In situ monitoring methods for selective laser melting additive manufacturing process based on images-A review

Selective laser melting(SLM)has been widely used in the fields of aviation,aerospace and die manufacturing due to its ability to produce metal components with arbitrarily complex shapes.However,the instability of SLM process often leads to quality fluctuation of the formed component,which hinders the further development and application of SLM.In situ quality control during SLM process is an effective solution to the quality fluctuation of formed components.However,the basic premise of feedback control during SLM process is the rapid and accurate diagnosis of the quality.Therefore,an in situ monitoring method of SLM process,which provides quality diagnosis information for feedback control,became one of the research hotspots in this field in recent years.In this paper,the research progress of in situ monitoring during SLM process based on images is reviewed.Firstly,the significance of in situ monitoring during SLM process is analyzed.Then,the image information source of SLM process,the image acquisition systems for different detection objects(the molten pool region,the scanned layer and the powder spread layer)and the methods of the image information analysis,detection and recognition are reviewed and analyzed.Through review and analysis,it is found that the existing image analysis and detection methods during SLM process are mainly based on traditional image processing methods combined with traditional machine learning models.Finally,the main development direction of in situ monitoring during SLM process is proposed by combining with the frontier technology of image-based computer vision.

Evolutionary processes and sources of high-nitrate haze episodes over Beijing,Spring

Rare and consecutive high-nitrate haze pollution episodes were observed in Beijing in spring2012. We present detailed characterization of the sources and evolutionary mechanisms of this haze pollution, and focus on an episode that occurred between 15 and 26 April. Submicron aerosol species were found to be substantially elevated during haze episodes, and nitrates showed the largest increase and occupation（average： 32.2%） in non-refractory submicron particles（NR-PM1）, which did not occur in other seasons as previously reported. The haze episode（HE） was divided into three sub-episodes, HEa, HEb, and HEc. During HEa and HEc, a shallow boundary layer, stagnant meteorological conditions, and high humidity favored the formation of high-nitrate concentrations, which were mainly produced by three different processes —daytime photochemical production, gas-particle partitioning, and nighttime heterogeneous reactions — and the decline in visibility was mainly induced by NR-PM1.However, unlike HEa and HEc, during HEb, the contribution of high nitrates was partly from the transport of haze from the southeast of Beijing — the transport pathway was observed at ~800–1000 m by aerosol Lidar —and the decline in visibility during HEb was primarily caused by PM（2.5）. Our results provide useful information for air quality improvement strategies in Beijing during Spring.