A Novel On-Site-Real-Time Method for Identifying Characteristic Parameters Using Ultrasonic Echo Groups and Neural Network

On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.

A novel approach to identifying the ultrasonic echoes for inspecting well cementing quality

In this paper, it is presented that an approach based on Continuous Wavelet Thansform(CWT) and Fourier Transform(FT) for identifying ultrasonic echoes in inspecting oil well cementing quality. First, CWT is used to process echo signals. Then spectra of the processing results in some specilic scale-time segments are calculated as pattern features. The research results show that theoretical calculations basically agree with experimental results. Compared with the aPproach based on the spectra or Discrete Wavlet Transform, our approach has advantages of fine analyzing scales, stable features and high recognizing rate. It is very suitable to identify echo signals whose spectra vary with time.

Identification of Denatured Biological Tissues Based on Improved Variational Mode Decomposition and Autoregressive Model during HIFU Treatment

During high-intensity focused ultrasound(HIFU)treatment,the accurate identification of denatured biological tissue is an important practical problem.In this paper,a novel method based on the improved variational mode decomposition(IVMD)and autoregressive(AR)model was proposed,which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment.Firstly,the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions(IMF).The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising.Then,the AR model was introduced to improve the recognition rate of denatured biological tissues.The AR model order parameter was determined by the Akaike information criterion(AIC)and the characteristics of the AR coefficients were extracted.Finally,the optimal characteristics of the AR coefficients were selected according to the results of receiver operating characteristic(ROC).The experiments showed that the signal-to-noise ratio(SNR)and root mean square error(RMSE)of the reconstructed signal obtained by IVMD was better than those obtained by variational mode decomposition(VMD).The IVMD-AR method was applied to the actual ultrasonic scattered echo signals during HIFU treatment,and the support vectormachine(SVM)was used to identify the denatured biological tissue.The results show that compared with sample entropy,information entropy,and energy methods,the proposed IVMD-AR method can more effectively identify denatured biological tissue.The recognition rate of denatured biological tissue was higher,up to 93.0%.

Temperature and pressure characteristics of ultrasonic transducer and the amplitude spectra correction of echoes

In this paper,the transfer functions of ultrasonic transducers under different temperatures are imitated according to Mason equivalent circuit. The relevant experiments are carried out. The results show that the transfer characteristic of ultrasonic transducer varies with temperature and pressure. Therefore, we present an approach to correct the amplitude spectra of ultrasonic echoes got in different temperature and pressure environmeots. The theoretical simulation and experimental results prove that the approach is simple, effective and practical.

Optimization and Parameters Estimation in Ultrasonic Echo Problems Using Modified Artificial Bee Colony Algorithm

The patterns of ultrasonic backscattered echoes represent valuable information pertaining to the geometric shape, size, and orientation of the reflectors as well as the microstructure of the propagation path. Accurate estimation of the ultrasonic echo pattern is essential in determining the object or propagation path properties. This paper proposes a parameter estimation method for ultrasonic echoes based on Artificial Bee Colony （ABC） algorithm which is one of the most recent swarm intelligence based algorithms. A modified ABC （MABC） algorithm is given by adding an adjusting factor to the neighborhood search formula of traditional ABC algorithm in order to enhance its performance. The algorithm could overcome the impact of different search range on estimation accuracy to solve the multi-dimensional parameter optimization problems. The performance of the MABC algorithm is demonstrated by numerical simulation and ultrasonic detection experiments. Results show that MABC not only can accurately estimate various parameters of the ultrasonic echoes, but also can achieve the optimal solution in the global scope. The proposed algorithm also has the advantages of fast convergence speed, short running time and real-time parameters esti- mation.

Classification of flaw by adaptive filtering deconvolution of ultrasonic backscattering echo

A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the transducer on echoes is reduced greatly and the flaw features stand out more clearly in the deconvolved echoes than in flaw echoes themselves. flaw echo signals of 18 flaw samples are processed by adaptive filtering deconvolution. As a result, flaws are classified successfully

Applications of Non-destructive Tests for Diagnosis of Heritage Buildings:Case Studies from Singapore and Malaysia

Non-destructive tests have been increasingly used in historic buildings not only for pre-restoration investigation but also as useful tools to evaluate the effectiveness of eventual interventions.These tests can complement and supplement destructive tests like laboratory analysis of extracted samples as long as a sound sampling plan has been put in place to commensurate with the pattern and extent of dilapidation and materials distribution.Common methods employed in projects in Singapore and Malaysia include the infrared thermography,ground penetrating radar,microwave moisture tomography and ultrasonic pulse echo tomography.The paper discusses about a selection of case studies,demonstrating the application of various techniques for the identification of hidden details,defects and deterioration,and moisture detection.