Research on Feature Extraction of Remnant Particles of Aerospace Relays

The existence of remnant particles, which significantly reduce the reliability of relays, is a serious problem for aerospace relays. The traditional method for detecting remnant particles—particle impact noise detection (PIND)—can be used merely to detect the existence of the particle; it is not able to provide any information about the particles’ material. However, information on the material of the particles is very helpful for analyzing the causes of remnants. By analyzing the output acoustic signals from a PIND tester, this paper proposes three feature extraction methods: unit energy average pulse durative time, shape parameter of signal power spectral density (PSD), and pulse linear predictive coding coefficient sequence. These methods allow identified remnants to be classified into four categories based on their material. Furthermore, we prove the validity of this new method by processing PIND signals from actual tests.

Research on Feature Extraction of Remnant Particles of Aerospace Relays

The existence of remnant particles, which significantly reduce the reliability of relays, is a serious problem for aerospace relays.The traditional method for detecting remnant particles-particle impact noise detection (PIND)-can be used merely to detect the existence of the particle; it is not able to provide any information about the particles' material. However, information on the material of the particles is very helpful for analyzing the causes of remnants. By analyzing the output acoustic signals from a PIND tester, this paper proposes three feature extraction methods: unit energy average pulse durative time, shape parameter of signal power spectral density(PSD), and pulse linear predictive coding coefficient sequence. These methods allow identified remnants to be classified into four categories based on their material. Furthermore, we prove the validity of this new method by processing PIND signals from actual tests.