ระบบผู้เชี่ยวชาญในการแก้ไขปัญหาข้อขัดข้องสำหรับโรงไฟฟ้าพลังน้ำเขื่อนนเรศวร
This research studies fault diagnosis on an unmanned 8 MW bulb turbine generator of the run of river hydropower plant locates far from the control and maintenance center by expert system scheme. The aim is to assist the inexpert maintenance crews to solve the failure by collecting knowledge from...
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Other Authors: | |
Format: | Theses and Dissertations |
Language: | other |
Published: |
เชียงใหม่ : บัณฑิตวิทยาลัย มหาวิทยาลัยเชียงใหม่
2020
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Online Access: | http://cmuir.cmu.ac.th/jspui/handle/6653943832/69747 |
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Institution: | Chiang Mai University |
Language: | other |
Summary: | This research studies fault diagnosis on an unmanned 8 MW bulb turbine generator of the run of river
hydropower plant locates far from the control and maintenance center by expert system scheme. The
aim is to assist the inexpert maintenance crews to solve the failure by collecting knowledge from
power plant equipment data, maintenance instruction manual, maintenance standard, historical failure
events, and body of knowledge from expertise. The studied system translates this information to the
knowledge base of an expert system by propositional logic together with failure analysis of
mechanical and electrical equipment that initiates lockout relay signal to shut down the power plant
by fault tree analysis technique for more accuracy and correctness of fault diagnosis. The
implementation of an inference engine comprises of failure search rules and problem-solving rules
with developing a graphical user interface that similar to the SCADA graphic of the operator station.
This helps inexpert maintenance crews to familiar with the expert system software and easy to use.
These will speed up the inexpert maintenance crews to correct the problem as fast as the expertise
does. For example, such a case that the generator cannot synchronize to the grid that took the inexpert
maintenance crews about 43 hours to correct the problem which causes a loss income of about 1,036,080 THB. With the help of the studied expert system, the inexpert maintenance crews could
take less than 4 hours to correct this problem and could save a loss of about 900,000 THB. |
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