| dc.contributor.advisor | Sasidhar, P S Kalyan | |
| dc.contributor.author | Swarnlata, Ch | |
| dc.date.accessioned | 2020-09-22T17:21:25Z | |
| dc.date.available | 2023-02-17T17:21:25Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Swarnlata, Ch (2020). Wind turbine power generation monitoring system along with predictive maintenance to identify the mean breakage time. Dhirubhai Ambani Institute of Information and Communication Technology. viii, 17 p. (Acc.No: T00901) | |
| dc.identifier.uri | http://drsr.daiict.ac.in//handle/123456789/986 | |
| dc.description.abstract | The wind turbine monitoring system is associated with electrical and control system failures through innovatively applying modern technologies like intelligent sensors, data acquisition along with the existing technologies to detect the electrical system failures for wind turbines economically. The system is based on Internet of Things. The wind turbine has intelligent sensors inside them which send the collected data to the Remote terminal unit. The remote terminal unit transmits the sensor data from input streams to the server. This data is used for triggering alarms for failure management. We have built an application programming interface that is used for processing analytical data to monitor the turbine. | |
| dc.subject | Internet of Things | |
| dc.subject | Sensors | |
| dc.subject | data acquisition | |
| dc.subject | Remote terminal Unit | |
| dc.classification.ddc | 621.312136 SWA | |
| dc.title | Wind turbine power generation monitoring system along with predictive maintenance to identify the mean breakage time | |
| dc.type | Dissertation | |
| dc.degree | M. Tech | |
| dc.student.id | 201811081 | |
| dc.accession.number | T00901 | |
