Document

Preventing accidents before they happen: Let’s take a look at the application of condition monitoring sensors in predictive maintenance of wind turbines

Posted by Balluff on Jul 4, 2020 8:43:22 AM

As a kind of common equipment for gas compression and gas transportation, fans are widely used in metallurgy, mining, petrochemical, electric power, urban rail transit, textile, shipbuilding and other national economic fields and various other places such as ventilation. It plays an extremely important role in process and environmental maintenance. For example, in the metal industry, there are many fans such as sintering fans, blast furnace blowers, iron furnace fans, converter secondary flue gas dust removal fans, etc. In mine applications, the main fan is straight up the most important equipment for the supply of air.

No matter the application, the wind turbine is an important equipment asset of the factory on one hand, and it is also the equipment that consumes the most energy on the other hand. For factories to save costs, avoid losses, ensure a safe production and to avoid accidents, it is essential to follow a correct maintenance concept and methods. This in turn will save energy, reduce consumption, and improve efficiency of the whole factory. Condition monitoring is a popular concept often adapted for fan maintenance.

Generally, the vibration of the bearing part is very small when the fan starts to work, but as the operating time increases, the dust accumulated in the fan will unevenly adhere to the impeller, thus, gradually destroying the dynamic balance of the fan, and increasingly disturb the vibration of the bearing. Once the vibration reaches the maximum value allowed by the fan, the fan itself must be shut down for repair. At the same time, because of abnormal vibration or lubricant, the bearing temperature of the fan will exceed the normal value range, or in the worst case, even damage the fan.

 

For a safe usage of the fan

The vibration status of the fan is one of the most important condition monitoring parameters of the rotating machineries. Monitoring and diagnosis of the fan based on the vibration signal collected by the sensor or adding a temperature signal are all crucial for achieving advanced predictive maintenance for the fan.

Balluff's BCM series of multi-function condition monitoring sensors can simultaneously detect multiple pump state variables, such as vibration and temperature. For vibration data, it is generally necessary to complete the entire steps from data collection, data processing to condition monitoring and analysis. According to these steps, BCM sensors can be applied in different stages. For example, if the state detection cannot be achieved by evaluating the signal of only one sensor, the sensor can be integrated into the data processing process to allow combined analysis with other sensor signals. The BCM solution can be used either as a dedicated sensor, as part of a body control module, or embedded in a general automation system application.

 

condition-monitoring-sensor

 

Based on the BCM sensor, once the operating parameters of the fan are detected to be outside of the set norm, it can alarm you immediately and analyze the reason to prevent unexpected equipment accidents. Secondly, you can diagnose and analyze abnormal phenomena such as a sudden increase in vibration during the operation of the fan, rise in bearing bush temperature, and reciprocal fluctuation of the vibration value. Adding, you can master the operation status of the fan, formulate a scientific maintenance plan, and save on unnecessary spare parts. Also, in the realm of the now possible is extending the running time of the fan, reducing parking, and increasing production and efficiency. Finally, condition monitoring can be combined with process operations to obtain better production benefits by optimizing process operations.

With the Balluff BCM sensor series, important plant assets such as wind turbines can benefit from condition monitoring and predictive maintenance.

Topics: PredictiveMaintenance, ConditionMonitoring

    Subscribe for more

    New Call-to-action