations are also necessary for embrittlement estimation. To improve the accuracy of statistical evaluations, a large amount of experimental data is required, but it takes time to obtain a sufficient amount of experimental data on embrittlement that progresses over time in advance. However, in conventional damage assessment devices and embrittlement evaluation methods, no methods or device configurations have been developed to utilize newly acquired embrittlement data and improve the estimation accuracy.

[0012] In the above, thermal power generation equipment such as turbine rotors and casings was used as an example, but embrittlement evaluation is not limited to these products and fields. For example, it is also expected to be applied to high-temperature members in other equipment such as high-temperature steam pipes, fuel cells, and engine parts.

[0013] In the damage assessment device that combines the above-described material degradation evaluation, the device configuration includes a sensor that acquires operation data, various arithmetic processing units, a data storage unit, and devices used for data input and presentation. Similarly, when configuring a device that predicts material degradation, material deformation, etc. based on operation data, similar processing is required in the sensor that acquires operation data and some of the arithmetic processing units. Therefore, when applying a plurality of evaluation devices such as damage assessment devices and material degradation assessment devices, the device configuration has overlapping functions. This is not desirable from the viewpoints of cost and space saving.

Prior Art Documents

Patent Documents

[0014]

Patent Document 1

Non-Patent Documents

[0015]

Non-Patent Document 1

Non-Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0016] Embrittlement is a type of material degradation that progresses over time and is affected by the operating temperature, operating time, and the amount of impurity elements in the material. In recent years, with the increasing opportunities for partial load operation in power generation equipment and the like, the operating temperature also fluctuates accordingly, making it difficult to appropriately predict and estimate embrittlement with conventional periodic embrittlement measurements. In addition, it is not desirable from a cost perspective to perform direct measurements involving product disassembly a sufficient number of times. Methods and devices for estimating the amount of embrittlement from the operating temperature, operating time, and the amount of impurity elements in the material have been proposed so far, but their applicability over a wide temperature range has been unknown. Furthermore, with existing embrittlement prediction formulas and embrittlement estimation devices using these formulas, it has been difficult to utilize newly acquired embrittlement measurement data, and an improvement in embrittlement estimation accuracy during the operation period of the device has not been expected. In addition, there are still problems with the applicability of devices that integrate various devices and arithmetic processing units constituting the evaluation device.

[0017] The present invention has been made in consideration of such conventional circumstances, and an object thereof is to provide a material degradation evaluation device and a material degradation evaluation method that can cope with diversification of equipment operation and realize highly reliable evaluation.

Means for Solving the Problems

[0018] The material degradation evaluation device according to the embodiment is a material degradation evaluation device for evaluating the embrittlement of equipment operated by a working fluid, and includes an operation data acquisition unit that detects the state of the equipment and acquires it as operation data, an operation data storage unit that stores the operation data, and based on the operation data, a predeterminedAt the evaluation site A temperature evaluation unit that calculates the temperature of the evaluation site, an evaluation component material storage unit that stores material data and embrittlement estimation formulas of the materials that make up the device, and based on the evaluation site temperature, the material data, and the embrittlement estimation formula, an embrittlement evaluation unit that calculates the amount of embrittlement of the materials that make up the device, a risk evaluation unit that calculates the damage risk of the materials that make up the device based on the amount of embrittlement, and a maintenance recommendation timing presentation unit that presents the recommended maintenance timing of the device based on the damage risk, and the temperature evaluation unit is (1) At the sensor measurement position The temperature data of the working fluid To the tower Based on At the said evaluation site Estimate the working fluid temperature, Of any site including the said evaluation site Calculate the evaluation site temperature based on the temperature obtained by calculating the heat balance by income and expenditure calculation, or (2) calculate the evaluation site temperature based on the temperature obtained by creating a relational expression between the measurement data of a sensor attached to a predetermined position of the device in advance and the evaluation site temperature Do In the embrittlement estimation formula used by the embrittlement evaluation unit, the amount of embrittlement is obtained as a function of the saturated embrittlement amount and time, and the saturated embrittlement amount of the evaluation site used for evaluating the amount of embrittlement is calculated by multiplying a constant (A1) determined experimentally in advance, a constant (B) calculated from the amount of elements contained in the materials that make up the device, an exponential function with the reciprocal of a linear function of temperature and a constant (A2) determined experimentally in advance as an exponent, and the saturated embrittlement amount of the evaluation site used for evaluating the amount of embrittlement is obtained by the following formula, saturated embrittlement amount = A1 × B × exp{A2 / (K)} where A1 and A2 are constants determined experimentally in advance, B is a constant calculated from the amount of elements contained in the materials that make up the device, and K is the absolute temperature.

Advantages of the Invention

[0019] According to the embodiment, it is possible to provide a material deterioration evaluation device and a material deterioration evaluation method that can cope with diversification of device operation and realize highly reliable evaluation.

Brief Description of the Drawings

[0020]

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MODE FOR CARRYING OUT THE INVENTION

[0021] Hereinafter, a material deterioration evaluation apparatus, a material deterioration evaluation method, and drawings according to embodiments will be described with reference to the drawings.

[0022] (Configuration of the First Embodiment) Hereinafter, the first embodiment will be described with reference to FIG. 1. As shown in FIG. 1, the material deterioration evaluation apparatus 1 of the first embodiment includes a sensor 10, a driving data acquisition unit 20, an evaluation component material storage unit 30, an input unit 35, a driving data storage unit 40, a temperature evaluation unit 50, a embrittlement evaluation unit 60, a risk evaluation unit 70, and a maintenance recommendation timing presentation unit 80.

[0023] The operation data acquisition unit 20 is an arithmetic block that acquires operation data via the sensor 10. The evaluation component material storage unit 30 stores material data of the embrittlement evaluation member. The input unit 35 is an input interface such as a keyboard, for example, and is used to pre-store material data and the like in the evaluation component material storage unit 30 and the like. It also has information communication terminals such as a LAN port, and can store data obtained from devices outside the apparatus in the evaluation component material storage unit 30 and the like. The operation data storage unit 40 stores operation data indicating the state of each part of the component parts forming the evaluation target device including the embrittlement evaluation member. The temperature evaluation unit 50 is an arithmetic block that evaluates the temperature of the evaluation part based on the operation data and the like acquired by the operation data acquisition unit 20. The embrittlement evaluation unit 60 is an arithmetic block that evaluates the amount of material embrittlement using the evaluation result of the temperature evaluation unit 50 and material data such as the chemical composition of the evaluation component. The risk evaluation unit 70 is an arithmetic block that evaluates the breakage risk based on the evaluation result of the amount of material embrittlement. The maintenance recommendation timing presentation unit 80 is an interface that presents the maintenance recommendation timing to the user based on the evaluation result of the breakage risk and the future plant operation plan.

[0024] The evaluation component material storage unit 30 stores material data such as the chemical composition and strength characteristics of the evaluation member. Further, the evaluation component material storage unit 30 may store the embrittlement evaluation results obtained at all times. The evaluation component material storage unit 30 can be realized by a non-volatile memory, a hard disk drive, or the like.

[0025] The operation data storage unit 40 stores operation data indicating the state of each part of the component that forms the evaluation target device including the embrittlement evaluation member. The operation data storage unit 40 can be realized by a non-volatile memory, a hard disk drive, or the like. The operation data storage unit 40 not only stores the acquired operation data, but may also store the past operation data before the start of the operation of this deterioration evaluation device as history data. The history data includes operation data obtained every moment, integrated histories such as total operation time, change amounts of temperature, pressure, etc. of each part at the time of startup, stop, or output fluctuation, change amounts per unit time, and the like. Note that, in addition to the operation data and its history data, the operation data storage unit 40 may store the state quantity corresponding to the operation data of the evaluation part and its history data.

[0026] (Sensor 10) The sensor 10 acquires the operation data of the evaluation target device including the embrittlement evaluation member. Examples of the operation data acquired by the sensor 10 include temperature, pressure, strain, etc. In addition to this, the sensor 10 may detect the output of the device, the load ratio, and the like. The sensor 10 is attached in advance at the time of the design and manufacture of the device, or newly added for evaluation.

[0027] An example of the application of the sensor 10 shows an operation example in the turbine casing. FIG. 2 shows an example of the attachment position of the sensor in the turbine casing 3 of the turbine device 2. The turbine device 2 shown in FIG. 2 has a turbine casing 3, a rotor 4, and a plurality of moving blades 5 forming stage group I and stage group II. Sensors 10a to 10f are disposed in this turbine casing 3. In the example shown in FIG. 2, the sensors 10a to 10f are temperature sensors that detect temperature.

[0028] Sensor 10a is disposed in the vicinity of the downstream of the first-stage moving blade 5 from the steam inlet 11 in the turbine casing 3. Sensor 10b is disposed in the vicinity of the steam outlet 12 of the stage group I in the turbine casing 3. Sensor 10c is disposed in the vicinity of the steam passage after the steam outlet 12 in the turbine casing 3. Sensor 10d is disposed in the vicinity of the steam inlet 13 of the stage group II in the turbine casing 3. Sensor 10e is disposed in the vicinity of the stage group II in the turbine casing 3. Sensor 10f is disposed in the vicinity of the steam outlet 14 of the stage group II in the turbine casing 3.

[0029] In the turbine casing 3 shown in FIG. 2, when estimating the temperature of each stage of the stage group I, the detection results of the sensor 10a near the steam inlet 11 and the sensor 10b near the steam outlet 12 can be used. Instead of the sensor 10b, the sensor 10c near the steam passage after the steam outlet 12 can also be used. However, when estimating the steam inlet temperature and the outlet temperature, the estimation error of the steam inlet and outlet temperatures can be reduced by estimating the steam temperature from the temperature measurement data at a position close to the steam inlet and outlet. In the above example, it is easier to estimate the steam outlet temperature by using the sensor 10b than the sensor 10c. When estimating the temperature of each stage from the steam inlet and outlet temperatures, the estimation accuracy of each stage temperature is affected by the estimation error of the steam inlet and outlet side temperatures. Therefore, an improvement in the estimation accuracy can be expected by appropriately selecting sensors.

[0030] Although the sensor 10a is disposed in the vicinity of the downstream of the first-stage moving blade 5 from the steam inlet 11 in the turbine casing 3, it is not limited thereto. The mounting position of each sensor varies depending on the design conditions and is not limited to the downstream of the first-stage moving blade 5, and may be other positions. For example, due to the design of the turbine casing 3, when it is difficult to measure the temperature at the position of the sensor 10b, it may be estimated using the temperature of the steam passage portion after the steam outlet 12 that can be detected by the sensor 10c. Similar to the sensor 10a, sensors may be installed between the stages.

[0031] The number of sensors 10 for extracting operation data is not limited to two locations near the steam inlet and the steam outlet, as it is determined according to the number of parts, positions, and estimation formulas for evaluating the state variables. For example, in the case of estimating the temperature near the trailing flow of the first-stage moving blade 5 from the steam inlet 11 in Paragraph Group I, it may be sufficient to use only the data of the sensor 10a close to the evaluation part. Also, for the data extracted to estimate the state variables of each paragraph in Paragraph Group II, the temperature of each part may be detected using two of the sensors 10d, 10e, or 10f, or three of the sensors 10d, 10e, and 10f. Additionally, a plurality of sensors 10 may be prepared as data extraction targets, and the sensors for data collection may be selected according to the collected data such as steam pressure and operation output, or the estimated data such as the state estimation quantity at an arbitrary time. The same applies to pressure and strain sensors, and the arrangement of the sensors can be determined according to the location and content of the operation data to be detected.

[0032] For the temperature estimation of each paragraph, a method of using the measured values of the temperature sensors near or before and after the paragraph to be estimated has been described, but the measured values of the pressure sensors may also be used in combination with the measured values of the temperature sensors. For example, in the calculation of heat transfer, there is a method of using and calculating the kinematic viscosity coefficient, Reynolds number, Nusselt number, Prandtl number, etc. The steam pressure is also required as a parameter for calculating these values. In that case, a pressure sensor is provided as the sensor 10, and the values of these parameters are calculated based on its measured value and combined with the measured value of the temperature sensor. Thereby, the temperature of the paragraph to be estimated can be calculated.

[0033] (Operation data acquisition unit 20) The operation data acquisition unit 20 has a function of acquiring the operation data measured by the sensor 10 provided in the turbine equipment 2 during operation at an appropriate sampling frequency, performing averaging and noise removal, and outputting the data to a subsequent process. Further, the operation data acquisition unit 20 can select the sensors 10 arranged at various locations of the turbine equipment 2 according to the content of the operation data to be acquired, and acquire the desired operation data from the sensors 10. That is, when acquiring a certain operation data, it is possible to set which sensor to acquire what data (such as temperature and pressure) from.

[0034] Figure 3 shows the operation data acquisition operation by the operation data acquisition unit 20. The operation data acquisition unit 20 reads detection data such as temperature and pressure, and operation data such as plant output and load ratio from the sensor 10 provided in the turbine equipment 2 (S21).

[0035] When the operation data is read, the operation data acquisition unit 20 performs data processing such as noise removal processing (S22) and averaging processing (S23) to perform data arrangement.

[0036] When the operation data is arranged, the operation data acquisition unit 20 reads the history data from the operation data storage unit 40 (S24). Examples of the history data include operation data obtained from moment to moment, integrated histories such as total operation time, change amounts of temperature, pressure, etc. of each part during startup, stop, or output fluctuation, and change amounts per unit time. That is, the operation data acquisition unit 20 acquires not only the operation data acquired through the sensor 10 but also the past history of the operation data. The history data may further include transient data indicating the state of the plant at the evaluation time, data obtained by integrating these transient data, change amounts of temperature, pressure, etc. of each part of the turbine equipment 2, and data obtained by adding and subtracting data at a plurality of arbitrary times. The operation data acquisition unit 20 acquires the history data from the operation data storage unit 40.

[0037] In addition, the operation data acquisition unit 20 integrates and calculates transient data (operation data) from the operation data storage unit 40 to generate history data (S25). The generated history data is stored in the operation data storage unit 40 (S26). Note that the history data generated by the operation data acquisition unit 20 is not limited to that based on the operation data acquired through the sensor 10. In the case of an existing plant that has been in operation continuously for a certain period, the operation data acquisition unit 20 may acquire and integrate the operation history from the start of operation to the installation of the device and store it in the operation data storage unit 40. Also, the operation data may be input through the input unit 35 and stored in the operation data storage unit 40.

[0038] (Temperature evaluation unit 50) The temperature evaluation unit 50 calculates the temperature of a predetermined evaluation site using the operation data and history data acquired and generated by the operation data acquisition unit 20. As calculation methods by the temperature evaluation unit 50, for example, (1) for the temperature at an arbitrary evaluation site, the operating fluid temperature is estimated based on temperature data at the inlet and outlet of the operating fluid such as steam, like the turbine casing 3 illustrated in FIG. 2, and operating conditions such as the output of the device, and the heat balance is obtained by a balance calculation method; (2) a relational expression between the measurement data of various sensors attached to a predetermined position of the evaluation target device in advance and the evaluation site temperature is created and obtained thereby, etc. are exemplified. Here, relational expressions between operating conditions such as device output and the temperature of each part can be stored in the operation data storage unit 40 in advance.

[0039] Note that depending on the plant configuration where the material degradation evaluation device 1 is installed, the device to be evaluated, and the number of evaluation sites, it may be difficult to perform all calculation processes on the operation data sequentially sent. In such a case, for example, for the operation data assumed in advance, state quantities such as the temperature and pressure of the evaluation site are stored in the operation data storage unit 40 in advance, and instead of the operation data acquired by the sensor 10, the state quantities stored in the operation data storage unit 40 may be used to output the temperature at a predetermined evaluation site.

[0040] (Brittleness evaluation unit 60) The embrittlement evaluation unit 60 estimates the amount of embrittlement at an arbitrary evaluation site of the device under evaluation based on the temperature at a predetermined evaluation site calculated by the temperature evaluation unit 50 and the material data of the evaluation component stored in the evaluation component material storage unit 30 in advance. Examples of the material data include strength data such as the chemical composition, crystal grain size, hardness, yield strength, and impact value of the material forming the member under evaluation. Also, the amount of embrittlement sequentially calculated by the embrittlement evaluation unit 60 is stored in the evaluation component material storage unit 30, and this amount of embrittlement is also included in the material data.

[0041] The amount of embrittlement is expressed, for example, by the fracture appearance transition temperature (FATT).

[0042] The fracture appearance transition temperature indicates the temperature at which the ductile fracture ratio, which indicates the ratio of ductile fracture surface to brittle fracture surface, corresponds to 50% on the fracture surface obtained by the impact test. Metal materials tend to have reduced ductility and become brittle with decreasing temperature. When the material becomes embrittled, it will not show a ductile fracture ratio of 50% unless the temperature is higher. That is, the fracture appearance transition temperature FATT increases with embrittlement. The amount of embrittlement may be indicated using the FATT (FATT0) at the time of manufacturing the material of the evaluation site and the increase amount ΔFATT of the FATT (FATT t ) at the current time. t It may also be shown using.

[0043] Figure 4 shows an example of the evaluation operation by the embrittlement evaluation unit 60. The embrittlement evaluation unit 60 calculates the amount of embrittlement after the elapse of a unit time. Here, the unit time refers to an arbitrary time period within the time when the input evaluation site temperature can be regarded as constant. The unit time may be set in advance, or the change in the operation state quantity and the change amount of the evaluation site temperature, which is the input of the calculation, may be monitored and sequentially determined. The embrittlement evaluation unit 60 acquires the material data of the evaluation component stored in the evaluation component material storage unit 30 (S61), and then acquires the evaluation site temperature calculated by the temperature evaluation unit 50 (S62).

[0044] Using the acquired material data, the evaluation site temperature calculated by the temperature evaluation unit 50, and the embrittlement estimation formula described later, the equivalent time t in the current state quantitye Calculate it (S63). The equivalent time t e refers to the time required to reach the current embrittlement amount when maintaining a constant temperature at the current temperature.

[0045] After the elapse of a unit time Δt during which the temperature can be regarded as constant, the apparent constant-temperature holding time t is calculated from the following formula (1), and based on the embrittlement estimation formula, material data, the evaluation site temperature, and the apparent holding time t, the embrittlement amount after the elapse of the unit time is calculated (S64). t = t e + Δt ···(1)

[0046] Next, the embrittlement evaluation unit 60 stores the calculated embrittlement amount in the evaluation component material storage unit 30 (S65).

[0047] The embrittlement evaluation unit 60 can calculate the embrittlement amount using the following embrittlement estimation formula assuming that, for example, the embrittlement amount is proportional to the grain boundary segregation amount of impurity elements. (Embrittlement amount ΔFATT t ) / (Saturated embrittlement amount ΔFATT ∞ ) = (1 - exp(X 2 ) × erfc(X)) ···(2) Here, X is a function of a constant Y calculated from the constant-temperature holding temperature T [°C], the holding time t [Hr], and the amount of a predetermined element in the material. X = f(t, T, Y) ···(3) By using the above formulas (2) and (3), if the saturated embrittlement amount ΔFATT ∞ in the same state quantity is determined, the embrittlement amount ΔFATT t at a certain time can be obtained.

[0048] One feature of the embrittlement estimation method shown in this embodiment lies in the form of the formula representing the saturated embrittlement amount, and an exponential function with the reciprocal of a linear function of temperature as the exponent is used as shown in the following formula (4). (Saturated embrittlement amount ΔFATT ∞ ) = A1 × B × exp{A2 / (T + 273)} ···(4) Here, A1 and A2 are experimentally determined constants, and B is a constant calculated from material data. The denominator of the exponent is shown as (T + 273), but it may also be T + 273.15 or the absolute temperature (K) if it is a linear function of temperature.

[0049] The details of the features of this embodiment will be described below in comparison with known examples. In the known example, the saturated embrittlement amount of CrMoV steel is estimated by the following formula (5), and the embrittlement amount is estimated in combination with the above formulas (2) and (3). (Saturated embrittlement amount ΔFATT ∞ ) = 425.0 + 1.778×K - 0.9643×T - 0.001990×K×T ··· (5) Here, K is a constant calculated from a predetermined element amount in the material, and T is the holding temperature.

[0050] Formula (5) approximates the saturated embrittlement amount by a linear function of temperature based on embrittlement measurement data in the temperature range of 300 to 450°C and is derived. In the estimation of the embrittlement amount using the above formula (5), the estimation accuracy in the above temperature range has been verified, but the estimation accuracy in a higher temperature range was unknown. Therefore, the estimation accuracy of formula (5) was verified using the embrittlement measurement data of CrMoV steel after holding for 90,000 to 140,000 hours at 470 to 520°C.

[0051] The graph in Fig. 5 shows a comparison between the embrittlement estimation method in this embodiment and the known example. The figure shows these relationships with the holding temperature (°C) on the horizontal axis and the saturated embrittlement amount (°C) on the vertical axis. The plots in the figure are the embrittlement measurement data in the range of 470 to 520°C and the saturated embrittlement amount calculated from formula (4), and the broken line shows the estimated result of the saturated embrittlement amount by the known example formula (5).

[0052] The estimated value of the saturation embrittlement amount according to the known example becomes zero at a holding temperature of about 460°C, and the result is that embrittlement does not occur in temperature ranges higher than that. However, embrittlement has been confirmed in CrMoV steel after holding at 470 - 520°C, which is inconsistent with the estimated result. From this result, in the estimation according to the known example, although there is an influence of the constant K calculated from the amount of a predetermined element in the material, it is considered that the applicable limit is up to a holding temperature of about 460°C, and it is difficult to apply it to the embrittlement estimation including temperature ranges of 450°C and above.

[0053] On the other hand, the solid line in the figure shows the estimated saturation embrittlement amount calculated by equation (4). In the temperature range of 450°C and above, formally in terms of the equation, the estimated value of the saturation embrittlement amount does not become zero, and there is no clear upper limit temperature for application. Also, the saturation embrittlement amount near a holding temperature of 500°C can be estimated with an error of about 10°C.

[0054] Figure 6 shows the estimated results of the embrittlement amount at 280 - 450°C using equations (4) and (2). The plots in the figure are the measured values of embrittlement, and the solid line and the dashed line are the estimated results. The measured values A and B are the embrittlement measurement results of test pieces taken from the same CrMoV steel respectively. The estimated values and the measured values generally agree, and the embrittlement estimation using equation (4) is also applicable at 280 - 450°C.

[0055] Figure 7 shows the results of verifying the embrittlement estimation accuracy using equations (4) and (2). Also, for comparison, the accuracy verification results according to the known example are shown together. The embrittlement measurement data used for the accuracy verification are the CrMoV steel embrittlement measurement data after holding for 3 - 280,000 hours in the temperature range of 280 - 536°C. The number of data points is about 200, and about 70% of them are the embrittlement measurement data held at 450°C and above.

[0056] The upper part of the figure shows the prediction accuracy by the known estimation method, and an estimation error can be recognized where the measured value is about twice as large as the estimated value for some data. On the other hand, the result of the embrittlement estimation using equation (4) is shown in the lower part of the figure. It can be confirmed that the estimated value and the measured value generally agree.

[0057] From these results, as shown in Equation (4), by estimating the saturation embrittlement amount with an exponential function of the reciprocal of temperature, it is possible to more appropriately predict the embrittlement amount in a wider temperature range compared to known examples, and the problem of establishing an embrittlement estimation method applicable up to a temperature range exceeding 500 °C has been solved by using this equation.

[0058] B in Equation (4) is a value calculated from the material data of the evaluation member. As an example of this determination method, there is a method of weighting and adding the mass weights of arbitrary impurity elements from the chemical composition of the evaluation member. B = α·D + β·E + γ·F + δ·G ···(6) Here, D, E, F, and G are the amounts of arbitrary impurity elements in wt%, and α, β, γ, and δ are the weighting coefficients.

[0059] Although Equation (6) is an example calculated from the amounts of four types of impurity elements, the elements used for calculating the constant B are not limited to four types. Since the types of elements to be used are determined by the material to be targeted, the number of terms in the above equation will increase or decrease accordingly. In the case of heat-resistant steel, out of the eight elements P, Si, Mn, Cu, Ni, Sn, Sb, and As as impurity elements, the elements to be used for calculating the coefficients are selected according to the material and calculated. Also, it may be calculated by multiplying the amounts of arbitrary impurity elements.

[0060] Note that depending on the evaluation target device and the number of evaluation parts of the material deterioration evaluation device 1, it may be difficult to process all the temperature data sequentially sent. In such a case, the embrittlement rate may be calculated in advance from the material data, the use temperature, and the embrittlement amount at the current time using the above embrittlement estimation formula, and the embrittlement amount per unit time may be calculated using this and integrated to output the embrittlement amount at a predetermined evaluation part. Or, a part of the calculation process, for example, the relationship between the right side of Equation (2) and the variable X, etc., may be calculated in advance and used to measure the embrittlement amount. In any case, using the saturation embrittlement amount estimation formula including an exponential function with the reciprocal of a linear function of temperature as shown in Equation (4) is one of the features of the embrittlement prediction method in this embodiment.

[0061] In addition, depending on the member to be evaluated, there may be no measurement record of a part of the amount of impurity elements used for calculating the constant B, and the amount of elements required for constant calculation may not be complete. In such a case, the amount of impurity elements may be assumed. For example, there is a method of using the average value of the amounts of impurity elements of a plurality of the same kind of metal members. In addition to this, statistical values such as standard deviation may also be used to calculate estimated values. Such statistical values may be selected based on conditions such as the manufacturing location, manufacturer, and manufacturing year, and the calculated values may be used.

[0062] The embrittlement estimation formula, the standard error in the embrittlement estimation formula, the embrittlement rate for each state quantity, and the statistical values of the amount of impurity elements, etc. can be stored in the evaluation component material storage unit 30 in advance. The constants A1 and A2 in formula (4), the embrittlement standard error, and the statistical values of the amounts of various impurity elements are all values calculated from experimental data. When the number of experimental data used for calculation is small, the reliability of the above coefficients and statistical values is also low, and the estimated value of the embrittlement amount using these is of low reliability. Even during the operation of the material deterioration evaluation apparatus 1, embrittlement evaluations involving direct measurements at the part to be evaluated, other parts, and other products are carried out, and these measurement results and experimental data are accumulated in a database outside the material deterioration evaluation apparatus 1. By using the measurement data stored in this database, the embrittlement measurement data obtained daily and the conventional embrittlement measurement data can be combined to recalculate the statistical values such as the above coefficients and standard errors.

[0063] Also, in the statistical values of the amounts of various impurity elements, the statistical values can be recalculated in the same way by collecting the measurement results of the amounts of elements in other members. By making the various coefficients and statistical values stored in the evaluation component material storage unit 30 updatable based on these calculation results, the reliability of the embrittlement evaluation by the material deterioration evaluation apparatus 1 can be improved. To achieve this, the input unit 35 is provided with a terminal for data communication to make the data in the evaluation component material storage unit 30 updatable. The material deterioration evaluation apparatus 1 may be made online via a LAN or the like and automatically update the data in the evaluation component material storage unit 30 periodically or at an arbitrary time, or may be updated using various media or the like.

[0064] Further, when the above coefficients and statistics are updated, the amount of embrittlement at the current time of the evaluation target part may be re-evaluated based on the history data stored in the driving data storage unit.

[0065] The embrittlement evaluation unit 60 also has a function of calculating the constant B (constant calculated from material data) in the formula (4) by back-calculation from the embrittlement measurement result by direct measurement and the driving data. As a specific example of implementation, consider the case where the material deterioration evaluation apparatus 1 is applied to a product after being operated for a certain period. When determining the constant B from the material data as in the formula (6), the elemental amount of the evaluation target part is required. When there is no material data at the time of product manufacture, it is possible to cut out a part of the product and analyze it from the cut-out material, but in many cases, it is not allowed to cut out the product during operation. In that case, the constant B is back-calculated using the above formulas (1) to (4) by inputting the driving history data from the start of operation to the current time and the embrittlement measurement result at the current time. Also, when there is no history data from the start of operation, it may be back-calculated based on the embrittlement measurement results at arbitrary times t1 and t2 and the driving history data from t1 to t2. Further, in the above example, the minimum number of embrittlement measurements required for back-calculating the constant B is shown, but a plurality of embrittlement measurement results may be combined and the constant B may be approximated from these. The calculated constant B is stored in the evaluation component material storage unit 30.

[0066] (Risk evaluation unit 70) The risk evaluation unit 70 evaluates the damage risk of the evaluation member based on the amount of embrittlement evaluated by the embrittlement evaluation unit 60 and statistics such as the standard error and standard deviation of the embrittlement estimation formula stored in the evaluation component material storage unit 30. FIG. 8 shows an example of damage risk evaluation. The standard error of embrittlement estimation according to the formulas (2) to (4) is combined with the amount of embrittlement evaluated by the embrittlement evaluation unit 60 to calculate an estimated value considering the confidence interval. The risk is evaluated from this value and the threshold value of the amount of embrittlement. The statistics such as the standard error and standard deviation are rewritable.

[0067] The threshold values A, B, and a in the figure may be values determined in advance from design conditions or the like, or may vary depending on the operating time of the device to be evaluated and the temperature of the evaluation site. The number of these threshold values is not limited to this. Parameters such as the operating time and the use temperature may be added. Also, any of the threshold values can be stored in the evaluation component material storage unit 30 and updated based on information obtained from devices outside the material deterioration evaluation device 1 and the like.

[0068] (Maintenance recommendation timing presentation unit 80) Based on the damage risk at the current time generated by the risk evaluation unit 70 and the future damage risk based on the operation plan, the maintenance recommendation timing presentation unit 80 presents the inspection recommendation timing such as direct measurement of embrittlement or the maintenance recommendation timing such as the component replacement timing. The maintenance recommendation timing presentation unit 80 has a display device such as a display device and can present the proposed content to the user. It has a function of evaluating the future damage risk based on the operation plan of the device to be evaluated separately input by the user via the input unit 35. Here, the operation plan is information indicating, for example, the equipment operation rate, the average output of the device, the frequency of start-stop times, etc., and is stored in advance in the operation data storage unit 40. The maintenance recommendation timing presentation unit 80 calculates the estimated embrittlement amount predicted for the given operation plan based on the obtained embrittlement amount, the operation data associated therewith, and the history data.

[0069] The above is the first embodiment. According to the first embodiment, by estimating the embrittlement amount of the evaluation member from the operation data, the number of embrittlement measurements involving the stop and release of the device to be evaluated can be reduced. Also, by sequentially calculating the evaluation site temperature from the operation data and performing embrittlement evaluation using this, it is possible to cope with changes in the use temperature due to load fluctuations of the generator equipment and the like. Furthermore, in the data storage unit that stores various statistical quantities used for embrittlement evaluation and experimentally calculated constants included in the embrittlement prediction formula, by making the data updatable based on data obtained from outside the embrittlement estimation device, the newly acquired embrittlement measurement data can be used for future embrittlement evaluation.

[0070] (Configuration of the second embodiment) The second embodiment comprises a module including an evaluation unit and a storage unit that constitute the material deterioration evaluation apparatus 1 shown as the first embodiment, and a embrittlement evaluation module including an embrittlement evaluation unit. A material deterioration evaluation apparatus configured by combining the two modules and the embrittlement evaluation module is illustrated in FIG. 9.

[0071] The embrittlement evaluation module 6 including the embrittlement evaluation unit 60 has an input unit 35, an evaluation component material storage unit 30, an embrittlement evaluation unit 60, a risk evaluation unit 70, and a maintenance recommendation timing presentation unit 80. Modules 7 and 8 used in combination therewith each have a sensor 10, an operation data acquisition unit 20, an input unit 35, an operation data storage unit 40, and a temperature evaluation unit 50.

[0072] In modules 7 and 8, from operation data acquisition to creation of history data and calculation of the temperature of the evaluation site are performed. Similar to the first embodiment, in the operation data acquisition unit 20, operation data is collected from the sensor 10 and stored in the operation data storage unit 40. In the temperature evaluation unit 50, the temperature of the evaluation site is calculated using the operation data or the history data and stored in the operation data storage unit 40.

[0073] The embrittlement evaluation module 6 performs from embrittlement evaluation to recommendation of the maintenance timing. The embrittlement evaluation module 6 collects the temperature of the evaluation site and the operation history data evaluated in modules 7 and 8. Based on these data, similar to the first embodiment, embrittlement evaluation is performed by the embrittlement evaluation unit 60 and stored in the evaluation component material storage unit 30. Also, risk evaluation is performed by the risk evaluation unit 70, and the maintenance recommendation timing is presented by the maintenance recommendation timing presentation unit 80 based on the embrittlement evaluation result, the risk evaluation result, the operation plan, etc. The maintenance recommendation timing presented by the maintenance recommendation timing presentation unit 80 may be determined by individually evaluating the damage risk of the evaluation site of each module, or may be determined considering the mutual state such as aligning or shifting the maintenance recommendation timing in consideration of the evaluation results of each device, the operation rate of the device to be evaluated, and the maintainability.

[0074] The embrittlement evaluation module 6, and modules 7 and 8 are connected by wired or wireless means capable of data communication. Or data may be exchanged using various media such as memory cards. Various terminals required for data communication are included in the input section 35. The connection to the accessory device and data communication may be at all times or after any elapsed time. The time may be determined in advance or determined based on operation data.

[0075] In the above example, the sensor 10, the operation data acquisition unit 20, the input section 35, the operation data storage unit 40, and the temperature evaluation unit 50 are included in modules 7 and 8, but the device configuration is not limited to this. The configuration can be changed, such as including the temperature evaluation unit 50 in the embrittlement evaluation module 6. Also, depending on the device configuration, the above operation data storage unit 40 or the evaluation component material storage unit 30 may be divided into a plurality, and the embrittlement evaluation module 6 and both of modules 7 to 8 may have data storage units.

[0076] For example, in the operation data storage unit 40, in addition to the operation data acquired by the operation data acquisition unit 20 and the temperature data calculated by the temperature evaluation unit 50 based on the operation data, the evaluation formula used by the temperature evaluation unit 50 is also stored. That is, when the temperature evaluation unit 50 is included in the embrittlement evaluation module 6, the operation data storage unit 40 is also provided in the embrittlement evaluation module 6 and modules 7 to 8. The operation data storage unit 40 included in modules 7 to 8 stores the operation data acquired by the operation data acquisition unit 20, and the operation data storage unit 40 provided in the embrittlement evaluation module 6 stores the temperature data calculated by the temperature evaluation unit 50 and the evaluation formula used for the calculation. Although an example of connecting two modules to the embrittlement evaluation module 6 is shown, the number of modules connectable to the embrittlement evaluation module is not limited to two and may be increased further. Also, one may be sufficient.

[0077] The various sensors, each evaluation unit, and the data storage unit included in the modules of the material degradation evaluation device may be shared with other material degradation evaluation devices such as the aforementioned damage evaluation device, and the sensors, evaluation units, and data storage units that make up the damage evaluation device. Fig. 10 shows an example of sharing the modules that make up the material degradation evaluation device. In Fig. 10, 9 is the aforementioned damage evaluation device, which evaluates the temperature and generated stress of the evaluation site based on the operation data of the device to be evaluated, and evaluates fatigue damage, creep damage, or crack propagation damage caused by these. The damage evaluation device 9 includes a sensor 10, an operation data acquisition unit 20, an evaluation component material storage unit 30, an input unit 35, an operation data storage unit 40, a temperature evaluation unit 50, a stress evaluation unit 90, a risk evaluation unit 70a, and a maintenance recommendation timing presentation unit 80a.

[0078] Similar to the first embodiment, the operation data acquisition unit 20 samples temperature, pressure, strain, device output, etc. as operation data from the sensor 10 provided on the member constituting the device to be evaluated, and stores it in the operation data storage unit 40.

[0079] The temperature evaluation unit 50 calculates the evaluation site temperature using the operation data stored in the operation data storage unit 40. For calculating the evaluation site temperature, a relational expression between the device output or the measured value of an arbitrary sensor 10 and the evaluation site temperature is stored in the operation data storage unit 40 in advance, and this is used to calculate the evaluation site temperature. The calculated temperature data is stored in the operation data storage unit 40 in association with the operation data.

[0080] The stress evaluation unit 90 calculates the stress generated at the evaluation site using the operation data stored in the operation data storage unit 40. For stress calculation, a relational expression between the device output or the measured value of an arbitrary sensor 10 and the generated stress is stored in the operation data storage unit 40 in advance, and this is used to calculate the stress generated at the evaluation site. The calculated stress is stored in the operation data storage unit 40 in association with the operation data.

[0081] In the risk assessment unit 70a, the fatigue damage and creep damage amounts are calculated from the driving data stored in the driving data storage unit 40, the temperature, stress evaluation results associated therewith, and material data such as the fatigue strength characteristics and creep characteristics of the evaluation part. The calculated damage amount and the damage risk are evaluated from the driving data. The calculated damage amount and the damage risk evaluation result are stored in the evaluation component material storage unit 30.

[0082] Based on the damage evaluation result stored in the evaluation component material storage unit 30, the driving data stored in the driving data storage unit 40, and the future equipment operation plan separately input, the maintenance recommendation timing presentation unit 80a predicts the future damage amount and presents the maintenance recommendation timing.

[0083] If the evaluation target parts of the material deterioration evaluation device 1a and the damage evaluation device 9 are the same, or if the temperature of any evaluation target part can be calculated by the temperature evaluation unit 50, the sensors, evaluation units, etc. constituting the device can be shared to satisfy the functions of both devices. The sensor 10, driving data acquisition unit 20, evaluation component material storage unit 30, input unit 35, driving data storage unit 40, and temperature evaluation unit 50 constituting the material deterioration evaluation device 1a are used as the module 7a, and the device can also be configured by sharing this with the damage evaluation device 9.

[0084] In the above example, the sensor 10, driving data acquisition unit 20, evaluation component material storage unit 30, input unit 35, driving data storage unit 40, and temperature evaluation unit 50 are modularized, but the configuration included in the module is not limited to this and can be changed. Also, although it is an example of sharing the module between the two devices of the damage evaluation device 9 and the material deterioration evaluation device 1a, the number of devices that can be shared is not limited to this, and the number of devices can be increased. The above is the second embodiment.

[0085] As described above, several embodiments of the present invention have been explained. However, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalent scope thereof.

Explanation of Reference Numerals

[0086] 1, 1a... Material degradation evaluation device, 2... Turbine equipment, 3... Turbine casing, 4... Rotor, 5... Moving blade, 6... Embrittlement evaluation module, 7, 7a, 8... Modules, 9... Damage evaluation device, 10... Sensor, 11... Steam inlet, 12... Steam outlet, 13... Steam inlet, 14... Steam outlet, 20... Operating data acquisition unit, 30... Evaluation component material storage unit, 40... Operating data storage unit, 50... Temperature evaluation unit, 60... Embrittlement evaluation unit, 70, 70a... Risk evaluation units, 80, 80a... Maintenance recommendation timing presentation units.

Claims

1. A material degradation evaluation device for evaluating the embrittlement of a device actuated by a working fluid, comprising: an operating data acquisition unit that detects the state of the device and acquires it as operating data; an operating data storage unit that stores the operating data; a temperature evaluation unit that calculates an evaluation site temperature at a predetermined evaluation site of the device based on the operating data; an evaluation component material storage unit that stores material data and an embrittlement estimation formula for the material forming the device; an embrittlement evaluation unit that calculates an embrittlement amount of the material forming the device based on the evaluation site temperature, the material data, and the embrittlement estimation formula; a risk evaluation unit that calculates a damage risk of the material forming the device based on the embrittlement amount; a maintenance recommendation timing presentation unit that presents a recommended maintenance timing of the device based on the damage risk; wherein the temperature evaluation unit (1) estimates the working fluid temperature at the evaluation site based on the temperature data of the working fluid at the sensor measurement position, and calculates the evaluation site temperature by the temperature obtained by calculating the heat balance of an arbitrary site including the evaluation site by income and expenditure calculation, or (2) calculates the evaluation site temperature by the temperature obtained by creating a relational expression between the measurement data of a sensor attached to a predetermined position of the device in advance and the evaluation site temperature, the embrittlement estimation formula used by the embrittlement evaluation unit obtains the embrittlement amount as a function of the saturated embrittlement amount and time, the saturated embrittlement amount of the evaluation site used for the evaluation of the embrittlement amount a constant (A1) determined experimentally in advance, a constant (B) calculated from the amount of elements contained in the material forming the device, an exponential function having an exponent that is the product of the reciprocal of a linear function of temperature and a constant (A2) determined experimentally in advance, is calculated by multiplying them together, the saturated embrittlement amount of the evaluation site used for the evaluation of the embrittlement amount is given by the following formula: Saturated embrittlement amount = A1 × B × exp{A2 / (K)} where A1 and A2 are constants determined experimentally in advance, B is a constant calculated from the amount of elements contained in the material forming the device, and K is the absolute temperature. A material degradation evaluation device characterized by obtaining it in this way.

2. The material degradation evaluation device according to Claim 1, composed of a plurality of modules including any one or a plurality of the operating data acquisition unit, the operating data storage unit, the temperature evaluation unit, the evaluation component material storage unit, the embrittlement evaluation unit, the risk evaluation unit, and the maintenance recommendation timing presentation unit, wherein the plurality of modules are capable of data communication between the modules. A material deterioration evaluation device characterized by the following.

3. The material deterioration evaluation device according to claim 1 or 2, wherein the risk evaluation unit calculates the damage risk using a statistic regarding the error of the embrittlement estimation formula stored in the evaluation component material storage unit. A material deterioration evaluation device characterized by the following.

4. The material deterioration evaluation device according to claim 3, wherein a statistic regarding the error of the embrittlement estimation formula stored in the evaluation component material storage unit is made rewritable. A material deterioration evaluation device characterized by the following.

5. The material deterioration evaluation device according to claim 1, wherein the exponential function is an exponential function with the base of the natural logarithm. A material deterioration evaluation device characterized by the following.

6. The material deterioration evaluation device according to any one of claims 1 to 5, wherein a constant (B) calculated from the amount of elements contained in the material forming the device, is calculated from the amount of one or more of the eight elements of P, Si, Mn, Cu, Ni, Sn, Sb, and As. A material deterioration evaluation device characterized by the following.

7. The material deterioration evaluation device according to claim 6, wherein the amount of embrittlement per unit time is calculated in advance, and the amount of embrittlement is calculated by integrating the amount of embrittlement per unit time based on the time during which the temperature of the evaluation site can be regarded as constant. A material deterioration evaluation device characterized by the following.

8. The material deterioration evaluation device according to claim 7, wherein the constant determined experimentally in advance and the amount of embrittlement per unit time are stored in the evaluation component material storage unit and made rewritable. A material deterioration evaluation device characterized by the following.

9. The material deterioration evaluation device according to claim 7 or 8, wherein, using the amount of embrittlement of the material forming the device at a certain time and the operation data stored in the operation data storage unit, a constant (B) calculated from the amount of elements contained in the material forming the device is inversely calculated, and the evaluation of the amount of embrittlement is performed using the inversely calculated constant. A material deterioration evaluation device characterized by the following.

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