Condition monitoring for
Energy and Industry
Sound based Condition Monitoring. How Does It Operate?
INSTALLATION OF MONITORING POINTS
Understading the soundscape of your investment area sets the basic principles for planning your project.
Evaluation will include the analysis of the sounds emitted by the planned investment against present soundscape.
Development phase monitoring will include sound monitoring during development and environmental noise monitoring.
Soundscape anlysis during start-up and full operation. Monitoring of environmental noise limits.
Wind Power Ice Detection and
Ice on wind turbine blades will change the sound profile of the turbine. Online alarms are preset to detect this condition and alarms to set when the icing occurs. Installation of the monitoring unit does not need anything on blades or hub and can be done in few hours for individual turbine.
Wind turbine has small but distictive sound that can be detected when monitored from close proximity. This sound identifies us typical for each turbine. AuresSound specialists will determine this typical soundscape and set alarms for specific changes on this.
Condition Monitoring in Energy Production and Process Industry.
Installation and detection of abnormal sounds
Monitoring sites of energy production and process industry are usually in the roof and around of the site. Sound is monitored 24/7 and normal operational sound is defined. Sounds that differentiate from normal trigger an alarm that can be listened and analysed. Distinct background sounds e.g. airplanes, weather related sounds are separated during start-up by AuresSound specialists.
What can be detected
All abnormal sounds can be detected. These sound can be abnormal steam releases, broken fans, broken bearings, broken pumps etc. Technicians can identify the abnormal sound when they listen to it.
Other benefits of online monitoring
Online monitoring will give you valid information 24/7 on your noise emissions and background noise emissions. With online monitoring you can easily separate background noise from actual operational noise. Sound monitoring can also detect work conducted on abnormal times.