This invention relates to a system and method of evaluating a turbine component and, more specifically, to a system and method of determining a total profile efficiency loss for a steam turbine component due to its surface conditions.
A steam turbine is often used to rotate a rotor in an electrical power generator. In particular, steam obtained by operation of a boiler may be directed along a steam flow path by a nozzle against a plurality of turbine blades, or buckets, connected to the rotor. The rotor is rotated within a stator by the steam flowing against the buckets to generate electrical power.
Abrasive materials are often carried by the steam as it flows through the turbine. These abrasive materials cause erosion of turbine components such as sealing strips, buckets and nozzles which are located along the steam flow path. Erosion of some of these turbine components result in excessive clearances being formed, often leading to increased steam leakage in the turbine. In addition to abrasive materials causing erosion of turbine components, the steam often carries contaminates which may deposit and collect on turbine components located along the steam flow path. These deposits of contaminates increase the surface roughness of the turbine components and may actually disturb the desired flow pattern of the steam.
The erosion of some turbine components and the collection of deposits on other turbine components are merely two examples of the many types of deterioration that may develop on the surfaces of turbine components after extended (e.g., ten years) operation. The operational efficiency losses of the steam turbine increase as the surface conditions of the turbine components deteriorate. In particular, the heat needed to enable the electrical generator to produce a given amount of electricity increases as the operational efficiency losses of the steam turbine increase.
In order to combat operational efficiency losses of the turbine, a service technician conducts a steam path audit. During the steam path audit, the service technician observes the surface conditions of turbine components located along the steam flow path for erosion, contaminate deposits and/or other signs of deterioration. This audit may be periodically scheduled for, for example, every five years of operation of the steam turbine.
A service technician typically determines a total profile efficiency loss for a turbine component in the steam flow path as a result of the judgments he/she reaches during the steam path audit. A determination on whether to repair or replace one or more of the turbine components can be made based on the judgments. However, the judgments reached are highly subjective and depend on the skill and experience level of the technician. The judgments may thus vary widely from technician to technician. Moreover, the judgment is “broad-brushed” in that a total profile efficiency loss for the entire turbine component is determined based on an evaluation of a single (local) surface location of that turbine component and a loss efficiency curve for that single surface location.
There thus remains a need to calculate the total profile efficiency loss of turbine components located along a steam path in a more accurate and repeatable fashion. That is, it would be beneficial to minimize the widely variable conclusions from different technicians evaluating the same turbine component and to increase accuracy of the total profile efficiency loss calculation by considering multiple surface conditions at different respective surface locations of the same turbine component. Exemplary embodiments of the present invention resolve these and other needs.
In one exemplary aspect of the invention, a method of evaluating a turbine component comprises obtaining data relating to respective surface conditions at a plurality of different surface locations of the turbine component and calculating the total profile efficiency loss for the turbine component based on the data relating to the respective surface conditions at the different surface locations. Calculating the total profile efficiency of the turbine component may include calculating the local profile efficiency loss percentage for each of the surface conditions at the different surface locations and calculating an average of the local profile efficiency loss percentages, each of the local efficiency loss percentages being weighted by respective predetermined weight factors. Calculating the total profile efficiency of the turbine component may include calculating respective local profile efficiency loss percentages for each of the surface conditions at a plurality of sub-areas of at least one of the different surface locations and calculating an average of the local profile efficiency loss percentages, each of the local efficiency loss percentages being weighted by respective predetermined weight factors. Calculating the total profile efficiency loss for the turbine component may include calculating a sand grain roughness number (Ks) for each surface condition at the different surface locations. Calculating the total profile efficiency loss for the turbine component may include calculating a sand grain roughness number (Ks) for each surface condition at a plurality of sub-areas of at least one of the different surface locations. Each of the local profile efficiency loss percentages for each of the surface conditions at the respective surface locations may be calculated based on a sand grain roughness number (Ks) determined for that surface condition. Each of the local profile efficiency loss percentages for each of the surface conditions at the respective sub-areas may be calculated based on a sand grain roughness number (Ks) determined for that surface condition. The obtained data relating to surface conditions at each of the different surface locations may include data relating to a condition type and a severity of condition of each of the surface conditions, and calculating the total profile efficiency loss for the turbine component may include determining a surface roughness factor for each surface condition based on the condition type and the severity of the condition obtained for that surface condition. The obtained data may include data relating to a condition type and a severity of condition for each of the surface conditions at the sub-areas, and calculating the total profile efficiency loss for the turbine component may include determining a surface roughness factor for each of the surface conditions at each of the sub-areas based on the condition type and the severity of the condition obtained for that surface condition. The obtained data relating to surface conditions of each of the different surface locations may be one or more of the following types of data: surface roughness, surface condition type and severity of surface condition. The turbine component may be a nozzle or a bucket and each of the surface locations of the turbine component may be one of following: admission suction surface, admission pressure surface, discharge suction surface and discharge pressure surface.
In another exemplary aspect of the present invention, a computerized system for evaluating a turbine component comprises (i) a data input that receives data relating to respective surface conditions at a plurality of different surface locations of the turbine component and (ii) a processor that calculates the total profile efficiency loss for the turbine component based on the data relating to the respective surface conditions at the different surface locations. The processor may calculate the total profile efficiency of the turbine component by at least calculating the local profile efficiency loss percentage for each of the surface conditions at the different surface locations and calculating an average of the local profile efficiency loss percentages, each of the local efficiency loss percentages being weighted by respective predetermined weight factors. The processor may calculate the total profile efficiency of the turbine component by at least calculating respective local profile efficiency loss percentages for each of the surface conditions at a plurality of sub-areas of at least one of the different surface locations and calculating an average of the local profile efficiency loss percentages, each of the local efficiency loss percentages being weighted by respective predetermined weight factors. The processor may calculate the total profile efficiency loss for the turbine component by at least calculating a sand grain roughness number (Ks) for each surface condition at the different surface locations. The processor may calculate the total profile efficiency loss for the turbine component by at least calculating a sand grain roughness number (Ks) for each surface condition at a plurality of sub-areas of at least one of the different surface locations. Each of the local profile efficiency loss percentages for each of the respective surface conditions at the surface locations may be calculated by the processor based on a sand grain roughness number (Ks) determined for that surface condition. Each of the local profile efficiency loss percentages for each of the surface conditions at the respective sub-areas may calculated by the processor based on a sand grain roughness number (Ks) determined for that surface condition. The received data relating to surface conditions at each of the different surface locations may include data relating to a condition type and a severity of condition of each of the surface conditions and the processor may calculate the total profile efficiency loss for the turbine component by at least determining a surface roughness factor for each surface condition based on the condition type and the severity of the condition obtained for that surface condition. The received data may include obtaining data relating to a condition type and a severity of condition for each of the surface conditions at the sub-areas and the processor may calculate the total profile efficiency loss for the turbine component by determining a surface roughness factor for each of the surface conditions at each of the sub-areas based on the condition type and the severity of the condition obtained for that surface condition. The received data relating to surface conditions at each of the different surface locations may be one or more of the following types of data: surface roughness, surface condition type and severity of surface condition. The turbine component may be a nozzle or a bucket and each of the surface locations of the turbine component may be one of following: admission suction surface, admission pressure surface, discharge suction surface and discharge pressure surface.
Referring to
Each of the respective surface locations has an associated predetermined weighting factor which relates that surface location's relative contribution to the total profile efficiency loss of the entire turbine component. As illustrated in
Steam generated by a boiler (not shown) of the steam turbine is directed by nozzle 17 against buckets 20 to rotate rotor 24 about axis 22. However, the surface conditions of turbine components, such as nozzle 17 and buckets 20, in the steam flow path deteriorate as a result of, for example, abrasive materials and contaminates carried by the steam. A total profile efficiency loss of the turbine component is produced as a result of its deteriorated surface conditions. The type(s) of the deteriorated surface condition(s) of a particular surface location (ASS, APS, DSS or DPS) of the turbine component or sub-areas of a particular surface location may be, for example, one of the following: new machining marks, coatings, deposits, solid particle erosions, grit blast cleaning, small particle impingement, foreign object damage, water erosion and corrosion pitting.
Device 32 wirelessly transmits the data to computer 30. Computer 30 includes a processor 34 for processing the input data such as calculating the local profile efficiency loss percentage for each of the surface conditions detected on the turbine component and the total profile efficiency loss of the turbine component based on the local profile efficiency loss percentages as will be discussed in detail below. Alternatively, device 32 can transmit data to computer 30 via a hard wire connection between device 32 and computer 30, or the technician may record the surface condition and later manually enter data into computer 30 for processing by processor 34 or transfer data via a computer storage medium.
Processor 34 selects a surface roughness factor (K) based on the received surface condition type and the severity of that condition type and the data matrix (step 42 of
One or more of the surface locations ASS, APS, DSS (including THT) and DPS may have a plurality of different surface conditions. For example, a first sub-area ASS1 of the ASS of a turbine component may have a surface roughness of 68 μ-in whereas a second sub-area ASS2 of the ASS surface location may have a surface roughness of 65 μ-in. Alternatively, a first sub-area ASS1 of the ASS surface location may have a “light” amount of deposit build-up whereas a second sub-area ASS2 of the same ASS of the turbine component may have a “very light” amount of deposit build-up. Data originating from technician input may therefore include identification of a number of sub-areas (e.g., ASS1 and ASS2) and measured or estimated % area of that surface location covered by the sub-area (see col. 55 of
After a surface roughness factor (K) is determined, processor 34 calculates an equivalent sand grain roughness factor (Ks) for each identified surface condition based on the surface roughness factor (K) and the measured surface roughness at that location (step 43 of
Processor 34 determines a local profile efficiency loss for each of the surface locations (or sub-areas of the surface locations) based on the sand grain roughness factor (Ks) earlier calculated for that surface location (or sub-area of the surface location) and the appropriate data curve (step 44 of
The local profile efficiency loss percentage for each surface condition of a particular surface location or sub-area (e.g., ASS1 and ASS2) of the surface location (e.g., ASS) is determined and stored by computer 30 as illustrated in column 58. Data in columns 51-55 of
Processor 34 then calculates the average of all of the local profile efficiency losses of the surface locations or their respective sub-areas of the turbine component to determine the total profile efficiency loss for the entire turbine component (step 45 of
As illustrated in
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.