Induction motor health identification using wavelet transform technique

2018 ◽  
Author(s):  
Rudra Narayan Dash ◽  
Chinmoy Panigrahi ◽  
Bidyadhar Subudhi ◽  
Sarada Prasanna Sahoo
Keyword(s):  
Wavelet Transform ◽  
Induction Motor

Pendeteksian Misalignment Menggunakan Multi Level Transformasi Wavelet Haar dan Coiflet pada Motor Induksi

2020 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
P.P.S Saputra
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Induction Motor ◽  
High Frequency ◽  
High Efficiency ◽  
Vibration Signal ◽  
Normal Operation ◽  
Discrete Wavelet ◽  
High Frequency Signal ◽  
Motor Operation

Currently induction motors are widely used in industry due to strong construction, high efficiency, and cheap maintenance. Machine maintenance is needed to prolong the life of the induction motor. As studied, bearing faults may account for 42% -50% of all motor failures. In general it is due to manufacturing faults, lack of lubrication, and installation errors. Misalignment of motor is one of the installation errors. This paper is concerned to simulation of discrete wavelet transform for identifying misalignment in induction motor. Modelling of motor operation is introduced in this paper as normal operation and two variations of misalignment. For this task, haar and coiflet discrete wavelet transform in first level until fifth level is used to extract vibration signal of motor into high frequency of signal. Then, energy signal and other signal extraction gotten from high frequency signal is evaluated to analysis condition of motor. The results show that haar discrete wavelet transform at thirth level can identify normal motor  and misalignment motor conditions well

Vibration signature analysis for monitoring rotor broken bar in double squirrel cage induction motors based on wavelet analysis

2014 ◽  
Vol 33 (5) ◽  
pp. 1625-1641 ◽  
Author(s):  
Rosario Miceli ◽  
Yasser Gritli ◽  
Antonino Di Tommaso ◽  
Fiorenzo Filippetti ◽  
Claudio Rossi
Keyword(s):  
Wavelet Transform ◽  
Induction Motor ◽  
Vibration Signal ◽  
Operating Conditions ◽  
Single Frequency ◽  
Content Type ◽  
Time Frequency ◽  
Wavelet Transform Analysis ◽  
Cage Induction Motor ◽  
Diagnosis Technique

Purpose – The purpose of this paper is to present a diagnosis technique, for rotor broken bar in double cage induction motor, based on advanced use of wavelet transform analysis. The proposed technique is experimentally validated. Design/methodology/approach – The proposed approach is based on a combined use of frequency sliding and wavelet transform analysis, to isolate the contribution of the rotor fault components issued from vibration signals in a single frequency band. Findings – The proposed technique is reliable for tracking the rotor fault components over time-frequency domain. The quantitative analysis results based on this technique are the proof of its robustness. Research limitations/implications – The validity of the proposed diagnosis approach is not limited to the analysis under steady-state operating conditions, but also for time-varying conditions where rotor fault components are spread in a wide frequency range. Practical implications – The developed approach is best suited for automotive or high power traction systems, in which safe-operating and availability are mandatory. Originality/value – The paper presents a diagnosis technique for rotor broken bar in double cage induction motor base on advanced use of wavelet transform which allows the extraction of the most relevant rotor fault component issued from axial vibration signal and clamping it in a single frequency bandwidth, avoiding confusions with other components and false interpretations.

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