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.

Red Tide Information Extraction Based on Multi-source Remote Sensing Data in Haizhou Bay

[Objective] The aim was to extract red tide information in Haizhou Bay on the basis of multi-source remote sensing data.[Method] Red tide in Haizhou Bay was studied based on multi-source remote sensing data,such as IRS-P6 data on October 8,2005,Landsat 5-TM data on May 20,2006,MODIS 1B data on October 6,2006 and HY-1B second-grade data on April 22,2009,which were firstly preprocessed through geometric correction,atmospheric correction,image resizing and so on.At the same time,the synchronous environment monitoring data of red tide water were acquired.Then,band ratio method,chlorophyll-a concentration method and secondary filtering method were adopted to extract red tide information.[Result] On October 8,2005,the area of red tide was about 20.0 km2 in Haizhou Bay.There was no red tide in Haizhou bay on May 20,2006.On October 6,2006,large areas of red tide occurred in Haizhou bay,with area of 436.5 km2.On April 22,2009,red tide scattered in Haizhou bay,and its area was about 10.8 km2.[Conclusion] The research would provide technical ideas for the environmental monitoring department of Lianyungang to implement red tide forecast and warning effectively.

Pre-and postoperative changes of regional cortical cerebral blood flow in patients with cerebral arteriovenous malformation

Objective To investigate pre- and postoperative changes of regional cerebral cortical blood flow in patients with cerebral arteriovenous malformation. Method Twenty-two adult patients with arteriovenous malformation(AVM) were recruited into this study at Beijing Tiantan Hospital from September 2001 to May 2002. Eight patients had giant cerebral AVM and the other 14 had a small one. Cortical cerebral blood flow (CBF) was measured by laser Doppler flowmetry (LDF) before and after AVM resections. After surgery,the probe of LDF was implanted adjacent to the area of AVM and monitored for 24 hours.Results CBF increased significantly after the resection in all patients regardless of AVM size. In patients with small AVM,CBF returned to the baseline level within 4 hours,but in patients with giant AVM,CBF remained high even after 24 hours.Conclusions Monitoring CBF is helpful to understand pre- and postoperative changes of regional cortical CBF in patients with cerebral AVM.