In Ultrasonic NDT, the background noise by the unresolved scatterers such as grain boundaries and other microstructure, and electrical noise by the ultrasonic defect detector often masks the flaw signal, creating a hindrance to detection.
To make the flaws more clear in the ultrasonic image, several suitable ways of ultrasonic image processing are discussed based on the particularity of ultrasonic imaging.
It was difficult to identify the ultrasonic defect signals of coarse grained materials, so a wavelet analysis method was applied to reduce the grained noise based on the discussion of the frequency spectrum distribution of the defect signals and grained noise.
Two application examples show the effectiveness of DSP in increasing the signal to noise ratio and resolution of signal and realizing real time processing for testing.
Korolev, the oldest worker of the Central Research Institute for Heavy Machinery (TsNIITMASh), has told about some episodes on the initial stages of the ultrasonic NDT development.
Today, the TOFD procedure is used for operational inspections or quality control of structures during production instead of routine radiography and ultrasonic NDT procedures [1].
A novel method of time-frequency analysis, wavelet-packet atomic decomposition based on the matching-pursuit (MP) algorithm, is proposed for improvement of ultrasonic flaw detection during ultrasonic NDT.
This paper introduces promiseful applications of a new wave type so called ultra sonic creeping wave in NDT. Tests have been done on the methods to locate defects and their qualitative evaluation. Some main conclusions have been given out.
in view of the difficulty of conventional ultrasonic nondestructive testing(UNDT) method inspecting the defects in austenitic steel weld, the portable ultrasonicP-scan imaging system is developed by combining of computer, signal processing withUNDT.This system has the advantages of high defect resolution, accurate positioning.clear image and easy operation. After the experiment of it in the field spot, this systemhas the wide application prospects in petrochemical, nuclear plant and pressure vessel.
It was difficult to identify the ultrasonic defect signals of coarse grained materials, so a wavelet analysis method was applied to reduce the grained noise based on the discussion of the frequency spectrum distribution of the defect signals and grained noise. The experimental results show that the SNR can be improved highly by this method.