Comparative Experimental Investigation of Broken Bar Fault Detectability in Induction Motors

[EN] It has been shown in the past that the zero-sequence current spectrum can be reliably used to detect broken bar faults in induction motors. Previous work was carried out with extensive FEM analysis. Although it allows detailed study of spatial and time-dependent electromagnetic characteristics of induction motors, FEM is a heavily time-consuming tool and this limits full study. So, in this work, extensive experimental testing has been performed to validate the zero sequence current spectrum for detecting rotor asymmetries. Three identical induction motors have been used: one healthy, one with a broken rotor bar, and one with two broken rotor bars. The motors were tested under different voltage supply levels and with different mechanical loads. The zero-sequence current spectrum was calculated after measuring the three phase currents. It is for the first time experimentally shown that this approach offers greater diagnostic potential than traditional MCSA.This work was supported in part by the U.K. Engineering and Physical Sciences Research Council funded FUTURE Vehicles project (EP/I038586/1).Gyftakis, KN.; Antonino-Daviu, J.; Garcia-Hernandez, R.; Mcculloch, MD.; Howey, DA.; Marques Cardoso, AJ. (2016). Comparative Experimental Investigation of Broken Bar Fault Detectability in Induction Motors. IEEE Transactions on Industry Applications. 52(2):1452-1459. doi:10.1109/TIA.2015.2505663S1452145952

Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods

"(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works"[EN] Induction motors are used in a variety of industrial applications where frequent startup cycles are required. In those cases, it is necessary to apply sophisticated signal processing analysis methods in order to reliably follow the time evolution of fault-related harmonics in the signal. In this paper, the zero-sequence current (ZSC) is analyzed using the high-resolution spectral method of multiple signal classification. The analysis of the ZSC signal has proved to have several advantages over the analysis of a single-phase current waveform. The method is validated through simulation and experimental results. The simulations are carried out for a 1.1-MW and a 4-kW induction motors under finite element analysis. Experimentation is performed on a healthy motor, a motor with one broken rotor bar, and a motor with two broken rotor bars. The analysis results are satisfactory since the proposed methodology reliably detects the broken rotor bar fault and its severity, both during transient and steady-state operation of the induction motor.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and in part by the FEDER program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P.Morinigo-Sotelo, D.; Romero-Troncoso, R.; Panagiotou, P.; Antonino-Daviu, J.; Gyftakis, KN. (2018). Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods. IEEE Transactions on Industry Applications. 54(2):1224-1234. https://doi.org/10.1109/TIA.2017.2764846S1224123454

Detection of nonadjacent rotor faults in induction motors via spectral subtraction and autocorrelation of stray flux signals

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] In this paper, statistical signal processing techniques are applied to electromotive force signals captured in external coil sensors for adjacent and nonadjacent broken bars detection in induction motors. An algorithm based on spectral subtraction analysis is applied for broken bar identification, independent of the relative position of the bar breakages. Moreover, power spectrum analyses enable the discrimination between healthy and faulty conditions. The results obtained with experimental data prove that the proposed approach provides good results for fault detectability. Moreover, the identification of the faults, and the signal correlation indicator to prove the results are also presented for different positions of the flux sensor.This work was supported in part by MEC under Project MTM 2016-7963-P and in part by the Spanish 'Ministerio de Ciencia Innovacion y Universidades' and FEDER program in the framework of the 'Proyectos de I+D de Generacion de Conocimiento del Programa Estatal de Generacion de Conocimiento y Fortalecimiento Cientifico y Tecnologico del Sistema de I+D+i, Subprograma Estatal de Generacion de Conocimiento' (ref: PGC2018-095747-B-I00).Iglesias-Martínez, ME.; Fernández De Córdoba, P.; Antonino Daviu, JA.; Conejero, JA. (2019). Detection of nonadjacent rotor faults in induction motors via spectral subtraction and autocorrelation of stray flux signals. IEEE Transactions on Industry Applications. 55(5):4585-4594. https://doi.org/10.1109/TIA.2019.2917861S4585459455

An Empirical Mode Decomposition Approach for Multiple Broken Rotor Bars Detection in Three-Phase Induction Motors at No-Load Condition

This paper presents an empirical mode decomposition (EMD) approach for multiple broken rotor bars detection in squirrel cage induction motors running at no-load condition, using the resultant magnetic flux density measured by a Hall Effect sensor installed between two stator slots of the electrical machine. Usually, the traditional motor current signature analysis (MCSA) has produced many cases of false indications related to, among other reasons, incorrect speed estimation, operation at low load (low slip) and nonadjacent broken bars. This study has investigated the application of the EMD technique in the signal collected from the Hall sensor, in order to detect broken rotor bars for an induction motor running at very low slip and subjected to adjacent and nonadjacent broken bars. The present approach has been validated from some experiments carried out by a 7.5 kW induction motor fed by a sinusoidal power supply in the laboratory

A New Approach for Broken Rotor Bar Detection in Induction Motors Using Frequency Extraction in Stray Flux Signals

This paper offers a reliable solution to the detection of broken rotor bars in induction machines with a novel methodology, which is based on the fact that the fault-related harmonics will have oscillating amplitudes due to the speed ripple effect. The method consists of two main steps: Initially, a time-frequency transformation is used and the focus is given on the steady-state regime; thereupon, the fault-related frequencies are handled as periodical signals over time and the classical fast Fourier transform is used for the evaluation of their own spectral content. This leads to the discrimination of subcomponents related to the fault and to the evaluation of their amplitudes. The versatility of the proposed method relies on the fact that it reveals the aforementioned signatures to detect the fault, regardless of the spatial location of the broken rotor bars. Extensive finite element simulations on a 1.1 MW induction motor and experimental testing on a 1.1 kW induction motor lead to the conclusion that the method can be generalized on any type of induction motor independently from the size, power, number of poles, and rotor slot numbers