JPS61140838A - Method for diagnosing structural member - Google Patents

Abstract

PURPOSE:To judge exactly the remaining life of a structural member by calculating the presence and propagation quantity of a crack as wall as the coefft. of stress expansion of the crack from the various use condition quantity and inspection data of the structural member and determining rupture probability from the breaking toughness value of the structural member. CONSTITUTION:A device 1 for detecting the using condition is connected to the structural member and the various use condition quantity such as temp. is measured at all times and is preliminarily stored into a storage device 2 for operating history. On the other hand, the inspection data 3 by various non-destructive inspection obtd. in the stage of inspecting the structural member is inputted from an input part to an arithmetic unit 4 for material characteristics, by which the initial crack size and the deterioration condition quantity of the member are stored. The crack depth is determined as a probability density distribution from both stored data by an arithmetic unit 5 for the crack propagation quantity and further the coefft. of stress expansion for each operation time is determined as the probability density distribution by an arithmetic unit 6 for the coefft. of stress expansion. The rupture probability is determined by an arithmetic unit 7 for the rupture probability from the coefft. of stress expansion and the deterioration condition quantity and the time until the probability exceeds the prescribed value is determined as the remaining life.

Description

DETAILED DESCRIPTION OF THE INVENTION (Field of Industrial Application) The present invention relates to a diagnostic method for accurately determining the remaining life of a structural member of a machine used, for example, in high-temperature steam and determining an optimal inspection period.

[Conventional technology]

Traditionally, in order to diagnose the lifespan of structural members, monthly eigenvalues such as tensile strength, fatigue strength, creep roughness, fracture toughness, and other fracture strengths, as well as stress, vibration stress, stress intensity factor, and other predicted load loads have been used. The conditions for failure were determined based on the size relationship. However, since there are variations in these values, the minimum value of fracture strength and the maximum value of load
The remaining life is determined as the period until the current state11, for example, crack depth, creep damage amount, fatigue damage amount, etc. reaches the limit value. There is.

Furthermore, when calculating the remaining life, the maximum value of the dispersion is used for the crack growth rate, etc.

[Problem that the invention seeks to solve]

As mentioned above, conventionally, 4. The remaining life, etc. is diagnosed by comparing the various fracture strengths of J II and the expected load lifting, but the minimum and maximum values are used for each of these values, and no consideration is given to the distribution form of the various values. Since this is not taken into consideration, there are the following inconveniences.

That is, Fig. 1 is a graph showing the relationship between the fracture strength and fracture probability density of two types of materials, and the lowest values of fracture strength are equal at δ for two types of materials A and B, but material A
is δ. There are many parts of the fracture strength near , and the fracture strength of material B is higher overall.

However, according to conventional diagnostic methods, material A.

For material A, which has the same fracture strength and has a high risk of fracture, it is possible to determine only the same remaining life as material B.

Furthermore, in the past, there was no relationship between the inspection period and the remaining life of structural members, and the inspection period was simply set as an appropriate period, which was not considered reasonable. It's hard to say.

[Means for solving problems]

In order to solve the above-mentioned problems, the present invention determines the current presence of cracks or the amount of crack growth from various usage state quantities and inspection data of structural members using a probability density distribution, and calculates the amount based on this probability density distribution. Similarly, the stress intensity factor of a crack is determined as a probability density distribution, the probability of fracture is determined from this stress intensity factor and the fracture toughness value as the characteristic property of the structural member, and the remaining life is calculated from this probability of fracture. The period during which the total cost calculated using the following as one criterion was set as the optimum inspection period, and these periods were displayed on a display device.

〔Example〕

Embodiments of the present invention will be described below with reference to the accompanying drawings.

FIG. 2 is a block diagram that comprehensively explains the method of the present invention, and the order of diagnosis is as follows: First, a usage condition detection device 1 is connected to the structural member, and this detection device 1 detects the condition of the structural member. The various usage state quantities are constantly measured and the measured values are stored in the driving history storage device 2. On the other hand, inspection data 3 from various non-destructive inspections of structural member inspections is inputted from the input section to the material property calculating device 4, and the initial crack size and the amount of deterioration of the member are stored in the device 4.

Here, the measured values, such as the above-mentioned measurement values, crack dimensions, deterioration state quantities, etc., are stored as a normal distribution with a measurement error range set to an appropriate multiple of the standard deviation, that is, as a probability density distribution as shown in FIG. In addition, if no cracks are found during the inspection, the fourth
As shown in the figure, it is assumed that cracks with dimensions below the measurement limit exist with a uniform probability density.

The data stored in the driving history storage device 2 and the data stored in the material property calculation device 4 are sequentially input to the crack growth amount calculation device 5, and the current crack depth is determined as a probability density distribution.

On the other hand, regarding the crack depth after the current time, assuming that the past operation history will continue in the same way in the future, the crack depth for each operating time after the current time is determined as a probability density distribution.

Next, the data obtained by the crack growth amount calculating device 5 is input to the stress intensity factor calculating device 6, and based on the crack depth, the stress severity factor for each operating time is calculated as an average value (
Solid line () and probability density distribution of standard deviation (dashed line ρ, tJ
2).

Then, the stress intensity factor determined above and the deterioration state quantities such as the crack size determined by the material property calculation device 4 are input to the fracture probability calculation device 7 to determine the probability of failure.

Here, the average value of the stress intensity factor is ml, and the standard deviation of the stress intensity factor is 81. The average crack size is m2. If the standard deviation of the crack usage is S2, the broken DJ jifr rate p can be determined by the following equation.

Also, Figure 6 shows the probability density and m, m2, S1
.

S2 is a J-graph showing which relationship.

The relationship between the probability of failure and the operating time determined as follows is shown in FIG. Therefore, in the present invention,
The life of the structural member is determined when the probability of failure reaches a predetermined value D (the life expectancy of the structural member is defined as the time 1 [f) until the probability of failure exceeds the predetermined value pt.

Furthermore, in this embodiment, the following four calculations are performed in order to determine the optimum inspection timing.

That is, the data from the end member failure probability calculation device 7 is input to the total cost calculation device 8, and the total cost calculation device 8
The following calculations are performed. If the estimated cost of damage when a structural member is damaged is Cf, the operating time is t, and the cost required for inspection is C8, the total cost 1-C is C= (C-pf+co), /l・Since it is expressed by (2), the total cost is calculated based on this formula.

Here, FIG. 8 is a graph showing the relationship between operating time and total cost, and as is clear from this graph, the operating time t at which the total cost C is the minimum. exists. In other words,
If the inspection period is too short, the cost required for the inspection will increase, and if the inspection period is too long, the probability of failure will increase, resulting in an increase in the total cost. Therefore, the operating time t at which the total cost is the minimum. is determined as the optimal inspection period.

Further, both the data obtained by the failure probability calculation device 7 and the data obtained by the total cost calculation device are input to the remaining life judgment device 9, and this remaining life judgment device determines the optimum inspection period. and the operating time t for which the probability of failure exceeds a predetermined value, and 1
If <1f, set t as the optimal inspection period, 1 >1
If f, then t (is output)j as the remaining life, and if 1f is zero or close to zero, an alarm is issued.

FIG. 9 shows another embodiment of the present invention, in which a steam turbine rotor is used as a structural member to determine the remaining life. That is, the rotor temperature detector 11
a and the rotor rotation speed detector 11b as the driving history storage device 1.
2, input the initial crack size and material deterioration degree as inspection data 13 to the material property calculation device 14, and input the operation history storage device 12 and material property calculation device 14 to the crack growth amount calculation device 15 to calculate the crack growth. The quantity calculation device 15 is placed in a stress intensity factor calculation device 16, the debris characteristic calculation device 14 is placed in a fracture probability calculation device 17, and the fracture probability calculation device 17 is placed in a total cost calculation device 1.
8, the total cost calculation device 18 and the failure probability calculation device 17 are connected to a remaining life determination device 19, and the remaining life, optimum inspection period, or alarm is selectively output based on the signal from the remaining life determination device 19. .

Specifically, the rotor temperature and rotor rotational speed are stored in the operation storage device 12 as an operating fat layer, and the crack growth amount calculation device 15 calculates the thermal stress and centrifugal stress from these temperatures and rotational speed, and calculates the stress change. From the following equation, find the stress coefficient change k.

Δ = 1.12 Δδ ``41...(3) Here,
a is the crack depth, which is given from the material property calculating device 14, and the amount of crack growth Δa due to - times of stress fluctuation is determined by the following equation.

Δa−Δn1 (4) Here, c −
nl is a material property value, which is stored in the material property calculation device 14 as a probability distribution.

Next, find the amount of creep crack growth under constant stress and constant dryness. From the acting stress, the stress intensity factor (k) is determined by the following equation.

k=1.12δ ``5 voyage...(5) Here δ
is the applied stress and a is the crack depth. And the minute time Δ
The crack advance B amount Δa during time t is calculated using the following formula % Δa-A-Kn2Δt (5) Here, Δ and n2 are 411 oblique characteristic values, and monthly interest characteristic calculation device 1
4 as a probability distribution.

Therefore, from the history of temperature and rotational speed stored in the operation history storage device 12, and the cracking characteristics and initial crack depth stored in the monthly profit characteristics calculation device 14, equations (3) and (5)
) by calculating the fatigue crack growth ω and creep crack growth amount, and by integrating these, the crack depth from the start of operation after the J:T-C1 inspection to the present is calculated. In addition, the amount of crack growth after this point is calculated assuming that the same operation as the previous operation history continues. Then, the amount of crack growth with respect to the operating time is determined as a probability density distribution as shown in FIG. 10, which is similar to FIG. 5. Here, in FIG. 10, the solid line O is the average value of the crack depth, and the broken line 01°η2 is the value separated by a standard deviation from the average value.

Then, the crack growth amount I) is determined by the device 15, and the stress intensity factor is calculated from the IC crack depth and the applied stress by the stress intensity factor calculation device 16, and the distribution of the stress intensity factor with respect to the operating time is obtained in the same manner as in FIG.

In addition, the fracture toughness value KIC is shown in Figure 11. l-J: Changes depending on the sea urchin temperature, and this value is also calculated by the material property calculation device 14.
is stored in These material property values (fatigue crack propagation velocity, creep crack propagation velocity, fracture toughness) are all given as probability density distributions in consideration of the measurement results of the state of deterioration.

Then, in the fracture probability calculation device 17, the probability of fracture is determined from the distribution of 1o in the fracture toughness value determined by the material I characteristic calculation device 14 and the distribution of 1 in the expansion factor determined by the stress intensity factor calculation device 16. In other words, since the distribution of K and 1o is as shown in Figure 6 above, ■ From the average value and standard deviation of both, calculate the failure probability with respect to the operating time using equation (1) as shown in Figure 7. Calculate the remaining life tr.

Next, in the total cost calculating device 18, the change in total cost with respect to the operating time is determined by equation (1) as shown in FIG. 8, and the optimum inspection period t is determined. seek.

= 12 - t at the remaining life determination device 19. Compare 1-f, and if t o > 1: (<>, output tr as the remaining step life, and if 1: f > t, then 1: as the optimal testing period.

is output, and if tr -0, a warning is issued as a dangerous situation.

FIG. 12 is a block diagram similar to FIG. 9 showing yet another embodiment, in which the structural member is a casing of a steam turbine, and the rotor temperature detector 11a and the rotor rotational speed detector 11b are Steam temperature detector 21 instead of
a and a steam pressure detector 21b are connected to the operation history storage device 12.

Since the other configurations are the same, the same numbers are numbered. That is, in the casing, the steam temperature i and the steam pressure are detected to detect the usage state quantities, and the stress and thermal stress due to the pressure difference between the inside and outside pressures are calculated.

〔Effect of the invention〕

As explained above, according to the present invention, variations in monthly interest rate data and measured data are not simply treated as upper and lower limit values, but are evaluated probabilistically by taking into account the overall distribution form. Therefore, it is possible to perform more accurate and reasonable life evaluation than conventional methods.

In addition, since we consider the failure of a component not as a measure of whether or not it will break, but as a probability of failure, we can determine the optimal inspection period by comparing the probability of failure, the degree of risk determined from damage at the time of failure, and the inspection cost. In addition, conventional life diagnosis devices did not provide any information regarding the inspection period, but by applying the present invention, this can be clearly known.

[Brief explanation of the drawing]

FIG. 1 is a graph showing the relationship between fracture strength and fracture probability density, FIG. 2 is a block diagram showing an outline of the method of the present invention, FIG. 3 is a graph showing the relationship between measured values and probability density, and FIG. 4 is a graph showing the relationship between measured values and probability density. is a graph showing the relationship between crack size and probability density, Figure 5 is a graph showing the relationship between operating time and stress intensity factor, Figure 6 is a graph showing the relationship between stress intensity factor and fracture toughness value, and Figure 7 is a graph showing the relationship between stress intensity factor and fracture toughness value. Figure 8 is a graph showing the probability of failure versus operating time, Figure 8 is a graph showing the relationship between operating time and total cost, Figure 9 is a block diagram similar to Figure 2, and Figure 9 shows another embodiment. A graph showing the relationship between operating time and crack depth, Figure 11 is a graph showing the relationship between operating time and crack depth.
FIG. 12 is a block diagram similar to FIG. 2 showing another embodiment. 1.11a, 11b, 21a, 21b...Status 1u detector, 2,12...Driving history storage device, 3.13...
・Detection data, 4, 14... Monthly charge characteristic calculation device, 5,
15...Crack growth amount calculation device N, 6.16...Stress intensity factor calculation device, 7.17...Put to "Fracture probability calculation", 8,18...Calculation device to total cost 1, 9 .19...
Remaining life determination device. Applicant's agent Kiyoshi Inomata, 50, 50, figure 5, figure 6, I fallen @me Shikou-ku, 50

Claims (1)

[Claims] 1. The existence and extent of crack growth are determined as a probability density distribution from various usage state quantities and inspection data of the structural member, and the stress intensity factor of the crack is determined as a probability distribution from this probability density distribution.
A structural member characterized in that the probability of fracture is calculated from this stress intensity factor and the fracture toughness value as an eigenvalue of the structural member, and the remaining life is defined as the time until this probability of fracture exceeds a predetermined value. Diagnostic method. 2. Determine the presence and extent of crack growth as a probability density distribution from various usage status quantities and inspection data of the structural member, determine the stress intensity factor of the crack as a probability density distribution from this probability density distribution, and calculate the stress intensity factor and the structural member as a probability density distribution. Calculate the fracture probability from the fracture toughness value as the eigenvalue of A method for diagnosing a structural member, characterized in that a total cost is determined from the above, and a period during which this total cost is minimized is set as an optimal inspection period. 3. When the optimum inspection period is smaller than the remaining life, the optimum inspection period is output to the display device, and when the remaining life is smaller than the optimum inspection period, the remaining life is displayed and output to the device, and the remaining life is zero. 3. The method for diagnosing a structural member according to claim 2, further comprising: issuing an alarm when the temperature approaches .