Variable speed drives as smart sensors
With the advance of Industry 4.0, the role of the drive has evolved from that of a pure power processor to that of an intelligent element in the automation system. The ability of the drive to act as a smart sensor makes it a good choice when implementing condition monitoring.
New drive capabilities for water and wastewater applications
More than 20% of all electric motors are driven by variable speed drives, mainly to reduce energy use. However, there are other reasons for employing drives in water and wastewater applications, including process control (keeping constant water pressure, thus avoiding leakage caused by high pressure), avoiding water hammer or optimised well exploitation.
Drives can perform pump de-ragging in wastewater applications; control several pumps in a cascade system in water pumping applications; or bypass certain frequencies to avoid resonances.
The advance of Industry 4.0 has boosted these functions. As Industry 4.0 deals with information and networking, the drives become smart and networked sensors.
Industry 4.0 in motor and drive systems
Industry 4.0 is characterised by networking — it migrates motor systems from an ‘automation pyramid’ to networked systems. This means that elements such as motors, drives, sensors and controls become interconnected and also connected to the cloud.
The drive as a sensor
In variable speed drive applications, microprocessors in the drive and bus communication options, combined with current and voltage sensors, open new opportunities. Additional sensors (such as vibration and pressure sensors) can be connected to the drive at almost no cost. This allows the drive to be used as a smart sensor for condition monitoring.
Embedded condition-based monitoring
Condition monitoring examines equipment health, requiring the selection of key parameters to indicate fault development. Equipment condition typically degrades over time. The figure below shows a typical degradation pattern, also known as a PF-curve. The point of functional failure is when the equipment fails to provide the intended function. The idea of condition-based maintenance is to detect the potential failure before the actual failure occurs. Maintenance actions can be planned before functional failure, with advantages such as reduced downtime, elimination of unexpected production stops, maintenance optimisation and reduction of spare part stock.
Many mechanical failures create some kind of vibration, meaning that vibration monitoring is standard practice for maintenance of rotating machines.
A widely used method is vibration velocity RMS monitoring, based on the RMS value of the vibration signal measured through a vibration sensor. Many mechanical faults have a significant impact on the RMS of the vibration eg, imbalances, shaft misalignment and looseness. However, the challenge in variable speed applications is the dependency of the vibration on speed. Mechanical resonances are typical examples — these are always present and a monitoring system has to cope with them. Fault detection levels are often set for ‘worst case’ to avoid false alarms. This reduces detection accuracy at speeds where no resonances are present.
By having a suitable vibration transmitter mounted and connected to the drive, the drive can offer advanced monitoring by correlating the transmitter signal with drive-internal signals such as speed or other signals relevant for the application. The drive can detect faults early and give traffic light information on the health state of the system to prevent functional failure. Maintenance can be prepared and scheduled in advance while the system can continue operation until the next possible maintenance break.
The vibration level in normal and faulty condition is also dependent on the type, location and mounting of the sensor, and varies with the actual application being monitored. Thus, a learning period is required, which can be achieved in different ways. One approach involves learning the normal vibration levels during the initial period of operation. This means the application is running normally and the drive learns the vibration in parallel without affecting the operation. When enough data has been collected, the drive starts to monitor the vibration. Alternatively, the drive can execute an identification run. Here, the drive controls the motor in a way that enough data is being collected. The possibility of using this second approach depends on the specific application. For example, in a water supply system the pump may not be allowed to run at full speed at the time of commissioning.
Electrical signature analysis
The condition of the motor and application can also be monitored through electrical signature analysis. With the available processing power and memory in today’s drives, these techniques can be integrated into products as product features.
Fault condition indicators can be extracted from motor currents and voltage signals. Frequency components of currents and voltages can be related to motor or application faults, eg, shaft misalignment or stator winding faults. The current and voltage sensors are already essential components of drives, providing the necessary signals for controlling the motor. These signals can be used for monitoring purposes. Thus, no extra sensor costs are added.
The drive being the controller of the motor can correlate the monitoring values with other available information inside the drive. Knowing the controller state for instance, the drive knows when meaningful spectrum calculations can be performed. As with vibration-level monitoring, the correlation of monitored values with motor speed, load and other relevant process data (eg, pressure in water pipes) can be performed to get more accurate fault information.
Load monitoring in pumps
The primary current and voltage measurement is used to calculate parameters such as motor power, energy, actual motor speed or torque, which can be used for monitoring motor load.
In applications where the load depends on the motor speed, the torque estimation can be used for determining overload and underload deviations. During baseline, the drive learns the normal distribution of the load. As in the previous functions, there is a correlation with the motor speed. During monitoring the drive can detect overload and underload conditions, which can be caused in pump applications by faults such as fouling, sanding, broken impeller or wear out.
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