The invention discloses a chaos-based early-stage
single point of failure detection and classification method for mechanical part. The method comprises the following steps that: firstly,
processing existing sample fault signals, under different states, of the mechanical part, and establishing
verification intervals of different fault types; secondly, obtaining fault feature frequency correspondingto all single-point failure states of the mechanical part to construct the
frequency matrix of a Duffing
chaotic oscillator; thirdly, solving the
critical threshold of a corresponding periodic stimulating force amplitude under different fault feature frequencies, and constructing a frequency-threshold matrix; and finally, adding a
signal to be detected to calculate a maximum Lyapunov index matrixM, carrying out
verification on data in the M, calculating the correlation dimension of the
signal to be detected if a fault
signal exists, carrying out fault classification by contrasting with the established correlation dimension interval of different fault types, carrying out fault classification, and determining a fault mode. By use of the method, the detection and the classification of the early-stage single-point failure of the mechanical part are realized, anti-
noise ability if high, and in addition, a fault detection success rate is high.