Patent Application
20230048806
This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2021-130513, filed on Aug. 10, 2021, the entire contents of which are incorporated herein by reference.
Embodiments of the present invention relate to a technique for evaluating blade damage in association with operation of a turbine.
In a turbine, blades are subjected to a jet of high-temperature and high-pressure steam or gas generated by heating in, for example, a boiler or a combustor so as to obtain driving force and rotate. In this steam or gas, solid particles are mixed. Although a capturing method such as a strainer is provided at an appropriate position such as a steam valve for the purpose of excluding all the solid particles, it is inevitable that a certain rate of the solid particles flow into the inside of the turbine. When the solid particles mixed in the steam or gas collide with the surfaces of the respective blades, the blades are thinned from the surfaces. This is due to occurrence of SPE (Solid Particle Erosion), i.e., phenomenon in which the surface is eroded or worn by the collision of the solid particles.
In particular, of the blades provided on the turbine rotating shaft in multiple stages, the thickness-loss due to SPE is remarkable in the first-stage rotor blades. The thickness-loss amount (i.e., reduction in thickness) of the first-stage rotor blades is managed in such a manner that the thickness-loss amount does not exceed a threshold value determined on the basis of strength evaluation of the blades. In a conventional general management method, the thickness-loss amount is measured at the time of a major inspection of the turbine, and parameters such as a thickness-loss rate are calculated from the thickness-loss amount measured at the previous inspection. On the basis of the relationship between the thickness-loss rate and the threshold value, the time for the next major inspection or the recommended time for blade replacement is estimated.
However, in the above-described conventional management method, it is required to periodically open the casing of the turbine and measure the thickness-loss amount of the rotor blades, which has a problem that a considerable number of processes and a considerable construction period are required. In recent years, thermal power generation is expected to be operated as adjustable thermal power such as low load operation and variable load operation, unlike the conventional baseload operation. Since the conventional prediction of thickness-loss amount due to SPE is on the premise of the baseload operation, it is difficult to apply the conventional prediction to the prediction of thickness-loss amount due to SPE when the turbine is operated as adjustable thermal power by dynamically changing the operating conditions.
In view of the above-described circumstances, embodiments of the present invention aim to provide a technique for accurately evaluating blade damage of a turbine that is operated under dynamically changing operating conditions.
In the accompanying drawings:
Hereinafter, embodiments of the present invention will be described by referring to the accompanying drawings.
The evaluation apparatus 10 includes: a first registration unit 201 configured to register design information D on both of a steam turbine 40 having a plurality of blades 34, which rotate a rotor 33 around its axis by being subjected to a jet of steam 48 (
The evaluation apparatus 10 further includes: a first discrimination processor 21 that discriminates first facility states Q1 of the steam turbine 40 at a plurality of past time points tm (m=1 to M−1) on the basis of the design information D and the maintenance information K; and a classification processor 26 that classifies each of the plurality of first facility states Q1 into one of classes Cn (n=1 to N).
The evaluation apparatus 10 further includes: a first determination processor 31 that determines first operating state values P1 of the steam turbine 40 on the basis of the detection data 16a acquired at the past time points tm (m=1 to M−1); a third registration unit 203 that registers first damage rates R1 of the blades 34 at the respective past time point tm; and a setting processor 25 that sets a characteristic function fn (n=1 to N) indicative of the relationship between the first operating state values P1 and the first damage rates R1 for each of the plurality of classes Cn (n=1 to N).
The evaluation apparatus 10 further includes: a second discrimination processor 22 that discriminates a second facility state Q2 of the steam turbine 40 at the current time point tM on the basis of the design information D and the maintenance information K; a second determination processor 32 that determines a second operating state value P2 of the steam turbine 40 on the basis of the detection data 16b acquired at the current time point tM; and an analyzer 27 that analyzes a second damage rate R2 at the current time point tM corresponding to the second operating state value P2 on the basis of the characteristic function fn that has been set in the class Cn corresponding to the second facility state Q2.
As shown in
The steam discharged by working on the steam turbine 40 is cooled by a steam condenser 38 in which cooling water 39 circulates, and then is condensed to become the condensed water (i.e., liquid medium) 47. The condensed water 47 is resupplied to the heat exchanger 55 of the boiler 35 via a water supply pipe 56. In the present embodiment, the blades 34 include both of: rotor blades that are radially provided along the radial direction of the rotor 33 and rotate along with the rotor 33; and stator blades that are disposed in the gap of the arrangement of the rotor blades and fixed to the casing 36. Note that the term “peripheral device of the steam turbine 40” refers to an arbitrary device or component that is connected to the steam turbine 40 mechanically or via the steam 48.
The steam 48 sent from the boiler 35 to the steam turbine 40 is mixed with a large amount of liberated solid particles that are generated by being separated from the oxide film (scale) generated mainly on the interior surface of the heat exchanger 55. Such solid particles collide with the blades 34, and consequently, the blades 34 undergoes erosion called SPE (Solid Particle Erosion).
When the blades 34 are eroded (i.e., worn) and damaged by the collision with the solid particles contained in the steam 48, the injection conditions (such as the angle and speed) of the steam 48 to be injected from the stator blades to the rotor blades change and the internal efficiency (i.e., performance) of the steam turbine 40 is reduced. As the erosion (i.e., wear) progresses further, damage such as breakage and bent of the blades 34 develops. Further, it is conceivable that cracks develop and grow in a blade 34 and this blade 34 is blown away so as to collide with another normal blade 34 and damage it.
Thus, in the thermal power plant 30, consideration is given in design, maintenance, and operation to prevent the introduction of solid particles of scale from the boiler 35 in operation to the steam turbine 40. However, it is not possible to completely prevent such mixture of the solid particles into the steam 48. Thus, it is necessary to accurately monitor and predict the progress of the damage in the blades 34 due to SPE (Solid Particle Erosion).
Returning to
The design information D to be registered in the first registration unit 201 is mainly composed of one or a plurality of the following: design conditions of the power plant 30; design conditions of the boiler 35 (heat exchanger 55); design conditions of pipes such as the main steam pipe 44 and the water supply pipe 56; design conditions of steam valves (not shown); and design conditions of the turbine 40.
The design conditions of the power plant 30 include, for example, generation capacity and combined cycle/conventional cycle. The design conditions of the boiler 35 include, for example, rated operating conditions (such as temperature and pressure), fuel, a model name, capacity, and tube material. The design conditions of pipes such as the main steam pipe 44 and the water supply pipe 56 include, for example, material, length, exposure temperature, and presence/absence of a turbine bypass flow path. The design conditions of the steam valves include, for example, presence/absence of a fine mesh, and presence/absence of auxiliary valves. The design conditions of the turbine 40 include, for example, steam conditions (such as temperature, flow rate, and pressure), rotor blade structure (such as number of blades, PCD, blade length, blade-nozzle distance, rotational circumferential speed), stator blade structure (such as number of blades and an outflow angle), and blade strength characteristics.
The maintenance information K to be registered in the second registration unit 202 is mainly composed of one or a plurality of the following: maintenance data of the boiler 35 (heat exchanger 55); maintenance data of pipes such as the main steam pipe 44 and the water supply pipe 56; and maintenance data of the turbine 40.
The maintenance data of the boiler 35 include, for example, tube replacement, a descaling method, descaling frequency, descaling timing, and a flushing method. The maintenance data of pipes such as the main steam pipe 44 and the water supply pipe 56 include, for example, a descaling method, descaling frequency, descaling timing, and a flushing method. The maintenance data of the turbine 40 include, for example, replacement history or maintenance history of the first-stage rotor blades and first-stage stator blades. All of these data are registered in the second registration unit 202 as the maintenance information K on the work history that contributes to reduction of solid particles to be mixed into the steam 48.
The steam turbine 40 and its peripheral devices are provided with many sensors 17, and status monitoring of the power plant 30 is performed on the basis of the acquired detection data 16. The large amount of detection data 16 include data reflecting inflow conditions and/or collision conditions of solid particles, and are time-sequentially acquired by the acquisition unit 15 so as to be stored. Specifically, the detection data 16 from the steam turbine 40 include opening degree of the bypass valve, opening degree of the steam valve, and steam conditions around the first-stage rotor blades and first-stage stator blades. The detection data 16 from the peripheral device, which causes abnormality as a result of damage of to the blades 34 on the upstream side of the steam turbine 40, are also useful.
Both of the first discrimination processor 21 and the second discrimination processor 22 have a common function of discriminating the facility state Q(Q1, Q2) of the steam turbine 40 on the basis of the design information D and the maintenance information K. The difference between both lies in that the first discrimination processor 21 discriminates the facility states of the steam turbine 40 (i.e., first facility states Q1) at the respective past time points tm (m=1 to M−1) whereas the second discrimination processor 22 discriminates the facility state of the steam turbine 40 (i.e., second facility state Q2) at the current time point tm.
This means that the device conditions change with various improvements and/or introduction of maintenance during the operation cycle between periodic inspections even in the case of the same steam turbine 40. Even between different steam turbines 40, they can be discriminated with each other and be adopted as information on the first facility states Q1.
The first damage rates R1 of the blades 34 at the respective past time points tm (m=1 to M−1) are registered in the third registration unit 203. The first damage rates R1 are obtained, for example, from the damage amount of the blades 34 actually measured in periodic major inspections for the steam turbine 40 or from simulation result combining various other information.
The first determination processor 31 determines each of the first operating state values P1 of the steam turbine 40 on the basis of the detection data 16a acquired at the past time points tm (m=1 to M−1). As a result, the combination of the first facility state Q1, the first operating state value P1, and the first damage rate R1 is established with the past time points tm (m=1 to M) included as the common term.
The classification processor 26 classifies each of the first facility states Q1 at the respective past time points tm (m=1 to M−1) into one of the plurality of classes Cn (n=1 to N) on the basis of commonality in damage characteristics of the blades 34. Thus, in the case of the first facility states Q1 classified into the common class Cn, the blades 34 wear out at the same damage rate R with respect to the same operating state value P.
The setting processor 25 acquires the first damage rate R1 related to the first operating state value P1 from the third registration unit 203. The setting processor 25 sets the characteristic function fn indicting the relationship between combinations of the first operating state value P1 and the first damage rate R1 in the set of the first facility states Q1 classified into the common class Cn. In this manner, the characteristic function fn (n=1 to N) is set for each of the plurality of classes Cn (n=1 to N).
The damage rate R of the blades 34 is expressed by the general expression of the characteristic function fn in which the operating state value P and the class Cn are used as independent variables, as Expression 1 below. Here, the facility state Q (Expression 3) is continuously expressed by the function g in which the design information D and the maintenance information K are used as independent variables, and the class Cn (Expression 2) is expressed as transformation of the facility state Q by using a step function in which constants are stepwisely given for respective sections.
R=f
n(P,Cn) Expression 1
C
n=[Q]n Expression 2
Q=g(D,K) Expression 3
The second determination processor 32 determines the second operating state value P2 of the steam turbine 40 on the basis of the detection data 16b obtained at the current time point tM. In other words, the second determination processor 32 determines the second operating state value P2 of the steam turbine 40 in operation on a real-time basis. Hence, the dynamically changing second operating state value P2 can be traced accurately under adjustable thermal power conditioning which does not premise base load operation. Further, the characteristic function fn is prepared for each class Cn, and thus, the determined value of the second damage rate R2 of the blades 34 accurately follows depending on the dynamically changing second operating state value P2.
The analyzer 27 analyzes the second damage rate R2 corresponding to the second operating state value P2 on the basis of the characteristic function fn that is set for the class Cn corresponding to the second facility state Q2. In a continuous operation period of the thermal power plant 30, the class Cn into which the second facility state Q2 should be classified can be regarded as invariant or variable. The class Cn (characteristic function fn) into which the second facility state Q2 should be classified can be maintained or changed depending on what is done (including what is not done) during the maintenance period between operation periods.
The calculator 45 calculates the damage amount U of the blade 34 on the basis of the second damage rate R2. Specifically, the damage amount U is calculated by time-integrating the second damage rate R2 obtained by the analyzer 27.
In addition, the evaluation apparatus 10 can simulate the second operating state value P2 on the basis of future operating plans so as to analyze and predict the second damage rate R2. On the basis of the predicted second damage rate R2, the damage amount U and the replacement time tc can be further estimated.
The evaluation apparatus 10 includes an update processor (not shown) that updates the design information D and the maintenance information K each time a maintenance period between operation periods arrives. When the operation period ends and the next operation period arrives after the maintenance period, the detection data 16b at the time point tM can be specified by the first determination processor 31 as the detection data 16a at the past time point tm (m=1 to M). At this time, the second determination processor 32 determines the detection data 16b at the current time point tM+1.
The processes of the blade damage evaluation method and the algorithm of the blade damage evaluation program are described on the basis of the flowchart of
In the first step S11, the design information D on the steam turbine 40 and its peripheral devices is registered and the maintenance information K on the work history contributing to reduction of solid particles is registered.
In the next step S12, the detection data 16 of the sensors 17 are acquired and stored.
On the basis of the design information D and the maintenance information K, the first facility states Q1 of the steam turbine 40 at the plurality of past time points tm (m=1 to M−1) are discriminated in the step S13, and each first facility state Q1 is classified into one of the classes Cn (n=1 to N) in the step S14.
In the next step S15, on the basis of the detection data 16a acquired at the past time points tm, the first operating state values P1 of the steam turbine 40 are determined.
In the next step S16, the first damage rates R1 of the blades 34 at the past time points tm are acquired.
In the next step S17, the characteristic function fn (n=1 to N) indicative of the relationship between the first operating state value P1 and the first damage rate R1 is set for each of the plurality of classes Cn.
In the next step S18, on the basis of the design information D and the maintenance information K, the second facility state Q2 of the steam turbine 40 at the current time point tM is discriminated.
In the next step S19, on the basis of the detection data 16b acquired at the current time point tM, the second operating state value P2 of the steam turbine 40 is determined.
In the next step S20, on the basis of the characteristic function fn having been set for the class Cn corresponding to the second facility state Q2 (
In the next step S21, on the basis of this second damage rate R2, the damage amount U of the blades 34 at the current time point tM and the replacement time tc of the blades 34 are evaluated.
The processing flow from the steps S18 to S21 is repeated until the operation period of the current time point tm is completed (i.e., until the determination result of the step S22 becomes YES).
If the next operation period resumes at the current time point tM after the maintenance period (YES in the step S23), the processing flow from the steps S11 to S22 is repeated.
If the operation period is not resumed, the processing is terminated (NO in the step S23).
According to at least one embodiment of the blade damage evaluation apparatus described above, the interrelationship between the design information, the maintenance information, the damage rate, and the sensor detection data at the past time points is clarified, the damage rate of the blades is analyzed on the basis of the sensor detection data at the current time point, the design information, and the maintenance information, and thus, it can provide technique for accurately evaluating the blade damage in a turbine to be operated under dynamically changing operating conditions. Although a description is given for the case of the steam turbine in the above-described embodiments, the present invention can be applied to gas turbines and other types of turbines.
While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.
The above-described blade damage evaluation apparatus includes: a controller in which one or more processors such as a dedicated chip, an FPGA (Field Programmable Gate Array), a GPU (Graphics Processing Unit), and a CPU (Central Processing Unit) are highly integrated; a memory such as a ROM (Read Only Memory) and a RAM (Random Access Memory); an external storage device such as a HDD (Hard Disk Drive) and an SSD (Solid State Drive); a display; an input device such as a mouse and a keyboard; and a communication interface. The blade damage evaluation apparatus can be realized by general computer-based hardware configuration. Thus, components of the blade damage evaluation apparatus can be achieved by processors of a computer and can be operated by a blade damage evaluation program.
The blade damage evaluation program may be provided in the form of being pre-embedded in a ROM or similar device. Additionally or alternatively, the blade damage evaluation program can be provided as an installable or executable file stored in a computer-readable storage medium such as a CD-ROM, a CD-R, a memory card, a DVD, and a flexible disk (FD).
Moreover, the blade damage evaluation program according to the present embodiment may be stored on a computer connected to a network such as the Internet so as to be provided by being downloaded via the network. Furthermore, the blade damage evaluation apparatus can also be configured by interconnecting separate modules, which independently achieve the respective functions of the components, via a network or dedicated lines and combining these modules (such that these modules work in combination).
Although the respective functions of the blade damage evaluation apparatus 10 are mainly achieved by the processors (21, 22, 25, 26, 31, 32) and similar components (27, 45, 46) in the above-described embodiments, these processors and similar components may be configured as one integrated processor or one integrated processing circuit.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2021-130513 | Aug 2021 | JP | national |
