The invention discloses a double-
spectrum analysis-based
fatigue damage state characterization and quantitative
evaluation system for an in-service 16
manganese steel bearing member. An original waveform
signal extracting unit (1) of the
system performs analog-to-
digital conversion on multipath sensing information Sn and then outputs
sound emission waveform information f0 (T); a double-spectrum evaluation module (21) processes the
sound emission waveform information f0 (T) by adopting a double-
spectrum analysis method to acquire double-spectrum evaluation B (
omega 1 and
omega 2); then, a double-spectrum
diagonal slice module (22) performs
diagonal slice analysis on the double-spectrum evaluation B (
omega 1 and omega 2) to acquire double-spectrum
diagonal slice information omega (F); and finally, a
fatigue damage state characteristic peak
frequency analysis module (23A) processes the diagonal slice information omega (F) to output a
fatigue damage state matrix P=[F0, F, Fm] for a fatigue damage grade evaluation unit (3) and an early warning unit (4) to perform evaluation and alarm. The
system monitors the in-service 16Mn steel bearing member by
sound emission technology to acquire fatigue damage state information expressed by sound emission signals, quantitatively evaluates the fatigue damage state of the bearing member by adopting the double-
spectrum analysis method, and evaluates the fatigue damage grade. The
system can be used for intuitively and quantitatively evaluating and judging the fatigue damage state of the 16Mn steel bearing member in real time so as to make early warning and reduce the loss of equipment, casualty and the like.