Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis

Guo-Jin Feng James Gu Dong Zhen Mustafa Aliwan Feng-Shou Gu Andrew D. Ball

Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu, Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2015, 12(1): 14-24. doi: 10.1007/s11633-014-0862-x
引用本文: Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu, Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2015, 12(1): 14-24. doi: 10.1007/s11633-014-0862-x
Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu and Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis. International Journal of Automation and Computing, vol. 12, no. 1, pp. 14-24, 2015 doi:  10.1007/s11633-014-0862-x
Citation: Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu and Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis. International Journal of Automation and Computing, vol. 12, no. 1, pp. 14-24, 2015 doi:  10.1007/s11633-014-0862-x

Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis

doi: 10.1007/s11633-014-0862-x
详细信息
    作者简介:

    Guo-Jin Feng received the B. Sc. degree in electronic and information engineering, andM. Sc. degree in automatic devices from Shandong University of Science and Technology, China in 2009 and 2012, respectively. He is currently a Ph. D. candidate in the field of industrial machine condition motoring and fault diagnosis, University of Huddersfield, UK. His research interests include wireless condition monitoring, real-time signal processing and wireless sensor network. E-mail: u1273230@hud.ac.uk ORCID iD: 0000-0001-9937-910X

Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis

  • 摘要: 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.
  • [1] C. W. de Silva. Vibration Monitoring, Testing, and Instrumentation, Boca Raton, FL, USA: CRC Press, 2007.
    [2] L. Q. Hou, N. W. Bergmann. Novel industrial wireless sensor networks for machine condition monitoring and fault diagnosis. IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 10, pp. 2787-2798, 2012.
    [3] B. Cai, X. C. Jin, S. M. Yao, J. X. Yang, X. B. Zhao, G. W. Zou. Application research on temperature WSN nodes in switchgear assemblies based on TinyOS and ZigBee. In Proceedings of the 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, IEEE, Weihai, China, pp. 535-538, 2011.
    [4] B. Lu, L.Wu, T. G. Habetler, R.G. Harley, J. A. Gutiérrez. On the application of wireless sensor networks in condition monitoring and energy usage evaluation for electric machines. In Proceedings of the 31st Annual Conference of IEEE Industrial Electronics Society, IEEE, Raleigh, NC, USA, pp. 2674-2679, 2005.
    [5] V. C. Gungor, G. P. Hancke. Industrial wireless sensor networks: Challenges, design principles, and technical approaches. IEEE Transactions on Industrial Electronics, vol. 56, no. 10, pp. 4258-4265, 2009.
    [6] L. Q. Hou, N. W. Bergmann. System requirements for industrial wireless sensor networks. In Proceedings of the 2010 IEEE Conference on Emerging Technologies and Factory Automation, IEEE, Bilbao, Spain, pp. 1-8, 2010.
    [7] P. J. Tavner. Review of condition monitoring of rotating electrical machines. IET Electric Power Applications, vol.2, no. 4, pp. 215-247, 2008.
    [8] L. Nachman, J. Huang, J. Shahabdeen, R. Adler, R. Kling. IMOTE2: Serious computation at the edge. In Wireless Communications and Mobile Computing Conference, IEEE, Crete Island, Greece, pp. 1118-1123, 2008.
    [9] J. P. Lynch. An overview of wireless structural health monitoring for civil structures. Philosophical Transactions of The Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 365, no. 1851, pp. 345-372, 2007.
    [10] J. M. Gilbert, F. Balouchi. Comparison of energy harvesting systems for wireless sensor networks. International Journal of Automation and Computing, vol. 5, no. 4, pp. 334-347, 2008.
    [11] Echo®Wireless Vibration Monitoring System, [Online], Available: https://www.imi-sensors.com/ Echo Wireless.aspx, August 11, 2013.
    [12] S. A. McInerny, Y. Dai. Basic vibration signal processing for bearing fault detection. IEEE Transactions on Education, vol. 46, no. 1, pp. 149-156, 2003.
    [13] N. Tandon, A. Choudhury. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International, vol. 32, no. 8, pp. 469-480, 1999.
    [14] G. Feng, A. Mustafa, J. X. Gu, D. Zhen, F. Gu, A. D. Ball. The real-time implementation of envelope analysis for bearing fault diagnosis based on wireless sensor network. In Proceedings of the 19th International Conference on Automation and Computing, IEEE, London, UK, pp. 1-6, 2013.
    [15] S. Holm. FFT pruning applied to time domain interpolation and peak localization. IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 35, no. 12, pp. 1776-1778, 1987.
    [16] L. S. Xu, Y. Wang, Y. P. Yao, C. Feng, Y. Zhao, M. Q. H. Meng. Comparison of six envelope extraction methods based on abnormal heart sounds. In Proceedings of the 2010 3rd International Conference on Biomedical Engineering and Informatics, IEEE, Yantai, China, vol. 2, pp. 813-817, 2010.
    [17] F. J. Harris. On the use of windows for harmonic analysis with the discrete Fourier transform. Proceedings of the IEEE, vol. 66, no. 1, pp. 51-83, 1978.
    [18] X. Liu, H. P. Chen, M. L. Wang, S. S. Chen. An XBee-Pro based energy monitoring system. In Proceedings of the 2012 Australasian Telecommunication Networks and Applications Conference, IEEE, Brisbane, QLD, Australia, pp. 1-6, 2012.
    [19] V. P. Raj, K. Natarajan, T. G. Girikumar. Induction motor fault detection and diagnosis by vibration analysis using MEMS accelerometer. In Proceedings of the 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications, IEEE, Bangalore, India, pp. 1-6, 2013.
    [20] R. B. Randall, J. Antoni. Rolling element bearing diagnostics — A tutorial. Mechanical Systems and Signal Processing, vol. 25, no. 2, pp. 485-520, 2011.
    [21] C. Zinner, W. Kubinger. ROS-DMA: A DMA double buffering method for embedded image processing with resource optimized slicing. In Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium, IEEE, San Jose, CA, USA, pp. 361-372, 2006
  • [1] Zhao-Hua Liu, Xu-Dong Meng, Hua-Liang Wei, Liang Chen, Bi-Liang Lu, Zhen-Heng Wang, Lei Chen.  A Regularized LSTM Method for Predicting Remaining Useful Life of Rolling Bearings . International Journal of Automation and Computing, 2021, (): 1-13. doi: 10.1007/s11633-020-1276-6
    [2] Hai-Rong Fang, Tong Zhu, Hai-Qiang Zhang, Hui Yang, Bing-Shan Jiang.  Design and Analysis of a Novel Hybrid Processing Robot Mechanism . International Journal of Automation and Computing, 2020, 17(3): 403-416. doi: 10.1007/s11633-020-1228-1
    [3] Erphan A. Bhuiyan, Md. Maeenul Azad Akhand, Sajal K. Das, Md. F. Ali, Z. Tasneem, Md. R. Islam, D. K. Saha, Faisal R. Badal, Md. H. Ahamed, S. I. Moyeen.  A Survey on Fault Diagnosis and Fault Tolerant Methodologies for Permanent Magnet Synchronous Machines . International Journal of Automation and Computing, 2020, 17(6): 763-787. doi: 10.1007/s11633-020-1250-3
    [4] Ruo-Mu Tan, Yi Cao.  Multi-layer Contribution Propagation Analysis for Fault Diagnosis . International Journal of Automation and Computing, 2019, 16(1): 40-51. doi: 10.1007/s11633-018-1142-y
    [5] Ann Smith, Fengshou Gu, Andrew D. Ball.  An Approach to Reducing Input Parameter Volume for Fault Classifiers . International Journal of Automation and Computing, 2019, 16(2): 199-212. doi: 10.1007/s11633-018-1162-7
    [6] Xiao-Hong Qiu, Yu-Ting Hu, Bo Li.  Sequential Fault Diagnosis Using an Inertial Velocity Difierential Evolution Algorithm . International Journal of Automation and Computing, 2019, 16(3): 389-397. doi: 10.1007/s11633-016-1008-0
    [7] Yu Zhang, Chris Bingham, Mike Garlick, Michael Gallimore.  Applied Fault Detection and Diagnosis for Industrial Gas Turbine Systems . International Journal of Automation and Computing, 2017, 14(4): 463-473. doi: 10.1007/s11633-016-0967-5
    [8] Chun-Ling Dong, Qin Zhang, Shi-Chao Geng.  A Modeling and Probabilistic Reasoning Method of Dynamic Uncertain Causality Graph for Industrial Fault Diagnosis . International Journal of Automation and Computing, 2014, 11(3): 288-298. doi: 10.1007/s11633-014-0791-8
    [9] Qi Wang,  Zhong-Wei Ren,  Zhong-Feng Guo.  XML-based Data Processing in Network Supported Collaborative Design . International Journal of Automation and Computing, 2010, 7(3): 330-335. doi: 10.1007/s11633-010-0511-y
    [10] Mou Chen,  Chang-Sheng Jiang,  Qing-Xian Wu.  Sensor Fault Diagnosis for a Class of Time Delay Uncertain Nonlinear Systems Using Neural Network . International Journal of Automation and Computing, 2008, 5(4): 401-405. doi: 10.1007/s11633-008-0401-8
    [11] Mohamed-Faouzi Harkat,  Salah Djelel,  Noureddine Doghmane,  Mohamed Benouaret.  Sensor Fault Detection, Isolation and Reconstruction Using Nonlinear Principal Component Analysis . International Journal of Automation and Computing, 2007, 4(2): 149-155. doi: 10.1007/s11633-007-0149-6
    [12] Marcello Bonfè, Paolo Castaldi, Walter Geri, Silvio Simani.  Design and Performance Evaluation of Residual Generators for the FDI of an Aircraft . International Journal of Automation and Computing, 2007, 4(2): 156-163. doi: 10.1007/s11633-007-0156-7
    [13] Sing Kiong Nguang, Ping Zhang, Steven X. Ding.  Parity Relation Based Fault Estimation for Nonlinear Systems: An LMI Approach . International Journal of Automation and Computing, 2007, 4(2): 164-168. doi: 10.1007/s11633-007-0164-7
    [14] Marek Kowal,  Józef Korbicz.  Fault Detection under Fuzzy Model Uncertainty . International Journal of Automation and Computing, 2007, 4(2): 117-124. doi: 10.1007/s11633-007-0117-1
    [15] Jochen Aβfalg, Frank Allgöwer.  Fault Diagnosis of Nonlinear Systems Using Structured Augmented State Models . International Journal of Automation and Computing, 2007, 4(2): 141-148. doi: 10.1007/s11633-007-0141-1
    [16] Erfu Yang, Hongjun Xiang, Dongbing Gu, Zhenpeng Zhang.  A Comparative Study of Genetic Algorithm Parameters for the Inverse Problem-based Fault Diagnosis of Liquid Rocket Propulsion Systems . International Journal of Automation and Computing, 2007, 4(3): 255-261. doi: 10.1007/s11633-007-0255-5
    [17] Wei-Hua Gui,  Chun-Hua Yang,  Jing Teng.  Intelligent Fault Diagnosis in Lead-zinc Smelting Process . International Journal of Automation and Computing, 2007, 4(2): 135-140. doi: 10.1007/s11633-007-0135-z
    [18] Ling-Lai Li,  Dong-Hua Zhou,  Ling Wang.  Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm . International Journal of Automation and Computing, 2007, 4(2): 183-188. doi: 10.1007/s11633-007-0183-4
    [19] S. Prabhudeva,  A. K. Verma.  Coverage Modeling and Reliability Analysis Using Multi-state Function . International Journal of Automation and Computing, 2007, 4(4): 380-387. doi: 10.1007/s11633-007-0380-1
    [20] You-Qing Wang, Dong-Hua Zhou, Li-Heng Liu.  Robust and Active Fault-tolerant Control for a Class of Nonlinear Uncertain Systems . International Journal of Automation and Computing, 2006, 3(3): 309-313. doi: 10.1007/s11633-006-0309-0
  • 加载中
计量
  • 文章访问数:  5070
  • HTML全文浏览量:  41
  • PDF下载量:  2154
  • 被引次数: 0
出版历程
  • 收稿日期:  2014-01-01
  • 修回日期:  2014-09-24

Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis

doi: 10.1007/s11633-014-0862-x
    作者简介:

    Guo-Jin Feng received the B. Sc. degree in electronic and information engineering, andM. Sc. degree in automatic devices from Shandong University of Science and Technology, China in 2009 and 2012, respectively. He is currently a Ph. D. candidate in the field of industrial machine condition motoring and fault diagnosis, University of Huddersfield, UK. His research interests include wireless condition monitoring, real-time signal processing and wireless sensor network. E-mail: u1273230@hud.ac.uk ORCID iD: 0000-0001-9937-910X

摘要: 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.

English Abstract

Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu, Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2015, 12(1): 14-24. doi: 10.1007/s11633-014-0862-x
引用本文: Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu, Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2015, 12(1): 14-24. doi: 10.1007/s11633-014-0862-x
Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu and Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis. International Journal of Automation and Computing, vol. 12, no. 1, pp. 14-24, 2015 doi:  10.1007/s11633-014-0862-x
Citation: Guo-Jin Feng, James Gu, Dong Zhen, Mustafa Aliwan, Feng-Shou Gu and Andrew D. Ball. Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis. International Journal of Automation and Computing, vol. 12, no. 1, pp. 14-24, 2015 doi:  10.1007/s11633-014-0862-x
参考文献 (21)

目录

    /

    返回文章
    返回