Low-Cost, High-Frequency, Data Acquisition System for Condition Monitoring of Rotating Machinery through Vibration Analysis-Case Study

Soto Ocampo, César Ricardo and Mera Sánchez De Pedro, José Manuel and Cano Moreno, Juan David and Garcia Bernardo, José Luis (2020). Low-Cost, High-Frequency, Data Acquisition System for Condition Monitoring of Rotating Machinery through Vibration Analysis-Case Study. "Sensors", v. 20 (n. 12); p. 3493. ISSN 1424-8220. https://doi.org/10.3390/s20123493.

Description

Title: Low-Cost, High-Frequency, Data Acquisition System for Condition Monitoring of Rotating Machinery through Vibration Analysis-Case Study
Author/s:
  • Soto Ocampo, César Ricardo
  • Mera Sánchez De Pedro, José Manuel
  • Cano Moreno, Juan David
  • Garcia Bernardo, José Luis
Item Type: Article
Título de Revista/Publicación: Sensors
Date: 20 June 2020
ISSN: 1424-8220
Volume: 20
Subjects:
Freetext Keywords: data acquisition system; low cost; high sampling rate; Raspberry Pi; vibration test bench; bearing diagnosis; envelope analysis
Faculty: E.T.S.I. Industriales (UPM)
Department: Ingeniería Mecánica
Creative Commons Licenses: Recognition

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Abstract

Data acquisition is a crucial stage in the execution of condition monitoring (CM) of rotating machinery, by means of vibration analysis. However, the major challenge in the execution of this technique lies in the features of the recording equipment (accuracy, resolution, sampling frequency and number of channels) and the cost they represent. The present work proposes a low-cost data acquisition system, based on Raspberry-Pi, with a high sampling frequency capacity in the recording of up to three channels. To demonstrate the effectiveness of the proposed data acquisition system, a case study is presented in which the vibrations registered in a bearing are analyzed for four degrees of failure.

More information

Item ID: 62950
DC Identifier: http://oa.upm.es/62950/
OAI Identifier: oai:oa.upm.es:62950
DOI: 10.3390/s20123493
Official URL: https://doi.org/10.3390/s20123493
Deposited by: MSc Cesar Soto
Deposited on: 20 Jul 2020 10:44
Last Modified: 20 Jul 2020 10:44
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