{"title":"Design and Evaluation of a Spider Web-Like Single-Axis Micro-Electro-Mechanical Systems Accelerometer with High Sensitivity and Fast Response","authors":"Haider Al-Mumen","doi":"10.18280/i2m.220504","DOIUrl":"https://doi.org/10.18280/i2m.220504","url":null,"abstract":"","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"86 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135979346","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}
Bernard A. Adaramola, Joseph F. Kayode, Sunday A. Afolalu, Oluwasina L. Rominiyi, Imhade P. Okokpujie, Omolayo M. Ikumapayi
{"title":"Investigating Fluid Flow Regimes: A Novel Design and Implementation of Bernoulli’s Apparatus","authors":"Bernard A. Adaramola, Joseph F. Kayode, Sunday A. Afolalu, Oluwasina L. Rominiyi, Imhade P. Okokpujie, Omolayo M. Ikumapayi","doi":"10.18280/i2m.220503","DOIUrl":"https://doi.org/10.18280/i2m.220503","url":null,"abstract":"","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"102 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135979349","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}
This article presents a proposed approach and mechanism for calibrating a spring hammer. The metrological characterization of the calibration results was discussed and the uncertainty of this measurement was evaluated. The proposed approach demonstrates a more applicable calibration method using a high accuracy force transducer to measure the spring force and a high-precision deflection measuring instrument to measure the corresponding deflection. Different relative errors are calculated to detect the applicability and accuracy of this approach. The overall relative expanded uncertainty is presented based on the introduced repeatability and reproducibility errors, side by side with the uncertainties of the reference force transducer and length measuring device used. The proposed calibration technique is used to calibrate both types of spring impact hammers; the multi-step hammer and the single-step hammer. Two examples for calibrating multi-step hammer and another single-step hammer are presented with relative expanded uncertainties from 0.36% up to 5.37%.
{"title":"Metrological Characterization of Spring Impact Hammer Calibration","authors":"Khaled M. Khaled, Riham S. Hegazy","doi":"10.18280/i2m.220505","DOIUrl":"https://doi.org/10.18280/i2m.220505","url":null,"abstract":"This article presents a proposed approach and mechanism for calibrating a spring hammer. The metrological characterization of the calibration results was discussed and the uncertainty of this measurement was evaluated. The proposed approach demonstrates a more applicable calibration method using a high accuracy force transducer to measure the spring force and a high-precision deflection measuring instrument to measure the corresponding deflection. Different relative errors are calculated to detect the applicability and accuracy of this approach. The overall relative expanded uncertainty is presented based on the introduced repeatability and reproducibility errors, side by side with the uncertainties of the reference force transducer and length measuring device used. The proposed calibration technique is used to calibrate both types of spring impact hammers; the multi-step hammer and the single-step hammer. Two examples for calibrating multi-step hammer and another single-step hammer are presented with relative expanded uncertainties from 0.36% up to 5.37%.","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"15 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135979499","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}
In this study, a novel measurement framework for two-phase air-water bubbly flow has been developed. It consists of ultrasonic and digital optical imaging systems. The measured parameters include instantaneous velocity profiles of the two phases, void fraction and bubble size of the gas phase. The simultaneous velocity profiles of both phases are measured by the state-of-the-art multiwave Ultrasonic Velocity Profile method - multiwave UVP for short. The void fraction and bubble size are measured by a digital imaging system that exploits high-speed video imaging. Non-intrusive measurement of these instantaneous flow parameters is still a challenge in two-phase flow study. In the present investigation, two ultrasonic signal processing algorithms have been implemented and tested, namely Doppler signal processing and correlation one. Similarly, rigorous digital image processing algorithms implemented in ImageJ tool have been exploited and tested to obtain the average void fraction and bubble size distribution. Furthermore, measurements and analyses have been carried out for various flow conditions. For the particular flow configuration investigated, important experimental data of the two-phase counter-current bubbly flow have been successfully obtained for the first time. The measured data are useful for both experimental and numerical analyses, especially computational fluid dynamics - CFD analyses, of two-phase flows.
{"title":"Measurement of Bubbly Two-Phase Flow in a Vertical Pipe Using Ultrasonic Velocity Profiler and Digital Optical Imaging","authors":"Nguyen Tat Thang","doi":"10.18280/i2m.220403","DOIUrl":"https://doi.org/10.18280/i2m.220403","url":null,"abstract":"In this study, a novel measurement framework for two-phase air-water bubbly flow has been developed. It consists of ultrasonic and digital optical imaging systems. The measured parameters include instantaneous velocity profiles of the two phases, void fraction and bubble size of the gas phase. The simultaneous velocity profiles of both phases are measured by the state-of-the-art multiwave Ultrasonic Velocity Profile method - multiwave UVP for short. The void fraction and bubble size are measured by a digital imaging system that exploits high-speed video imaging. Non-intrusive measurement of these instantaneous flow parameters is still a challenge in two-phase flow study. In the present investigation, two ultrasonic signal processing algorithms have been implemented and tested, namely Doppler signal processing and correlation one. Similarly, rigorous digital image processing algorithms implemented in ImageJ tool have been exploited and tested to obtain the average void fraction and bubble size distribution. Furthermore, measurements and analyses have been carried out for various flow conditions. For the particular flow configuration investigated, important experimental data of the two-phase counter-current bubbly flow have been successfully obtained for the first time. The measured data are useful for both experimental and numerical analyses, especially computational fluid dynamics - CFD analyses, of two-phase flows.","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135990227","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}
Time series analysis is pivotal in discerning temporospatial data patterns and facilitating precise forecasts. This study scrutinizes the cardinal challenges associated with time series modeling, namely stationarity, parsimony, and overfitting, focusing on the application of Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. An examination of six datasets reveals that these models adeptly encapsulate underlying data trends, enabling reliable predictions and yielding insightful conclusions. Relative to baseline methods, the proposed models demonstrate superior performance, as indicated by five evaluation metrics: Mean Squared Error (MSE), Frantic, Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and Theil's U-statistics. The most parsimonious ARIMA or SARIMA model was selected for each dataset, with the resultant forecast summary graphically demonstrating the proximity between original and predicted observations. This study aims to contribute to the discourse on the validity and applicability of ARIMA and SARIMA models in time series analysis and forecasting.
{"title":"Time Series Modeling and Forecasting Using Autoregressive Integrated Moving Average and Seasonal Autoregressive Integrated Moving Average Models","authors":"Vignesh Arumugam, Vijayalakshmi Natarajan","doi":"10.18280/i2m.220404","DOIUrl":"https://doi.org/10.18280/i2m.220404","url":null,"abstract":"Time series analysis is pivotal in discerning temporospatial data patterns and facilitating precise forecasts. This study scrutinizes the cardinal challenges associated with time series modeling, namely stationarity, parsimony, and overfitting, focusing on the application of Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. An examination of six datasets reveals that these models adeptly encapsulate underlying data trends, enabling reliable predictions and yielding insightful conclusions. Relative to baseline methods, the proposed models demonstrate superior performance, as indicated by five evaluation metrics: Mean Squared Error (MSE), Frantic, Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and Theil's U-statistics. The most parsimonious ARIMA or SARIMA model was selected for each dataset, with the resultant forecast summary graphically demonstrating the proximity between original and predicted observations. This study aims to contribute to the discourse on the validity and applicability of ARIMA and SARIMA models in time series analysis and forecasting.","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135990230","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}
Iron losses are a major source of inefficiency in electrical devices, such as transformers and rotating machines. Accurately estimating iron losses is essential for optimizing the performance, energy efficiency, and cost-effectiveness of these devices. The swelling phenomenon is a significant factor that affects the accuracy of iron loss estimation. This phenomenon appears in the saturation region of the hysteresis loop under high-frequency regimes and can significantly affect the magnetic properties of the device. This paper presents a novel methodology for addressing the swelling phenomenon and improving the accuracy of iron loss estimation. The methodology is based on the Jiles-Atherton model, which is a well-established model for describing the hysteresis phenomenon in ferromagnetic materials. The methodology is improved by incorporating a novel formulation of the excess field based on magnetic viscosity. The Bertotti approach is used to account for the dynamic effects of the swelling phenomenon. The fmincon algorithm is used to identify the parameters of the Jiles-Atherton model in both quasi-static and dynamic regimes. This algorithm is a MATLAB®-based constrained optimization method that is used to find the set of parameters that minimizes the error between the simulated and measured hysteresis loops. The obtained results show that the proposed methodology is able to accurately estimate iron losses under both quasi-static and dynamic regimes.
{"title":"Improving the Swelling Phenomenon in the Dynamic Jiles-Atherton Hysteresis Model Using Magnetic Viscosity","authors":"Aidel Sofiane, Mourad Hamimid","doi":"10.18280/i2m.220405","DOIUrl":"https://doi.org/10.18280/i2m.220405","url":null,"abstract":"Iron losses are a major source of inefficiency in electrical devices, such as transformers and rotating machines. Accurately estimating iron losses is essential for optimizing the performance, energy efficiency, and cost-effectiveness of these devices. The swelling phenomenon is a significant factor that affects the accuracy of iron loss estimation. This phenomenon appears in the saturation region of the hysteresis loop under high-frequency regimes and can significantly affect the magnetic properties of the device. This paper presents a novel methodology for addressing the swelling phenomenon and improving the accuracy of iron loss estimation. The methodology is based on the Jiles-Atherton model, which is a well-established model for describing the hysteresis phenomenon in ferromagnetic materials. The methodology is improved by incorporating a novel formulation of the excess field based on magnetic viscosity. The Bertotti approach is used to account for the dynamic effects of the swelling phenomenon. The fmincon algorithm is used to identify the parameters of the Jiles-Atherton model in both quasi-static and dynamic regimes. This algorithm is a MATLAB®-based constrained optimization method that is used to find the set of parameters that minimizes the error between the simulated and measured hysteresis loops. The obtained results show that the proposed methodology is able to accurately estimate iron losses under both quasi-static and dynamic regimes.","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135990235","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}
{"title":"Soft Sensor Modelling Method Using Improved LWPLS for Fermentation Monitoring of Pichia Pastoris","authors":"Ligang Zhang, Bo Wang, Li Zhu, Qiwei Zhu","doi":"10.18280/i2m.220402","DOIUrl":"https://doi.org/10.18280/i2m.220402","url":null,"abstract":"","PeriodicalId":38637,"journal":{"name":"Instrumentation Mesure Metrologie","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135990234","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：