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This paper investigates effects of temperature variation on output signal of rosette eddy current array (RECA) sensor and proposes a new RECA sensor with temperature compensation capability for quantitative monitoring crack of bolt-jointed structures. A temperature simulation experiment shows that temperature variation has a great influence on output signal AR of RECA sensor as crack does and even results in false alarm when environment temperature changes. Temperature-compensated RECA (TC-RECA) sensor using the new output signal ΔC considering impacts of conductivity and lift-off is developed to eliminate impacts of temperature variation on monitoring process. Then, the relation between crack length and output signal ΔC is obtained by an online monitoring experiment, which shows TC-RECA sensor can quantitatively monitor crack with an accuracy of 1 mm. Then, a temperature simulation experiment is performed to verify the sensor’s ability to eliminate effects of temperature variation on monitoring process. Results shows that output signal ΔC just changes within about 0.5% when temperature changes from −20 °C to 70 °C, which has no effects on monitoring process. Finally, a crack monitoring experimental of a bolt-jointed structure under temperature disturbance is performed to verify the sensor’s abilities of quantitative monitoring crack of bolt-jointed structures and temperature compensation. It can be concluded that TC-RECA sensor has the ability to eliminate effects of temperature variation and can quantitatively monitor crack of bolt-jointed structures with an accuracy of 1 mm. [ABSTRACT FROM AUTHOR]

The amount of coke deposition on catalyst pellets is one of the most important indexes of catalytic property and service life. As a result, it is essential to measure this and analyze the active state of the catalysts during a continuous production process. This paper proposes a new method to predict the amount of coke deposition on catalyst pellets based on image analysis and soft computing. An image acquisition system consisting of a flatbed scanner and an opaque cover is used to obtain catalyst images. After imaging processing and feature extraction, twelve effective features are selected and two best feature sets are determined by the prediction tests. A neural network optimized by a particle swarm optimization algorithm is used to establish the prediction model of the coke amount based on various datasets. The root mean square error of the prediction values are all below 0.021 and the coefficient of determination R2, for the model, are all above 78.71%. Therefore, a feasible, effective and precise method is demonstrated, which may be applied to realize the real-time measurement of coke deposition based on on-line sampling and fast image analysis. [ABSTRACT FROM AUTHOR]

Monitoring liver fibrosis progression by liver biopsy is important for certain treatment decisions, but repeated biopsy is invasive. We envision redefinition or elimination of liver biopsy with surface scanning of the liver with minimally invasive optical methods. This would be possible only if the information contained on or near liver surfaces accurately reflects the liver fibrosis progression in the liver interior. In our study, we acquired the second-harmonic generation and two-photon excitation fluorescence microscopy images of liver tissues from bile duct-ligated rat model of liver fibrosis. We extracted morphology-based features, such as total collagen, collagen in bile duct areas, bile duct proliferation, and areas occupied by remnant hepatocytes, and defined the capsule and subcapsular regions on the liver surface based on image analysis of features. We discovered a strong correlation between the liver fibrosis progression on the anterior surface and interior in both liver lobes, where biopsy is typically obtained. The posterior surface exhibits less correlation with the rest of the liver. Therefore, scanning the anterior liver surface would obtain similar information to that obtained from biopsy for monitoring liver fibrosis progression. [ABSTRACT FROM AUTHOR]

• The effect of atmospheric exposure corrosion on the fatigue properties of epoxy-coated aluminum alloys is studied. • A fatigue life probability model and C (corrosion)– S – N surface that considers the effect of corrosion are proposed and verified. • The effects of the atmospheric exposure time and stress intensity on the fatigue life and attenuation ratio of fatigue life are studied. The effect of atmospheric exposure corrosion on the fatigue properties of epoxy-coated aluminum alloys is studied using experimental atmospheric exposure data and some data presented in the literature. Based on a single-point model and the maximum likelihood method, a fatigue life probability model and C (corrosion)– S – N surface that considers the effect of corrosion are proposed and verified. This study finds that the epoxy coatings gradually lose their protective effect on the aluminum alloy substrates after four years of atmospheric exposure, and corrosion factors play a more pronounced role in the latter period of atmospheric exposure. [ABSTRACT FROM AUTHOR]

The modification of epoxy primers with graphene can significantly improve their anticorrosion properties and reduce environmental pollution. In this study, the modified epoxy primers with different graphene contents were prepared and tested in a UVA acidic alternation immersion environment. The deterioration characteristics under different corrosion times were analyzed in terms of their microscopic morphology, electrochemical characteristics, and molecular structure. It was shown that graphene nanoplates can impede the penetration of corrosive media, promote the cathodic protection of fillers, and easily cross-link with amino radicals to improve the binding force at the interface. The coated surface of graphene nanoplates with a content of 1.0 wt% was flatter than those with a content of 0.5 wt% and 2.0 wt%. After corrosion, the roughness of the surfaces all increased significantly. Especially, the coatings with graphene contents of 0.5 wt% increased nearly three times. And the impedance improvement of the coatings with graphene contents of 0.5 wt% and 1.0 wt% is more significant, both reaching more than 6 × 1011 Ω·cm2. The most obvious corrosion inhibiting effect was the coatings with a graphene content of 1.0% wt. [Display omitted] • The graphene-modified epoxy primers were prepared. • The deterioration characteristics of GNP-EPs with different graphene contents were analyzed. • The anticorrosive mechanism of GNP-EPs was elucidated. [ABSTRACT FROM AUTHOR]