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The exploration target at different depths through the ground-airborne frequency domain electromagnetic method (GAFDEM) is detected by transmitting waveforms at different frequencies. When taking these different depths into detail, arbitrarily distributed frequencies are needed. However, the current transmitting waveforms are mostly in a fixed frequency ratio or frequency difference, which fails to meet the requirements of exploration accuracy and efficiency at the same time. Therefore, as a solution to this problem, this paper proposes a transmitting waveform design method based on selective harmonic eliminated pulse width modulation (SHEPWM) technology. In the SHEPWM method, three transmitting waveforms with the desired spectrum are obtained by directly controlling the switching angles of a binary sequence with an artificial neural network algorithm. Firstly, our study puts forward the basic theories and principles of the full-periodic asymmetric SHEPWM waveform. Secondly, the study, through simulation, realizes the pseudorandom, depth-focused, and layer-identification waveform with different detection depths. Finally, the application of the proposed SHEPWM waveform to the geological survey in Kaili City, Guizhou Province, proves the correctness and feasibility of this proposed method. [ABSTRACT FROM AUTHOR]

Guaranteeing the quality of the transmitting current under low switching frequency conditions is the crucial point in the helicopter transient electromagnetic (HTEM) system which affects the efficiency and exploration accuracy. HTEM requires high efficiency and low switching loss of the inverter power supply due to the facts that HTEM uses air-launched and air-received measurement methods, and the power storage capacity of the airborne transmitting system is limited. Paradoxically, low switching frequency directly affects the transmitting waveform quality and thereby affects the detection accuracy. In this study, we present a semiperiodic mirror symmetry selective harmonic elimination pulse width modulation (SHEPWM) based on the subsection control approach to balance transmitting current quality and switching loss. In the SHEPWM method, the semiperiodic mirror symmetry SHEPWM nonlinear equations are established by the time frequency domain information of the inverter output voltage and resolved by the artificial neural network (ANN) algorithm to attain switching time sequence of desired transmitting current. The simulation and experimental results verify the effectiveness of the SHEPWM subsection control strategy, which can reduce the switching loss while ensuring the current waveform quality and detection accuracy. [ABSTRACT FROM AUTHOR]