Method and system for automated inspection utilizing a multi-modal database
A method and system for performing automated defect detection is disclosed. The system may include at least one database, an image capture device and a processor. The method may comprise providing at least one database for storing information used in processing data to detect a defect in at least one member of a plurality of members in a device. The information may include a plurality of different modes of data. The method may further comprise providing a processing unit for processing the information; receiving, by the database, updates to the information; identifying a potential defect in a first mode of data; applying, by the processing unit, analysis of a second mode of data, the analysis of the second mode of data triggered by the identifying, the second mode of data different than the first mode of data; and reporting defects based on the results of the applying.
1. A method for detecting a defect in a part of a gas turbine engine comprising:
receiving image data of the part from an image capture device;
using the image data and another type of data about the part other than the image data to create composite data through multi-modal data fusion, wherein the another type of data is a 3-D CAD model of a shape of the part, and the multi-modal data fusion comprises overlaying the 3-D CAD model of the shape of the part on the image data of the part to create the composite data;
identifying a potential defect in the part by analyzing the composite data by computing a posterior probability of a potential defect based on new data and prior data of the composite data and generating a ranked list of failure parts/regions based on the posterior probability to identify a potential defect having a higher probability;
upon identifying a potential defect in the part, analyzing a type of data about the part other than the image data and the composite data to identify a defect; and
reporting the defect.
2. The method of claim 1 , in which the analyzing of the composite data to identify a potential defect includes utilizing linear or non-linear registration.
3. The method of claim 2 , wherein the type of data other than the image data and the composite data that is analyzed upon detection of a potential defect is a manufacturing record of the part.
4. The method of claim 3 , wherein the part is a blade.