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This paper aims to propose a new ultrasonic diagnosis method for stainless steel weld defects based on multi-domain feature fusion to solve two problems in the ultrasonic diagnosis of austenitic stainless steel weld defects. These are insufficient feature extraction and subjective dependence of diagnosis model parameters.

To express the richness of the one-dimensional (1D) signal information, the 1D ultrasonic testing signal was derived to the two-dimensional (2D) time-frequency domain. Multi-scale depthwise separable convolution was also designed to optimize the MobileNetV3 network to obtain deep convolution feature information under different receptive fields. At the same time, the time/frequent-domain feature extraction of the defect signals was carried out based on statistical analysis. The defect sensitive features were screened out through visual analysis, and the defect feature set was constructed by cascading fusion with deep convolution feature information. To improve the adaptability and generalization of the diagnostic model, the authors designed and carried out research on the hyperparameter self-optimization of the diagnostic model based on the sparrow search strategy and constructed the optimal hyperparameter combination of the model. Finally, the performance of the ultrasonic diagnosis of stainless steel weld defects was improved comprehensively through the multi-domain feature characterization model of the defect data and diagnosis optimization model.

The experimental results show that the diagnostic accuracy of the lightweight diagnosis model constructed in this paper can reach 96.55% for the five types of stainless steel weld defects, including cracks, porosity, inclusion, lack of fusion and incomplete penetration. These can meet the needs of practical engineering applications.

This method provides a theoretical basis and technical reference for developing and applying intelligent, efficient and accurate ultrasonic defect diagnosis technology.

This study aims to solve the problem of weld quality inspection, for the aluminum alloy profile welding structure of high-speed train body has complex internal shape and thin plate thickness (2–4 mm), the conventional nondestructive testing method of weld quality is difficult to implement.

In order to solve this problem, the ultrasonic creeping wave detection technology was proposed. The impact of the profile structure on the creeping wave detection was studied by designing profile structural test blocks and artificial simulation defect test blocks. The detection technology was used to test the actual welded test blocks, and compared with the results of X-ray test and destructive test (tensile test) to verify the accuracy of the ultrasonic creeping wave test results.

It is indicated that that X-ray has better effect on the inspection of porosities and incomplete penetration defects. However, due to special detection method and protection, the detection speed is slow, which cannot meet the requirements of field inspection of the welding structure of aluminum alloy thin-walled profile for high-speed train body. It can be used as an auxiliary detection method for a small number of sampling inspection. The ultrasonic creeping wave can be used to detect the incomplete penetration welds with the equivalent of 0.25 mm or more, the results of creeping wave detection correspond well with the actual incomplete penetration defects.

The results show that creeping wave detection results correspond well with the actual non-penetration defects and can be used for welding quality inspection of aluminum alloy thin-wall profile composite welding joints. It is recommended to use the echo amplitude of the 10 mm × 0.2 mm × 0.5 mm notch as the criterion for weld qualification.

This study aims to solve the problems of ambiguous localization, large calculation, poor real-time and limited applicability of bolt thread defect detection.

First, the acquired ultrasound image is used to acquire the larger area of the image, which is set as the compliant threaded area. Second, based on the determined coordinates of the center point in each selected region, the set of coordinates on the left and right sides of the bolts is acquired by DBSCAN method with parameters eps and MinPts, which is determined by data set dimension D and the k-distance curve. Finally, the defect detection boundary line fitting is completed using the acquired coordinate set, and the relationship between the distance from each detection point to the curve and d, which is obtained from the measurement of the standard bolt sample with known thread defect, is used to locate the bolt thread defect simultaneously.

In this paper, the bolt thread defect detection method with ultrasonic image is proposed; meanwhile, the ultrasonic image acquisition system is designed to complete the real-time localization of bolt thread defects.

The detection results show that the method can effectively detect bolt thread defects and locate the bolt thread defect location with wide applicability, small calculation and good real-time performance.

Development of non‐destructive methodology for detection of arc strike, spatter and fusion type of welding defects which may form on steam generator (SG) tubes that are in close proximity to the circumferential shell welds. Such defects, especially fusion‐type defects, are detrimental to the structural integrity of the SG. This paper aims to focus on this problem.

This paper presents a new methodology for non‐destructive detection of arc strike, spatter and fusion type of welding defects. This methodology uses remote field eddy current (RFEC) ultrasonic non‐destructive techniques and K‐means clustering.

Distinctly different RFEC signals have been observed for the three types of defects and this information has been effectively utilized for automated identification of weld fusion which produces two back‐wall echoes in ultrasonic A‐scan signals. The methodology can readily distinguish fusion‐type defect from arc strike and spatter type of defects.

The methodology is unique as there is no standard guideline for non‐destructive evaluation of peripheral tubes after shell welding to detect arc strike, spatter and fusion type of welding defects.

A data fusion approach to the classification of eddy current and ultrasonic measurements is proposed in a context of defect detection/recognition methods for non‐destructive testing/evaluation systems: the purpose is to demonstrate that a multi‐sensor approach that combines the advantages carried by each sensor is able to locate potential cracks on the inspected specimen. Different approaches have been compared: a pixel level data fusion approach, that distinguishes between the defect area and the no‐defect areas, by means of the information carried by the intensity of each pixel of the eddy current and ultrasonic data; a feature level data fusion approach that uses the features computed on the measured data; a symbol level data fusion approach that extracts symbols from the two sensors as complementary information and classifies the data by using these symbols. The experimental results, carried out on an aluminium plate, pointed out the ability of the symbol level proposed approach to classify the input images within a minimum overall error, by taking into account the probability of detection and the probability of false alarm for the defect.

Defects can be caused by a number of factors, such as maintenance damage, ground handling and foreign objects thrown up from runways during an in-service use of composite aerospace structures. Sandwich structures are capable of absorbing large amounts of energy under impact loads, resulting in high structural crashworthiness. This situation is one of the many reasons why sandwich structures are extensively used in many aerospace applications nowadays. Their non-destructive inspection is often more complex. Hence, the choice of a suitable non-destructive testing (NDT) method can play a key role in successful damage detection. The paper aims to discuss these issues.

A comparison of detection capabilities of selected C-scan NDT methods applicable for inspections of sandwich structures was performed using water-squirt, air-coupled and pitch-catch (PC) ultrasonic techniques, supplemented by laser shearography (LS).

Test results showed that the water-squirt and PC techniques are the most suitable methods for core damage evaluation. Meanwhile, the air-coupled method showed lower sensitivity for the detection of several artificial defects and impact damage in honeycomb sandwiches when unfocussed transducers were used. LS can detect most of the defects in the panels, but it has lower sensitivity and resolution for honeycomb core-type sandwiches.

This study quantitatively compared the damage size indication capabilities of sandwich structures by using various NDT techniques. Results of the realised tests can be used for successful selection of a suitable NDT method. Combinations of the presented methods revealed most defects.

Quantitatively detecting surface defects in a circular annulus with high levels of accuracy and efficiency has been paid more attention by researchers. The purpose of this study is to investigate the theoretical dispersion equations for circumferential guided waves and then develop an efficient technique for accurate reconstruction of defects in pipes.

The methodology applied to determine defects in pipelines includes four steps. First, the theoretical work is carried out by developing the appropriate dispersion equations for circumferential guided waves in a pipe. In this phase, formulations of strain-displacement relations are derived in a general equidistant surface coordinate. Following that, a semi-analytical finite element method (SAFEM) is applied to solve the dispersion equations. Then, the scattered fields in a circular annulus are calculated using the developed hybrid finite element method and simulation results are in accord with the law of conservation of energy. Finally, the quantitative detection of Fourier transform (QDFT) approach is further enhanced to efficiently reconstruct the defects in the circular annuli, which have been widely used for engineering applications.

Results obtained from four numerical examples of flaw detection problems demonstrate the correctness of the developed QDFT approach in terms of accuracy and efficiency. Reconstruction of circumferential surface defects using the extended QDFT method can be performed without involving the analytical formulations. Therefore, the streamlined process of inspecting surface defects is well established and this leads to the reduced time in practical engineering tests.

In this paper, the general dispersion equations for circumferential ultrasonic guided waves have been derived using an equidistant surface coordinate and solved by the SAFEM technique to discover the relationship between wavenumber of a wave and its frequency. To reconstruct defects with high levels of accuracy and efficiency, the QDFT approach has been further enhanced to inspect defects in the annular structure.

The need to examine the integrity of infrastructure in the rail industry in order to improve its reliability and reduce the chances of breakdown due to defects has brought about development of an inspection and diagnostic robot.

In this study, an inspection robot was designed for detecting crack, corrosion, missing clips and wear on rail track facilities. The robot is designed to use infrared and ultrasonic sensors for obstacles avoidance and crack detection, two 3D-profilometer for wear detection as well as cameras with high resolution to capture real time images and colour sensors for corrosion detection. The robot is also designed with cameras placed in front of it with colour sensors at each side to assist in the detection of corrosion in the rail track. The image processing capability of the robot will permit the analysis of the type and depth of the crack and corrosion captured in the track. The computer aided design and modeling of the robot was carried out using the Solidworks software version 2018 while the simulation of the proposed system was carried out in the MATLAB 2020b environment.

The results obtained present three frameworks for wear, corrosion and missing clips as well as crack detection. In addition, the design data for the development of the integrated robotic system is also presented in the work. The confusion matrix resulting from the simulation of the proposed system indicates significant sensitivity and accuracy of the system to the presence and detection of fault respectively. Hence, the work provides a design framework for detecting and analysing the presence of defects on the rail track.

The development and the implementation of the designed robot will bring about a more proactive way to monitor rail track conditions and detect rail track defects so that effort can be geared towards its restoration before it becomes a major problem thus increasing the rail network capacity and availability.

The novelty of this work is based on the fact that the system is designed to work autonomously to avoid obstacles and check for cracks, missing clips, wear and corrosion in the rail tracks with a system of integrated and coordinated components.

The purpose of this paper is to present the results of acoustic emission (AE) and ultrasonic inspection of two H₂S storage tanks carried out in a heavy water plant, in order to characterize point type defects observed during earlier ultrasonic inspection and to ensure that these defects are not growing during hydrotesting of the tanks.

Using multiple AE sensors and AE source location methodology, the entire tank could be covered to detect and locate any dynamic sources of AE associated with local plastic deformation and/or growing discontinuities from any part of the tank during the hydrotest. For confirmation of the results obtained by AE, ultrasonic inspection on the tanks and on virgin plates from which the tanks were manufactured, were carried out.

The AE signals generated during first pressurisation are attributed to the micro yielding of the material of the tanks. A few scattered AE events were observed at a few locations during the hydrotesting of the tanks and these are due to structural and rubbing noise. During hold periods and repressurising cycle of the hydrotesting, no detectable AE events were observed and this confirmed the absence of any growing discontinuity in the tanks during the hydrotesting. Ultrasonic inspection on the tanks and on virgin plates confirmed that the point type defects detected are manufacturing defects and not formed during service life.

The combined results from AE and ultrasonic techniques confirmed the structural integrity of the tanks and ensured their healthiness for continued operation.

The paper brings out the use of AE and ultrasonic techniques for monitoring hydrotesting of storage tanks of a heavy water plant. The storage tanks where point type defect indications were reported during previous ultrasonic inspection and whether these defects are growing during hydrotesting of the tanks or not, were required to be known before the tanks are put in to further service. AE signals collected during pressurising and repressurising cycles of the hydrotest and subsequent inspection by ultrasonic confirmed the vessels to be free from growing defects during the hydrotest and provided baseline data for future inspection.

In the “in‐service” maintenance and inspection of aircraft structures, an uneasy alliance exists between corrosion detection and Non‐Destructive Testing. NDT is a widely used and generally successful way of inspecting for structural defects and as the service life of aircraft is extended and corrosion therefore tends to become a not uncommon structural defect, why should not NDT be as useful in this situation as it often is in detecting cracks occasioned by extended flying hours and increased flight cycles? This paper tries to answer that question by pointing out some of the advantages and disadvantages of NDT applied to corrosion detection in the aviation industry.