2022 Prognostics and Health Management Conference (PHM-2022 London)最新文献_第2页

Gear Tooth Crack Detection Using Modal Analysis 基于模态分析的齿轮齿裂纹检测

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00029

O. Mohammed, Sadok Sassi

引用次数: 0

Dynamics Modeling and Optimization for the Tilting System of Unmanned Aerial Vehicles 无人机倾斜系统动力学建模与优化

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00083

Junqi Lu, Su Cao, Xiangbo Meng, Xiangke Wang, Huangchao Yu

引用次数: 0

Dynamic Model of Planetary Gear with Consideration of Tooth Surface Roughness 考虑齿面粗糙度的行星齿轮动力学模型

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00039

Jirui Zhu, D. Zhen, X. Liang, Guojin Feng, F. Gu, A. Ball

{"title":"Dynamic Model of Planetary Gear with Consideration of Tooth Surface Roughness","authors":"Jirui Zhu, D. Zhen, X. Liang, Guojin Feng, F. Gu, A. Ball","doi":"10.1109/PHM2022-London52454.2022.00039","DOIUrl":"https://doi.org/10.1109/PHM2022-London52454.2022.00039","url":null,"abstract":"Planetary gearbox is numerously used in various mechanical transmission systems because of their extensive bearing range and high reliability. However, due to limitations in manufacturing technique and economic considerations, the gear tooth surface roughness inevitable exists in practical manufacturing process. To analyze the influence of the tooth surface roughness on the vibration signals of a planetary gear system, a nonlinear dynamic model considering multi-factor coupling is established. The dynamic model takes into account gear tooth surface roughness, the gear backlash, time-varying meshing stiffness (TVMS) and vibration transfer path. Via this nonlinear model, the effects of different tooth surface roughness on the system dynamics response are analyzed. Furthermore, the dynamic responses in the time domain and frequency domain are used to examine the influences in the main dynamic parameters, such as rotational speed and meshing force. The results show that the tooth surface roughness significantly affect the system dynamic characteristics, and with the increase of the roughness, the influence on the response of the system will enlarge. This paper can offer some theoretic guidance for the development, operation and fault identification of planetary gear transmission system.","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127873261","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}

引用次数: 0

Joint Memory with Distance Recalculation for Unsupervised Person Re-Identification 无监督人再识别的联合记忆与距离重计算

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00087

Lifeng Zheng, Yangbin Yu, Haifeng Hu, Dihu Chen

{"title":"Joint Memory with Distance Recalculation for Unsupervised Person Re-Identification","authors":"Lifeng Zheng, Yangbin Yu, Haifeng Hu, Dihu Chen","doi":"10.1109/PHM2022-London52454.2022.00087","DOIUrl":"https://doi.org/10.1109/PHM2022-London52454.2022.00087","url":null,"abstract":"Most of the purely unsupervised person Re-Identification (Re-ID) methods use memory dictionary to calculate loss, and use clustering to create memory dictionary and generate pseudo labels. But most of these methods neglect the camera style of the training images, which will severely affect the results of clustering. This paper aims at this challenge, proposes the Joint Memory mechanism with Distance Recalculation. We make full use of and group the feature vectors according to the camera IDs of the training images, and use the clustering algorithm to generate pseudo labels and create memory dictionary inside the same camera. Further, we take advantage of this memory dictionary to recalculate the distances between the training images across all cameras and second time use clustering algorithm to generate pseudo labels and create a new memory dictionary. By jointly utilizing these two kinds of memory dictionary, we can train the network more robustly. Our method accomplishes excellent performance compared to most of state-of-the-art unsupervised Re-ID methods on many datasets, e.g., 91.7%, 84.2%, 59.1% rank-1 accuracy and 80.9%, 71.1%, 32.4% mAP on the Market, Duke and MSMT17 datasets. We achieve this performance when we train the network with a very small batch size, and it is very possible that we can reach a better, maybe surpass state-of-the-art, performance when using a bigger batch size.","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131319909","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}

引用次数: 0

Efficient pavement Distress Detection Based on Attention Fusion and Feature Integration 基于注意力融合和特征融合的路面破损检测方法

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00071

Andong Xie, Zhi Yu, Xiaochun Cao, Yangyang Wang, Shoujing Yan

引用次数: 1

Fault Diagnosis of Reactor Based on Vibration Signal Information Entropy 基于振动信号信息熵的电抗器故障诊断

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00090

Jing Zhang, Yi Jiang, Qinqing Huang, Haidan Lin, Tiancheng Zhao, Yongka Qi

引用次数: 0

A deep partial adversarial transfer learning network for cross-domain fault diagnosis of machinery 机械故障跨域诊断的深度部分对抗迁移学习网络

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00095

Jiachen Kuang, Guanghua Xu, Sicong Zhang, T. Tao, Fan Wei, Yunhui Yu

{"title":"A deep partial adversarial transfer learning network for cross-domain fault diagnosis of machinery","authors":"Jiachen Kuang, Guanghua Xu, Sicong Zhang, T. Tao, Fan Wei, Yunhui Yu","doi":"10.1109/PHM2022-London52454.2022.00095","DOIUrl":"https://doi.org/10.1109/PHM2022-London52454.2022.00095","url":null,"abstract":"Recently, the deep transfer learning-based methods have been widely applied in intelligent fault diagnosis of modern manufacturing equipment in real-industrial scenarios, which are capable of identifying the health conditions of unlabeled target samples under various working conditions. In transfer learning- based intelligent fault diagnosis, the source diagnostic knowledge, which is usually extracted by supervised learning approaches, is transferred and reused in related target fault identification tasks. However, the tremendous success of these transfer learning methods is mainly achieved in the field of close-set cross-domain fault diagnosis. But in practical applications, a partial cross-domain scenario is more common and difficult, where the health conditions of the target domain are less than that of the source domain. To address this issue, a deep partial adversarial transfer learning network (PATLN) based on convolutional neural networks and adversarial training is proposed. Experiments on a public rolling element bearing dataset verify the effectiveness of the PATLN method.","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122339455","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}

引用次数: 5

An Fault Diagnostic Method Based on DRN-ACGAN for Data Imbalance 基于DRN-ACGAN的数据不平衡故障诊断方法

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00025

Jiayu Chen, Cuiying Lin, Jingjing Cui, Hongjuan Ge

引用次数: 2

Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array 基于平面阵列的相干光源到达方向估计的矩阵重构

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00030

Hao Zhang, D. Zhen, Fang Zeng, Guojin Feng, Zhaozong Meng, F. Gu

{"title":"Matrix Reconstruction to Estimate Direction of Arrival of Coherent Sources Based on Planar Array","authors":"Hao Zhang, D. Zhen, Fang Zeng, Guojin Feng, Zhaozong Meng, F. Gu","doi":"10.1109/PHM2022-London52454.2022.00030","DOIUrl":"https://doi.org/10.1109/PHM2022-London52454.2022.00030","url":null,"abstract":"The Multiple Signal Classification (MUSIC) algorithm has become a landmark algorithm in the theoretical system of spatial spectrum estimation. This technology has excellent estimation performance and wide application prospects. Accurate Direction of Arrival (DOA) estimation plays a pivotal role in the detection of narrow wave sources. Nevertheless, when the signals are partially correlated or even coherent, the performance of the traditional MUSIC algorithm is greatly reduced. Methods such as spatial smoothing and Toeplitz matrix reconstruction have been proposed to decoherence and minimize the DOA estimation error in the MUSIC algorithm. However, these methods can only be applied to uniform linear arrays, which greatly reduces the practicability of the algorithm. This paper proposes to combine a decoherence method with MUSIC algorithm to estimate the azimuth angle (θ) and elevation angle (φ) of the source in a planar array which is composed of two orthogonal minimum redundant linear arrays (MRLA). The algorithm is implemented under different Signal-to-Noise Ratio (SNR) and compared with other decoherence methods. Simulation results show the proposed decoherence algorithm can achieve higher DOA estimation accuracy for coherent sources.","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134575623","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}

引用次数: 0

Current Sharing Control of Two - phase Interleaved Parallel Boost Converter Based on Sensorless Current 基于无传感器电流的两相交错并联升压变换器的电流共享控制

2022 Prognostics and Health Management Conference (PHM-2022 London) Pub Date : 2022-05-01 DOI: 10.1109/PHM2022-London52454.2022.00070

Huiyun Hou, Jian-Kun Lu, Chen Yang

{"title":"Current Sharing Control of Two - phase Interleaved Parallel Boost Converter Based on Sensorless Current","authors":"Huiyun Hou, Jian-Kun Lu, Chen Yang","doi":"10.1109/PHM2022-London52454.2022.00070","DOIUrl":"https://doi.org/10.1109/PHM2022-London52454.2022.00070","url":null,"abstract":"In this paper, based on the traditional single closed-loop voltage-type control method, a current sensorless current sharing control method is proposed to solve the current sharing problem in two-phase staggered Boost converters. Based on the characteristics and structure of the circuit itself, the equivalent dc circuit model of the converter is established. It is found that the main reason of phase current imbalance is the mismatch of effective duty cycle and phase parasitic resistance. In order to eliminate the current imbalance caused by them, the relationship between effective duty cycle mismatch compensation, parasitic resistance mismatch of each phase and duty cycle compensation is estimated, and the duty cycle of the second corresponding compensation is obtained based on the first phase. Compared with the traditional current-sharing control strategy, the proposed current-sharing control strategy does not need to collect phase current to judge and process the detected current, which reduces the complexity of the control loop in the controller, and also reduces the influence caused by low precision and high design cost of the current sensor. Finally, the simulation results on Matlab platform show that the equalizing effect of phase current has been significantly improved under various mismatches and different loads, which verifies the effectiveness of the equalizing current control.","PeriodicalId":269605,"journal":{"name":"2022 Prognostics and Health Management Conference (PHM-2022 London)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115048763","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}

引用次数: 0