2019 13th International Conference on Sensing Technology (ICST)最新文献_第8页

Real- Time Recognition Algorithm of Tractor Random Dynamic Load Characteristics for Control 拖拉机随机动态载荷特性实时识别控制算法

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047736

Zhili Zhou, Yiwei Wu, Jun Wang, Jiaxin Chen, Zhanqiang Li

{"title":"Real- Time Recognition Algorithm of Tractor Random Dynamic Load Characteristics for Control","authors":"Zhili Zhou, Yiwei Wu, Jun Wang, Jiaxin Chen, Zhanqiang Li","doi":"10.1109/ICST46873.2019.9047736","DOIUrl":"https://doi.org/10.1109/ICST46873.2019.9047736","url":null,"abstract":"The tractor load is a continuous and dynamic random load with time-varying amplitude and frequency, the time domain characteristics of which are represented by steady-state value, instantaneous value and dynamic load variation coefficient. The time domain characteristics of the random load reflect tractor working state, which are important parameters of tractor control systems for ploughing depth, selection of operating gears and timing of shifting, and load distribution of hybrid power. This kind of dynamic load signal is a colored random signal mixed in other random noises, and its time domain characteristics are difficult to obtain online, which becomes the bottleneck influencing the random load characteristics applied to the field of tractor real-time control. In this paper, based on the study of time domain and frequency domain characteristics of tractor random load signal, the triggered quadratic frequency conversion adaptive Kalman filter algorithm is used to realize the real-time extraction of random load characteristics. Then white noise is eliminated by Kalman filter to extract colored random load signals, and the load steady-state value is obtained after the colored noise is whitened by reducing sampling frequency of secondary filtering. In view of the unknown statistical characteristics of secondary filtering noise, a triggered fading adaptive filter combined with vehicle bus network information sharing technology is adopted to ensure the ability of filter to quickly track the load change. The simulation results show that the random load signal obtained by the algorithm is close to the reference value, and the load variation coefficient can reflect the characteristic changes of the random load, which lays a foundation for the dynamic control of tractor operation process.","PeriodicalId":344937,"journal":{"name":"2019 13th International Conference on Sensing Technology (ICST)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133083551","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

Anomaly Detection Models for Detecting Sensor Faults and Outliers in the IoT - A Survey 物联网中传感器故障和异常点检测的异常检测模型——综述

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047684

A. Gaddam, Tim Wilkin, M. Angelova

{"title":"Anomaly Detection Models for Detecting Sensor Faults and Outliers in the IoT - A Survey","authors":"A. Gaddam, Tim Wilkin, M. Angelova","doi":"10.1109/ICST46873.2019.9047684","DOIUrl":"https://doi.org/10.1109/ICST46873.2019.9047684","url":null,"abstract":"Over the past few years, the Internet of Things (IoT) has gained significant recognition to become a novel sensing paradigm to interact with the physical world. The sensors within the Internet of Things are indispensable parts and are the first port to capture the raw data. As the sensors within IoT are usually deployed in environments which are harsh, which inevitably make the sensors venerable to failure and malfunction. Beside sensor faults and malfunctions, the inherent environment where the sensors are usually installed could also make the sensor to fail prematurely. These conditions will make the sensors within the IoT to generate unusual and erroneous data, often known as outliers. Outliers detection is very crucial in IoT to detect the high probability of erroneous reading or data corruption, thereby ensuring the quality of the data collected by sensors. Data anomalies, abnormal data or outliers are considered to be the sensor data streams that are significantly distinct from the normal behavioural data. In this paper, we present a comprehensive survey that can be used as a guideline to select which outlier model is adequate for the application in the IoT context.","PeriodicalId":344937,"journal":{"name":"2019 13th International Conference on Sensing Technology (ICST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130916866","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: 17

Precision Cylindricity Error Measurement System Design and Error Analysis 精密圆柱度误差测量系统设计及误差分析

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047697

Xiqiang Ma, Fang Yang, Jishun Li, Z. Guan, H. Gurgenci

引用次数: 0

Compensation of the Size-of-Source Effect of Infrared Cameras Using Image Processing Methods 利用图像处理方法补偿红外相机的光源尺寸效应

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047669

S. Schramm, R. Schmoll, A. Kroll

引用次数: 1

A Planar Inductive Based Oil Debris Sensor Plug 一种基于平面电感的油屑传感器插头

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047688

P. Muthuvel, B. George, G. Ramadass

{"title":"A Planar Inductive Based Oil Debris Sensor Plug","authors":"P. Muthuvel, B. George, G. Ramadass","doi":"10.1109/ICST46873.2019.9047688","DOIUrl":"https://doi.org/10.1109/ICST46873.2019.9047688","url":null,"abstract":"Online monitoring of debris in hydraulic and lubrication oil is an effective method to enable preventive maintenance of the associated machinery. The debris particles generated by the machinery due to wear and tear are carried by the working or lubrication fluids. This paper presents a new online magneto-inductive sensor plug. The new sensor plug consists of a permanent magnet (PM) and a spiral-shaped planar sensor coil. The static magnetic field of the PM is utilized to attract the ferrous wear debris particles, that reach the oil tank/reservoir, to the sensor coil. The inductance of the sensor coil placed close to the PM will change as a function of the presence of magnetic/conductive debris. The change in inductance is measured using a high-resolution inductance to digital converter. The prototype of the proposed sensor unit is tested in an experimental setup similar to an industrial hydraulic system. The sensor responses for different size and quantities of debris particles were recorded after injecting them into the hydraulic circuit. The particles that are attracted towards the sensor plug are retained in the plug itself. Hence its recirculation in the machinery is avoided.","PeriodicalId":344937,"journal":{"name":"2019 13th International Conference on Sensing Technology (ICST)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130605982","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

Determining the desertification risks of the Mashhad regions using integrated indices based on the AHP method 基于层次分析法的综合指数确定马什哈德地区沙漠化风险

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047746

A. Abdollahi, Mozhgan Pashaei Nezhad, B. Pradhan

{"title":"Determining the desertification risks of the Mashhad regions using integrated indices based on the AHP method","authors":"A. Abdollahi, Mozhgan Pashaei Nezhad, B. Pradhan","doi":"10.1109/ICST46873.2019.9047746","DOIUrl":"https://doi.org/10.1109/ICST46873.2019.9047746","url":null,"abstract":"Desertification is a natural event that endangers the the world's ecology in different ways, and the unfavorable consequences of this event can be observed in various sections of the Earth. Designing evaluation systems that can investigate the process of destruction and adopt suitable strategies for dealing with this phenomenon is essential and important. In the meantime, selecting indices that can show a clear picture of the status of desertification can play a key role in the decision-making process. In this research, effective indices in desertification, such as vegetation, evapotranspiration, soil moisture, land surface temperature(LST), soil salinity, and rainfall were used on the basis of MODIS satellite data, MERRA, and TRMM for two periods in 2000 and 2013. Then, an AHP method was used to weigh the time variations of each index for 2000 and 2013. Finally, the most effective index for assessing the vulnerability of the study area to desertification in a 13-year period was determined. Results showed that the evapotranspiration index with a weight of 0.412 had the highest importance, and the LST index with a weight of 0.037 had the least importance among other indices. Therefore, the time variations of these indices showed a significant role in the vulnerability assessment of the Mashhad regions to desertification.","PeriodicalId":344937,"journal":{"name":"2019 13th International Conference on Sensing Technology (ICST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123659119","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 Sensor Accuracy Enhancement by Harmonic Spectrum Analysis 谐波频谱分析提高电流传感器精度

2019 13th International Conference on Sensing Technology (ICST) Pub Date : 2019-12-01 DOI: 10.1109/ICST46873.2019.9047692

V. Mateev, Martin Ralchev, I. Marinova

引用次数: 4