Mingrui Zhao;Xiaokang Yin;Martin Mwelango;Guangqiang Rong;Pengcheng Ma;Jiaxing Huang;Xin’an Yuan;Wei Li
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引用次数: 0
Abstract
Insulator-conductor hybrid structures are widely used in various engineering fields. However, the differing properties of the materials comprising these structures result in different types of defects, posing challenges for comprehensive nondestructive testing and evaluation. This research proposes a dual-frequency electromagnetic sensor capable of inspecting both insulating and conductive materials. By employing a superposition of high-frequency and low-frequency signals for excitation, the sensor simultaneously performs detection in two modes, namely capacitive and inductive. The sensor’s frequency response characteristics are optimized through the incorporation of compensating inductors and capacitors, significantly enhancing sensitivity to capacitance while maintaining eddy current detection capability. This sensor addresses the challenges posed by the complex structure and rigorous timing requirements of conventional dual-mode sensor systems. Furthermore, a compact signal processing system was developed. Finally, experiments were conducted using the developed dual-frequency detection system to detect various types of defects, verifying its effectiveness and feasibility. The experimental results demonstrate that the characteristics of the two frequencies are complementary, and the developed system effectively detects and distinguishes between material-deficient defects in plexiglass and both material-deficient defects and cracks in aluminum alloys, thus fulfilling the requirements for identifying and locating defects in hybrid structures in practical applications.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.