Hydro Power Plant fault status and status
According to the statistics of equipment failures of Hydro Power Plants in the past 10 years (73-82 years) published in the technical report of the Institute of Electrical Engineering, most of the failures related to turbines occurred in water supply and drainage devices, followed by the turbine body and oil pressure devices The number of failures occurred approximately once every two years. In addition, in view of the failure rate of each part of these devices, the oil supply equipment of the oil pressurization device such as the guide vanes of the water turbine main body, the guide vanes of the turbine body, the water sealing devices around the guide vanes, The failure rate of pipelines, valves, oil pumps and other components is high. Furthermore, in terms of causes, failures that are naturally degraded account for the overwhelming majority, followed by poor implementation, poor manufacturing, and poor maintenance.
The following is an overview of which state quantities are related to various faults. Most fault occurrence pairs will be accompanied by changes in certain state quantities. If they are classified in a centralized manner, it is much more convenient to manage. These state quantities are called Related state quantity. For the water supply and drainage device, it refers to the increase in water pressure, flow, vibration, etc. Similarly, for the turbine bearing, it refers to -Taijin wear, bearing temperature, vibration value, etc. J For the casing, runner, suction tube , Refers to noise, vibration, etc. For the oil pressure device, it refers to the oil pressure, oil level, load relief valve operation time and number of times, etc. I For the main shaft water sealing device, it refers to the increase in the amount of packing friction and water leakage, etc. .
Monitoring rules
One of the important purposes of preventive maintenance is to use daily monitoring of the temperature, vibration and other status to predict the pre-existence. There are two methods here. One is to find out the trend from the highest daily or monthly value that has been viewed, and then predict when the given limit will be crossed. Another method is to find abnormal signs from the above data changes. To effectively implement these methods, consider the following monitoring rules.
