The traditional detection methods of SF6 decomposition components under partial discharge have some shortages，including consuming much detected gas，long detecting time，and unsuitable for on-line monitoring. While，photoacoustic spectroscopy has some advantages，including high sensitivity on detecting gas，and without consuming detected gas，etc. According to these reasons，the detection technology used in SF6 decomposition components under partial discharge is studied，and the feature spectrum of SO2，CO2 and CF4by SF6 decomposing is given. Through the photoacoustic spectroscopy device，the relation lines between photoacoustic spectroscopy(PAS) signal and concentration of gas components are obtained. The minimum detection limits of SO2，CO2 and CF4are about 3.8×10 -6，3.1×10 -6 and 4.7×10 -6 respectively. A method of RBF neural network is set up to reduce the crossover response of PAS signals of SO2，CO2 and CF4 mixed gas. It makes the average examination error of three gases reduce to 5.6%，1.6% and 3.3% respectively. Its reliability is checked by comparative testing of gas ehromatography and detector tube. The results indicate that the RBF neural network is useful in improving detection precision and provides a kind of technology to crossover response problem.