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During electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel composite sensor of an electromagnetic acoustic transducer (EMAT) and pulse eddy current (PEC) is designed. We use the amplitude of a bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on the amplitude of bottom echo are distinguished by combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect a bottom crack as small as 0.1 mm × 0.3 mm. The signal fusion method can accurately correct the amplitude of defect signals and the relative error is less than ±8%. [ABSTRACT FROM AUTHOR]

The quantitative evaluation of defects is extremely important, as it can avoid harm caused by underevaluation or losses caused by overestimation, especially for internal defects. The magnetic permeability perturbation testing (MPPT) method performs well for thick-walled steel pipes, but the burial depth of the defect is difficult to access directly from a single time-domain signal, which is not conducive to the evaluation of defects. In this paper, the phenomenon of layering of magnetization that occurs in ferromagnetic materials under an unsaturated magnetizing field is described. Different magnetization depths are achieved by applying step magnetization. The relationship curves between the magnetization characteristic currents and the magnetization depths are established by finite element simulations. The spatial properties of each layering can be detected by different magnetization layering. The upper and back boundaries of the defect are then localized by a double-sided scan to finally arrive at the depth size of the defect. Defects with depth size of 2 mm are evaluated experimentally. The maximum relative error is 5%. [ABSTRACT FROM AUTHOR]

It's challenging to use the machine vision to inspect the hot-rolled steel pipes with complex surface texture, uneven colour greyscale, and micro-cracks. On the basis of the principle of magnetic particle detection, a visual inspection method of steel pipe surface cracks based on the dry magnetic particle feature enhancement is proposed, in which the dry red magnetic particles are applied to the steel pipe's surface to form magnetic particle indication, and complementary colour images are captured in red and green light sources, and image difference is used to eliminate background noise and enhance magnetic particle indication features in view of the fact that the red light source improves and the green light source reduces the magnetic particle indication greyscale. Afterwards, the principle of selection of complementary colours and the detection principle are presented and analysed. Then, the magnetic particle images acquisition and the processing operations of the magnetic particle indication feature enhancement and crack segmentation are presented in detail. Finally, the feasibility of the method proposed in this paper is verified by experiments, and image segmentation metrics demonstrate that it has a good detection effect on the hot-rolled steel pipes with complex surface texture, uneven colour greyscale, and fuzzy cracks. [ABSTRACT FROM AUTHOR]

Magnetic flux leakage (MFL) testing is a widely used nondestructive testing (NDT) method for the inspection of ferromagnetic materials. This review paper presents the basic principles of MFL testing and summarizes the recent advances in MFL. An analytical expression for the leakage magnetic field based on the 3D magnetic dipole model is provided. Based on the model, the effects of defect size, defect orientation, and liftoff distance have been analyzed. Other influencing factors, such as magnetization strength, testing speed, surface roughness, and stress, have also been introduced. As the most important steps of MFL, the excitation method (a permanent magnet, DC, AC, pulsed) and sensing methods (Hall element, GMR, TMR, etc.), have been introduced in detail. Finally, the algorithms for the quantification of defects and the applications of MFL have been introduced. [ABSTRACT FROM AUTHOR]

Although many adaptive techniques for active vibration reduction have been designed to achieve optimal performance in practical applications, few are related to reinforcement learning (RL). To explore the best performance of the active vibration reduction system (AVRS) without prior knowledge, a self-adaptive parameter regulation method based on the DDPG algorithm was examined in this study. The DDPG algorithm is unsuitable for a random environment and prone to reward-hacking. To solve this problem, a reward function optimization method based on the integral area of the decibel (dB) value between transfer functions was investigated. Simulation and graphical experimental results show that the optimized DDPG algorithm can automatically track and maintain optimal control performance of the AVRS. [ABSTRACT FROM AUTHOR]

This paper proposes a method of injected alternating current-field measurement (IAC-FM) for detecting orthogonal cracks in the piston rod of a hydraulic cylinder in a gate hoist. Using this method, both longitudinal and transverse cracks can be detected at the same time. An alternating magnetic field is produced inside the steel rod by axially injecting an alternating current into the rod. The longitudinal crack perturbs the circumferential magnetic field, whereas the transverse crack perturbs the current in the axial direction. Analyses of the behaviors of the magnetic field in the vicinity of the cracks were proposed, using a three-dimensional finite element software. An experimental setup was built and validation experiments were performed. The effects of the operating frequency and scan path were also studied. The results verified the feasibility of the IAC-FM method and showed great potential for the inspection of in-service hydraulic cylinders of gate hoists. [ABSTRACT FROM AUTHOR]

Delaminations have been detected based on the principle of ultrasonic thickness measurement. However, there are blind zones in the detection of surface delamination. Besides, the high-speed detection system is complicated. A novel permeability perturbation testing (PPT) method for the inspection of delaminations in ferromagnetic materials is proposed in this paper. When DC magnetisation is applied in the thickness direction of steel plate, the delamination in the plate will distort the internal magnetic field, leading to local permeability perturbation. This perturbation is transmitted to the surface layer of steel plate in the thickness direction. Using a differential-type eddy current transducer, internal delaminations are detected by measuring relative variation of surface permeability. The variation of permeability in the near surface of steel plate with the movement of delamination and the change of magnetisation state of the steel plate are obtained through finite element simulation. The feasibility of the above method is further verified through an experiment. This new method has the advantage in high-speed detection of delamination. [ABSTRACT FROM AUTHOR]

As one of the most important processes in steel wire rope inspection, defect signal processing is of great significance in guaranteeing safety and precision measurement. Aiming at the weak signal detection of steel wire rope with mixed strands and noise, a combined signal processing method based on magnetic flux leakage testing and multi-step filtering techniques are proposed in this paper. The experiments are first introduced and performed on three typical types of steel wire rope with diameters of 28 mm, 32 mm, 45 mm, and different wire broken defects detected under liftoff distances of 13 mm and 20 mm; the acquired signals are then analyzed both in time and frequency domain. According to the weak signal characterizations, the principle of the proposed methods and algorithm are given concretely. Afterwards, comparison of signal processing results between the traditional lowpass filtering, wavelet denoising, median filtering, and the proposed method are presented. Finally, the influence factors of smoothing types and moving average span of the proposed methods are investigated. The processing results of the proposed methods are shown through short-time Fourier transform and signal-to-noise ratio analysis, which not only demonstrates the validity and feasibility of the combined methods with the highest signal to noise ratio of 90.37 dB, but also exhibits a great potential of precision defect detection and practical application in steel wire rope inspection. [ABSTRACT FROM AUTHOR]