Acoustic diagnostics of electrical origin fault modes with readily available consumer-grade sensors

被引:8
作者
Grebenik, Jarek [1 ]
Bingham, Chris [1 ]
Srivastava, Saket [1 ]
机构
[1] Univ Lincoln, Sch Engn, Lincoln LN6 7TS, England
关键词
brushless DC motors; wavelet transforms; control engineering computing; power electronics; fault diagnosis; signal denoising; physical component damage; real-time fault diagnostics; unreported acute electrical origin fault; system operation; suitability study; acoustic measurements; readily available consumer-grade sensors; real-time diagnostics; audible faults; optimal wavelet selection methods; empirical mode decomposition processing algorithms; example electrical origin fault; acoustic techniques; electrical origin faults; acoustic diagnostics; electrical origin fault modes; mechanical fault modes; wider range; monitoring applications; BAR DETECTION; DECOMPOSITION; EMISSION; VIBRATION; MOTORS; EXTRACTION; TRANSFORM; MACHINE;
D O I
10.1049/iet-epa.2019.0232
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Acoustic diagnostics, traditionally associated with mechanical fault modes, can potentially solve a wider range of monitoring applications. Typically, fault modes are induced purposefully by the researcher through physical component damage whilst the system is shutdown. This study presents low-cost real-time fault diagnostics of a previously unreported acute electrical origin fault that manifests sporadically during system operation with no triggering intervention. A suitability study into acoustic measurements from readily available consumer-grade sensors for low-cost real-time diagnostics of audible faults, and a brief overview of the theory and configuration of the wavelet packet transform (including optimal wavelet selection methods) and empirical mode decomposition processing algorithms is also included. The example electrical origin fault studied here is an unpredictable current instability arising with the pulse-width modulation controller of a BrushLess DC motor. Experimental trials positively detect 99.9% of the 1160 resultant high-bandwidth torque transients using acoustic measurements from a USB microphone and a smartphone. While the use of acoustic techniques for detecting emerging electrical origin faults remains largely unexplored, the techniques demonstrated here can be readily adopted for the prevention of catastrophic failure of drive and power electronic components.
引用
收藏
页码:1946 / 1953
页数:8
相关论文
共 49 条
[1]   Energy Index technique for detection of Acoustic Emissions associated with incipient bearing failures [J].
Al-Balushi, Khamis R. ;
Addali, A. ;
Charnley, B. ;
Mba, D. .
APPLIED ACOUSTICS, 2010, 71 (09) :812-821
[2]   A comparative experimental study on the use of acoustic emission and vibration analysis for bearing defect identification and estimation of defect size [J].
Al-Ghamd, Abdullah M. ;
Mba, David .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2006, 20 (07) :1537-1571
[3]  
Amarnath M., 2011, IET SCI MEAS TECHNOL, V6, P279
[4]   Comparative Study of Time-Frequency Decomposition Techniques for Fault Detection in Induction Motors Using Vibration Analysis during Startup Transient [J].
Antonio Delgado-Arredondo, Paulo ;
Garcia-Perez, Arturo ;
Morinigo-Sotelo, Daniel ;
Alfredo Osornio-Rios, Roque ;
Gabriel Avina-Cervantes, Juan ;
Rostro-Gonzalez, Horacio ;
de Jesus Romero-Troncoso, Rene .
SHOCK AND VIBRATION, 2015, 2015
[5]   Winding condition monitoring scheme for a permanent magnet machine using high-frequency injection [J].
Arellano-Padilla, J. ;
Sumner, M. ;
Gerada, C. .
IET ELECTRIC POWER APPLICATIONS, 2011, 5 (01) :89-99
[6]   Early fault diagnosis of rotating machinery based on wavelet packets-Empirical mode decomposition feature extraction and neural network [J].
Bin, G. F. ;
Gao, J. J. ;
Li, X. J. ;
Dhillon, B. S. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2012, 27 :696-711
[7]   Broken rotor bar detection via four-band wavelet packet decomposition of motor current [J].
Cekic, Yalcin ;
Eren, Levent .
ELECTRICAL ENGINEERING, 2018, 100 (03) :1957-1962
[8]   Quaternion Signal Analysis Algorithm for Induction Motor Fault Detection [J].
Contreras-Hernandez, Jose L. ;
Almanza-Ojeda, Dora Luz ;
Ledesma-Orozco, Sergio ;
Garcia-Perez, Arturo ;
Romero-Troncoso, Rene J. ;
Ibarra-Manzano, Mario A. .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (11) :8843-8850
[9]  
da Costa C., 2015, CASE STUD MECH SYST, V1, P15, DOI DOI 10.1016/J.CSMSSP.2015.05.001
[10]   The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing [J].
Eftekharnejad, B. ;
Carrasco, M. R. ;
Charnley, B. ;
Mba, D. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2011, 25 (01) :266-284