Eggshell crack detection based on the transient impact analysis and cross-correlation method

Sun, Li-Peng; Zhang, Pengqi; Feng, Siyu; Qiang, Min; Cai, Jun

doi:10.1016/j.crfs.2021.09.012

Cited by 8 publications

(3 citation statements)

References 22 publications

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“…In contrast, damaged shells displayed different responses at distinct equatorial locations. This research inspired several other researchers to build accurate crack detection algorithms based on the vibration of the egg [ 13 , 14 , 15 , 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 85%

Non-Destructive Eggshell Strength Assessment Using Hertz Contact Theory Part I: Theory and Applicability

Ketelaere

Corion

Adriaens

et al. 2023

Foods

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In the egg industry, fast and highly reliable quality measurements are crucial. This study presents a novel method based on Hertz contact theory that allows for non-destructive determination of eggshell strength. The goal of the study was to evaluate the material strength (Young’s Modulus) and structural strength (stiffness) of eggshells. To this end, an experimental setup was constructed to measure the collision of an eggshell with a small steel ball, which was recorded using a laser vibrometer. The study analyzed a sample of 120 eggs and found a correlation of 0.85 between the traditional static stiffness measured during quasi-static compression tests and the stiffness obtained from the Hertz contact theory. The results show that Hertz contact theory is valid for small steel spheres impacting eggshells, while a sensitivity analysis indicated that the most important factor in determining the strength of the eggshell is the contact duration between the egg and the impactor. These results open up the possibility of grading eggs based on their shell strength in a non-destructive manner.

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Section: Introductionmentioning

confidence: 85%

Non-Destructive Eggshell Strength Assessment Using Hertz Contact Theory Part I: Theory and Applicability

Ketelaere

Corion

Adriaens

et al. 2023

Foods

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“…Based on the features of these two kinds of vibrations, power/energy cross-correlation between different positions is proposed to detect periodic/transient vibration in this paper. Our results demonstrate that power and energy cross-correlation coefficients work well to locate these two vibration events [2][3] .…”

Section: Introductonmentioning

confidence: 56%

Vibration detection by energy/power cross-correlation in φ-OTDR

Wen

Zhou

Chen

et al. 2023

14th International Photonics and Optoelectronics Meetings (POEM 2022)

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Reducing false alarming of vibration and shortening data processing time are one of the key problems of phase sensitive optical time-domain reflectometer (φ-OTDR). Generally speaking, there are two demodulation methods to locate vibrations: phase demodulation and amplitude demodulation. At present, an often-used method is phase-based crosscorrelation, which shows a comparatively reliable detection performance. Compared with phase cross-correlation, energy/power cross-correlation between different positions is simpler and has certain advantages in practical applications. In this paper, we use φ-OTDR to collects periodic vibration signals (power signals) and transient vibration signals (energy signals). Amplitude differentiation is firstly calculated along slow time axis for the Rayleigh backscattering trajectories. For periodic vibration, power spectrum is then obtained at each position, and cross-correlation coefficients between any two spectrums are computed. If the vibration is transient, average energy is calculated along fast time axis and average energy cross-correlation is performed between any two locations. With the cross-correlation values, we are able to determine whether there is vibration on the optical fiber. In the experiment, periodic vibration is simulated by a sine-driven PZT and transient vibration is mimicked by pencil-break. These results demonstrate that power (energy) cross-correlation coefficients work well to locate periodic (transient) vibrations.

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“…Li Sun et al built an equivalent mechanical model based on an automatic excitation device and analyzed the transient impact. They used cross-correlation analysis and Bayesian classification to detect eggshell cracks, which could reach a detection level of 97% [4]. P. Coucke et al proposed exciting the eggs with a small impact hammer and extracting the spectral features of acoustic signals as the input vector of the classification algorithm, whose detection accuracy could reach 90% [5].…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Detection of Microcracks in Poultry Eggs Based on the Electrical Characteristics Model

et al. 2022

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The eggshell is the major source of protection for the inside of poultry eggs from microbial contamination. Timely detection of cracked eggs is the key to improving the edible rate of fresh eggs, hatching rate of breeding eggs and the quality of egg products. Different from traditional detection based on acoustics and vision, this paper proposes a nondestructive method of detection for eggshell cracks based on the egg electrical characteristics model, which combines static and dynamic electrical characteristics and designs a multi-layer flexible electrode that can closely fit the eggshell surface and a rotating mechanism that takes into account different sizes of eggs. The current signals of intact eggs and cracked eggs were collected under 1500 V of DC voltage, and their time domain features (TFs), frequency domain features (FFs) and wavelet features (WFs) were extracted. Machine learning algorithms such as support vector machine (SVM), linear discriminant analysis (LDA), decision tree (DT) and random forest (RF) were used for classification. The relationship between various features and classification algorithms was studied, and the effectiveness of the proposed method was verified. Finally, the method is proven to be universal and generalizable through an experiment on duck eggshell microcrack detection. The experimental results show that the proposed method can realize the detection of eggshell microcracks of less than 3 μm well, and the random forest model combining the three features mentioned above is proven to be the best, with a detection accuracy of cracked eggs and intact eggs over 99%. This nondestructive method can be employed online for egg microcrack inspection in industrial applications.

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Eggshell crack detection based on the transient impact analysis and cross-correlation method

Cited by 8 publications

References 22 publications

Non-Destructive Eggshell Strength Assessment Using Hertz Contact Theory Part I: Theory and Applicability

Non-Destructive Eggshell Strength Assessment Using Hertz Contact Theory Part I: Theory and Applicability

Vibration detection by energy/power cross-correlation in φ-OTDR

Nondestructive Detection of Microcracks in Poultry Eggs Based on the Electrical Characteristics Model

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