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Underwater GMR sensor data storage using RFID tags 水下GMR传感器数据存储采用RFID标签
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00036
N. Sathappan, M. Tokhi, Zhanfang Zhao, Fang-wei Duan, G. Shirkoohi, Liam Penaluna
Radio-frequency Identification (RFID) technology is now widely used in many commercial and industrial sectors, from object tracking to personal identification. Few studies have investigated the possibility of using RFID systems for underwater monitoring operations in fluvial environments. While the technical limitations of these circumstances can be surmountable in certain cases, ad hoc studies have shown that RFID technology can work even under water. This paper presents the development of a device to collect and store data from a giant magnetoresistance (GMR) sensor for underwater corrosion monitoring using RFID. The findings show that RFID systems can be used to store data at near ranges of less than 5 mm regardless of frequency. This paper also provides an investigation into RFID, transponders, and reader classification, as well as existing applications underwater and their benefits.
射频识别(RFID)技术现在广泛应用于许多商业和工业部门,从物体跟踪到个人识别。很少有研究调查了在河流环境中使用RFID系统进行水下监测操作的可能性。虽然这些情况的技术限制在某些情况下是可以克服的,但特别研究表明,RFID技术甚至可以在水下工作。本文介绍了一种利用射频识别技术收集和存储巨磁电阻(GMR)传感器的水下腐蚀监测数据的装置。研究结果表明,无论频率如何,RFID系统都可以用于在小于5毫米的近距离内存储数据。本文还对RFID、应答器和读取器的分类以及现有的水下应用及其好处进行了研究。
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引用次数: 1
An Modified Earth Mover’s Distance for Few-Shot Image Classification 一种用于少拍图像分类的改进型推土机距离
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00077
Zhiyu Jin, Zhuohe Tang, Jintao Yan
The problem of few-shot image classification has become a popular research area in the field of imaging. In order to improve the accuracy of few-shot image classification, many learning methods have been proposed, among which there are four main approaches: meta-based learning, data augmentation-based, migration-based learning and metric-based learning. In this paper, we propose a modified earth mover’s distance (MEMD) based on the metric learning approach, which has received much attention due to its simple structure and accurate classification. Similarly, MEMD constructs correlations between image regions, using such correlations to characterise the class of the image. MEMD generates a stream of best matches between image regions, and this stream of matches represents the similarity of the classified images. the MEMD algorithm requires the generation of feature weights for image regions, and EMD uses a mechanism of cross-referenced citations to generate uniform consultation weights. in contrast to EMD, MEMD generates inconsistent reference weights based on the similarity of regions. In dealing with the K-Shot problem, we used a learnable class prototype to characterise the class feature vectors. We conducted comprehensive experiments to validate our improved MEMD algorithm and tested it on four popular few-shot datasets. Namely: miniImageNet, tieredImageNet, Fewshot-CIFAR100 (FC100) and the CUB dataset.
少镜头图像分类问题已成为成像领域的研究热点。为了提高少拍图像分类的准确率,人们提出了许多学习方法,其中主要有四种方法:基于元的学习、基于数据增强的学习、基于迁移的学习和基于度量的学习。本文提出了一种基于度量学习方法的改进型推土机距离(MEMD),该方法因其结构简单、分类准确而受到广泛关注。类似地,MEMD在图像区域之间构建相关性,使用这种相关性来表征图像的类别。MEMD生成图像区域之间的最佳匹配流,该匹配流表示分类图像的相似性。MEMD算法需要生成图像区域的特征权值,而EMD算法使用交叉引用机制生成统一的咨询权值。与EMD相比,MEMD基于区域的相似性产生不一致的参考权重。在处理K-Shot问题时,我们使用可学习的类原型来表征类特征向量。我们进行了全面的实验来验证我们改进的MEMD算法,并在四个流行的少量数据集上进行了测试。即:miniImageNet, tieredImageNet, few - shot- cifar100 (FC100)和CUB数据集。
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引用次数: 0
From the Air to the Ground: An Experimental Approach to Assess LiPo Batteries for a Second Life 从空中到地面:评估锂电池第二寿命的实验方法
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00092
Julio Castro, Carolina Flores, Diego Gonzalez, Vanessa L. Quintero, Aramis Pérez
Many are the applications that use energy stored in lithium-ion (Li-ion) batteries to power themselves. Without a doubt this type of energy storage device has changed the way of living. However, a major concern regarding these Li-ion batteries is associated on the way how they should be treated or disposed when they reach their End of Life (EoL). Although, this rises a major consideration which is that perhaps the battery reached its EoL for its original application, but there are still many other applications where these batteries can be utilized. In this regard, developing a series of simple tests to understand how a degraded Li-ion battery can transfer its stored energy for less demanding applications becomes of utmost importance. This paper illustrates how the original battery pack of a drone can be reutilized for second life applications such as a small power bank. An easy procedure is proposed to assess the capability of a degraded cell to transfer energy for other applications where the Li-ion battery is working under less stress.
许多应用都是利用锂离子(Li-ion)电池中储存的能量来为自己供电。毫无疑问,这种储能装置已经改变了人们的生活方式。然而,关于这些锂离子电池的一个主要问题是,当它们达到使用寿命(EoL)时,应该如何处理或处置它们。虽然,这引起了一个主要的考虑,那就是电池可能达到了其原始应用的EoL,但仍然有许多其他应用可以利用这些电池。在这方面,开发一系列简单的测试来了解退化的锂离子电池如何将其储存的能量转移到要求较低的应用中变得至关重要。本文说明了如何将无人机的原始电池组重新用于小型充电宝等第二生命应用。我们提出了一个简单的方法来评估退化电池转移能量的能力,以用于锂离子电池在较小压力下工作的其他应用。
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引用次数: 1
Pit Detection in Current Monitoring of Control Rod Drive Mechanism Based on Daubechies Wavelet Analysis 基于daubecies小波分析的控制棒驱动机构电流监测中的坑检测
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00103
Dehuai Ou, Guoliang Lu
Control rod drive mechanism is an important part of nuclear reactor. The power regulation of nuclear reactor is accomplished by control rod. The safe and effective operation of the control rod driving mechanism is the premise to ensure the normal operation of the nuclear reactor. This paper first introduce the basic structure and driving principle of the control rod drive mechanism, and explains the cause of trough in the coil current signal during normal operation. Secondly, the acquisition and display of current signals are completed through the hardware acquisition system. Then, the timing sequence of the changes of the current signals of the three coils and the completion of their actions are analyzed. Finally, the intelligent diagnosis of the control rod drive mechanism is realized by detecting the trough in the current signal through the Daubechies Wavelet analysis.
控制棒驱动机构是核反应堆的重要组成部分。核反应堆的功率调节是由控制棒来完成的。控制棒驱动机构的安全有效运行是保证核反应堆正常运行的前提。本文首先介绍了控制棒驱动机构的基本结构和驱动原理,并说明了正常工作时线圈电流信号出现波谷的原因。其次,通过硬件采集系统完成电流信号的采集和显示。然后,分析了三个线圈电流信号变化的时序以及它们动作的完成情况。最后,通过Daubechies小波分析检测电流信号中的波谷,实现对控制棒驱动机构的智能诊断。
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引用次数: 0
A Relation Prediction Method for Industrial Knowledge Graph with Complex Relations 具有复杂关系的工业知识图关系预测方法
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00015
Jie Liu, Lin Lin, Yancheng Lv, Hao Guo, Chang-sheng Tong, Zhiquan Cui
In the industrial knowledge graph, relations between entities has important physical significance. In some cases, the relations determines product quality or fault prediction accuracy. Therefore, relation prediction is particularly important. The existing translation models are poor in relation prediction, because the current method of generating incorrect triples cannot generate incorrect triples with incorrect relations. Therefore, this paper develops an incorrect triple generation method by combining uniform distribution and Bernoulli distribution to improve the relation prediction accuracy. Then UBTransH model is developed by combining TransH with the incorrect triples based on uniform distribution and Bernoulli distribution. In the UBTransH, the relation replacement probability and entity replacement probability of the correct triples are first obtained through uniform distribution, then the head entity replacement probability and tail entity replacement probability are calculated with the entity replacement probability and Bernoulli distribution. Second, the incorrect triples are generated by replacing the relation/head entity/tail entity with the relation/head entity/tail entity replacement probability. Third, the incorrect triples are applied to train TransH. Finally, based on relation prediction, the developed UBTransH are compared with TransH on several typical datasets. Experimental results show that the developed UBTransH significantly improves the relation prediction accuracy.
在工业知识图谱中,实体之间的关系具有重要的物理意义。在某些情况下,这些关系决定了产品质量或故障预测的准确性。因此,关系预测就显得尤为重要。现有的翻译模型在关系预测方面较差,因为现有的生成不正确三元组的方法无法生成具有不正确关系的不正确三元组。因此,本文提出了一种将均匀分布与伯努利分布相结合的不正确三生成方法,以提高关系预测精度。然后将TransH与基于均匀分布和伯努利分布的错误三元组相结合,建立UBTransH模型。在UBTransH中,首先通过均匀分布得到正确三元组的关系替换概率和实体替换概率,然后利用实体替换概率和伯努利分布计算头部实体替换概率和尾部实体替换概率。其次,用关系/头实体/尾实体替换概率替换关系/头实体/尾实体,生成不正确的三元组。第三,使用不正确的三元组来训练TransH。最后,在关系预测的基础上,将开发的UBTransH与几个典型数据集上的TransH进行了比较。实验结果表明,开发的UBTransH显著提高了关系预测精度。
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引用次数: 0
The Survey of Algorithms for Comprehensive Transmission Fault Detection 输电系统综合故障检测算法综述
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00098
Yingshun Li, Wenbo Zhang, Huanhuan Sui, De-biao Wang
As the main component of the armored vehicle transmission system, the performance of the integrated transmission directly affects the overall performance of the vehicle. Due to the complex working conditions of the integrated transmission device, faults are prone to occur, so the fault diagnosis of the integrated transmission device is particularly important. The fault mechanism of the integrated transmission is complex, and it is difficult to directly determine the cause of the failure.Therefore,the algorithms for fault detection of the integrated transmission are constantly being introduced in recent years.This article will summarize these fault detection algorithms.
综合变速器作为装甲车辆传动系统的主要组成部分,其性能的好坏直接影响到车辆的整体性能。由于集成传动装置工作条件复杂,容易发生故障,因此集成传动装置的故障诊断就显得尤为重要。综合传动的故障机理复杂,难以直接确定故障原因。因此,近年来集成传动故障检测算法不断被引入。本文将对这些故障检测算法进行总结。
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引用次数: 0
Intelligent slurry level measurement system of coal mine based on SVM 基于支持向量机的煤矿料浆液位智能测量系统
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00091
Hua Guo, Xuejing Zhang, Wenya Yang, Jinshan Zhuang, Mengjuan Zhu, Le Kong, Qinglin Han, Zhiying Zhang
The filling mining technology is a new trend in coal mining. This paper designs an intelligent sensor system for slurry level measurement of pulping station. Multi-sensor data fusion and the SVM algorithm are adopted for training of collected liquid level values, and compared with the BP neural network, the MSE of the liquid level prediction results obtained using our method is 73.7% lower. This system cannot only address the current state requiring manual monitoring of mixing tank slurry level in coal mine filling system, but can also be used to accurately measure the liquid levels in other complicated industrial applications.
充填采矿技术是煤炭开采的新趋势。本文设计了一种用于制浆站料浆液位测量的智能传感器系统。采用多传感器数据融合和SVM算法对采集的液位值进行训练,与BP神经网络相比,该方法得到的液位预测结果的MSE降低了73.7%。该系统不仅可以解决目前煤矿充填系统搅拌槽料浆液位需要人工监测的现状,也可用于其他复杂工业应用中对液位的精确测量。
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引用次数: 0
Aero-engine Performance Evaluation Based on Gas Path Parameters and Operating Characteristics 基于气路参数和工作特性的航空发动机性能评价
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00066
Wei-Zhe Jiang, Xu-yun Fu, Keqiang Liu, S. Zhong, Bin Yu, Z. Bai
Aero-engine performance evaluation plays an important role in the operation and maintenance management of aviation engines, and it is the basis for formulating aero-engine operation and maintenance plans. To improve the accuracy of aero-engine performance evaluation, we propose to use the principal component analysis evaluation method to study the performance evaluation of the whole aero-engine and the module by combining the operating characteristics of the module, the original value, and the deviation value of the gas path parameters. By decoupling the original value and deviation value of high-dimensional gas path parameters, the direction with the largest performance difference if the module is selected as the principal component. Combined with the operating characteristics of modules to quantify the principal component evaluation indexes, the performance is comprehensively evaluated by using the regression model. To demonstrate the effectiveness of the method, we performed method validation using actual monitoring data from a CFM56-5B engine. The experimental results show that the method can accurately assess the whole engine and module block performance variation of the aero-engine.
航空发动机性能评估在航空发动机运维管理中起着重要作用,是制定航空发动机运维计划的依据。为提高航空发动机性能评价的准确性,提出采用主成分分析评价方法,结合航空发动机模块的工作特性、气路参数的原始值和偏差值,对整个航空发动机和模块进行性能评价研究。通过对高维气路参数的原始值和偏差值进行解耦,选择该模块为主成分时性能差异最大的方向。结合各模块的运行特点,量化主成分评价指标,运用回归模型对性能进行综合评价。为了证明该方法的有效性,我们使用CFM56-5B发动机的实际监测数据进行了方法验证。实验结果表明,该方法能够准确地评估航空发动机整机和模块块性能变化情况。
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引用次数: 1
Research on Pedestrian Intrusion Detection in Static Scenes 静态场景下行人入侵检测研究
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00084
Xunlei Chen, Erkang Li, Jun Yu Li, Siqi Yang, Siwen Zhang, Ziyi Wang
Security system is an important technical means of implementing security prevention and control, and its use in the field of security technology prevention is becoming more and more widespread in the current situation of expanding demand for security. The security systems used now primarily mainly rely on human visual judgment, which demonstrate the lack of intelligent analysis of video content. Static Pedestrian Intrusion Detection (SPID), which determines whether a pedestrian invades a target area in a static scene, is an important vision task in the field of intelligent video surveillance, and has a wide range of applications in scenarios such as intelligent security. To address the problem of static pedestrian intrusion detection data construction, this paper fully investigates the data set and provides sufficient data preparation for the study of this task. This paper proposes a multi-task deep network model based on target detection region segmentation and fast pedestrian detection to achieve accurate pedestrian intrusion determination in static scenes using the powerful nonlinear feature extraction capability of the network. To solve the real-time problem, the model proposes two mobile network optimization strategies, feature sharing and feature cropping, to reduce the computational complexity of the algorithm. Experimental results show that the proposed model achieves 83.1% accuracy and 20.4 FPS detection speed on the static pedestrian intrusion detection datasets, outperforming existing algorithms in terms of both accuracy and speed to achieve end-to-end real-time pedestrian intrusion detection.
安防系统是实现安全防控的重要技术手段,在安防需求不断扩大的当前形势下,其在安防技术防范领域的应用越来越广泛。目前使用的安防系统主要依靠人的视觉判断,缺乏对视频内容的智能分析。静态行人入侵检测(Static Pedestrian Intrusion Detection, SPID)是智能视频监控领域的一项重要视觉任务,在智能安防等场景中有着广泛的应用。为了解决静态行人入侵检测数据构建问题,本文对数据集进行了充分的研究,为本任务的研究提供了充分的数据准备。本文提出了一种基于目标检测区域分割和快速行人检测的多任务深度网络模型,利用网络强大的非线性特征提取能力,实现静态场景下行人入侵的准确判断。为了解决实时性问题,该模型提出了特征共享和特征裁剪两种移动网络优化策略,以降低算法的计算复杂度。实验结果表明,该模型在静态行人入侵检测数据集上的准确率为83.1%,检测速度为20.4 FPS,在准确率和速度上均优于现有算法,实现了端到端实时行人入侵检测。
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引用次数: 0
The coupled vibration response analysis of gearbox with a bearing localized defect 含轴承局部缺陷的齿轮箱耦合振动响应分析
Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00020
Yihao Yu, Juanjuan Shi, Yang Luo, Weiguo Huang, Zhongkui Zhu
Gearbox plays an essential part in railway vehicles, aero engines, and other rotational machinery. Its health condition is significant for the reliable operation of such rotational machinery. To pave the way for the feature extraction of gearbox for its health condition monitoring, the vibration response of gearbox with defects is mandatory. The existing dynamic models of gearbox are mainly oriented on its individual components. However, in reality, the vibration measured from the gearbox housing usually couples the ones of the rolling bearing rotor (RBR) system, gear meshing and gearbox housing, as well as the effect of the elastohydrodynamic lubrication. Therefore, the dynamic model of individual component cannot reflect the actual vibration behaviour of the gearbox. To address this problem, a systematic model coupled the dynamic model of the gear mesh, pinion rolling bearing rotor (RBR) system, gear RBR system, the time-varying displacement excitation caused by a localized defect (LOD), and the effect of the elastohydrodynamic (EHD) lubrication has been established to predict the vibration response of gearbox in this paper. The various excited vibration of the gearbox housing can then be obtained for analyzing the vibration behaviour of the gearbox with the bearing LOD. Moreover, the influences of rotating speed and LOD sizes on the vibration characteristics of the gearbox housing are also analyzed. The established dynamic model is validated by experiments.
齿轮箱在铁路车辆、航空发动机和其他旋转机械中起着重要作用。其健康状况对此类旋转机械的可靠运行具有重要意义。为实现齿轮箱健康状态监测的特征提取,对存在缺陷的齿轮箱振动响应进行了强制性分析。现有的齿轮箱动力学模型主要针对齿轮箱的各个部件。然而,在实际中,从齿轮箱壳测得的振动通常与滚动轴承转子系统、齿轮啮合和齿轮箱壳的振动耦合,以及弹流润滑的影响。因此,单个部件的动力学模型不能反映齿轮箱的实际振动特性。针对这一问题,建立了齿轮啮合、小齿轮滚动轴承转子(RBR)系统、齿轮RBR系统、局域缺陷(LOD)引起的时变位移激励和弹流润滑(EHD)效应耦合的系统模型来预测齿轮箱的振动响应。然后可以得到齿轮箱壳体的各种激发振动,用于分析齿轮箱随轴承LOD的振动特性。此外,还分析了转速和LOD尺寸对齿轮箱壳体振动特性的影响。通过实验验证了所建立的动力学模型。
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引用次数: 0
期刊
2022 Prognostics and Health Management Conference (PHM-2022 London)
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