Abstract:It is known that fatigue cracks are one of the most important problems of the mechanical components, since their propagation can cause severe loss, both personal and economic. So, it is essential to know deeply the behavior of the cracked element to have tools that allow predicting the breakage before it happens. The shafts are elements that are specially affected by the described problem, because they are subjected to alternative compression and tension stresses. This work presents, firstly, an analytical exp… Show more
“…Different methods and tools have been applied to address this problem. Of all of them, neural networks (Mohammed et al 2014;Muñoz-Abella et al 2020;Bilotta et al 2023) currently occupy a prominent place in comparison with conventional optimisation techniques (Suh et al 2000;Shekar 2004;Rubio 2009), or those based on constructive algorithms based on vibration problems (Fernández-Sáez et al 2017;Rubio et al 2018) or on genetic algorithms or other optimization methods (Maity and Tripathy 2005;Muñoz-Abella et al 2018;Ramezani and Bahar 2021;Muñoz-Abella et al 2022a, Gordan et al 2017, Jahangiri et al 2016, Marques et al 2018. However, there are some methods whose use is currently gaining more strength with the development of AI.…”
This article aims to identify the presence of cracks in slender rotating beams (Euler Bernoulli) from the dynamic behaviour of cracked beams operating at low rotational speeds. For this purpose, the behavioural model of the cracked rotating beam developed by the authors in previous works is shown. The results of the mathematical model developed (natural frequencies) feed a novel meta-heuristic optimisation algorithm based on the survival tactics of rabbits against their predators: Artificial Rabbit Optimization (ARO). The application of this algorithm to the first two natural frequencies of vibration obtained with the analytical model and contrasted in previous works gives rise to the identification of the characteristic parameters of the crack contained in the beams. The estimation of the parameters: position along the beam and crack depth, show a high similarity with the initial data, which allows validating the application of the optimisation algorithm to the identification of cracks in this type of component as a first approach to a health monitoring method for more complex rotating cantilever beam structures.
“…Different methods and tools have been applied to address this problem. Of all of them, neural networks (Mohammed et al 2014;Muñoz-Abella et al 2020;Bilotta et al 2023) currently occupy a prominent place in comparison with conventional optimisation techniques (Suh et al 2000;Shekar 2004;Rubio 2009), or those based on constructive algorithms based on vibration problems (Fernández-Sáez et al 2017;Rubio et al 2018) or on genetic algorithms or other optimization methods (Maity and Tripathy 2005;Muñoz-Abella et al 2018;Ramezani and Bahar 2021;Muñoz-Abella et al 2022a, Gordan et al 2017, Jahangiri et al 2016, Marques et al 2018. However, there are some methods whose use is currently gaining more strength with the development of AI.…”
This article aims to identify the presence of cracks in slender rotating beams (Euler Bernoulli) from the dynamic behaviour of cracked beams operating at low rotational speeds. For this purpose, the behavioural model of the cracked rotating beam developed by the authors in previous works is shown. The results of the mathematical model developed (natural frequencies) feed a novel meta-heuristic optimisation algorithm based on the survival tactics of rabbits against their predators: Artificial Rabbit Optimization (ARO). The application of this algorithm to the first two natural frequencies of vibration obtained with the analytical model and contrasted in previous works gives rise to the identification of the characteristic parameters of the crack contained in the beams. The estimation of the parameters: position along the beam and crack depth, show a high similarity with the initial data, which allows validating the application of the optimisation algorithm to the identification of cracks in this type of component as a first approach to a health monitoring method for more complex rotating cantilever beam structures.
“…Then, in Ref. [44] they introduced an analytical expression to evaluate the first four bending natural frequencies of a nonrotating pinned-pinned Euler-Bernoulli shaft. And as an inverse problem, they proposed a genetic algorithm technique to identify elliptical crack using these known natural frequencies.…”
Purpose
In this paper, dynamic behavior of a rotor system with an elliptical breathing crack that simulates the real shape of the crack front is investigated.
Methods
A finite element model of the cracked rotor system is developed. The crack breathing mechanism is modelled based on an improved breathing model which considers the inclination of the neutral axis of the cracked element cross-section during shaft rotation. Harmonic balance method is used to solve the equations of motion of the rotor system for steady-state response characteristics. The effect of some parameters such as crack depth, crack shape factor and the spinning speed is investigated.
Results and conclusions
The results show that the unique whirl orbits behavior during passage through the subcritical speeds serve as a key indicator of crack presence in the shaft. The effects of the crack front curvature and the breathing model are revealed. The value of shape factor affects the whirl orbit characteristics such as size of the inner or outer loops and the amount by which the orbits rotate while crossing the subcritical speeds. The presented model considering the real crack front shape may contribute towards improved modelling of cracked rotors and better interpretation of measured vibration response.
“…On crack modeling, most authors model the cracked beam as two beams connected by one or more springs, located in the section that contains the crack, and whose stiffness represents the increase in local flexibility as a result of its presence. In most of the works, the stiffness of the spring is obtained from the application of Fracture Mechanics concepts such as the Stress Intensity Factor (SIF) or the integral J, such as in [27,28]. When addressing the problem of studying the behavior of the blade with a defect, the appearance of a crack implies the modification of the movement equations, requiring the introduction of terms that take into account the effect of damage.…”
In this study, two closed-form solutions for determining the first two natural frequencies of the flapwise bending vibration of a cracked Euler–Bernoulli beam at low rotational speed have been developed. To solve the governing differential equations of motion, the Frobenius method of solution in power series has been used. The crack has been modeled using two undamaged parts of the beam connected by a rotational spring. From the previous results, two novel polynomial expressions have been developed to obtain the first two natural frequencies as a function of angular velocity, slenderness ratio, cube radius and crack characteristics (depth and location). These expressions have been formulated using multiple regression techniques. To the knowledge of the authors, there is no similar expressions in the literature, which calculate, in a simple way, the first two natural frequencies based on beam features and crack parameters, without the need to know or solve the differential equations of motion governing the beam. In summary, the derived natural frequency expressions provide an extremely simple, practical, and accurate instrument for studying the dynamic behavior of rotating cracked Euler–Bernoulli beams at low angular speed, especially useful, in the future, to establish small-scale wind turbines’ maintenance planes.
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