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Satellite positioning and static leveling-based layered settlement monitoring system and method

The invention discloses a satellite positioning and static leveling-based layered settlement monitoring system and method. The system comprises a base station, a monitoring station which is arranged in a settlement monitoring area and a monitoring center which communicates with the monitoring station, wherein the base station communicates with the monitoring station; the monitoring station comprises an observation pillar, a second Beidou satellite signal receiver mounted on the observation pillar, a data transmission unit, a plurality of layered settlement marks and a static level system; the static level system comprises a plurality of static level gauges; each layered settlement mark is provided with one static level gauge; one of the static level gauges is arranged on the observation pillar. The method comprises the following steps: I, setting of the monitoring system; II, data acquisition and transmission; III, data processing and analysis. According to the satellite positioning and static leveling-based layered settlement monitoring system and method, the calibration and correction problems of the instable working base points during the static leveling can be effectively solved, and the long-term, remote and real-time monitoring for the layered settlement deformation of the geologic bodies can be realized.
Owner:CHINA JK INST OF ENG INVESTIGATION & DESIGN

Predication method and device for top-oil temperature of transformer based on error predicting amendment

The invention discloses a predication method and device for top-oil temperature of a transformer based on error predicting amendment, pertaining to the on-line monitoring field of the transformer. The method comprises following steps: obtaining a prediction dataset comprising load current and ambient environment of the transformer; using load current of the transformer at the current moment as input amount, utilizing a Susa thermal circuit model to predict top-oil temperature of the transformer in order to obtain top-oil temperature prediction value of the Susa thermal circuit model; normalizing top-oil temperature prediction value of the Susa thermal circuit model and the prediction dataset; using the normalized top-oil temperature prediction value of the Susa thermal circuit model and the prediction dataset as input amount and utilizing a GA-KEDLM model to make a regression forecast to obtain prediction errors; carry out anti-normalization operation on regression prediction errors; using prediction value of top-oil temperature of the Susa thermal circuit model before normalization to delete the regression prediction errors after anti-normalization operation in order to obtain top-oil temperature prediction value corrected by the transformer. The predication method and device for top-oil temperature of the transformer based on error predicting amendment are capable of accurately predicting top-oil temperature of the transformer.
Owner:SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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