2results about How to "With early warning function" patented technology

The invention relates to the technical field of hydrological monitoring and computer vision, in particular to a hydrological station flow monitoring system and method based on deep learning, and the method comprises the steps: synchronously collecting the water level time sequence data of a river section and a video key frame flow containing water surface texture; converting the water level time sequence data into a corresponding water passing area numerical value and a hydraulic radius numerical value; outputting a flow state feature vector representing the dispersion degree of the water surface flow velocity; outputting a physical parameter vector changing along with time; calculating a moving average value of the river course roughness coefficient in a preset time window; judging whether the moving average value is greater than a preset siltation alarm threshold value or not; if the judgment result is yes, generating a river deposition early warning data packet and sending the data packet to a remote monitoring terminal; otherwise, generating a state log of normal operation of the river channel and storing the state log into the local database; the limit that a traditional flowmeter can only output numerical values is broken through, and a key diagnosis basis is provided for operation and maintenance and flood control decision making of a hydrological station.

The application discloses a method for detecting activated sludge state based on settling image texture entropy change characteristics, which comprises the following steps: measuring and controlling sludge concentration of a sludge-water mixture sample; placing the sample in a transparent container to make the sludge in a suspended state; fixing the position and focal length of a camera to shoot a video of the activated sludge settling process; cutting a plurality of activated sludge settling images from the video of the activated sludge settling process to obtain an image set; cutting the image set at a proper position; performing pretreatment operation on the cut image set to calculate data of texture entropy change with time at a plurality of different heights; drawing the data into a settling image entropy change hologram; calculating the slope and slope direction of the matrix formed by the settling time, settling height and image texture entropy; drawing a polar coordinate scatter plot of the slope and slope direction data to calculate the normalized sedimentation separation time, normalized clarification degree and normalized compression degree; and analyzing the activated sludge state.