scholarly journals Development of low-cost inclination sensor based on MEMS accelerometers

2021 ◽  
Vol 906 (1) ◽  
pp. 012057
Author(s):  
Jan Balek ◽  
Petr Klokočník
Keyword(s):  
Power Consumption ◽  
Web Application ◽  
Temperature Compensation ◽  
Rapid Development ◽  
Complete Solution ◽  
Building Structures ◽  
Mems Accelerometer ◽  
Laboratory Conditions ◽  
Stable Conditions ◽  
Mems Accelerometers

Abstract Rapid development of Micro Electro Mechanical Systems (MEMS) and the minimization of sensor cost, size and energy consumption in the last two decades leads to an effort to replace traditional sensors with their MEMS alternatives. The power consumption is one of the key problems, due to necessity to provide long term device power supply. Therefore a newly developed device was designed with the accent to low power consumption, to be able to operate with one small internal battery at range several months to years. The main goal was to develop a wireless monitoring system capable of continuous stability monitoring of various building structures. The sensor is designed to measure slow inclination variations or changes and in combination with variant designed for high frequency monitoring should represent complete solution of real time structure health monitoring. The STATOTEST compact measurement system is mainly composed of triaxial MEMS accelerometer as a sensing unit, motherboard containing IOT modules and battery, all placed in single waterproof box. The raw signal measured by MEMS accelerometer is preprocessed inside the unit and the data are sent to the cloud via LoRaWan, NBIoT or satellite. The results can be displayed, managed and exported through the web application. This paper presents current state of sensor development, refer to number of problems, which were solved during the process and deals with estimation of its accuracy characteristics in the laboratory conditions. During the laboratory experiment, small defined changes of inclination were performed and compared with values registered by the inclination sensor. The testing was performed before and after calibration procedures. After eliminating of accelerometers production errors, the accuracy of the unit measurement RMSE is less than 0.002° for the step change of 0.09°, tested in six different orientations of the sens or. One measurement is mean of 1000 measurements and its residual random error for one measurement is 2°x10e-5. Series of laboratory tests proved high short-term device accuracy in stable conditions. It is well known, that MEMS accelerometers strongly depend on the sensor temperature. To perform temperature compensation, we built own climate chamber, which is able to change automatically temperature of the several devices at once in specified ranges. Temperature compensation was then performed by using of polynomial approximation to obtain the field measurement accuracy close to laboratory conditions. This task is challenging because it is necessary to improve the proper material composition between the MEMS and the monitored structure and the device fixing methods.

scholarly journals Fusion Algorithm-Based Temperature Compensation Method for High-G MEMS Accelerometer

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Qing Lu ◽  
Chong Shen ◽  
Huiliang Cao ◽  
Yunbo Shi ◽  
Jun Liu
Keyword(s):  
Temperature Compensation ◽  
Signal Reconstruction ◽  
Measurement Data ◽  
Wavelet Thresholding ◽  
Fusion Algorithm ◽  
Temperature Drift ◽  
Mems Accelerometer ◽  
Accelerometer Signal ◽  
Mems Accelerometers ◽  
And Performance

In recent years, High-G MEMS accelerometers have been widely used in aviation, medicine, and other fields. So it is extremely important to improve the accuracy and performance of High-G MEMS accelerometers. For this purpose, we propose a fusion algorithm that combines EMD, wavelet thresholding, and temperature compensation to process measurement data from a High-G MEMS accelerometer. In the fusion algorithm, the original accelerometer signal is first decomposed by EMD to obtain the intrinsic mode function (IMF). Then, sample entropy (SE) is used to divide the IMF components into three segments. The noise segment is directly omitted, wavelet thresholding is performed on the mixing segment, and a GA-BP performs temperature compensation on the drift segment. Finally, signal reconstruction is implemented. Later, a comparative analysis is carried out on the results from four models: EMD, wavelet thresholding, EMD + wavelet thresholding, and EMD + wavelet thresholding + temperature compensation. The experimental data show that the acceleration random walk change from 1712.66 g/h/Hz0.5 to 79.15 g/h/Hz0.5 and the zero-deviation stability change from 49275 g/h to 774.7 g/h. This indicates that the fusion algorithm (EMD + wavelet thresholding + temperature compensation) not only effectively suppresses the noise of high-frequency components but also compensates for temperature drift in the accelerometer.

scholarly journals A Tool for Energy Consumption Monitoring and Analysis of the Android Terminal

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Deguang Li ◽  
Zhanyou Cui ◽  
Chenguang Bai ◽  
Qiurui He ◽  
Xiaoting Yan
Keyword(s):  
Power Consumption ◽  
Rapid Development ◽  
Mobile Terminal ◽  
Power Model ◽  
Power Modeling ◽  
Application Layer ◽  
Consumption Data ◽  
Android Platform ◽  
Instrument Measurement ◽  
Original Information

With the rapid development of communication technology, the intelligent mobile terminal brings about great convenience to people’s life with rich applications, while its power consumption has become a great concern to researchers and consumers. Power modeling is the basis to understand and analyze the power consumption characteristics of the terminal. In this paper, we analyze the Bluetooth and hidden power consumption of the android platform and fix the power model of open-source Android platform. Then, a power consumption monitoring tool is implemented based on the model; the tool is divided into three layers, which are original information monitor layer, power consumption calculation layer, and application layer. The original monitor layer gets the power consumption data and running time of the different components under different states, the calculation layer calculates the power consumption of each hardware and each application based on the power model of each component, and the application layer displays the real-time power consumption of the software and hardware. Finally, we test our tool in real environment by using Xiaomi 9 Pro and perform comparison with actual instrument measurement; the error between the monitored value and the measured value is less than 5%.

scholarly journals Monthly Electricity Consumption Forecasting Method Based on X12 and STL Decomposition Model in an Integrated Energy System

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Tianhe Sun ◽  
Tieyan Zhang ◽  
Yun Teng ◽  
Zhe Chen ◽  
Jiakun Fang
Keyword(s):  
Power Consumption ◽  
Rapid Development ◽  
Electricity Consumption ◽  
Energy System ◽  
Small Scale ◽  
Power Demand ◽  
Distributed Energy ◽  
Strategic Competition ◽  
Integrated Energy System ◽  
Monthly Electricity Consumption

With the rapid development and wide application of distributed generation technology and new energy trading methods, the integrated energy system has developed rapidly in Europe in recent years and has become the focus of new strategic competition and cooperation among countries. As a key technology and decision-making approach for operation, optimization, and control of integrated energy systems, power consumption prediction faces new challenges. The user-side power demand and load characteristics change due to the influence of distributed energy. At the same time, in the open retail market of electricity sales, the forecast of electricity consumption faces the power demand of small-scale users, which is more easily disturbed by random factors than by a traditional load forecast. Therefore, this study proposes a model based on X12 and Seasonal and Trend decomposition using Loess (STL) decomposition of monthly electricity consumption forecasting methods. The first use of the STL model according to the properties of electricity each month is its power consumption time series decomposition individuation. It influences the factorization of monthly electricity consumption into season, trend, and random components. Then, the change in the characteristics of the three components over time is considered. Finally, the appropriate model is selected to predict the components in the reconfiguration of the monthly electricity consumption forecast. A forecasting program is developed based on R language and MATLAB, and a case study is conducted on the power consumption data of a university campus containing distributed energy. Results show that the proposed method is reasonable and effective.

Creating Structural Analysis Model from IFC-Based Structural Model

2013 ◽  
Vol 712-715 ◽  
pp. 901-904 ◽  
Author(s):  
Xuan Wang ◽  
Zai Peng Cui ◽  
Qi Lin Zhang ◽  
Hui Zhu Yang
Keyword(s):  
Information Exchange ◽  
Structural Model ◽  
Collaborative Work ◽  
Rapid Development ◽  
Building Structures ◽  
Analysis Model ◽  
Information Gap ◽  
Information Transformation ◽  
Complex Building

In recent years, with the rapid development of the complex building structures, the lack of collaborative work platform for the information exchange between different disciplines results in the phenomenon of information gap and information isolated island. Realizing such a demand, a software was developed for supporting information transformation from IFC-format data model to structural model. In this paper, A case study was implemented to illustrate the method of structural model transformation, The results show that the software can extract the information of IFC structural model and form a corresponding structural model.

Identification of Vibration Parameters of Mechanical System Utilizing Low-Cost MEMS Accelerometers

2019 ◽  
Vol 894 ◽  
pp. 1-8
Author(s):  
Khanh Duong Quang ◽  
Huong Vuong Thi ◽  
Anh Luu Van
Keyword(s):  
High Speed ◽  
Low Cost ◽  
Damping Ratio ◽  
Vibration Reduction ◽  
Mechanical Systems ◽  
Micro Electro Mechanical Systems ◽  
Mems Accelerometer ◽  
System Parameters ◽  
Mems Accelerometers ◽  
Vibration Parameters

Multi-axial mechanical systems commonly encounter the problem of vibration while attempting to drive machining systems at high speed. Many effective methods based on feed-forward and feedback control have been proposed and applied for vibration reduction. In order to design controllers all methods require the exact knowledge of system parameters: vibration frequency and damping ratio. In recent years, low-cost Micro Electro Mechanical Systems (MEMS) accelerometers have been used for many applications in industry. This paper presents the advantage of low cost MEMS accelerometer to identify vibration parameters of mechanical systems in comparison to conventional expensive devices.

scholarly journals Multi-Objective Optimization of Massive MIMO 5G Wireless Networks towards Power Consumption, Uplink and Downlink Exposure

2019 ◽  
Vol 9 (22) ◽  
pp. 4974 ◽  
Author(s):  
Michel Matalatala ◽  
Margot Deruyck ◽  
Sergei Shikhantsov ◽  
Emmeric Tanghe ◽  
David Plets ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Electric Field ◽  
Power Consumption ◽  
Massive Mimo ◽  
Rapid Development ◽  
Multiple Input Multiple Output ◽  
Base Stations ◽  
Reference Scenario ◽  
User Coverage ◽  
Input Multiple Output

The rapid development of the number of wireless broadband devices requires that the induced uplink exposure be addressed during the design of the future wireless networks, in addition to the downlink exposure due to the transmission of the base stations. In this paper, the positions and power levels of massive MIMO-LTE (Multiple Input Multiple Output-Long Term Evolution) base stations are optimized towards low power consumption, low downlink and uplink electromagnetic exposure and maximal user coverage. A suburban area in Ghent, Belgium has been considered. The results show that the higher the number of BS antenna elements, the fewer number of BSs the massive MIMO network requires. This leads to a decrease of the downlink exposure (−12% for the electric field and −32% for the downlink dose) and an increase of the uplink exposure (+70% for the uplink dose), whereas both downlink and uplink exposure increase with the number of simultaneous served users (+174% for the electric field and +22% for the uplink SAR). The optimal massive MIMO network presenting the better trade-off between the power consumption, the total dose and the user coverage has been obtained with 37 64-antenna BSs. Moreover, the level of the downlink electromagnetic exposure (electric field) of the massive MIMO network is 5 times lower than the 4G reference scenario.

Analysis and Optimization Design of DRX Mechanism for Power Saving in LTE

2014 ◽  
Vol 556-562 ◽  
pp. 2076-2080
Author(s):  
Xiang Yu ◽  
Yao Song
Keyword(s):  
Power Consumption ◽  
Data Model ◽  
Optimization Design ◽  
Transmission Rate ◽  
Rapid Development ◽  
Power Saving ◽  
Evolution System ◽  
Semi Markov Process ◽  
Discontinuous Reception

With the rapid development of emerging applications and data transmission rate in LTE (Long Term Evolution) system, terminal power consumption is becoming seriously. In LTE, the discontinuous reception (DRX) mechanism was taken as an important method of saving energy of terminal. Through operations of all sorts of timers, a detailed analysis of the principle of DRX is introduced in this paper. And based on this, adjustable DRX long cycle is proposed. On the basis of the DRX semi-Markov process and ETSI data model, formulas of power saving factor and wake-up delay for adjustable LTE DRX are derived. Then from the comparisons of fixed frame DRX cycle and adjustable DRX cycle in terms of power saving and wake-up delay, we know that this optimizing mechanism has obvious improvement in the reduction of terminal power consumption.

scholarly journals Peptimetric: Quantifying and visualizing differences in peptidomic data

2021 ◽  
Author(s):  
Erik Hartman ◽  
Simon Mahdavi ◽  
Sven Kjellstrom ◽  
Artur Schmidtchen
Keyword(s):  
Mass Spectrometry ◽  
Web Application ◽  
Healthy Subjects ◽  
Rapid Development ◽  
Protein Quantification ◽  
Diabetic Patients ◽  
The Novel ◽  
Single Experiment ◽  
Endogenous Peptides ◽  
Multiple Samples

Finding new sustainable means of diagnosing and treating diseases is one of the most pressing issues of our time. In recent years, several endogenous peptides have been found to be both excellent biomarkers for many diseases and to possess important physiological roles which may be utilized in treatments. The detection of peptides has been facilitated by the rapid development of biological mass spectrometry and now the combination of fast and sensitive high resolution MS instruments and stable nano HP-LC equipment sequences thousands of peptides in one single experiment. In most research conducted with these advanced systems, proteolytically cleaved proteins are analyzed and the specific peptides are identified by software dedicated for protein quantification using different proteomics workflows. Analysis of endogenous peptides with peptidomics workflows also benefit from the novel sensitive and advanced instrumentation, however, the generated peptidomic data is vast and subsequently laborious to visualize and examine, creating a bottleneck in the analysis. Therefore, we have created Peptimetric, an application designed to allow researchers to investigate and discover differences between peptidomic samples. Peptimetric allows the user to dynamically and interactively investigate the proteins, peptides, and some general characteristics of multiple samples, and is available as a web application at \url{https://peptimetric.herokuapp.com}. To illustrate the utility of Peptimetric, we've applied it to a peptidomic dataset of 15 urine samples from diabetic patients and corresponding data from healthy subjects.

scholarly journals Penerapan Knowledge Sistem Informasi Penjaminan Mutu Fakultas Berbasis Web Di FTI-UKSW

2021 ◽  
Vol 3 (1) ◽  
pp. 31-44
Author(s):  
William Christopher ◽  
Indrastanti Ratna Widiasari
Keyword(s):  
Information Technology ◽  
Knowledge Management ◽  
Management System ◽  
Web Application ◽  
Rapid Development ◽  
Knowledge Management System ◽  
Data Archiving ◽  
Christian University ◽  
System Life ◽  
Or Organization

Information technology is one of the assets of a company or organization that is important for its development, with the rapid development of technology today, technology must always be updated. One of the roles of information technology is the application of knowledge management. Knowledge Management is a system that is able to improve and manage knowledge information in companies or agencies that apply knowledge management. In this study, it focuses on implementing a knowledge management system in the Quality Assurance of the Faculties at Satya Wacana Christian University. This research is based on the fact that PMF institutions still use manual methods in data archiving, the purpose of this study is to design a web application that is useful for archiving PMF data to make it more effective and efficient. In this study, the KMS (Knowledge Management System) is applied, and uses the Knowledge Management System Life Cycle method which consists of several process stages consisting of infrastructure evaluation, KMS design analysis and development, and evaluation at the final stage. The result of this research is a useful data archiving web application for PMF. It is hoped that PMF will be more efficient in data archiving.

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