Degradation of the Cast Elements of Steam Turbines of Thermal Power Plants Made of 20KhMFL Steel in the Course of Long-Term Operation

2005 ◽  
Vol 41 (3) ◽  
pp. 423-426 ◽  
Author(s):  
O. I. Balyts'kyi ◽  
I. V. Ripei ◽  
Kh. A. Protsakh
Keyword(s):  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Steam Turbines ◽  
Term Operation

Studying the Metal from Drums at Thermal Power Plants after Long-Term Operation Using Subsize Charpy Specimens

2021 ◽  
Vol 68 (8) ◽  
pp. 640-646
Author(s):  
A. G. Rudenko ◽  
V. N. Voyevodin ◽  
S. V. Gozhenko ◽  
P. A. Mischenko
Keyword(s):  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Term Operation

Reliability of steam pipelines of thermal power plants in the course of long-term operation

2006 ◽  
Vol 42 (4) ◽  
pp. 461-465 ◽  
Author(s):  
O. I. Balyts’kyi ◽  
I. V. Ripei ◽  
Kh. A. Protsakh
Keyword(s):  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Term Operation

Influence of the Long-Term Operation of 12Kh1МF Steel of the Bends of Main Steam Pipelines of Thermal Power Plants on Its Mechanical Properties

2018 ◽  
Vol 53 (4) ◽  
pp. 460-467 ◽  
Author(s):  
О. Z. Student ◽  
H. V. Krechkovs’ka ◽  
T. E. Palashchuk ◽  
Ya. М. Hladkyi
Keyword(s):  
Mechanical Properties ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Term Operation ◽  
Main Steam

Steam turbines of the T-50/60-8.8, K-63-8.8, and Tp-100/110-8.8 types destined for modernization of thermal power plants with K-50-90 and K-100-90 turbines

2012 ◽  
Vol 59 (12) ◽  
pp. 907-912 ◽  
Author(s):  
A. Ye. Valamin ◽  
A. Yu. Kultyshev ◽  
Yu. A. Sakhnin ◽  
M. V. Shekhter ◽  
M. Yu. Stepanov
Keyword(s):  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Steam Turbines

Findings on Creep-Fatigue Damage in Pressure Parts of Long-Term Service-Exposed Thermal Power Plants

1985 ◽  
Vol 107 (3) ◽  
pp. 260-270 ◽  
Author(s):  
F. Masuyama ◽  
K. Setoguchi ◽  
H. Haneda ◽  
F. Nanjo
Keyword(s):  
Fatigue Damage ◽  
Power Plants ◽  
Thermal Power ◽  
Field Experiences ◽  
Creep Damage ◽  
Thermal Power Plants ◽  
Damage Analysis ◽  
Creep Fatigue ◽  
Fatigue Damage Analysis

The increase of long-term service exposure to thermal power plants, the tendency toward intermediate and cyclic operation to meet the change in electric power demand and supply situation, and the requirement to develop higher-temperature and higher-pressure plants have led to increasing attention towards the reliability improvement. This paper presents findings from field experiences of cracking or failure and two types of damage analyses—(1) creep-fatigue damage analysis based on the life fraction rule and (2) metallurgical damage analysis—of boiler pressure parts that have been exposed to long-term elevated temperature service. The field experiences are (1) cracking or failure of thick-walled Type 316 stainless steel pressure parts in the main steam line of an ultra-supercritical thermal power plant and (2) dissimilar metal weld joints for boiler tubing. The creep-fatigue damage analysis of these pressure parts showed a reasonable correspondence with the field experience. According to the creep-fatigue damage analysis and the metallurgical damage analysis, most of damage was restrained creep mode phenomenon without deformation. The creep damage was composed of metallurgical damage and mechanical damage such as microvoids and structural defects. One method of simulating field experienced creep damage was proposed and performed. As a result, the process of creep voids being generated and growing into cracks without deformation was successfully observed. Also a review of the current status of nondestructive detecting methods of creep damage suggests that detecting the creep voids metallurgically is more practical at the present time than doing so analyzing the changes in physical properties of the material. It is also suggested that, in the metallurgical approach, detecting the creep voids and cracks by replica method and anlayzing precipitates for evaluation of material deterioration by precipitate extraction method will make it possible to successfully address the problem of plant equipment creep damage evaluation and life prediction.

Detection of Machinery Failure Signs From Big Time-Series Data Obtained by Flow Simulation of Intermediate-Pressure Steam Turbines

2021 ◽  
Author(s):  
Kazuhiko Komatsu ◽  
Hironori Miyazawa ◽  
Cheng Yiran ◽  
Masayuki Sato ◽  
Takashi Furusawa ◽  
...  
Keyword(s):  
Time Series ◽  
Power Plants ◽  
Time Series Data ◽  
Thermal Power ◽  
Turbine Blades ◽  
Series Data ◽  
Thermal Power Plants ◽  
Steam Turbines ◽  
Pressure Steam ◽  
The Status

Abstract The periodic maintenance, repair, and overhaul (MRO) of turbine blades in thermal power plants are essential to maintain a stable power supply. During MRO, older and less-efficient power plants are put into operation, which results in wastage of additional fuels. Such a situation forces thermal power plants to work under off-design conditions. Moreover, such an operation accelerates blade deterioration, which may lead to sudden failure. Therefore, a method for avoiding unexpected failures needs to be developed. To detect the signs of machinery failures, the analysis of time-series data is required. However, data for various blade conditions must be collected from actual operating steam turbines. Further, obtaining abnormal or failure data is difficult. Thus, this paper proposes a classification approach to analyze big time-series data alternatively collected from numerical results. The time-series data from various normal and abnormal cases of actual intermediate-pressure steam-turbine operation were obtained through numerical simulation. Thereafter, useful features were extracted and classified using K-means clustering to judge whether the turbine is operating normally or abnormally. The experimental results indicate that the status of the blade can be appropriately classified. By checking data from real turbine blades using our classification results, the status of these blades can be estimated. Thus, this approach can help decide on the appropriate timing for MRO.

Detection of Machinery Failure Signs From Big Time-Series Data Obtained by Flow Simulation of Intermediate-Pressure Steam Turbines

2021 ◽  
Author(s):  
Kazuhiko Komatsu ◽  
Hironori Miyazawa ◽  
Cheng Yiran ◽  
Masayuki Sato ◽  
Takashi Furusawa ◽  
...  
Keyword(s):  
Time Series ◽  
Power Plants ◽  
Time Series Data ◽  
Thermal Power ◽  
Turbine Blades ◽  
Series Data ◽  
Thermal Power Plants ◽  
Steam Turbines ◽  
Pressure Steam ◽  
The Status

Abstract The periodic maintenance, repair, and overhaul (MRO) of turbine blades in thermal power plants are essential to maintain a stable power supply. During MRO, older and less-efficient power plants are put into operation, which results in wastage of additional fuels. Such a situation forces thermal power plants to work under off-design conditions. Moreover, such an operation accelerates blade deterioration, which may lead to sudden failure. Therefore, a method for avoiding unexpected failures needs to be developed. To detect the signs of machinery failures, the analysis of time-series data is required. However, data for various blade conditions must be collected from actual operating steam turbines. Further, obtaining abnormal or failure data is difficult. Thus, this paper proposes a classification approach to analyze big time-series data alternatively collected from numerical results. The time-series data from various normal and abnormal cases of actual intermediate-pressure steam-turbine operation were obtained through numerical simulation. Thereafter, useful features were extracted and classified using K-means clustering to judge whether the turbine is operating normally or abnormally. The experimental results indicate that the status of the blade can be appropriately classified. By checking data from real turbine blades using our classification results, the status of these blades can be estimated. Thus, this approach can help decide on the appropriate timing for MRO.

scholarly journals Recent Life Assessment Technology for Existing Steam Turbines

2005 ◽  
Author(s):  
K. Saito ◽  
A. Sakuma ◽  
M. Fukuda
Keyword(s):  
High Temperature ◽  
Power Plants ◽  
High Reliability ◽  
Thermal Power ◽  
Life Assessment ◽  
Life Extension ◽  
Steam Turbines ◽  
Term Operation ◽  
Assessment Technology ◽  
Technical Features

A large and growing portion of electricity is produced by aging thermal power plants. Although excellent, high quality materials such as CrMoV steel and 12% Cr steel, etc. are used for the steam turbines, various forms of metallurgical degradation, due to creep and fatigue, etc. affect the parts and components during long-term operation at high temperature. Extending the life of steam turbines and ensuring high reliability requires life assessment technology, scheduled repairing, conversion, modification and upgrading of components in order to provide a stable power supply. As the high temperature parts and components of aged steam turbines are mainly metallurgically damaged by creep, fatigue and the interaction of both, life assessment combined with analytical and nondestructive methods is essential for realizing strategic plant life extension. We have developed a life assessment technology that takes material degradation into consideration, and have applied the procedure to more than 650 units and 2500 components since 1983. A rotor bore replication device was developed in 1989 for the purpose of nondestructive observation of creep voids and supporting the validity of life prediction results. This paper describes the technical features and applied experience of recent life assessment technology for existing high temperature steam turbines.

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