| With the increasing shortage of land for urban construction and the substantial increase in car ownership,the stereo garage has been developed rapidly,and many problems of operation maintenance have become increasingly serious.At present,most of the stereo garages are not connected to the Internet,using manual supervision,which is time-consuming and laborintensive,and the level of intelligence is low.In response to this situation,with the support of Primary Research and Developement Project of Jiangsu Province,a cloud Intelligent operation and maintenance system for stereo garage is developed in this thesis,including the development of fault diagnosis algorithms of garage motor,intelligent pedestrian detection algorithms based on video,and the realization of the server and client of the cloud intelligent operation and maintenance system,which improves the safety and reliability of the stereo garage,management efficiency and the level of intelligence.First,the needs of the stereo garage operation and maintenance system are analyzed in this thesis,the module of each service is determined,key algorithms and the development technology of cloud platform are combined,and the architecture and overall plan of the cloud intelligent operation and maintenance system for stereo garage are designed.Secondly,according to the fault diagnosis requirements of the stereo garage motor,the vibration signal of the motor is analyzed in the time and frequency domain,and then DBN is used to extract the depth characteristics of the vibration signal in the time and frequency domain.According to the characteristics of the positive and negative motor samples,the motor fault diagnosis model based on DBN-OCSVM is designed and implemented.Through the comparison experiment with PCA feature extraction algorithm,the accuracy of the model in the motor fault diagnosis for stereo garage is verified,and the operation safety of the stereo garage is improved.Then,according to the needs of pedestrian detection in the stereo garage,a pedestrian detection algorithm based on the frame difference method and YOLOv3 is proposed to improve the detection efficiency of pedestrian detection and reduce the computing pressure of the cloud server.First,the frame difference method is used to filter out the video clips with moving targets,and then the YOLOv3 pedestrian detection model is used in the filtered video.Through the comparison experiment with some pedestrian detection algorithms which are current used commonly,the efficiency and accuracy of the pedestrian detection method for the stereo garage are verified,and the reliability and management efficiency of the stereo garage are significantly improved.Finally,the cloud intelligent operation and maintenance server and client system for stereo garage are designed and implemented through the fusion of stereo garage motor fault diagnosis algorithm and video-based pedestrian detection algorithm,including garage overview,garage management,real-time monitoring,fault management,system management,statistical reports and maintenance services.System joint debugging and actual operation testing were carried out in the project partner company.The test results show that the cloud intelligent operation and maintenance system for stereo garage developed in this thesis significantly improves the level of intelligent management in the stereo garage. |
