Icing detection and evaluation of the electro-impulse de-icing system based on infrared images processing

Lü, Hao; Li, Qingying; Pan, Weichen; Li, Baolei

doi:10.1016/j.infrared.2020.103424

Cited by 21 publications

(6 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The components are arranged from high frequency to low frequency, and the components are nearly orthogonal. At the same time, the trend of infrared image is presented by residual quantity [10]. Assume that the source infrared image acquired by the UAV in the distribution network is represented by 𝐺 𝑥, 𝑦 , in which 𝑥 = 1,2, .…”

Section: Fast Adaptive Two-dimensional Empirical Mode Decomposition A...mentioning

confidence: 99%

An adaptive infrared image denoising method based on two-dimensional empirical mode decomposition for distribution network inspection UAV

Zhou¹,

Yang²,

Liu³

et al. 2023

J. meas. eng.

View full text Add to dashboard Cite

An adaptive denoising method based on 2D empirical mode decomposition (EMD) is proposed to improve the infrared image quality of inspection UNMANNED aerial vehicles (UAVs) and provide guarantee for improving the inspection level of distribution network. Through rapid adaptive two-dimensional empirical mode decomposition algorithm decomposition of a UAV collected for distribution network inspection original noise of infrared image, get more than the IMF component and the residual amount, a forecast noise dominated the IMF component parameters such as threshold value and the variance of noise, using the estimated parameters in combination with the optimal linear interpolation algorithm of noise threshold function of leading the IMF component implementation of threshold denoising. After the denoised IMF component is obtained, the denoised infrared image is obtained after reconstruction with the signal-dominated IMF component, and the adaptive denoising of the infrared image of the distribution network inspection UAV is realized. The experimental results show that the method in this paper can maintain the details of the image, improve the definition, significantly improve the visual effect, the overall denoising performance is stable and feasible, and ensure the quality inspection UAV to collect infrared images.

show abstract

Section: Fast Adaptive Two-dimensional Empirical Mode Decomposition A...mentioning

confidence: 99%

An adaptive infrared image denoising method based on two-dimensional empirical mode decomposition for distribution network inspection UAV

Zhou¹,

Yang²,

Liu³

et al. 2023

J. meas. eng.

View full text Add to dashboard Cite

show abstract

“…It is recommended that pixels are selected within the ice accretion zone. Principal component analysis and edge detection can be used to determine the ice accretion area from thermal images [34], to ensure that the data is representative of the ice accretion.…”

Section: Features Extractionmentioning

confidence: 99%

Ice accretion thickness prediction using flash infrared thermal imaging and BP neural networks

Lü

Qingying

Pan

et al. 2022

IET Image Processing

Self Cite

View full text Add to dashboard Cite

The present study investigated ice accretion thickness under non-incoming flow icing conditions on the ground using an infrared thermography system that converts infrared radiation temperature. Two back propagation (BP) neural network models were developed to measure ice thickness. Both theoretical model and polynomials were employed to fit the icing surface temperature elevation sequence to extract the pixel-level temperature attenuation characteristics, which were served as the input to the BP neural networks. The prediction method of ice thickness by the BP neural network was analysed from three perspectives of sensitivity, dimension, and precision. In addition, K-nearest neighbour (KNN) and support vector regression (SVR) algorithms were compared with BP neural network. In terms of prediction effect, the BP neural network performed the best. The verification of the BP neural network based on the characteristics of the theoretical model proved that the method can effectively predict the thickness of ice accretion, and its prediction error does not exceed 10%.

show abstract

“…23,24 Even if the extended finite element method is used, it is necessary to select the appropriate enrichment function to accurately construct the discontinuous displacement field, which greatly reduces the calculation efficiency, [25][26][27] and are not suitable for the numerical simulation of de-icing progression to the leading edge of an aircraft wing. 28 Peridynamics is a new nonlocal modeling approach first proposed by Silling and Askari 29 that employs an integral equation to reconstruct the equation of motion, solving the problems associated with the use of differential equations to address discontinuities in traditional mechanical systems. This method has been successfully applied to the simulation of discontinuity problems at different scales.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic simulation of aircraft electro-impulse de-icing using bond-based peridynamics

Zhang

Hou

Ji³

et al. 2022

Advances in Mechanical Engineering

View full text Add to dashboard Cite

Electro-impulse de-icing is a lightweight type of mechanical de-icing system that consumes little energy, provides high reliability, and offers wide application prospects. In this study, the bond-based peridynamics theory was used to simulate the dynamic damage process and evolution law of aircraft electro-impulse de-icing. The ice layer was simplified as a brittle material that satisfies the linear elastic constitutive relation. A numerical analysis model of the ice layer, aircraft skin substrate, and their interface was established to simulate the dynamic responses under a high strain rate. Considering the anisotropy of ice adhesion on the substrate, the interfacial bonds were described as shear bonds and tensile bonds, and the critical elongations of the two were derived. The tensile and shear capacities of the ice on the substrate were then simulated using these critical elongations, and the peeling rates of single ice particles and interfacial ice layers were taken as indexes describing the efficacy of electro-impulse de-icing. The process of electro-impulse de-icing was then analyzed for an aluminum substrate with two adjacent clamped edges. Finally, the results of the peridynamic simulation were compared with those of existing experiments and finite element models to verify the effectiveness of the peridynamic approach.

show abstract

Icing detection and evaluation of the electro-impulse de-icing system based on infrared images processing

Cited by 21 publications

References 33 publications

An adaptive infrared image denoising method based on two-dimensional empirical mode decomposition for distribution network inspection UAV

An adaptive infrared image denoising method based on two-dimensional empirical mode decomposition for distribution network inspection UAV

Ice accretion thickness prediction using flash infrared thermal imaging and BP neural networks

Dynamic simulation of aircraft electro-impulse de-icing using bond-based peridynamics

Contact Info

Product

Resources

About