Aircraft Electrical Circuit Board Infrared Thermal Imaging Intelligent Fault Detection

Airborne equipment inspection and maintenance is an important link of the civil aviation industry, in a timely and accurate for detection of aircraft components is important guarantee of the civil aviation flight safety, the electronic board maintenance is an important part among them. However, the traditional detection methods due to the low efficiency, high complexity, and the contact detection method will cause certain damage to precision circuit board. This method can't well adapt to the development of civil aviation industry in China. Therefore, only a highly efficient, noncontact, intelligent detection method can meet the requirements of intelligent, accurate and resource saving in airborne electronic equipment repair.Infrared thermal imaging technique as a method for no contact fault detection method is more and more used in various fields because of its no physical contact, simple operation and intuition. At the same time, the research of artificial intelligence technology is gradually mature, and applied in many fields. A kind of intelligent second-order integration support vector machine(SVM) fault detection infrared thermal imaging is proposed through a combination of the above two kinds of technology. This method judge the working state for the single time point temperature information matrix of circuit board, then match a series of state number composed of the characteristic curves, thus obtain the final fault location. The traditional method and the second-order system are compared. In the part of intelligent information processing, the results of discrimination between SVM and traditional machine learning method are compared, at the same the optimization algorithm is joined in the selection of SVM parameter in order to further improve its accuracy.