Condition Monitoring of Mechanical Faults in Variable Speed Induction Motor Drives. Application of Stator Current Time-Frequency Analysis and Parameter Estimation

Ce travail de thèse traite de la détection et du diagnostic de défaillances mécaniques par analyse du courant statorique dans les entraînements électriques à base de machine asynchrone. Deux effets d'un défaut mécanique, des oscillations de couple et une excentricité d'entrefer, sont supposés. La modélisation par approche des ondes de forces magnétomotrices et de perméance conduit à deux modèles analytiques du signal courant. La conséquence des défauts est soit une modulation de phase, soit une modulation d'amplitude du signal courant statorique. Ces phénomènes sont détectés par une analyse spectrale en régime permanent, ou des méthodes temps fréquence en régime transitoire. Les méthodes étudiées sont la fréquence instantanée, le spectrogramme et la représentation de Wigner-Ville. L'estimation paramétrique d'indices de modulation a également été traitée. Des résultats de simulation et expérimentaux permettent de valider les signatures et d'extraire de façon automatique des indicateurs de défaut. De plus, une méthode permettant la distinction des oscillations de couple d'une excentricité dynamique est proposée. L'étude est complétée par une implémentation sur DSP des méthodes temps-fréquence afin de démontrer la faisabilité d'une surveillance en ligne. ABSTRACT : This Ph.D. thesis deals with condition monitoring of mechanical failures in variable speed induction motor drives by stator current analysis. Two effects of a mechanical fault are considered: load torque oscillations and airgap eccentricity. The analytical modelling using the magnetomotive force and permeance wave approach leads to two stator current models. The fault provokes amplitude or phase modulation of the fundamental current component. Suitable detection methods are spectral analysis and parameter estimation in steady state whereas time-frequency analysis is required during transients. Instantaneous frequency estimation, the Wigner Distribution and the spectrogram are studied. Simulation and experimental results validate the theoretical approach. Automatic extraction of fault indicators is proposed for an unsupervised monitoring system. Moreover, load torque oscillations and dynamic eccentricity can be discriminated with the proposed methods. The feasibility of an on-line monitoring system is demonstrated by a DSP implementation of the time-frequency analysis including indicator extraction

Understanding the role of health information in patients' experiences: secondary analysis of qualitative narrative interviews with people diagnosed with cancer in Germany

Objective To analyse the role and meaning of health information in individuals' experiences with either breast, colorectal or prostate cancer in order to better understand unmet information needs of people with a cancer diagnosis. Design This is a secondary analysis of data from a qualitative interview study including narrative interviews and maximum variation sampling. A thematic analysis was conducted, followed by an in-depth analysis based on the principles of grounded theory. Setting Interviewees were sought across Germany through self-help organisations, primary care clinics, rehabilitation facilities, physicians and other healthcare professionals to develop cancer modules for the website kr ankheitserfahrungen.de (illness experiences.de). Participants Women with a diagnosis of breast cancer, individuals with a diagnosis of colorectal cancer and men with a diagnosis of prostate cancer. Results The meaning and role of information in the illness experiences were clearly associated with gaining control in a seemingly uncontrollable situation in which others people, the disease take over. Four categories characterise the ways in which information helped interviewees to regain a sense of control following a diagnosis of cancer: 'becoming confident in one's treatment decision', 'taking responsibility for one's situation', 'understanding the consequences of the disease and treatment for one's life', and 'dealing with fear'. There was, however, always a fine line between information seeking and becoming overwhelmed by information. Conclusions Information needs to be understood as a management tool for handling the disease and its (potential) consequences. Patients' unmet needs for information might not be easily solved by a simple increase in the amount of information because emotional support and respect for patient autonomy might also play a role. The evaluation of one's own information behaviour and the information received is closely linked to how the illness unfolds. This makes it challenging to document unmet information needs and satisfaction with information independent of an individual's illness trajectory over time

Condition Monitoring of Mechanical Faults in Variable Speed Induction Motor Drives - <br />Application of Stator Current Time-Frequency<br />Analysis and Parameter Estimation

This Ph.D. thesis deals with condition monitoring of mechanical failures in variablespeed induction motor drives by stator current analysis. Two effects of a mechanicalfault are considered: load torque oscillations and airgap eccentricity. The analyticalmodelling using the magnetomotive force and permeance wave approach leadsto two stator current models. The fault provokes amplitude or phase modulationof the fundamental current component. Suitable detection methods are spectralanalysis and parameter estimation in steady state whereas time-frequency analysisis required during transients. Instantaneous frequency estimation, the Wigner Distributionand the spectrogram are studied. Simulation and experimental resultsvalidate the theoretical approach. Automatic extraction of fault indicators is proposedfor an unsupervised monitoring system. Moreover, load torque oscillationsand dynamic eccentricity can be discriminated with the proposed methods. Thefeasibility of an on-line monitoring system is demonstrated by a DSP implementationof the time-frequency analysis including indicator extraction.Ce travail de thèse traite de la détection et du diagnostic de défaillances mécaniques par analyse du courant statorique dans les entraînements électriques à base de machine asynchrone. Deux effets d'un défaut mécanique, des oscillations de couple et une excentricité d'entrefer, sont supposés. La modélisation par approche des ondes de forces magnétomotrices et de perméance conduit à deux modèles analytiques du signal courant. La conséquence des défauts est soit une modulation de phase, soit une modulation d'amplitude du signal courant statorique. Ces phénomènes sont détectés par une analyse spectrale en régime permanent, ou des méthodes temps fréquence en régime transitoire. Les méthodes étudiées sont la fréquence instantanée, le spectrogramme et la représentation de Wigner-Ville. L'estimation paramétrique d'indices de modulation a également été traitée. Des résultats de simulation et expérimentaux permettent de valider les signatures et d'extraire de façon automatique des indicateurs de défaut. De plus, une méthode permettant la distinction des oscillations de couple d'une excentricité dynamique est proposée. L'étude est complétée par une implémentation sur DSP des méthodes temps-fréquence afin de démontrer la faisabilité d'une surveillance en ligne

Détection et diagnostic de défauts mécaniques dans les entraînements asynchrones à vitesse variable (analyse temps-fréquence du courant statorique et estimation paramétrique)

This Ph.D. thesis deals with condition monitoring of mechanical failures in variable speed induction motor drives by stator current analysis. Two effects of a mechanical fault are considered: load torque oscillations and airgap eccentricity. The analytical modelling using the magnetomotive force and permeance wave approach leads to two stator current models. The fault provokes amplitude or phase modulation of the fundamental current component. Suitable detection methods are spectral analysis and parameter estimation in steady state whereas time-frequency analysis is required during transients. Instantaneous frequency estimation, the Wigner Distribution and the spectrogram are studied. Simulation and experimental results validate the theoretical approach. Automatic extraction of fault indicators is proposed for an unsupervised monitoring system.Ce travail de thèse traite de la détection et du diagnostic de défaillances mécaniques par analyse du courant statorique dans les entraînements électriques à base de machine asynchrone. Deux effets d'un défaut mécanique, des oscillations de couple et une excentricité d'entrefer, sont supposés. La modélisation par approche des ondes de forces magnétomotrices et de perméance conduit à deux modèles analytiques du signal courant. La conséquence des défauts est soit une modulation de phase, soit d'amplitude du signal courant statorique. Ces phénomènes sont détectés par une analyse spectrale en régime permanent ou des méthodes temps fréquence en régime transitoire. Les méthodes étudiées sont la fréquence instantanée, le spectrogramme et la représentation de Wigner-Ville. L'estimation paramétrique d'indices de modulation a également été traitée. Des résultats de simulation et expérimentaux permettent de valider les signatures et d'extraire de façon automatique des indicateurs de défaut.TOULOUSE-ENSEEIHT (315552331) / SudocSudocFranceF

Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring

International audienceThis paper describes a new analytical model for the influence of rolling-element bearing faults on induction motor stator current. Bearing problems are one major cause for drive failures. Their detection is possible by vibration monitoring of characteristic bearing frequencies. As it is possible to detect other machine faults by monitoring the stator current, a great interest exists in applying the same method for bearing fault detection. After a presentation of the existing fault model, a new detailed approach is proposed. It is based on the following two effects of a bearing fault: 1) the introduction of a particular radial rotor movement and 2) load torque variations caused by the bearing fault. The theoretical study results in new expressions for the stator current frequency content. Experimental tests with artificial and realistic bearing damage were conducted by measuring vibration, torque, and stator current. The obtained results by spectral analysis of the measured quantities validate the proposed theoretical approach

Mechanical fault detection in induction motor drives through stator current monitoring - Theory and application examples

Available from: http://sciyo.com/articles/show/title/mechanical-fault-detection-in-induction-motor-drives-through-stator-current-monitoring-theory-and-apIn a wide variety of industrial applications, an increasing demand exists to improve the reliability and availability of induction motor drives. Common failures occurring in such drives can be classified into electrical and mechanical faults (rotor eccentricity, bearing faults, shaft misalignment, load unbalance, gearbox fault or general failure in the load part of the drive). Mechanical faults are most commonly detected through vibration or noise monitoring, but stator current monitoring is an interesting alternative. Indeed, current sensors are cost-effective, easy to implement, and most drives already contain such sensors for protection and control purposes. However, the effects of mechanical faults on the stator currents are more indirect compared to vibration or noise analysis. This work focuses on various aspects of mechanical fault detection through stator current monitoring, starting from a general theoretical analysis to signal processing methods for fault detection and several application examples

Models for bearings damage detection in induction motors using stator current monitoring

International audienceThis paper describes new models for the influence of rolling-element bearing faults on induction motor stator current. Bearing problems are one major cause for drive failures. Their detection is possible by vibration monitoring of characteristic bearing frequencies. As it is possible to detect other machine faults by monitoring the stator current, a great interest exists in applying the same method for bearing fault detection. After a presentation of the existing fault model, a new detailed approach is proposed. It is based on two effects of a bearing fault: the introduction of a particular radial rotor movement and load torque variations caused by the bearing fault. The theoretical study results in new expressions for the stator current frequency content. Experimental tests with artificial and realistic bearing damage were conducted by measuring vibration, torque and stator current. The obtained results by spectral analysis of the measured quantities validate the proposed theoretical approach