Vibration Analysis for Engine fault Detection

Angad Gude, Shubham Pawar, Siddharth Alhat, Sashikala Mishra

Abstract


In the Vibration analysis for engine fault detection, we use different visualization graph. Today‘s world growing fast and machinery part getting complex so it’s difficult to find out fault in the machine so here means in this paper we explain how we find out the fault of the machine with help of visualization it’s easy to find out a fault here we use angular.js, D3.js for visualization and use MQTT protocol for publishing and subscribe sensor data. In the automobile industries machines are the main part of how we find out fault yes we find out fault with help of sensors using sensors here we analyze the machine.


Keywords


Sensor; Protocol; Visualization; Fault detection; Graph

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References


Prof. Dr. Sabry Allam, Mohammed Abdo and Dr. M. Rabie,” Diesel Engine Fault Detection Using Vibration and Acoustic Emission Signals”, IJASRE-International Journal of Advances in Scientific Research and Engineering, Volume 4, Issue 12 December – 2018

D. Ding, D. Zhao, X. Zhang, X. Lan, C. Li, and B. Cui, “Investigation of vibration impacts on HVAC transformer from HVDC system under monopole operation,” IEEE Trans. Dielectr. Electr. Insul., vol. 23, no. 3, pp. 1386–1392, 2016.

T. Li, C. Shi, Y. Tan, and Z. Zhou, “Fiber Bragg Grating Sensing-Based Online Torque Detection on Coupled Bending and Torsional Vibration of Rotating Shaft,” IEEE Sens. J., vol. 17, no. 7, pp. 1199–2007, 2017.

Y. Wang et al., “Optical Fiber Vibration Sensor Using Chaotic Laser,” IEEE Photonics Technol. Lett., vol. 29, no. 16, pp. 1336–1339, 2017.

Y. Park, M. Jeong, S. Bin Lee, J. A. Antonino-Daviu, and M. Teska, “Influence of Blade Pass Frequency Vibrations on MCSA-Based Rotor Fault Detection of Induction Motors,” IEEE Trans. Ind. Appl., vol. 53, no. 3, pp. 2049–2058, 2017.

B. Liu, H. Ma, and P. Ju, “Partial discharge diagnosis by simultaneous observation of discharge pulses and vibration signal,” IEEE Trans. Dielectr. Electr. Insul., vol. 24, no. 1, pp. 288–295, 2017.

M. Bentoumi, D. Chikouche, A. Mezache, and H. Bakhti, “Wavelet DT method for water leak-detection using a vibration sensor: An experimental analysis,” IET Signal Process., vol. 11, no. 4, pp. 396–405, 2017.

Y. Wang and J. Pan, “Comparison of Mechanically and Electrically Excited Vibration Frequency Responses of a Small Distribution Transformer,” IEEE Trans. Power Deliv., vol. 32, no. 3, pp. 1173–1180, 2017.

S. Yang, W. Wu, S. Xu, Y. J. Zhang, D. Stutts, and D. J. Pommerenke, “A Passive Intermodulation Source Identification Measurement System Using a Vibration Modulation Method,” IEEE Trans. Electromagn. Compat., vol. 59, no. 6, pp. 1677–1684, 2017.

Santos, R. Santos, M. Silva, E. Figueiredo, C. Sales, and J. C. W. A. Costa, “A Global Expectation-Maximization Approach Based on Memetic Algorithm for Vibration-Based Structural Damage Detection,” IEEE Trans. Instrum. Meas., vol. 66, no. 4, pp. 661–670, 2017.

B.-G. Gu, “Study of IPMSM Interturn Faults Part II: Online Fault Parameter Estimation,” IEEE Trans. Power Electron., vol. 31, no. 10, pp. 7214–7223, Oct. 2016.

Tabbache, M. E. H. Benbouzid, A. Kheloui, and J.-M. Bourgeot, “Virtual-Sensor-Based Maximum-Likelihood Voting Approach for Fault-Tolerant Control of Electric Vehicle Powertrains,” IEEE Trans. Veh. Technol., vol. 62, no. 3, pp. 1075–1083, Mar. 2013.

Elez, S. Car, S. Tvoric, and B. Vaseghi, “Rotor Cage and Winding Fault Detection Based on Machine Differential Magnetic Field Measurement (DMFM),” IEEE Trans. Ind. Appl., vol. 53, no. 3, pp. 3156–3163, May 2017.

Xu, L. Sun, L. Xu, and G. Xu, “Improvement of the Hilbert Method via ESPRIT for Detecting Rotor Fault in Induction Motors at Low Slip,” IEEE Trans. Energy Convers., vol. 28, no. 1, pp. 225–233, Mar. 2013.

H. Liu, J. Huang, Z. Hou, J. Yang, and M. Ye, “Stator inter-turn fault detection in closed-loop controlled drive based on switching sideband harmonics in CMV,” IET Electr. Power Appl., vol. 11, no. 2, pp. 178–186, Feb. 2017.

Soualhi, G. Clerc, and H. Razik, “Detection and Diagnosis of Faults in Induction Motor Using an Improved Artificial Ant Clustering Technique,” IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 4053–4062, Sep. 2013.

R. de Jesus Romero-Troncoso, “Multirate Signal Processing to Improve FFT-Based Analysis for Detecting Faults in Induction Motors,” IEEE Trans. Ind. Informatics, vol. 13, no. 3, pp. 1291–1300, Jun. 2017.

S. Mohanty, K. K. Gupta, and K. S. Raju, “Effect of unitary sample shifted Laplacian and rectangular distributions in bearing fault identifications of induction motor,” IET Sci. Meas. Technol., vol. 11, no. 4, pp. 516–524, Jul. 2017.

Kamal Jafarian, Morteza Darjani, Zahra Honarkar,” Vibration Analysis for Fault Detection of Automobile Engine Using PCA Technique”, 2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA) 27-28 January 2016, Qazvin Islamic Azad University, Qazvin, Iran

Y. Wang, B. Jin, Y. Wang, D. Wang, X. Liu, and Q. Bai, “Real-Time Distributed Vibration Monitoring System Using Phi-OTDR,” IEEE Sens. J., vol. 17, no. 5, pp. 1333–1341, 2017.

Wylomanska, R. Zimroz, J. Janczura, and J. Obuchowski, “Impulsive Noise Cancellation Method for Copper Ore Crusher Vibration Signals Enhancement,” IEEE Trans. Ind. Electron., vol. 63, no. 9, pp. 5612–5621, 2016.

H. Sun, S. Yuan, and Y. Luo, “Cyclic Spectral Analysis of Vibration Signals for Centrifugal Pump Fault Characterization,” IEEE Sens. J., vol. 18, no. 7, pp. 2925–2933, 2018.

T. J. Matarazzo et al., “Crowdsensing Framework for Monitoring Bridge Vibrations Using Moving Smartphones,” Proc. IEEE, vol. 106, no. 4, pp. 577–593, 2018.

L. Song, H. Wang, and P. Chen, “Vibration-Based Intelligent Fault Diagnosis for Roller Bearings in Low-Speed Rotating Machinery,” IEEE Trans. Instrum. Meas., vol. 67, no. 8, pp. 1887–1899, 2018.

J. Wang et al., “An FBG-based 2-D vibration sensor with adjustable sensitivity,” IEEE Sens. J., vol. 17, no. 15, pp. 4716–4724, 2017.

T. Li, C. Shi, Y. Tan, R. Li, Z. Zhou, and H. Ren, “A Diaphragm Type Fiber Bragg Grating Vibration Sensor Based on Transverse Property of Optical Fiber with Temperature Compensation,” IEEE Sens. J., vol. 17, no. 4, pp. 1021–1029, 2017.

V. Maiwald, M. Müller, C. Ritz, C. Hierold, and C. Roman, “Off-resonant vibration amplifier with flattened band-pass characteristic and improved axis selectivity,” J. Microelectromechanical Syst., vol. 26, no. 6, pp. 1345–1355, 2017.J. C. Jauregui, J. R. Resendiz, S. Thenozhi, T. Szalay, A. Jacso, and M. Takacs, “Frequency and Time-Frequency Analysis of Cutting Force and Vibration Signals for Tool Condition Monitoring,” IEEE Access, vol. 6, pp. 6400–6410, 2018.

J. Rivas, R. Wunderlich, and S. J. Heinen, “Road Vibrations as a Source to Detect the Presence and Speed of Vehicles,” IEEE Sens. J., vol. 17, no. 2, pp. 377–385, 2017.

Pal Banlaki, Zoltan Magosi,” Part failure diagnosis for internal combustion engine using noise and vibration analysis”, Transportation Engineering 38/1 (2010) 53–60 doi: 10.3311/pp.tr.2010-1.09

F. R. Salmasi, “A Self-Healing Induction Motor Drive With Model Free Sensor Tampering and Sensor Fault Detection, Isolation, and Compensation,” IEEE Trans. Ind. Electron., vol. 64, no. 8, pp. 6105–6115, Aug. 2017.

Y. C. Soh, S. K. Kommuri, J. J. Rath, M. Defoort, and K. C. Veluvolu, “Decoupled current control and sensor fault detection with second-order sliding mode for induction motor,” IET Control Theory Appl., vol. 9, no. 4, pp. 608–617, Feb. 2015.

M. Manohar and S. Das, “Current Sensor Fault-Tolerant Control for Direct Torque Control of Induction Motor Drive Using Flux-Linkage Observer,” IEEE Trans. Ind. Informatics, vol. 13, no. 6, pp. 2824–2833, Dec. 2017.

Chakraborty and V. Verma, “Speed and Current Sensor Fault Detection and Isolation Technique for Induction Motor Drive Using Axes Transformation,” IEEE Trans. Ind. Electron., vol. 62, no. 3, pp. 1943–1954, Mar. 2015.

Sumit Kumar Sar, Dr. Ramesh Kumar,” Techniques of Vibration Signature Analysis”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 4, Issue 3, March 2015

Priyanka, Neelam Turk, Ratna Dahiya,” Condition monitoring of Induction motors through Simulation of Bearing Fault and Air Gap Eccentricity Fault”, International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-3, September 2019

Amandeep Sharma, S. Chatterji, Lini Mathew, Mohammad Junaid Khan,” A Review of Fault Diagnostic and Monitoring Schemes of Induction Motors”, International Journal for Research in Applied Science & Engineering Technology (IJRASET) Volume 3 Issue IV, April 2015

Tejas K. Rathod, Prof. V.P. Patel,” Research Trends in Fault Detection and Analysis of Three Phase Induction Machine”, International Journal of Science, Engineering and Technology Research (IJSETR) Volume 6, Issue 3, March 2017

Prof. P. C. Latane, Punit C. Urolgin,” Fault Detection in Electric Motors Using Vibration Analysis and DSP Processor”, International Journal of Innovative Research in Science, Engineering and Technology Vol. 5, Issue 6, June 2016




DOI: https://doi.org/10.18196/jrc.2379

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