Proceedings of 7th International Electronic Conference on Sensors and Applications最新文献

筛选

英文中文

Multispectral Sensing and Data Integration for the Study of Heritage Architecture 遗产建筑研究中的多光谱传感与数据集成

Proceedings of 7th International Electronic Conference on Sensors and Applications Pub Date : 2020-11-14 DOI: 10.3390/ecsa-7-08198

E. Adamopoulos, F. Rinaudo, M. Volinia, M. Girotto

{"title":"Multispectral Sensing and Data Integration for the Study of Heritage Architecture","authors":"E. Adamopoulos, F. Rinaudo, M. Volinia, M. Girotto","doi":"10.3390/ecsa-7-08198","DOIUrl":"https://doi.org/10.3390/ecsa-7-08198","url":null,"abstract":"The recording and processing of terrestrial multispectral information can have significant value for built heritage studies. The efficient adoption of active and passive sensing techniques operating at multiple wavelengths and the integrated analyses of the produced data is essential for enhanced observation of historical architecture, especially for the implementation of rapid non-destructive surveys, which can provide an overall assessment of the state-of-preservation of a historical structure to indicate areas of interest for more detailed diagnostics. Based on this rationale, the presented work aims at providing methods for prompt recording, fusion, and integrated visual analysis of two-dimensional multispectral results to study architectural heritage. Spectral images—captured with a modified digital camera—thermograms, photogrammetrically produced orthophoto-maps, and spatial raster data produced from point clouds are integrated and analyzed. The results are evaluated within the scope of studying building materials, deterioration patterns, and hidden defects, towards the employment of advanced geomatics approaches to monitor built heritage effectively.","PeriodicalId":270652,"journal":{"name":"Proceedings of 7th International Electronic Conference on Sensors and Applications","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125083042","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: 1

Simulation of FBG temperature sensor array for oil identification via Random Forest Classification 基于随机森林分类的光纤光栅温度传感器阵列油品识别仿真

Proceedings of 7th International Electronic Conference on Sensors and Applications Pub Date : 2020-11-14 DOI: 10.3390/ecsa-7-08177

Katiuski Pereira, Renan C. Lazaro, Wagner Coimbra, A. Frizera-Neto, A. Leal-Junior

{"title":"Simulation of FBG temperature sensor array for oil identification via Random Forest Classification","authors":"Katiuski Pereira, Renan C. Lazaro, Wagner Coimbra, A. Frizera-Neto, A. Leal-Junior","doi":"10.3390/ecsa-7-08177","DOIUrl":"https://doi.org/10.3390/ecsa-7-08177","url":null,"abstract":"Water–oil separation is important in the oil industry, as the incorrect classification of oil can lead to losses in the production and have an environmental impact. This paper proposes the use of fiber Bragg grating (FBG) temperature sensor array to identify the oil in water–emulsion–oil systems, using only the temperature responses for oil classification results in operational and economic benefits. To demonstrate the possibility of using the FBG temperature sensor to classify oil level, the temperature distribution of an oil storage tank, with 2 m height and 0.8 m in diameter, is simulated using thermal distribution models. Then, the temperature effect in a 2 m long FBG array with a different number and distribution of FBGs is simulated using the transfer matrix method. In each case, we extract the wavelength shift (Δλ), total width at half the maximum (FWHM) and the location of the FBG in the fiber. For the oil classification, we dichotomized the fluids into oil and non-oil (water and emulsion). Due to the low separability of the classes, the random forest algorithm was chosen for classification, starting with 200 FBG equidistant sensors and decreasing to 6, with different distributions along the fiber. As expected, the highest accuracy occurs with the 200 FBGs array (96%). However, it was possible to classify the oil with an accuracy of 94.89% with only 8 FBGs, using tests for two proportions (with a significance of 5%); the accuracy of 8 FBGs is the same as of 50 FBGs.","PeriodicalId":270652,"journal":{"name":"Proceedings of 7th International Electronic Conference on Sensors and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130360125","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: 1

A comparison between piezoelectric sensors applied to multiple Partial Discharge detection by advanced signal processing analysis 采用先进的信号处理分析方法对压电传感器在多次局部放电检测中的应用进行了比较

Proceedings of 7th International Electronic Conference on Sensors and Applications Pub Date : 2020-11-14 DOI: 10.3390/ecsa-7-08243

A. Binotto, B. A. Castro, Vitor Vecina dos Santos, J. A. Rey, A. Andreoli

{"title":"A comparison between piezoelectric sensors applied to multiple Partial Discharge detection by advanced signal processing analysis","authors":"A. Binotto, B. A. Castro, Vitor Vecina dos Santos, J. A. Rey, A. Andreoli","doi":"10.3390/ecsa-7-08243","DOIUrl":"https://doi.org/10.3390/ecsa-7-08243","url":null,"abstract":"The development of sensors applied to failure detection systems for power transformers is a critical concern since this device stands out as a strategic component of the electric power system. Among the most common issues is the presence of partial discharges (PDs) in the insulation system of the transformer, which can lead the device to total failure. Aiming to prevent unexpected damages, several PD monitoring approaches have been developed. One of the most promising is the Acoustic Emission (AE) technique, which captures the acoustic signals generated by PDs using piezoelectric sensors. Although many studies have proved the effectiveness of AE, most signal processing approaches are strictly related to the frequency analysis of PD signals, which can hide important information such as the repetition rate of the failure. This article presents a comparison between two types of piezoelectric transducers: the microfiber composite (MFC) and the lead zirconate titanate (PZT). To ensure the detection of multiple PDs, time–frequency analysis was carried out by short-time Fourier transform (STFT). Intending to compare the sensibility of the transducers, the AE signals were windowed, and the root mean square (RMS) value was extracted for each part of the signal. The results indicate that spectrogram and RMS analysis have great potential to detect multiple PD activity. Although MFC was two times more sensitive to PD detection than the PZT sensor, PZT presents a higher frequency response band (0–100 kHz) than MFC (80 kHz).","PeriodicalId":270652,"journal":{"name":"Proceedings of 7th International Electronic Conference on Sensors and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125275503","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: 8

首页上一页