To solve the problem that traditional contact electric parameter fault detection methods are difficult to meet the maintenance requirement of increasingly complex electronic equipment, a temperature rising multi-feature method based on infrared thermography which can improve noncontact electrionic equipment abnormality detection is proposed. Firstly, on the basis of infrared and optical heterologous registration, the accurate position of each element in an electronic equipment is obtained. Then, the mean value curves of temperature rising in the central areas of each standard element and each element to be detected are obtained on the basis of the infrared images observed. After the curves are divided into multiple subsections, the temperature rising statistical vectors are extracted precisely. Secondly, the difference between the temperature rising statistical vector to be detected and the standard temperature rising statistical vector is calculated and normalized so as to construct the temperature rising multi-feature vector. Finally, according to the vector, the whole situation awareness of thermal abnormality of the equipment to be detected is implemented by segmental judgment and abnormal quantification. Compared with the traditional thermal abnormality detection method, the temperature rising multi-feature vector constructed can more precisely and robustly describe the variation of temperature rising. The experimental result shows that this method has the advantages of high accuracy and good real-time performance. It lays a foundation for the subsequent intelligent reasoning of electric circuit fault.