Current-, force-, and vibration-based techniques for induction motor condition monitoring

The aim of this research was to discover the best indicators of induction motor faults, as well as suitable techniques for monitoring the condition of induction motors. Numerical magnetic field analysis was used with the objective of generating reliable virtual data to be analysed with modern signal processing and soft-computing techniques. In the first part of the research, a fuzzy system, based on the amplitudes of the motor current, was implemented for online detection of stator faults. Later on, from the simulation studies and using support vector machine (SVM), the electromagnetic force was shown to be the most reliable indicator of motor faults. Discrete wavelet transform (DWT) was applied to the stator current during the start-up transient, showing how the evolution of some frequency components allows the identification and discrimination of induction motor faults. Predictive filtering was applied to separate the harmonic components from the main current signal. The second part of the research was devoted to the development of a mechanical model to study the effects of electromagnetic force on the vibration pattern when the motor is working under fault conditions. The third part of this work, following the indications given by the second part, is concerned with a method that allows the prediction of the effect of the electromechanical faults in the force distribution and vibration pattern of the induction machines. The FEM computations show the existence of low-frequency and low-order force distributions acting on the stator of the electrical machine when it is working under an electrical fault. It is shown that these force components are able to produce forced vibration in the stator of the machine. This is corroborated by vibration measurements. These low-frequency components could constitute the primary indicator in a condition monitoring system. During the research, extensive measurements of current, flux and vibration were carried out in order to supply data for the research group. Various intentional faults, such as broken rotor bars, broken end ring, inter-turn short circuit, bearing and eccentricity failures, were created. A real dynamic eccentricity was also created. Moreover, different supply sources were used. The measurements supported the analytical and numerical results.reviewe

Air-gap force distribution and vibration pattern of Induction motors under dynamic eccentricity

[EN] A method for determining the signatures of dynamic eccentricity in the airgap force distribution and vibration pattern of induction machine is presented. The radial electromagnetic force distribution along the airgap, which is the main source of vibration, is calculated and developed into a double Fourier series in space and time. Finite element simulations of faulty and healthy machines are performed. They show that the electromagnetic force distribution is a sensible parameter to the changes in the machine condition. The computations show the existence of low frequency and low order force distributions, which can be used as identifiable signatures of the motor condition by measuring the corresponding low order vibration components. These findings are supported by vibration measurements and modal testing. The low frequency components offer an alternative way to the monitoring of slot passing frequencies, bringing new components that allow to discriminate between dynamic eccentricity and rotor mechanical unbalance. The method also revealed a non linear relationship between loading, stress waves and vibration during dynamic eccentricity.Jover Rodríguez, PV.; Belahcen, A.; Arkkio, A.; Laiho, A.; Antonino-Daviu, J. (2008). Air-gap force distribution and vibration pattern of Induction motors under dynamic eccentricity. Electrical Engineering. 90(3):209-218. doi:10.1007/s00202-007-0066-2S209218903Rao JS (2000). Vibratory condition monitoring of machines. CRC Pr. Llc., Boca RatonTavner P, Penman J (1987) Condition monitoring of electrical machines. Research Studies Press, Letchworth, pp 203–205Pöyhönen S, Negrea M, Jover P, Arkkio A and Hyötyniemi H (2003). Numerical magnetic field analysis and signal processing for fault diagnostic of electrical machines. COMPEL Int J Comput Math Elect Eng 22(4): 969–981Finley W, Hodowanec M, Holter W (2000) An analytical approach to solving motor vibration problems. IEEE Trans Industry Appl 363(5)Cameron JR, Thomson WT, Eng C, Dow AB (1986) Vibration and current monitoring for detecting airgap eccentricity in large induction motors. IEE Proc Inst Elect Eng 133(Pt. B, No. 3)Smith AC, Dorrell DG (1996) Calculation and measurements of unbalance magnetic pull in cage induction motors with eccentric rotors. Part 1: Analytical model. IEE Proc Elect Power Appl 143(3)Dorrell DG, Smith AC (1996) Calculation and measurements of unbalance magnetic pull in cage induction motors with eccentric rotors. Part 2: Experimental investigation. IEE Proc Elect Power Appl 143(3)Dorrell DG, Thomson WT and Roach S (1997). Analysis of airgap flux, current, and vibration signals as a function of a combination of static and dynamic eccentricity in 3-phase induction motors. IEEE Trans Indus Appl 33: 24–34Verma SP, Balan A (1994) Determination of radial forces in relation to noise and vibrations problems of squirrel cage induction motors. IEEE Trans Energy Convers 9(2)Vandevelde L, Melkebeek AA (2001) Numerical analysis of vibrations of squirrel-cage induction motors based on magnetic equivalent circuits and structural finite element models. In: Industry Application Conference, 2001. Thirsty-six IAS Annual Meeting. Conference records of the 2001 IEEE, vol 4, September/October 2001, pp 2288–2295Belahcen A, Arkkio A, Klinge P, Linjama J, Voutilainen V, Westerlund J (1999) Radial forces calculation in a synchronous generator for noise analysis. In: Proceeding of the Third Chinese International Conference on Electrical Machines, August 29–31, 1999, Xi’an, China, pp 199–122Jover Rodríguez P, Belahcen A, Arkkio A (2007) Signatures of electrical faults in force distribution and vibration pattern of induction motors. IEE Proc Elect Power Appl (in press)Arkkio A (1987) Analysis of induction motor based on numerical solution of the magnetic field and circuits equations. Acta Polytechn. Scand Electri Eng Serie 59:97. Available at  Ewings DG (2000). MODAL TESTING: theory, practice and application, 2nd edn. Research studies press Ltd., BaldockDeBertoli MJ, Salon SJ, Burow DW, Slavik CJ (1993) Effects of rotor eccentricity and parallel windings on induction machine behaviour: a study using finite element analysis. IEEE Trans Magnet 29(2)Arkkio A, Antila M, Pokki K, Lanto E (2000) Electromagnetic force in a whirling cage rotor. IEE Proc Elect Power Appl 147(5

Transient detection of eccentricity-related components in induction motors through the Hilbert-Huang Transform

[EN] The identification and extraction of characteristic patterns are proposed in this work for the diagnosis and evaluation of mixed eccentricities in induction electrical machines with parallel stator branches. Whereas the classical diagnosis approaches, deeply spread in the industrial environment, are based on the Fourier analysis of the steady-state current, the basis of the proposed methodology consist of analysing the current demanded by the machine during the connection process (startup transient); the objective is to extract the characteristic evolution during the transient of some harmonic components created by the fault; this evolution is caused by the dependence of these components on the slip (s), a quantity varying during the startup transient from 1 to almost 0. For this feature extraction. the Hilbert-Huang Transform (HHT) is proposed. An analysis of the-behaviour of this transform in comparison with another time-frequency approach used in other works, the Discrete Wavelet Transform (DWT), is also presented in the paper. The results show the usefulness of the methodology for the reliable diagnosis of the mixed eccentricity fault and for the correct discrimination against other types of failures. (C) 2009 Elsevier Ltd. All rights reserved.The research leading to these results has received funding from the European Community's Seventh Framework Programme FP7/2007-2013 under Grant Agreement no. 224233 (Research Project PRODI "Power plant Robustification based on fault Detection and Isolation algorithms"). The authors also thank Vicerrectorado de Investigacion, Desarrollo e Innovacion of Universidad Politecnica de Valencia for financing a part of this research through the program Programa de Apoyo a la Investigacion y Desarrollo (PAID-06-07).Antonino-Daviu, J.; Jover Rodríguez, PV.; Riera-Guasp, M.; Arkkio, A.; Roger-Folch, J.; Pérez, R. (2009). Transient detection of eccentricity-related components in induction motors through the Hilbert-Huang Transform. Energy Conversion and Management. 50(7):1810-1820. https://doi.org/10.1016/j.enconman.2009.03.008S1810182050

Down syndrome as risk factor for respiratory syncytial virus hospitalization : A prospective multicenter epidemiological study

Respiratory syncytial virus (RSV) infection in childhood, particularly in premature infants, is associated with significant morbidity and mortality. To compare the hospitalization rates due to RSV infection and severity of disease between infants with and without Down syndrome (DS) born at term and without other associated risk factors for severe RSV infection. In a prospective multicentre epidemiological study, 93 infants were included in the DS cohort and 68 matched by sex and data of birth (±1 week) and were followed up to 1 year of age and during a complete RSV season. The hospitalization rate for all acute respiratory infection was significantly higher in the DS cohort than in the non-DS cohort (44.1% vs 7.7%, P<.0001). Hospitalizations due to RSV were significantly more frequent in the DH cohort than in the non-DS cohort (9.7% vs 1.5%, P=.03). RSV prophylaxis was recorded in 33 (35.5%) infants with DS. The rate of hospitalization according to presence or absence of RSV immunoprophylaxis was 3.0% vs 15%, respectively. Infants with DS showed a higher rate of hospitalization due to acute lower respiratory tract infection and RSV infection compared to non-DS infants. Including DS infants in recommendations for immunoprophylaxis of RSV disease should be considered

Dietary inflammatory index and all-cause mortality in large cohorts: The SUN and PREDIMED studies

[Background]: Inflammation is known to be related to the leading causes of death including cardiovascular disease, several types of cancer, obesity, type 2 diabetes, depression-suicide and other chronic diseases. In the context of whole dietary patterns, the Dietary Inflammatory Index (DII®) was developed to appraise the inflammatory potential of the diet. [Objective]: We prospectively assessed the association between DII scores and all-cause mortality in two large Spanish cohorts and valuated the consistency of findings across these two cohorts and results published based on other cohorts.[Design]: We assessed 18,566 participants in the “Seguimiento Universidad de Navarra” (SUN) cohort followed-up during 188,891 person-years and 6790 participants in the “PREvencion con DIeta MEDiterránea” (PREDIMED) randomized trial representing 30,233 person-years of follow-up. DII scores were calculated in both cohorts from validated FFQs. Higher DII scores corresponded to more proinflammatory diets. A total of 230 and 302 deaths occurred in SUN and PREDIMED, respectively. In a random-effect meta-analysis we included 12 prospective studies (SUN, PREDIMED and 10 additional studies) that assessed the association between DII scores and all-cause mortality.[Results]: After adjusting for a wide array of potential confounders, the comparison between extreme quartiles of the DII showed a positive and significant association with all-cause mortality in both the SUN (hazard ratio [HR] = 1.85; 95% CI: 1.15, 2.98; P-trend = 0.004) and the PREDIMED cohort (HR = 1.42; 95% CI: 1.00, 2.02; P-trend = 0.009). In the meta-analysis of 12 cohorts, the DII was significantly associated with an increase of 23% in all-cause mortality (95% CI: 16%–32%, for the highest vs lowest category of DII).[Conclusion]: Our results provide strong and consistent support for the hypothesis that a pro-inflammatory diet is associated with increased all-cause mortality. The SUN cohort and PREDIMED trial were registered at clinicaltrials.gov as NCT02669602 and at isrctn.com as ISRCTN35739639, respectively.Supported by the official funding agency for biomedical research of the Spanish Government, Instituto de Salud Carlos III (ISCIII), through grants provided to research networks specifically developed for the trial (RTIC G03/140, to R.E.; RTIC RD 06/0045, to Miguel A. Martínez-González) and through Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBERobn), and by grants from Centro Nacional de Investigaciones Cardiovasculares (CNIC 06/2007), Fondo de Investigación Sanitaria–Fondo Europeo de Desarrollo Regional (Proyecto de Investigación (PI) 04-2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, PI13/00462, PI13/00615, PI13/01090, PI14/01668, PI14/01798, PI14/01764), Ministerio de Ciencia e Innovación (Recursos y teconologia agroalimentarias(AGL)-2009-13906-C02 and AGL2010-22319-C03 and AGL2013-49083-C3-1- R), Fundación Mapfre 2010, the Consejería de Salud de la Junta de Andalucía (PI0105/2007), the Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (Generalitat Valenciana Ayuda Complementaria (GVACOMP) 06109, GVACOMP2010-181, GVACOMP2011-151), Conselleria de Sanitat y, PI14/01764 AP; Atención Primaria (CS) 2010-AP-111, and CS2011-AP-042), and Regional Government of Navarra (P27/2011).). Drs. Shivappa and Hébert were supported by grant number R44DK103377 from the United States National Institute of Diabetes and Digestive and Kidney Diseases