Adjustable depth of field optical coherence tomography

1. A method of surface inspection of an object using optical coherence tomography (OCT), the method comprising:

determining a first working distance between a scanner head and a first surface location on the object;

determining a first depth of field, based on the first working distance, in which the surface of the object at the first surface location is in focus;

changing a current depth of field to the first depth of field;

performing an A-scan of the object;

moving the object relative to the scanner head;

determining a subsequent working distance being a distance between the scanner head and a subsequent surface location of the moved object;

determining whether the object is in focus at the subsequent surface location, if the object is not in focus:

determining a subsequent depth of field, based on the subsequent working distance, in which the surface of the object at the subsequent surface location is in focus;

changing the current depth of field to the subsequent depth of field; and

performing an A-scan of the object; and

otherwise, performing an A-scan of the object.

2. The method of claim 1 , wherein at least a portion of the object has a curved surface profile.

3. The method of claim 1 , wherein determining the first working distance and determining the subsequent working distance each comprise measuring a distance between the scanner head and the surface of the object.

4. The method of claim 1 , further comprising retrieving a surface geometry of the object from a database and wherein determining the first working distance and determining the subsequent working distance each comprise determining a distance between the scanner head and the surface of the object from the surface geometry of the object.

5. The method of claim 1 , wherein moving the object relative to the scanner head comprises continuously moving the object.

6. The method of claim 1 , wherein at least some of the A-scans are aggregated together into a B-scan.

7. The method of claim 1 , wherein determining the first depth of field comprises:

setting a first centric working distance as the first working distance;

setting a first upper boundary of the first depth of field as equivalent to subtracting half of the value of an A-scan depth of field from the centric working distance; and

setting a first lower boundary of the first depth of field as equivalent to adding the A-scan depth of field to the first upper boundary; and

wherein determining the subsequent depth of field comprises:

setting a subsequent centric working distance as the subsequent working distance;

setting a subsequent upper boundary of the subsequent depth of field as equivalent to subtracting half of the value of an A-scan depth of field from the centric working distance; and

setting a subsequent lower boundary of the subsequent depth of field as equivalent to adding the A-scan depth of field to the subsequent upper boundary.

8. The method of claim 1 , wherein, using the A-scans data, detecting a feature on a surface or subsurface of the object using a neural network trained using a training set, the training set comprising A-scans data with a known feature.

9. The method of claim 8 , further comprising detecting a location of the detected feature using the neural network.