Volume Of Influence Research Articles

A Discrimination method of three types of defects in insulated cladding components based on the lift-off effect of capacitive imaging (CI) technology

In insulated cladding components, simultaneously detecting and distinguishing surface defects on the insulation layer, hidden defects in the insulation layer, and surface defects on the metal layer of insulated cladding components can help in formulating appropriate maintenance plans and promptly eliminating safety hazards, which is of great significance for ensuring the safety of insulated cladding components in relevant application fields. This paper applies capacitive imaging (CI) to detect three different types of defects. A three-dimensional simulation model of the CI sensor detecting the three types of defects is established using COMSOL software. The corresponding measurement sensitivity distribution (MSD) and volume of influence (VOI) are obtained, and the detection mechanisms of the three different types of defects are analyzed in detail. By analyzing the lift-off height variation, the VOI regions' changing patterns for different types of defects are determined, and the distinguishing mechanisms for the three types of defects are obtained. Based on the monotonicity of the normalized variation ratio (NVR) and the differences in the positions of the intersection points, a comparative distinguishing method for the three types of defects based on the variation of the lift-off height is established. Experimental results demonstrate that the defect comparative distinguishing method based on the lift-off effect can effectively differentiate surface defects on the insulation layer, hidden defects in the insulation layer, and surface defects on the metal layer.

3D time-domain airborne electromagnetic inversion based on secondary field finite-volume method

We investigate an algorithm for 3D time-domain airborne electromagnetic (AEM) inversion based on the finite-volume (FV) method and direct Gauss-Newton optimization, where we obtain high efficiency by constraining the modeling volume to the AEM volume of influence (VOI) of a 3D source within the earth, rather than using the larger VOI of the AEM system. A half-space or layered earth is used to model the background field in the time domain, taking into account the transmitter waveform through convolution. Assuming that the 3D source of any secondary field detected at a survey point lies within the moving VOI of the airborne system, we conduct time-domain forward modeling and Jacobian calculation using an FV method within the 3D source VOI that requires a small number of cells for discretization. A local mesh and direct solver are shown to further speed up the computation. A synthetic isolated synclinal conductor inversion shows good agreement with the model geometry and provides a good fit to the data contaminated with noise. A synthetic multiple-body model inversion was also quite successful, showing that our algorithm is effective and about four times faster than inversion using the total-field method. Finally, we inverted GEOTEM data over the Lisheen deposit, where our inversion result was consistent with the published geology.

Volume of Influence for Magnetic Soils and Electromagnetic Induction Sensors

The concept of volume of influence (VoI) for electromagnetic induction (EMI) sensors is introduced and accurately defined. It enables one to better understand the response of a magnetic soil to an EMI sensor, as well as the effect of soil inhomogeneity on soil compensation. The VoI is first defined as the volume producing a fraction of the total response of a homogeneous half-space. As this basic definition is not appropriate for sensor heads with intrinsic soil compensation, a generalized definition is then proposed. These definitions still do not yield a unique VoI, and a constraint must be introduced to reach uniqueness. Two constraints are investigated: one yielding the smallest VoI and the other one the layer of influence. Those two specific volumes of influence have a number of practical applications which are discussed. The smallest VoI is illustrated for typical head geometries, and we prove that, apart from differential heads such as the quad head, the shape of the smallest VoI is independent of the head geometry and can be computed from the far-field approximation. In addition, quantitative head characteristics are provided and show-among others-that double-D heads allow for a good soil compensation, assuming, however, approximate homogeneity over a larger volume of soil. The effect of soil inhomogeneity is further discussed, and a worst case VoI is defined for inhomogeneous soils.