FPGA-Based Online Induction Motor Multiple-Fault Detection with Fused FFT and Wavelet Analysis

Abstract

Online monitoring of rotary machines, like induction motors, can effectively diagnosis electrical and mechanical faults. The origin of most recurrent faults in rotary machines is in the components: bearings, stator, rotor and others. Different methodologies based on current and vibration monitoring have been proposed using FFT and wavelet analysis for preventive monitoring of induction motors resulting in countless techniques for diagnosing specific faults, arising the necessity for a generalized technique that allows multiple fault detection. This work presents a novel methodology and its FPGA implementation for multiple fault online detection analyzing the current and vibration signals of an induction motor combining FFT and wavelet processing during its startup transient and steady state, precisely performing the identification of different faults like misalignment, unbalance, outerrace bearing defects and broken bars. The results obtained using the proposed methodology show its effectiveness providing a precise diagnosis of the induction motor condition.

Rotating Electrical Machine Condition Monitoring Automation—A Review

“…The literature shows the implementation of intellectual property (IP) cores to enable hardware implementation of diagnostic algorithms [62], but they are not still practical yet. Smart sensor development and low cost continuous monitoring are ongoing research activities: the intended outcome is to offer low-cost, accurate and reliable monitoring sensors [63].…”

Análisis estocástico de señales vibratorias de motores de inducción para la detección de fallas usando descomposición de modo empírico

“…La base de datos es descrita por (Cabal-Yepez, 2009), pertenece a la Universidad de Guanajuato (México) y con ella se hicieron las pruebas en este trabajo usando las señales de vibración correspondientes a las direcciones x y y. En la etapa de preprocesamiento se remuestreó la señal a 150 Hz con un filtrado antialiasing y una normalización en la escala [-1, 1] usando la ecuación (1).…”

Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

“…This type of data acquisition system deals with the parameter related sample values and those samples values are generally collected in a PC through its USB or serial port. The PC software (MATLAB, Lab-VIEW based) performs the required analysis to identify any incipient fault through various techniques out of which current signature analysis (CSA) using FFT [4,5], neural networked CBM [6], multi variable supervision system [7], FPGA with fuzzy logic [8], inter turn fault using wavelet transform [9], Hilbert transform [10] are remarkable. Due to its predictive nature the use of condition monitoring allows maintenance to be scheduled or other action to be taken to prevent failure and avoid its consequences.…”