JP4347193B2 - Method and apparatus for predicting scale behavior of plant - Google Patents

Description

  The present invention relates to a plant scale behavior prediction method and apparatus.

In a plant operated at high temperature and high pressure, for example, a thermal power generation boiler, a steam oxidation scale is generated on the inner wall of a pipe such as a superheater pipe and a reheater pipe through which steam passes. The steam oxidation scale is peeled off and deposited on the downstream vent portion, which causes a problem due to tube blockage.
Therefore, a technique for measuring the thickness of the steam oxidation scale that causes peeling is well known. For example, as shown in Patent Document 1, a method has been proposed in which the scale thickness is measured by a nondestructive measurement method during plant operation and the thickness is monitored to reach the peeling limit.

JP-A-8-285211 (paragraphs [0019] to [0031] and FIGS. 1 to 3)

  By the way, what is shown in Patent Document 1 is only to measure the scale thickness and monitor whether or not the separation limit is reached, and to estimate the amount of separation that occurs thereafter and grasp the blockage state of the tube. Nothing is shown. Moreover, there existed a problem that the future situation could not be predicted.

  In view of the above-described problems, the present invention provides a plant scale behavior prediction method and apparatus that can accurately estimate the amount of scale peeling, grasp the state of blockage of pipes, and predict them in the future. For the purpose.

In order to solve the above problems, the present invention employs the following means.
In other words, the plant scale behavior prediction method according to the present invention is a plant scale behavior prediction method for predicting the behavior of steam oxidation scale generated in a stainless steel pipe. The scale thickness during operation calculates the scale thickness probability distribution by calculating the scale thickness according to the first probability distribution selected according to the use environment from the scale thickness distribution previously created by actual values or experimental data. The distribution calculation step and the scale peeling amount at the time of plant stoppage are selected according to the use environment from the peeling probability of the scale thickness previously created by the actual value or experimental data in the scale thickness probability distribution. Scale peeling calculated by multiplying the peeling rate according to the outer scale thickness expressed by the probability distribution An amount calculation step, a blockage rate calculation step of calculating the blockage rate of the tube based on the scale peeling amount calculated in the scale peeling amount calculation step, and a scale peeling amount calculation step calculated from the scale thickness probability distribution And a stop-time scale thickness distribution calculating step for calculating a stop-time scale thickness probability distribution excluding the scale peeling amount.

The steam oxidation scale generated in the stainless steel pipe has a two-layer structure of a dense inner layer scale and a porous outer layer scale, and the growth rates of both layers are substantially the same. This growth rate is proportional to the 1/2 power of the oxidation time, and also depends on the oxidizing atmosphere such as the temperature and the amount of dissolved oxygen.
According to the present invention, the first probability distribution reflects the difference in scale growth accompanying the change in the oxidizing atmosphere that varies depending on the plant location and time, etc., and the thickness of the outer scale generated during operation is the scale thickness probability distribution. Calculate as
And when the outer layer scale exceeds a certain thickness, the outer layer scale starts to peel off particularly when the plant is shut down. However, when the thickness of the outer layer scale reaches a certain value, the outer scale does not peel at the same time, and even at the same thickness, the outer scale may or may not peel from place to place. However, the thicker the outer layer scale, the easier it is to peel off.
In the present invention, the peeling rate corresponding to the thickness of the outer layer scale is reflected by the second probability distribution, and the peeling amount of the outer layer scale is calculated stochastically.

In this way, the amount of scale generation is reflected in the first probability distribution that incorporates the difference in conditions for each location, is calculated as a scale thickness probability distribution, and the amount of peeling of the outer scale is factored in the difference in conditions for each location. Since the calculation is performed by reflecting the second probability distribution, the amount of scale peeling can be accurately estimated in accordance with the actual situation.
The first probability distribution and the second probability distribution are selected and used according to the usage environment of the plant from those created in advance based on actual results or experimental data.
Further, the peeled outer layer scale is caused to flow downstream, and is deposited, for example, on the vent portion of the pipe and closes the same portion. When the outer layer scale peeled off in the closed portion is further accumulated, it is finally sealed. If sealed in this way, it will overheat and eventually lead to a crash.

According to the present invention, since the blockage rate of the pipe is calculated based on the scale peel amount calculated in the scale peel amount calculation step, it is possible to grasp the state of the blockage.
In addition, the relationship between the scale peeling amount and the blockage rate is obtained from the result of measurement with an actual machine in advance.
According to the present invention, since the scale thickness probability distribution at the time of stop after the outer layer scale peeling is calculated in the scale thickness distribution calculation process at the time of stop, the scale thickness distribution calculation during operation is calculated based on the scale thickness probability distribution at the time of stop. By repeating the following steps, it is possible to predict the scale peeling amount and the tube blockage at the time of plant stoppage in the future. For this reason, depending on the scale peeling amount and the pipe clogging situation at each plant stoppage, for example, optimization of the actual inspection interval considering the risk, change of the plant operation mode for reducing the scale peeling amount, or effective It can take measures such as maintenance planning.

  Further, in the plant scale behavior prediction method according to the present invention, before the scale peeling amount calculation step, the scale thickness at a plurality of locations is measured, and the first probability distribution is corrected based on the actually measured value. An operation scale thickness distribution recalculation step for recalculating the probability distribution is provided.

As described above, when the plant is stopped, the scale thicknesses at a plurality of locations are measured, the first probability distribution is corrected based on the measured values, and the scale thickness probability distribution is recalculated. One probability distribution can be used to calculate the scale thickness probability distribution.
For this reason, since the accuracy of the scale thickness probability distribution increases, it is possible to more accurately estimate the scale peeling amount and the tube blockage state.
Note that the scale thickness is measured, for example, by ultrasonic waves or by extubation.
Further, the number of measurement points needs to be sufficient to create the first probability distribution, for example, 10% of the total number of tubes. If the number of measurement points is increased, the scale peeling amount and the tube blockage state can be estimated more accurately.

  Furthermore, the scale behavior prediction method for a plant according to the present invention includes a correcting step of measuring the amount of scale accumulation at a plurality of locations during operation, and correcting the second probability distribution based on the measured value. .

As described above, since the scale accumulation amount at a plurality of locations is measured during operation and the second probability distribution is corrected based on the measured value, the second probability distribution can be obtained from time to time even during operation. You can change it to suit your situation. Even if there is a change in the operating status, the second probability distribution can be corrected to an appropriate one each time, so a more accurate scale separation amount can be calculated, and a more accurate estimation of the tube blockage status can be made. .
For example, the scale accumulation amount is estimated by looking at a display of a thermometer attached to the downstream header.
In addition, the number of measurement points needs to be sufficient to create the second probability distribution, for example, 10% of the total number of tubes. If the number of measurement points is increased, the scale peeling amount and the tube blockage state can be estimated more accurately.
Furthermore, since it can be grasped if a significant abnormality, for example, a rapid rise in temperature, occurs at the measurement location, it can also be used for abnormality monitoring.

The plant scale behavior prediction apparatus according to the present invention is a plant scale behavior prediction apparatus for predicting the behavior of a steam oxidation scale generated in a stainless steel pipe, and the outer layer scale thickness of the steam oxidation scale generated during operation. Calculate the scale thickness probability distribution during operation by calculating the scale thickness probability distribution using the first probability distribution selected according to the usage environment from the scale thickness distribution previously created from actual values or experimental data. And a second probability distribution in which the scale peeling amount at the time of the plant shutdown is selected in accordance with the use environment from the scale thickness peeling probability previously created in the scale thickness probability distribution based on the actual value or experimental data. Scale peeling amount calculation means for calculating by multiplying the peeling rate according to the outer layer scale thickness represented by A clogging rate calculating means for calculating a clogging rate of the tube based on the scale peeling amount calculated by the scale peeling amount calculating means; and a scale peeling calculated by the scale peeling amount calculating means from the scale thickness probability distribution. And a stop scale thickness distribution calculating means for calculating a stop scale thickness probability distribution excluding the amount.

As described above, the scale generation amount during operation is reflected in the first probability distribution incorporating the difference in conditions for each place by the scale thickness distribution calculation unit, and is calculated as the scale thickness probability distribution, and the scale peeling amount calculation unit Therefore, the amount of peeling of the outer scale is calculated by reflecting the second probability distribution incorporating the difference in conditions for each location, so that the amount of peeling of the scale can be accurately estimated according to the actual situation.
In addition, since the blockage rate of the tube is calculated based on the scale peel amount calculated by the scale peel amount calculating means, it is possible to grasp the state of the blockage.
Furthermore, since the scale thickness probability distribution during stoppage is calculated by the scale thickness distribution calculation during stoppage, the scale thickness distribution during stoppage is calculated based on the scale thickness probability distribution during stoppage. By operating it, it is possible to predict the scale peeling amount and the tube blockage state at the time of plant stoppage in the future. For this reason, depending on the scale peeling amount and the pipe clogging situation at each plant stoppage, for example, optimization of the actual inspection interval considering the risk, change of the plant operation mode for reducing the scale peeling amount, or effective It is possible to take measures such as maintenance plans.

  Further, the plant scale behavior prediction apparatus according to the present invention corrects the first probability distribution by an actual measurement unit that actually measures the scale thickness at a plurality of locations when the plant is stopped, and an actual measurement value that is actually measured by the actual measurement unit, A scale thickness distribution recalculation unit for operation that recalculates the scale thickness probability distribution.

As described above, when the plant is stopped, the scale thicknesses at a plurality of locations are actually measured by the measuring unit, the first probability distribution is corrected by the actually measured values, and the scale thickness probability distribution is re-read by the operating scale thickness distribution recalculating unit. Since the calculation is performed, the scale thickness probability distribution can be calculated using the first probability distribution according to the conditions of the current plant.
For this reason, since the accuracy of the scale thickness probability distribution increases, it is possible to more accurately estimate the scale peeling amount and the tube blockage state.
As the actual measurement means, for example, a measuring instrument using ultrasonic waves or a measuring instrument that directly measures by extubation is used.
Further, the number of measurement points needs to be sufficient to create the first probability distribution, for example, 10% of the total number of tubes. If the number of measurement points is increased, the scale peeling amount and the tube blockage state can be estimated more accurately.

  Further, the scale behavior prediction apparatus for a plant according to the present invention includes a measuring unit that measures the amount of scale accumulation at a plurality of locations during operation, and a correcting unit that corrects the second probability distribution based on the measurement value measured by the measuring unit. And.

As described above, the measurement means measures the amount of scale accumulation at a plurality of locations during operation, and includes a correction means for correcting the second probability distribution based on the measured value. Therefore, even during operation, the second probability distribution can be obtained at any time. It can be changed according to the driving situation at that time. Even if there is a change in the operating status, the second probability distribution can be corrected to an appropriate one each time, so a more accurate scale separation amount can be calculated, and a more accurate estimation of the tube blockage status can be made. .
As the measuring means, for example, a thermometer attached to the downstream header is employed.
In addition, the number of measurement points needs to be sufficient to create the second probability distribution, for example, 10% of the total number of tubes. If the number of measurement points is increased, the scale peeling amount and the tube blockage state can be estimated more accurately.
Furthermore, if a significant abnormality, for example, a rapid rise in temperature, occurs at the measurement location, it can be grasped by the measuring means, so that it can also be used for abnormality monitoring.

  Furthermore, a plant according to the present invention is characterized in that the plant scale behavior prediction apparatus according to any one of claims 4 to 6 is used.

  The scale behavior prediction device can accurately estimate the amount of scale peeling and the condition of tube blockage, and can predict future fluctuations. To optimize the actual inspection interval considering the risk and reduce the amount of scale peeling. The plant operation mode can be changed or an effective maintenance plan can be taken.

  According to the present invention, the amount of scale peeling can be accurately estimated in accordance with the actual situation. In addition, the state of blockage of the tube can be grasped. Further, it is possible to predict the scale peeling amount and the pipe blockage state when the plant is stopped in the future, and it is possible to take measures according to the scale peeling amount and the pipe blockage state when each plant is stopped.

Embodiments according to the present invention will be described below with reference to the drawings.
[First embodiment]
Hereinafter, a first embodiment of the present invention will be described with reference to FIGS. This embodiment is applied to the boiler 1 as a plant.
FIG. 1 is a block diagram showing an overall schematic configuration of the boiler 1.
The boiler 1 includes a furnace 3 installed in a vertical direction, a combustion device 7 installed in a lower part of the furnace wall 5 of the furnace 3, a flue 9 connected to an outlet of the furnace 3, and an upper part of the furnace 3. A superheater 11, a reheater 13 and a economizer 15 provided over the flue 9, and a steam drum 17 provided at the upper part of the furnace 3 are provided.
A large number of water pipes (not shown) extend in the vertical direction inside the furnace wall 5. Each water pipe is connected to the steam drum 17 at upper and lower ends.

When a flame is generated in the lower part of the furnace 3 by the combustion device 7, the combustion gas flows from the bottom to the top in the furnace 3 and is discharged to the flue 9. At this time, water supplied from a water supply pump (not shown) is preheated by the economizer 15 and then supplied to the steam drum 17. The water supplied from the steam drum 17 to each water pipe (not shown) of the furnace wall 5 is heated to flow into the steam drum 17 while flowing through the water pipe from the bottom to the saturated steam. Further, the saturated steam of the steam drum 17 is introduced into the superheater 11 and is heated by the combustion gas. The superheated steam generated by the superheater 11 is supplied to, for example, a turbine.
In addition, the steam taken out in the middle of the expansion process in the turbine or the like is introduced into the reheater 13 and reheated and returned to the turbine.

FIG. 2 is a front view showing a schematic configuration of the superheater 11.
The superheater 11 has an inlet header 19 and an outlet header 21 arranged parallel to each other on a horizontal plane, and the inlet header 19 and the outlet header 21 are connected by a number of heat transfer tubes (tubes) 23.
A steam supply pipe 25 that feeds the steam in the steam drum 17 to the inlet header 19 is connected to the center of the inlet header 19 in the axial direction, and from the outlet header 21 to the center of the outlet header 21 in the axial direction. A steam discharge pipe 27 for sending steam to a turbine or the like is connected.
The heat transfer tubes 23 are provided at predetermined intervals in the axial direction of the inlet header 19 and the outlet header 21, and are distributed in the circumferential direction on the lower half side of the headers 19, 21 at each mounting location in the axial direction. For example, 300 books (for convenience of illustration in FIG. 2, 6 books) are provided. Each heat transfer tube 23 is made of stainless steel, and as shown in FIG. 2, the heat transfer tube 23 is bent into a substantially W shape to increase the flow path length, and the steam residence time in the heat transfer tube 23 is increased. Therefore, the heat transfer tube 23 is formed with a vent portion 24 having a small radius of curvature.
Note that the reheater 13 is configured in substantially the same manner.

ｄ：スケール厚み（mm）
ｋ：速度定数（mm／ｓ^0.5）
ｔ：酸化時間（運転時間）（ｓ）
速度定数ｋは、ステンレス鋼の材質および酸化雰囲気（温度、溶存酸素量等）によって異なるので、それらの条件毎に実績からみた値が求められている。 Since high-temperature superheated steam (steam) passes through the heat transfer tubes 23 constituting the superheater 11 and the reheater 13, stainless steel is oxidized by the superheated steam, and a scale (steam oxidation scale) is formed on the inner wall of the heat transfer tube 23. ) Is generated.
This scale has a two-layer structure of a dense inner layer scale and a porous outer layer scale, and the growth rates of both layers are substantially equal.
The growth rate of the scale is given by the parabolic law shown in equation (1) with respect to time.

d: Scale thickness (mm)
k: Speed constant (mm / s ^0.5 )
t: oxidation time (operation time) (s)
Since the rate constant k varies depending on the material of the stainless steel and the oxidizing atmosphere (temperature, dissolved oxygen amount, etc.), a value obtained from actual results is required for each of these conditions.

FIG. 3 schematically shows the growth situation of the scale. When the operation of the boiler 1 is started from a state where there is no scale, the scale grows abruptly and increases in thickness according to the formula (1), but the growth rate decreases as the operation time becomes longer. .
The peeling of the scale occurs at the boundary between the inner layer scale and the outer layer scale, particularly when the boiler 1 is stopped, that is, in the process of cooling the scale.
When the operation of the boiler 1 is resumed, the scale grows along the formula (1) where the scale is not peeled off. On the other hand, when the scale is peeled off, the outer layer scale grows again together with the inner layer scale. This re-growth rate does not become the initial rapid growth rate, but is almost the same as the rate at which the regrowth did not peel off.
This is because the thickness of the inner scale is the same both when the scale is peeled off and where it is not peeled off, so the amount of metal ions mainly composed of iron diffusing from the base material is almost the same. Because.

The behavior of this scale, i.e., growth, separation, deposition, etc., has a great influence on the operation of the boiler 1. In the present embodiment, a scale behavior prediction device 31 that estimates or predicts this behavior is provided.
FIG. 4 is a block diagram showing a schematic configuration of the scale behavior prediction apparatus 31. As shown in FIG.
The scale behavior prediction apparatus 31 includes a processing unit 33 and a display unit 35 having an input / output function.
The processing unit 33 includes a storage unit 37 that stores programs, data, processing results, and the like, an input / output interface 39 that controls input / output between the display unit 35, and an operating scale thickness distribution calculation processing unit (operation Medium scale thickness distribution calculating means) 41, scale peeling amount calculating section (scale peeling amount calculating means) 43, blockage rate calculating section (blocking rate calculating means) 45, and stop-time scale thickness distribution calculating section (stopping) Hour scale thickness distribution calculating means) 47.

  The operating scale thickness distribution calculation processing unit 41, the scale peeling amount calculation unit 43, the blockage rate calculation unit 45, and the stopped scale thickness distribution calculation processing unit 47 are illustrated separately in FIG. Alternatively, it is composed of a plurality of CPUs, each having a required function in accordance with an instruction from the display unit 35 or a program. Although these required functions will be described in detail later, the operating scale thickness distribution calculation processing unit 41 calculates the outer layer scale thickness of the steam oxidation scale generated during the operation as a scale thickness probability distribution. It is. The scale peeling amount calculation unit 43 calculates the scale peeling amount when the boiler 1 is stopped. The blockage rate calculating unit 45 calculates the blockage rate of the heat transfer tube based on the scale peel amount calculated by the scale peel amount calculating means. The stop-time scale thickness distribution calculation processing unit 47 calculates a stop-time scale thickness probability distribution that is a scale thickness probability distribution after the scale is peeled off.

The operation of the scale behavior prediction apparatus 31 according to the present embodiment described above will be described.
FIG. 5 is a flowchart showing the processing flow of the scale behavior prediction apparatus 31.
First, the operating scale thickness distribution calculation step S1 will be described.
The storage unit 37 stores, as a probability distribution K (first probability distribution), values for the rate constant k for each condition such as the stainless steel material and the oxidizing atmosphere (temperature, dissolved oxygen amount, etc.). In the operating scale thickness distribution calculation processing unit 41, the probability distribution K that matches the operating conditions of the boiler 1 is selected, and the scale growth calculation is performed by equation (1). By this calculation, an operating scale thickness distribution along the probability distribution K is obtained as shown in FIG.

Next, the scale peeling amount calculation step S2 will be described.
As shown in FIG. 8, when the outer layer scale exceeds a certain thickness D as shown in FIG. 8, the outer layer scale begins to peel off particularly when the plant is shut down. However, when the thickness of the outer layer scale reaches a certain value, the outer scale does not peel at the same time, and even at the same thickness, the outer scale may or may not peel from place to place. This event can be expressed by a normal distribution model such as a peeling limit outer layer scale thickness distribution (second probability distribution) S.
Now, for example, assuming that the outer scale is growing uniformly as a whole, the state of peeling will be described with reference to FIG. When the boiler 1 is stopped after being operated for Δt time, the thickness of the outer layer scale becomes D1 (> D). At this time, the peeling probability based on the peeling limit outer layer scale thickness distribution S is X1 in the standard normal distribution, and peeling occurs in the entire X1. As a result, the average thickness of the outer scale is D1 × (1−X1). In this state, when the boiler 1 is operated and stopped for the next Δt time and the thickness of the outer layer scale becomes D2 (> D), the separation probability due to the separation limit outer layer scale thickness distribution S is a standard normal distribution of X2. Thus, peeling occurs at the entire X2. As a result, the average thickness of the outer scale is D1 × (1−X1).

FIG. 9 shows the relationship between the outer layer scale thickness and the peeling rate (peeling probability) by developing X1 and X2, and is expressed based on actual results in the plant.
The water quality management of the boiler 1 includes a method called All Volatile Treatment (AVT) that suppresses the progress of corrosion by maintaining the oxygen concentration in water at a predetermined value (for example, 7 ppb) or less, There is a method called combined water treatment (CWT) which suppresses the progress of corrosion and the growth of scale by maintaining the oxygen concentration contained in 20 to 200 ppb, and the peeling rates are different. Since the scale produced by CWT is more easily peeled off, the peel rate is higher even if the outer layer scale thickness is thin.

In the scale peeling amount calculation unit 43, the operation in which the peeling rate of either CWT or AVT in the data of FIG. 9 stored in the storage unit 37 by water quality management of the boiler 1 is calculated in the operating scale thickness distribution calculation step S1. Multiply the medium scale thickness distribution (FIG. 6) to obtain the peeled portion R. FIG. 7 shows this state.
Then, the scale peeling amount calculation unit 43 calculates the scale peeling weight by the following equation (2).
Scale peel weight = scale thickness x internal surface area x peel rate x specific gravity (2)
Here, the inner surface area is the area of the inner surface of the heat transfer tube 23, and the specific gravity is, for example, 5.2 g / cm ³ .

  In this way, the scale generation amount is reflected by the probability distribution K of the rate constant k created based on the results incorporating the difference in conditions for each place, calculated as a scale thickness probability distribution, and peeling of the outer scale Since the amount is calculated by reflecting the separation limit outer layer scale thickness distribution S that incorporates the difference in conditions for each location, the amount of separation of the scale can be accurately estimated according to the actual situation.

Next, the blockage rate calculation step S3 will be described.
The peeled outer layer scale flows downstream, and is deposited on, for example, the vent portion 24 having a small radius of curvature formed in the heat transfer tube, thereby closing the portion. This clogging occurs approximately in proportion to the scale peel weight. FIG. 10 shows the relationship between the scale peel weight and the blockage rate based on actual performance.
The blockage rate calculation unit 45 calculates the blockage rate of the heat transfer tube 23 from the scale peel weight calculated in the scale peel amount calculation unit 43 using the relationship between the scale peel weight and the blockage rate stored in the storage unit 37. To do.
Thereby, the obstruction | occlusion condition of the heat exchanger tube 23 can be grasped | ascertained.

Next, the stop-time scale thickness distribution calculating step S4 will be described.
Since the peeling of the steam oxidation scale occurs at the boundary between the inner layer scale and the outer layer scale, the portion of the peeling portion R in FIG. 7 has no outer layer scale. The thickness of the outer scale remains the same for the part that has not been peeled off.
The stop scale thickness distribution calculation processing unit 47 uses this relationship to calculate the stop scale thickness distribution.
This scale thickness distribution at the time of stop is the original data when the scale growth calculation is performed at the start of the next boiler 1 operation.

In the present embodiment, the scale thickness distribution calculation unit 47 at the time of stoppage calculates the probability scale distribution at the time of stoppage after the outer layer scale is peeled off, so the scale thickness distribution calculation during operation is calculated based on the scale thickness probability distribution at the time of stoppage. The scale thickness distribution during operation is calculated by the unit 41, the scale peeling weight is then calculated by the scale peeling amount calculation unit 43, and then the blockage rate of the heat transfer tube 23 is calculated by the blockage rate calculation unit 45. By repeating this, it is possible to predict the scale peeling weight and the heat transfer tube blockage when the plant is stopped in the future.
Thus, since the scale peeling amount at the time of a plant stop in the future and the pipe | tube obstruction | occlusion situation can be estimated, the operation | use of the boiler 1 corresponding to it can be performed.

For example, the optimization of the actual inspection interval considering the risk will be described with reference to FIG.
If the peeled outer layer scale accumulates on the vent portion 24 of the heat transfer tube 23 and is sealed, it will be overheated and eventually lead to a breakage accident. For this reason, the actual condition is inspected to inspect the sealed state. This inspection is expensive. If the number of inspections is small, that is, the inspection interval is increased, the inspection cost C per operation time of the boiler 1 is reduced.
On the other hand, the blocking rate increases as the operation time increases. That is, as the operation time between inspections becomes longer, the blocking rate also increases. Assuming that the amount of damage caused by the tsunami accident multiplied by the blockage rate is the pipe blockage risk E, the pipe blockage risk E is expressed as the inspection interval becomes longer as shown in FIG.
The total risk amount F obtained by adding the inspection cost C and the piping blockage risk E becomes a downwardly convex curve, and the inspection interval at which the total risk E becomes the minimum can be found.

The operation mode of the boiler 1 includes LSS (Long Start Stop), WSS (Week Start Stop), and DSS (Day Start Stop). LSS has a long operation time and a large scale growth amount during operation. Therefore, a large amount of scale peeling occurs at the time of stoppage, and the scale tends to accumulate. On the other hand, in WSS and DSS, since the operation time is short, the scale growth during operation is not large, the amount of scale peeling at the time of stoppage is small, and the scale tends to be difficult to deposit.
In the present embodiment, it is possible to predict how the scale peeling weight and the blockage rate will change for each operation mode of LSS, WSS, and DSS, or for an operation mode that combines them. For example, there is little possibility of blockage in the long term. Operation can be performed.
Furthermore, since the state of the blockage can be grasped in the future, the effect of the maintenance can be predicted accordingly, and an effective maintenance plan can be made.
[Second Embodiment]
Next, the scale behavior prediction apparatus 31 according to the second embodiment of the present invention will be described with reference to FIGS.
Since the scale behavior prediction apparatus 31 of the present embodiment is applied to the same boiler 1 as that of the first embodiment, description of the structure and operation of the boiler 1 is omitted. The basic configuration of the scale behavior prediction apparatus 31 of the present embodiment is the same as that of the first embodiment, but is different from the first embodiment in that there is an additional part in the configuration of the processing unit 33. Therefore, in this embodiment, this additional part is mainly demonstrated and the overlapping description is abbreviate | omitted about another part.
In addition, the same code | symbol is attached | subjected to the component same as 1st embodiment, and the detailed description is abbreviate | omitted.

In this embodiment, the scale growth calculation is performed by the first probability distribution calculating means 49 for recalculating the probability distribution K in the processing unit 33, and the probability distribution K calculated by the first probability distribution calculating means 49 to establish the scale thickness. An operation-time scale thickness distribution recalculation means 51 for calculating the distribution is provided.
The scale peeling amount calculation unit 43 is configured to calculate the scale peeling weight based on the scale thickness probability distribution calculated by the operating scale thickness distribution recalculation means 51.

The scale behavior predicting device 31 measures the scale thickness at a plurality of locations when the boiler is stopped, and transmits the results to the first probability distribution calculating means 49 via the display device 35 and the I / O interface 39. Is provided.
As the measurement of the scale thickness by the actual measurement means 53, an appropriate means such as measurement by ultrasonic waves or measurement by extubation can be used.
In addition, the number of measurement points is required to be at least a sufficient number to create the probability distribution K by the first probability distribution calculation means 49, for example, 30 points.

The operation of the scale behavior prediction apparatus 31 according to the present embodiment configured as described above will be described with reference to FIG.
The operating scale thickness distribution calculating step S1, the scale peeling amount calculating step S2, the blockage rate calculating step S3, and the stop-time scale thickness distribution calculating step S4 are the same as those in the first embodiment, and thus redundant description is omitted. .
In the present embodiment, the operating scale thickness distribution recalculation step S5 is inserted between the operating scale thickness distribution calculation step S1 and the scale peeling amount calculation step S2.

The operating scale thickness distribution recalculation step S5 will be described.
When the boiler 1 is stopped, the scale thicknesses of 30 locations (10% of the number of heat transfer tubes 23) of the heat transfer tubes 23 of the superheater 11 are measured by ultrasonic waves. This may be measured by extubation.
The measurement result is transmitted from the actual measurement means 53 to the first probability distribution calculation means 49 via the display device 35 and the I / O interface 39.
The first probability distribution calculating unit 49 calculates the probability distribution K of the rate constant k of the scale growth rate from the transmitted 30 scale amounts, and transmits the probability distribution K to the operating scale thickness distribution recalculating unit 51.

The operating scale thickness distribution recalculation means 51 recalculates the scale thickness probability distribution based on the transmitted probability distribution K in the same manner as the operating scale thickness distribution calculation step S1.
In the scale peeling amount calculation step S2, the scale peeling weight is calculated based on the scale thickness probability distribution calculated by the operating scale thickness distribution recalculation means 51.

As described above, in this embodiment, the scale thickness is actually measured when the boiler 1 is stopped, the probability distribution K is corrected based on the measured scale thickness, and the scale thickness probability distribution is recalculated. The scale thickness probability distribution can be calculated using the obtained probability distribution K.
For this reason, since the accuracy of the scale thickness probability distribution increases, it is possible to more accurately estimate the scale peeling amount and the tube blockage state.
If the number of scale thickness measurement points is increased, the scale peeling amount and the tube blockage state can be estimated more accurately.
Moreover, in this embodiment, there exists the effect | action and effect of above-described 1st embodiment similarly.

[Third embodiment]
Next, the scale behavior prediction apparatus 31 according to the third embodiment of the present invention will be described with reference to FIGS.
Since the scale behavior prediction apparatus 31 of the present embodiment is applied to the same boiler 1 as that of the first embodiment, description of the structure and operation of the boiler 1 is omitted. The basic configuration of the scale behavior prediction apparatus 31 of the present embodiment is the same as that of the first embodiment, but is different from the first embodiment in that there is an additional part in the configuration of the processing unit 33. Therefore, in this embodiment, this additional part is mainly demonstrated and the overlapping description is abbreviate | omitted about another part.
In addition, the same code | symbol is attached | subjected to the component same as 1st embodiment, and the detailed description is abbreviate | omitted.

In the present embodiment, the processing unit 33 is provided with a second probability distribution calculating means 55 for recalculating the peeling limit outer layer scale thickness distribution S and a risk evaluating means 57.
The scale peeling amount calculation unit 43 is configured to calculate the scale peeling weight based on the peeling limit outer layer scale thickness distribution S calculated by the second probability distribution calculating means 55.
The scale behavior prediction device 31 measures the amount of scale accumulation at a plurality of locations during operation of the boiler 1 and transmits the result to the second probability distribution calculation means 55 via the display device 35 and the I / O interface 39. Means 59 are provided.

As the measurement of the amount of scale accumulation by the measuring means 59, a thermometer attached to the outlet header 21 provided on the downstream side is used, and the scale accumulation amount is estimated by looking at the display of the thermometer.
In addition, the number of measurement points is required to be at least a sufficient number, for example, 30 points, for creating the separation limit outer layer scale thickness distribution S by the second probability distribution calculating means 55.
If the number of measurement points by the measuring means 59 is increased, the peeling limit outer layer scale thickness distribution S can be estimated more accurately, but on the other hand, the equipment cost becomes expensive.
The risk evaluation means 57 calculates the optimal number of measurement points that minimizes the risk.

The operation of the scale behavior prediction apparatus 31 according to the present embodiment configured as described above will be described with reference to FIG.
The operating scale thickness distribution calculating step S1, the scale peeling amount calculating step S2, the blockage rate calculating step S3, and the stop-time scale thickness distribution calculating step S4 are the same as those in the first embodiment, and thus redundant description is omitted. .
In the present embodiment, in addition to the first embodiment, the peeling limit outer layer scale thickness distribution S used in the scale peeling amount calculation step S2 is corrected based on the actual machine data. ) Is provided.

The peeling limit outer layer scale thickness distribution S correction step S6 will be described.
During the boiler 1 operation, the steam temperature at 30 locations (10% of the number of heat transfer tubes 23) is measured in the vicinity of the outlet header 23 of the heat transfer tubes 23.
If there is a place where scale has accumulated on the upstream side, the temperature rises in accordance with the amount of deposition, so the amount of scale deposition can be estimated by displaying the thermometer.
The measurement result is transmitted from the measuring means 59 to the second probability distribution calculating means 55 via the display device 35 and the I / O interface 39.
The second probability distribution calculating means 55 calculates the separation limit outer layer scale thickness distribution S from the transmitted 30 accumulated scale amounts and transmits it to the scale separation amount calculation unit 43.
Based on the transmitted peeling limit outer layer scale thickness distribution S, the scale peeling amount calculation unit 43 calculates the scale peeling weight from the scale thickness probability distribution calculated in the operating scale thickness distribution calculation step S1.

Next, the operation of the risk evaluation means 57 will be described with reference to FIG.
If the peeled outer layer scale accumulates on the vent portion 24 of the heat transfer tube 23 and is sealed, it will be overheated and eventually lead to a breakage accident. For this reason, it is important to accurately estimate the sealing situation. If the number of measurement points by the measuring means 59 increases, the sealed state can be estimated more accurately. An increase in measurement points leads to an increase in measurement cost G.
On the other hand, since the blockage rate can be estimated more accurately, the piping blockage risk (which is obtained by multiplying the amount of damage caused by the jet accident by the blockage rate) E decreases as the number of measurement points increases.
The total risk amount F including the measurement cost G and the piping blockage risk E becomes a downwardly convex curve, and the number of measurement points where the total risk E becomes the minimum can be found.
The risk evaluation means 57 calculates the optimum number of measurement points from the relationship as shown in FIG.

Further, the number of measurement points can be set to be small for, for example, an LSS in which large peeling is likely to occur, and less for WSS and DSS where there is less possibility depending on the operation mode of the boiler 1.
Further, when there is a difference between the estimated accumulation amount and the actual accumulation amount by the periodic inspection, the number of measurement points may be increased or decreased. For example, when the actual deposition amount is smaller, it is decreased, and when it is larger, it is increased.

As described above, the measuring means 59 measures the amount of scale deposition at a plurality of locations during operation, and includes a correction process for correcting the peeling limit outer layer scale thickness distribution S based on this measurement value. The separation limit outer layer scale thickness distribution S can be changed in accordance with the operation state at that time. Even if there is a change in the operating conditions, the separation limit outer layer scale thickness distribution S can be corrected to an appropriate one each time, so that a more accurate scale separation weight can be calculated, and the tube clogging situation can be estimated more accurately. Can do.
If the number of scale thickness measurement points is increased, the scale peeling amount and the tube blockage state can be estimated more accurately.

Moreover, since it can grasp | ascertain if remarkable abnormality, for example, a rapid rise of temperature, etc. generate | occur | produce in a measurement location, it can utilize also as abnormality monitoring.
In addition, in this embodiment, the effect | action of the above-mentioned 1st embodiment and an effect are show | played similarly.

In the present embodiment, the second probability distribution calculating means 55 and the risk evaluating means 57 are added to the scale behavior predicting means 31 of the first embodiment, but the present invention is not limited to this, and the second embodiment You may make it add the 2nd probability distribution calculation means 55 and the risk evaluation means 57 to the scale behavior prediction apparatus 31 of this.
In this way, the scale peeling amount and the tube blockage state can be predicted even more accurately.
Further, the risk evaluation means 57 is not particularly essential in the present invention and may be omitted.

It is a block diagram showing a schematic structure of a boiler concerning a first embodiment of the present invention. It is a front view showing a schematic structure of a superheater concerning a first embodiment of the present invention. It is a schematic diagram explaining the growth condition of a scale. It is a block diagram which shows the scale behavior prediction apparatus concerning 1st embodiment of this invention. It is a flowchart which shows the processing flow in the scale behavior prediction apparatus concerning 1st embodiment of this invention. It is a figure which shows scale thickness probability distribution. It is a figure which shows the example of the amount of scale peeling. It is a figure which shows a scale peeling condition. It is a figure which shows a peeling limit outer layer scale thickness distribution. It is a figure which shows the relationship between peeling weight and the obstruction | occlusion rate. It is a figure which shows the relationship between a test | inspection interval and the obstruction | occlusion risk. It is a block diagram which shows the scale behavior prediction apparatus concerning 2nd embodiment of this invention. It is a flowchart which shows the processing flow of the scale behavior prediction apparatus concerning 2nd embodiment of this invention. It is a block diagram which shows the scale behavior prediction apparatus concerning 3rd embodiment of this invention. It is a flowchart which shows the processing flow of the scale behavior prediction apparatus concerning 3rd embodiment of this invention. It is a figure which shows the relationship between the number of measurement, and obstruction | occlusion risk.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Boiler 23 Heat transfer tube 31 Scale behavior prediction apparatus 41 Scale thickness distribution calculation means 43 during operation Scale peeling amount calculation means 45 Blocking rate calculation means 47 Stop scale thickness probability distribution calculation means 51 Operation scale thickness distribution recalculation means 53 Actual measurement means 55 Second probability distribution calculation means 59 Measurement means K Probability distribution S Peeling limit outer layer scale thickness distribution S1 In-operation scale thickness distribution calculation step S2 Scale peeling amount calculation step S3 Blockage rate calculation step S4 Stop scale thickness Probability distribution calculation step S5 Operation scale thickness distribution recalculation step S6 Peeling limit outer layer scale thickness distribution S correction step

Claims (7)

In the plant scale behavior prediction method for predicting the behavior of steam oxidation scale generated in a stainless steel pipe,
The outer layer scale thickness of the steam oxidation scale generated during operation is calculated by the first probability distribution selected according to the use environment from the scale thickness distribution created in advance by actual values or experimental data. An operating scale thickness distribution calculating step for calculating a thickness probability distribution;
The amount of scale peeling when the plant is stopped is expressed by the second probability distribution selected according to the use environment from the scale thickness peeling probability previously created from the actual value or experimental data in the scale thickness probability distribution. A scale peeling amount calculation step of calculating by multiplying the peeling rate according to the outer layer scale thickness,
A blockage rate calculating step of calculating the blockage rate of the tube based on the scale peel amount calculated in the scale peel amount calculating step;
Stop scale thickness distribution calculation step for calculating a stop scale thickness probability distribution by removing the scale peel amount calculated in the scale peel amount calculation step from the scale thickness probability distribution;
A scale behavior prediction method for a plant, comprising:   Before the scale peeling amount calculating step, the scale thickness distribution at the time of operation is obtained by actually measuring the scale thickness at a plurality of locations, correcting the first probability distribution based on the actually measured value, and recalculating the scale thickness probability distribution. The method according to claim 1, further comprising a step.   The scale behavior of the plant according to claim 1, further comprising a correction step of measuring scale accumulation amounts at a plurality of locations during operation, and correcting the second probability distribution based on the measured values. Prediction method. In the plant scale behavior prediction device that predicts the behavior of steam oxidation scale generated in stainless steel pipes,
The outer layer scale thickness of the steam oxidation scale generated during operation is calculated by the first probability distribution selected according to the use environment from the scale thickness distribution created in advance by actual values or experimental data. An operating scale thickness distribution calculating means for calculating a probability distribution;
The amount of scale peeling when the plant is stopped is expressed by the second probability distribution selected according to the use environment from the scale thickness peeling probability previously created from the actual value or experimental data in the scale thickness probability distribution. Scale peeling amount calculating means for calculating by multiplying the peeling rate according to the outer layer scale thickness,
A blockage rate calculating means for calculating the blockage rate of the tube based on the scale peel amount calculated by the scale peel amount calculating means;
Stop scale thickness distribution calculating means for calculating the stop scale thickness probability distribution by removing the scale peel amount calculated by the scale peel amount calculating means from the scale thickness probability distribution;
An apparatus for predicting scale behavior of a plant, comprising: Actual measurement means for actually measuring the scale thickness at multiple locations when the plant is stopped,
5. The operating scale thickness distribution recalculation means for correcting the first probability distribution based on the actual measurement value actually measured by the actual measurement means and recalculating the scale thickness probability distribution. The scale behavior prediction apparatus of the described plant. A measuring means for measuring the amount of scale accumulation at a plurality of locations during operation;
The plant scale behavior prediction apparatus according to claim 4, further comprising: a correction unit that corrects the second probability distribution based on a measurement value measured by the measurement unit.   A plant characterized by using the plant scale behavior prediction apparatus according to claim 4.

Images