Research Of Pulsed Eddy Current Nondestructive Testing Based On FPGA For Hardness

The Pulsed Eddy Current test, as one of the common Nondestructive Testing, not only can be used to detect the thickness of the coat on the surface of the conductor, the ingredients of the conductor, the state of the crystal in the conductor, and some others physical parameters, but also can be used to identify the defect and confirm the shape, size, distributing, tendency of the defect in the conductors or in the constructers. And because of the characteristic of the actuator in the frequency, PEC has a higher efficiency and accuracy. Thus it has wide potential application in modern industry.Electromagnetic nondestructive testing on the quality of steel has been studied for many years and acquired a great deal of achievement. However there are many problems in the testing of hardness and cracks, and mess problem of work pieces. For example the traditional nondestructive testing is difficult for the hardness gearwheel roughcast, and the traditional artificial test means is comparative slowly.The dissertation starts by introducing the fundamental theory of PEC. we designed and built a PEC system to detect metal hardness. The system consists of two parts. one is the PC-based hardware, the other is software implement. The system contains four important components. They are impulse excitation, probe, process of handling data and LCD display. Because there are a lot of factors influencing eddy current, signal processing becomes very hard. The system is based on FPGA. It makes the signal generation and the signal acquisition using one circuit, which enhances the accurate of signal processing. The principal component analysis method is used to eliminate the noise, get the characteristic value of the signal and build regression equation. By means of least square method, the hardness of steel and iron can be identified. The result indicates that the getting hardness of detected steel and iron become more accurate and faster, making use of FPGA as the platform, PEC as active source and PCA as a method for signal processing.