Implementation of envelope analysis on a wireless condition monitoring system for bearing fault diagnosis

Guo-jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Fengshou Gu, Andrew D. Ball

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Envelope analysis is an effective method for characterizing impulsive vibrations in wired condition monitoring (CM) systems. This paper depicts the implementation of envelope analysis on a wireless sensor node for obtaining a more convenient and reliable CM system. To maintain CM performances under the constraints of resources available in the cost effective Zigbee based wireless sensor network (WSN), a low cost cortex-M4F microcontroller is employed as the core processor to implement the envelope analysis algorithm on the sensor node. The on-chip 12 bit analog-to-digital converter (ADC) working at 10 kHz sampling rate is adopted to acquire vibration signals measured by a wide frequency band piezoelectric accelerometer. The data processing flow inside the processor is optimized to satisfy the large memory usage in implementing fast Fourier transform (FFT) and Hilbert transform (HT). Thus, the envelope spectrum can be computed from a data frame of 2048 points to achieve a frequency resolution acceptable for identifying the characteristic frequencies of different bearing faults. Experimental evaluation results show that the embedded envelope analysis algorithm can successfully diagnose the simulated bearing faults and the data transmission throughput can be reduced by at least 95% per frame compared with that of the raw data, allowing a large number of sensor nodes to be deployed in the network for real time monitoring.
LanguageEnglish
Pages14-24
JournalInternational Journal of Automation and Computing
Volume12
Issue number1
DOIs
Publication statusPublished - 2015

Fingerprint

Bearings (structural)
Condition Monitoring
Condition monitoring
Fault Diagnosis
Monitoring System
Sensor nodes
Envelope
Failure analysis
Algorithm Analysis
Zigbee
Digital to analog conversion
Microcontrollers
Accelerometers
Fault
Fast Fourier transforms
Data communication systems
Vertex of a graph
Frequency bands
Costs
Wireless sensor networks

Cite this

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title = "Implementation of envelope analysis on a wireless condition monitoring system for bearing fault diagnosis",
abstract = "Envelope analysis is an effective method for characterizing impulsive vibrations in wired condition monitoring (CM) systems. This paper depicts the implementation of envelope analysis on a wireless sensor node for obtaining a more convenient and reliable CM system. To maintain CM performances under the constraints of resources available in the cost effective Zigbee based wireless sensor network (WSN), a low cost cortex-M4F microcontroller is employed as the core processor to implement the envelope analysis algorithm on the sensor node. The on-chip 12 bit analog-to-digital converter (ADC) working at 10 kHz sampling rate is adopted to acquire vibration signals measured by a wide frequency band piezoelectric accelerometer. The data processing flow inside the processor is optimized to satisfy the large memory usage in implementing fast Fourier transform (FFT) and Hilbert transform (HT). Thus, the envelope spectrum can be computed from a data frame of 2048 points to achieve a frequency resolution acceptable for identifying the characteristic frequencies of different bearing faults. Experimental evaluation results show that the embedded envelope analysis algorithm can successfully diagnose the simulated bearing faults and the data transmission throughput can be reduced by at least 95{\%} per frame compared with that of the raw data, allowing a large number of sensor nodes to be deployed in the network for real time monitoring.",
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Implementation of envelope analysis on a wireless condition monitoring system for bearing fault diagnosis. / Feng, Guo-jin; Gu, James; Zhen, Dong; Aliwan, Mustafa; Gu, Fengshou; Ball, Andrew D.

In: International Journal of Automation and Computing, Vol. 12, No. 1, 2015, p. 14-24.

Research output: Contribution to journalArticle

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