نشریه فناوری آزمون های غیرمخرب
سال دوم شماره 9 (پیاپی 10، پاییز و زمستان 1400)

With the increasing development of additive manufacturing processes and the production of more precise products using different materials, parts made from these processes are increasingly being used as end products. In this paper Fused Deposition Modeling (FDM) printed parts are studied and tested by Active IR Thermography method. to this regard, Three PLA samples are printed with different infill rates. The filament burnout defect was produced during the printing process. The excitation performed by means of two halogen lamps, directly radiated to the samples. Two different set-ups including transmission and reflection modes are selected. The Thermal images are captured during heating as well as cooling time and all the defects are revealed in the thermal images. Results indicated that the proposed Active IR Thermography, is capable in detection of filament burnout defect in this parts. Moreover, it has been indicated that the reflection method leads to better outcomes in comparison with the transmission mode.

The main focus of this article is to Analysis of Pressure Vessel Behaviour by Acoustic Emission Method and Ability of Experimental methods in Cylinder defects detection By Strain Measuring and obtaining the pressure limit FRP composite tanks.In this Study, for performing experiments, first, the experimental set-up was prepared by installing emission acoustic sensors and strain gauges on the tank; then, the behavior of the Pressure Vessel was investigated by data of acoustic emission method and the strain gauge data were investigated. Observed that The studied composite tank was in the safe range at a pressure less than 2 bar and the mentioned tank leaks with holes up to 2mm did not high risk for destructive deformation & defect spread; if it has other operating conditions, it does not need to be monitored up to pressures above 5 bar where the strain ratio out of the linear phase and at higher pressures, other failure mechanisms, such as elastic-plastic deformation, cracking, etc are also added to the signals and should be studied and this means the need to monitor the tank at higher pressures or refuse to use it.The result is that the acoustic signals are mostly produced by failure mechanisms. Experimentally based on the volume and characteristics of the signals and the obtained data showed that the acoustic emission activity in a non-defective cylinder is much lower compared to a defective cylinder. Usually, the signal increase at the beginning of the leak, and the leak is detectable.

Coating metals as a technique to increase the corrosion resistance of industrial parts is very practical and common in various industries, especially oil and gas, petrochemical and marine industries. Corrosion characterization in coated metals is a major challenge in the field of Non-destructive testing (NDT). In this work, 20 flat bottom holes (FBH) with diameters of 10, 8, 6, 4, 2 mm were drilled to distances from the test piece surface ranging between 0.5 and 2 mm on the St37 steel plate with epoxy coating simulate corrosion defect. Step heating thermography (SHT) has been applied to evaluate corrosion defects. Median filter and Gaussian low-pass filter are used for noise reduction and smoothing the thermal images. Principal component analysis (PCA) has been applied to raw thermal images to process thermographic signals and improve the defect detection capability. Results showed that after applying signal processing methods, the number of the detected defects increased from 12 to 14 holes. Also the signal-to-noise ratio (SNR) has more than quadrupled.

This study aims to design and manufacture a crack detection/measurement system for railway lines. Rolling contact fatigue cracks are among the most significant railway surface defects and most failures and rail fractures arise from this type of defect. In case of well-timed detection of these cracks, the overgrowth of them and subsequently rail fracture could be avoided by preventive grinding. In this study, the capability of two conventional non-destructive methods for crack detection, including Magnetic Flux Leakage (MFL) and Eddy Current (EC) tests, have been evaluated. The results indicate that, despite capability of detecting the position and depth of cracks, the MFL method has several limitations, such as the high weight of the yoke and high field strength, making the probe move harder over the rail. Instead, the EC probes are very light and excite the rail surface with a weak magnetic field, providing a higher scanning speed. Besides, EC probes indicate high accuracy and reliability for determination the location and depth of cracks. In RDD-S11, which is currently being used in lines one and two of Mashhad Urban Railway Company to detect three common defects, the proposed EC sensors have been used.

In this laboratory study, a mixing design was made of ordinary concrete containing Portland cement with a grade of 500 kg/m3 and a mixing design was made of alkaline concrete based on slag from the composing furnace. In order to investigate the mechanical properties, a non-destructive test was performed to determine the velocity of ultrasonic vibrations in concrete at 21 and 600 °C at a 90-day curing age. In order to evaluate the microstructure of concrete and verify the results of ultrasonic test, compressive strength test and scanning electron microscopy imaging was performed on concrete samples. The results showed a decrease in the speed of ultrasonic vibrations after applying high temperature (600 °C) in concrete, so that in ordinary concrete and hard concrete, the deceleration rate was 44.79% and 40.58% in the results after and before, respectively. Obtained by applying heat. In this regard, the passage speed of ultrasonic vibrations in ferrous concrete was lower than ordinary concrete, so that at 21 and 600°C, the percentage of velocity drop in ferrous concrete compared to conventional concrete is equal to 10.48 and 3.66%, respectively. Was obtained. The results of the compressive strength test and the images obtained from the scanning electron microscope, in coordination and overlap with the results of the ultrasonic vibration test in concrete were subjected to 21 and 600°C.

Identifying the internal components of old specimens such as antique guns is very important to restoration experts in terms of the internal design and their connections. It is also important to check the safety of the weapon in terms of whether it is full or empty or how the cartridges are positioned. In this case study, radiography testing was used to investigate the condition of two antique guns, revolver and colt. Image processing techniques based on the curvelets was used to for better evaluation of the radiographs. The results show that radiography provides good information in revealing the internal structure and the parts arrangements in the two weapons. Their processed images also provide more detailed and accrued information. Experts have confirmed the radiographic information in the two guns and their internal structure and defects and and also confirmed the efficiency of the “curvelet” wavelet method for the definition increasing of the images up to 25%.

Surface hardening is one of the common methods to improve the surface properties of steel components such as axles and gears. One of the control parameters measured in this process is the case depth, which can be measured by either destructive or nondestructive methods. In this paper, the ultrasonic nondestructive backscattering technique is utilized to measure the case depth of steel shafts. Measurements are carried out on four steel shafts with different case depths by using contact ultrasonic testing method. The ultrasonic signals collected from these shafts are rectified and filtered by smoothing filters. Comparison of the results of the ultrasonic tests with those of the destructive tests confirms the capability and high precision of the ultrasonic backscattering technique in measuring the case depth. The maximum error in ultrasonic backscattering measurements was less than 4%. Due to its nondestructive and portable nature, this technique can be a good choice for quality control induction hardened components with a case depth of 2 mm or more.

Today, computed tomography has a wide of applications in medical and industrial imaging systems. In CT the inside image of the objects is obtained by scanning it at different angles and reconstructing the image. Industrial CT is used in many industrial areas for internal inspection of parts. Some of its key applications in industry are fault detection, non-destructive inspection, failure analysis, metrology, assembly analysis and reverse engineering. In this study, the CT feasibility study of a standard phantom specimen was performed with a cargo scanner system. The phantom contains 5.0 mm, 10.0 mm, 20.0 mm, diameter rods made of iron, aluminium and polyethylene and the total number of phantom rods was 9. The Imaging system geometry consists of a linear array detector and a gamma ray source. Two mathematical methods, MLEM and BackProjection, were used for reconstructing the projection that obtained from the sample. First the proposed CT system was simulated using the MCNPX Monte Carlo code. The CT images of phantom were compared in terms of the reconstruction methods and the experimental and simulated geometry.

In this study a non-destructive system was designed and fabricated to detect wear and measure its parameters on railway tracks. Delayed detection of wear on railway lines can cause critical problems and makes the repair and maintenance process more time and cost-consuming. Even worth, if the wear passes the critical value, it changes the geometry of the line, causing the derailment of the train. In the proposed method for wear detection, a system with a line laser and a camera is applied. The laser lights the surface of the rail, and the camera captures an image from it. By processing the shape of the lit pattern, which is different in worn and unworn areas, we could detect wear and estimate its several parameters. In the proposed method, after applying some preprocessing techniques to extract the shape of the lit pattern, an artificial neural network (ANN) is used to quantify w1, w2, and w3 as the three parameters of the wear. The performance of three artificial neural networks (MLP, GRNN, and RBF) to estimate w1, w2, and w3 was studied. Among all, GRNN had the best performance with the maximum error of 0.27, 0.24, and 0.32 mm, respectively for W1, W2, and W3. It shows the high efficiency of the suggested measurement system. In RDD-S11, which is currently being used in lines one and two of Mashhad Urban Railway Company to detect three common defects, the proposed method is being used to detect and measure the wear on railway tracks.

In this study, acoustic and vibration response methods were used to non-destructively estimate the firmness of apples. Gala apples were stored at 0 and 20 ° C for 9 and 6 weeks and were tested for acoustic response every week during storage. During the test, the samples were placed on a special device designed and made for this test and stimulated with a gentle tap. Impact sound and vibration were received by the microphone and accelerometer and transmitted as analog signals to the computer sound card and then converted to digital signals. Digital signals were converted from time domain to frequency domain by Fourier transform in MATLAB software. The dominant frequencies of the sound and vibration signals were extracted and the firmness indices were obtained from special equations. The results of acoustic and vibration tests were compared with the results of puncture test. The correlation coefficient between puncture firmness and firmness index was more than 0.92, which was significant at the probability level of 1%. Also, the dominant acoustic and vibrational frequencies and mass of the samples were used as three features as single, binary and ternary using artificial neural network to estimate the shelf life of apples. The shelflife was estimated at one, two and three week intervals and the results of fusion of binary and ternary in different modes increased from 9% to 30% the accuracy of classification of individual features.

The microwave chamber disturbance method (CDM) is a commonly used procedure for determining the electromagnetic properties of materials in the microwave frequency range. This method is based on the change in the resonance frequency and the quality coefficient of a measurement chamber due to the penetration of the sample at the location of the maximum electric or magnetic field, depending on the nature of the parameter under study. The main limitation of the CDM is the requirement that the sample size must be small so as not to have a negligible effect on the geometry of the fields inside the chamber. In this paper, we propose an enhanced CDM for accurate measurement of dielectric constant and magnetic permeability of materials with very low error rates. The chamber consists of a rectangular waveguide with a cap that fits the location of the sample. This arrangement provides a suitable measuring device that minimizes the measuring errors, including the uncertainty in the perforated plate and use of liquid adhesive for sample-waveguide attachment. To validate the accuracy of the proposed method, the predicted values of dielectric constant and magnetic permeability of several sample materials are compared with their actual values and the error rate of this proposed method has finally reached less than 1.5%

In this study, the discriminatory power of Metal Oxide Semiconductor (MOS) gas sensors was evaluated to develop a portable electronic nose (e-nose) system for clustering different types of saffron samples based on their Volatile Organic Components (VOCs). The system was comprised of ten MOS gas sensors, direct headspace sampling, microcontroller devices, and a laptop computer coupled with multivariate computational tools. Eleven saffron samples were procured from different geographical origins for the experiments. Principal Component Analysis (PCA) and Hiricultural Cluster Analysis (HCA) models were applied for sample clustering and for demonstrating the discriminatory power of the gas sensors as well. The quality assessment of the samples was also performed by the standard laboratory method (ISO3632). The gas sensors data were acquired at 350-360 seconds after the samples were exposed to the sensors. Results of the PCA and HCA analysis of the sensors data indicated that the saffron samples were divided into three main clusters. Also, it was found that the discrimination power of the sensors was different and the possibility of removing sensors with low discriminatory power (2 sensors) was provided. Results of laboratory analysis (destructive method) were obtained in accordance with the classification results of the e-nose data analysis. Using the proposed method to find the most effective MOS sensors and eliminating the redundant sensors can help to reduce the development costs of the electronic nose systems and the processor input data. It also increases the classification accuracy of the e-nose system in the quality control of medicinal plants.

Neutron Computed Tomography (nCT) is proposed as one of the modern and high accuracy 3-dimensional imaging modalities of nondestructive testing of the materials and components. Volumetric rendering and representation capability of tomographic imaging has many advantages for interrogating the internal structures, defect detection and quality testing of objects. Implementation of Filtered Back-Projection (FBP) reconstruction method for nCT facility at Tehran Research Reactor has been investigated in this study. The facility consists of experimental data acquisition system, integrated automation digital imaging system, image processing, FBP reconstruction, and 3D visualization softwares. Test subject was turned within the neutron radiation field at half screen and 360 two-dimensional projections were acquired through data acquisition. Preprocessing was performed on projections and tomographic images of subject were reconstructed using MuhrRec software and FBP algorithm. The results were indicated that reconstructed images have appropriate quality. Internal defects were recognizable having dimensions above the maximum spatial resolution of the facility (~200 µm).