{"title":"Health Status Prediction of High-Speed Railway Wheel Diameter Size Based on Hidden Markov Model","authors":"Yu Zhang, Wen-Ling Jian, Chun-rong Qiu, Lin Luo","doi":"10.1109/fendt50467.2020.9337511","DOIUrl":"https://doi.org/10.1109/fendt50467.2020.9337511","url":null,"abstract":"It is beneficial for reducing maintenance costs and improving train safety and reliability to predict and evaluate the condition of railway wheel-set dimensional value. A wheel-set size state prediction model based on the Hidden Markov Model (HMM) algorithm is proposed to predict the state of high-speed railway wheel diameter. The state interval is established according to the change range of the wheel diameter value. And then the corresponding transition probability matrix is used as the input data of the HMM to establish a state prediction model of the wheel size. Finally, the state prediction result is obtained by this method. The experimental results show that aiming at wheel-set data, the accuracy, precision, recall rate and Fl of HMM can reach 0.9, 0.8, 0.8 and 0.8 respectively. Compared with Markov, Graymarkov based on state prediction algorithm and Anfis algorithm based on data prediction, the validity and accuracy of the HMM model in predicting wheel-set size state are verified.","PeriodicalId":302672,"journal":{"name":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124867057","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}
Jin Zhang, Z. Dong, Xue-bin Wang, Wenze Shi, Xin Wang, Qinchun Tang
{"title":"Study on characteristics of radiation sound field of line-focusing angled SV wave EMAT","authors":"Jin Zhang, Z. Dong, Xue-bin Wang, Wenze Shi, Xin Wang, Qinchun Tang","doi":"10.1109/fendt50467.2020.9337541","DOIUrl":"https://doi.org/10.1109/fendt50467.2020.9337541","url":null,"abstract":"The Electromagnetic acoustic transducer (EMAT) has valuable applications in ultrasonic nondestructive testing. The bidirectional radiation characteristics of the meander-line coil EMAT interfere with the location/ quantification of defects and affect the sensitivity of defect detection. It is the basis of defect detection to study the influence of the design parameters of the meander-line coil EMAT on its radiation sound field. Therefore, a finite element model for radiation sound field of line-focusing angled SV wave EMAT (LF-EMAT) is proposed to analyze the influences of meander-line coil turns and the initial angle on the main lobe peak and width of SV wave of the focusing side, as well as on the ratio of the peak value of the focusing side to that of the non-focusing side. Meanwhile, the experimental measurement and verification of the radiation sound field has been carried out. Results have shown that the lobe peak of the focusing side of LF-EMAT radiation sound field can reach about twice that of the non-focusing side. And as the number of meander-line coil turns increases, the energy and directivity of the focusing SV wave are enhanced, and the main lobe peak increases by more than 79.41%.","PeriodicalId":302672,"journal":{"name":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128920649","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}
Jingjun Li, C. Yan, Z. Rui, Luo-Dan Zhang, Ying-tao Wang
{"title":"A Quantitative Evaluation Method of Aero-engine Blade Defects Based on Ultrasonic C-Scan","authors":"Jingjun Li, C. Yan, Z. Rui, Luo-Dan Zhang, Ying-tao Wang","doi":"10.1109/fendt50467.2020.9337557","DOIUrl":"https://doi.org/10.1109/fendt50467.2020.9337557","url":null,"abstract":"Given the unintuitive and nonquantitative analysis of traditional artificial detection results of aero-engine blades, a characterization evaluation technique has been carried out based on ultrasonic defect point cloud. 3-D reconstruction display model of ultrasonic point cloud was completed by ultrasonic C-Scan imaging principle, spatial surface display technology, and 3-D visualization technology. A hybrid reconstruction method based on Delaunay triangulation and mesh growth algorithm was proposed, which achieved the 3-D reconstruction of a defect point cloud of regional discretization, the obtained results exhibited the spatial distribution of defect area, which intuitively provided the comprehensive view of 3-D defect model. Furthermore, the defect area was calculated via the vertex coordinates of each triangle in the reconstruction mesh. Taking flat-bottom holes as an example, an experimental model for quantitative evaluation was established based on the method. The quantization error of defect size is less than ±10% with comparison of the prefabricated defect size, so the feasibility and accuracy of the method are verified, which provides a convenient and effective way to quantitatively characterize the defects of curved components with immersion ultrasonic testing.","PeriodicalId":302672,"journal":{"name":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123727330","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":"Defect Length Prediction of Aluminum Alloy Sheet by Using Differential Evolution-Support Vector Regression (DE-SVR)","authors":"Y. Wu, Xiaoqin Gao, Hong-na Zhu","doi":"10.1109/fendt50467.2020.9337552","DOIUrl":"https://doi.org/10.1109/fendt50467.2020.9337552","url":null,"abstract":"Aluminum alloy sheet has been widely applied in transport manufacturing industry due to its good mechanical properties. However, aluminum alloy sheet can inevitably generate defects in the process of processing and forming. In this paper, through the Support Vector Regression (SVR) model optimized by Differential Evolution (DE) algorithm, the collected Lamb wave signal in aluminum alloy sheet is analyzed and processed to detect the defect length in aluminum alloy sheet. The error penalty parameter $C$ and kernel function $g$ of SVR can be optimized constantly by using the selection, crossover, mutation operators and greedy selection strategies of DE algorithm. The feature matrix of Lamb wave signal is extracted and introduced into Particle Swarm Optimization-Support Vector Regression (PSO-SVR), Genetic Algorithm-Support Vector Regression (GA-SVR) and DE-SVR to compare and analyze the defect length error evaluation indexes. The results show that DE-SVR can greatly improve the speed and accuracy of defect length prediction of aluminum alloy sheet.","PeriodicalId":302672,"journal":{"name":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126327975","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}
Ming Sun, J. Li, Shiying Li, D. Lin, Hanna Chen, Zhi-Shui Li
{"title":"Ultrasonic Stress Measurement and Finite Element Analysis of Settlement Pipeline","authors":"Ming Sun, J. Li, Shiying Li, D. Lin, Hanna Chen, Zhi-Shui Li","doi":"10.1109/fendt50467.2020.9337535","DOIUrl":"https://doi.org/10.1109/fendt50467.2020.9337535","url":null,"abstract":"Due to the influence of geological factors, the settlements of pipelines occur in the service process. Local high stress positions of settlement pipelines have the phenomena of stress concentration, which threatens the safe operation of pipelines. How to measure and evaluate the stress state of settlement pipelines is an urgent problem to be solved for pipeline enterprises. Because the acoustic elastic effect of ultrasonic mainly depends on the stress in the material, the specific relationship between the acoustoelastic constant of ultrasonic and stress can be used to measure the pipeline stress. Taking the settlement pipeline in a gas storage station as an example, the axial stress of the pipeline is measured based on the ultrasonic longitudinal wave method, and the finite element model is established. The finite element analysis results are compared with the stress measurement results to determine the current settlement displacement and safety state of the pipeline.","PeriodicalId":302672,"journal":{"name":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127042432","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":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","authors":"","doi":"10.1109/fendt36516.2015","DOIUrl":"https://doi.org/10.1109/fendt36516.2015","url":null,"abstract":"","PeriodicalId":302672,"journal":{"name":"2020 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121429134","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}