Wavelet based signal analysis of pulsed eddy current signals
نویسندگان
چکیده
This paper deals with response signals processing in eddy current non-destructive testing. Non-sinusoidal excitation is utilized to drive eddy currents in a conductive specimen. The response signals due to a notch with variable depth are calculated by numerical means. The signals are processed in order to evaluate the depth of the notch. Wavelet transformation is used for this purpose. Obtained results are presented and discussed in this paper. Streszczenie. Praca dotyczy sygnałów wzbudzanych przy nieniszczącym testowaniu za pomocą prądów wirowych. Przy pomocy symulacji numerycznych wyznaczono sygnały odpowiedzi dla niesinusoidalnych sygnałów wzbudzających i defektów o różnej głębokości. Celem symulacji jest wyznaczenie zależności pozwalającej wyznaczyć głębokość defektu w zależności od odbieranego sygnału. W artykule omówiono wykorzystanie do tego celu transformaty falkowej. (Analiza falkowa impulsowych prądów wirowych)
منابع مشابه
transformer differential protection using the fault-generated high-frequency transient components
Power transformers are the most important components of a power system, so their protection is a critical issue. This paper proposes a novel and efficient algorithm based on the high-frequency components of the differential current signal to discriminate between the magnetizing inrush currents and the internal faults. After detecting the over-current in the differential current signals, samples...
متن کاملComparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition
Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...
متن کاملA COMPARATIVE ANALYSIS OF WAVELET-BASED FEMG SIGNAL DENOISING WITH THRESHOLD FUNCTIONS AND FACIAL EXPRESSION CLASSIFICATION USING SVM AND LSSVM
This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...
متن کاملPulsed eddy current empirical modeling
The pulsed eddy current responses to varying material thickness and conductivity are modeled using an electrical circuit ideal transformer non-linear model. The Levenberg-Marquardt algorithm is used to curve fit the experimental signal to the model. The resulting synthetic signal is examined for its ability to preserve experimental signal features such as lift-off point of intersection (LOI), a...
متن کاملAutomatic Classification and Characterization of Hidden Corrosion Using Pulsed Eddy Current Data
Detection and characterization of the material loss due to corrosion in aircraft fuselage joints plays an important role in life management of aging aircraft. Pulsed eddy current has been shown to effectively characterize hidden corrosion in lap splices. However, variation of the probe lift-off and interlayer gap can cause false indications or inaccuracy in quantification. This paper presents t...
متن کامل