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学者姓名：刘增华
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Abstract ：
Bolted joints frequently experience loosening in vibrating environments, posing a threat to structural safety. Therefore, quantitatively assessing bolt loosening is critical. This study reveals the correlation between bolt preload and acoustic emission (AE) signal characteristics at the connection interface under vibration, establishing a method for quantitatively assessing the tightening state of bolted joints. First, an AE testing platform was constructed to capture AE signals across varying preload forces, enabling the calculation of frequency and energy parameters. Next, leveraging the relationship between these AE characteristics and preload force, a loosening index was developed to quantitatively assess the extent of bolt loosening. Finally, a quantitative AE-based assessment method and workflow for evaluating bolted joint status were developed, allowing for effective assessment of the full transition from tightened to loosened states. This approach provides a valuable tool for detecting bolt loosening and monitoring structural health.
Keyword ：
acoustic emission acoustic emission Bolted joint Bolted joint bolt loosening bolt loosening quantitative assessment quantitative assessment
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| GB/T 7714 | Wang, Xiaoran , Chen, Yongjia , Liu, Zenghua et al. Frequency domain-based quantitative assessment of bolted joint tightening status using acoustic emission [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2025 . |
| MLA | Wang, Xiaoran et al. "Frequency domain-based quantitative assessment of bolted joint tightening status using acoustic emission" . | NONDESTRUCTIVE TESTING AND EVALUATION (2025) . |
| APA | Wang, Xiaoran , Chen, Yongjia , Liu, Zenghua , Zhang, Jianing , Li, Hongyu . Frequency domain-based quantitative assessment of bolted joint tightening status using acoustic emission . | NONDESTRUCTIVE TESTING AND EVALUATION , 2025 . |
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Abstract ：
Bolted joints are a critical fastening method widely used in mechanical structures, and monitoring their loosening, particularly in the early loosening, is crucial for ensuring structural safety and reliability. This article presents a method for full lifecycle quantitative monitoring and early warning of bolt loosening based on acoustic emission (AE) technology. Variational mode decomposition is applied to the AE signals from the bolted joint interface to extract the energy characteristics of the intrinsic mode functions (IMFs). The IMFs most sensitive to changes in preload force are then selected as the characteristic mode. Segmented fitting equations are developed for the relationship between the energy of this characteristic mode and the bolt preload force across three key stages of loosening: early loosening, intermediate loosening, and late loosening. These equations enable effective monitoring and quantitative assessment of bolt loosening. This method not only allows for full lifecycle monitoring of bolted joints from fastening to loosening but also provides effective early warnings during the initial loosening phase.
Keyword ：
acoustic emission acoustic emission early warning early warning quantitative monitoring quantitative monitoring variational mode decomposition variational mode decomposition Bolted joint Bolted joint
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| GB/T 7714 | Wang, Xiaoran , Zhang, Jianing , Liu, Zenghua et al. Full lifecycle quantitative monitoring and early warning of bolt loosening based on acoustic emission [J]. | STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL , 2025 . |
| MLA | Wang, Xiaoran et al. "Full lifecycle quantitative monitoring and early warning of bolt loosening based on acoustic emission" . | STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2025) . |
| APA | Wang, Xiaoran , Zhang, Jianing , Liu, Zenghua , He, Tian , Tang, Guoliang . Full lifecycle quantitative monitoring and early warning of bolt loosening based on acoustic emission . | STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL , 2025 . |
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Abstract ：
Thermal barrier coatings (TBCs) are critical thermal protection systems for the high-temperature components of aero-engines, and their performance evaluation is essential. Terahertz nondestructive testing (THz-NDT) technology, known for its unique advantages of non-contact application and high penetration capability, has demonstrated significant potential in evaluating TBCs. This paper presents an overview of recent advances in THz-NDT applications for TBCs, with a focus on detecting optical parameters, thickness, porosity, and thermal growth oxide of the coatings. Terahertz time-domain spectroscopy enables an in-depth analysis of the physical properties of TBCs through two detection methods: transmission and reflection. Moreover, advancements in signal processing algorithms, image processing technologies, and machine learning have substantially enhanced the sensitivity, spatial resolution, and real-time performance of THz-NDT. The integration of these technologies has improved the analysis of complex coating structures and broadened the application range of terahertz technology. However, terahertz technology still encounters various challenges in practical applications, including signal attenuation in high-temperature environments and processing difficulties due to complex coating structures. In the future, as terahertz technology continues to advance and new algorithms are integrated, THz-NDT is expected to play an increasingly vital role in the quality assessment, life prediction, and health monitoring of high-temperature materials.
Keyword ：
Thermal barrier coatings Thermal barrier coatings terahertz non-destructive testing terahertz non-destructive testing optical parameter optical parameter thickness thickness thermal growth oxide thermal growth oxide porosity porosity
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| GB/T 7714 | Liu, Zenghua , Li, Rui , Wu, Yuheng et al. Progress in terahertz nondestructive testing of thermal barrier coatings: a review [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2025 . |
| MLA | Liu, Zenghua et al. "Progress in terahertz nondestructive testing of thermal barrier coatings: a review" . | NONDESTRUCTIVE TESTING AND EVALUATION (2025) . |
| APA | Liu, Zenghua , Li, Rui , Wu, Yuheng , Ye, Dongdong , He, Cunfu . Progress in terahertz nondestructive testing of thermal barrier coatings: a review . | NONDESTRUCTIVE TESTING AND EVALUATION , 2025 . |
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Abstract ：
Carbon steel and low alloy steel are pearlitic heat-resistant steels with a lamellar microstructure. There are good mechanical properties and are widely used in crucial components of high-temperature pressure. However, longterm service in high-temperature environments can easily lead to material degradation, including spheroidization, graphitization, and thermal aging. This study proposes a theoretical model of ultrasonic backscattering with a lamellar structure in pearlite areas. It analyzes the effects of different pearlite area ratios and interlamellar spacing on ultrasonic backscattering signals. A Voronoi diagram is used to constructs a two-dimensional finite element (FE) model of the lamellar structure, and the effects of different pearlite area ratio and interlamellar spacing on the backscattering signals are analyzed to verify the correctness of the theoretical model. By preparing spheroidization samples of various grades, the change values of pearlite area ratio and interlamellar spacing are measured. The backscattering signals of different spheroidization samples are collected through the ultrasonic testing experimental platform, and the root-mean-square (RMS) maximum values of the ultrasonic backscattering are extracted. The observed trend is consistent with the theoretical model, finite element method (FEM), and experimental. Compared with the experimental results, the model results have some errors, but can be used to evaluate the performance degradation of metallic materials with lamellar pearlite structure.
Keyword ：
Lamellar pearlite structure Lamellar pearlite structure Ultrasonic testing Ultrasonic testing Polycrystalline material Polycrystalline material Finite element model Finite element model Ultrasonic backscattering Ultrasonic backscattering
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| GB/T 7714 | Liu, Zenghua , Li, Jinlong , Zheng, Yang et al. Ultrasonic backscattering model of lamellar duplex phase microstructures in polycrystalline materials [J]. | ULTRASONICS , 2025 , 149 . |
| MLA | Liu, Zenghua et al. "Ultrasonic backscattering model of lamellar duplex phase microstructures in polycrystalline materials" . | ULTRASONICS 149 (2025) . |
| APA | Liu, Zenghua , Li, Jinlong , Zheng, Yang , He, Cunfu . Ultrasonic backscattering model of lamellar duplex phase microstructures in polycrystalline materials . | ULTRASONICS , 2025 , 149 . |
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Abstract ：
Ultrasonic testing plays a crucial role in detecting early structural damage and identifying micro-defects, particularly in processes like additive manufacturing and welding. The full matrix capture (FMC) method, leveraging laser ultrasound technology, excels in imaging sub-millimeter micro defects. However, its extensive data acquisition time hinders real-time imaging. To address this, a selection matrix capture approach is adopted to reduce data collection and enhance detection speed. Specifically, a multi-parameter genetic algorithm (MPGA) is proposed to optimize sparse array layouts. This optimization is based on theoretical detection sensitivity means and standard deviations, evaluating array layout quality. The imaging method combined multi-scale principal component analysis with phase weighting techniques. Experiments on sub-millimeter defects, including side drilling holes (SDH), blind holes (BH), and spherical holes (SH), were conducted. Results showed that, compared to random and uniform sparsity, the genetic algorithm optimized sparse array provided superior imaging as sparsity decreased. Effective defect detection was achieved with only 5 %-20 % of full matrix data.
Keyword ：
Array scanning Array scanning Laser ultrasonic Laser ultrasonic Selection matrix capture Selection matrix capture Genetic algorithm Genetic algorithm
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| GB/T 7714 | Chen, Long , Liu, Zenghua , Tang, Zhenhe et al. Optimization of selection matrix capture for micro defects laser ultrasound imaging using multi-parameter genetic algorithm [J]. | NDT & E INTERNATIONAL , 2025 , 152 . |
| MLA | Chen, Long et al. "Optimization of selection matrix capture for micro defects laser ultrasound imaging using multi-parameter genetic algorithm" . | NDT & E INTERNATIONAL 152 (2025) . |
| APA | Chen, Long , Liu, Zenghua , Tang, Zhenhe , Duan, Jian , Zhu, Yanping , Zhang, Zongjian et al. Optimization of selection matrix capture for micro defects laser ultrasound imaging using multi-parameter genetic algorithm . | NDT & E INTERNATIONAL , 2025 , 152 . |
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Abstract ：
As a key load-bearing component of the crane, the health status of the boom directly affects the performance and safety of the crane. Therefore, it is especially important to develop a structural health monitoring (SHM) method for the boom. In this study, a compact array intelligent location algorithm based on combined time-of-flight method (CTFM) is proposed and applied to the defect detection of U-shaped boom. In this algorithm, direct time-of-flight (DTFM) and time-of-flight difference (TFDM) are combined to build a scattering point evaluation model to screen scattering point, and evolutionary strategies and clustering algorithms are used to search and locate scattering points quickly. The algorithm transforms the classical imaging problem into the estimation and search scattering points, and uses individual distribution to identify the defect position. First of all, the numerical simulation proves that the proposed intelligent location algorithm has reliable performance in detecting defects of different shapes and sizes. Compared with the traditional ellipse imaging algorithm, the compact array intelligent location algorithm based on CTFM shows advantages in positioning resolution, positioning accuracy and algorithm execution efficiency. Subsequently, through the analysis of the experimental signals of doublehole defect, it is further verified that the algorithm can not only improve the defect positioning accuracy and algorithm execution efficiency, but also effectively remove the interference of direct waves by adjusting parameters. Finally, the influence of parameter setting on the detection results is studied, and the optimal parameter setting of the algorithm is discussed. This algorithm provides a tool for multi-defect detection of U-shaped boom.
Keyword ：
Imaging algorithm Imaging algorithm Intelligent location algorithm Intelligent location algorithm Structural health monitoring Structural health monitoring U-shaped boom U-shaped boom Ultrasonic guided waves Ultrasonic guided waves
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| GB/T 7714 | Lu, Zhaojing , Yang, Jian , Liu, Zenghua et al. Intelligent location algorithm of U-shaped boom compact array based on evolutionary strategy and clustering algorithm [J]. | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2025 , 230 . |
| MLA | Lu, Zhaojing et al. "Intelligent location algorithm of U-shaped boom compact array based on evolutionary strategy and clustering algorithm" . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING 230 (2025) . |
| APA | Lu, Zhaojing , Yang, Jian , Liu, Zenghua , Liu, Xiaoyu , Chen, Long . Intelligent location algorithm of U-shaped boom compact array based on evolutionary strategy and clustering algorithm . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2025 , 230 . |
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| GB/T 7714 | Liu, Zenghua . Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation [J]. | SENSORS , 2024 , 24 (2) . |
| MLA | Liu, Zenghua . "Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation" . | SENSORS 24 . 2 (2024) . |
| APA | Liu, Zenghua . Smart Sensors for Structural Health Monitoring and Nondestructive Evaluation . | SENSORS , 2024 , 24 (2) . |
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Abstract ：
The magneto acoustic emission (MAE) technique is an emerging non-destructive testing (NDT) method that has shown potential for defect detection in the bulk material, proven vital for the safety and integrity of the material. The MAE technique has shown promising results among modern non-destructive testing techniques for ferromagnetic materials. Although MAE technique is a long-established NDT method, it has the potential for further development. This paper provides an in-depth review of MAE signals ' physical origin and characteristics, compares them with their counterpart, Magneto Barkhausen Noise (MBN), and explores data acquisition methods and applications, including specific case studies in material defect detection. The research gaps in the MAE technique are discussed, and the paper explores potential developments, highlighting future perspectives and possible improvements.
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| GB/T 7714 | Liu, Zenghua , Riaz, Wasil , Shen, Yongna et al. Magneto acoustic emission technique: A review of methodology, applications, and future prospects in non-destructive testing [J]. | NDT & E INTERNATIONAL , 2024 , 146 . |
| MLA | Liu, Zenghua et al. "Magneto acoustic emission technique: A review of methodology, applications, and future prospects in non-destructive testing" . | NDT & E INTERNATIONAL 146 (2024) . |
| APA | Liu, Zenghua , Riaz, Wasil , Shen, Yongna , Wang, Xiaoran , He, Cunfu , Shen, Gongtian . Magneto acoustic emission technique: A review of methodology, applications, and future prospects in non-destructive testing . | NDT & E INTERNATIONAL , 2024 , 146 . |
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Abstract ：
15CrMo steel has good mechanical properties and is widely used in high-temperature pressure components. After long term service, it is easy to cause material spheroidisation. The metallographic and mechanical property tests are used to evaluate the spheroidisation of specimens. Ultrasonic backscattering signal is sensitive to microstructure and contains more microstructure information, which can be used for the evaluation of spheroidisation. However, the ultrasonic backscattering signal is nonlinear, and feature extraction is difficult. In this study, ultrasonic testing is used to scan different spheroidisation specimens, and the ultrasonic backscattering signal is extracted as the input to the deep learning model, which is used to extract features from the backscattering signal. The models are evaluated using classification and regression evaluation metrics. The results show that the proposed CNN-LSTM model has good identification performance for the classification of spheroidisation and the prediction of mechanical properties. The classification accuracy, recall, precision, and F1-score are all 1. Additionally, the maximum predicted RMSE and MAE values are only 2.33 MPa and 1.70 MPa, and the minimum R2 is only 0.97. The worst prediction is the tensile strength, with an average value of 442.2 MPa and a maximum value of 481.1 MPa.
Keyword ：
Ultrasonic testing Ultrasonic testing performance deterioration performance deterioration deep learning deep learning spheroidization spheroidization quantitative evaluation quantitative evaluation
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| GB/T 7714 | Li, Jinlong , Liu, Zenghua , Zheng, Yang et al. Quantitative evaluation of spheroidisation in 15CrMo steel based on deep learning [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 , 40 (5) : 1914-1945 . |
| MLA | Li, Jinlong et al. "Quantitative evaluation of spheroidisation in 15CrMo steel based on deep learning" . | NONDESTRUCTIVE TESTING AND EVALUATION 40 . 5 (2024) : 1914-1945 . |
| APA | Li, Jinlong , Liu, Zenghua , Zheng, Yang , Zhang, Zongjian , He, Cunfu . Quantitative evaluation of spheroidisation in 15CrMo steel based on deep learning . | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 , 40 (5) , 1914-1945 . |
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Abstract ：
This study explores the effect of strain on Magneto Acoustic Emission (MAE) characteristics in Q235 steel plates under various excitation frequencies and voltages. Using Maximal Overlap Discrete Wavelet Transform (MODWT), we processed envelope energy signals derived from MAE signals generated from samples subjected to incremental tensile forces revealing critical variations in features extracted from AC and DC components such as RMS, mean bias and energy distribution. The results demonstrate the significant impact of strain on MAE signal characteristics, particularly under higher excitation frequencies and voltages, which enhances the detection of subtle plastic deformations. Our approach provides a refined methodology for enhancing MAE-based Non-Destructive Testing (NDT) practices, crucial for the reliable assessment of material integrity in engineering applications.
Keyword ：
Magneto acoustic emission Magneto acoustic emission strain strain excitation condition excitation condition maximal overlap discrete wavelet transform maximal overlap discrete wavelet transform wavelet wavelet
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| GB/T 7714 | Liu, Zenghua , Riaz, Wasil , Shen, Yongna et al. Effect of strain and excitation conditions on magneto acoustic emission signals in Q235 steel using maximal overlap discrete wavelet transform [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 . |
| MLA | Liu, Zenghua et al. "Effect of strain and excitation conditions on magneto acoustic emission signals in Q235 steel using maximal overlap discrete wavelet transform" . | NONDESTRUCTIVE TESTING AND EVALUATION (2024) . |
| APA | Liu, Zenghua , Riaz, Wasil , Shen, Yongna , Wang, Xiaoran , He, Cunfu , Shen, Gongtian . Effect of strain and excitation conditions on magneto acoustic emission signals in Q235 steel using maximal overlap discrete wavelet transform . | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 . |
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