Modal testing and evaluation of cracks on cantilever beam using mode shape curvatures and natural frequencies

Chinka, Siva Sankara Babu; Putti, Srinivasa Rao; Adavi, Bala Krishna

doi:10.1016/j.istruc.2021.03.049

Cited by 48 publications

(19 citation statements)

References 51 publications

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“…The main focus of this study is demonstrating whether the proposed method can be used as an efficient health monitoring system for wind turbine components such as the blades and the tower. More detailed information on the mathematical background and the derivation of the technique can be reached through the references [26,27]. This work also proposes a novel and simplified analysis algorithm, which is very efficient, accurate, and easy to implement on the existing finite element models.…”

Section: Data Processing and Analysis Methodologymentioning

confidence: 99%

An Innovative Structural Damage Detection System for Preventive Maintenance of Wind Turbines

Ozbek

2022

Arab J Sci Eng

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This study aims to develop a novel damage detection and preventive maintenance system that can be used for continuous or periodic monitoring of wind turbine components. The main features of the proposed system such as the measurement technique, data analysis procedure, and damage estimation methodology are described in detail by presenting the results of finite element model-based damage simulations, laboratory experiments, and in-field vibration tests. A hybrid measurement system with accelerometers and an automated infrared laser scanner is used to acquire vibration data with high spatial resolution. The obtained response data are then processed to extract the dynamic properties (e.g., natural vibration periods and mode shapes) of the structure. An efficient damage detection algorithm, which is based on monitoring sudden changes observed in mode shapes, is utilized to determine the location and extent of a possible damage. Within the scope of the work, a novel and simplified version of the widely used mode shape curvature method is developed for the rapid analysis and interpretation of the acquired vibration data. The applicability of the proposed methodology is demonstrated on a 61.5 m long numerical blade model proposed for NREL 5 MW Benchmark wind turbine.

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Section: Data Processing and Analysis Methodologymentioning

confidence: 99%

An Innovative Structural Damage Detection System for Preventive Maintenance of Wind Turbines

Ozbek

2022

Arab J Sci Eng

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“…Through the literature review, it has been found that there are mainly three types of studies about damage detection: analytical, numerical, and experimental studies [8][9][10][11][12]. The previous research of damage detection focused on aluminum alloys, steel alloys, conventional composites, functionally graded materials [13], and concrete structures.…”

Section: Introductionmentioning

confidence: 99%

The Coupled Effect of Temperature Changes and Damage Depth on Natural Frequencies in Beam-Like Structures

Al-hababi¹,

Alkayem²,

Cui³

et al. 2022

Structural Durability &Amp; Health Monitoring

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A significant amount of research is concerned with dynamic modal parameters for damage detection of structural conditions due to their simplicity in use and feasibility. However, their use for damage detection should be performed with special attention, particularly in operational and environmental conditions subjected to temperature changes. Beams in construction industries experience different loading types, such as temperature changes leading to crack initiation and propagation. Changed physical and dynamic properties such as natural frequencies and mode shapes indicate that damage has occurred within the structures. In this study, vibration analysis of cantilever and cantilever simply supported beams has been carried out on intact and damaged beams to investigate the coupled effect of temperature changes and damage depth on natural frequencies. A numerical analysis of beams is completed using ANSYS software. The results of numerical simulation are validated using two other studies from literature. Numerical results revealed that in order to perform a successful damage assessment using the frequency shift, the vibration modes should be selected properly. In addition, an increase in temperature results in a decrease in structural frequencies. The assessment of the effect of damage depth on natural frequencies also confirms that when damage depth is increased, there is a significant decrease in natural frequency responses.

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“…Since the natural frequency is much easier to measure than the mode and curvature, it has been used by some scholars to investigate the crack detection of cantilever beams [8][9][10]. More scholars applied the mode shape and natural frequency together for damage identification and location [11][12][13][14][15]. Flexibility is another key parameter for structure damage identification, the comparative study of vibration and wave propagation approaches based on the flexibility matrix of cantilever beams has been implemented [16], and a damage detection method based on a modal flexibility matrix has been proposed for the cantilever beam structures [17].…”

Section: Introductionmentioning

confidence: 99%

A Novel Low-Velocity Impact Region Identification Method for Cantilever Beams Using a Support Vector Machine

Wang

Kang

Xiao

et al. 2022

Mathematical Problems in Engineering

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Damage induced by a low-velocity impact can reduce the stability and reliability of structures. In this study, a novel low-velocity impact region identification method based on the spectral peak frequency (SPF) and support vector machine (SVM) is proposed to identify the low-velocity impact regions on a steel cantilever beam. A low-velocity impact region identification system of the cantilever beam is established by applying fiber Bragg grating (FBG) sensors, and only 2 sensors are used in this system. The power spectral density functions of the impact response signal are smoothed using the linear weighting method to remove pseudospectral peak frequencies, and then, SPFs are extracted as the features. For 25 low-velocity impact regions with dimensions of 30 mm × 10 mm, the results show that the recognition rate obtained by the proposed method is 100% and the feature vector consisting of the first two SPFs with the largest amplitude has the highest recognition rate. Through the comparative study, it is found that the recognition rate of SVM is higher than that of the probabilistic neural network (PNN) and extreme learning machine (ELM) for low-velocity impact area recognition of cantilever beams. As a result, the low-velocity impact region identification method of this paper can be applied to the real-time health monitoring of cantilever beam structures.

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Modal testing and evaluation of cracks on cantilever beam using mode shape curvatures and natural frequencies

Cited by 48 publications

References 51 publications

An Innovative Structural Damage Detection System for Preventive Maintenance of Wind Turbines

An Innovative Structural Damage Detection System for Preventive Maintenance of Wind Turbines

The Coupled Effect of Temperature Changes and Damage Depth on Natural Frequencies in Beam-Like Structures

A Novel Low-Velocity Impact Region Identification Method for Cantilever Beams Using a Support Vector Machine

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