2016 10th International Conference on Sensing Technology (ICST)最新文献_第2页

Multi-domain sequential signature analysis for machinery intelligent diagnosis 面向机械智能诊断的多域序列特征分析

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796265

Jinjiang Wang, Yulong Zhang, Li-xiang Duan, Xuduo Wang

{"title":"Multi-domain sequential signature analysis for machinery intelligent diagnosis","authors":"Jinjiang Wang, Yulong Zhang, Li-xiang Duan, Xuduo Wang","doi":"10.1109/ICSENST.2016.7796265","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796265","url":null,"abstract":"Feature extraction plays an important role in machinery fault diagnosis and prognosis. The features extracted from time, frequency and time-frequency domains are widely investigated to describe the properties of overall signal from different perspectives, seldom considering the sequential characteristic of time-series signal in which the fault information may be embedded. This paper investigates a novel approach combing modified Symbolic Aggregate approXimation (SAX) framework and Kernel Principal Component Analysis (KPCA) to extract fault information by analyzing sequential pattern in time-series signal for fault diagnosis. SAX reduces the dimensionality of raw data by transforming the original real valued time series into a discrete one with analyzing signal sequential characteristic and then multiple features are fused by KPCA for fault classification. The proposed approach has high computation efficiency and feature extraction accuracy. Experimental studies on reciprocating compressor valve demonstrate that the presented approach outperforms the methods of SAX-entropy using support vector machine for classification.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128968389","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: 2

A motion tracking method by combining the IMU and camera in mobile devices 一种移动设备中IMU与摄像头相结合的运动跟踪方法

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796235

Wei Fang, Lianyu Zheng, Huanjun Deng

引用次数: 8

Linear regression models for chew count estimation from piezoelectric sensor signals 基于压电传感器信号的咀嚼计数估计线性回归模型

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796222

Muhammad Farooq, E. Sazonov

引用次数: 11

Study on different touch object recognition algorithm based on Android and capacitive touch panel 基于Android和电容式触摸屏的不同触摸对象识别算法研究

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796300

Zhu Qiwen, Sun Jun, H. Xueqin, Zhou Hongmei, Tang Yongming

引用次数: 2

A video-based monitor for assessing free-fall droplet motion 用于评估自由落体液滴运动的视频监视器

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796219

Chih-Yen Chen, C. Weng, C. Hwang, C. Hsieh

{"title":"A video-based monitor for assessing free-fall droplet motion","authors":"Chih-Yen Chen, C. Weng, C. Hwang, C. Hsieh","doi":"10.1109/ICSENST.2016.7796219","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796219","url":null,"abstract":"A newly video-based monitoring technique was developed in this study to characterize the shape and free-fall velocity of water droplets. The free-fall droplet monitoring system integrates three main components which are containing the CCD image sensor for capturing video images, the backlight source for illuminating the water droplets, and the computation unit for the image acquisition and function control. Subsequently, the high-speed CCD image sensor was used to capture images in 200 fps and the exposure time was set at 100 μs. With high contrast images, we mark out every droplet by detecting its contour. Later, a series of droplet detection and tracking algorithms were executed to obtain the velocity of the free-fall droplets. In the simulation experiments, the glass balls and the water droplets ejected from a sprinkler were both introduced for the verification of the system performance. The experimental results support the proposed free-fall droplet monitoring system including the combination of droplet detection and droplet tracking algorithms are capable to provide a promising approach for the measurement of the free-fall droplets. Additionally, this apparatus could be improved by replacing a CCD image sensor with larger sensing area or the faster sampling rate in our next attempt.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132060026","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

Research on reflective pulse oximetry based on fiber optic spectrometer 基于光纤光谱仪的反射式脉搏血氧仪研究

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796304

Zheng Liu, Dezhi Zheng, Wei Zhou, Meiling Zhou

引用次数: 0

A high performance VCO using adaptive class C technique for sensor application 采用自适应C类技术的高性能压控振荡器，用于传感器应用

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796255

W. Lai, S. Jang, Ho Chang Lee, Wei-Te Liu, C. Hsue

引用次数: 2

Improving performance of an omnidirectional range sensor for 3D modeling of environments 改进全向距离传感器的三维环境建模性能

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796230

R. Marani, N. Mosca, V. Renó, M. Nitti, G. Cicirelli, E. Stella, T. D’orazio

{"title":"Improving performance of an omnidirectional range sensor for 3D modeling of environments","authors":"R. Marani, N. Mosca, V. Renó, M. Nitti, G. Cicirelli, E. Stella, T. D’orazio","doi":"10.1109/ICSENST.2016.7796230","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796230","url":null,"abstract":"High resolution in distance (range) measurements can be achieved by means of accurate instrumentations and precise analytical models. This paper reports an improvement in the estimation of distance measurements performed by an omnidirectional range sensor already presented in literature. This sensor exploits the principle of laser triangulation, together with the advantages brought by catadioptric systems, which allow the reduction of the sensor size without decreasing the resolution. Starting from a known analytical model in two dimensions (2D), the paper shows the development of a fully 3D formulation where all initial constrains are removed to gain in measurement accuracy. Specifically, the ray projection problem is solved by considering that both the emitter and the receiver have general poses in a global system of coordinates. Calibration is thus made to estimate their poses and compensate for any misalignment with respect to the 2D approximation. Results prove an increase in the measurement accuracy due to the more general formulation of the problem, with a remarkable decrease of the uncertainty.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131827328","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

Energy-efficient flooding with minimum latency for low-duty-cycle WSNs 低占空比无线传感器网络的最小时延节能泛洪

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796228

Huahua Song, Zhen Xu, Xiangang Wang

引用次数: 3

Gearbox fault classification using S-transform and convolutional neural network 基于s变换和卷积神经网络的齿轮箱故障分类

2016 10th International Conference on Sensing Technology (ICST) Pub Date : 2016-11-01 DOI: 10.1109/ICSENST.2016.7796330

Xueqiong Zeng, Yixiao Liao, Weihua Li

引用次数: 29