Hao-ran Liu, Tonghua Ling, Liang Zhang, Dan-ping Gu, Feng Cao
{"title":"An improved predictive deconvolution based on wavelet analysis for GPR signal processing","authors":"Hao-ran Liu, Tonghua Ling, Liang Zhang, Dan-ping Gu, Feng Cao","doi":"10.1109/FENDT47723.2019.8962690","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962690","url":null,"abstract":"In order to reduce the interference of multiple echoes from water and metal on detection effect of ground penetrating radar (GPR), an improved predictive deconvolution has been proposed based on wavelet analysis (short for PDWA method). The PDWA method firstly decomposes the GPR signals into time domain sub-signals with different scales by wavelet analysis, and then filters the time domain sub-signals by predictive deconvolution and wavelet threshold denoising, at last reconstructs the filtered sub-signals to obtain the analysis result. Processing detection signal of model experiment by the PDWA method, the result shows that, comparing with predictive deconvolution, the PDWA method can suppress multiple echo interference, identify the target reflection accurately, and enhance the signal to interference ratio (SIR) of target reflection, thereby improving the detection resolution and the accuracy of image analysis of GPR signals.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117305031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chao Zhang, Bin Zhang, Jingfeng Wang, Guang Yang, Kai-wen Xie, Xin Fu
{"title":"Experimental Study on Ultrasonic Testing of TC4 Titanium Alloy by Additive Manufacturing","authors":"Chao Zhang, Bin Zhang, Jingfeng Wang, Guang Yang, Kai-wen Xie, Xin Fu","doi":"10.1109/FENDT47723.2019.8962546","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962546","url":null,"abstract":"Research about ultrasonic testing was carried out for different processing states (hot isostatic and heat treated) of the additive manufacturing TC4 titanium alloy (Ti-6Al-4V) by electron beam rapid manufacturing technique. Firstly, the longitudinal wave velocity and attenuation coefficient of the parts in these two processing states were measured by the contact longitudinal wave reflection method. Then, the signal-to-noise ratio of the φ0.8mm flat bottom hole defect buried depth 20-50mm was studied by using the water immersion ultrasonic method, the ultrasonic testing parameters and detection methods for different processes were analyzed. The results show that for the same processing state, the longitudinal wave velocity parallel to the deposition direction is significantly higher than that perpendicular to the deposition direction, and the attenuation coefficient is smaller than that perpendicular to the deposition direction; For the situation of different processing states, compared with the hot isostatic state , the longitudinal wave velocity of the material in heat treatment state is obviously reduced, and the attenuation coefficient is relatively close. For defects with buried depth of not more than 40 mm, it’s more effective to detect the defects in the direction perpendicular to the deposition direction, within the heat treatment state, the signal-to-noise ratio is relatively high; When the buried depth is greater than 40mm, the signal-to-noise ratio is significantly reduced, and the detection result can be optimized by setting correct DAC curve.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121312507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FENDT 2019 Cover Page","authors":"","doi":"10.1109/fendt47723.2019.8962559","DOIUrl":"https://doi.org/10.1109/fendt47723.2019.8962559","url":null,"abstract":"","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131046970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FENDT 2019 Author Index","authors":"","doi":"10.1109/fendt47723.2019.8962656","DOIUrl":"https://doi.org/10.1109/fendt47723.2019.8962656","url":null,"abstract":"","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121348129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Attention structured Pattern Deep Learning for region induction thermography NDT","authors":"Jue Hu, B. Gao, G. Tian","doi":"10.1109/FENDT47723.2019.8962614","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962614","url":null,"abstract":"Induction Thermography is a crucial nondestructive testing technology which has a rapidly increasing range of applications for crack detection. A series of studies have been carried out in thermal sequences processing algorithms. However, these methods often suffer from the complex surface conditions of experiment components. In this study, we propose an end-to-end attention structured pattern deep learning method to achieve precise crack detection and localization. The proposed method integrates both time and spatial pattern mining for crack information with a deep region convolution neural network. Experiments on welding line cracks have shown attractive performance and verified the efficacy of the proposed structure.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126806223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaolong Zhang, Zhenying Xu, Tao Yao, Yuan-xia Wang, Mengqi Wu
{"title":"The Simulation of SH Guided Wave at Weld by Peridynamics Theory","authors":"Xiaolong Zhang, Zhenying Xu, Tao Yao, Yuan-xia Wang, Mengqi Wu","doi":"10.1109/FENDT47723.2019.8962708","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962708","url":null,"abstract":"SH guided wave detection technology is a new type of weld inspection technology. In order to solve non derivable problem of the SH guided wave at the defects, an integral equation of SH guided wave in the weld seam is established based on the peridynamics theory. This integral equation of guided wave can synchronously represent the wave motion state at the weld and the defects. It can also simulate the wave propagation characteristics at the weld. In the simulation, when there is no defect in the weld, the group velocity of SH guided wave is around 2886 m/s, however, defects in the weld will attenuate the guided wave, increase dispersion and slow down group velocity. By comparing the experimental and simulated data, the simulated and experimented results are in good agreement with each other and show that the peridynamics can simulate the SH guided wave at the weld and defects, which provides a theoretical basis for the study of SH guided wave at weld.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126923820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FENDT 2019 Copyright Page","authors":"","doi":"10.1109/fendt47723.2019.8962640","DOIUrl":"https://doi.org/10.1109/fendt47723.2019.8962640","url":null,"abstract":"","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129080761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hong Zhang, Yunze He, Songming Yan, R. Wu, Wenhui Chen, Maozi Lin
{"title":"Exposed Corrosion Progression Characterisation Using Pulsed Eddy Current Sensing and Laser Profilometry","authors":"Hong Zhang, Yunze He, Songming Yan, R. Wu, Wenhui Chen, Maozi Lin","doi":"10.1109/FENDT47723.2019.8962571","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962571","url":null,"abstract":"The progression characterisation of exposed atmospheric corrosion on metal substrates is a major problem in the field of corrosion science and Non-destructive Evaluation (NDE). A pulsed eddy current (PEC) sensing system and a laser profilometry have been used to characterise the corrosion on the mild steel plate. These mild steel (S275) samples have been exposed to marine environment (exposure time from 1 month to 10 months). Four features have been utilized to characterise conductivity, permeability, roughness and thickness variation in the corrosion layer. The relationship between these features and corrosion exposed time has been derived which is useful for corrosion progression measurement, early stage corrosion monitoring and prediction in industrial fields such as the marine industry.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116720762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ensemble Tensor Factorization for Background Subtraction in Thermography NDT","authors":"Junru Song, B. Gao, G. Tian","doi":"10.1109/FENDT47723.2019.8962747","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962747","url":null,"abstract":"This paper proposes an ensemble tensor factorization to extract defects signal of infrared thermography video. The proposed algorithm jointly models the soft weighted low rank and sparse tensor patterns as well as removing the ghosting. In particular, the weak defects information can be separated from the strong interference and the resolution contrast is significantly improved. A multi-layer ensemble iterative decomposition structure is conducted to further enhance the weak information. In order to verify the effectiveness and robustness of the proposed method, experimental studies have been carried out by applying electromagnetic thermal imaging system for cracks detection on samples with different geometry. The results of the experiments have indicated that the proposed method has significantly enhanced the contrast ratio between the defective regions and the non-defective regions.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126782259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Q. Ma, B. Gao, G. Tian, Chang Rong Yang, Kefan Chen
{"title":"Complexed Shape Micro Defects Inspection By High Sensitivity Flexible TRT Eddy Current Array","authors":"Q. Ma, B. Gao, G. Tian, Chang Rong Yang, Kefan Chen","doi":"10.1109/FENDT47723.2019.8962592","DOIUrl":"https://doi.org/10.1109/FENDT47723.2019.8962592","url":null,"abstract":"High sensitivity nondestructive testing on the complex geometric sample with near-surface micro defects is a critical research area in both scientific and industrial fields. This paper proposes a TRT (transmitting-receiving-transmitting)flexible eddy current sensing system in which incorporating double square windings excitation in parallel with multi-detectors for cracks inspection. Parameters of the probes are optimized through simulations to obtain satisfactory detection sensibilities of defects with different sizes and different orientation. The optimized new structure performs more capability and sensitivity to all presented near-surface micro defects. In addition, the simulation results can be used to cross-referenced and contrasted with the experimental investigations.","PeriodicalId":232572,"journal":{"name":"2019 Far East NDT New Technology & Application Forum (FENDT)","volume":"515 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116564140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}