Abstract
Induction machines drive many industrial processes and their unexpected failure can cause heavy production losses. The analysis of the current spectrum can identify online the characteristic fault signatures at an early stage, avoiding unexpected breakdowns. Nevertheless, frequency domain analysis requires stable working conditions, which is not the case for wind generators, motors driving varying loads, and so forth. In these cases, an analysis in the time-frequency domain—such as a spectrogram—is required for detecting faults signatures. The spectrogram is built using the short time Fourier transform, but its resolution depends critically on the time window used to generate it—short windows provide good time resolution but poor frequency resolution, just the opposite than long windows. Therefore, the window must be adapted at each time to the shape of the expected fault harmonics, by highly skilled maintenance personnel. In this paper this problem is solved with the design of a new multi-band window, which generates simultaneously many different narrow-band current spectrograms and combines them into as single, high resolution one, without the need of manual adjustments. The proposed method is validated with the diagnosis of bar breakages during the start-up of a commercial induction motor.
Highlights
Induction machines (IMs) are a key component of many industrial processes, either as motors or as generators, such as double fed induction generators (DFIGs) used for wind energy generation.Their reliability ensures the continuity of the production processes but they are subjected to eventual failures, which may cause unexpected breakdowns and high economic losses
Diverse quantities have been proposed in the technical literature for implementing condition based maintenance systems (CBMS) [1,2], such as the analysis of the stator currents [3,4,5,6,7], machine vibrations [8,9,10], fluxes [11,12], thermal images [13] or acoustic signals [14,15]
A diagnostic technique that has gained a widespread interest in recent years is the motor current signature analysis (MCSA) [23,24,25,26], which is based on the detection of the characteristic fault signatures that each type of fault impresses in the current spectrum
Summary
Induction machines (IMs) are a key component of many industrial processes, either as motors or as generators, such as double fed induction generators (DFIGs) used for wind energy generation. The use of the current spectrum as signal processing tool in MCSA limits its field of application to machines working in stationary conditions, which is not the case of industrial processes with varying load or speed conditions, or of wind generators operating under variable wind regimes Instead of running a separate STFT for each of the windows used in the analysis, a single, multi-band window is built by stacking all the desired analysing windows in consecutive frequency bands This approach obtains in parallel the spectrograms corresponding to several hundreds of different analysis windows with the computing cost of a single one, which makes it suitable for fast, online diagnostic systems in transient regime. The traditional STFT analysis of the stator current using a Gaussian window will be first reviewed and, after, the proposed method using a multi-band frequency window will be presented and compared with the traditional one
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
