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Vibration analysis and parametric identification of low-pressure steam turbine blade with crack using ANN

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Abstract

The structural integrity of steam turbine blades is crucial for successful operation and power generation. These blades are subjected to various types of excitations which include harmonic blade passing loads and fatigue loads that generate alternating stresses. In particular, fatigue loads result in microcracks at the root regions of the blades. The crack length varies with the operating speed, and if it is undetected in the early stages of operation, it may result in a catastrophic failure. The present work focuses on free and forced vibration analysis of a large pre-twisted aerofoil cantilever blade of the last-stage low-pressure (LP) turbine configuration. Initially, the Campbell diagram is obtained to identify critical speeds. Further, an interactive graphic user interface (GUI) is developed for free and forced vibration analysis of the twisted blade based on the conventional coupled bending–twisting theory. The user of the GUI can control various input parameters including root flexibility, pre-twist angle, and root-level damage factor, and study their variations on the natural frequencies and dynamic response. An artificial neural network (ANN) model based on a multilayer perceptron is employed to identify the output parameters using the measured modal data.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Machine Design and Analysis, Department of Mechanical Engineering, National Institute of Technology, Rourkela, Odisha, 769008, India

    Keshav Ramesh Shetkar & J. Srinivas

Authors
  1. Keshav Ramesh Shetkar
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  2. J. Srinivas
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Correspondence to Keshav Ramesh Shetkar.

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Technical Editor: Jarir Mahfoud.

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Shetkar, K.R., Srinivas, J. Vibration analysis and parametric identification of low-pressure steam turbine blade with crack using ANN. J Braz. Soc. Mech. Sci. Eng. 45, 314 (2023). https://doi.org/10.1007/s40430-023-04238-2

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  • DOI: https://doi.org/10.1007/s40430-023-04238-2

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