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Image enhancement algorithm of Dongba manuscripts based on wavelet analysis and grey relational theory 13

Image enhancement algorithm of Dongba manuscripts based on w...

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2017 13th IEEE International Conference on Electronic measurement & Instruments (ICEMI)

作者： Xia Xinyu Wu Guoxin Zhu Chunmei Ding Chunyan Geng Qiaoman Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Minzu University of China

ISBN: (纸本)9781509050369;9781509050352

Image enhancement is an important part of the image processing of Dongba manuscripts. For the low-contrast and fuzzy Dongba manuscripts image, in this paper, an image enhancement algorithm based on wavelet analysis and grey relational analysis is proposed. Firstly, the wavelet transform is used to decompose the Dongba manuscripts image into three levels, and the corresponding low-frequency components and high-frequency components are obtained. Then, the interference signal and the useful signal in the high frequency component are distinguished by the grey relation analysis theory. Finally, inverse wavelet transformation is used to reconstruct the image so that the contrast enhancement and background suppression can be achieved. The experimental results show that compared with the conventional filtering method and wavelet threshold denoising enhancement method, the proposed method has the highest peak signal-to-noise ratio, suppresses the noise while enhancing the image details and improving the image contrast.

关键词： wavelet transform grey relation analysis image enhancement Dongba manuscripts image

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Review of fault diagnosis methods for rotating machinery based on deep learning 8

Review of fault diagnosis methods for rotating machinery bas...

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8th International Symposium on Test Automation and Instrumentation, ISTAI 2020

作者： Guo, Yong L. Wu, Guo X. Liu, Xiu L. Xu, Xiao L. Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science&Technology University Beijing China

ISBN: (纸本)9781839535635

Mechanical equipment fault diagnosis technology is a new research field with the development of modern science and technology. In recent years, the deep learning has been applied into the field of mechanical equipment fault diagnosis by more and more researchers. Deep learning has been widely applied in various industries and fields with its unique advantages in feature extraction and pattern recognition. The development history of deep learning is first briefly reviewed. Then, four fault diagnosis methods based on deep learning model are emphatically analyzed combined with the characteristics and requirements of fault diagnosis technology for large rotating machinery equipment, and the problems and challenges they face are discussed. Finally, the research direction worth to be carried out in the future is prospected. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Rotating machinery

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Research on denoising methods of linear CCD spectrum data using combined filter based on wavelet threshold 13

Research on denoising methods of linear CCD spectrum data us...

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2017 13th IEEE International Conference on Electronic measurement & Instruments (ICEMI)

作者： Zhang Long Wu Guoxin Ding Chunyan Lu Jiwei Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Minzu University of China

ISBN: (纸本)9781509050369;9781509050352

Due to the influence of various factors, such as the test environment, the instrument itself and the target's spectrum characteristics, the measured linear CCD spectrum data contains noise. If the noise can not be removed effectively, the results of spectrum detection will be affected. Since the noise contained in the linear CCD spectrum data is mainly Gauss white noise and impulsive noise, a combined filter method based on wavelet threshold and median filter is proposed to denoise the linear CCD spectrum data in this paper. The simulation spectrum data and the measured spectrum data captured by spectrum instrument are used to check the validity of this method. The simulation results show that using the combined filter method, the noise of the spectrum data can be effectively reduced, and the signal-to-noise ratio of the spectrum signal is improved.

关键词： linear CCD spectrum data denoising wavelet threshold median filter combined filter

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DESIGN OF AN ELECTROMAGNETICALLY TUNED MASS DAMPER AND ITS EXPERIMENTAL STUDY ON VIBRATION REDUCTION FOR FLYWHEEL ROTOR SYSTEMS 10

DESIGN OF AN ELECTROMAGNETICALLY TUNED MASS DAMPER AND ITS E...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Nie, Haidu Tang, Changliang Mu, Mengliang Xu, Henglei Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781837242672

The trend towards higher speeds in flywheel energy storage systems is highlighting the need for improved bearing support. To overcome the limitations of traditional oil dampers, such as narrow damping range and insufficient damping, this study introduces an Electromagnetic Tuned Mass Damper (ETMD) designed for high-speed, low-inertia flywheel systems. Using Comsol finite element software, a model was created to optimize the damper's parameters. A comparative experiment was conducted between the newly designed ETMD and a conventional oil damper on vibration damping single point flexible support. The experimental findings indicate that a uniform arrangement of permanent magnets within the eddy current damper yields greater damping forces, with the damping coefficient significantly increasing at amplitudes beyond 0.2 mm, and notably effective in controlling low-frequency vibrations within the 75 Hz to 25 Hz range. Although the magnetic yoke is crucial, variations in its thickness minimally affect performance, and the optimal damping effect is achieved with a back iron thickness of 4mm, highlighting the existence of an ideal thickness for the back iron. Rotor experiments have demonstrated that eddy current dampers demonstrate enhanced vibration control with amplitudes of 49 urn, outperforming hydrodynamic dampers at 75 μm during acceleration and 71 μm during deceleration. © The Institution of Engineering & technology 2024.

关键词： Permanent magnets

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RESEARCH PROGRESS ON WIRELESS SENSOR NETWORKS FOR MECHANICAL VIBRATION MONITORING: A CITESPACE VISUALIZATION ANALYSIS APPROACH 10

RESEARCH PROGRESS ON WIRELESS SENSOR NETWORKS FOR MECHANICAL...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Zha, Zhendong Jiang, Zhanglei Li, Zihan Liu, Xiuli Wu, Guoxin The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing100192 China

ISBN: (纸本)9781837242672

The application of wireless sensor networks (WSNs) in mechanical vibration monitoring is pivotal for achieving efficient monitoring within the realms of industrial automation and intelligent manufacturing, playing a significant role in the digital transformation and upgrading of China's manufacturing industry. This paper provides a comprehensive overview of the major technological advancements made by scholars and institutions globally over the past sixteen years in the domain of mechanical vibration monitoring using WSNs. Subsequently, employing CiteSpace for knowledge mapping and visualization, a multifaceted statistical analysis is conducted on over four hundred publications from both domestic and international sources. Through clustering analysis, keyword co-occurrence, and other analytical techniques, the paper delineates the multidimensional evolution of research hotspots and the dynamics of author collaboration networks over time. Building on this foundation, the paper delves into the cutting-edge trends of the field, emphasizing the critical importance of establishing efficient energy management systems and leveraging machine learning and artificial intelligence to process large-scale sensor data. These strategies are essential for optimizing system performance and propelling the development of WSNs towards miniaturization, integration, multifunctionality, systematization, and networking. The synergistic effects of these measures are anticipated to provide robust support for the intelligent upgrade of the manufacturing industry, fostering its progression towards greater efficiency and intelligence. © The Institution of Engineering & technology 2024.

关键词： Information management

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Condition Monitoring and Diagnosis for Grid-connected Photovoltaic Power System

Condition Monitoring and Diagnosis for Grid-connected Photov...

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2013 IEEE 11th International Conference on Electronic measurement & Instruments

作者： Xu Xiaoli Chen Tao Zuo Yunbo Key Laboratory of Modern Measurement & Control Technology Ministry of EducationBeijing Information Science and Technology University

ISBN: (纸本)9781479907571;9781479907588

The photovoltaic power generation directly converts the solar energy into electric energy through photovoltaic cell, which is an important way to solve energy shortage and environmental pollution. In order to raise the reliability and reduce costs of grid-connected photovoltaic power station, we analyze types of common faults and causes, and specify numerous devices and disperse layout, design wireless monitoring diagnosis system to realize wireless monitor and control for grid-connected photovoltaic power station in order to ensure the safe operation.

关键词： Photovoltaic power generation, monitoring, diagnosis.

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Research on Failure Prediction Using DBN and LSTM Neural Network 57

Research on Failure Prediction Using DBN and LSTM Neural Net...

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57th Annual Conference of the Society of Instrument and control Engineers of Japan, SICE 2018

作者： Yuhai, Gu Shuo, Liu Linfeng, He Liyong, Wang Beijing Information Science Technology University Ministry of Education Key Laboratory of Modern Measurement Control Technology Bcijing100192 China

ISBN: (纸本)9784907764609

Because the vibration signal data has a high dimension, ordinary fault prediction methods are very complicated for data preprocessing. A fault diagnosis method combining DBN and LSTM was proposed in this paper. This method uses DBN's excellent feature extraction capability to extract feature vectors of time-series fault data, and uses LSTM network to perform fault prediction on the extracted feature vectors, because LSTM network has good adaptability to sequential data. The author used the bearing data of Case Western Reserve University to build a training set and conduct experiments. Experimental results show that this method can reduce the difficulty of data preprocessing and increase the accuracy of fault prediction. © 2018 The Society of Instrument and control Enginners - SICE.

关键词： Forecasting

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FAST DETECTION ALGORITHM BASED ON YOLOV8 WITH STRUCTURAL REPARAMETERISATION AND GROUPED CONVOLUTIONAL HEADS 10

FAST DETECTION ALGORITHM BASED ON YOLOV8 WITH STRUCTURAL REP...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Chen, Xuanyu Wu, Guoxin Zhang, Guolong Zhou, Linglong The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing100192 China

ISBN: (纸本)9781837242672

As autonomous driving technology advances swiftly, the precise identification of road signs has become essential for enabling autonomous driving. This paper introduces an enhanced YOLOv8 model for road sign recognition. This model enhances the original C2f module by incorporating the RepViT Block, resulting in the C2f_RVB module. This alteration not only hastens the convergence rate of the model but also markedly boosts detection precision. Furthermore, we introduce a highly efficient architectural framework utilizing lightweight ViTs, which augments the model's detection speed while minimizing the parameter count. Lastly, we incorporate grouped convolution to enhance the detection head of YOLOv8. Tests were conducted utilizing the Street Sign Locator dataset, which was improved with information from the Roboflow stage. The exploratory comes about illustrate that the proposed RVB-YOLOv8 demonstrate accomplishes critical upgrades in discovery measurements like mAP and FLOPs when compared to the initial YOLOv8 demonstrate, whereas too diminishing the number of parameters by one-third. © The Institution of Engineering & technology 2024.

关键词： Convolution

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PAPR Reduction in OFDM-IM Using Dither Signal Sets

PAPR Reduction in OFDM-IM Using Dither Signal Sets

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2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Zhang, Si-Yu Zheng, Hui Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Beijing100101 China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Similar to most multicarrier modulations, orthog-onal frequency division multiplexing with index modulation (OFDM-IM) also suffers high peak to average power ratio (PAPR) issue due to its inherit structure. In this paper, a novel PAPR reduction scheme for OFDM-IM with dither signals is proposed. Unlike the previous method that utilizes convex programming to determine the optimized signals that are added to the idle subcarriers of OFDM-IM. The proposed scheme utilizes several fixed sets which contain constraint amplitude dither signals to reduce the PAPR. Simulation results show that the proposed scheme can achieve solid PAPR reduction performance similar to that of the classical PAPR reduction schemes (e.g. partial transmit sequence (PTS), selected mapping (SLM)). Moreover, compared with the conventional PAPR reduction scheme with dither signals, the proposed one does not need convex optimization, which owns high computational complexity. Also, by utilizing selected dither signals, the proposed scheme can achieve lower error performance than that of the conventional scheme with dither signal. © 2022 IEEE.

关键词： Peak to average power ratio

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EXPERIMENTAL STUDY ON THE VIBRATION CHARACTERISTICS OF CONFLUENCE PLANETARY ROW IN HEALTH AND BROKEN TEETH FAILURE 10

EXPERIMENTAL STUDY ON THE VIBRATION CHARACTERISTICS OF CONFL...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Henglei, Xu Changliang, Tang Haoyan, Chen Shaodong, He Xuelian, Qu Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781837242672

As one of the core components to realize dual-power convergence in the transmission device, the confluence planetary row is characterized by large force and high rotational speed in the actual operation process, and its failure is easy to lead to the failure of straight driving and steering function of the crawler vehicle. The design and construction of the converging planetary row vibration test bench, with the planetary wheel broken teeth fault as an example, respectively, to carry out healthy and broken teeth fault confluence planetary row dynamics characteristics of experimental research, through different loads and different degree of broken teeth faults and other groups of tests, for the groups of experimental results of the data analysis of the time-frequency domain response characteristics of the planetary wheel broken teeth faults to get the characteristics of the vibration of the planetary wheel broken teeth faults, as a confluence planetary row failure identification and diagnosis to provide the basis. The vibration characteristics of planetary wheel broken teeth are obtained to provide a basis for the identification and diagnosis of confluence planetary row fault. © The Institution of Engineering & technology 2024.

关键词： Semantic Segmentation

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