{"title":"Exploring the potential of smartphone MEMS sensors for cost-effective rotating machinery speed estimation","authors":"Anuj Kumar Goel, V.N.A. Naikan","doi":"10.1108/sr-11-2023-0584","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>The purpose of this study is to explore the use of smartphone-embedded microelectro-mechanical sensors (MEMS) for accurately estimating rotating machinery speed, crucial for various condition monitoring tasks. Rotating machinery (RM) serves a crucial role in diverse applications, necessitating accurate speed estimation essential for condition monitoring (CM) tasks such as vibration analysis, efficiency evaluation and predictive assessment.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>This research explores the utilization of MEMS embedded in smartphones to economically estimate RM speed. A series of experiments were conducted across three test setups, comparing smartphone-based speed estimation to traditional methods. Rigorous testing spanned various dimensions, including scenarios of limited data availability, diverse speed applications and different smartphone placements on RM surfaces.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The methodology demonstrated exceptional performance across low and high-speed contexts. Smartphones-MEMS accurately estimated speed regardless of their placement on surfaces like metal and fiber, presenting promising outcomes with a mere 6 RPM maximum error. Statistical analysis, using a two-sample <em>t-</em>test, compared smartphone-derived speed outcomes with those from a tachometer and high-quality (HQ) data acquisition system.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>The research limitations include the need for further investigation into smartphone sensor calibration and accuracy in extremely high-speed scenarios. Future research could focus on refining these aspects.</p><!--/ Abstract__block -->\n<h3>Social implications</h3>\n<p>The societal impact is substantial, offering cost-effective CM across various industries and encouraging further exploration of MEMS-based vibration monitoring.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This research showcases an innovative approach using smartphone-embedded MEMS for RM speed estimation. The study’s multidimensional testing highlights its originality in addressing scenarios with limited data and varied speed applications.</p><!--/ Abstract__block -->","PeriodicalId":49540,"journal":{"name":"Sensor Review","volume":"234 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensor Review","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1108/sr-11-2023-0584","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
The purpose of this study is to explore the use of smartphone-embedded microelectro-mechanical sensors (MEMS) for accurately estimating rotating machinery speed, crucial for various condition monitoring tasks. Rotating machinery (RM) serves a crucial role in diverse applications, necessitating accurate speed estimation essential for condition monitoring (CM) tasks such as vibration analysis, efficiency evaluation and predictive assessment.
Design/methodology/approach
This research explores the utilization of MEMS embedded in smartphones to economically estimate RM speed. A series of experiments were conducted across three test setups, comparing smartphone-based speed estimation to traditional methods. Rigorous testing spanned various dimensions, including scenarios of limited data availability, diverse speed applications and different smartphone placements on RM surfaces.
Findings
The methodology demonstrated exceptional performance across low and high-speed contexts. Smartphones-MEMS accurately estimated speed regardless of their placement on surfaces like metal and fiber, presenting promising outcomes with a mere 6 RPM maximum error. Statistical analysis, using a two-sample t-test, compared smartphone-derived speed outcomes with those from a tachometer and high-quality (HQ) data acquisition system.
Research limitations/implications
The research limitations include the need for further investigation into smartphone sensor calibration and accuracy in extremely high-speed scenarios. Future research could focus on refining these aspects.
Social implications
The societal impact is substantial, offering cost-effective CM across various industries and encouraging further exploration of MEMS-based vibration monitoring.
Originality/value
This research showcases an innovative approach using smartphone-embedded MEMS for RM speed estimation. The study’s multidimensional testing highlights its originality in addressing scenarios with limited data and varied speed applications.
期刊介绍:
Sensor Review publishes peer reviewed state-of-the-art articles and specially commissioned technology reviews. Each issue of this multidisciplinary journal includes high quality original content covering all aspects of sensors and their applications, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of high technology sensor developments.
Emphasis is placed on detailed independent regular and review articles identifying the full range of sensors currently available for specific applications, as well as highlighting those areas of technology showing great potential for the future. The journal encourages authors to consider the practical and social implications of their articles.
All articles undergo a rigorous double-blind peer review process which involves an initial assessment of suitability of an article for the journal followed by sending it to, at least two reviewers in the field if deemed suitable.
Sensor Review’s coverage includes, but is not restricted to:
Mechanical sensors – position, displacement, proximity, velocity, acceleration, vibration, force, torque, pressure, and flow sensors
Electric and magnetic sensors – resistance, inductive, capacitive, piezoelectric, eddy-current, electromagnetic, photoelectric, and thermoelectric sensors
Temperature sensors, infrared sensors, humidity sensors
Optical, electro-optical and fibre-optic sensors and systems, photonic sensors
Biosensors, wearable and implantable sensors and systems, immunosensors
Gas and chemical sensors and systems, polymer sensors
Acoustic and ultrasonic sensors
Haptic sensors and devices
Smart and intelligent sensors and systems
Nanosensors, NEMS, MEMS, and BioMEMS
Quantum sensors
Sensor systems: sensor data fusion, signals, processing and interfacing, signal conditioning.