Research And Design Of Equipment Information Inspection System Based On Wifi Positioning

Iron and steel production site runs many kinds of machinery,electrical and instrumentation equipment.So maintaining the equipment running normally has a great meaning to the production.And the equipment inspection is an important part to ensure the stable running of the equipment.Now most of the iron and steel enterprises still use the paper to record the result of inspection.This traditional method is not only inefficient but also difficult for people to analyze the inspection data.And it’s not easy to notify the maintenance staff timely when an exception is found.Furthermore,it’s also difficult to establish a supervision system on the work of equipment inspection,affecting the credibility of inspection adversely.Combined with the project of “Intelligent equipment inspection management”,an equipment information system is designed in this paper to solve the above problems.And the system uses C/S structure as the software system,including a background server and an inspection client.The server uses a standard SSH framework while the client is based on the Android platform.Http and Websocket protocol are used to achieve data communication between server and client.In addition,the main functions of this system include inspection data uploading,notification of equipment exceptions,safety supervision of equipment maintenance,internal communication and so on.With all the functions,the system has achieved a closed loop of equipment inspection.As a result,it has successfully improved the intelligence and information level of iron and steel enterprises’ equipment inspection,guaranteeing the progress of production.On the basis of the completed function,a more accurate indoor positioning system is needed to strengthen the supervision of the staff as well as provide more accurate location based information services.Thus,an indoor location method based on multi classifier ensemble learning has been proposed in this paper.The positioning process of this method is divided into two stages.The first stage is based on the method of homogeneous classifiers ensemble,using random forest algorithm to get the first positioning point under Wifi environment.Then,from the perspective of heterogeneous classifiers ensemble,a Bluetooth positioning system is used as gating system in which the second positioning points is acquired through an improved weighted k-nearest neighbor algorithm.Finally,fuse these two points on decision layer to get a more accurate positioning result.To verify the validity of the proposed method,an experimental environment has been built up and the fingerprint data of Wifi and Bluetooth has also been collected respectively.A series of classical fingerprint positioning algorithms are carried out as comparative experiments.And the results demonstrate that the proposed method exhibits remarkable advantages in positioning accuracy and anti-interference ability.At last,the proposed method is applied to form the final equipment inspection system based on Wifi positioning.