Multi-variable classification model for valve internal leakage based on acoustic emission time-frequency domain characteristics and random forest.

To use acoustic-emission technology to detect leaks inside valves, the necessary first step is to model the valve-internal-leakage acoustic-emission signal (VILAES) mathematically. A multi-variable classification model that relates the VILAES characteristics and the leakage rate under varying pressure is built by combining time-frequency domain characteristics and the random-forest method. A Butterworth bandpass filter is used to preprocess the VILAES from a liquid medium, and the best frequency band for filtering is determined as being 140 kHz-180 kHz.