Abstract: The present disclosure provides an optical integrated device and an optical time domain reflectometer. The optical integrated device includes: a packaging outer shell, a first collimator, an optical splitting device, a circulator assembly and a second collimator. The optical splitting device is provided close to the first collimator, is used to reflect a part of the detecting light from the first pigtail and couple the part of the detecting light to the third pigtail, and allows the other part of the detecting light to pass through the optical splitting device. The circulator assembly is provided close to the optical splitting device, the circulator assembly is used to couple the detecting light passing through the optical splitting device to the second pigtail, and couple the detecting light returned from the second pigtail to the third pigtail.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: Provided are a cutting method, apparatus and system for a point cloud model. In an embodiment, the method includes: using one two-dimensional first cutting window to select a point cloud structure comprising a target object from among one point cloud model; adjusting the depth of the first cutting window, the length, width and depth of the first cutting window constituting one three-dimensional second cutting window, the target object being located in the second cutting window; identifying and marking all point cloud structures in the second cutting window to form a plurality of three-dimensional third cutting windows, the target object being located in one of the third cutting windows; and calculating the volume ratio of the point cloud structure in each third cutting window relative to the second cutting window, and selecting the third cutting window having the largest volume ratio.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: Various embodiments include a method for a robot to grab a 3D object. The method may include: determining a current position and attitude of a visual sensor of the robot relative to the 3D object; acquiring a grabbing template of the 3D object, the grabbing template comprising a specified grabbing position and attitude of the visual sensor relative to the 3D object; judging whether the grabbing template further comprises at least one reference grabbing position and attitude of the visual sensor relative to the 3D object, wherein the reference grabbing position and attitude is generated on the basis of the specified grabbing position and attitude; and based on a judgment result, using the grabbing template and the current position and attitude to generate a grabbing position and attitude of the robot.

Abstract: Various embodiments include a semantic-based causal event probability analysis method. The method may include: generating a cause event instance and corresponding effect event instances thereof according to user requirements and based on a cause event template and an effect event template; assigning each cause event or effect event instance to a parent node, wherein the event instance comprises a plurality of entities and a mutual relationship between the entities; and calculating a probability of a cause event instance or an effect event instance having a common parent node. A probability that a first cause event instance causes a first effect event instance equals: P R E 1 R C E 1 C = P C E 1 R R E 1 C ? P R E 1 R P C E 1 C P(CE1(R) |RE1(C)) represents a probability of the first cause event occurring when the first effect event occurs. P(RE1(R)) represents a probability of the first effect event occurring among all effect events.

Abstract: Various embodiments of the teachings herein include a method for building a graph-based industrial flow model. The method may comprise: importing a set of entities based on an industrial flow including a user-defined entity and a system-defined entity; querying the model for the user-defined entity, and if found, obtaining a connection of the user-defined entity, otherwise generating a new implementation layer; querying the model for an implementation layer of the user-defined entity, and if found, obtaining a connection of the implementation layer of the user-defined entity, otherwise generating a new implementation layer; querying the model for the system-defined entity, and if the system-defined entity is found, obtaining a connection of the system-defined entity, otherwise generating a new implementation layer; and iteratively performing the above queries until a final graph-based model for the industrial flow results.

Abstract: Provided are a cutting method, apparatus and system for a point cloud model. In an embodiment, the method includes: using one two-dimensional first cutting window to select a point cloud structure comprising a target object from among one point cloud model; adjusting the depth of the first cutting window, the length, width and depth of the first cutting window constituting one three-dimensional second cutting window, the target object being located in the second cutting window; identifying and marking all point cloud structures in the second cutting window to form a plurality of three-dimensional third cutting windows, the target object being located in one of the third cutting windows; and calculating the volume ratio of the point cloud structure in each third cutting window relative to the second cutting window, and selecting the third cutting window having the largest volume ratio.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: A point cloud model reconstruction method, apparatus, and system are disclosed. In an embodiment, the method includes randomly selecting four non-coplanar reconstruction points in a point cloud model; iteratively selecting other reconstruction points successively until a reconstruction condition is met, and reconstructing the point cloud model based on all reconstruction points. A reduction degree of a reconstructed point cloud model is: Reward=?k·(PointNum?4)+g·VolRate, where PointNum represents a number of current selected reconstruction points, VolRate represents a ratio of a volume of a solid shape, k represents a proportion of the number of the selected points, and g represents a proportion of the volume ratio. The reconstruction method further includes adjusting a ratio of g to k based on user requirements to adjust the reconstruction condition.

Abstract: The present invention provides a point cloud model reconstruction method, apparatus, and system. The method includes the following steps: randomly selecting four non-coplanar reconstruction points in the point cloud model; keeping iteratively selecting other reconstruction points successively until a reconstruction condition is met, and reconstructing the point cloud model based on all reconstruction points, where a reduction degree of the reconstructed point cloud model is: Reward=?k·(PointNum?4)+g·VolRate, where PointNum represents a number of current selected reconstruction points, VolRate represents a volume ratio of a volume of a solid shape formed by all of the current reconstruction points to an original volume of the point cloud model, k represents a proportion of the number of the selected points in the reduction degree, and g represents a proportion of the volume ratio in the reduction degree.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: The present invention discloses a detection method, a synchronization method, and a terminal for a symmetrical synchronization signal. The detection method includes the following steps: obtaining a received signal of a synchronization signal for synchronous detection, and subsequently, performing an auto-correlation calculation on the received signal twice in the time domain, where the received signal includes a first-part received signal whose length is N and a second-part received signal whose length is NCP, the first-part received signal is symmetrical about a first central point, and the second-part received signal is symmetrical about a second central point. With low complexity of calculation and good detection performance, and being insensitive to a carrier frequency offset (CFO), the present invention is particularly applicable to an Internet of Things (IoT) environment.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.

Abstract: A method and apparatus for forecasting output power of wind turbine in a wind farm. The present invention provides a method for forecasting output power of a wind turbine in a wind farm, including: generating a corrected data set based on environmental data collected from at least one sensor in the wind farm; correcting a weather forecasting model by using the corrected data set; obtaining a forecast value of wind information at the wind turbine based on the corrected weather forecasting model; and forecasting the output power of the wind turbine based on the forecast value and a power forecasting model.

Abstract: The present invention discloses a cell clustering method, used to classify multiple small cells into N clusters and including the following steps: based on throughputs, respectively placing N small cells having a largest interference with each other into the N clusters to initialize the clusters; and based on the throughputs, separately adding a small cell having a smallest interference with the clusters into the clusters, and repeating the step until all the small cells are allocated into the clusters. The present invention further discloses a spectrum overlapping multiplexing method based on the cell clustering method. According to the present invention, the cell system average spectral efficiency and the cell edge spectral efficiency in an ultra dense network can be improved.

Abstract: A mechanism is provided for forecasting air pollution. One or more air-pollution monitoring stations correlated to a forecasting point from a plurality of air-pollution monitoring stations are identified. For the one or more air-pollution monitoring stations that correlate to the forecasting point, one or more patterns of the forecasting point, historical patterns of the forecasting point relating to the one or more patterns of the forecasting point, and one or more patterns of the air-pollution monitoring stations that relate to the one or more patterns of the forecasting point are identified. Based on the one or more patterns of the forecasting point, the historical patterns of the forecasting point relating to the one or more patterns of the forecasting point, and the one or more patterns of the air-pollution monitoring stations that relate to the one or more patterns of the forecasting point, a pollution forecast is provided.

Abstract: The present invention relates to a method and apparatus for controlling a wind turbine. The method includes: dividing a plurality of wind turbines into at least one group based on a similarity in status information of the plurality of wind turbines; in response to having detected a fault in a first wind turbine of the plurality of wind turbines, searching a group to which the first wind turbine belongs for a second wind turbine matching status information of the first wind turbine; and controlling the first wind turbine based on parameters from the second wind turbine.