The acoustic emission signal generated by the end face of mechanical seals is easy to be disturbed by the background noise in the transmission process, and it is difficult to separate from the background noise.The application of particle filter technology on monitoring the end face film thickness and open condition of mechanical seals by acoustic emission was studied.Acoustic emission sensor was installed in stationary ring seat of the mechanical seal to detect the contact condition indirectly of the dynamic and static rings.The collected acoustic emission signals were processed by particle filter, and the signal features of time domain, frequency domain and wavelet packet energy was extractedBP neural network model was established to identify the film thickness and open condition of mechanical seals.The result shows that the particle filter technology can effectively separate the signals of seal face from the background noise.By using BP neural network to identify the pattern of the extracted characteristic parameters, the indirect measurement of film thickness variation is achieved.The measurement result by this method is the same as the directly measurement result by eddy current sensor.