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Hierarchical arrays of ZnO/Si nanowires were prepared through very convenient two-step solution method on silicon substrates. The tree-like nanowire structures showed high crystal quality, where well aligned Si nanowires were grown vertical to the substrate surface, whereas uniform assembly of branched ZnO nanowires was grown normal to the Si nanowires (backbones). Raman analysis indicated that among all the specimens having identical chemical compositions and dimensions but different forms (thin films or nanowires), Ag-decorated hierarchical arrays of ZnO/Si nanowires possessed the highest intensity peak in surface enhanced Raman scattering spectra. Such arrays demonstrated exceptional ability of detecting Rhodamine 6 G, limiting to a value as low as 1×10−8 mol/L and an enhancement factor up to 1.5 × 104. Both, experimental designing and band structure analysis indicated that electromagnetic effect of the localized surface plasmon resonance of Ag nanoparticles caused eight times enhancement, whereas chemical effect of hierarchical arrays of ZnO/Si nanowires played a more critical role in the high Raman sensitivity. Our results would be helpful to better understand the enhancement mechanisms and meanwhile, could be extended for further potential applications of hierarchical semiconducting nanowires.

The diameter of fine steel wire rope (FSWR) is generally a few millimeters. Its magnetic flux leakage (MFL) signal is weak, and the number of magnetic sensors installed for defect detection is limited because of the small diameter. In FSWR production workshops, different kinds of machinery work together, deteriorating the power quality and making the spatial electromagnetic environment complex; the weak MFL is thus interfered with further. It is difficult to carry out online nondestructive testing (NDT) of FSWR in the process of manufacturing. In this paper we present a novel MFL method for FSWR NDT in a strong electromagnetic interference environment. We use a three-dimensional finite element method (FEM) to analyze the MFL signals. A simplified magnetic circuit is presented to excite the FSWR; the circuit comprises two half-sized radial magnetizing ring NdFeB magnets, and because there is no need for a magnetic yoke, the device is simple and light. A single Hall sensor is used to measure the flux leakage field. A stable performance power system is designed for the NDT power supply, which is not only resistant to voltage sags, but also has very low output noise. To enhance the signal-to-noise ratio (SNR) of the MFL defects signal, a signal conditioning and processing circuit are designed to enhance the detectability of signals in MFL data. The novel and small FSWR NDT system realizes on-line testing in an environment of strong electromagnetic interference, and for the experiment with a 1.5-mm-diameter wire rope twisted by 19 wires, the minimum damage of a pit on half of a wire can be identified.

Inductive coil is used as the nondestructive testing sensor of a wire rope or a pipe, because of its low cost and high durability. However, the winding structure is complex and difficult to design during the field test. Hundreds or even thousands of turns are needed to improve the signal to noise ratio (SNR) and the data processing is cumbersome. In this paper, based on the theoretical analysis and 3D transient magnetic field simulation, a kind of iron core is presented as coil winding skeleton for the wire rope nondestructive testing. Additional iron core plays a role of magnetism concentration, where the magnetic flux leakage (MFL) path is changed and the MFL of the defect is converged to the core. Therefore, the SNR of the coil which is wound on the iron core is improved, and the coil winding skeleton is simplified with the iron core structure optimization. Meanwhile, the influence of the coil cross-section area on the test result analysis is eliminated, and the influence of the lift-off distance between coil and wire rope on the detection result is also reduced. Finally, it is proved by experiment that the SNR of coil with the iron core proposed in this paper is increased almost six times, which makes it easier for defect analysis.

The detection of internal and external defects in steel wire rope is a very important task. Current nondestructive testing methods cannot distinguish between internal and surface defects, and cannot determine the quantitative characteristics of internal defects. This paper first analyzes the advantages and disadvantages of induction coil magnetic flux detection and Hall sensor-based magnetic flux leakage detection. The problem of simultaneous detection using these two methods is then solved, and a new quantitative detection method is proposed for internal and surface defects in wire rope. Finally, a calculation method that uses a two-step training algorithm to establish two sets of neural networks is proposed. Results from simulations and experiments verify that the proposed method can accurately distinguish between internal and surface defects in wire rope, and can also quantitatively detect the width, cross-sectional loss rate, and depth of the defects.