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Depth-Focused Waveform Based on SHEPWM Method for Ground-Airborne Frequency-Domain Electromagnetic Survey

机译:基于SHEPWM方法的深度聚焦波形用于地面机载频域电磁测量

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摘要

The ground-airborne frequency-domain electromagnetic (GAFDEM) survey is a mixture of ground and airborne electromagnetic methods with a source on the ground and a magnetic field receiver in the air. The technique probes different depths of the earth by transmitting waveforms at different frequencies. Therefore, multiple closely spaced frequencies are needed when surveying a specific target depth in detail. However, in the existing GAFDEM systems using a square wave or a 2(n) pseudorandom wave, the ground source needs to transmit more sets of waveforms with different fundamental frequencies in more flights to improve the vertical resolution for the same observed line, which will seriously reduce the exploration efficiency. In this paper, we design a depth-focused waveform to solve this problem based on a new full-cycle asymmetrical selective harmonic elimination pulse width modulation (SHEPWM) method. In the SHEPWM method, we obtain a desired spectrum by directly controlling the switching angles of a binary sequence with an artificial neural network algorithm. In our study, we first provide the basic theory and method for waveform design. Then, we realize the depth-focused waveform and pseudorandom waveform via simulation. Next, we employ the depth-focused waveform into practice and compare it with the 2n pseudorandom wave in a GAFDEM field survey. The test shows that the survey result with a depth-focused waveform has a higher vertical resolution and efficiency.
机译:地面机载频域电磁(GAFDEM)调查是地面和机载电磁方法的混合,地面上有信号源,空中有磁场接收器。该技术通过以不同的频率传输波形来探测地球的不同深度。因此,在详细测量特定目标深度时,需要多个紧密间隔的频率。但是,在现有的使用方波或2(n)伪随机波的GAFDEM系统中,地源需要在更多的飞行中传输更多组具有不同基频的波形,以提高同一条观测线的垂直分辨率,这将严重降低勘探效率。在本文中,我们基于新的全周期非对称选择性谐波消除脉冲宽度调制(SHEPWM)方法,设计了深度聚焦波形来解决此问题。在SHEPWM方法中,我们通过使用人工神经网络算法直接控制二进制序列的切换角度来获得所需频谱。在我们的研究中,我们首先提供波形设计的基本理论和方法。然后,通过仿真实现了深度聚焦波形和伪随机波形。接下来,我们将深度聚焦波形付诸实践,并在GAFDEM现场调查中将其与2n伪随机波进行比较。测试表明,深度聚焦波形的测量结果具有较高的垂直分辨率和效率。

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