Research On Automatic Alarm Technology Of Machine Tool Based On Machine Vision

With the rapid development of economy,frequent fires have resulted in huge losses in the process of industrial production.Although traditional fire detection sensors have important significance for fire prevention,they have many limitations,especially in the complex factory production environment.In order to solve the drawback of the traditional sensor in some environments,Many domestic and foreign scholars have studied the algorithm of fire detection.The work of this paper in fire detection technology is as follows:(1)Review the the development status of fire detection technology,the drawbacks of traditional fire detection technology are analyzed.Then the development of machine vision fire detection at home and abroad is analyzed,and the video image detection algorithm is introduced.Finally we draw conclusions that it cannot adapt well to all kinds of geological condition.(2)Research on the color detection algorithm,moving object detection algorithm and infrared spectrum flame detection algorithm.The color detection algorithm is based on the principle of statistics.The moving object detection mainly includes the difference frame,the optical flow method and the Gaussian background subtraction algorithm.Those will be studied in depth and mathematical derivation will be conducted.(3)Based on these algorithms,a fire flame detection method is developed by combining both background subtraction and region covariance.The color distribution method and background model with an adaptive background learning model are used to preprocess the image firstly.We then extract the space-temporal covariance matrix,which is used to fuse all the discriminative cues together.Finally we use support vector machine to classify fire scene.And compared with the existing algorithm.(4)Based on the requirements of machine tools,we develop a system about vision detection.Which includes the system structure,software system and hardware system.The software system has been tested in the Beijing Institute of Electrical.After testing,the software system algorithm is reliable and the high rate of detection.Which is able to meet the needs of the field of electric machine tools.The paper develops a fire detection method,which combines background subtraction algorithm and space-temporal covariance matrix.Finally,support vector machine is used to classify the video data to obtain the flame region.Finally we develop a machine vision system for machine tool to detect flame in Beijing Institute of Electrical Engineering.