The detection and quantification of the rolling contact fatigue (RCF) in rail tracks are essential for rail safety and condition-based maintenance. The tomographic reconstruction of the rolling contact fatigue is challenging work. The x-ray is unable to do in-situ inspection effectively. This paper proposes a new approach for RCF construction using 3D eddy current pulsed thermography. A differential time-square-root (sqrt) of temperature drop (DTSTD) is proposed as a mean to construct the sectional images and to reconstruct the thermal tomography image. The proposed method is validated through artificial angular crack slots as well as natural RCF crack. The thermal tomographic reconstruction is compared with the x-ray computed tomography on a rail track head cut-off with RCF cracks.

Paint coated corrosion detection and evaluation is a big challenge for steel performance and structure health. Eddy current pulsed thermography (ECPT) technique is investigated because it can reflect the corrosion physical properties through paint coating by the infrared signal. This paper proposes skewness method, which presents the feature of temperature curve’s shape automatically, and compares it with principal component analysis (PCA), phase analysis, and kurtosis feature extraction methods for paint coated corrosion characterization and evaluation. The averaged skewness shows the best sensitivity for 0–6 months corrosion. The normalized second principal component (PC) presents good sensitivity and the best measurement scale for corroded time. Furthermore, the temperature curve analysis proves that the electrical conductivity dominates the induced heating and heat distribution. The corrosion height is utilized to explain why ECPT technique is valid within 10 months corroded time. ECPT technique is proved as a smart sensor system for paint coated corrosion detection and characterization.

For detecting early-stage corrosion in carbon steel, infrared image sequences were captured using eddy-current pulsed thermography (ECPT). This study proposes an integrated evaluation framework—comprising bidimensional empirical mode decomposition (BEMD), temperature-rise-rate mapping, U-Net segmentation, and subsequent feature extraction methods (fast Fourier transform (FFT), principal component analysis (PCA), and skewness analysis)—to comprehensively denoise thermal images, precisely segment corrosion regions, and accurately quantify corrosion severity. On the test dataset, the proposed method achieved a mean intersection-over-union (mIoU) of 0.92, mean pixel accuracy (mPA) of 0.96, precision of 0.95, and recall of 0.975. Compared with conventional feature-extraction methods (PCA, FFT, and skewness analysis), the proposed integrated framework substantially enhanced sensitivity (increased by 19%–62%) and reduced root-mean-square error (decreased by 5%–23%), providing a more reliable and precise quantification of early-stage corrosion. These results confirm that the presented evaluation framework surpasses traditional corrosion assessment techniques, demonstrating substantial potential for practical implementation in industrial facilities.

In this paper, a high-performance Extended Gate Field Effect Transistor (EGFET) with replaceable sensing area was designed using HfO ₂ and In ₂ O ₃ . A 3D simulation model was built based on Silvaco TCAD software. This model could capture the internal physical structure of the device accurately, to guide the design of EGFETs. Based on the material and structure simulation analysis, the optimal simulation model was constructed. Then, the EGFET was fabricated in accordance with this model. The results demonstrated that the EGFET designed in this study exhibited high performance with pH voltage sensitivity of 110.91 mV/pH, linearity (R ² ) of 97.67%, and relative standard deviation (RSD) of threshold voltage of 3.51%. Furthermore, the thrombin, which requires high detection accuracy and wide concentration range, was chosen as the detecting target biomaker to validate the performance of EGFETs in detecting trace markers. A hand-held device was fabricated based on the EGFET to realize the detection of thrombin concentration in the range of 1~10000 pM (R ² = 95.64%), indicating the excellent performance and enormous potential of the EGFET.