检索结果-内蒙古大学图书馆

A Detection Method for Vortex Precession Frequency Based on MEMS three-axis acceleration sensor

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Xu, Ying Wei, Chuanshun Yuan, Chao Zhang, Yumeng Li, Tao Wan, Bo Cui, Ziqiang Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Proc Measurement & Control Tianjin 300072 Peoples R China China Classificat Soc Beijing 100007 Peoples R China

Swirlmeters are widely used in the wellhead metering of low permeability gas fields in China. However, the swirlmeter's piezoelectric sensor has difficult distinguishing the vortex precession signal from fluid pulsation noise, pipeline mechanical vibration, and other interference. In this article, in order to detect the vortex precession frequency signal effectively and accurately from the interference noises, a signal detection method based on micro-electro-mechanical systems (MEMS) three-axis acceleration sensor was proposed. According to the difference between the force direction of vortex signal and interference signals, a dual-differential technique based on three-axis measurement is proposed to eliminate interference noises. The radiated interference of electromagnetic noise was eliminated by adding a notch circuit and radio frequency interference filter to the measuring circuit. Then, the sensitivity characteristics of vortex precession with different swirl angles were investigated by numerical simulation and the performance of the method was evaluated by experiments. The results of experiments show that the method proposed in this article can improve the sensor's capability of anti-interference and widen the measurement range. Further wet gas experimental results show that the vortex precession frequency signal detected by MEMS-three-axis acceleration sensor (TAAS) does not change its linear output law in spite of the presence of liquid phase. Finally, a correction model of the instrument coefficient of the swirlmeter for wet gas measurement was established. The relative errors of the fitting model are within +/- 2.0%, the mean percentage error (MPE) is 0.17%, and the mean absolute percentage error (MAPE) is 0.81%. The method proposed in this article can improve the ratio of signal to noise of swirlmeter, overcome the influence of interference noise on the precession frequency, and broaden the gas flow measurement range. It realizes the efficient and accurat

关键词： Interference Fluids Frequency measurement Fluid flow Vibrations Pipelines Velocity measurement Anti-interference differential three-axis acceleration sensor vortex precession frequency wet gas

来源：评论

学校读者我要写书评

暂无评论

A New Active RFID Tag Based on three-axis acceleration sensor 5

A New Active RFID Tag Based on Three-axis Acceleration Senso...

引用

5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Qi Xinte Tang Ying Xia Yuanman Xu Jiwei Chengdu Univ Technol Dept Informat Sci & Technol Chengdu Peoples R China

ISBN: (纸本)9781665423144

This paper proposed a new active RFID tag based on three-axis acceleration sensor. This device can not only store ID and other information, but also process the three-axis acceleration data and extract feature information of moving objects. After being analyzing and processing by the NRF24LE1E chip with RF module, the acceleration data collected by the LIS3DH three-axis acceleration sensor in the three-dimensional space can be sent to the related devices though the antenna module to complete the data collection and feature extraction. This new active RFID tag can be used in the falling detection system, especially in large application places such as nursing homes.

关键词： RFID tag three-axis acceleration sensor fall detection

来源：评论

学校读者我要写书评

暂无评论

Fabrication and Characteristics of a SOI three-axis acceleration sensor Based on MEMS Technology

引用

MICROMACHINES 2019年第4期10卷 238-238页

作者： Zhao, Xiaofeng Wang, Ying Wen, Dianzhong Heilongjiang Univ Coll Heilongjiang Prov Key Lab Elect Engn Harbin 150080 Heilongjiang Peoples R China

A silicon-on-insulator (SOI) piezoresistive three-axis acceleration sensor, consisting of four L-shaped beams, two intermediate double beams, two masses, and twelve piezoresistors, was presented in this work. To detect the acceleration vector (a(x), a(y), and a(z)) along three directions, twelve piezoresistors were designed on four L-shaped beams and two intermediate beams to form three detecting Wheatstone bridges. A sensitive element simulation model was built using ANSYS finite element simulation software to investigate the cross-interference of sensitivity for the proposed sensor. Based on that, the sensor chip was fabricated on a SOI wafer by using microelectromechanical system (MEMS) technology and packaged on a printed circuit board (PCB). At room temperature and V-DD = 5.0 V, the sensitivities of the sensor along x-axis, y-axis, and z-axis were 0.255 mV/g, 0.131 mV/g, and 0.404 mV/g, respectively. The experimental results show that the proposed sensor can realize the detection of acceleration along three directions.

关键词： three-axis acceleration sensor MEMS technology sensitivity L-shaped beam

来源：评论

学校读者我要写书评

暂无评论

Improving Fall Classification Accuracy of Multi-Input Models Using three-axis Accelerometer and Heart Rate Variability Data

引用

sensorS 2025年第4期25卷 1180-1180页

作者： Kim, Seunghui Ko, Jae Eun Baek, Seungbin Kim, Daechang Kim, Sungmin Dongguk Univ Dept Regulatory Sci Med Device Seoul 04620 South Korea Dongguk Univ Dept Med Device Business Seoul 04620 South Korea Dongguk Univ Dept Biomed Engn Goyang Si 10326 South Korea

Reduced body movement and weakened musculoskeletal function as a result of aging increase the risk of falls and serious physical injuries requiring medical attention. To solve this problem, a fall prevention algorithm using an acceleration sensor has been developed, and research is being conducted to enable continuous monitoring using a Holter electrocardiograph. In this study, we implemented a multi-input model that can detect and classify movements, including falls, utilizing the baroreflex characteristics of the heart's potential energy changes due to movement, measured with an electrocardiogram with a three-axis acceleration sensor and a Holter electrocardiograph. Patterns were identified from the various movement characteristics of acceleration sensor data using a deep learning model consisting of CNN-LSTM, and heart rate variability (HRV) data were analyzed using a wide learning model to provide additional weight values for fall classification. Finally, a multi-input model using wide and deep learning was proposed to enhance the accuracy of fall classification. The results show that the HRV increased in fall case except in two motion types, while it decreased when standing up from a chair, indicating the application of the baroreflex characteristics reflecting the heart's potential energy. Compared to the classification model using conventional HRV and ACC, a higher accuracy was achieved in the multi-input model using ACC-HRV data, and a precision, recall, and F1 score of 0.91 was measured, indicating improved performance. This is expected to have a positive impact on fall prevention by improving the accuracy of fall classification in the elderly for 15 different movements.

关键词： three-axis acceleration sensor Holter electrocardiograph multi-input model fall classification heart rate variability (HRV)

来源：评论

学校读者我要写书评

暂无评论

Fabrication and Characterization of Monolithic Integrated three-axis acceleration/Pressure/Magnetic Field sensors

引用

MICROMACHINES 2024年第3期15卷 412-412页

作者： Wang, Ying Xiao, Yu Zhao, Xiaofeng Wen, Dianzhong Heilongjiang Univ Coll Heilongjiang Prov Key Lab Elect Engn Harbin 150080 Peoples R China Heilongjiang Univ Heilongjiang Prov Key Lab Micronano Sensit Devices Harbin 150080 Peoples R China

In order to realize the measurement of three-axis acceleration, pressure, and magnetic field, monolithic integrated three-axis acceleration/pressure/magnetic field sensors are proposed in this paper. The proposed sensors were constructed with an acceleration sensor consisting of four L-shaped double beams, two masses, middle double-beams, and twelve piezoresistors, a pressure sensor made of a square silicon membrane, and four piezoresistors, as well as a magnetic field sensor composed of five Hall elements. COMSOL software and TCAD-Atlas software were used to simulate characteristics of integrated sensors, and analyze the working principles of the sensors in measuring acceleration, pressure, and magnetic field. The integrated sensors were fabricated by using micro-electro-mechanical systems (MEMS) technology and packaged by using inner lead bonding technology. When applying a working voltage of 5 V at room temperature, it is possible for the proposed sensors to achieve the acceleration sensitivities of 3.58 mV/g, 2.68 mV/g, and 9.45 mV/g along the x-axis, y-axis, and z-axis (through an amplifying circuit), and the sensitivities towards pressure and magnetic field are 0.28 mV/kPa and 22.44 mV/T, respectively. It is shown that the proposed sensors can measure three-axis acceleration, pressure, and magnetic field.

关键词： monolithic integrated sensors three-axis acceleration sensor pressure sensor magnetic field sensor MEMS technology

来源：评论

学校读者我要写书评

暂无评论

Measurement method of wet gas two-phase flow rate based on the main frequency and the modulus of vector acceleration of swirl flowmeter

引用

MEASUREMENT 2023年 221卷

作者： Xu, Ying Zhang, Yumeng Yuan, Chao Wei, Chuanshun Li, Tao Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Proc Measurement & Control Tianjin 300072 Peoples R China

The swirl flowmeter is widely used in the wellhead measurement of low-permeability gas fields in China. In this study, the MEMS three-axis acceleration sensor (MEMS-TAAS) replaced the traditional piezoelectric sensor to distinguish the frequency signal from the interference noise. Based on the MEMS-TAAS, the vector acceleration signals of swirl flowmeter were acquired and analyzed simultaneously with the precession frequency signals to establish a wet gas two-phase flow measurement model. The method of establishing a liquid volume fraction prediction model based on the vector acceleration modulus parameter was pioneered. Finally, a dual-parameter wet gas measuring method under normal pressure was constructed using an iteration algorithm. The results demonstrate that this model's relative errors are acceptable. This method effectively provides further development thought for swirl flowmeter which can achieve the accurate prediction of two-phase flow using only one swirl meter with a MEMS-TAAS, without the need for other flow meters or differential pressure sensors, especially for the low-liquid-fraction wet gas.

关键词： Differential three-axis acceleration sensor Vortex precession frequency Wet gas Modulus of vector acceleration

来源：评论

学校读者我要写书评

暂无评论

Classification and Visualization of Long-Term Life-monitoring sensor Signals Using Topological Characteristics of Category Maps 18

Classification and Visualization of Long-Term Life-monitorin...

引用

18th International Conference on Control, Automation and Systems (ICCAS)

作者： Iguchi, Kazuya Madokoro, Hirokazu Sato, Kazuhito Nakasho, Kazuhisa Shimoi, Nobuhiro Akita Prefectural Univ Fac Syst Sci & Technol Dept Machine Intelligence & Syst Engn Yurihonjo City Akita 0150055 Japan Yamaguchi Univ Fac Engn Div Informat Sci & Engn Ube Yamaguchi 7558611 Japan

ISBN: (纸本)9788993215151

This paper presents a novel extraction and visualization method of human behavior patterns as life rhythms from sensor signals obtained using our originally developed life-monitoring system. Our method visualizes categorical relations and distribution characteristics on category maps and their tired units. For creating category maps that preserve data topology, we optimized three main parameters: vigilance thresholds, mapping size, and learning iterations. The mapping size related to classification granularity and expression ability must be changed along with analysis of the data length. Experimentally obtained results reveal that the distribution of burst units is spread evenly along with the setting of learning iterations greater than the data size. This characteristic indicates that it is necessary to increase learning iterations when the mapping size is increased. Moreover, we demonstrate characteristics of integration and division of categories for the relation between fired units and category maps with changing of the vigilance parameter.

关键词： life monitoring category maps three-axis acceleration sensor category boundaries and learning iterations

来源：评论

学校读者我要写书评

暂无评论

three-axis acceleration sensor Using Polyurea Films

引用

JAPANESE JOURNAL OF APPLIED PHYSICS 2008年第5期47卷 4044-4047页

作者： Tabaru, Masaya Nakazawa, Marie Nakamura, Kentaro Ueha, Sadayuki Tokyo Inst Technol Precis & Intelligence Lab Yokohama Kanagawa 2268503 Japan

Focusing on the possibilities of polyurea as an acceleration sensor with characteristics such as flexibility, durability against large deformation, good linearity, and capability of deposition in dryprocess and insolubility in organic solvent, we first fabricated a cantilever acceleration sensor and a three-axis acceleration sensor. The output voltage in the large-strain region is measured using a polyurea cantilever sensor attached to a beryllium copper substrate. The results show that output voltages have good linearity for large strains up to 1%. This value is much larger than the breakdown limit of lead zirconate titanate. Second, we fabricated a polyurea three-axis acceleration sensor. The sensor consists of an insulation layer of polyurea on the cross beam substrate of phosphor bronze, a bottom aluminum electrode, a polyurea active layer, and four top aluminum electrodes. The experimental results for harmonic acceleration show that the sensor works as expected. The cross-axis sensitivity of the polyurea sensor was less than 8%, which is close to that of conventional microelectromechanical system sensors. [DOI: 10.1143/JJAP.47.4044]

关键词： piezoelectric polymer polyurea vapor deposition polymerization large strain acceleration sensor three-axis acceleration sensor cross-axis sensitivity

来源：评论

学校读者我要写书评

暂无评论

Design of Elderly Tumble Detection System Based on Fuzzy Algorithm

Design of Elderly Tumble Detection System Based on Fuzzy Alg...

引用

6th International Symposium on Computational Intelligence and Design (ISCID)

作者： Wang, Ping Zhang, Yangyang Hong, Yang Dong, Lei Chongqing Univ Posts & Telecommun Minist Educ Key Lab Network Control & Intelligent Instrument Chongqing Peoples R China

ISBN: (纸本)9780769550794

The design is based on fuzzy control algorithm, which is an elderly tumble detection system using three-axis acceleration sensor as the detector of the elderly tumble detection condition. Based on human acceleration measured by the three-axis acceleration sensor, and the posture change when the aging fell, and acceleration and angle that followed as the foundation, the adaptive neural network is adopted as a membership function to fuzzy correct the threshold of acceleration SVM that have judged. And then we can have a good solution to the judgment of non-qualitative standard problem concerning the tumble, improving the accuracy and reliability of the monitoring. This system mainly includes six modules: the core control module, three axis acceleration sensor module, GPS module, a wireless communication module, alarm module and key input module, and can achieve the function of tumble detection, positioning and remote wireless alarm.

关键词： tumble detection Adaptive fuzzy neural network three-axis acceleration sensor

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：