The utilization of signal processing techniques in nondestructive testing, especially in ultrasonics, is widespread. Signal averaging, matched filtering, frequency spectrum analysis, neural nets, and autoregressive analysis have all been used to analyze ultrasonic signals. The Wavelet Transform (WT) is the most recent technique for processing signals with time-varying spectra. Interest in wavelets and their potential applications has resulted in an explosion of papers; some have called the wavelets the most significant mathematical event of the past decade. In this work, the Wavelet Transform is utilized to improve ultrasonic flaw detection in noisy signals as an alternative to the Split-Spectrum Processing (SSP) technique. In SSP, the frequency spectrum of the signal is split using overlapping Gaussian passband filters with different central frequencies and fixed absolute bandwidth. A similar approach is utilized in the WT, but in this case the relative bandwidth is constant, resulting in a filter bank with a self-adjusting window structure that can display the temporal variation of the signal's spectral components with varying resolutions. This property of the WT is extremely useful for detecting flaw echoes embedded in background noise. The detection of ultrasonic pulses using the wavelet transform is described and numerical results show good detection even for signal-to-noise ratios (SNR) of -15 dB. The improvement in detection was experimentally verified using steel samples with simulated flaws.

Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection

Ultrasound beams propagating in biological tissues undergo distortions due to local inhomogeneities of the acoustic parameters and the nonlinearity of the medium. The spectral analysis of the radio-frequency (RF) backscattered signals may yield important clinical information in the field of tissue characterization, as well as enhancing the detectability of tissue parenchymal diseases. Here, the authors propose a new tissue spectral imaging technique based on the wavelet packets (WP) decomposition. In a conventional ultrasound imaging system, the received echo-signals are generally decimated to generate a medical image, with a loss of information. With the proposed approach, all the RF data are processed to generate a set of frequency subband images. The ultrasound echo signals are simultaneously frequency decomposed and decimated, by using two quadrature mirror filters, followed by a dyadic subsampling. In addition, to enhance the lesion detectability and the image quality, the authors apply a nonlinear filter to reduce noise in each subband image. The proposed method requires simple additional signal processing and it can be implemented on any real-time imaging system. The frequency subband images, which are available simultaneously, can be either used in a multispectral display or summed up together to reduce speckle noise. To localize the different frequency response in the tissues, the authors propose a multifrequency display method where 3 different subband images, chosen among those available, are encoded as red, green, and blue intensities (RGB) to create a false-colored RGB image. According to the clinical application, different choices can evidence different spectral proprieties in the biological tissue under investigation. To enhance the lesion contrast in a grey-level image, one of the possible methods is the summation of the images obtained from narrow frequency subbands, according to the frequency compounding technique. The authors show that by adding the denoised subband images created with the WP decomposition, the contrast-to-noise ratio in 2 phantom images is largely increased.

Frequency decomposition and compounding of ultrasound medical images with wavelet packets

This article deals with the monitoring of the composite wing skin-to-spar joint in unmanned aerial vehicles using ultrasonic guided waves The study investigates simulated wing skin-to-spar joints with two different types of bond defects, namely poorly cured adhesive and disbonded interfaces The bond-sensitive feature considered is the ultrasonic strength of transmission through the joints The dispersive wave propagation problem is studied numerically by a semi-analytical finite element method that accounts for viscoelastic damping, and experimentally by ultrasonic testing that uses highly durable, flexible macro fiber composite transducers The discrete wavelet transform is also employed to de-noise and compress the ultrasonic measurements Both numerical and experimental tests confirm that the ultrasonic strength of transmission increases across the defected bonds

Health Monitoring of UAV Wing Skin-to-spar Joints using Guided Waves and Macro Fiber Composite Transducers:

A new acoustic nondestructive method using Lamb waves as a probe is presented. These waves are generated and received by an ElectroMagnetic Acoustic Transducer (EMAT). The position of flaws in the structure under test is computed from the time of arrival of the main peak of the reflected signal. Due to the noisy nature of the received signal, we use a wavelet transform algorithm to extract the required time information. The main advantage of such a multi-scale method of signal analysis is to be suitable for peak detection problems especially in highly noisy environments. We explain how we proceed to do the feature extraction, and we propose two methods for reconstructing the image of the inspected structure. Results of real-world ultrasonic Lamb waves signal analysis are presented. In addition, to test the noise robustness of the method, the case of synthetic noisy signals is also treated.

Wavelet-transform-based method of analysis for Lamb-wave ultrasonic NDE signals

Wavelet based noise suppression technique and its application to ultrasonic flaw detection.

The wavelet transform is applied to the analysis of ultrasonic waves for improved signal detection and analysis. In instances where the mother wavelet is well defined, the wavelet transform has relative insensitivity to noise and does not need windowing. Peak detection of ultrasonic pulses using the wavelet transform is described and results show good detection even when large white noise was added. The use of the wavelet transform to extract the frequency dispersion relation of the Lamb wave velocity is also described. The two-dimensional wavelet transform allows for both time and frequency analysis, thus making it particularly suitable for dispersion studies. Experimental and numerical results show the superior performance of the wavelet transform signal processor

Application of wavelet transform signal processor to ultrasound

Metallic coatings are produced for various purposes, and methods employed for testing their quality vary accordingly. Many tests have been developed in the past to determine the various properties of the coatings. Wear-resistance tests are commonly carried out on metallic deposits, plated specifically as a protection for the metal substrate against wear and erosion. A typical example is chromium plated on steel substrates.

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=3119&context=qnde

Characterization of Surfaces and Coatings Using Laser-Generated Ultrasonic Surface Waves

The Rayleigh or surface wave velocity in a metallic coating electro-deposited on steel was measured and an experimental correlation was found between the velocity and the hardness of the coating. Since qualitative coating properties are commonly inferred from hardness tests, this result suggests the utilization of nondestructive surface ultrasonic velocity measurements to evaluate the coating hardness over regions which are inaccessible to conventional hardness tests, or where it is not possible to allow a hardness indentation. Here we propose a nondestructive ultrasonic technique to evaluate the hardness of electrodeposited chromium coatings, based on the empirical relationship we have relating hardness and Rayleigh velocity. In view of available experimental evidence of relationship between surface hardness and Rayleigh velocity in other bulk metals this relationship should be investigated in other coatings as well.

/pdf/rayleigh-velocities-for-the-evaluation-of-coating-hardness-161wpfz8vc.pdf

S. C. Schroeder

Papers

Application of wavelet transform signal processor to ultrasound

Characterization of Surfaces and Coatings Using Laser-Generated Ultrasonic Surface Waves

Rayleigh velocities for the evaluation of coating hardness