The Research And Implementation Of Anomaly Detection System On High-speed Rail Catenary Insulator Based On Multi-core Parallel Technology

Insulators are important parts of Catenary suspension and supporting devices,which perform well in isolating live part and insulation part.However,due to the long working hours and poor working environment,insulators are prone to damaged and be contained with foreign matters.It might affect the performance of insulation,even cause tripping,and it makes great challenge to train operation safety.Above all,this paper introduces the machine learning theory and technology,the development history of multi-core parallel technology including Open MP development scheme.In addition,this paper introduces the related image processing and image recognition technology,including Gauss filter,edge extraction technology based on Canny operator,line extraction technology based on Hough Transform and several image similarity comparing technology.On this basis,combined with the need of insulator anomaly detection of the Railway Bureau,this paper use User Case Diagram to make the system requirements analysis and the overall design framework.This paper describes the design of database by means of the Entity Diagram and tables.Subsequently,this paper introduces the design and implementation of the five sub modules of the anomaly detection system.The five sub modules are image preprocessing module,machine learning module,anomaly detecting module,manual accurate detecting module and multi-core parallel detecting module.In image preprocessing module,this system filters the picture of excessive exposure or lack of exposure,and the picture of repeat shooting by extracting line information.Later,the system enhances the image.In machine learning module,by extracting the feature of sample pictures,the system does modeling of insulators.Through modeling results,the system creates cascade classifier of insulators,which is used to located the position of insulator in the picture.In anomaly recognition module,the system gets angle of deflection by Gabor filter.Furtherly,the system determines whether there is abnormal insulator by the means of gray level statistic.In manual accurate detecting module,the paper describes the process of detecting abnormal insulators manually which is designed by the method of sequence diagram.In multi-core parallel detecting module,this paper introduces the application of parallel technology in the system based on Open MP multi-core programming framework.Finally,this paper describes the development and testing environment.Besides,this paper analyzes the effect of each functional module of the system on the basis of different resolution images,different CPU cores and different application scenarios.Experiments show that the system can run efficiently on different CPU core computers.The system can detect anomaly of insulators automatically with higher processing speed and higher detection efficiency.The accurate detecting system is confirmed to has good human-computer interaction.