Pub Date : 2024-02-01DOI: 10.1784/insi.2024.66.2.82
Xianguo Li, Dongdong Wu, Yi Liu, Ying Chen
Existing idler fault diagnosis methods have problems in failing to fully obtain global context information and providing poor diagnostic accuracy. To address these problems, this paper investigates a new method for diagnosing faults in belt conveyor idlers, based on analysis of their acoustic signals. The method is also applied to existing databases of bearing fault data. Firstly, an eight-element microphone array sound signal collector is designed to suppress environmental noise and raise the signal-to-noise ratio of the idler sound signal. Secondly, a multi-scale feature fusion (MSFF) module is constructed to learn complementary information between features at different scales. Then, a residual mask convolutional attention (MCA) module is designed to raise the modelling capability of local features and global contextual information. Finally, the structure of the ResNet-18 network is optimised to improve model fitting performance. Experimental results on self-made and public datasets show that the suggested method outperforms other comparative methods, achieving real-time accurate detection and classification of belt conveyor idler faults and typical bearing faults.
{"title":"Belt conveyor idler fault diagnosis method based on multi-scale feature fusion and residual mask convolution attention","authors":"Xianguo Li, Dongdong Wu, Yi Liu, Ying Chen","doi":"10.1784/insi.2024.66.2.82","DOIUrl":"https://doi.org/10.1784/insi.2024.66.2.82","url":null,"abstract":"Existing idler fault diagnosis methods have problems in failing to fully obtain global context information and providing poor diagnostic accuracy. To address these problems, this paper investigates a new method for diagnosing faults in belt conveyor idlers, based on analysis of their\u0000 acoustic signals. The method is also applied to existing databases of bearing fault data. Firstly, an eight-element microphone array sound signal collector is designed to suppress environmental noise and raise the signal-to-noise ratio of the idler sound signal. Secondly, a multi-scale feature\u0000 fusion (MSFF) module is constructed to learn complementary information between features at different scales. Then, a residual mask convolutional attention (MCA) module is designed to raise the modelling capability of local features and global contextual information. Finally, the structure\u0000 of the ResNet-18 network is optimised to improve model fitting performance. Experimental results on self-made and public datasets show that the suggested method outperforms other comparative methods, achieving real-time accurate detection and classification of belt conveyor idler faults and\u0000 typical bearing faults.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139892897","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}
Pub Date : 2024-02-01DOI: 10.1784/insi.2024.66.2.94
Yuanling Chen, Hao Shi, Yaguang Jin, Yuan Liu
Bearing fault diagnosis plays an important part in preventing rotating equipment faults, especially in the field of ultra-low-speed bearing fault diagnosis. Due to their low fault frequency and insignificant fault characteristics, it is difficult to realise the fault diagnosis of ultra-low-speed bearings using traditional methods; therefore, based on acoustic emission (AE) signals, this study proposes an ultra-low-speed bearing recognition model with EfficientNet as the backbone feature extraction network and successfully achieves bearing fault diagnosis under small-sample variable working conditions combined with transfer learning. The coordinate attention (CA) mechanism is introduced into the EfficientNet backbone feature extraction network to improve the ability of the model to extract detailed position information. The AdamW optimisation algorithm is introduced to improve the generalisation ability of the model. Combined with the idea of transfer learning, the data under different working conditions are trained and tested to form a high-performance and lightweight small-sample variable condition bearing recognition model called EfficientNet-CA-AdamW (EfficientNet-CAA). Comparison experiments show that the EfficientNet-CAA model proposed in this study has an accuracy of 99.81% for ultra-low-speed bearing recognition when the training samples are sufficient. Furthermore, the recognition accuracy is smoother and the loss function is significantly lower compared with convolutional neural network (CNN) models such as AlexNet, VGG-16, ResNet-34, ShuffleNet-V2 and EfficientNet-B0. In small-sample variable condition fault recognition, it has more powerful advantages compared with the other models. The recognition accuracy under variable conditions can reach more than 98%, which is significantly higher than that of the other models, and effectively improves the bearing fault recognition accuracy under small-sample variable conditions. In this study, the CA mechanism and the AdamW optimisation algorithm are introduced to lessen the difficulty of extracting detailed features and address the lack of generalisation ability of the EfficientNet model, which provides an idea for the application of the deep learning model to small-sample bearing fault diagnosis under variable working conditions.
{"title":"Study on fault diagnosis of ultra-low-speed bearings under variable working conditions based on improved EfficientNet network","authors":"Yuanling Chen, Hao Shi, Yaguang Jin, Yuan Liu","doi":"10.1784/insi.2024.66.2.94","DOIUrl":"https://doi.org/10.1784/insi.2024.66.2.94","url":null,"abstract":"Bearing fault diagnosis plays an important part in preventing rotating equipment faults, especially in the field of ultra-low-speed bearing fault diagnosis. Due to their low fault frequency and insignificant fault characteristics, it is difficult to realise the fault diagnosis of ultra-low-speed\u0000 bearings using traditional methods; therefore, based on acoustic emission (AE) signals, this study proposes an ultra-low-speed bearing recognition model with EfficientNet as the backbone feature extraction network and successfully achieves bearing fault diagnosis under small-sample variable\u0000 working conditions combined with transfer learning. The coordinate attention (CA) mechanism is introduced into the EfficientNet backbone feature extraction network to improve the ability of the model to extract detailed position information. The AdamW optimisation algorithm is introduced to\u0000 improve the generalisation ability of the model. Combined with the idea of transfer learning, the data under different working conditions are trained and tested to form a high-performance and lightweight small-sample variable condition bearing recognition model called EfficientNet-CA-AdamW\u0000 (EfficientNet-CAA). Comparison experiments show that the EfficientNet-CAA model proposed in this study has an accuracy of 99.81% for ultra-low-speed bearing recognition when the training samples are sufficient. Furthermore, the recognition accuracy is smoother and the loss function is significantly\u0000 lower compared with convolutional neural network (CNN) models such as AlexNet, VGG-16, ResNet-34, ShuffleNet-V2 and EfficientNet-B0. In small-sample variable condition fault recognition, it has more powerful advantages compared with the other models. The recognition accuracy under variable\u0000 conditions can reach more than 98%, which is significantly higher than that of the other models, and effectively improves the bearing fault recognition accuracy under small-sample variable conditions. In this study, the CA mechanism and the AdamW optimisation algorithm are introduced to lessen\u0000 the difficulty of extracting detailed features and address the lack of generalisation ability of the EfficientNet model, which provides an idea for the application of the deep learning model to small-sample bearing fault diagnosis under variable working conditions.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139882835","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}
Pub Date : 2024-02-01DOI: 10.1784/insi.2024.66.2.109
Pu Huang, Xiaofei Huang, Gao Peng, Shuliang Wang, Yuedong Xie
Metallic samples are widely applied in modern industrial production. Due to non-uniformities in the stress load, such samples may become damaged and produce defects, which can cause unnecessary economic losses. In this paper, an online defect detection method is proposed for the quality monitoring of metallic plates. The research involves the design and optimisation of an electromagnetic tomography (EMT) sensor and the development of a fast tomography algorithm. Specifically, a planar array eddy current sensor is designed for in-situ structural health monitoring of metallic specimens. The parameters of the sensor are optimised using an orthogonal methodology and a response surface methodology to improve the uniformity of the sensitivity field. In addition, a second-order iterative Bregman reconstruction algorithm is investigated to reconstruct the defect image, which can improve the reconstruction speed for this ill-posed problem. Simulation and experimental results indicate that the proposed method can be applied to effectively evaluate the locations and sizes of defects in metallic specimens. The correlation coefficients of the reconstructed images using the proposed method are larger than 0.8. Compared with traditional reconstruction algorithms, the method proposed in this paper shows fast convergence speed and smaller estimation errors.
{"title":"Online defect detection on metallic plates using electromagnetic tomography","authors":"Pu Huang, Xiaofei Huang, Gao Peng, Shuliang Wang, Yuedong Xie","doi":"10.1784/insi.2024.66.2.109","DOIUrl":"https://doi.org/10.1784/insi.2024.66.2.109","url":null,"abstract":"Metallic samples are widely applied in modern industrial production. Due to non-uniformities in the stress load, such samples may become damaged and produce defects, which can cause unnecessary economic losses. In this paper, an online defect detection method is proposed for the quality\u0000 monitoring of metallic plates. The research involves the design and optimisation of an electromagnetic tomography (EMT) sensor and the development of a fast tomography algorithm. Specifically, a planar array eddy current sensor is designed for in-situ structural health monitoring of metallic\u0000 specimens. The parameters of the sensor are optimised using an orthogonal methodology and a response surface methodology to improve the uniformity of the sensitivity field. In addition, a second-order iterative Bregman reconstruction algorithm is investigated to reconstruct the defect image,\u0000 which can improve the reconstruction speed for this ill-posed problem. Simulation and experimental results indicate that the proposed method can be applied to effectively evaluate the locations and sizes of defects in metallic specimens. The correlation coefficients of the reconstructed images\u0000 using the proposed method are larger than 0.8. Compared with traditional reconstruction algorithms, the method proposed in this paper shows fast convergence speed and smaller estimation errors.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"16 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139891904","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}
Pub Date : 2024-02-01DOI: 10.1784/insi.2024.66.2.109
Pu Huang, Xiaofei Huang, Gao Peng, Shuliang Wang, Yuedong Xie
Metallic samples are widely applied in modern industrial production. Due to non-uniformities in the stress load, such samples may become damaged and produce defects, which can cause unnecessary economic losses. In this paper, an online defect detection method is proposed for the quality monitoring of metallic plates. The research involves the design and optimisation of an electromagnetic tomography (EMT) sensor and the development of a fast tomography algorithm. Specifically, a planar array eddy current sensor is designed for in-situ structural health monitoring of metallic specimens. The parameters of the sensor are optimised using an orthogonal methodology and a response surface methodology to improve the uniformity of the sensitivity field. In addition, a second-order iterative Bregman reconstruction algorithm is investigated to reconstruct the defect image, which can improve the reconstruction speed for this ill-posed problem. Simulation and experimental results indicate that the proposed method can be applied to effectively evaluate the locations and sizes of defects in metallic specimens. The correlation coefficients of the reconstructed images using the proposed method are larger than 0.8. Compared with traditional reconstruction algorithms, the method proposed in this paper shows fast convergence speed and smaller estimation errors.
{"title":"Online defect detection on metallic plates using electromagnetic tomography","authors":"Pu Huang, Xiaofei Huang, Gao Peng, Shuliang Wang, Yuedong Xie","doi":"10.1784/insi.2024.66.2.109","DOIUrl":"https://doi.org/10.1784/insi.2024.66.2.109","url":null,"abstract":"Metallic samples are widely applied in modern industrial production. Due to non-uniformities in the stress load, such samples may become damaged and produce defects, which can cause unnecessary economic losses. In this paper, an online defect detection method is proposed for the quality\u0000 monitoring of metallic plates. The research involves the design and optimisation of an electromagnetic tomography (EMT) sensor and the development of a fast tomography algorithm. Specifically, a planar array eddy current sensor is designed for in-situ structural health monitoring of metallic\u0000 specimens. The parameters of the sensor are optimised using an orthogonal methodology and a response surface methodology to improve the uniformity of the sensitivity field. In addition, a second-order iterative Bregman reconstruction algorithm is investigated to reconstruct the defect image,\u0000 which can improve the reconstruction speed for this ill-posed problem. Simulation and experimental results indicate that the proposed method can be applied to effectively evaluate the locations and sizes of defects in metallic specimens. The correlation coefficients of the reconstructed images\u0000 using the proposed method are larger than 0.8. Compared with traditional reconstruction algorithms, the method proposed in this paper shows fast convergence speed and smaller estimation errors.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"202 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139831995","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}
Pub Date : 2024-02-01DOI: 10.1784/insi.2024.66.2.103
Beomjin Kim, Younho Cho, Jeongnam Kim, Jiannan Zhang, Kyoung-Sik Jeong, Yunhyeon Baek
The integrity of heat exchanger (HE) tubes is essential for power plant safety and efficiency. Numerous tube assessment techniques have been proposed, including eddy current inspection and the guided wave method. However, they mainly evaluate from the inside of the tubes. Hence, when the interior region of a tube wall is not accessible, inspection is difficult. To overcome this issue, a new guided wave device is fabricated that inspects from the exterior of the heat exchanger tubes. Using this device, a few sample heat exchanger tubes are selected and inspected in a field evaluation during an overhaul period. Furthermore, the feasibility of the device is evaluated. This new approach is expected to contribute to the efficient evaluation of heat exchanger tubes.
{"title":"Preliminary assessment of the feasibility of field evaluation of heat exchanger tube structure using ultrasonic guided wave with exterior approach","authors":"Beomjin Kim, Younho Cho, Jeongnam Kim, Jiannan Zhang, Kyoung-Sik Jeong, Yunhyeon Baek","doi":"10.1784/insi.2024.66.2.103","DOIUrl":"https://doi.org/10.1784/insi.2024.66.2.103","url":null,"abstract":"The integrity of heat exchanger (HE) tubes is essential for power plant safety and efficiency. Numerous tube assessment techniques have been proposed, including eddy current inspection and the guided wave method. However, they mainly evaluate from the inside of the tubes. Hence, when\u0000 the interior region of a tube wall is not accessible, inspection is difficult. To overcome this issue, a new guided wave device is fabricated that inspects from the exterior of the heat exchanger tubes. Using this device, a few sample heat exchanger tubes are selected and inspected in a field\u0000 evaluation during an overhaul period. Furthermore, the feasibility of the device is evaluated. This new approach is expected to contribute to the efficient evaluation of heat exchanger tubes.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"28 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139871987","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}
Pub Date : 2024-01-01DOI: 10.1784/insi.2024.66.1.25
Xiaoxiao Li, Kexi Liao, Guoxi He, Jianhua Zhao
In this paper, a theoretical model of a magnetoelastic coupling magnetic dipole is established to analyse the influence of stress on the magnetic signal in magnetic memory testing. Based on the theory of ferromagnetism, the equivalent field strength under the combined action of stress and the magnetic field is determined and a numerical solution for the stress magnetisation of isotropic ferromagnetic materials under a weak environmental magnetic field is obtained. Based on the assumption of a double rectangular crack in a three-dimensional problem for the magnetic signal, a theoretical analysis model of a magnetoelastic coupling-type magnetic dipole is established. Based on the theory of the magnetoelastic coupling magnetic dipole, the influence factors and rules of the magnetic signal are analysed in detail. The theoretical research shows that the solution based on the theoretical model in this paper can explain some basic experimental phenomena and laws in magnetic memory inspection. The magnetic signal of a defect-free plate shows a 'horseshoe shape'. The length, width and height of the plate will affect Hx but have no effect on Hy . In addition, the lift-off value has a great influence on the magnetic signal of the plate. When the two cracks are a small distance apart, the magnetic signal of the plate is the superposition of the magnetic signals of the two cracks. For plates with cracks, the crack size, spacing, external magnetic field strength and stress will affect the magnetic signal of the plate.
本文建立了磁弹性耦合磁偶极子的理论模型，以分析磁记忆测试中应力对磁信号的影响。基于铁磁理论，确定了应力和磁场共同作用下的等效场强，并得到了各向同性铁磁材料在弱环境磁场下应力磁化的数值解。基于磁信号三维问题中双矩形裂缝的假设，建立了磁弹性耦合型磁偶极子的理论分析模型。基于磁弹性耦合磁偶极理论，详细分析了磁信号的影响因素和规律。理论研究表明，基于本文理论模型的解可以解释磁记忆检测中的一些基本实验现象和规律。无缺陷平板的磁信号呈现 "马蹄形"。磁板的长度、宽度和高度会影响 Hx，但对 Hy 没有影响。此外，升程值对磁记忆板的磁信号也有很大影响。当两条裂缝相距很小时，板的磁信号是两条裂缝磁信号的叠加。对于有裂缝的板，裂缝大小、间距、外部磁场强度和应力都会影响板的磁信号。
{"title":"Research on magnetoelastic coupling model based on magnetic dipole theory","authors":"Xiaoxiao Li, Kexi Liao, Guoxi He, Jianhua Zhao","doi":"10.1784/insi.2024.66.1.25","DOIUrl":"https://doi.org/10.1784/insi.2024.66.1.25","url":null,"abstract":"In this paper, a theoretical model of a magnetoelastic coupling magnetic dipole is established to analyse the influence of stress on the magnetic signal in magnetic memory testing. Based on the theory of ferromagnetism, the equivalent field strength under the combined action of stress\u0000 and the magnetic field is determined and a numerical solution for the stress magnetisation of isotropic ferromagnetic materials under a weak environmental magnetic field is obtained. Based on the assumption of a double rectangular crack in a three-dimensional problem for the magnetic signal,\u0000 a theoretical analysis model of a magnetoelastic coupling-type magnetic dipole is established. Based on the theory of the magnetoelastic coupling magnetic dipole, the influence factors and rules of the magnetic signal are analysed in detail. The theoretical research shows that the solution\u0000 based on the theoretical model in this paper can explain some basic experimental phenomena and laws in magnetic memory inspection. The magnetic signal of a defect-free plate shows a 'horseshoe shape'. The length, width and height of the plate will affect Hx but have no effect on\u0000 Hy . In addition, the lift-off value has a great influence on the magnetic signal of the plate. When the two cracks are a small distance apart, the magnetic signal of the plate is the superposition of the magnetic signals of the two cracks. For plates with cracks, the crack size,\u0000 spacing, external magnetic field strength and stress will affect the magnetic signal of the plate.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"355 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139632277","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}
Pub Date : 2024-01-01DOI: 10.1784/insi.2024.66.1.12
O. Trushkevych, S. Dixon
Magnetically soft and malleable magnetostrictive (MS) alloys are highly promising as low-cost solutions for high-efficiency generation of guided waves in industrial applications and a variety of magnetostrictive patch transducers (MPTs) have been described in the literature. This work focuses on understanding the mechanisms and behaviour of soft MPTs used in the Wiedemann effect geometry, generating shear horizontal (SH) guided waves using FeCo alloy patches. MPT operation is explored in relation to patch geometry, size, magnetic field directions and guided wave wavelength. MPTs are compared with electromagnetic acoustic transducers (EMATs) and EMATs are also placed on MS and copper foil patches bonded to large glass plates for some of the measurements. Periodic permanent magnet (PPM) array EMATs operating on MPTs bonded to ferritic steel samples produced significant enhancements in the generated wave amplitude and the detected signal amplitude when compared to directly generating on the steel substrate, which primarily operates through the Lorentz mechanism. This enhanced performance was investigated and was found to be due to the magnetic fringing fields at the magnet edges. Moreover, EMAT lift-off behaviour was significantly improved when an EMAT was placed above a magnetostrictive patch, with 50 mm lift-off between the EMAT and the patch demonstrated for SH wave generation at a 22 mm nominal wavelength at a 170 kHz excitation frequency on a glass plate sample.
磁性软且可塑性强的磁致伸缩（MS）合金作为工业应用中高效产生导波的低成本解决方案，前景非常广阔，文献中已介绍了多种磁致伸缩贴片传感器（MPT）。这项工作的重点是了解维德曼效应几何中使用的软 MPT 的机制和行为，利用铁钴合金贴片产生剪切水平（SH）导波。研究探讨了 MPT 运行与贴片几何形状、尺寸、磁场方向和导波波长的关系。将 MPT 与电磁声学传感器（EMAT）进行了比较，在某些测量中，还将 EMAT 放置在粘接在大型玻璃板上的 MS 和铜箔贴片上。与直接在主要通过洛伦兹机制运行的钢基板上产生的波幅和检测到的信号幅值相比，在粘接到铁素体钢样品的 MPT 上运行的周期性永磁（PPM）阵列电磁声纳传感器产生的波幅和检测到的信号幅值显著增强。经研究发现，这种性能的增强是由于磁体边缘的磁频闪场造成的。此外，当 EMAT 放置在磁致伸缩贴片上方时，EMAT 的升离性能得到显著改善，在玻璃板样品上以 170 kHz 的激励频率产生 22 mm 标称波长的 SH 波时，EMAT 和贴片之间的升离距离为 50 mm。
{"title":"Soft magnetostrictive patches for guided wave ultrasonics using Wiedemann effect-based MPTs and EMATs","authors":"O. Trushkevych, S. Dixon","doi":"10.1784/insi.2024.66.1.12","DOIUrl":"https://doi.org/10.1784/insi.2024.66.1.12","url":null,"abstract":"Magnetically soft and malleable magnetostrictive (MS) alloys are highly promising as low-cost solutions for high-efficiency generation of guided waves in industrial applications and a variety of magnetostrictive patch transducers (MPTs) have been described in the literature. This work\u0000 focuses on understanding the mechanisms and behaviour of soft MPTs used in the Wiedemann effect geometry, generating shear horizontal (SH) guided waves using FeCo alloy patches. MPT operation is explored in relation to patch geometry, size, magnetic field directions and guided wave wavelength.\u0000 MPTs are compared with electromagnetic acoustic transducers (EMATs) and EMATs are also placed on MS and copper foil patches bonded to large glass plates for some of the measurements. Periodic permanent magnet (PPM) array EMATs operating on MPTs bonded to ferritic steel samples produced significant\u0000 enhancements in the generated wave amplitude and the detected signal amplitude when compared to directly generating on the steel substrate, which primarily operates through the Lorentz mechanism. This enhanced performance was investigated and was found to be due to the magnetic fringing fields\u0000 at the magnet edges. Moreover, EMAT lift-off behaviour was significantly improved when an EMAT was placed above a magnetostrictive patch, with 50 mm lift-off between the EMAT and the patch demonstrated for SH wave generation at a 22 mm nominal wavelength at a 170 kHz excitation frequency on\u0000 a glass plate sample.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"44 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139633311","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}
Pub Date : 2024-01-01DOI: 10.1784/insi.2024.66.1.41
M. Hu, Guofeng Wang, Zenghuan Cao
This paper addresses the problem of identifying faults in the harmonic reducers of industrial robots by analysing their vibration signals. In order to solve the problem of obtaining fault data and rotation error from harmonic reducers in service, an accuracy performance prediction method based on transfer learning and Gaussian process regression (GPR) is proposed. The Euclidean distance between the spectral sequence of each component is proposed as the fitness index to optimise the transition bandwidth of the filter banks. The optimised empirical wavelet transform (OEWT) is used for signal decomposition to obtain sensitive frequency bands. A feature transfer method based on semi-supervised transfer component analysis (SSTCA) is proposed to achieve target domain feature transfer under missing data conditions. A prediction model based on GPR is established using the mapped features to predict the performance and accuracy of the harmonic reducer. The effectiveness of the proposed method is verified through model evaluation indicators and degradation experiments.
{"title":"Performance prediction of industrial robot harmonic reducer via feature transfer and Gaussian process regression","authors":"M. Hu, Guofeng Wang, Zenghuan Cao","doi":"10.1784/insi.2024.66.1.41","DOIUrl":"https://doi.org/10.1784/insi.2024.66.1.41","url":null,"abstract":"This paper addresses the problem of identifying faults in the harmonic reducers of industrial robots by analysing their vibration signals. In order to solve the problem of obtaining fault data and rotation error from harmonic reducers in service, an accuracy performance prediction method\u0000 based on transfer learning and Gaussian process regression (GPR) is proposed. The Euclidean distance between the spectral sequence of each component is proposed as the fitness index to optimise the transition bandwidth of the filter banks. The optimised empirical wavelet transform (OEWT) is\u0000 used for signal decomposition to obtain sensitive frequency bands. A feature transfer method based on semi-supervised transfer component analysis (SSTCA) is proposed to achieve target domain feature transfer under missing data conditions. A prediction model based on GPR is established using\u0000 the mapped features to predict the performance and accuracy of the harmonic reducer. The effectiveness of the proposed method is verified through model evaluation indicators and degradation experiments.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"6 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140524263","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}
Pub Date : 2024-01-01DOI: 10.1784/insi.2024.66.1.34
Lijun Meng, Zhengang Guo, Chenglong Ma
Current damage localisation methods often require many sensors and complex signal processing methods. This paper proposes a fusion algorithm based on elliptical localisation and the reconstruction algorithm for probabilistic inspection of damage (RAPID) to locate and image multiple damages. Experimental verification of the damage algorithm was conducted. An ultrasonic probe was used to excite Lamb signals on an aluminium alloy plate, the ultrasonic response signals at different positions within the plate under multiple damages were measured and the constructed algorithm was employed to image the damage location. In the experiment, this method improved localisation efficiency by excluding invalid sensing paths in the sensor network, saving 31.32% of computational time. When some sensors in the sensor network were damaged, this algorithm ensured a positioning accuracy with a positioning error of 5.83 mm. Finally, the algorithm was used to locate multiple damages in the sensor network and the results showed the good robustness of the algorithm.
{"title":"Research on multiple damage localisation based on fusion of the Lamb wave ellipse algorithm and RAPID algorithm","authors":"Lijun Meng, Zhengang Guo, Chenglong Ma","doi":"10.1784/insi.2024.66.1.34","DOIUrl":"https://doi.org/10.1784/insi.2024.66.1.34","url":null,"abstract":"Current damage localisation methods often require many sensors and complex signal processing methods. This paper proposes a fusion algorithm based on elliptical localisation and the reconstruction algorithm for probabilistic inspection of damage (RAPID) to locate and image multiple\u0000 damages. Experimental verification of the damage algorithm was conducted. An ultrasonic probe was used to excite Lamb signals on an aluminium alloy plate, the ultrasonic response signals at different positions within the plate under multiple damages were measured and the constructed algorithm\u0000 was employed to image the damage location. In the experiment, this method improved localisation efficiency by excluding invalid sensing paths in the sensor network, saving 31.32% of computational time. When some sensors in the sensor network were damaged, this algorithm ensured a positioning\u0000 accuracy with a positioning error of 5.83 mm. Finally, the algorithm was used to locate multiple damages in the sensor network and the results showed the good robustness of the algorithm.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"17 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139633766","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}
Pub Date : 2024-01-01DOI: 10.1784/insi.2024.66.1.19
R. Wasif, I. Pinson, S. Majidnia
The inspection of welds and components for nuclear applications can be more challenging due to extreme levels of radiation and temperature. A development project in collaboration with the UK Atomic Energy Authority (UKAEA) is being conducted to develop non-destructive testing (NDT) procedures for inspecting the remotely welded joints within the ITER facility. Initially, a feasibility study has been carried out to identify the most suitable non-destructive technique. Eddy current array (ECA), phased array ultrasonics and guided wave electromagnetic acoustic transducers (EMATs) were considered as candidate solutions and, following the feasibility study, ECA was selected to be taken forward for further development. Subsequently, dedicated high- and low-frequency array probes have been developed and tested to detect and size surface and buried defects employing encoder and calibration curves. The research has been extended to characterise defects such as tungsten inclusions using the phase angle. To avoid damage to the electronics in extreme environments, the ECA probe coils were separated from the excitation and data acquisition unit with 60 m coaxial coils to achieve a high signal-to-noise ratio. The results revealed that the ECA technique can successfully be deployed remotely for the detection and sizing of defects down to 3 mm in extreme environments.
{"title":"Eddy current array developments for remote deployment on the ITER project","authors":"R. Wasif, I. Pinson, S. Majidnia","doi":"10.1784/insi.2024.66.1.19","DOIUrl":"https://doi.org/10.1784/insi.2024.66.1.19","url":null,"abstract":"The inspection of welds and components for nuclear applications can be more challenging due to extreme levels of radiation and temperature. A development project in collaboration with the UK Atomic Energy Authority (UKAEA) is being conducted to develop non-destructive testing (NDT)\u0000 procedures for inspecting the remotely welded joints within the ITER facility. Initially, a feasibility study has been carried out to identify the most suitable non-destructive technique. Eddy current array (ECA), phased array ultrasonics and guided wave electromagnetic acoustic transducers\u0000 (EMATs) were considered as candidate solutions and, following the feasibility study, ECA was selected to be taken forward for further development. Subsequently, dedicated high- and low-frequency array probes have been developed and tested to detect and size surface and buried defects employing\u0000 encoder and calibration curves. The research has been extended to characterise defects such as tungsten inclusions using the phase angle. To avoid damage to the electronics in extreme environments, the ECA probe coils were separated from the excitation and data acquisition unit with 60 m coaxial\u0000 coils to achieve a high signal-to-noise ratio. The results revealed that the ECA technique can successfully be deployed remotely for the detection and sizing of defects down to 3 mm in extreme environments.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"100 s4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139638578","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}
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