9 results about "Component video" patented technology

The invention relates to a wind turbine generator fault diagnosis method based on audio and video recognition, which comprises the following steps of: firstly, installing a pan-tilt camera and a microphone array at a specific position, calibrating the position of each component, and simultaneously monitoring by adopting two modes: in the first mode, carrying out audio and video fault diagnosis and round inspection on large components in a cabin, and according to the position of each large component, carrying out fault diagnosis and round inspection on the large components; performing specific large component video and area enhanced audio data acquisition, and using audio and video algorithms for timing diagnosis; in the second mode, for abnormal sound recognition, spatial position information of a sound source is obtained by means of a cooperative acquisition mechanism of multiple microphones and a sound source positioning technology of a sound array, accurate resolving of the sound source direction is completed, sound position positioning of a large part in a closed space in a cabin of the wind turbine generator is achieved, and a pan-tilt camera is called to shoot the abnormal sound position; and fault diagnosis is carried out, so that operation and maintenance personnel can carry out processing in time to avoid great economic loss.

To provide a method of video processing which performs coding or decoding by using cross-component linear model prediction, and a video processing apparatus.SOLUTION: The method of video processing includes determining, for a conversion between a video block of a video and a bitstream of the video, a parameter of a cross-component linear model (CCLM) for the video block according to a rule, and performing the conversion based on the determining. The rule specifies to use a variable representing a neighbouring luminance sample in the determining of the parameter of the CCLM only in a case that the variable has a certain value.SELECTED DRAWING: Figure 18

The invention relates to the technical field of photovoltaic fault diagnosis, in particular to a photovoltaic fault diagnosis method, system, equipment and medium based on big data analysis, and the method comprises the steps: obtaining meteorological data, thermal image data, power generation data, sensor data and component video data based on a big data platform; performing big data analysis by adopting a deep learning algorithm according to the meteorological data, the thermal image data, the power generation data, the sensor data and the component video data to obtain a group of photovoltaic component data and a group of component data; inputting the photovoltaic module data and the component data into the trained fault diagnosis model, and performing fault diagnosis, fault prediction and fault early warning on the photovoltaic module and the key device to obtain fault diagnosis results of the photovoltaic module and the key device; and the fault diagnosis model adjusts the data feature weight according to the real-time data. The method can perform accurate fault diagnosis on the photovoltaic module and the device.

Video processing methods, systems, and apparatuses are described. An example method includes performing a conversion between a block of a video and a bitstream of the video according to a rule. The rule specifies that whether a syntax element identifying a deblocking offset for a chroma component of the video is included in a video region level is determined based on a color format of the video.

A method of video processing includes determining, for a conversion between a video region of a component of a video and a bitstream representation of the video, a maximum allowed block size for a video block coded using a transform skip mode, and performing the conversion based on the determination.

The coding efficiency of a multi-component picture or video coding concept is improved by reconstructing a third component signal relating to a third component of the multi-component video using inter-component prediction from both a reconstructed first component signal and a reconstructed second component signal.

A video processing method includes: for conversion between a chroma block of a video and a bitstream representation of the video, deriving parameters of a cross-component linear model by using downsampled luminance samples, the downsampled luminance samples being generated from N upper neighboring lines of a co-located luminance block of the chroma block using a downsampling filter, where N is a positive integer; and performing the conversion using a predicted chroma block generated using the cross-component linear model.

To provide a multi-component picture or video coding concept that enables higher coding efficiency.SOLUTION: In an encoder 100, the coding efficiency of a multi-component picture or video coding concept is improved by reconstructing a third component signal 30 relating to a third component of the multi-component video using inter-component prediction from a reconstructed first component signal 22 and a reconstructed second component signal 26.SELECTED DRAWING: Figure 3

The invention provides a gateway quality determination method and device, equipment and a medium, and relates to the technical field of computers. The method comprises the following steps: firstly, acquiring target vibration data for performing a vibration test on an internal component of a target gateway and a target component video formed by monitoring the process of performing the vibration test on the internal component; secondly, through a semantic mining unit in a target quality determination network, respectively performing semantic mining on the target vibration data and the target component video to form vibration semantic features and component semantic features; then, semantic enhancement is carried out on the component semantic features based on the vibration semantic features through a semantic enhancement unit, and enhanced component semantic features are formed; and finally, through a quality determination unit, based on the semantic features of the enhanced component, determining target quality data. Based on the content, the problem that the reliability of gateway quality determination is relatively low in the prior art can be improved.