Quantitative Nondestructive Testing Research Articles

Gain-scale ultrasonic properties measurement of cast austenitic stainless steel

Ultrasonic properties of coarse-grained austenite are critical to the quantitative nondestructive testing and evaluation of cast austenitic stainless steel (CASS). However, the orientation-dependent information is quite difficult to acquire from polycrystalline materials. Here a grain-scale measurement technique was developed based on electron backscatter diffraction (EBSD) and water-immersion focusing ultrasonic testing. 2-D angular distributions of the longitudinal wave velocity and attenuation coefficient in (0 1 0) plane were obtained respectively, which were correlated with the top-view and side-view orientation of columnar austenite grains. 〈1 0 1〉 orientation presented the largest velocity 6210 m/s and the smallest attenuation coefficient 1.9 dB/mm, while 〈0 0 1〉 reversed. The data deviation and universality were discussed.

Quantitative nondestructive testing of wire rope based on pseudo-color image enhancement technology

ABSTRACTDetection of magnetic flux leakage (MFL) is widely used in nondestructive testing (NDT) of wire rope. We built and tested an MFL measuring device based on unsaturated magnetic excitation to address the problems of large volume, low accuracy and inconvenience of the traditional MFL instruments for locating and quantifying broken wires in wire ropes. We employed a pseudo-color imaging protocol to convert the MFL information to a pictorial representation. Localization of the breaks in the wire utilized the maximum modulus method. The color moment, statistical texture features, and spectral texture features were extracted from the image, revealing a network of broken wires, which could be localized and quantified. Testing showed that the device has high-detection accuracy and could detect small broken wires. Compared with traditional wire inspection devices, it has the advantages of small size, light weight and portability. We showed that pseudo-color image enhancement can effectively improve the recognition rate of broken wires and reduce the recognition error.

Quantitative Nondestructive Testing of Wire Rope Using Image Super‐Resolution Method and AdaBoost Classifier

Magnetic flux leakage (MFL) detection is commonly employed to detect wire rope defects. However, nondestructive testing (NDT) of a wire rope still has problems. A wire rope nondestructive testing device based on a double detection board is designed to solve the problems of large volume, complex operations, and limited circumferential resolution due to sensor size in traditional devices. The device adopts two magnetic sensor arrays to form the double detection board and collects the MFL data of the magnetized wire rope. These sensors on the double detection board are staggered and evenly arranged on the circumference of the wire rope. A super‐resolution algorithm based on interpolation uses non‐subsampled shearlet transform (NSST) combining principal component analysis (PCA) and Gaussian fuzzy logic (GFL) and fuses the data of double detection board to improve the resolution and quality of defect images. Image quality measurement and comparison experiments are designed to verify that defect images are effectively enhanced. An AdaBoost classifier is designed to classify defects by texture features and invariant moments of defect images. The experimental results show that the detection device not only improves the circumferential resolution, but also the operation is simple; the resolution and quality of the defect images are improved by the proposed super‐resolution algorithm, and defects are identified by using the AdaBoost classifier.

Quantitative Nondestructive Testing of Wire Ropes Based on Features Fusion of Magnetic Image and Infrared Image

Magnetic flux leakage (MFL) detection is one of the most widely used and best performing wire rope nondestructive testing (NDT) methods for more than a decade. However, the traditional MFL detection has the disadvantages of single source of information, low precision, easy to miss detection, and false detection. To solve these problems, we propose a method of fusion recognition of magnetic image features and infrared image features. A denoising algorithm based on Hilbert vibration decomposition (HVD) and wavelet transform is proposed to denoise the MFL signal, and the modulus maxima method is used to locate and segment the defect. An infrared image acquisition system was designed to collect the infrared image of the surface of the wire rope. Digital image processing techniques are used to segment infrared defect images. The features of the MFL image and the infrared image are extracted separately for fusion. The fusion feature is input into the nearest neighbor (NN) algorithm for quantitative identification, and the same data are input into the backpropagation (BP) neural network for comparison verification. The experimental results show that the fusion of MFL features and infrared features effectively improves the recognition rate of wire rope defects and reduces the recognition error.

Application of Variational Mode Decomposition and k‐Nearest Neighbor Algorithm in the Quantitative Nondestructive Testing of Wire Ropes

In this paper, we present a nondestructive testing device for wire rope by unsaturated magnetic excitation as an alternative to existing magnetic flux leakage (MFL) detection devices. The existing devices are heavy and inconvenient and offer somewhat lower accuracy and low signal‐to‐noise ratios (SNRs). Our design implements variational mode decomposition (VMD) and a wavelet transformation to remove noise from the raw MFL signals. Grayscale images representing the denoised MFL data simplify visual interpretation of the results and location of defects in both axial and circumferential directions. Quantification of defects is enabled using a k‐nearest neighbor (KNN) algorithm to classify broken wires. Experimental results show that our design offers lighter weight, better convenience, and high sensitivity along with better removal of noise and more accurate classification of defects.

Nondestructive testing of objects of complex shape using infrared thermography: Determination of the spatiotemporal distribution of the irradiation heat flux

The existing inverse methods used to determine the heat flux density require that the forward problem and the problem domain (geometry) be known. In this paper, in order to determine the spatiotemporal heat flux density without knowing the real problem domain, we propose an approach based on temporal tracking of the thermal front. The proposed approach is particularly relevant when a three-dimensional formulation is adopted for nondestructive testing using infrared thermography. For such a formulation, heat flux density resulting from the external thermal stimulus is needed and must be determined to accurately characterize the defects and reconstruct the internal geometry of the inspected objects. The proposed approach uses only two inputs: the time-dependent temperature of the frontal surface recorded by an infrared camera and the 3D point cloud of the frontal surface collected by a 3D scanner. The method is evaluated numerically on an object of complex shape. We consider the case of pulsed thermal stimulus as well as the cases of unit step and modulated thermal stimuli. An experimental validation is performed on a cylindrical object submitted to a pulsed thermal stimulus and a modulated thermal stimulus. The results show the accuracy of the method which can easily be implemented as the initial step of the three-dimensional quantitative nondestructive testing of objects using infrared thermography.

MICROWAVE PROPAGATION IN TOOTH AND DENTAL DEFECT

INTRODUCTION:The most common method of conventional dental diagnosisinvolves X-rays, such as Radio Tomography (RT) or Computer Tomography (CT). Such methods are used for diagnosing pores in dental material that can lead to premature failure of dental material. Diagnosis by X-ray provides an objective analysis. However, repeated radiation from X-rays can cause biological damage to human tissues. From this point of view, there is a significant need to progress to quantitative non-invasive and non-destructive testing (NDT) methods to measure dental material and improve treatment options. This article focuses on applying microwave technology to characterize teeth and teeth replacements. Knowledge of microwave propagation in biomaterial with no defects, using a defined microwave frequency range, and subsequently comparing the result with defective material could provide a means of dental diagnosis without the risk of radiation for the patient, i.e. without X-ray. OBJECTIVES: The primary objective of this study was to examine microwave technology in the field of dental medical diagnosis as a new NDT method. METHODS: The basic concept of applying microwave technology to characterize teeth in dental diagnosis was examined using a basic algorithm designed in the MATLAB programming language. Tests used dielectric properties of tooth and tooth decay and propagated electromagnetic (EM) waves to show different characteristics of chosen materials.RESULTS: The analyses of frequency dependent reflection and transmission coefficients of the chosen material, specificallyteeth, atfrequency range 0 GHz to 30 GHz, computed differences between healthy and defective dental material.CONCLUSION: Thus, this could be used in providing a dental diagnosis without exposing patients to radiation, i.e. without X-ray. The next stage will involve creating a complete model of a jaw with teeth, and designing a sensor for crack detection for comparisons using this basic algorithm.

Methodology for the Stress Measurement of Ferromagnetic Materials by Using Magneto Acoustic Emission

Magneto acoustic emission (MAE) is a magnetic nondestructive testing (NDT) method that has been used in different fields for 30 years. MAE is a promising method for the early characterization of damage and the evaluation of the residual stress of ferromagnetic materials. However, this technique is still in its early stage and requires further development. The mechanism and influence factors of MAE are still under investigation. Quantitative NDT is difficult because of the lack of robust theoretical bases and models. In this study, we investigated the influence factors of MAE signals systematically and established a mathematical model to describe these influences. The special design of the specimen and the precise control of experimental conditions are the key points for obtaining reasonable experimental results and for developing the model. A methodology for stress assessment was developed on the basis of the proposed model and was verified by using the pure bending test. Results show that stresses within a measureable depth of 4 mm can be evaluated and that the maximum testing error is 30 %.

Partial least square regression: an analysis tool for quantitative non-destructive testing

The scanning of parts in eddy current testing can lead to a large amount of measurement data (predictors). Partial least square (PLS) regression is a mean to reduce the dimensionality of the subsequent inverse problem by projecting the predictors in a latent subspace of reduced dimension maximizing the covariance between the projection and the responses which have to be estimated. In a second step, a regression model is elaborated linking the responses to the latent variables. PLS was originally developed in the field of chemical analysis. In this paper, the PLS method is applied in the field of eddy current testing for the characterization of minute cracks. It is tested firstly on simulated data and then on experimental data. It is found that the reconstruction of the area of minute cracks is made possible by PLS.

An Efficient Numerical Scheme for Sizing of Cavity Defect in Metallic Foam From Signals of DC Potential Drop Method

Quantitative nondestructive testing is important to guarantee the integrity of metallic foam (MF) structures. To predict the profile of a cavity defect in an MF material, a database-type fast forward scheme is upgraded at first by introducing a kind of multimedium element (MME) for the efficient simulation of dc potential drop (DCPD) signals of MF with defect of complicated shape. Second, a code of the hybrid strategy combining the neural network and the conjugate gradient optimization method is proposed to obtain the size and the position parameters of the defect. Both simulated and measured DCPD signals are adopted to reconstruct the bubble defects in MF. The good consistency of the true and the reconstructed results demonstrated the validity of the new scheme. In addition, it is also proved that the updated database-type fast-forward scheme is efficient for the signal simulation of MF with defect of complicated shape with the help of MME, and the hybrid inverse strategy has a better numerical performance for the defect sizing.

Linear Polarization Method Research of Quantitative Detection Based on Concrete Reinforcement Corrosion

In order to achieve internal reinforcement of concrete bridges quantitative nondestructive testing, this paper has adopted linear polarization method to test reinforcement passivation in the pore solution of simulated concrete and corrosion current density value in the corrosion process under different external environments and has built calculation model for amount of reinforcement corrosion based on detection signal. That is to say a new idea, which makes the evaluation results more effective, has been put forward to efficiently correspond with reinforcement corrosion ratio with potential signal, and the quantification evaluation for damage of reinforced concrete can be carried directly. It has modified theoretical model and analyzed the error through weightlessness tests. The research result shows that the calculation model after modified can significantly improve the detection accuracy for the actual rate of reinforcement corrosion. CLC: TU528.33 Document code:

An approach to reduce lift-off noise in pulsed eddy current nondestructive technology

The pulsed eddy current (PEC) technique, as an emerging technique of the eddy current technique, has been used in engineering, such as aircrafts, oil/gas pipelines, nuclear steam pipes and high-speed rails, due to its richer information in time domain and frequency domain. However, the lift-off noise, introduced by varying coating thicknesses, irregular sample surface or movement of transducers, has a serious influence on the accuracy of the detection for the defects in these key structures. It greatly limits the application of PEC in quantitative nondestructive testing. In order to reduce the effect of the lift-off, the lift-off effect is analyzed theoretically and experimentally; based on the investigation of the relationship between the peak value of the difference signal and the lift-off, an approach to reduce the lift-off noise for detection the defect depth or width is proposed. In this approach, the defect depth and width are determined by the slope of the linear curve of the peak value of the difference signal and the lift-off. The proposed approach is verified by experiment and the results indicate that it can highly reduce the lift-off noise in the PEC technique. Therefore, it can be applied in characterization of the surface defects in sample with non-ferrous material.

Application of quantitative modal analysis for investigation of thermal degradation of microelectronic packages

The influence of high temperature storage on the properties of epoxy based materials in microelectronic packages was investigated by application of a quantitative modal analysis technique. An electromagnetic shaker in combination with scanning laser Doppler vibrometry was used to extract the alteration of the modal response of the components in relationship with the thermal aging time. Data analysis was accomplished by the error ratio (ER) method, modal assurance criterion (MAC) and determination of an aspect ratio (AR) using an image correlation technique. Increasing the storage time resulted in a higher degree of degradation which was reflected by an increase in the values of ER, MAC and the AR. Microstructural investigations confirmed that alteration of the modal response is related to the temperature dependent gradual degradation and modification of the properties of the packaging material which was supported by finite element analysis. This present work shows the feasibility of modal analysis as an efficient and quantitative non-destructive testing method for evaluation of degradation of electronic packages.

Characterizing Influence Parameters in Pulsed Phase Thermography for Defect Detection in Sheet Metal Parts

Pulsed phase thermography (PPT) is a common infrared technique for quantitative nondestructive testing and evaluation (NDT&E). PPT was initially applied in the aeronautical and aerospace engineering to the detection and quantification of defects in materials with either high or low thermal conductivity, such as aluminium and composite materials. This paper presents for the first time the application of PPT-technique for defect inspection in sheet metal parts, attempting to provide a solution for an alternative quality control rather than the traditional optical survey in the press shop. The inspected defects in this paper were produced in deep drawing cups, to effectively creating various crack lengths and depths respectively in both steel and aluminium alloys. The approach of the characterizing influence parameters is primarily based on the particular parameters of the PPT-technique. These parameters were firstly classified into various categories, and a DoE model was subsequently designed to define the required experiments for a process window analysis. According to the defined process window, more accurate conclusions of defect detecting effects were achieved. Studies in the paper present the fundamental perceptions for defect inspecting in the sheet metal parts by using PPT-technique in the press shop.

Ultrasonic arrays for quantitative nondestructive testing an engineering approach

The Ultrasonic Pulse-Echo inspection method is extremely capable of detecting cracks that limit the structural integrity of loaded technical components and systems. However, the applied principles of ultrasonic material testing do not in general allow the characterization of flaws and the required measurement of crack dimensions. Appropriate wave field data sampling at the scanned surface with the subsequent field reconstruction improves both the resolution and the contrast sensitivity of inspection results. We use arrays with elements adapted for the inspection task with an optimized arrangement and element apertures of point source character. First results have been received applying linear arrays that are promising for the quantitative assessment of flaws by high-resolved high contrast imaging of inspection results in real-time.

Quantitative Non-Destructive Testing of Metallic Foam Based on Direct Current Potential Drop Method

To detect cavity defects in metallic foam and to predict its size, a quantitative nondestructive testing (NDT) method based on the direct current potential drop (DCPD) technique was proposed and validated in this study. At first, an efficient forward analysis scheme was introduced to simulate the DCPD signals. In order to obtain measured signals for defect reconstruction, specimens of practical aluminum metal foam with defects of different sizes were fabricated and inspected then by using a DCPD testing system. Third, an inverse analysis scheme in model based optimization category was proposed and implemented for sizing cavity defects in the metal foam. Through inversion of both simulated and measured DCPD signals, the validity of both the forward and the inverse analysis schemes was demonstrated for the quantitative DCPD evaluation of the metallic foam.

Square pulse thermography in frequency domain as adaptation of pulsed phase thermography for qualitative and quantitative applications in cultural heritage and civil engineering

A methodical approach for qualitative and quantitative non-destructive testing of near-surface structures in civil engineering (CE) with active thermography is presented. It adopts the non-destructive testing (NDT) method of pulsed phase thermography (PPT) for the special requirements of CE and cultural heritage. The concept might be understood as a square pulse thermography (SPT) in frequency domain or an amplitude-expanded PPT with square pulse heating. After a discussion of the material spanning concept and qualitative results in cultural heritage a new approach for quantitative non-destructive testing (NDT) of near-surface structures in CE with active thermography is introduced and tested by investigations on concrete specimen with artificial defects. It is based on the thermal diffusivity of the material and the characteristic frequency of the first extrema of phase and amplitude contrast and aims at complementing the established approaches for defect depth calculation for measurements with long heating and observation times. It should be easily extendable to other fields of application.

Quantitative Nondestructive Evaluation of the Aluminum Alloy Using the Sheet Type Induced Current and the Single Sensor Scanning

Single sensor scanning (hereafter SSS) used to inspect cracks on paramagnetic materials can measure the distribution of the root mean squared value (RMS) of the magnetic field around crack tips quantitatively when sheet type current is induced on the specimen. The vertical direction magnetic field alternates to the surface of the crack tips because the sheet type induced current on the specimen is distorted by the existence of the crack in an SSS system. The RMS distribution of the magnetic field, which can be measured by using SSS, depends on the crack size and shape, so it can be used to evaluate a crack size quantitatively. An algorithm of quantitative nondestructive testing and evaluation of cracks of various shapes and sizes on the aluminum alloy, Al7075 is proposed in this paper.

Enhancements of eddy current testing techniques for quantitative nondestructive testing of key structural components of nuclear power plants

In this paper, studies on upgrade of eddy current testing (ECT) techniques for inspection of stress corrosion cracks (SCC) in key structural components of a nuclear power plant are reported. Access and scanning vehicle (robot), advanced probes for steam generator (SG) tube inspection, developments and evaluations of new ECT probes for welding joint, and ECT-based crack sizing technique are described, respectively. Based on these techniques, it is demonstrated that ECT can play as a supplement of ultrasonic testing (UT) for the quantitative inspection of welding zone. It is also proved in this work that new ECT sensors are efficient even for inspection of a stainless steel plate as thick as 15 mm.

Solution of identification inverse problems in elastodynamics using semi-analytical sensitivity computation

The purpose of this work is to study a class of inverse problems that arises in solid mechanics areas such as quantitative non-destructive testing (QNDT) or shape optimization. The technique is based on the boundary integral equations (BIEs) used in the classical boundary element method (BEM), which are differentiated semi-analytically with respect to variations of the boundary geometry and used in an iterative search algorithm. The extension of this strategy is presented here for the case of elasticity in dynamics using the displacement or singular BIE, which allows to apply this strategy to QNDT problems based on vibrations or ultrasonics. The central point is the evaluation of the capability of solving numerically a QNDT problem such as the location and characterization of cavity and inclusion-type defects by measuring the dynamic response at an accessible boundary of the specimen. To test this capability, comprehensive convergence tests are made for the badness of the initial guess, the amount of supplied measurements, and simulated errors on measurements, geometry, elastic constants and frequency.