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Unsupervised method for detecting surface defects in steel based on joint optimization of pseudo-labeling and clustering 基于伪标记和聚类联合优化的钢材表面缺陷无监督检测方法
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-15 DOI: 10.1088/1361-6501/ad6344
D. Bai, Gongfa Li, Du Jiang, Guozhang Jiang, Zhiqiang Hao, Dalin Zhou, Zhaojie Ju
Advances in the field of measurement science and technology have improved the detection of defects in industrial production. One of the key challenges in steel plate surface defect detection is the need to quickly detect a small number of defects in an overwhelmingly defect-free sample. Unlike supervised learning, which relies heavily on precise sample labeling, unsupervised learning leverages its inherent learning capabilities for detection. This paper introduces an innovative method for smart steel diagnosis, integrating joint optimization of feature extraction and clustering. The proposed approach merges mini-batch K-Means clustering with a feature extraction network to acquire pseudo-label information for current images. It employs a multi-view transformation strategy, enabling classification through the optimized feedback from pseudo-labels. This method allows the network to self-optimize the distinction of image features through backpropagation. The method exhibits a mere 4% classification failure rate for steel surface images. This significant reduction in additional data processing requirements enhances the inspection system's efficiency and accuracy. Furthermore, the versatility of this method extends beyond steel defect diagnosis. It holds potential for application in various engineering domains, particularly in scenarios characterized by data imbalance.
测量科学和技术领域的进步改善了工业生产中的缺陷检测。钢板表面缺陷检测的主要挑战之一是需要在绝大多数无缺陷样本中快速检测出少量缺陷。与主要依赖精确样本标记的监督学习不同,无监督学习利用其固有的学习能力进行检测。本文介绍了一种用于智能钢诊断的创新方法,它整合了特征提取和聚类的联合优化。所提出的方法将小批量 K-Means 聚类与特征提取网络相结合,以获取当前图像的伪标签信息。它采用多视角转换策略,通过伪标签的优化反馈实现分类。这种方法允许网络通过反向传播自我优化图像特征的区分。该方法对钢铁表面图像的分类失败率仅为 4%。这大大减少了额外的数据处理要求,提高了检测系统的效率和准确性。此外,这种方法的多功能性还超出了钢铁缺陷诊断的范围。它有望应用于各种工程领域,尤其是在数据不平衡的情况下。
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引用次数: 0
Improving the ambiguity resolution with the consideration of unmodeled errors in GNSS medium and long baselines 考虑到全球导航卫星系统中长基线的未建模误差,提高模糊性分辨率
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-15 DOI: 10.1088/1361-6501/ad6340
Jiafu Wang, Xianwen Yu
Ambiguity resolution (AR) is fundamental to achieve high-precision solution in GNSS (Global Navigation Satellite System) relative positioning. Extensive research has shown that systematic errors are associated with the performance of AR. However, due to the physical complexity, some systematic errors would inevitably remain in the observation equations even after processed with some popular models and parameterization. In the medium and long baselines, these unmodeled errors are the leading cause of the slow or even incorrect fixation of ambiguity. Therefore, to improve the AR performance in the medium and long baselines, we present a procedure with the careful consideration of unmodeled errors. At first, we develop a method to estimate the unmodeled errors based on the float ambiguity bias. Then, the overall procedure and key steps to fix the float solutions corrected by the unmodeled error estimate is designed. Finally, some real-measured baselines (from 68 km to 120 km) are utilized to validate the proposed procedure. The experimental results are analyzed and discussed from the aspects of AR and positioning, respectively. For the AR performance, the time required for the first fixation have been reduced by about 41.58% to 83.51%, from 12 to 100 min. Besides, 12.72% to 48.59% and 2.96% to 36.28% improvements of the ambiguity-fixed rate and the ambiguity-correct rate can be respectively obtained in the four baselines. As for the positioning performance, the mean values and RMSEs have improved by 0.2 to 4.8 cm (1.63% to 22.43%) and 0.2 to 2.8 cm (1.47% to 10.57%), respectively.
模糊分辨率(AR)是实现全球导航卫星系统(GNSS)相对定位高精度解决方案的基础。大量研究表明,系统误差与模糊解析的性能有关。然而,由于物理的复杂性,即使使用一些常用模型和参数化处理后,观测方程中仍不可避免地存在一些系统误差。在中长期基线中,这些未建模的误差是导致模糊性固定缓慢甚至不正确的主要原因。因此,为了提高中长期基线的 AR 性能,我们提出了一种仔细考虑未建模误差的程序。首先,我们开发了一种基于浮动模糊偏差来估计未建模误差的方法。然后,我们设计了通过未建模误差估算修正浮标解的整体程序和关键步骤。最后,利用一些实际测量的基线(从 68 千米到 120 千米)来验证所提出的程序。实验结果分别从自动增益和定位两个方面进行了分析和讨论。在自动增益性能方面,首次固定所需的时间从 12 分钟到 100 分钟减少了约 41.58% 到 83.51%。此外,四种基线的模糊固定率和模糊正确率也分别提高了 12.72% 到 48.59%,以及 2.96% 到 36.28%。在定位性能方面,平均值和均方根误差分别提高了 0.2 至 4.8 厘米(1.63% 至 22.43%)和 0.2 至 2.8 厘米(1.47% 至 10.57%)。
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引用次数: 0
An Investigation of Shaft Voltage in Synchronous Generators Under SAGE and Variable Load Condition 对 SAGE 和可变负载条件下同步发电机轴电压的研究
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-15 DOI: 10.1088/1361-6501/ad633e
Kai Sun, Yuling He, Xue-wei Wu, Hao-ran Luo, Ling-yu Jiao, David Gerada
Synchronous generators are widely used in power generation systems. Static air-gap eccentricity (SAGE) often occurs in synchronous generators due to the component wear over prolonged operation. This paper presents a comprehensive mathematical model specifically tailored for SAGE fault, incorporating for the influence of stator slotting. The study thoroughly examines the impacts of both eccentricity and varying loads on the shaft voltage using the developed model. Furthermore, a novel method for detecting SAGE is introduced, leveraging the mathematical model of shaft voltage. This detection method proves effective for identifying eccentricity in synchronous generators across different load conditions by reasonably combining shaft voltage and phase current. The mathematical model of shaft voltage and the proposed detection method are validated through three-dimensional finite-element calculations and experimental studies. The work is helpful to manage and predict the shaft voltage. This paper contributes to the prevention of shaft voltage damage and real-time monitoring of the SAGE fault in synchronous generators.
同步发电机广泛应用于发电系统。由于长时间运行会造成部件磨损,同步发电机经常会出现静态气隙偏心(SAGE)现象。本文提出了一个专门针对 SAGE 故障的综合数学模型,其中包含定子开槽的影响。研究利用所开发的模型,深入探讨了偏心和负载变化对轴电压的影响。此外,研究还利用轴电压数学模型引入了一种新的 SAGE 检测方法。事实证明,这种检测方法通过合理结合轴电压和相电流,能有效识别同步发电机在不同负载条件下的偏心。轴电压数学模型和所提出的检测方法通过三维有限元计算和实验研究得到了验证。这项工作有助于管理和预测轴电压。本文对同步发电机轴电压损坏的预防和 SAGE 故障的实时监控做出了贡献。
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引用次数: 0
Three-dimensional surface temperature measurement using lifetime-based phosphor thermometry 利用基于寿命的荧光粉测温法测量三维表面温度
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-15 DOI: 10.1088/1361-6501/ad6346
T. Cai, Ruiyu Fu, Di Luan, Yingzheng Liu, Di Peng
In this study, we propose a three-dimensional (3D) surface temperature measurement method based on the principle of stereoscopic 3D reconstruction and the dependence of phosphorescence lifetime on temperature. A 385-nm UV(Ultraviolet) light was used as the excitation light, and two high-speed cameras were used as the detectors. The phosphor MFG (Mg4FGeO6: Mn4+) was mixed with the binder HPC and sprayed onto the tested 3D surface. The natural texture generated by the surface roughness of the phosphor coating was used as a feature for cross-correlation calculations. The digital image correlation (DIC) algorithm was used to match these feature positions in the phosphorescent images from the two cameras. The effects of the excitation angle and detecting angle were analyzed. The results indicate that the temperature measurement based on phosphorescent lifetime was not affected by the excitation and detecting angle. The method was validated on a turbine blade as an example of a 3D surface to demonstrate the capability. A comparison of the measurement results with the thermocouples proves that the current method can successfully measure the temperature on 3D surfaces with a maximum difference of 1.63°C. The spatial accuracy of the method was obtained by comparing with the measurement results of a 3D scanner, which shows that the maximum absolute error of the 3D reconstruction was 0.350 mm. The current study proposes a promising 3D surface temperature measurement method, which is expected to be widely used in gas turbine blades, Internal Combustion (IC) engine cylinders, complex curved heat exchangers, and other fields due to its non-contact measurement, low susceptibility to infrared radiation interference, high measurement accuracy, and ability to withstand harsh environments.
本研究基于立体三维重建原理和磷光寿命对温度的依赖性,提出了一种三维(3D)表面温度测量方法。激发光为 385 纳米紫外光,探测器为两台高速相机。将荧光粉 MFG(Mg4FGeO6: Mn4+)与粘合剂 HPC 混合后喷涂到测试的三维表面上。荧光粉涂层表面粗糙度产生的自然纹理被用作交叉相关计算的特征。数字图像相关(DIC)算法用于匹配两台相机磷光图像中的这些特征位置。分析了激发角和检测角的影响。结果表明,基于磷光寿命的温度测量不受激发角和检测角的影响。该方法以涡轮叶片为例进行了三维表面验证,以证明其测量能力。与热电偶的测量结果比较证明,目前的方法可以成功测量三维表面的温度,最大差值为 1.63°C。通过与三维扫描仪的测量结果进行比较,获得了该方法的空间精度,结果表明三维重建的最大绝对误差为 0.350 毫米。本研究提出的三维表面温度测量方法具有非接触测量、不易受红外辐射干扰、测量精度高、可承受恶劣环境等优点,有望广泛应用于燃气轮机叶片、内燃机气缸、复杂曲面热交换器等领域。
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引用次数: 0
High-Precision Tropospheric Correction Method for NRTK Regions with Significant Height Differences 针对高度差异显著的 NRTK 区域的高精度对流层校正方法
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-15 DOI: 10.1088/1361-6501/ad6343
xiaoting lei, Xiaolong Xu, Jun Tao, Tianyu Yang, Qile Zhao, Jing Guo
In response to the issue of poor Network Real-Time Kinematic (NRTK) service performance in regions with significant height differences, an Improved Tropospheric Height Correction (ITHC) method is proposed. Precise Point Positioning (PPP) is employed to compute the troposphere delay at base stations. Subsequently, a Tropospheric Vertical Profile Fitting Model (TVPFM) is established for the vertical reduction of the troposphere in regions with significant height differences. In this case, the tropospheric errors introduced by the height differences between the base and rover stations can be calculated. Finally, the tropospheric error can be corrected during the generation of virtual observations, ensuring high-accuracy positioning of NRTK rovers. With the troposphere delay computed based on the PPP approach, datum errors introduced by inaccurate tropospheric correction methods are mitigated. To reduce the dependence of the troposphere delay on height, ECMWF Reanalysis v5 (ERA5) data are employed to fit the TVPFM. Experimental analysis demonstrates that the troposphere exhibits distinct vertical variation characteristics, allowing for its segmentation into three layers. Consequently, a piecewise TVPFM is established. Observations obtained from the Continuously Operating Reference Stations (CORS) network located in Yunnan, China, are utilized for validation. The selected stations exhibit a maximum height difference of approximately 2 km. The experimental results exhibit a notable enhancement in correction accuracy with the ITHC in comparison to conventional correction methodologies. Specifically, the ambiguity fixing rate demonstrates a noteworthy improvement of 13.3%, accompanied by a substantial increase in positioning accuracy by 51.4%.
针对高度差异明显地区的网络实时运动学(NRTK)服务性能不佳的问题,提出了一种改进的对流层高度校正(ITHC)方法。采用精确点定位(PPP)来计算基站的对流层延迟。随后,建立了对流层垂直剖面拟合模型(TVPFM),用于在高度差异显著的区域对流层进行垂直缩减。在这种情况下,可以计算出基站和漫游站之间的高度差带来的对流层误差。最后,对流层误差可在生成虚拟观测数据时进行修正,从而确保 NRTK 漫游车的高精度定位。通过基于 PPP 方法计算的对流层延迟,可以减少不准确的对流层校正方法带来的基准误差。为了减少对流层延迟对高度的依赖,采用了 ECMWF Reanalysis v5 (ERA5) 数据来拟合 TVPFM。实验分析表明,对流层具有明显的垂直变化特征,可将其划分为三个层次。因此,建立了片状 TVPFM。从位于中国云南的连续运行参考站(CORS)网络获得的观测数据被用于验证。所选站点的最大高度差约为 2 公里。与传统的校正方法相比,实验结果表明 ITHC 显著提高了校正精度。具体来说,模糊修正率显著提高了 13.3%,定位精度也大幅提高了 51.4%。
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引用次数: 0
Equivalent circuit fitting method for microwave characterisation of low-k dielectric thin films 用于低介电薄膜微波特性分析的等效电路拟合方法
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-15 DOI: 10.1088/1361-6501/ad6342
Anaïs Guerenneur, Dmitry Kouznetsov, Daniele Narducci, Federica Luciano, Xiao Sun, Pol Van Dorpe, F. Ciubotaru, Christoph Adelmann
An equivalent fitting analysis scheme is proposed for extending a method developed for high-k dielectrics to correctly characterise low-k dielectrics, which are more sensitive to various parasitics. The same concentric capacitor devices and measurement setup are used as in the original method, as they are easy to fabricate, which made the old approach attractive in the first place. The physical model used in the analysis step of the original method, which overestimates the dielectric permittivity, is improved by implementing fringing fields and a parasitic gap capacitance as a circuit element. The new approach is verified on experimental data and is demonstrated to more accurately determine the dielectric permittivity compared to the original method.
本文提出了一种等效拟合分析方案,将针对高 k 电介质开发的方法扩展到正确描述低 k 电介质的特性,因为低 k 电介质对各种寄生现象更为敏感。使用的同心电容器器件和测量设置与原始方法相同,因为它们易于制造,这也是旧方法的吸引力所在。原始方法的分析步骤中使用的物理模型高估了介电常数,而新方法则通过将频闪场和寄生间隙电容作为电路元素加以改进。新方法在实验数据上进行了验证,证明与原始方法相比,新方法能更准确地确定介电常数。
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引用次数: 0
A high-speed YOLO detection model for steel surface defects with the channel residual convolution and fusion-distribution 利用通道残余卷积和融合分布建立的钢表面缺陷高速 YOLO 检测模型
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-12 DOI: 10.1088/1361-6501/ad6281
建行 Huang 黄, Xinliang Zhang, Lijie Jia, Yitian Zhou
Accurately and efficiently detecting steel surface defects is a critical step in steel manufacturing. However, the compromise between the detection speed and accuracy remains a major challenge, especially for steel surface defects with large variations in the scale. To address the issue, an improved YOLO based detection model is proposed through the reinforcement of its backbone and neck. Firstly, for the reduction of the redundant parameters and also the improvement of the characterization ability of the model, an effective channel residual structure is adopted to construct a channel residual convolution module (CRCM) and channel residual cross stage partial (CRCSP) module as components of the backbone network, respectively. They realize the extraction of both the shallow feature and multi-scale feature simultaneously under a small number of convolutional parameters. Secondly, in the neck of YOLO, a fusion-distribution (FD) strategy is employed, which extracts and fuses multi-scale feature maps from the backbone network to provide global information, and then distributes global information into local features of different branches through an inject attention mechanism, thus enhancing the feature gap between different branches. Then, a model called CRFD-YOLO is derived for the steel surface defect detection and localization for the situations where both speed and accuracy are demanding. Finally, extensive experimental validations are conducted to evaluate the performance of CRFD-YOLO. The validation results indicate that CRFD-YOLO achieves a satisfactory detection performance with a mean average precision of 81.3% on the NEU-DET and 71.1% on the GC10-DET. Additionally, CRFD-YOLO achieves a speed of 161 frames per second, giving a great potential in real-time detection and localization tasks.
准确高效地检测钢材表面缺陷是钢材生产的关键步骤。然而,检测速度与精度之间的折衷仍然是一个重大挑战,尤其是对于尺度变化较大的钢材表面缺陷。为解决这一问题,本文提出了一种基于 YOLO 的改进型检测模型,并对其主干和颈部进行了强化。首先,为了减少冗余参数,提高模型的表征能力,采用了有效的通道残差结构,分别构建了通道残差卷积模块(CRCM)和通道残差交叉阶段局部模块(CRCSP)作为骨干网络的组成部分。它们实现了在少量卷积参数下同时提取浅层特征和多尺度特征。其次,在 "YOLO "颈中采用了融合分布(FD)策略,从骨干网络中提取并融合多尺度特征图,提供全局信息,然后通过注入注意机制将全局信息分布到不同分支的局部特征中,从而增强不同分支之间的特征差距。然后,针对速度和精度要求都很高的情况,推导出一种名为 CRFD-YOLO 的模型,用于钢材表面缺陷的检测和定位。最后,对 CRFD-YOLO 的性能进行了广泛的实验验证。验证结果表明,CRFD-YOLO 的检测性能令人满意,在 NEU-DET 上的平均精度为 81.3%,在 GC10-DET 上的平均精度为 71.1%。此外,CRFD-YOLO 的速度达到每秒 161 帧,在实时检测和定位任务中具有巨大潜力。
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引用次数: 0
Harmonic Voltage Measurement Based on Capacitive Equipment Dielectric Equivalent Model and Responding Current 基于电容设备介电等效模型和响应电流的谐波电压测量技术
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-12 DOI: 10.1088/1361-6501/ad627f
Lin Du, Feng Hui Feng, Xin Li, Xianjun Shao, Zhi Yang
With the increasing proportion of new energy and the power electronic equipment in the power grid, accurate measurement of harmonic voltage has become increasingly important for power quality monitoring. In order to solve the problem of high-precision measurement of harmonic voltage in the power grid, this manuscript proposes a high-precision harmonic voltage measurement method based on the dielectric equivalent model (DEM) of capacitive equipment and its responding current. Based on DEM, a voltage-current transfer function of the capacitive device is established, and harmonic voltage is reconstructed with the responding current. Considering the dielectric relaxation characteristics of capacitive device other than a pure capacitor model, this manuscript analyzes the fitting performance of different equivalent capacitance models and improves the traditional pure capacitance model to a more suitable DEM for harmonic voltage reconstruction. The DEM parameters of capacitive devices are obtained through the frequency domain spectroscopy (FDS) and intelligent parameter identification algorithms, which improved the measurement accuracy of harmonic voltage and reduced computational complexity. The harmonic voltage testing platform is established to test the simulated high-voltage harmonics and the harmonic voltage of the actual grid voltage. The results show that the proposed harmonic voltage measurement method can meet the high-precision reconstruction of harmonic voltage in the frequency range of 50~2500Hz, and the system testing error with sensors is less than 2%. The testing accuracy is higher than traditional voltage transformers and testing systems based on pure capacitance models.
随着新能源和电力电子设备在电网中所占比例的不断增加,谐波电压的精确测量对于电能质量监测变得越来越重要。为了解决电网中谐波电压的高精度测量问题,本手稿提出了一种基于电容式设备的介质等效模型(DEM)及其响应电流的高精度谐波电压测量方法。基于 DEM,建立了电容式设备的电压-电流传递函数,并利用响应电流重建谐波电压。考虑到纯电容器模型以外的电容设备介电弛豫特性,本稿件分析了不同等效电容模型的拟合性能,并将传统的纯电容模型改进为更适合谐波电压重建的 DEM。通过频域光谱(FDS)和智能参数识别算法获得电容器件的 DEM 参数,提高了谐波电压的测量精度,降低了计算复杂度。建立谐波电压测试平台,测试模拟高压谐波和实际电网电压的谐波电压。结果表明,所提出的谐波电压测量方法可满足 50~2500Hz 频率范围内谐波电压的高精度重建,且系统测试与传感器的误差小于 2%。测试精度高于传统的电压互感器和基于纯电容模型的测试系统。
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引用次数: 0
Three-dimensional contour detection method based on fusion of machine vision and laser radar 基于机器视觉和激光雷达融合的三维轮廓检测方法
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-12 DOI: 10.1088/1361-6501/ad6282
Jun Wu, Shuo Huang, Shaobo Yuan, Long Jin, Runxia Guo, Jiusheng Chen
In the current methods of point cloud processing, there are still several limitations, particularly in achieving high precision and accuracy for large objects in complex environments. Existing techniques often struggle with incomplete or noisy data, leading to inaccurate contour extraction. In view of the challenges associated with the sparse and discrete nature of point clouds in complex environments, which lead to poor accuracy and stability in object contour extraction, this paper proposes a novel method for accurately extracting the contours of three-dimensional target point clouds. The method integrates high-resolution images with sparse point cloud information to address these issues. Firstly, the local characteristics of the point cloud are calculated, allowing for the selection of a contour point cloud. Next, depth information from two-dimensional images is obtained through a fuzzy mapping relationship. Finally, constraint conditions are established to derive a more accurate predicted value of the contour point cloud. Experiments demonstrate that the proposed method effectively improves the precision and accuracy of contour extraction for large objects, reducing measurement deviation by approximately 64.9% compared to using the original point cloud alone. Additionally, the method shows a more accurate completion effect on parts of the contour that are missing, underscoring its robustness and effectiveness in challenging scenarios.
在目前的点云处理方法中,仍存在一些局限性,尤其是在复杂环境中对大型物体实现高精度和高准确度方面。现有技术往往难以处理不完整或有噪声的数据,导致轮廓提取不准确。鉴于复杂环境中点云的稀疏性和离散性导致物体轮廓提取的精度和稳定性较差,本文提出了一种精确提取三维目标点云轮廓的新方法。该方法整合了高分辨率图像和稀疏点云信息,以解决这些问题。首先,计算点云的局部特征,从而选择轮廓点云。接着,通过模糊映射关系从二维图像中获取深度信息。最后,建立约束条件,得出更精确的轮廓点云预测值。实验证明,所提出的方法有效提高了大型物体轮廓提取的精度和准确性,与单独使用原始点云相比,测量偏差减少了约 64.9%。此外,该方法对等高线缺失部分的补全效果更为准确,从而突出了其在具有挑战性的场景中的鲁棒性和有效性。
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引用次数: 0
A novel simulation-assisted transfer method for bearing unknown fault diagnosis 轴承未知故障诊断的新型仿真辅助转移法
IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Pub Date : 2024-07-12 DOI: 10.1088/1361-6501/ad6280
Fengfei Huang, Xianxin Li, Kai Zhang, Qing Zheng, Jiahao Ma, Guofu Ding
Supervised data-driven bearing fault diagnosis methods rely on completed datasets of faults, which can be challenging for signals collected in real engineering. Recognizing unknown faults using a data-driven approach is particularly difficult, as purposefully modeling these faults is complex. To address this challenge, this study proposes a new simulation-assisted transfer bearing unknown fault diagnosis method for realizing unknown compound fault diagnosis of rotating machinery. Firstly, finite element method is used to obtain the compound fault data that does not exist in the historical data, and wavelet packet transform is performed on the simulated and measured signals to enhance the detailed features of the signals. Then, a deep convolutional feature fusion network based on hybrid multi-wavelet spatial attention is constructed to fuse the time-frequency information processed by different wavelet bases. Finally, by integrating the concepts of intra-class splitting and transfer learning, the model is fine-tuned using simulation data to recognize unknown compound faults of rolling bearings. The method validates the simulated signals’ feasibility and the unknown faults’ diagnostic validity under the publicly available rolling bearings dataset. Compared to the comparison methods, the method’s accuracy increased by 2.86%, 2.61%, 5.41%, 4.77%, and 7.07%, respectively.
有监督的数据驱动轴承故障诊断方法依赖于完整的故障数据集,而这对于在实际工程中收集的信号来说具有挑战性。使用数据驱动方法识别未知故障尤其困难,因为对这些故障进行有目的的建模非常复杂。为应对这一挑战,本研究提出了一种新的仿真辅助传递轴承未知故障诊断方法,以实现旋转机械的未知复合故障诊断。首先,利用有限元法获取历史数据中不存在的复合故障数据,并对模拟信号和测量信号进行小波包变换,以增强信号的细节特征。然后,构建基于混合多小波空间注意的深度卷积特征融合网络,以融合不同小波基处理的时频信息。最后,结合类内分割和迁移学习的概念,利用模拟数据对模型进行微调,以识别滚动轴承的未知复合故障。该方法在公开的滚动轴承数据集下验证了模拟信号的可行性和未知故障诊断的有效性。与对比方法相比,该方法的准确率分别提高了 2.86%、2.61%、5.41%、4.77% 和 7.07%。
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引用次数: 0
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