Search

The combination of superelastic shape memory alloy fibers and ECC materials can form a new SMA fiber reinforced ECC composite material (SMAF-ECC) with good self-centering performance. In order to study the self-centering performance of the new composite material, 6 groups of pre-notch beam specimens were made for three-point bending cyclic loading tests, and the failure phenomenon, hysteresis curve, self-centering effect and influencing factors of the specimens were analyzed. The research results show that when the SMA fibers are effectively anchored in the ECC matrix, the SMA fibers can exert the superelastic properties to provide the ECC beams with recoverying force, and realize the crack self-closure and deflection self-recovery function for the beams, with the minimum residual crack width and deflection is only 0.9 mm and 1.3 mm respectively. Increasing fiber content can cause a small increase in the self-centering ability of the beams. However, only when the fiber diameter is appropriate, better self-centering effect can be achieved, but the difference caused by fiber diameter in the test was only 5%. SMA Fiber end forms have significant influence on self-centering performance. The knotted end beam can get a more than 70% self-centering ratio, while the straight end beams and bended end beams have no self-centering ability. The research results provide important reference for the research and application of this new self-centering materials and their structures. [ABSTRACT FROM AUTHOR]

With the popularity of electric vehicles, the ever-increasing demand for high-capacity batteries highlights the need for monitoring the health status of batteries. In this article, we proposed a magnetic imaging technique (MIT) to investigate the health status of power batteries nondestructively. This technique is based on a magnetic sensor array, which consists of a 16-channel high-performance magnetoelectric sensor, and the noise equivalent magnetic induction (NEB) of each channel reaches 3–5 pT/Hz1/2@10 Hz. The distribution of the magnetic field is imaged by scanning the magnetic field variation of different positions on the surface. Therefore, the areas of magnetic anomalies are identified by distinguishing different magnetic field abnormal results. and it may be possible to classify the battery failure, so as to put forward suggestions on the use of the battery. This magnetic imaging method expands the application field of this high-performance magnetoelectric sensor and contributes to the battery's safety monitoring. Meanwhile, it may also act as an important role in other nondestructive testing fields. [ABSTRACT FROM AUTHOR]