- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2017 Far East NDT New Technology & Application Forum (FENDT) - Xi'an, China (2017.6.22-2017.6.24)] 2017 Far East NDT New Technology & Application Forum (FENDT) - EMD of EMAT NDT in X70 Pipeline Weld Defects
摘要： Electromagnetic acoustic transducer (EMAT) is an emerging non-destructive testing technique which has been applied to the pipelines inspection. EMAT has advantages of Non coupling agent and can be used with high temperature environment. Due to the roughness remaining in surface of the pipeline, the quantitative analysis of defect location are challenges by using EMAT NDT. This paper introduces a new detection method of EMAT by hybriding Empirical Mode Decomposition (EMD) with IMFs reconstruction to quantitative detect weld defects. The new method has been validated to detect the defects of weld for the X70 pipeline by using Bulk-wave. Experiments have been proved that it improves the accuracy of the measurement, and achieve the recognition of millimeter-level defects.
关键词： Pipeline EMAT NDT,X70 pipelines,EMD and IMFs reconstruction
更新于2025-09-23 15:23:52
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An automated shearography system for cylindrical surface inspection
摘要： A shearography system has been developed to inspect the external heat proof coating bonded to a cylinder. The system consists of a shearography device integrated with thermal excitation, a mechanical translation and rotation device, and a central control unit. The translation and the rotation are driven with 2 servo motors. The combination of these two movements enables full inspection of the entire surface of the cylinder. The inspection sequence is automatically scheduled by inputting the geometry of the sample. Artificial intelligence (AI) has been first introduced to aid defect recognition from the resulted phase shifting fringe patterns. A recognition algorithm based on deep learning has been developed using Faster R-CNN model for recognition of bonding defects. By training the system using typical butterfly fringe patterns which are captured from bonding samples, the system can accurately identify the bonding defects on the cylindrical surface at a high success rate.
关键词： Defect recognition,Automatic inspection,Shearography,NDT
更新于2025-09-23 15:23:52
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[IEEE 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - Stuttgart, Germany (2018.11.20-2018.11.22)] 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - 3D Point Cloud Coarse Registration based on Convex Hull Refined by ICP and NDT
摘要： Non-rigid registration is a crucial step for many applications such as motion tracking, model retrieval, and object recognition. The accuracy of these applications is highly dependent on the initial position used in registration step. In this paper we propose a novel Convex Hull Aided Coarse Registration refined by two algorithms applied on projected points.Firstly,the proposed approach uses a statistical method to find the best plane that represents each point cloud. Secondly, all the points of each cloud are projected onto the corresponding planes. Then, two convex hulls are extracted from the two projected point sets and then matched optimally. Next, the non-rigid transformation from the reference to the model is robustly estimated through minimizing the distance between the matched point's pairs of the two convex hulls.Finally, this transformation estimation is refined by two methods. The first one is the refinement of coarse registration by Iterative Closest Point (ICP). The second one consists of the refinement of coarse registration by the Normal Distribution Transform (NDT). An experimental study ,carried out on several clouds, shows that the refinement of coarse registration with ICP gives, in the most cases, a better result than refinement with NDT.
关键词： Iterative Closest Point (ICP),Convex Hull,Normal Distribution Transform (NDT),Non rigid registration,3D point cloud,Principal Component Analysis (PCA)
更新于2025-09-23 15:22:29
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Absorption Coefficient Dispersion in Flash Thermography of Semitransparent Solids
摘要： Pulse and flash thermography are experimental techniques which are widely used in the field of non-destructive testing for materials characterization and defect detection. We recently showed that it is possible to determine quantitatively the thickness of semitransparent polymeric solids by fitting of results of an analytical model to experimental flash thermography data, for both transmission and reflection configuration. However, depending on the chosen experimental configuration, different effective optical absorption coefficients had to be used in the model to properly fit the respective experimental data, although the material was always the same. Here, we show that this effect can be explained by the wavelength dependency of the absorption coefficient of the sample material if a polychromatic light source, such as a flash lamp, is used. We present an extension of the analytical model to describe the decay of the heating irradiance by two instead of only one effective absorption coefficient, greatly extending its applicability. We show that using this extended model, the experimental results from both measurement configurations and for different sample thicknesses can be fitted by a single set of parameters. Additionally, the deviations between experimental and modeled surface temperatures are reduced compared to a single optimized effective absorption coefficient.
关键词： Dispersion,Flash thermography,NDT,Absorptance,Infrared thermography,Semitransparency
更新于2025-09-23 15:22:29
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Fault Classification in Electrofusion Polyethylene Joints by Combined Machine Learning, Thermal Pulsing and IR Thermography Methods - A Comparative Study
摘要： The capability of conveniently classifying the fault types in the electrofusion joints can certainly increase the security of polyethylene gas pipelines. Therefore in the current study, we use machine learning to push the horizons of our recent thermal pulsing and IR thermography method, to identify ovality versus unalignment faults. To do so, we extend our experimental IR-thermography data bank and then apply k-means, Random Forests and GLMNet algorithms in a two stage approach. The overall classification accuracy for k-means and Random Forests were 70.37% and 84.21% respectively; GLMNet could successfully outperform the others with a classification accuracy of 93.75%.
关键词： Machine Learning,Electrofusion Polyethylene Joint,IR Thermography,Fault Classification,Thermal Pulsing NDT
更新于2025-09-23 15:21:21
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Joint Scanning Laser Thermography Defect Detection Method for Carbon Fiber Reinforced Polymer
摘要： In this paper, a new inspection method, joint scanning laser thermography (JSLT) as well as its data reconstruction and processing algorithm, is proposed. The new inspection method is utilized to detect and characterize the flat-bottom holes (FBH) in carbon fiber composites by using joint laser scanning scheme. By analyzing the nature of the thermal image sequences sampled under such a scanning scheme, a quick and simple reconstruction method is developed to characterize the buried depth of defects based on 1D heat conduction model. The processed thermal images are expected to get higher temporal resolution and spatial resolution. It can inspect larger area within shorter acquisition time than the pulse thermography. Thus, the study solves the dilemma between the inspection speed and the inspection capacity. Later, a joint laser scanning thermography test is set up to test the algorithm on a carbon fiber composite panel with defects buried at different depth. The experimental results show that the reconstructed data almost behave as those under pulse excitation. The tendency of temperature to change in the logarithmic domain over time is similar to the curve in the TSR method. But, unlike the pulse thermography data, the defect detection rate of PCA based on reconstructed data is higher than that of independent component analysis (ICA) and FFT phase image. The JSLT system is used to detect FBH and the diameter-depth ratio reached 3.33.
关键词： data reconstruction,scanning laser,defect detection,thermography,NDT
更新于2025-09-12 10:27:22
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Detectability of Delamination in Concrete Structure Using Active Infrared Thermography in Terms of Signal-to-Noise Ratio
摘要： Detecting subsurface delamination is a dif?cult and vital task to maintain the durability and serviceability of concrete structure for its whole life cycle. The aim of this work was to obtain better knowledge of the effect of depth, heating time, and rebar on the detectability capacity of delamination. Experimental tests were carried out on a concrete specimen in the laboratory using Long Pulsed Thermography (LPT). Six halogen lamps and a long wavelength infrared camera with a focal plane array of 640 × 480 pixels were used as the heat source and infrared detector, respectively. The study focused on the embedded imitation delaminations with the size of 10 cm × 10 cm × 1 cm, located at depths varying from 1 to 8 cm. The signal-to-noise ratio (SNR) was applied as a criterion to assess the detectability of delamination. The results of this study indicate that as the provided heating time climbed, the SNR increased, and the defect could be identi?ed more clearly. On the other hand, when using the same heating regime, a shallow delamination displayed a higher SNR than a deeper one. The moderate fall of the SNR in the case of imitating defect located below reinforced steel was also observed. The absolute contrast was monitored to determine the observation time, and the nondimensional prefactor k was empirically proposed to predict the depth of delamination. The mean absolute percentage error (MAPE) was used to quantitatively evaluate the difference between forecasted and real depth, which evaluation con?rmed the high reliability of the estimated value of the prefactor k.
关键词： signal-to-noise ratio (SNR),nondestructive technique (NDT),reinforced concrete,infrared thermography,long pulsed thermography,delamination
更新于2025-09-10 09:29:36
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[IEEE 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI) - Bangalore, India (2018.9.19-2018.9.22)] 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI) - FPGA based Ultrasonic thickness measuring device
摘要： This paper aims at the development of ultrasound based thickness measurement device. A Spartan 6 FPGA from Xilinx has been used in the hardware design along with external parallel Analog to Digital and digital to Analog converter. The device is interfaced with a PC or laptop through USB cable. A measurement and control software is developed using MATLAB for conceptual level and final Graphical User Interface has been developed in .NET to transfer different user defined control parameters to the hardware and receive the captured signal. Ultrasonic probes are used to generate and receive physical sound wave in pulse-echo mode. Time of flight (ToF) based calculations are used for deriving the subject dimension.
关键词： ADC Module,Contact Transducer,DAC Module,NDT,Ultrasonic testing,Spartan XC6SLX9 FPGA
更新于2025-09-09 09:28:46
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[IEEE 2018 2nd International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech) - Kolkata (2018.5.4-2018.5.5)] 2018 2nd International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech) - Nondestructive testing image enhancement based on a bag of enhancement functions and Bat algorithm
摘要： Nondestructive Testing image (NDT) has a wide range of applications in industry. Enhancing the visual quality of an NDT image is dif?cult and it is a challenging domain of research. In this paper, we propose a novel method for NDT image enhancement. In the proposed method a bag of enhancement functions is combined to generate an ef?cient enhancement function for the NDT image. The enhancement function is generated adaptively by taking into consideration the statistics of the NDT image in hand. To speed up the process of combination in the proposed method, we use evolutionary Bat algorithm. The Bat algorithm generates the optimal enhancement function using the bag. The performance of the proposed method is found to be superior to that of the stare-of-the-art methods for NDT image on standard data set.
关键词： image enhancement,enhancement function,Bat algorithm,NDT image
更新于2025-09-09 09:28:46
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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - Automatic Inspection of Aerospace Welds Using X-Ray Images
摘要： The non-destructive testing (NDT) of components is very important to the aerospace industry. Welds in these components may contain porosities and other defects. These reduce the fatigue life of components and may result in catastrophic accidents if they end up in the aircraft. Currently such welds are inspected by humans studying radiographs of the welds. We describe an automatic system for detecting defects in welds, with the aim of creating a triage system to reduce the workload on human inspectors. Given an X-ray image of the aerospace weld, the system locates the weld line, then analyses the region around the line to identify abnormalities. Our results show that the weld can be precisely extracted from X-ray images and the defect detection operation can identify 83% of defects with fewer than 3 false positives per image, and thus may be useful for prompting human inspectors to reduce their workload.
关键词： weld,NDT,random forests,NDE,defect detection,Non-destructive evaluation/testing
更新于2025-09-04 15:30:14