Case Study Application of Cold Peening in Combination with Thermal Stress Relieving as Effective Method for Straightening Large Turbine Rotor

Burhani, Ahmad; Rozaq, Fatchur; Supriyanto, Eko

doi:10.1109/icpects49113.2020.9336994

Cited by 3 publications

(5 citation statements)

References 4 publications

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“…To ensure uninterrupted operation and prevent damage of the rotor shaft components, it is necessary to balance it [36][37][38][39]. In some cases, it may be necessary to replace the rotor-shaft components [40][41][42][43][44][45][46][47].…”

Section: Literature Survey: State-of-the-artmentioning

confidence: 99%

Hydrogen Cooling of Turbo Aggregates and the Problem of Rotor Shafts Materials Degradation Evaluation

Balitskii,

Syrotyuk,

Havrilyuk

et al. 2023

Energies

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Changes in the properties of 38KhN3MFA steel, from which the rotor shaft is made, were investigated by comparing the hardness of the shaft surface and hydrogen concentration in the chips and analyzing changes in the morphology of the chips under the influence of various factors. The microstructures obtained from the surface of the rotor shaft samples are presented, and histograms reflecting the parameters of the structural components are constructed. An abbreviated diagram of the “life cycle” of the turbine rotor shaft is given. It was found that, during long-term operation (up to 250 thousand hours), the hardness of the rotor shaft surface decreases from 290 HB to 250 HB. It was recorded that, in the microstructure of the shaft during 250 thousand hours of operation, the amount of cementite decreased from 87% to 62%, and the proportion of free ferrite increased from 5% to 20%. The average values of ferrite microhardness decreased from 1.9 GPa to 1.5 GPa. An increase in the content of alloying elements in carbides was recorded: Cr and V—by 1.15–1.6 times; and Mo—by 2.2–2.8 times. With the help of the developed program (using computer vision methods), changes in their microrelief were detected to study photos of chips.

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Section: Literature Survey: State-of-the-artmentioning

confidence: 99%

Hydrogen Cooling of Turbo Aggregates and the Problem of Rotor Shafts Materials Degradation Evaluation

Balitskii,

Syrotyuk,

Havrilyuk

et al. 2023

Energies

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“…Various types of straightening methods (such as cold mechanical straightening, hammer peening, hot spotting, etc.) have been developed to restore the balance of the rotor [4,5]. The straightening method is selected considering the size of the rotor, the degree of the deformation, the location of the deformation, and so on.…”

Section: Introductionmentioning

confidence: 99%

“…The concave side of the maximum deflection location is then impacted using a round-shaped metal hammer. While this method is known to be effective for rotors with diameters of 100 mm or less, this method has also been used for larger rotors with deflection of less than 0.5 mm [5,6]. The hot spotting or heating and cooling methods are employed to correct rotors with larger diameters of 100 mm or more or large deformations of 0.5 mm or more [6,7].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Hammer Peening Process for Gas Turbine Rotor Straightening

Kim¹,

Kim

2022

Machines

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Some rotors are bent permanently due to high operating temperatures, repeated transition periods, and so on. Rotors with large deformations often require straightening processes. The goal of this study is to develop a method to determine the optimal locations and strengths of hammer peening for straightening gas turbine rotors. A set of parametric hammer peening simulations were performed for various dimensions of straight rotors and peening locations. The deformed geometries of the rotor from the parametric simulations were presented as curvature vectors. These curvature vectors were fitted using an empirical function. For a given initial geometry of the rotor and hammer peening plans, the post-peening geometry of the rotor was predicted by superimposing the initial curvature and newly induced curvature. An optimization statement was defined to determine a set of hammer peening locations and strengths. Constraints were imposed to exclude areas where hammer peening could not be performed such as locations for bearings. The proposed method provides an optimal hammer peening plan for the given runout data. The proposed method was validated against a series of hammer peening test results for a simple shaft. The developed method can be applied to other types of rotor straightening methods such as hot spotting.

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“…Various researches have proposed genetic algorithms, differential evolution technique and different artificial neural network technique to improve the performance of steam turbine [4].…”

Section: Introductionmentioning

confidence: 99%

“…In turbine algorithm, controller implementation is carried out using the neural network. In many industrial application, neural network is used to control the stress in steam turbines [4]. Dominiczak et al [5] proposed a mathematical model -Nonlinear Auto-Regressive neural networks with exogenous inputs (NARX) for maintaining the stress of steam turbines.…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement in Steam Turbine in Thermal Power Plants Using Artificial Neural Network

Abdullah¹,

Hamoodi²,

Mohammed³

2021

JESA

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Artificial intelligence has proven its effectiveness in many industrial fields to enhance the existing functionality. Artificial intelligence and machine learning algorithms integrated with turbines can be useful in controlling important variables such as pressure, temperature, speed, and humidity. In this research, the Simulink library from MATLAB is used to build an artificial neural network. The NARMA L2 neural controller is used to generate data and for training networks. To obtain the result and compare it with the real-time power plant, data is collected. The input variables provided to the neural network have a large effect on the hidden layer and the output of the neural network. The circuit board used in this research has a DC bridge, a transformer and voltage regulators. The result comparison shows that the integration of artificial neural networks and electric circuits shows enhanced performance with high accuracy of prediction. It was observed that the ANN integration system and electric circuit design have a result deviation of less than 1%. This shows that the integration of ANN improves the performance of turbines.

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Case Study Application of Cold Peening in Combination with Thermal Stress Relieving as Effective Method for Straightening Large Turbine Rotor

Cited by 3 publications

References 4 publications

Hydrogen Cooling of Turbo Aggregates and the Problem of Rotor Shafts Materials Degradation Evaluation

Hydrogen Cooling of Turbo Aggregates and the Problem of Rotor Shafts Materials Degradation Evaluation

Optimization of Hammer Peening Process for Gas Turbine Rotor Straightening

Performance Improvement in Steam Turbine in Thermal Power Plants Using Artificial Neural Network

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