Gaussian mixture model and delay-and-sum based 4D imaging of damage in aircraft composite structures under time-varying conditions

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Fang, Fang

doi:10.1016/j.ymssp.2019.106390

Cited by 44 publications

(17 citation statements)

References 34 publications

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“…Based on the assumption that h i are independent, the likelihood function, equation (21), can be acquired by factoring equation ( 23) over N measured NODIS p Dju ð Þ=…”

Section: Bayesian Damage Identification Framework Under Uncertaintymentioning

confidence: 99%

“…18 Probabilistic approaches can alleviate the problem by calculating the probability distribution of the damage parameter and quantifying the confidence level of the identified results. [19][20][21] Among them, the Bayesian statistical framework is frequently used to handle illposed problems and describe uncertainty level in model updating and later in damage identification. Also, the Bayesian framework can integrate a prior probability of the random variables based on engineering knowledge.…”

Section: Introductionmentioning

confidence: 99%

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IWSHM 2019: Perturbation-based Bayesian damage identification using responses at vibration nodes

Huang

Schröder

2021

Structural Health Monitoring

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One important topic for structural health monitoring is to achieve accurate damage detection with a small number of noisy sensors and without the requirement of a high-fidelity finite element model. This article adopts the Bayesian probabilistic approach combined with a perturbation model using responses at a few vibration nodes for damage monitoring. First, the node displacement, or the response at vibration node, is adopted in this study for real-time damage assessment with a relatively small number of sensors. Then, the construction method of the node displacement response curves based on the perturbation model is proposed to replace the expensive finite element model. After that, a Bayesian framework integrated the node displacement measurement and the response curves are adopted to acquire the probability distribution of the damage parameter. In this article, the accuracy of the node displacement–based Bayesian framework with the perturbation method is evaluated. The proposed method is applied to a supporting structure of a sailplane under different noise levels.

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“…Based on the assumption that h i are independent, the likelihood function, equation (21), can be acquired by factoring equation ( 23) over N measured NODIS p Dju ð Þ=…”

Section: Bayesian Damage Identification Framework Under Uncertaintymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IWSHM 2019: Perturbation-based Bayesian damage identification using responses at vibration nodes

Huang

Schröder

2021

Structural Health Monitoring

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“…With the help of advanced signal and information processing algorithms, Lamb wave damage imaging technology, which can intuitively provide the location and size of the damage, has become a topic of interest in SHM technology. Existing Lamb wave damage imaging technologies, such as probabilistic reconstruction algorithms [ 16 , 17 ], phased arrays [ 18 , 19 ], tomography [ 20 , 21 ] and delay-and-sum [ 22 , 23 ] methods, can realize damage location and even quantification in plate-type structures. However, due to the limitations of wave diffraction, existing damage imaging algorithms have poor resolution and difficulty distinguishing two neighboring damage within the Rayleigh limit.…”

Section: Introductionmentioning

confidence: 99%

A Local TR-MUSIC Algorithm for Damage Imaging of Aircraft Structures

Fan

Zhang

Sun

et al. 2021

Sensors

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Lamb wave-based damage imaging is a promising technique for aircraft structural health monitoring, as enhancing the resolution of damage detection is a persistent challenge. In this paper, a damage imaging technique based on the Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) algorithm is developed to detect damage in plate-type structures. In the TR-MUSIC algorithm, a transfer matrix is first established by exciting and sensing signals. A TR operator is constructed for eigenvalue decomposition to divide the data space into signal and noise subspaces. The structural space spectrum of the algorithm is calculated based on the orthogonality of the two subspaces. A local TR-MUSIC algorithm is proposed to enhance the image quality of multiple damages by using a moving time window to establish the local space spectrum at different times or different distances. The multidamage detection capability of the proposed enhanced TR-MUSIC algorithm is verified by simulations and experiments. The results reveal that the local TR-MUSIC algorithm can not only effectively detect multiple damages in plate-type structures with good image quality but also has a superresolution ability for detecting damage with distances smaller than half the wavelength.

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“…In the research on imaging methods based on sparse sensor arrays, Michaels et al [17] used a multisensing method to acquire structural response signals and image fusion technology to realize hole damage imaging in aluminum plates. Yuan et al [18] combined the delay-sun imaging method with the probabilistic hybrid model and proposed a 4D damage imaging method. The damage imaging of a carbon fiber reinforced structure under the influence of temperature is realized.…”

Section: Introductionmentioning

confidence: 99%

Sector Piezoelectric Sensor Array Transmitter Beamforming MUSIC Algorithm Based Structure Damage Imaging Method

Wang

Qiu

et al. 2020

Sensors

Self Cite

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Elastic-wave-based structural health monitoring technology has a broad application potential for its sensitivity and ability to achieve regional monitoring. For structures with large damping and specific shapes, the traditional damage monitoring method is limited by the sensor arrangement area and affected by low signal-to-noise ratios, so it is difficult to accurately locate the damage in a structure. To solve this problem, this paper proposed a damage monitoring method based on a sector piezoelectric sensor array for multiple signal classification algorithm. By arranging two sector piezoelectric sensor arrays that are suitable for a specific structure, the damage scattering array signal under the multi-excitation source was obtained and synthesized, the signal-to-noise ratios were improved, and the damage location accuracy was thus improved. The effectiveness of the method was verified by monitoring the damage in a circular bonded structure with a metal ring. Compared with the damage localization methods based on the traditional single excitation source multiple signal classification algorithm, path imaging and delay-sum imaging, this method can achieve better damage location and has a higher localization accuracy.

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Gaussian mixture model and delay-and-sum based 4D imaging of damage in aircraft composite structures under time-varying conditions

Cited by 44 publications

References 34 publications

IWSHM 2019: Perturbation-based Bayesian damage identification using responses at vibration nodes

IWSHM 2019: Perturbation-based Bayesian damage identification using responses at vibration nodes

A Local TR-MUSIC Algorithm for Damage Imaging of Aircraft Structures

Sector Piezoelectric Sensor Array Transmitter Beamforming MUSIC Algorithm Based Structure Damage Imaging Method

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