JP2005134115A - Diagnostic method and risk evaluation method for tendency of low-cycle fatigue damage of equipement - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a diagnostic method for tendency of "low"-cycle fatigue damage resulted from thermal stress at the time of starting/stopping equipment such as a device constituting a boiler, and an evaluation method based on risk of the "low"-cycle fatigue damage. <P>SOLUTION: The tendency index (breakage probability) of damage is calculated on the basis of the temperature T of the equipment, a starting/stopping frequency N, an equipment-specific breakage factor F determined depending on the presence/absence of a stress collection part or a welding part, a Young's modulus E, and a fatigue life determined by the material of the equipment, whereby the tendency of the "low"-cycle fatigue damage due to thermal stress at the time of starting/stopping the equipment can be diagnosed. A RBM (risk-based maintenance) method for evaluating the risk of the equipment while taking the resulting tendency of low-cycle fatigue damage as the vertical axis and the degree of influence as the horizontal axis is executed, and the result is served for the preservative maintenance of the equipment. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a low-cycle fatigue damage diagnosis method and a risk evaluation method for equipment, and particularly increases the risk (risk) of alkali stress corrosion cracking (SCC) and alkali corrosion damage that can occur in an evaporator tube of a boiler. The present invention relates to a method for accurately evaluating and diagnosing.

  A risk-based maintenance (RBM) assessment method for equipment damage is introduced in the American Petroleum Institute (API) API 581: Risk-Based Inspection Base Resource Document, May 2000.

  In large facilities such as petrochemical plants and thermal power plants, in recent years, maintenance plans that take risks into account from the viewpoint of deregulation, that is, RBMs have become mainstream.

  Fig. 3 shows an example of an RBM. The RBM in Fig. 3 shows the impact of assessing the degree of economic and human damage at the time of damage, with the probability of damage as assessed by the probability of damage as the vertical axis. This is a method of evaluating the risk of damage at each part of the device, taking the degree as the horizontal axis, finding parts and damage where both the likelihood of damage and the degree of impact are large, prioritizing maintenance, and evaluating and diagnosing risk reduction methods. is there. The RBM can optimize the preventive maintenance plan such as inspection and repair of each part of the apparatus, and this evaluation method has the effect of improving the plant operation rate and reducing the operation and repair costs.

  RBM diagnostic methods have been developed for petrochemical industries and power plants, starting with the evaluation of nuclear power plants in the 1980s, and various methods have been proposed. Among them, the American Petroleum Institute (API) method (API581: Risk-Based Inspection Base Resource Document, May 2000) is objective in judging and diagnosing and has a database.

  In API581, (1) general corrosion and local corrosion (Appendix G), (2) stress corrosion cracking (SCC, Appendix H), (3) hydrogen corrosion at high temperature (Appendix I), (4) creep damage (Appendix J) (5) Fatigue damage due to mechanical vibration (Appendix K), (6) Brittle fracture (Appendix L), (7) Lining (Appendix M), (8) External surface damage (Appendix N) Since the plant is the main target, there are some events that require some corrections to be applied to boiler facilities for thermal power generation.

  FIG. 4 shows a mechanical “high” cycle fatigue damage assessment flow for piping in API 581. The failure probability of “high” cycle fatigue damage is based on the failure probability of the basic piping, whether there is any previous failure experience, frequency of vibration, type of vibration source, design change, piping complexity, piping welding method, etc. This is a flow that can be obtained by multiplying the correction coefficient determined in (1), and allows an objective piping diagnosis.

  The probability of damage in FIG. 3 is determined in FIG. 4, for example, when the index indicating the damage probability of the pipe is 1 to 10, 1 to 11 to 100, 101 to 1,000, 3, The logarithmic determination is made such that 4 is in the case of 1,001 to 10,000, and 5 is in the case of 10,001 to 100,000. Further, the degree of influence on the horizontal axis in FIG. 3 is calculated from the amount of damage calculated from the power generation output plan and the amount of power sold during the shutdown period, such as human damage, equipment repair costs, and the number of days of plant shutdown.

Also, a method of diagnosing the life of a heat transfer tube by determining the degree of progress of corrosion fatigue, the rate of thinning damage, the crack growth depth of the heat transfer tube, etc. Kaihei 11-294708) and a method for diagnosing an abnormal state of water quality in a heat transfer tube that causes prevention of corrosion of the tube (Japanese Patent Laid-Open No. 5-264538) are known.
JP-A-11-294708 Japanese Patent Laid-Open No. 5-264538 API581 `` Risk-Based Inspection Base Resource Document '' of American Petroleum Institute (API), H1-H30, May 2000

  The API581 RBM also includes a method for diagnosis of fatigue damage as Appendix-K, but the object is limited to piping as can be seen from the damage evaluation flow shown in FIG. It is made for the purpose of fatigue damage ("high" cycle fatigue damage) caused by various vibrations. Therefore, it cannot be applied to “low” cycle fatigue damage caused by thermal stress at the time of starting and stopping, which is a problem due to boiler heading.

  Accordingly, an object of the present invention is to provide a method for diagnosing the likelihood of occurrence of “low” cycle fatigue damage caused by thermal stress at the time of starting and stopping of equipment such as a device constituting a boiler, and the risk-based evaluation of the “low” cycle fatigue damage. Is to provide the law.

The problems of the present invention are solved by the following means.
In the first aspect of the invention, the damage likelihood index (failure probability) is calculated from the failure factor (F) inherent in the device, the temperature difference (ΔT) in the device, and the Young's modulus (E) of the device. This is a low-cycle fatigue damage susceptibility diagnosis method for equipment characterized by evaluating strain (ε = F × ΔT / E) as an index.

  The invention according to claim 4 is a low cycle fatigue damage risk evaluation method for equipment that evaluates risk by taking the degree of influence when equipment damage occurs on the vertical axis and the likelihood of equipment damage on the vertical axis, The vertical axis represents the low cycle fatigue damage likelihood index (failure probability) calculated by the method of claim 1, and the horizontal axis represents the power generation output plan and the amount of power sold during the equipment shutdown period. The degree of influence (CF) due to low cycle fatigue damage of equipment, which is the sum of the product of coefficient and input value of items including damage amount, compensation cost, repair cost, labor accident cost, environmental countermeasure cost and secondary damage cost. Thus, this is a low cycle fatigue damage risk evaluation method for equipment that evaluates the risk based on the product of the damage likelihood index and the degree of influence due to damage, which are obtained by dividing into 4 × 4 or 5 × 5.

  According to the present invention, the temperature (T) of the device, the number of start / stop times (N), the failure coefficient (F) specific to the device determined by the presence or absence of a stress concentration portion or a welded portion, the Young's modulus (E), and the device By calculating the fatigue probability index (failure probability) based on the fatigue life determined by the material, it is possible to diagnose the likelihood of the occurrence of “low” cycle fatigue damage due to the thermal stress at the start and stop of the equipment. Further, this is achieved by the RBM (risk-based maintenance) method in which the susceptibility of the obtained low cycle fatigue damage is plotted on the vertical axis and the influence level is plotted on the horizontal axis, and the risk of the equipment is evaluated.

Specifically, the following method can be considered.
(1) In the RBM (risk-based maintenance) method, where the vertical axis indicates the likelihood of damage and the horizontal axis indicates the degree of influence, and the risk of the equipment is evaluated, the damage factor (F) specific to the equipment is the It is set in consideration of the number of start / stop times, presence / absence of stress concentrated parts and welds, material (steel type), and past damage status. For example, F = 2.0 (MPa / ° C.) in the case of piping, and F = 5.0 (MPa / ° C.) in the case of the nozzle weld. Therefore, in the low cycle fatigue damage diagnostic method caused by the thermal stress of the equipment, the damage likelihood index (failure probability) is expressed as the failure coefficient (F) inherent in the equipment, the temperature difference (ΔT) in the equipment, Strain (ε = F × ΔT / E) calculated from Young's modulus (E) is evaluated as an index.

(2) Using the strain (ε) in (1) above and the number of times of start and stop of the boiler (N), the low cycle fatigue life obtained by regressing the low cycle fatigue damage test result of the target material in advance. By making a comparison, a low cycle fatigue damage likelihood index (failure probability) of the equipment is obtained, and in the low cycle fatigue damage diagnostic method caused by the thermal stress of the equipment, the likelihood of damage is diagnosed.

(3) The RBM (risk-based maintenance) method is used to evaluate the risk of equipment by taking the ease of low cycle fatigue damage of the equipment in (2) above on the vertical axis and taking the degree of influence on the horizontal axis. .

(Function)
In equipment that undergoes low cycle fatigue damage due to thermal stress at the time of starting and stopping, such as boiler headers and water walls, the low cycle fatigue damage is mainly caused by the number of times N the boiler starts and stops and its temperature T, Determined by generated stress (generated strain) and material.

Since the stress σ generated in the device is considered to be proportional to the temperature difference ΔT in the device, a relational expression such as equation (1) is obtained. Here, F is a failure coefficient specific to the equipment, and is determined by the degree of stress concentration in the equipment, the presence or absence of welds, and the like. This damage factor is determined in advance by finite element method analysis or the like. The failure factor F inherent to the equipment is, for example, 2.0 (MPa / ° C.) for pipes, 5.0 (MPa / ° C.) for welds on the nozzles, 6.0 (MPa / ° C.) for metal fittings on pipes, It is set to 10.0 (MPa / ° C.) for the water wall and 11.0 (MPa / ° C.) when there is a breakage in the past.
σ = F × ΔT (1)

From this, the strain ε generated in the part is expressed by the equation (2) using the Young's modulus E of the device.
ε = σ / E (2)

  Next, a low cycle fatigue test is performed on materials used in the device in advance, and low cycle fatigue property values (a, b, c, SEE) obtained by regression of the results are obtained. An example of low cycle fatigue property values is shown in Tables 1 and 2.

  Table 1 shows the values of SB49 steel (boiler and pressure vessel carbon steel) among the low cycle fatigue properties used in the evaluation flow, and Table 2 shows the values of SCMV3 steel (boiler and pressure vessel Cr-Mo steel). Yes.

Using these values, the low cycle fatigue life Nf is obtained from Equation (3).
log (Nf) = a × log (ε−b) + c (3)

If the low cycle fatigue life Nf is known in this way, the failure probability of the equipment can be obtained by using the equation (4) by taking into account the standard deviation SEE of the low cycle fatigue data and the number of times of start and stop of the boiler N. it can.
Failure probability = cumulative probability (log (N) −log (Nf) / SEE) (4)

  The vertical axis shows the probability of failure obtained by equation (4) as the probability of low cycle fatigue damage of the equipment, and the horizontal axis shows the power generation output plan during the shutdown period, such as human damage, equipment repair costs, and plant shutdown days. The RBM (risk-based maintenance) method for evaluating the risk of the device is performed by taking the degree of influence calculated from the amount of damage calculated from the amount of electricity sold.

  ADVANTAGE OF THE INVENTION According to this invention, the low cycle fatigue damage resulting from the thermal stress which becomes a problem by the header of a boiler etc. can be diagnosed with high precision, and the possibility of the damage in RBM can be determined with high precision. If the risk in RBM can be determined accurately, preventive maintenance plans such as inspections and repairs can be optimized, which has the effect of improving plant operating rates and reducing operation and repair costs.

An embodiment of the present invention will be described below with reference to FIG.
FIG. 1 is a flowchart for evaluating an index for determining the probability of occurrence of low cycle fatigue damage in an embodiment according to the present invention. FIG. 2 is a flowchart for determining the likelihood of damage to an RBM targeting low cycle fatigue according to the present invention. It is an evaluation flow with respect to SB49 steel (boiler and carbon steel for pressure vessels).

  1 and 2 are actual flowcharts for determining the likelihood of RBM damage targeting low cycle fatigue according to the present invention. The damage likelihood index (breakage probability) is actually calculated according to the following flow.

(1) The Young's modulus E is calculated from the material of the target device (for example, SB49 steel) and the temperature (for example, 300 ° C.).
(2) In this embodiment, since the welded portion of the nozzle is assumed, the inherent failure factor F is 10.0 and the temperature difference ΔT is 120 ° C.
(3) Using the obtained Young's modulus E (192300 MPa), the failure coefficient F, and the temperature difference ΔT, the strain ε generated from the equations (1) and (2) is obtained to be 0.62 (%).
(4) Using the low cycle fatigue property values (a, b, c, SEE) shown in Table 1, when the low cycle fatigue life Nf is obtained from the equation (3), Nf = 1110 is obtained.
(5) Failure probability from equation (4) using fatigue life Nf obtained in (1) to (4), low cycle fatigue property value SEE (0.2126), and boiler start / stop frequency N (2000 times) Can be requested. In the case of the present embodiment, the damage probability of the device is calculated to be 88.5 (%).

  As described above, in this example, the low cycle fatigue damage likelihood index (failure probability) is calculated from the failure coefficient (F) inherent to the device, the temperature difference (ΔT) in the device, and the Young's modulus (E) of the device. Strain (ε = F × ΔT / E) can be evaluated as an index.

  The obtained low-cycle fatigue damage likelihood index (probability of failure) is plotted on the vertical axis, and the horizontal axis represents the power generation output plan and power sales during the shutdown period, such as equipment shutdown period, human damage, and equipment repair costs. The degree of impact due to low cycle fatigue damage of equipment consisting of the sum of the coefficient and input values of items including damage amount, compensation cost, repair cost, labor accident cost, environmental countermeasure cost and secondary damage countermeasure cost calculated from ) To evaluate the risk of the equipment based on the product of the damage likelihood index and the degree of influence of damage obtained by dividing into 4 × 4 or 5 × 5 shown in FIG. Base maintenance) method can be implemented. It should be noted that the power generation output and the power sale amount may be introduced into the influence degree (CF).

  According to the present invention, low cycle fatigue damage caused by thermal stress, which is a problem in boiler headers, etc., can be diagnosed with high accuracy, the likelihood of damage in RBM can be determined with high accuracy, and due to equipment damage Predict the degree of impact and optimize the preventive maintenance plan for equipment.

It is an evaluation flowchart of an index for determining the likelihood of occurrence of low cycle fatigue damage in an embodiment according to the present invention. It is an evaluation flow with respect to SB49 steel (boiler and carbon steel for pressure vessels) which is a specific embodiment according to the present invention. Assess the risk of damage at each part of the device, with the probability of damage as assessed by the probability of damage as the vertical axis and the degree of impact assessed as the degree of economic and human damage when the damage occurred as the horizontal axis. It is a graph of the RBM evaluation method of API581. It is the high cycle fatigue damage evaluation flow with respect to mechanical vibration among RBM evaluation of API581 which is a prior art.

Claims (4)

  The damage likelihood index (breakage probability) is calculated from the damage coefficient (F) inherent to the device, the temperature difference (ΔT) in the device and the Young's modulus (E) of the device (ε = F × ΔT / A method for diagnosing the likelihood of low cycle fatigue damage of equipment, characterized by evaluating E) as an index.   The cumulative damage probability of a device is calculated using the number of start / stop times of the device (N), the operating temperature of the device (T), and material property values (fatigue curve) relating to fatigue that has been regressed in advance. 1. A method for diagnosing the likelihood of low cycle fatigue damage of the device according to 1.   The apparatus as claimed in claim 1, wherein the apparatus is a boiler apparatus. In the low cycle fatigue damage risk assessment method for equipment, where the vertical axis represents the likelihood of equipment damage and the horizontal axis represents the degree of impact when equipment damage occurs,
Take the low cycle fatigue damage likelihood index (failure probability) of the equipment calculated by the method of claim 1 on the vertical axis,
The coefficient of items including the amount of damage, compensation cost, repair cost, industrial accident cost, environmental countermeasure cost and secondary damage countermeasure cost calculated from the power generation output plan and the amount of power sales during the equipment shutdown period obtained on the horizontal axis Taking the degree of influence (CF) due to low cycle fatigue damage of equipment consisting of the sum of products of input values,
A low cycle fatigue damage risk assessment method for equipment that evaluates the risk based on the product of the damage likelihood index and the degree of influence of damage obtained by dividing into 4 × 4 or 5 × 5.

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