Sunday, July 26, 2009

桌上型機器人鎖螺絲機 精度高

可台公司新推出桌上型機器人鎖螺絲機,擁有多項特點,使用XY TABLE鎖付螺絲,精度高,操作簡單,採用液晶教導盒操作,可視XY座標數值,程式記錄容量大,至少可存99組,每組4,000點,重覆精度高 (±0.02mm),鎖付範圍內(300×300mm),可同時擺放多個工件,且一位工作人員可同時操作多台鎖付機,採用氣吹式,將螺絲吹至夾頭前端,可 以迅速鎖付,無需浪費其他位移時間,因為沒有回程吸取螺絲,所以比氣吸方式快1倍鎖付時間以上,並具有滑牙檢知功能,所以可以檢知螺絲是否鎖付完成,該機 台為投資最少,效率最高,回收最快,鎖付螺絲的利器。

Friday, July 03, 2009

Thursday, July 02, 2009

[Robotics & Machine Learning] New analytical science findings from C.C. Ho and co-authors described

Robotics & Machine Learning

New analytical science findings from C.C. Ho and co-authors described

2009 APR 20 - ( -- According to a study from Taiwan, "This paper proposes a novel real-time machine video-based flame and smoke detection method that can be incorporated with a surveillance system for early alerts. Automatic monitoring systems use the motion history detection algorithm to register the possible flame and smoke position in a video and then analyze the spectral, spatial and temporal characteristics of the flame and smoke regions in the image sequences."

"The spectral probability density is represented by comparing the flame and smoke color histogram model, where HSI color spaces are used. The spatial probability density is represented by computing the flame and smoke turbulent phenomena with the relation of perimeter and area. Statistical distribution of the spectral and spatial probability density is weighted with the fuzzy reasoning system to give the potential flame and smoke candidate region. The temporal probability density is represented by extracting the flickering area with level crossing and separating the alias objects from the flame and smoke region. Then, the continuously adaptive mean shift (CAMSHIFT) vision tracking algorithm is employed to provide feedback of the flame and smoke real-time position at a high frame rate," wrote C.C. Ho and colleagues.

The researchers concluded: "Experimental results under a variety of conditions show that the proposed method is capable of detecting flame and smoke reliably."

Ho and colleagues published their study in Measurement Science & Technology (Machine vision-based real-time early flame and smoke detection. Measurement Science & Technology, 2009;20(4):45502).

For more information, contact C.C. Ho, National Yunlin University Science & Technology, Dept. of Mech Engineering, Yunlin 64002, Taiwan.

Publisher contact information for the journal Measurement Science & Technology is: IOP Publishing Ltd., Dirac House, Temple Back, Bristol BS1 6BE, England.

Keywords: Emerging Technologies, Fuzzy Logic, Machine Learning, Machine Vision, Measurement Science.

This article was prepared by VerticalNews Robotics & Machine Learning editors from staff and other reports. Copyright 2009, VerticalNews Robotics & Machine Learning via