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Design and fabrication of accelerometer sensor using fused filament fabrication technique

PROGRESS IN ADDITIVE MANUFACTURING 2025年第4期10卷 2473-2486页

作者： Bhandari, Soumya Krishnanand, Soumyendu Roy, Soumyendu Singh, Alok Taufik, Mohammad Maulana Azad Natl Inst Technol Bhopal Ctr Excellence Prod Design & Smart Mfg Bhopal 462003 MP India Maulana Azad Natl Inst Technol Bhopal Dept Mech Engn Bhopal 462003 MP India Bennett Univ Dept Phys Noida 201310 UP India

This research aims to investigate the design and manufacturing possibilities of micro-electro-mechanical devices, specifically accelerometers, utilizing a fused filament fabrication (FFF) system. This study involves the design of a 3D model for an accelerometer sensor, followed by the selection of suitable materials for its fabrication. Polylactic acid (PLA) is chosen for constructing the base structure, while conductive acrylonitrile-butadiene-styrene (ABS) is utilized for the sensing layer. Three distinct sensor models are generated, each featuring different shapes of sensing layers. Subsequently, various combinations of sensor models are subjected to testing using a source measurement unit to maintain constant voltage while measuring current, enabling the calculation of resistance values. The study reveals that both the selection of materials and the design of the sensing layer exert a substantial influence on sensor performance. Through the comparison of various sensor models and configurations, the research endeavors to pinpoint the most effective sensor design, characterized by commendable sensitivity and a streamlined manufacturing process. This study makes a significant contribution to the advancement of micro-electro-mechanical device fabrication through additive manufacturing (AM) or 3D printing by exploring the design and material selection for sensors. Present study offers valuable insights that could pave the way for the development of enhanced sensitivity in sensors with low cost and the optimization of manufacturing processes.

关键词： 3D printing 3D-printed sensor Additive manufacturing accelerometer sensor

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Mobile Voice Health Monitoring Using a Wearable accelerometer sensor and a Smartphone Platform

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2012年第11期59卷 3090-3096页

作者： Mehta, Daryush D. Zanartu, Matias Feng, Shengran W. Cheyne, Harold A., II Hillman, Robert E. Massachusetts Gen Hosp Ctr Laryngeal Surg & Voice Rehabil Boston MA 02114 USA Harvard Univ Sch Med Dept Surg Boston MA 02115 USA Harvard Univ Sch Engn & Appl Sci Cambridge MA 02138 USA Univ Melbourne Dept Otolaryngol Parkville Vic 3010 Australia Univ Tecn Federico Santa Maria Dept Elect Engn Valparaiso 1680 Chile MIT Speech & Hearing Biosci & Technol Program Harvard MIT Div Hlth Sci & Technol Cambridge MA 02139 USA Cornell Univ Ornithol Lab Bioacoust Res Program Ithaca NY 14853 USA Massachusetts Gen Hosp Inst Hlth Profess Boston MA 02114 USA

Many common voice disorders are chronic or recurring conditions that are likely to result from faulty and/or abusive patterns of vocal behavior, referred to generically as vocal hyperfunction. An ongoing goal in clinical voice assessment is the development and use of noninvasively derived measures to quantify and track the daily status of vocal hyperfunction so that the diagnosis and treatment of such behaviorally based voice disorders can be improved. This paper reports on the development of a new, versatile, and cost-effective clinical tool for mobile voice monitoring that acquires the high-bandwidth signal from an accelerometer sensor placed on the neck skin above the collarbone. Using a smartphone as the data acquisition platform, the prototype device provides a user-friendly interface for voice use monitoring, daily sensor calibration, and periodic alert capabilities. Pilot data are reported from three vocally normal speakers and three subjects with voice disorders to demonstrate the potential of the device to yield standard measures of fundamental frequency and sound pressure level and model-based glottal airflow properties. The smartphone-based platform enables future clinical studies for the identification of the best set of measures for differentiating between normal and hyperfunctional patterns of voice use.

关键词： accelerometer sensor vocal hyperfunction voice production model voice use wearable voice sensor

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Automating QA analysis for a six-degree-of-freedom (6DOF) couch using image displacement and an accelerometer sensor

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PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS 2022年第0期101卷 129-136页

作者： Popreeda, Tippawan Masa-nga, Wilia Deeharing, Aphisara Udee, Nuntawat Tannanonta, Chirapha Thongsawad, Sangutid Chulabhorn Royal Acad Princess Srisavangavadhana Coll Med Bangkok Thailand Chulabhorn Hosp Chulabhorn Royal Acad Dept Radiat Oncol Bangkok Thailand Naresuan Univ Fac Allied Hlth Sci Dept Radiol Technol Phitsanulok Thailand 906 Kamphangpech 6 Rd Bangkok 10210 Thailand

The purpose of this study is to develop an approach for automating quality assurance (QA) analysis for a sixdegree-of-freedom (6DOF) couch using image displacement and an accelerometer sensor. A cubic phantom was fabricated using 3D printing and the accelerometer sensor was embedded in the phantom to measure the couch in the pitch and roll directions. The accuracy and reliability of image displacement and the accelerometer sensor were investigated prior to their practical use for 6DOF couch QA. Image displacement performance had an accuracy and reliability of 0.026 +/- 0.026 mm for the translation direction and 0.021 +/- 0.016 degrees for the rotation direction. accelerometer sensor performance had an accuracy and reliability of 0.023 +/- 0.018 degrees for pitch rotation and 0.051 +/- 0.024 degrees for roll rotation. Automating QA analysis was used to perform 6DOF couch QA, and the couch position errors measured using image displacement were less than 0.99 mm, 0.91 mm, 0.82 mm for the vertical, longitudinal, lateral translation in range between +/- 20 mm, and 0.07 degrees, 0.23 degrees, and 0.2 degrees for pitch, roll, and yaw rotation in range between +/- 3 degrees whereas the couch position errors measured using the accelerometer sensor were less than 0.1 degrees and 0.19 degrees for the pitch and roll rotation in range between +/- 3 degrees.

关键词： Automating QA analysis 6DOF couch QA Image displacement accelerometer sensor

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Applied a multi-scale entropy algorithm to analyze dynamic COP signal via accelerometer sensor 13

Applied a multi-scale entropy algorithm to analyze dynamic C...

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13th IEEE Int Conf on Ubiquitous Intelligence and Comp/13th IEEE Int Conf on Adv and Trusted Comp/16th IEEE Int Conf on Scalable Comp and Commun/IEEE Int Conf on Cloud and Big Data Comp/IEEE Int Conf on Internet of People/IEEE Smart World Congress

作者： Lu, Shih-Hui Shieh, Jiann-Shing Hansen, Clint Yuan Ze Univ Ctr Big Data & Digital Convergence Dept Mech Engn & Innovat Chungli 320 Taiwan Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore

ISBN: (纸本)9781509027712

In this study, we use an accelerometer sensor to measure human postural signals during a dynamic task. In previous studies, the step stability index (SSI) has been used to assess human balance via similar sensors. However, the placement of the 3 dimensional sensor differed and placed on the lower back of the subjects. To improve the detection method, we placed the accelerometer on the shoe. The purpose of this research is to compute the SSI and to evaluate whether human balance can be objectively measured with an accelerometer. The results are compared with dynamic centre of pressure (COP) measurements obtained from a force plate that serves as the ground truth. The complexity index (CI) is calculated from dynamic COP to compare with the results of SSI.

关键词： falling noninvasive physiological signs accelerometer sensor multi-scale entropy

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Real-time Distance Awareness Algorithm based on Wireless Signal Strength and accelerometer sensor of Smart Device in an Indoor Environment 5

Real-time Distance Awareness Algorithm based on Wireless Sig...

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5th IEEE International Conference on Consumer Electronics Berlin

作者： Jung, Joon-young Kang, Dong-oh Choi, Jang-ho Bae, Chang-seok Elect & Telecommun Res Inst Human Comp Res Sect Daejeon South Korea

ISBN: (纸本)9781479987481

When mobile devices use the distance between devices in an application, the distance should be measured easily and accurately. The RSSI system can be used to estimate the distance easily and inexpensively because most devices can estimate the received signal strength. However, estimating the distance using a RSSI is difficult due to inaccuracies. Therefore, we propose distance awareness algorithm based on the RSSI and accelerometer sensor suitable for real-time distance estimation in an indoor environment. To evaluate the effectiveness of the proposed algorithm, we tested the distance measurement in an indoor hall environment. The results of this test indicate that the proposed algorithm does not only reduces the inaccuracy of Bluetooth RSSI significantly, but also estimates real-time distance more accurately using an accelerometer sensor.

关键词： Distance awareness Filtering algorithm Wireless signal strength accelerometer sensor

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Vibration feature extraction and analysis of industrial ball mill using MEMS accelerometer sensor and synchronized data analysis technique 2

Vibration feature extraction and analysis of industrial ball...

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2nd International Symposium on Computer Vision and the Internet (VisionNet)

作者： Mohanty, Satish Gupta, Karunesh K. Raju, Kota Solomon BITS Dept EEE Pilani 333031 Rajasthan India CEERI CSIR Digital Syst Grp Pilani 333031 Rajasthan India

The use of advanced technologies such as Micro-electromechanical system (MEMS) sensors and low power wireless communication hold a great promise for optimal performance of industrial wet ball mill The direct translation of the natural phenomena of the batch mill in a lab setup to a continuous process mill in the industry is quite perplexed in the nature of their intent and operating conditions. In this paper, the vibration signatures are analyzed for industrial wet ball mill using a MEMS accelerometer sensor. The signals are acquired using two wireless accelerometer sensors;mounted at feed and discharge end of the ball mill to validate the grinding status of the copper ore. The vibration spectrum before and after feed are compared to estimate the actual grinding status of the ore inside the mill A limiting threshold level for the intensity is identified from the spectral analysis to monitor the desired grinding status of the ore. The high frequency (ZigBee) transmission loss due to diffraction is also compensated by the novel arrangement of the sensor transceiver. Finally, Pearson correlation technique is used to analyze the effect of sample length and its dependency with the rpm of the mill in determining the actual vibration signature. (C) 2015 Published by Elsoviet B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Ball Mill accelerometer sensor ZigBee Vibration Fast Fourier Transform (FFT)

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A Framework for Hand Gesture Recognition based on fusion of Flex, Contact and accelerometer sensor 3

A Framework for Hand Gesture Recognition based on fusion of ...

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3rd International Conference on Image Information Processing (ICIIP)

作者： Pathak, Vishal Mongia, Sushant Chitranshi, Gaurav Amity Univ Amity Sch Engn & Technol ECE Dept Noida Uttar Pradesh India

ISBN: (纸本)9781509001484

This paper presents a framework for hand gesture recognition using information received from Flex, Contact and 3 axis accelerometer sensor. A final decision is made on the basis of matching the sensor values with the already stored values for each sign in the database. Experimental results for 26 American Sign Language Recognition demonstrate the functionality and effectiveness of the framework. An accuracy of 100% is achieved for recognizing the ASL alphabets.

关键词： Sign Language Recognition Microcontroller Flex sensor accelerometer sensor Contact sensor

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Hand Gesture Recognition Using accelerometer sensor for Traffic Light Control System

Hand Gesture Recognition Using Accelerometer Sensor for Traf...

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International Conference on Electronics and Communication Systems (ICECS)

作者： Swapnali, Shirke Chilveri, P. G. SKNCOE ENTC Dept Pune Maharashtra India

ISBN: (纸本)9781479966387

Hand Gesture Recognition is a dynamic area of research. For different application, different gesture recognition techniques are used. In this paper hand gesture recognition is implemented for traffic light control system(TLC). Thresholding Algorithm is used for recognition purpose. The accelerometer sensors are used to sense the gesture of hand Using ARM based control unit. To indicate the traffic light's, LED's are used. XBee, SD card and Speaker are used for as transceiver, storage purpose and important announcement respectively.

关键词： accelerometer sensor ARM Gesture Recognition SD Card Thresolding Algorithm Xbee

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Prototype of sensor Node for Low-Cost Machine Vibration Monitoring System Using accelerometer sensor 9

Prototype of Sensor Node for Low-Cost Machine Vibration Moni...

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9th IEEE International Conference on Communication, Networks and Satellite (IEEE Comnetsat)

作者： Susanto, Misfa Saputra, Rizky Herlinawati Savetlana, Shirley Alam, Syaiful Univ Lampung Dept Elect Engn Bandar Lampung Indonesia Univ Lampung Dept Mech Engn Bandar Lampung Indonesia

ISBN: (纸本)9780738125176

One important aspect in industrial manufacturing processes is the maintenance of machines' conditions. Therefore, monitoring the machine healthiness conditions is a crucial action. The drawback of conventional monitoring method is inefficiencies of the method due to the need to visit every single machine. One parameter for monitoring the machine's healthiness is vibration for the machines that have the motor components. This paper proposes a real-time monitoring system for such vibration monitoring. The proposed system is based on wireless sensor network (WSN). The nodes' prototype of proposed WSN was built and consisted of three nodes i.e. two sensor nodes and one sink node. The main component of the proposed system is Arduino uno which is not expensive relatively. In order to monitor the vibration parameter, the used sensor is the ADXL345 accelerometer sensor. The system design and testing have been carried out. The testing has been done for two aspects;the evaluation of communication performances and the machine vibration field measurements. The parameter for the testing of communication aspect is the data throughput that has been collected for the network performance evaluation. For the testing in real situations, the coffee grinder machine was chosen to be applied for the vibration monitoring system using one sensor and one sink nodes. From the testing results, the system achieved 546 bps of best throughput and was able to measure on the conditions of various supply powers to the machine. It implies the feasibility of the system in monitoring the vibration of the machine.

关键词： Monitoring system wireless sensor node prototype accelerometer sensor industrial machine vibration field testing

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Human Movement Detection Algorithm Using 3-Axis accelerometer sensor Based on Low-Power Management Scheme for Mobile Health Care System

Human Movement Detection Algorithm Using 3-Axis Acceleromete...

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5th International Conference on Grid and Pervasive Computing

作者： Shin, Jaewan Shin, Dongkyoo Shin, Dongil Her, Sungmin Kim, Soohan Lee, Myungsoo Sejong Univ Dept Comp Engn 98 Kunja Dong Seoul 143747 South Korea SevenCore Co Ltd Seocho Dong Seoul 137855 South Korea Sansung Electron Co Ltd Suwon South Korea

ISBN: (纸本)9783642130663

Phone and PDA mobile devices that recognize a user's movements and biometric information that can be utilized in a sensor system have been generating interest among users. This paper proposes a low-power management scheme that uses the baseband processor installed in a portable communications device to limit the electric power consumed by the device, along with a human movement detection algorithm that records and predicts the movement of the mobile user in a low-power mode. In addition, a mobile healthcare system is developed to use the proposed scheme and algorithm. This system uses 3-axis accelerometer sensors on an Android platform and calculates the amount of human movement from the sensor output. The user's uphill, downhill, flat area, climbing stairs, going down stairs, and jogging movements were measured with accuracies of 93.2%, 97.4%, 97.6%, 98.8%, 92.2%, and 90.8%, respectively.

关键词： MEMS Low-Power Management accelerometer sensor Movement Detection Algorithm

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