Non-Destructive Testing Technology
Year:2020 | Volume:2 | Issue:6|Papers Count:9

Pipelines are very important in the oil and gas industries and due to their high cost of construction, they are considered as a national asset in Iran. Erosion is known to be one of the most important pipelines damages that leads to the reduction of pipe thickness. Reduction in thickness causes more stress to be concentrated in the pipelines and failure occurs more easily. Ultrasonic tests are one of the methods used to inspect pipelines. Among various ultrasonic testing techniques, Lamb waves have a special place due to their low attenuation. However, the complex behavior of these waves in structures of variable thickness makes it difficult to interpret the data obtained from a test. In this paper, two-dimensional finite element modeling of the behavior of these waves is carried out and the transmission and reflection coefficients in the presence of thickness variations are verified. The results of the study of the effect of changing the erosion depth on the transmitting and reflecting signals indicate that by using Lamb waves, changes in the thickness of a pipe can be monitored. Moreover, the study of changes in the frequency of the signal sent to the plate shows that in some frequency ranges, the S0 mode shows little sensitivity to changes in thickness. Therefore, the choice of the test frequency in Lamb waves testing is an important step in determining the condition of the structure.

Long-range guided wave inspection systems are often used in low frequency– thickness ranges below the cut-off frequencies of higher wave modes to simplify data interpretation. In this paper, the potential of high-order guided wave modes for the inspection of plate structures is considered. The characteristics of high-order lamb wave modes and their corresponding sensitivity and detectability are investigated. Using a commercially available software package, finite element simulations are carried out to model the propagation of A1 and S1 wave modes in steel plate. Using a variable angle transducer, experimental pulse– echo measurements are also conducted to evaluate the measurement errors when implementing higher order modes A1 and S1 on a 2-mm thick steel plate at 4 MHz. mm. Experimental measurements show that when using S1 mode for short-range measurements, the relative error is less than 10%.

Conveyor belts play an important role in mining industry and processing factories; therefore, it is es-sential to maintain them and prevent their sudden failure. In recent years, condition monitoring of these devices by vibration analysis has helped in diagnosis of defective rotational components such as bearings in the early stages of failure. In this study, the driving bearing of the conveyor belt number 9 of Sarcheshmeh copper complex has been monitored by vibration analysis. Due to relatively low speed of these bearings, it is difficult to identify their defects. Visual inspection of the bearing agrees with results obtained from vibration analysis. Moreover, wear on the outer ring and bearing failure patterns correspond to a pivot force exerted on the bearing due to deflection of the belt from the centre of the drum.

The eddy current nondestructive testing (ECT) is one of the electromagnetic methods that can be used to evaluate and control the metallurgical quality of industrial alloys. The rapid implementation and digital nature of the answers have led to its use in setting up automatic inspection and quality control lines. The purpose of this paper is to investigate the metallurgical quality control conditions of 7075 aluminum alloy sheets after aging heat treatment using the ECT method. For this purpose, the destructive tests of metallography, hardness and electrical conductivity were performed along with the eddy currents Nondestructive testing and then their data were compared with each other. The sheet samples of this alloy were prepared in the form of a 1. 2 mm thickness. The solution heat treatment was performed at 470 centigrade for 20 minutes and then artificial aging heat treatment was performed at different temperatures and times. Microstructural studies were performed by optical and scanning electron microscopes, standard conductivity (% ICAS) and Brinell hardness methods. Then, using a eddy current apparatus at 8 kHz, the electromagnetic responses of the samples were evaluated and compared. The results showed that to quality control and assurance of the aged products, the use of hardness index alone cannot suffice. In addition, the metallographic method has executive limitations in production processes. It was found that the eddy current responses are affected by microstructural changes resulting from aging process. Using this method, different parts of 7075 aluminum alloy can be Nondestructively separated from each other.

Nowadays, as the application of additive manufactured equipment is increasing in the industry, an appropriate inspection method for identifying defects of these products has become a pressing need. In this contribution, a study on inspection of the artificial defects of an additive manufactured specimen via thermography was carried out. A projector with 2KW in power was utilized as the heating source. The temperature of the sample was recorded by a thermal camera. Moreover, the camera kept recording the sample’ s temperature for a while after that heating source was shut down. The best frame of raw thermal data was selected. To enhance the thermal raw data in case of the contrast between defective and sound regions and the number of detectable defects, two well-known thermal image processing methods, namely, Pulsed Phase Thermography (PPT) and Principle Component Analysis (PCA), were applied to the initial data. It was illustrated that all defects could be detected through processed images, whereas only 18 defects out of 20 could be revealed in the best frame of raw thermal data. Furthermore, for evaluating the ability of each technique to improve the contrast, the SNR parameter was adopted. According to the concluded data, the processed image via PCA with SNR average equal to 14. 75 had the highest amount. This amount was almost three times higher than that of the best frame of initial thermal data.

Turbine blades are one of the most sensitive and important hot parts of gas turbines, so that the efficiency and life of turbines are directly related to the operation of these components. Therefore, to prevent damage caused by high temperatures, they must be properly cooled. The common method of cooling these parts is to pass the cooling fluid through their complex internal channels. Nondestructive testing of thermography, is one of the new methods for detecting imperfections in these cooling paths which is considered in this article. Thermal loading is applied in an active manner by hot steam generator system. In order to identify the capability of this system in the detection of the residuals in the cooling system of blades, 3 kinds of different blades are studied and tested using active thermography. Results show the appropriateness of the system in detection of the blockages in all three blades. But it worth to notify that the success of the system is strongly related to the best detection of the system parameters as steam pressure, temperature and Fluid flow. So, the best parameters are chosen as: pressure of 2bars, ambient temperature of 25 oC and the maximum fluid of the hot steam.

Prognostic Health Management (PHM) is a new philosophy in maintenance that deals with the diagnosis and prognosis of failures and defects in devices PHM in rotary machines is usually utilizing the analysis of vibration signals, acoustic emission, temperature or oil analysis. By having a proper health index obtained from signal analysis, it is possible to detect system defects and prepare the device for maintenance operation. In this paper, the acoustic emission signals of a milling machine are used to detect tool wear or breakage. First, with wavelet analysis, the signal noise was reduced in order to achieve a suitable analysis to select the health index. Here, three mother wavelet functions db4, sym5 and haar and three thresholding methods are used. Research has shown that the parent functions sym5 and haar with low penalize threshold method, with 3 levels of analysis, have the lowest MSE of 0. 0018 and 0. 0019, respectively. In the next step, fourteen signal feature functions were extracted and compared with each other. Among the functions studied for the health index, the result showed that from healthy to unhealthy instrument in addition to the root mean square (RMS) function with 10% change, signal root square with 10%, entropy 15%, energy 28%, impact factor 33%, the maximum signal index of 48% can also be suitable criteria for the health index.

Health and security of foods are recognized as one of the most important human priorities, so effective and new techniques have been implemented to improve and development of effective methods in the quality assessment of food industry. Extra Virgin Olive Oil (EVOO) has many amazing benefits for the human body's health. Due to the nutritional value and high price of EVOO, there is a lot of adulteration in it. The ultrasonic approach has many advantages in the food studies, it is fast and nondestructive. In this study, to fraud detection of EVOO four ultrasonic properties of oil in five levels of adulteration (5%, 10%, 20%, 35% and 50%) were extracted. The 2 MHz ultrasonic probes were used in the DOI 1000 STARMANS diagnostic ultrasonic device in a "probe holding mechanism". The four extracted ultrasonic features include: "percentage of amplitude reduction, time of flight (TOF), the difference between the first and second maximum amplitudes of the domain (in the time-amplitude diagram) and the ratio of the first and second maximum of amplitude". Seven classification algorithms include "Naï ve Bayes, support vector machine, gradient boosting classifier, K-nearest neighbors, artificial neural network, logistic regression and Ada-Boost" were used to classifying the pre-processed data. Results showed that the Naï ve Bayes algorithm with 90. 2% provided the highest accuracy among the others, and the SVM and GBC with 88. 2% were in the next ranks after Naï ve Bayes.

Pipelines are commonly used in various industries such as oil and gas, water supplies and petrochemical. Composite Pipes are appropriate choice due to some properties including high strength, lightness and high corrosion resistance. It is necessary to employ Nondestructive Tests (NDT) during construction as well as maintenance of such pipelines, in order to reduce costs. One of the damages that may occur on composite pipes is joint failure which normally happens during construction and operation of the pipes. Furthermore, the most common method of joints in composite pipes is adhesive joint. Ultrasonic Guided Wave (UGW) is suitable method of NDT. In this research, a numerical simulation of L(0, 1) guided mode is carried out in order to inspect the adhesive joint between two composite pipes. A parametric study is performed on damage length variation in order to extract suitable feature from damaged pipe signals for damaged joint identification. Using two sensors which are located before and after the adhesive joint, with the purpose of receiving the reflected and transmitted ultrasound wave from the joint, two signals energy indices have been developed for damaged joint identification.