Transformer station intelligent alarm model method for big data and cloud environment

Abstract

The invention relates to a transformer station intelligent alarm model method for big data and a cloud environment. The method is technically characterized by comprising the following steps: a data obtaining phase; data cleaning; data aligning; data calculation and data display. The data calculation comprises inputting historical data after the cleaning and aligning to multiple calculation algorithms, calculating a probability of failure of each device, and by use of corresponding relations of families where the devices belong to, calculating probabilities of other devices of the families, wherein relations between input data and device defects and device faults can be automatically learned through each algorithm. According to the invention, through a mode for the big data and the cloud environment, an alarm information total amount is automatically counted and monitored, an alarm information trend is analyzed and monitored, causes of alarm amount abnormal growth points are determined, and distribution of failure probability of each device of a whole network is analyzed. The method provided by the invention can be widely applied to an electric power company and a transformer station.

Description

technical field [0001] The invention belongs to the field of power system information technology, in particular to a substation intelligent alarm model method for big data and cloud environment. Background technique [0002] At present, a lot of equipment adopts the traditional regular inspection method. When there are potential unsafe factors in the equipment, the hidden dangers cannot be eliminated in time because the time for maintenance has not arrived; the equipment is in good condition, but it must be repaired when the time for maintenance has arrived, and there is a lot of blindness in the maintenance, resulting in waste of manpower and material resources. The effect is not good. Therefore, a substation intelligent alarm model method oriented to big data and cloud environment, according to the equipment status information provided by advanced status monitoring and diagnosis technology, judges the abnormality of the equipment, predicts the failure of the equipment, an...

AI Technical Summary

Problems solved by technology

When there are potential unsafe factors in the equipment, the hidden dangers cannot be eliminated in time because the maintenance time has not arrived; the equipment is in good condition, but it must be repaired when the maintenance time has come, and there is a lot of blindness in the maintenance, resulting in waste of manpower and material resources. The effect is not good

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