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SUMMARYThis paper describes an algorithm which recognizes the position and the orientation of a structural industrial part, such as a crankshaft, utilizing the relationships between its elementary blobs. Crankshafts are arranged tightly and piled up in multiple layers and their image from above includes regions (i.e. pictures) of crankshafts not only of the current top layer but also of the lower ones; it thus becomes complicated. First, the algorithm carries out the connectivity analysis for an input binary image, and then extracts elementary blobs by applying a line fitting procedure on every sequence of boundary pixels of connected regions. Next, each blob is judged to determine to which component of a part it corresponds, using the size model. Then the relationships (distances and orientations) between blobs are examined, using their relational models, and a group of blobs of one part is recognized. Its position and orientation are calculated simultaneously. This model matching algorithm is implicitly included in the procedures.

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This paper presents high temperature performance of CSTBT TM (III) and its main parameters. The key for high temperature operation is suppressing the parasitic NPN transistor action. N + emitter width, P + diffusion layer depth and gate oxide thickness are main parameters for suppressing the parasitic action. The optimized 1200V CSTBT TM (III) succeeded in 200°C operation without any thermal runaway or turn-off failure.