[307] Monitoring rotating machines: how monitoring voltage and current has prompted new mathematical research and new insights into machine behaviour
G Walker
Faraday Predictive Ltd, UK
Measurements of the relationship between voltage and current being drawn by a motor can provide a powerful monitoring and diagnostic capability, not just for the motor, but also for the entire machine (motor + transmission + driven equipment + sometimes the process) being driven by the motor.
This talk will describe how the technique of model-based voltage and current (MBVI) analysis can detect, identify and predict the behaviour of a wide range of faults, covering mechanical and operational issues as well as electrical ones, allowing users to avoid unexpected breakdowns, adopt a condition-based maintenance regime and identify energy being wasted by faults in the machines, allowing cost justification of corrective work based on energy savings.
MBVI overcomes some of the limitations of conventional vibration monitoring, which mainly covers mechanical phenomena rather than electrical phenomena, and faces challenges when dealing with inaccessible equipment, inverter-driven machines and variable load operation. These limitations of conventional vibration monitoring may at least partly explain why 50 years after RCM methodologies first highlighted condition-based tasks as being the preferred option wherever they are ‘applicable and effective’, and 40 years after vibration monitoring systems became readily commercially available, so few organisations rely on condition-based maintenance as their primary strategy.
This paper also describes new mathematical research prompted by the observed outputs from MBVI systems that moves our understanding of these mainly torsional phenomena forward beyond previous understanding. This can be thought of as a third-generation understanding of machine dynamics, where the first generation was centred around resonant frequencies of shaft bending associated with proximity probe sensing, the second generation was built around identifying four separate stages of rolling element bearing deterioration associated with accelerometer sensing and this third generation is based around torsional behaviour of machines and how this reveals itself in coupling with motor current and voltage.
This talk will describe how the technique of model-based voltage and current (MBVI) analysis can detect, identify and predict the behaviour of a wide range of faults, covering mechanical and operational issues as well as electrical ones, allowing users to avoid unexpected breakdowns, adopt a condition-based maintenance regime and identify energy being wasted by faults in the machines, allowing cost justification of corrective work based on energy savings.
MBVI overcomes some of the limitations of conventional vibration monitoring, which mainly covers mechanical phenomena rather than electrical phenomena, and faces challenges when dealing with inaccessible equipment, inverter-driven machines and variable load operation. These limitations of conventional vibration monitoring may at least partly explain why 50 years after RCM methodologies first highlighted condition-based tasks as being the preferred option wherever they are ‘applicable and effective’, and 40 years after vibration monitoring systems became readily commercially available, so few organisations rely on condition-based maintenance as their primary strategy.
This paper also describes new mathematical research prompted by the observed outputs from MBVI systems that moves our understanding of these mainly torsional phenomena forward beyond previous understanding. This can be thought of as a third-generation understanding of machine dynamics, where the first generation was centred around resonant frequencies of shaft bending associated with proximity probe sensing, the second generation was built around identifying four separate stages of rolling element bearing deterioration associated with accelerometer sensing and this third generation is based around torsional behaviour of machines and how this reveals itself in coupling with motor current and voltage.
