Design And Implementation Of Temperature Monitoring Software System Based On Mobile AI Image Recognition

When the electrical equipment is running,the temperature will inevitably rise due to the thermal effect of current.The difference between the temperature of electrical equipment and the ambient temperature,namely,the temperature rise,is caused by the heating of the equipment itself.If the temperature rise exceeds a certain value,it indicates that the equipment may have abnormal conditions.If the fault is not handled and eliminated in time,the heating will accelerate the insulation aging of the equipment,and even damage the equipment.Therefore,temperature measurement is the main means for the inspection of electrical equipment defects by power inspectors.At present,the temperature measurement mainly depends on infrared detection technology,but in practical application,the detection equipment is expensive,the resolution is low,and the technical level of the detector is higher.This paper presents a method to establish machine learning intelligent recognition model based on visible light image to measure the temperature of equipment.In this paper,a temperature monitoring software system for electrical equipment is designed and implemented by using machine learning temperature identification model and facing the practical application of the method.Firstly,the paper determines the overall design scheme on the premise of fully analyzing the user’s function requirements and the specific requirements of artificial intelligence temperature detection system.The system deployed the machine learning model on the server,and realized the device temperature identification by using Android mobile phone to connect to the server over the network.Secondly,use Node.js to build the background environment of the server,which enables the machine learning model to recognize the temperature on the server,and connects the database to realize the storage of user information and temperature recognition records.Thirdly,the Android mobile app is developed,which enables users to take photos of electrical equipment,cut them and upload them to the server,and receive the returned results to complete the temperature recognition function after login successfully,and save the upload records locally for viewing.Finally,the application software of temperature monitoring management in the front of web page is developed.Users can visit the database to view and analyze the temperature data of the equipment,change and delete the data,use the new data to retrain the machine learning,and establish a new identification model to achieve better recognition effect.This paper has successfully realized the designed function,and has been running on the mobile phone and network,realizing the intelligent temperature monitoring.