Method, device and computer program for determining the performance of a welding method via digital processing of an image of the welded workpiece

A method for determining the performance of a welding process carried out on at least one metal part, comprising:

• a) acquiring, with an image-capturing device, at least one initial image of at least one surface segment of said part
• b) carrying out a first digital processing operation on the initial image, thereby locating, in said initial image, presumed spatters,
• c) inputting one or more extracts from the initial image, each comprising one presumed spatter, into at least one neural network, so as to classify the presumed spatters into confirmed spatters or unconfirmed spatters,
• wherein step a) is carried out on said part previously welded comprising a weld bead, welding of said part having finished, confirmed spatters being located on the surface of said part, and further comprising:
• d) carrying out a second digital processing operation on the initial image comprising the spatters classified confirmed in step c) thereby determining at least one parameter representative of the quantity of confirmed spatters chosen from:
• the area of one or more confirmed spatters,
• the total area of the confirmed spatters, which is defined as the sum of the areas of each confirmed spatter,
• the number of confirmed spatters,
• the number of confirmed spatters per unit area,
• spatter density, defined as the total area of confirmed spatters divided by the total area of the initial image (2),
• the average of the distances between each confirmed spatter and the weld bead, and
• e) determining the performance of the welding process on the basis of the at least one parameter determined in step d),
• wherein the first digital processing operation carried out in step b) on the initial image comprises the following sub-steps:
• i) filtering the initial image so as to obtain a differentiation between the metal spatters and a background of the initial image,
• ii) removing the background of the initial image,
• iii) binarizing the filtered image resulting from step i), especially via brightness-based thresholding, so as to form a binary image with two pixel values,
• iv) selecting one of the two pixel values so as to define, in the binary image, regions of interest formed by the pixels of the selected,
• v) marking the regions of interest in the binary image and transporting the resultant markings to the initial image so as to locate presumed spatters therein.