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Prof. Yunze He
College of Electrical and Information Engineering, Hunan Univerity, Changsha 410072, China

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0 Machine Learning
0 UAV
0 EDGE COMPUTING
0 Thermography
0 intelligent sensing

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Journal article
Published: 14 July 2021 in IEEE Sensors Journal
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Eddy current testing (ECT), is a non-destructive method widely applied in detecting defects of metal plates based on the principle of electromagnetic induction. The flexible eddy current testing (FECT) has been developed from ECT. What’s more, it’s also an effective method that is given a higher priority in defect detection of metal with complex surface structure due to its flexibility and small size. An arrayed differential flexible butterfly-shape eddy current sensor is proposed to detect the surface defect of iron screw thread in this paper, which has one butterfly-shape coil, four sets of differential receiver (RX) coils and one top RX coil, and the proposed sensor is designed as butterfly-shape with a certain folding angle to match with the curvature of the internal and external screw thread, which can solve the lift-off problem of screw thread defect detection at the bottom. The theoretical analysis illustrates the design principle for the proposed sensors. The simulation based on COMSOL Multiphysics is applied to illustrate the probability of the proposed sensor, and the experimental testing system is adopted to verify the high performance of the proposed sensors. The results of simulation and experiment are identical, which show the flexible differential butterfly-shape array eddy current sensor can not only improve the sensitivity and reduce the error rate, but also orientate the defect on the surface of the screw thread.

ACS Style

Saibo She; Youzhi Liu; Shijing Zhang; Yizhang Wen; Zhongji Zhou; Xiaoke Liu; Zihao Sui; Dantong Ren; Fan Zhangb; Yunze He. Flexible Differential Butterfly-Shape Eddy Current Array Sensor for Defect Detection of Screw Thread. IEEE Sensors Journal 2021, PP, 1 -1.

AMA Style

Saibo She, Youzhi Liu, Shijing Zhang, Yizhang Wen, Zhongji Zhou, Xiaoke Liu, Zihao Sui, Dantong Ren, Fan Zhangb, Yunze He. Flexible Differential Butterfly-Shape Eddy Current Array Sensor for Defect Detection of Screw Thread. IEEE Sensors Journal. 2021; PP (99):1-1.

Chicago/Turabian Style

Saibo She; Youzhi Liu; Shijing Zhang; Yizhang Wen; Zhongji Zhou; Xiaoke Liu; Zihao Sui; Dantong Ren; Fan Zhangb; Yunze He. 2021. "Flexible Differential Butterfly-Shape Eddy Current Array Sensor for Defect Detection of Screw Thread." IEEE Sensors Journal PP, no. 99: 1-1.

Journal article
Published: 05 July 2021 in IEEE Sensors Journal
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The traditional condition monitoring (CM) methods for power electronic devices are normally using electrical, magnetic, and thermal sensors. Alternatively, this paper uses the acoustic emission (AE) sensor to measure the mechanical stress wave generated inside the power electronic devices such as MOSFETs. Specifically, this paper focuses on the influence of measured surface, electrical parameters, and filters on the stress wave signal and the reliability of repeatability tests. Under the single pulse test with 300V drain-source voltage (Vds), the same acoustic emission sensor is pasted on the MOSFET package and the cooling surface with a coupling agent. The factors affecting stress waves are studied by changing electrical parameters and filters. The proposed experiments draw the following conclusions. 1) The characteristic parameters of the stress wave measured on the package and cooling surface of MOSFET are different under the same electrical parameters. 2) The characteristic parameters of the stress wave are almost unchanged under the same test conditions, which shows that the stress wave measurement method is reliable. 3) The peak value of the stress wave, the frequency domain amplitude, and energy are affected by Vds and turn-on time (ton). Specifically, the gate voltage Vgs has no obvious trend to the amplitude. The impact on package is basically the same as the cooling surface.

ACS Style

Yun Bai; Haoning Shen; Yunze He; Lei Wang; Fei Liu; Xuefeng Geng; Dantong Ren; Songyuan Liua; Xiangzhao Dang; Yunjia Li. Analysis of the Stress-Wave Influence Parameters of Silicon MOSFET Under 300V Drain Source Voltage. IEEE Sensors Journal 2021, PP, 1 -1.

AMA Style

Yun Bai, Haoning Shen, Yunze He, Lei Wang, Fei Liu, Xuefeng Geng, Dantong Ren, Songyuan Liua, Xiangzhao Dang, Yunjia Li. Analysis of the Stress-Wave Influence Parameters of Silicon MOSFET Under 300V Drain Source Voltage. IEEE Sensors Journal. 2021; PP (99):1-1.

Chicago/Turabian Style

Yun Bai; Haoning Shen; Yunze He; Lei Wang; Fei Liu; Xuefeng Geng; Dantong Ren; Songyuan Liua; Xiangzhao Dang; Yunjia Li. 2021. "Analysis of the Stress-Wave Influence Parameters of Silicon MOSFET Under 300V Drain Source Voltage." IEEE Sensors Journal PP, no. 99: 1-1.

Journal article
Published: 21 January 2021 in Sensors
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The health detection of lithium ion batteries plays an important role in improving the safety and reliability of lithium ion batteries. When lithium ion batteries are in operation, the generation of bubbles, the expansion of electrodes, and the formation of electrode cracks will produce stress waves, which can be collected and analyzed by acoustic emission technology. By building an acoustic emission measurement platform of lithium ion batteries and setting up a cycle experiment of lithium ion batteries, the stress wave signals of lithium ion batteries were analyzed, and two kinds of stress wave signals which could characterize the health of lithium ion batteries were obtained: a continuous acoustic emission signal and a pulse type acoustic emission signal. The experimental results showed that during the discharge process, the amplitude of the continuous acoustic emission signal decreased with the increase of the cycle times of batteries, which could be used to characterize performance degradation; there were more pulse type acoustic emission signals in the first cycle of batteries, less in the small number of cycles, and slowly increased in the large number of cycles, which was in line with the bathtub curve and could be used for aging monitoring. The research on the health of lithium ion batteries by acoustic emission technology provides a new idea and method for detecting the health lithium ion batteries.

ACS Style

Kai Zhang; Jianxiang Yin; Yunze He. Acoustic Emission Detection and Analysis Method for Health Status of Lithium ion Batteries. Sensors 2021, 21, 712 .

AMA Style

Kai Zhang, Jianxiang Yin, Yunze He. Acoustic Emission Detection and Analysis Method for Health Status of Lithium ion Batteries. Sensors. 2021; 21 (3):712.

Chicago/Turabian Style

Kai Zhang; Jianxiang Yin; Yunze He. 2021. "Acoustic Emission Detection and Analysis Method for Health Status of Lithium ion Batteries." Sensors 21, no. 3: 712.

Journal article
Published: 18 December 2020 in IEEE Transactions on Industrial Informatics
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To solve the problems of low efficiency and manual dependence of industrial motor winding testing, a joint scanning electromagnetic thermographic (JSET) method and a new quantitative evaluation algorithm are proposed to inspect defects automatically and assess detection capability. We establish a JSET-based defect inspection system including a joint scanning model and induction heating to simulate industrial assembly lines and acquire real-time thermograms. However, the acquired thermograms are misaligned in time and space which cannot be used for dimension analysis. Therefore, a new 3D data reconstruction algorithm is proposed to achieve accurate spatial-temporal alignment of the image sequence. Moreover, the parameters (scanning speed and excitation current) of the developed inspection system are optimized through obtaining the maximum inspection quantity. The new quantitative evaluation algorithm can measure the detection capability of different defects types, sizes, and positions by two features of significance and detected area. Experimental results show that the proposed methods can inspect multiple motor winding defects automatically and enhance the inspect efficiency.

ACS Style

Yu Peng; Shoudao Huang; BaoYuan Deng; Yunze He; Xin Guo; Hongjin Wang; Jian Han. Joint Scanning Electromagnetic Thermography for Industrial Motor Winding Defect Inspection and Quantitative Evaluation. IEEE Transactions on Industrial Informatics 2020, 17, 6832 -6841.

AMA Style

Yu Peng, Shoudao Huang, BaoYuan Deng, Yunze He, Xin Guo, Hongjin Wang, Jian Han. Joint Scanning Electromagnetic Thermography for Industrial Motor Winding Defect Inspection and Quantitative Evaluation. IEEE Transactions on Industrial Informatics. 2020; 17 (10):6832-6841.

Chicago/Turabian Style

Yu Peng; Shoudao Huang; BaoYuan Deng; Yunze He; Xin Guo; Hongjin Wang; Jian Han. 2020. "Joint Scanning Electromagnetic Thermography for Industrial Motor Winding Defect Inspection and Quantitative Evaluation." IEEE Transactions on Industrial Informatics 17, no. 10: 6832-6841.

Journal article
Published: 30 October 2020 in IEEE Transactions on Instrumentation and Measurement
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Joint laser scanning thermography (JLST) is well-known for its efficiency to overcome the field of view (FOV) limitation of thermal imagers. However, JLST requires a data reconstruction to reveal the location of the defective area straightforwardly. Moreover, its detection capacity is limited by the lack of a deconvolution algorithm adaptive to the reconstructed data. In this study, a deconvolutional reconstruction method based on the Lucy-Richardson (LR) algorithm has been developed for JST, which is effective in suppressing random noise and the blur effect caused by thermal diffusion. A JLST inspection is carried out on a functional coating material with cylinder-like defects to test the performance of the proposed method. In comparison to the directly processed method on the original data, the proposed method is processed on the reconstructed data and then compared with principal component analysis (PCA), restored pseudo heat flux (RPHF), fast Fourier transform (FFT) methods, and non-negative matrix factorization (NMF). The experimental results indicated that our proposed LR method exhibited a higher signal-to-noise ratio. Besides, it can detect the cylinder-mocked debonding defects with a diameter of 1.5 mm and a depth of 2.0 mm buried under the 1.0 mm coating. In addition, the defect detection diameter-to-depth ratio reached 1.5, while the defect detection rate of the test specimens can approach 90%.

ACS Style

Zhiyi He; Hongjin Wang; Yiwen Li; Zhenjun Zhang; Yudong Zhang; Hanbo Bi; Yunze He. A Deconvolutional Reconstruction Method Based on Lucy–Richardson Algorithm for Joint Scanning Laser Thermography. IEEE Transactions on Instrumentation and Measurement 2020, 70, 1 -8.

AMA Style

Zhiyi He, Hongjin Wang, Yiwen Li, Zhenjun Zhang, Yudong Zhang, Hanbo Bi, Yunze He. A Deconvolutional Reconstruction Method Based on Lucy–Richardson Algorithm for Joint Scanning Laser Thermography. IEEE Transactions on Instrumentation and Measurement. 2020; 70 (99):1-8.

Chicago/Turabian Style

Zhiyi He; Hongjin Wang; Yiwen Li; Zhenjun Zhang; Yudong Zhang; Hanbo Bi; Yunze He. 2020. "A Deconvolutional Reconstruction Method Based on Lucy–Richardson Algorithm for Joint Scanning Laser Thermography." IEEE Transactions on Instrumentation and Measurement 70, no. 99: 1-8.

Journal article
Published: 03 August 2020 in Measurement
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Remote field eddy current (RFEC) nondestructive testing has its unique advantages in defect detection of metal pipelines, such as being unaffected by skin effect and material properties, but the size of RFEC probe is large and the signal received by the detection coil is weak. In this paper, a shielding plate is introduced between excitation and detection coil, and a ferromagnetic ring is introduced outside the ferromagnetic pipeline. Both theoretical analysis and finite element method (FEM) simulation are carried out. The result of FEM simulation shows that the distance between the excitation and the detection coil can be shortened after adding a shielding plate; particularly, setting a 1 mm-thick shielding plate 5 mm away from the excitation coil has an optimum optimization effect, which could shorten the distance between the excitation coil and the detection coil by 2 times. The ferromagnetic ring can strengthen the detected signal, and the closer it gets to the detection coil, the stronger magnetic flux density will be detected in the latter. Therefore, it provides a direction for the structural optimization of RFEC testing device.

ACS Style

Saibo She; Yifang Chen; Yunze He; Zhongji Zhou; Xiang Zou. Optimal design of remote field eddy current testing probe for ferromagnetic pipeline inspection. Measurement 2020, 168, 108306 .

AMA Style

Saibo She, Yifang Chen, Yunze He, Zhongji Zhou, Xiang Zou. Optimal design of remote field eddy current testing probe for ferromagnetic pipeline inspection. Measurement. 2020; 168 ():108306.

Chicago/Turabian Style

Saibo She; Yifang Chen; Yunze He; Zhongji Zhou; Xiang Zou. 2020. "Optimal design of remote field eddy current testing probe for ferromagnetic pipeline inspection." Measurement 168, no. : 108306.

Review article
Published: 01 August 2020 in Mechanical Systems and Signal Processing
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Renewable energy (RE) does not pollute environment at the point of energy generation, and generally has a much lower pollution footprint than traditional energy from installing to decommissioning, and can diversify the power generation technology. Because of the high operation and maintenance (O&M) costs, it is necessary to build remote, online, credible monitoring and inspection techniques. Acoustic emission (AE) technology is effective and efficient to monitor and detect mechanical damage, deterioration, and failure, etc. Over the recent years, a remarkable number of scientific papers demonstrate the capability of AE in nondestructive testing (NDT), structure health monitoring (SHM), condition monitoring (CM) and fault diagnosis for RE generation, transmission, transformation and storage systems. Most of work focusing on detection principle, sensor design, signal processing and diagnosis has provided a lot of valuable contributions for academic and industrial fields. Nevertheless, all this valuable information is scattered over many sub-fields of literature, and the knowledge is not systematic. This paper is dedicated to analyze the different AE principles in RE systems, and to comprehensively summarize and clearly highlight the advanced methods and challenges. Development trends in research, application and standard are also discussed and suggested.

ACS Style

Yunze He; Mengchuan Li; Zhiqiang Meng; Sheng Chen; Shoudao Huang; Yi Hu; Xiang Zou. An overview of acoustic emission inspection and monitoring technology in the key components of renewable energy systems. Mechanical Systems and Signal Processing 2020, 148, 107146 .

AMA Style

Yunze He, Mengchuan Li, Zhiqiang Meng, Sheng Chen, Shoudao Huang, Yi Hu, Xiang Zou. An overview of acoustic emission inspection and monitoring technology in the key components of renewable energy systems. Mechanical Systems and Signal Processing. 2020; 148 ():107146.

Chicago/Turabian Style

Yunze He; Mengchuan Li; Zhiqiang Meng; Sheng Chen; Shoudao Huang; Yi Hu; Xiang Zou. 2020. "An overview of acoustic emission inspection and monitoring technology in the key components of renewable energy systems." Mechanical Systems and Signal Processing 148, no. : 107146.

Review
Published: 30 May 2020 in Infrared Physics & Technology
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Renewable and sustainable energy (RSE) system has a significant potential to mitigate carbon emissions and diversify the electricity generation portfolios acknowledged by international policy. Faults and damages are inevitable during either fabrication or lifetime of the key equipment of the RSE system. Owing to the high operation and maintenance (O&M) costs, it is essential to develop reliable and remote detection techniques for key equipment of the RSE system. In this paper, the research progress in infrared thermography (IRT) fault diagnosis for the RSE system is reviewed in detail. For the RSE generation system, the applications of IRT in parabolic trough receiver, wind turbine blade, and photovoltaic cell are reviewed. For the RSE transmission and transmainly used under open-circuit conditions formation system, this work focuses on detecting damage in insulators and IGBT. For the RSE storage system, fault diagnosis in proton exchange membrane fuel cell and lithium-ion battery based on IRT are reviewed. Moreover, state-of-the-art methods have been comprehensively summarized and highlighted. Besides, challenges and future trends in NDT and fault diagnosis for the RSE system based on IRT are also discussed and analyzed. Finally, this paper will serve as a guide for defect detection and fault diagnosis of RSE key equipment based on IRT. It has essential academic and industrial application value in the fields of RSE system security control and cost-saving.

ACS Style

Bolun Du; Yigang He; Yunze He; Chaolong Zhang. Progress and trends in fault diagnosis for renewable and sustainable energy system based on infrared thermography: A review. Infrared Physics & Technology 2020, 109, 103383 .

AMA Style

Bolun Du, Yigang He, Yunze He, Chaolong Zhang. Progress and trends in fault diagnosis for renewable and sustainable energy system based on infrared thermography: A review. Infrared Physics & Technology. 2020; 109 ():103383.

Chicago/Turabian Style

Bolun Du; Yigang He; Yunze He; Chaolong Zhang. 2020. "Progress and trends in fault diagnosis for renewable and sustainable energy system based on infrared thermography: A review." Infrared Physics & Technology 109, no. : 103383.

Journal article
Published: 18 May 2020 in IEEE Sensors Journal
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In this work, multiple floral eddy current probes (FECP) are proposed. FECP consists of a detection coil and a plurality of symmetric excitation coils, and due to the number of excitation coils, it could be classified into 4-coils, 6-coils, 8-coils, or 10-coils FECP. Due to the innovation of its configuration that transmitter (TX) coils are successively connected in reverse order and distributed symmetrically around receiver (RX) coil, the proposed new probe is not only less sensitive to the change of the lift-off distance but also has high accuracy and sensitivity of detection and could resist vibration interference. In this paper, the theoretical model of FECP is established, and simulation and experiment verification are carried out respectively. Firstly, the lift-off effect is studied. Moreover, an aluminum tested plate with artificial flaws is used to evaluate the performance of differenttype of flexible FECP, which shows higher sensitivity in flaws than the conventional single coil.

ACS Style

Saibo She; Yunze He; Yifang Chen; Tomasz Chady. Flexible Floral Eddy Current Probe for Detecting Flaws in Metal Plate. IEEE Sensors Journal 2020, 20, 10521 -10529.

AMA Style

Saibo She, Yunze He, Yifang Chen, Tomasz Chady. Flexible Floral Eddy Current Probe for Detecting Flaws in Metal Plate. IEEE Sensors Journal. 2020; 20 (18):10521-10529.

Chicago/Turabian Style

Saibo She; Yunze He; Yifang Chen; Tomasz Chady. 2020. "Flexible Floral Eddy Current Probe for Detecting Flaws in Metal Plate." IEEE Sensors Journal 20, no. 18: 10521-10529.

Journal article
Published: 17 February 2020 in IEEE Sensors Journal
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In this paper, based on acoustic emission (AE) monitoring and digital filtering technology, the low and high frequency components in the switching mechanical stress wave (MSW) of insulated gate bipolar transistor (IGBT) device were discovered for the first time. Then, the effects of turn-off current on the low and high frequency components were studied. The obviously linear relationship was found between the low frequency component and the turn-off current, and the low frequency component could closely follow the change of turn-off current, showing that the low frequency component was strongly related with turn-off current. The high frequency component contained two pulse waves with the inverse phase, single frequency and high similarity, and it was weakly linear related with or not linear related the turn off current, and it was insensitive to the change of turn-off current, proving that the turn-off current was not the main cause of the high frequency component. Besides, the repeatability test was performed on another IGBT device, showing good repeatability for the experimental results.

ACS Style

Mengchuan Li; Yunze He; Zhiqiang Meng; Jun Wang; Xiang Zou; Yi Hu; Zhibin Zhao. Acoustic Emission-Based Experimental Analysis of Mechanical Stress Wave in IGBT Device. IEEE Sensors Journal 2020, 20, 6064 -6074.

AMA Style

Mengchuan Li, Yunze He, Zhiqiang Meng, Jun Wang, Xiang Zou, Yi Hu, Zhibin Zhao. Acoustic Emission-Based Experimental Analysis of Mechanical Stress Wave in IGBT Device. IEEE Sensors Journal. 2020; 20 (11):6064-6074.

Chicago/Turabian Style

Mengchuan Li; Yunze He; Zhiqiang Meng; Jun Wang; Xiang Zou; Yi Hu; Zhibin Zhao. 2020. "Acoustic Emission-Based Experimental Analysis of Mechanical Stress Wave in IGBT Device." IEEE Sensors Journal 20, no. 11: 6064-6074.

Journal article
Published: 11 November 2019 in IEEE Sensors Journal
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Electrical rotating motor is one of kernel equipment of industrial applications. They are subjected to various thermal, environmental, load stresses that ultimately lead to failure and catastrophic accidents. Winding inter-turn fault is the most severe faults in the motors. Defects inspection is of great significance to ensure safety operation and reduce downtime. In this paper, eddy current pulsed thermography (ECPT) was firstly applied to defect four types of winding defects, namely, transverse crack, slot crack, insulation breakage and insulation thinning. The mechanisms of electromagnetic induction and heat conduction in the process of ECPT are introduced. The electromagnetic fields and temperature distributions of different types of defects are simulated and analyzed through multiphysics-based models. Experiments are conducted on a winding copper bar cracks sample covered by polyimide (PI) film. The validity of ECPT is verified with the analysis of IR images and thermal responses. In order to further improve the detection capability of ECPT, signal processing algorithms such as Fast Fourier Transform (FFT) and Principal Component Analysis (PCA) are applied to enhance cracks characteristics in the original IR images by eliminating the non-uniform heating effect. Obtained results demonstrated that ECPT is a feasible and effective approach for motor winding defects inspection.

ACS Style

Yu Peng; Shoudao Huang; Yunze He; Xin Guo. Eddy Current Pulsed Thermography for Noncontact Nondestructive Inspection of Motor Winding Defects. IEEE Sensors Journal 2019, 20, 2625 -2634.

AMA Style

Yu Peng, Shoudao Huang, Yunze He, Xin Guo. Eddy Current Pulsed Thermography for Noncontact Nondestructive Inspection of Motor Winding Defects. IEEE Sensors Journal. 2019; 20 (5):2625-2634.

Chicago/Turabian Style

Yu Peng; Shoudao Huang; Yunze He; Xin Guo. 2019. "Eddy Current Pulsed Thermography for Noncontact Nondestructive Inspection of Motor Winding Defects." IEEE Sensors Journal 20, no. 5: 2625-2634.

Journal article
Published: 12 September 2019 in IEEE Sensors Journal
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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 flatbottom 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 fast Fourier transform (FFT) amplitude image, independent component analysis (ICA) and FFT phase image. The JSLT system is used to detect FBH and the diameter-depth ratio reached 3.33.

ACS Style

Zhiyi He; Hongjin Wang; Yunze He; Guixiang Zhang; Jiazheng Wang; GaoYu Zou; Tomasz Chady. Joint Scanning Laser Thermography Defect Detection Method for Carbon Fiber Reinforced Polymer. IEEE Sensors Journal 2019, 20, 328 -336.

AMA Style

Zhiyi He, Hongjin Wang, Yunze He, Guixiang Zhang, Jiazheng Wang, GaoYu Zou, Tomasz Chady. Joint Scanning Laser Thermography Defect Detection Method for Carbon Fiber Reinforced Polymer. IEEE Sensors Journal. 2019; 20 (1):328-336.

Chicago/Turabian Style

Zhiyi He; Hongjin Wang; Yunze He; Guixiang Zhang; Jiazheng Wang; GaoYu Zou; Tomasz Chady. 2019. "Joint Scanning Laser Thermography Defect Detection Method for Carbon Fiber Reinforced Polymer." IEEE Sensors Journal 20, no. 1: 328-336.

Journal article
Published: 13 June 2019 in IEEE Transactions on Industrial Informatics
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In the process of research, development, production, service and maintenance of silicon photovoltaic (Si-PV) cells, the requirements for detection technology become more and more important. This paper aims to investigate electromagnetic induction (EMI) and image fusion to improve detection effect of Electro-thermography (ET) and Electroluminescence (EL) of multi-defects in Si-PV cells. Firstly, the principle of ET, EL and other physical processes including EMI, thermal radiation, luminescence radiation are analyzed in this work. ET and EL techniques after EMI improvement are used to detect different defects including scratch, broken gridline, surface impurity, hidden crack and so on. The qualitative results show that EMI can greatly improve the defect detection ability of ET and EL. Then, an image fusion rule based on L1 norm is proposed to fuse the sparse vector of the ET and EL images. The integration and complementarity of the two wavelength detection data are achieved. Finally, the image fusion results of Sparse Representation (SR) algorithm is compared with Discrete Wavelet Transform (DWT), Curvelet Transform (CVT), Dual-tree Complex Wavelet Transforms (DTCWT) and Nonsubsampled Contourlet Transform (NSCT). Five objective evaluation indexes including Root Means Square Error (RMSE), Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), Mutual Information (MI) and Structural Similarity Index (SSIM) are used to evaluate the fusion results. Overall evaluation results show that the SR algorithm is superior to the other algorithms.

ACS Style

Ruizhen Yang; Bolun Du; Puhong Duan; Yunze He; Hongjin Wang; Yigang He; Kai Zhang. Electromagnetic Induction Heating and Image Fusion of Silicon Photovoltaic Cell Electrothermography and Electroluminescence. IEEE Transactions on Industrial Informatics 2019, 16, 4413 -4422.

AMA Style

Ruizhen Yang, Bolun Du, Puhong Duan, Yunze He, Hongjin Wang, Yigang He, Kai Zhang. Electromagnetic Induction Heating and Image Fusion of Silicon Photovoltaic Cell Electrothermography and Electroluminescence. IEEE Transactions on Industrial Informatics. 2019; 16 (7):4413-4422.

Chicago/Turabian Style

Ruizhen Yang; Bolun Du; Puhong Duan; Yunze He; Hongjin Wang; Yigang He; Kai Zhang. 2019. "Electromagnetic Induction Heating and Image Fusion of Silicon Photovoltaic Cell Electrothermography and Electroluminescence." IEEE Transactions on Industrial Informatics 16, no. 7: 4413-4422.

Journal article
Published: 18 December 2018 in IEEE Transactions on Industrial Informatics
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ACS Style

Hongjin Wang; Nichen Wang; Zhiyi He; Yunze He. Phase-Locked Restored Pseudo Heat Flux Thermography for Detecting Delamination Inside Carbon Fiber Reinforced Composites. IEEE Transactions on Industrial Informatics 2018, 15, 2938 -2946.

AMA Style

Hongjin Wang, Nichen Wang, Zhiyi He, Yunze He. Phase-Locked Restored Pseudo Heat Flux Thermography for Detecting Delamination Inside Carbon Fiber Reinforced Composites. IEEE Transactions on Industrial Informatics. 2018; 15 (5):2938-2946.

Chicago/Turabian Style

Hongjin Wang; Nichen Wang; Zhiyi He; Yunze He. 2018. "Phase-Locked Restored Pseudo Heat Flux Thermography for Detecting Delamination Inside Carbon Fiber Reinforced Composites." IEEE Transactions on Industrial Informatics 15, no. 5: 2938-2946.

Journal article
Published: 18 December 2018 in Composites Part B: Engineering
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The impact damage of carbon-fiber-reinforced polymers (CFRPs) must be considered important in order to avoid catastrophic accidents. Low-velocity impact commonly results in barely visible impact damages (BVIDs) in a CFRP component, and is impossible to be detected by visual inspection or machine vision. To rapidly and effectively detect BVIDs in CFRPs, this work proposes a damage inspection method based on an ultrasound wave distortion indicator. The indicator reveals ultrasound higher harmonics, subharmonics, and self-modulation caused by local damage in CFRPs. The experimental system was built after the proposed non-destructive testing (NDT) methodology was introduced. An intact CFRP plate specimen, and specimens with BVIDs and visible impact damage (VID) were tested using the proposed method. The relationship between impact energies and the ultrasound wave distortion indicator was built. The proposed method could provide an effective inspection means for assessing the impact damage of CFRP materials.

ACS Style

Xiaofei Zhang; Xuan Wu; Yunze He; Shuming Yang; Sheng Chen; Shigang Zhang; Deqiang Zhou. CFRP barely visible impact damage inspection based on an ultrasound wave distortion indicator. Composites Part B: Engineering 2018, 168, 152 -158.

AMA Style

Xiaofei Zhang, Xuan Wu, Yunze He, Shuming Yang, Sheng Chen, Shigang Zhang, Deqiang Zhou. CFRP barely visible impact damage inspection based on an ultrasound wave distortion indicator. Composites Part B: Engineering. 2018; 168 ():152-158.

Chicago/Turabian Style

Xiaofei Zhang; Xuan Wu; Yunze He; Shuming Yang; Sheng Chen; Shigang Zhang; Deqiang Zhou. 2018. "CFRP barely visible impact damage inspection based on an ultrasound wave distortion indicator." Composites Part B: Engineering 168, no. : 152-158.

Journal article
Published: 01 December 2018 in Infrared Physics & Technology
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Pedestrian recognition is the core technology of pedestrian detection in pedestrian protection systems. This paper compares and analyzes, visible and infrared images obtained via visible-spectrum, near-infrared, short-wave infrared, and long-wave infrared cameras. The results show that near-infrared camera was the best for nighttime pedestrian detection when device cost and pedestrian imaging quality were considered. This paper reports on the first time use of a self-learning softmax with a 9-layer Convolutional Neural Network (CNN) model to identify near-infrared nighttime pedestrians. 267,000 samples obtained from the near-infrared images were employed to optimize the CNN recognition model. Collected near-infrared nighttime samples had 3 categories (background, pedestrian, and cyclist or motorcyclist) and will be made publicly available for researchers use. Testing results indicated that the optimized CNN model using self-learning softmax had a competitive accuracy and potential in real-time pedestrian recognition.

ACS Style

Xiaobiao Dai; Yuxia Duan; Junping Hu; Shicai Liu; Caiqi Hu; Yunze He; Dapeng Chen; Chunlei Luo; Jianqiao Meng. Near infrared nighttime road pedestrians recognition based on convolutional neural network. Infrared Physics & Technology 2018, 97, 25 -32.

AMA Style

Xiaobiao Dai, Yuxia Duan, Junping Hu, Shicai Liu, Caiqi Hu, Yunze He, Dapeng Chen, Chunlei Luo, Jianqiao Meng. Near infrared nighttime road pedestrians recognition based on convolutional neural network. Infrared Physics & Technology. 2018; 97 ():25-32.

Chicago/Turabian Style

Xiaobiao Dai; Yuxia Duan; Junping Hu; Shicai Liu; Caiqi Hu; Yunze He; Dapeng Chen; Chunlei Luo; Jianqiao Meng. 2018. "Near infrared nighttime road pedestrians recognition based on convolutional neural network." Infrared Physics & Technology 97, no. : 25-32.

Journal article
Published: 26 October 2018 in Applied Sciences
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In this paper, we investigate pulsed eddy current (PEC) testing based on a rectangular sensor for the purpose of defect shape mapping in electric vehicle lightweight alloy material. Different dimensional defects were machined on the 3003 aluminum alloy and detected using the A-scan technique and C-scan imaging in two scanning directions. The experiment results indicated that defect plane shape could be preliminarily obtained and length and width could be estimated based upon C-scan contour images. Consequently, the comparison of results between the two directions showed that the C-scan identification in the direction of magnetic flux was better than in the direction of the exciting current. Finally, subsurface defects and irregular defects were detected to verify the performance of shape mapping as a recommended approach. The conclusion drawn indicates that the proposed method, based on PEC rectangular sensors, is an effective approach in reconstructing a defect’s shape.

ACS Style

Kai Zhang; Zhurong Dong; Zhan Yu; Yunze He. Shape Mapping Detection of Electric Vehicle Alloy Defects Based on Pulsed Eddy Current Rectangular Sensors. Applied Sciences 2018, 8, 2066 .

AMA Style

Kai Zhang, Zhurong Dong, Zhan Yu, Yunze He. Shape Mapping Detection of Electric Vehicle Alloy Defects Based on Pulsed Eddy Current Rectangular Sensors. Applied Sciences. 2018; 8 (11):2066.

Chicago/Turabian Style

Kai Zhang; Zhurong Dong; Zhan Yu; Yunze He. 2018. "Shape Mapping Detection of Electric Vehicle Alloy Defects Based on Pulsed Eddy Current Rectangular Sensors." Applied Sciences 8, no. 11: 2066.

Journal article
Published: 21 August 2018 in IEEE Transactions on Industrial Informatics
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Impact damage, caused by low-energy impact, is inevitable during the whole life time of carbon fiber reinforced plastic (CFRP) material. However, the barely visible impact damage (BVID) is difficult to be detected by visual methods. Ultrasonic thermography (UT) is an emerging non-destructive testing technique that visualizes damage in thermal images captured by an infrared (IR) camera when the material is stimulated by ultrasound. However, noise and blurry edges around the high temperature areas may cause confusion and lead to unreliable results in the thermal images of UT test. In this work, an impact damage inspection method is proposed based on manifold learning for CFRP material. Low-power ultrasonic excitation is used for this UT. The IR image sequences are processed as data sets in high-dimensional space. These data sets are reduced to lower dimensions by manifold learning to find the intrinsic structure in the two-dimensional manifold. Each dimension of the embedding manifold correlates highly with one degree of freedom underlying the original pixel: steady and random components. The steady component, which reflects the temperature rise caused by damage, is used for VID and BVID detection. The experimental system was set up, and CFRP plate specimens with different impact damage were tested. All the impact damage could be detected and shown in reconstructed static image with little noise. The proposed method using image sequences could provide a visualized, reliable and effective impact damage inspection and localization means for CFRP material during manufacturing and in service.

ACS Style

Xiaofei Zhang; Yunze He; Tomasz Chady; Gui Yun Tian; Jingwei Gao; Hongjin Wang; Sheng Chen. CFRP Impact Damage Inspection Based on Manifold Learning Using Ultrasonic Induced Thermography. IEEE Transactions on Industrial Informatics 2018, 15, 2648 -2659.

AMA Style

Xiaofei Zhang, Yunze He, Tomasz Chady, Gui Yun Tian, Jingwei Gao, Hongjin Wang, Sheng Chen. CFRP Impact Damage Inspection Based on Manifold Learning Using Ultrasonic Induced Thermography. IEEE Transactions on Industrial Informatics. 2018; 15 (5):2648-2659.

Chicago/Turabian Style

Xiaofei Zhang; Yunze He; Tomasz Chady; Gui Yun Tian; Jingwei Gao; Hongjin Wang; Sheng Chen. 2018. "CFRP Impact Damage Inspection Based on Manifold Learning Using Ultrasonic Induced Thermography." IEEE Transactions on Industrial Informatics 15, no. 5: 2648-2659.

Journal article
Published: 01 August 2018 in Sensors and Actuators A: Physical
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ACS Style

Deqiang Zhou; Xiang Chang; Yunze He; Hua Wang; Piyu Cao; Li Yang. Influence of key factors on Eddy current testing sensitivity and monotonicity on subsurface depth for ferromagnetic and non-ferromagnetic materials. Sensors and Actuators A: Physical 2018, 278, 98 -110.

AMA Style

Deqiang Zhou, Xiang Chang, Yunze He, Hua Wang, Piyu Cao, Li Yang. Influence of key factors on Eddy current testing sensitivity and monotonicity on subsurface depth for ferromagnetic and non-ferromagnetic materials. Sensors and Actuators A: Physical. 2018; 278 ():98-110.

Chicago/Turabian Style

Deqiang Zhou; Xiang Chang; Yunze He; Hua Wang; Piyu Cao; Li Yang. 2018. "Influence of key factors on Eddy current testing sensitivity and monotonicity on subsurface depth for ferromagnetic and non-ferromagnetic materials." Sensors and Actuators A: Physical 278, no. : 98-110.

Journal article
Published: 12 June 2018 in IEEE Sensors Journal
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In the whole life time of carbon fiber reinforced plastic (CFRP) component, it will inevitably suffer from low-energy impact (LEI) loads, which may lead to barely visible impact damage (BVID). Thus, non-destructive testing (NDT) of impact damage has attracted more and more attention. In this work, the detection of BVID in CFRP plates induced by LEI is investigated by means of nonlinear ultrasound (NU) with the help of signal sparse reconstruction with overcomplete dictionary obtained from training of the acquired responses of the undamaged component. A damage inspection and structural health monitoring (SHM) framework for CFRP component is proposed. The intact CFRP plate specimen and specimens with 12J and 16J BVID were tested using the proposed method. Experimental results have shown that all the BVIDs could be detected effectively using a short segment of response signal. The proposed method has potential application in instrumentation design for unsupervised damage inspection and SHM during daily maintain in service of CFRP material.

ACS Style

Xiaofei Zhang; Derong Luo; Yunze He; Xinpeng Zhang; Sheng Chen; Yonggang Xiao. CFRP Barely Visible Impact Damage Inspection Based on Nonlinear Ultrasound Signal Sparse Reconstruction. IEEE Sensors Journal 2018, 18, 6303 -6310.

AMA Style

Xiaofei Zhang, Derong Luo, Yunze He, Xinpeng Zhang, Sheng Chen, Yonggang Xiao. CFRP Barely Visible Impact Damage Inspection Based on Nonlinear Ultrasound Signal Sparse Reconstruction. IEEE Sensors Journal. 2018; 18 (15):6303-6310.

Chicago/Turabian Style

Xiaofei Zhang; Derong Luo; Yunze He; Xinpeng Zhang; Sheng Chen; Yonggang Xiao. 2018. "CFRP Barely Visible Impact Damage Inspection Based on Nonlinear Ultrasound Signal Sparse Reconstruction." IEEE Sensors Journal 18, no. 15: 6303-6310.