A wind farm supervision monitoring method includes: displaying, by a user interface (UI) unit, a location of the site server on a map along with a dashboard menu, a navigation menu, and an alarm & event menu; collecting, by a data collection unit, data about status monitoring of each wind turbine from the site server; detecting, by an abnormality status detection unit, an abnormality status of each wind turbine based on the data about the status monitoring of each wind turbine and issuing an alarm based on the detecting the abnormality status; providing, by a supervision unit, a turbine operation status of each wind turbine using the dashboard menu, managing operation and maintenance; and establishing, by the supervision unit, an operation and maintenance plan for the detected abnormality status of the wind turbine.

Wind farm supervision monitoring method

The example systems, methods, and devices disclosed herein generally relate to performing predictive analytics on behalf of wind turbines. In some instances, a data-analytics platform defines and executes a predictive model for a specific wind turbine. The predictive model may be defined and executed based on operating data for the specific wind turbine and for other wind turbines that experience similar environmental conditions as the specific wind turbine and that are operating in an expected operational state. In response to executing the predictive model, the data-analytics platform may cause an action to occur at the specific wind turbine or cause a user interface to display a representation of the output of the executed model, among other possibilities.

Computer System & Method for Predicting an Abnormal Event at a Wind Turbine in a Cluster

The invention provides an on-line state monitoring and failure diagnosing method of a wind turbine generator set. The on-line state monitoring and failure diagnosing method comprises the following steps: adopting an unscented Kalman method for processing SCADA data serving as the state variables, input quantity and measuring quantity to acquire the current predicted value of the state variables; calculating the difference value between the current predicted value of the state variables and the measured value of the state variables in the SCADA data to serve as a first difference value; and when the first difference value exceeds the threshold value, judging that the current alarm failure needs to be handled. According to the on-line state monitoring and failure diagnosing method of the wind turbine generator set, the data collection quantity is small, failures of the wind turbine generator set can be detected on line and in real time, the reliability is high, and the operating cost is low.

On-line state monitoring and failure diagnosing method of wind turbine generator set

The invention discloses a household electric appliance, a fault diagnosis system thereof, a method and a server. The fault diagnosis system comprises the household electric appliance and the server, wherein communication is performed between the household electric appliance and the server. The household electric appliance comprises an acquisition module which is used for acquiring operation parameter information of the household electric appliance and transmitting the operation parameter information to the server through communication between the household electric appliance and the server. A fault database is stored in the server. The service is used for receiving the operation parameter information and analyzing the operation parameter information according to the fault database for analyzing whether a fault of the household electric appliance occurs, generating fault information when the fault of the household electric appliance occurs and transmitting the fault information to the household electric appliance for presenting the fault information to the user through the household electric appliance. The fault diagnosis system according to the invention can conveniently and effectively diagnose whether the fault of the household electric appliance occurs and transmits the fault information to the user when the fault occurs.

Household electric appliance, fault diagnosis system thereof, method and server

The invention discloses a state management method for a substation inspection robot, which comprises steps of extracting inspection data of an inspection robot within a preset time period; dividing the inspection data into the preset number of types according to difference in influence on the safety operation of the inspection robot; separately calculating the scores of the preset number of typesof the inspection data and adding them to obtain a total score; and prompting the total score. The invention provides a complete and reliable state management method for the inspection robot, the total score of the state evaluation of the inspection robot obtained by the method is relatively accurate, and when the state of the inspection robot is found to be poor by the total score, the staff cancarry out real-time maintenance to prevent large faults in the inspection robot and reduce safety hazards. The invention also discloses a state management device and equipment for a substation inspection robot, which has the same beneficial effects as the state management method above.

State management method, device and equipment for substation inspection robot

Provided is a wind power generation management apparatus including: a collection unit configured to collect first data generated in a wind power plant; a fault occurrence prediction unit configured to compare the collected first data with a predefined normal state model, to create a second data indicating a state of the wind power plant based on a result of the comparison, and to predict occurrence of a fault in the wind power plant according to the second data; and a maintenance plan establishment unit configured to estimate an operating time corresponding to a time from a start of the wind power plant until the fault occurs, and to generate a maintenance plan which can be performed for the fault during the estimated operating time.

Jong Duk Son

Papers

Wind power plant management system and method thereof