| Poor lubrication between mechanical equipment may cause serious accidents,and timely detection of lubricants in mechanical equipment is of great significance.The use of hyperspectral data analysis and processing technology for oil detection has not only strong anti-interference,but also high sensitivity.The study of oil detection technology based on the principle of hyperspectral analysis and the construction of an oil detection system can quickly and efficiently obtain parameter information in the oil,which has important theoretical significance and practical value.This paper designs and implements an oil detection system based on hyperspectral acquisition and analysis technology.First of all,this article introduces the development status and existing problems of oil detection technology in detail,and establishes the research direction of this article.Secondly,based on the hyperspectral data collected by the Insion model spectrometer,starting from the oil hyperspectral data detection algorithm,the advantages and disadvantages of each algorithm are analyzed,and the regression model of oil parameter detection is realized.Then,starting from the demand analysis of the oil detection system,the overall scheme of the system was designed,the system hardware was selected and built,and the software system was developed.In order to satisfy that the detection system runs in the embedded Linux operating system,the Qt development environment is selected and the system software is developed in C++ language;in order to meet the remote operation,this paper uses Java language in the Android Studio development environment to develop an APP based on the Android mobile phone client software.The software system can realize the functions of hyperspectral data collection,data processing,data transmission,data calculation and display.The system test results show that the hyperspectral oil detection system has the advantages of real-time,fast and convenient.The test software has sound functions and convenient operation,which fulfills the expected functional requirements. |