Abstract: A digital and informationized fully-automatic aluminum thermal-spraying production line includes: an automatic feeding system including first transfer mechanisms and first carrying conveying mechanisms; a laser cleaning system including a laser cleaning tank, laser cleaning nozzles and cleaning conveying mechanisms; a first transfer system including second carrying conveying mechanisms and second transfer mechanisms; an aluminum thermal-spraying system including traveling mechanisms, turning mechanisms and an aluminum spraying mechanism, the traveling mechanisms being configured to convey workpieces on the second carrying conveying mechanisms onto the turning mechanisms one-by-one, the turning mechanisms being configured to turn the workpieces by a preset angle, and the aluminum spraying mechanism being configured to perform aluminum arc-spraying on the workpieces.

Abstract: A non-intrusive load identification method based on the Power Fingerprint characteristics of the load is provided. The method includes: S1, collecting Power Fingerprint characteristic data of several loads of the same type; S2, after preprocessing Power Fingerprint characteristic data of load, establishing convolution neural network based on attention mechanism to learn load characteristics; S3, using sliding time window algorithm to realize load switching event detection, In order to extract the change of electrical data of user bus before and after the switching event, the non-intrusive load identification problem is converted into the single load identification problem; S4, the load identification is realized, and the extracted electrical information features of single load are identified using the trained model.