A novel method for autonomous remote condition monitoring of rotating machines using piezoelectric energy harvesting approach

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15 Citations (Scopus)

Abstract

This paper presents a novel autonomous method for condition monitoring of rotating machines during operation based on radio frequency (RF) pulse transmission using energy harvesting from operational vibration. An energy harvesting unit is designed to generate and rectify the energy harvested from the machine vibration using Voltage Multiplier (VM) circuit and to store the energy into a capacitor. Then, this energy harvesting unit runs a smart system consisting of a microcontroller and the RF transmitter designed to send a pulse at specific capacitor voltage. A pulse-based condition monitoring approach is introduced which monitors the state of the machine during the operation. In order to estimate power output of the piezoelectric harvester for a realistic vibration signal, the Fourier Transform concept for signal decomposition is incorporated into the well-known electromechanical distributed parameter model. Using experimental data, performance of this autonomous condition monitoring system is tested for a water pump at different conditions. To do so, acceleration data from a centrifugal water pump are acquired with an accelerometer, which then decomposed into a series of harmonics using Fast Fourier Transform. Then using analytical distribute model, a bimorph energy harvester with two Piezoceramic layers is optimized to generate maximum power from the water pump vibration. Consequently, the condition monitoring of the water pump is performed using the presented pulse-based approach. Results of this study show that, the fault diagnosis can be performed autonomously by applying the pulse-based method presented in this work, and by using the piezoelectric harvesting device as an energy source.
Original languageEnglish
JournalSensors and Actuators A: Physical
Volume295
Pages (from-to)37-50
Number of pages14
ISSN0924-4247
DOIs
Publication statusPublished - 15 Aug 2019

Keywords

  • Condition Monitoring
  • Autonomous System
  • Piezoelectirc Harvesting
  • Power Management
  • Fault diagnosis
  • Water Pump

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