Ett flervariabelt feldetekteringssystem för övervakning av bärlagertemperaturen i vattenkraftturbiner

Sammanfattning: The purpose of this thesis work was to develop an automatic fault detection system for surveillance of bearing temperature in hydropower turbines. The parameters used except the bearing temperature were cooling water temperature and cooling water flow. A simple static model based on data sampled every minute was developed to estimate the bearing temperature. Then a detector for detection of change in bearing temperature based on the CUSUM-algorithm was designed. Since the amount of data was very small the developed model was too uncertain to be used in a working system. The designed fault detection system showed to work well for the available data. It is, however, recommended that the performance of the system should be evaluated using more data. Another model based on data sampled once every minute for at least a year has to be developed before the system can be fully evaluated. The results shown were: • The fault detection system can discover fast and slow changes in bearing temperature. • No false alarms were given for measuring faults and sensor faults of the types used in this thesis. If a measuring fault occurs for too long there will be an alarm. The fault detection algorithm was also implemented in Delphi to be used in a working system over the Internet where for example trends and alarms will be presented.