Abstract: An intrinsic process signal-based online expulsion detection method for resistance spot welding process, which comprises: acquiring the intrinsic process signal and current signal output by sensors installed at two electrodes in real-time during the welding process and establishing a relationship graph; performing expulsion judgement based on the relationship graph to obtain expulsion frequency, single intrinsic process signal feature and an accumulated feature; calculating expulsion metal volume according to the accumulated feature and electrode profile features to obtain a prediction expulsion metal amount. The method performs online prediction of the expulsion metal amount according to the intrinsic process signal for resistance spot welding process, thereby achieving online quantitative estimation of the expulsion intensity, overcoming the defect of the traditional technology which relies on manual detection, and improving detection efficiency and accuracy.

Abstract: The present invention discloses a four-double working method for danger assessment and prediction of water inrush in a roof aquifer of a coal seam, and belongs to the coal mining field. The method includes: calculating a water abundance index and/or a danger index of water inrush of a roof of a to-be-mined coal seam according to position classification of the roof of the to-be-mined coal seam; and obtaining a water inrush assessment result of the roof of the to-be-mined coal seam according to the water abundance index and/or the danger index of water inrush of the roof of the to-be-mined coal seam and excavation area position information of the roof of the to-be-mined coal seam. The present invention resolves the problem that current water abundance assessment and danger assessment and prediction of water inrush are complex and inaccurate.