Method and system for material degradation detection in an object by analyzing acoustic vibration data

摘要

The invention claims a method and a system for material degradation detection in an object (11, 12) of said material by analyzing acoustic vibration data (VD) from said object (11, 12). The method comprises the following steps:
- training (100) a supervised learning machine (5) to recognize said acoustic vibration data (VD) without material degradation by extraction of at least one time-frequency feature (FF) of said acoustic vibration data (VD),
- detecting (101) said acoustic vibration data (VD) from said object (11),
- converting (102) said acoustic vibration data (VD) to a time-frequency domain representation (FR),
- extracting (105) at least one time-frequency feature (FF) of the time-frequency representation (FR) which is characteristic for said material degradation and
- detecting (106) by the learning machine (5) if the value of the extracted at least one time-frequency feature (FF) of the time-frequency domain representation (FR) is novel compared to the value of the time-frequency feature (FF) of the training. The invention provides the advantage of robust material degradation detection under severe environmental conditions. With the method or system corrosion of down-hole pipes can be detected exactly and robustly.