Vertical Elevator Screw Fault Detection System Based On Image Processing

With the continuous popularization of automation technology,the combination of various industries and automation technology has significantly improved production efficiency.But there are some traditional industries using traditional methods.Technologies such as fault diagnosis and maintenance of mechanical equipment in the production process still use traditional methods and rely on experienced employees to make judgments.Take the vertical hoist widely used in factories as an example.In some factories,the detection of loose screws on vertical hoists is still judged by human eyes,and the accuracy is naturally not as accurate as that of machine equipment.If the employee misjudges,it is likely to cause an accident at the factory and affect production safety.It is therefore necessary to develop a system that automatically detects the failure of vertical hoist screws.This paper designed an automatic screw fault detection system based on image processing technology according to the requirements of vertical hoist screw failure detection in a cement factory in Guizhou.The system is mainly divided into two parts: server and client.The server runs on the industrial computer,and its main function is to obtain the photo of the vertical hoist screw through the camera,and use the image processing technology to identify the loose distance of the screw and the material bucket label,store it in the SQLite-based database,and listen to the client.The client is based on the human-computer interaction interface developed by QT to display the data transmitted from the server through the TCP/IP protocol,as well as real-time image viewing and data statistics.In this paper,the image processing algorithm was developed using the API of OpenCV3.3.Both client and server software run on the Windows platform.