Porosity evaluation of in-service thermal barrier coated turbine blades using a microwave nondestructive technique

Akbar, M.S.; Jawad, Ghassan Nihad; Duff, Christopher I.; Sloan, R.

doi:10.1016/j.ndteint.2017.09.015

Cited by 16 publications

(9 citation statements)

References 26 publications

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“…The working principle microwave NDT using OERWs is based on recording and analyzing the reflected, scattered electric field from an OERW probe scanned over a surface of the insulated structure using a calibrated Vector Network Analyzer (VNA). OERWs are widely used for microwave NDT applications such as dielectric property measurement of materials [13], the thickness measurement of dielectric slabs [14], [15], and porosity level estimation in ceramics [16]. Detecting the defects in under-insulated structures using open-ended rectangular waveguides also has been reported in [18].…”

Section: Several Microwave Ndt Techniques Have Been Reported For Undementioning

confidence: 99%

Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

et al. 2021

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Section: Several Microwave Ndt Techniques Have Been Reported For Undementioning

confidence: 99%

Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

et al. 2021

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“…Various microwave NDT techniques have been proposed for underneath defect evaluation [21][22][23][24][25][26]. In [21], an openended waveguide that depends on the phase profile is proposed to measure the delamination in terms of detection and thickness variations of the composite structure.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Delamination Under Insulation Using Ridge Waveguide

et al. 2022

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Insulation has been widely used to protect metal substrates in various industries such as turbine blades and oil and gas pipelines. Due to aging and cyclic processes, delamination between the metal component and insulation could grow. Such defects represent a critical problem that may result in catastrophic failure of the asset. Therefore, detecting and evaluating delaminated areas is mandatory for providing urgent maintenance solutions before the failure occurrence. In this paper, microwave nondestructive technique (NDT) is proposed for delamination detection and thickness estimation under dielectric insulation. In microwave NDT, the electromagnetic waves are induced into the dielectric material's surface using a ridge waveguide. The complex reflection coefficients are acquired using a vector network analyzer for further analysis in the time domain. Next, a time-domain reflectometry (TDR) technique-based inverse discrete Fourier transform is used to evaluate the complex reflection coefficients in terms of delamination's size and thickness estimation. The delamination evaluation is performed by measuring the maximum peak's time-step variations instead of the magnitude reduction in conventional TDR techniques in terms of the defect and defect-free reflections. Next, a comparison is made between implementing the proposed technique using a ridge waveguide and a regular rectangular waveguide. The results prove the superiority of using the ridge waveguide for delamination evaluation in terms of sizing and thickness with a minimum error rate of 5% and 7.87%, respectively. These novel results of ridge waveguide due to its small aperture and relatively wide bandwidth. The microwave NDT technique reported here could provide a predictive maintenance tool for many industries to minimize the maintenance effort and cost.

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“…Metal substrates are often protected against corrosion and higher temperatures by a ceramic-based coating [1]. Ceramic coating is often used on the turbine blades, vanes, and combustors of gas turbines to improve thermal protection against steam and higher temperatures [2]. Subsurface defects, such as debonding and delamination, reduce the ceramic's lifespan.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Defects under Insulation Using K-Medoids Clustering Algorithm-Based Microwave Nondestructive Testing

et al. 2022

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Composite insulations, such as ceramics, are commonly utilized in the turbine system as a thermal coating barrier to protect the metal substrate against high temperatures and pressure. The presence of delamination in the composite insulations may cause turbine failure, leading to a catastrophic accident. Thus, regular non-destructive testing is required to detect and evaluate insulation defects. Among the non-destructive testing techniques, the microwave technique has emerged as a promising method for assessing defects in ceramic coatings. Although the method is promising, microwave non-destructive testing suffers from poor spatial imaging, making the defect assessment challenging. In this paper, a novel technique based on microwave non-destructive testing with a k-medoids clustering algorithm for delamination detection is proposed. The representative ceramic coating sample is scanned using a Q-band open-ended rectangular waveguide with 101 frequency points that operated between 33 to 50 GHz. The measured data is transformed from the frequency domain to the time domain using an inverse fast Fourier transform. The principal component analysis is then used to reduce the dimensionality of 101 time steps into only 3 dominant attributes. The attributes of each inspected location are classified as defect or defect-free using the k-medoids clustering algorithm for accurately detecting and sizing the defects in the ceramic insulation. The results reported in this paper highlight the superiority of the k-medoids clustering algorithm in delamination detection, with an accuracy rate of 95.4%. This is a significant step forward compared to earlier approaches for identifying ceramic defects.

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Porosity evaluation of in-service thermal barrier coated turbine blades using a microwave nondestructive technique

Cited by 16 publications

References 26 publications

Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

Assessment of Delamination Under Insulation Using Ridge Waveguide

Assessment of Defects under Insulation Using K-Medoids Clustering Algorithm-Based Microwave Nondestructive Testing

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