Vibration based damage detection of rotor blades in a gas turbine engine

Madhavan, S.; Jain, Rajeev; Sujatha, C.; Sekhar, A. S.

doi:10.1016/j.engfailanal.2014.07.021

Cited by 93 publications

(47 citation statements)

References 14 publications

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“…Wang and Zhang 2005 [21] Engine prognosis based upon oil analysis Ogbonnaya 2009 [22] Rotor shaft fault diagnosis and prognosis using misalignment, imbalance, crack and eccentricity Walker et al 2012 [23] Localizing unbalancy looking at stationary and rotating vibration phenomena Madhavan et al 2014 [24] Vibration-based damage detection of rotor blades Faults in auxiliary subsystems Pennacchi and Vania 2008 [25] Diagnostics of a crack in load coupling Watson et al 2010 [26] Vibration diagnostics of accessories Sensor uncertainties Pourbabaee et al [27] Sensor Fault Detection, Isolation, and Identification Fadlun et al 2008 [28] Demonstration of influence of instruments accuracy on condition-based maintenance Palmé et al 2011 [29] Fault detection and isolation of sensor As shown in Figure 3, gas turbine monitoring system can be generally categorized as online and off-line monitoring.…”

Section: Mechanical Errormentioning

confidence: 99%

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Tahan¹,

Tsoutsanis

Muhammad³

et al. 2017

Applied Energy

335

158

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With the privatization and intense competition that characterize the volatile energy sector, the gas turbine industry currently faces new challenges of increasing operational flexibility, reducing operating costs, improving reliability and availability while mitigating the environmental impact. In this complex, changing sector, the gas turbine community could address a set of these challenges by further development of high fidelity, more accurate and computationally efficient engine health assessment, diagnostic and prognostic systems. Recent studies have shown that engine gas-path performance monitoring still remains the cornerstone for making informed decisions in operation and maintenance of gas turbines. This paper offers a systematic review of recently developed engine performance monitoring, diagnostic and prognostic techniques. The inception of performance monitoring and its evolution over time, techniques used to establish a highquality dataset using engine model performance adaptation, and effects of computationally intelligent techniques on promoting the implementation of engine fault diagnosis are reviewed. Moreover, recent developments in prognostics techniques designed to enhance the maintenance decision-making scheme and main causes of gas turbine performance deterioration are discussed to facilitate the fault identification module. The article aims to organize, evaluate and identify patterns and trends in the literature as well as recognize research gaps and recommend new research areas in the field of gas turbine performance-based monitoring. The presented insightful concepts provide experts, students or novice researchers and decision-makers working in the area of gas turbine engines with the state of the art for performance-based condition monitoring.

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Section: Mechanical Errormentioning

confidence: 99%

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Tahan¹,

Tsoutsanis

Muhammad³

et al. 2017

Applied Energy

335

158

View full text Add to dashboard Cite

show abstract

“…Therefore, the analysis of dynamic behavior of the gas turbine is attracting much attention from the researcher and industrialists. It is based on the study of vibration behavior of the main element of the gas turbine which is the high pressure rotor (HP) (Madhavan et al, 2014;Rahmoune et al, 2015).…”

Section: Dynamic Vibration Behavior In Gas Turbinementioning

confidence: 99%

“…Therefore, in order to improve the performances of these systems, many researches previously built mathematical models that represent the real time operation state more accurately and instantaneously. Madhavan et al (2014) developed a vibration model based on damage detection of rotor blades in a gas turbine engine. They showed that the developed model can be used to carry out the analysis of mechanical components failures detection of the system under study.…”

Section: Introductionmentioning

confidence: 99%

Faults detection in gas turbine rotor using vibration analysis under varying conditions

Djaidir

Hafaifa

Kouzou

2017

jtam

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Monitoring of rotating machines is a very important task in most industrial sectors, which requires a chosen number of performance indicators during the exploitation of such kind of equipments. Indeed, for understanding the undesirable phenomena complexity of the industrial systems under operation, a reliable and an accurate mathematical modeling is required to ensure the diagnosis and the control of these phenomena. This work proposes development of a fault monitoring system of a gas turbine type GE MS 3002 based on vibration analysis technique using spectral analysis tools. The obtained results prove the effectiveness of the presented monitoring tool approach which is applied on the gas turbine, for avoiding the operation under vibration mode and for generating optimal performance during the exploitation of the gas turbine.

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“…e blade vibration was monitored, and blade cracks were detected during machine operation [3]. e abnormalities found in the vibration characteristics of the BTT data measured during engine tests were used to identify blade damage [4]. BTT measurements were employed for identifying the dynamic behavior and detecting a small mistuning pattern of rotating bladed disks [5].…”

Section: Introductionmentioning

confidence: 99%

Wavelet Transform‐Based Damage Identification in Bladed Disks and Rotating Blades

Rajendran

Jamia

El-Borgi

et al. 2018

Shock and Vibration

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Blade vibration and blade clearance are effective diagnostic features for the identification of blade damage in rotating machines. Blade tip-timing (BTT) is a noncontact method that is often used to monitor the vibration and clearance of blades in a rotating machinery. Standard signal processing of BTT measurements give one blade response sample per revolution of the machine which is often insufficient for the diagnosis of damage. This paper uses the raw data signals from the sensors directly and employs a wavelet energy-based mistuning index (WEBMI) to predict the presence and locations of damage in rotating blades. The Lipschitz exponent is derived from the wavelet packet coefficients and used to estimate the severity of the damage. In this study, experiments were conducted to obtain BTT measurements on rotating blades at 100 rpm using three different sensors: an active eddy current sensor, a passive eddy current sensor, and an optical sensor. In addition, hammer excitation experiments were conducted for various added mass (damage) cases to compute the damage severity for a bladed disk. To simulate the damage experimentally in the bladed disk and rotating blades, masses were added to the blades to alter their dynamics and mimic the damage. The results indicate that the WEBMI can detect the presence and location of damage in rotating blades using measurements from common BTT sensors. To check the robustness of the proposed damage severity index, the experimental results were compared with numerical simulation for the bladed disk and showed good agreement.

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Vibration based damage detection of rotor blades in a gas turbine engine

Cited by 93 publications

References 14 publications

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Faults detection in gas turbine rotor using vibration analysis under varying conditions

Wavelet Transform‐Based Damage Identification in Bladed Disks and Rotating Blades

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