Monitoring system warns of potential pump failure

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Increased noise and vibration levels on two centrifugal pumps at the Perlenbach water treatment plant in Germany were causing bearing defects which could have led to pump failure and a threat to water supplies. Perlenbach changed from regular patrol pump monitoring to a continuous online system from Schaeffler which detects any signs of wear or damage to the bearings early before the pumps fail

Monitoring system warns of potential pump failurePerlenbach water supply association supplies fresh drinking water every day to around 50,000 residents across seven municipalities in the Eifel region of Germany. This equates to around 2.4 million cubic metres of water per year, which needs to be filtered and treated using complex methods.

Increased noise and vibration levels on the centrifugal pumps are often caused by bearing defects, which can result in pump failure, posing a threat to water supplies. To prevent this, Perlenbach decided to change from regular patrol pump monitoring to a continuous online system — the objective being the early detection of any signs of wear or damage to the bearings before the pumps failed.

Schaeffler and its local partner KSA recommended the FAG SmartQB system. As part of a pilot project, two centrifugal pumps were fitted with two SmartQB sensors (for measuring vibration and temperature) and connected via one FAG SmartQB. In the event of any bearing defects, the FAG SmartLamp installed next to the FAG SmartQB illuminates red and the system generates an alarm message. With only two additional clicks on the touchscreen display, the maintenance technician can view more detailed information about the fault and is provided with specific recommended actions.

After a short period of time, the system has proven itself. Due to the information provided by FAG SmartQB and its automatic fault assessment feature that gives an early warning of the onset of any bearing damage, maintenance personnel are now able to react quickly and in a targeted manner. Both bearings in the eight-stage centrifugal pump were replaced in a very short time, which prevented severe damage to the facility — and as a consequence, unplanned downtime of up to several weeks combined with significant damage amounting to several thousands of euros was prevented.

The pilot project was so successful that Perlenbach is currently considering fitting sensors to additional pumps and integrating the FAG SmartQB system into its internal maintenance alarm management system. In this way, all condition monitoring data can be centralised as well as viewed locally on the FAG SmartQB display.

Local data to cloud-based diagnosis

Vibration monitoring systems are one of the most reliable methods of monitoring the condition of rolling bearings and for detecting the early onset of damage to bearings and other machine components. However, as the use of sensor technologies becomes more and more prevalent, the volume of measurement data available is increasing.

Schaeffler’s FAG SmartQB is a standalone system for monitoring the condition of rotating plant and equipment with fixed or variable speeds from 100 to 15,000rpm. Due to its unique automatic fault assessment feature, the system can be operated by maintenance staff with little or no expertise in vibration monitoring technology. This ready-to-use, pre-configured condition monitoring system for electric motors, pumps, fans, compressors and gearboxes is simple to install — commissioning takes just five minutes — and requires no specific skills or knowledge of vibration diagnosis. When changes occur in the condition of the equipment, FAG SmartQB automatically generates plain text messages on its seven-inch display

The FAG SmartQB system consists of a FAG SmartQB sensor unit, a cube-shaped housing with touchscreen display, and a cable for power and data transmission (Power-over-Ethernet). The system is supplied with ready-to-use, preset measurement configurations. Five causes of faults can be identified and displayed using the system — bearing damage, imbalance, friction/cavitation (for centrifugal pumps), temperature increases, and general changes in vibration patterns that cannot be clearly attributed to one of the aforementioned causes and so may require additional analyses. The automatic fault assessment feature provides clearly understood plain text messages on its display, giving users clear instructions for action, enabling them to immediately undertake any corrective maintenance work and order any replacement parts if required.

Initial start-up

When starting FAG SmartQB for the first time, the customer selects one of the 16 languages provided. After selecting the component on which the FAG SmartQB sensor is mounted (i.e. a motor, pump or fan), the user then specifies whether the machine operates at constant or variable speed, and enters the individual name of the drive system/assembly. FAG SmartQB then automatically selects the best measurement configuration. The system is immediately ready for the automatic learning mode which enables the device to automatically adjust alarm thresholds. After set up and commissioning, FAG SmartQB operates autonomously — the relevant machine parameters are measured and saved continuously in the system, creating a substantial database of historical data over time.

A total of six sensors can be connected to one FAG SmartQB and allocated to multiple machines, individual machine components or sub-assemblies as required. Sensors can be easily added using the display in a similar way to initial system installation. After initial operation, FAG SmartQB displays relevant information such as operating hours counter, fault frequency, maximum values, average values, trend curves, and the alarm status of each individual FAG SmartQB sensor.

If an alarm due to a change in vibration signals occurs, which cannot be attributed to one of the five main causes, the system makes a recommendation to maintenance staff via the display, to send the measurement data to Schaeffler’s technical support centre for a more in-depth analysis.

 

 

 
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