| 摘要 |
The invention relates to a method for providing a prediction model for crack detection on a semiconductor structure that is a photovoltaic solar cell, a precursor of a photovoltaic solar cell in the production process, more particularly a semiconductor material for producing a solar cell, the method comprising the following steps: A) provision of a reference semiconductor structure having at least one crack; B) provision of crack data for the at least one crack, the crack data comprising geometric position data regarding the position of the crack on the reference semiconductor structure; C) spatially resolved scanning of the reference semiconductor structure by spatially resolved measurement of a plurality of spatial measurement points of the photoluminescence generated in the semiconductor structure and/or spatially resolved measurement of IR absorption of the semiconductor structure, and D) creation of a prediction model by training a learning algorithm on the basis of the spatially resolved measurement data acquired in step C and the crack data provided in step B, the training of the learning algorithm comprising the following steps: D1) creation of at least one descriptor for at least one spatial descriptor point by specifying or determining a test region for the descriptor point and creating the descriptor on the basis of the measurement data inside the test region, which descriptor is a feature vector and/or a feature distribution and/or a feature histogram, and D2) training the learning algorithm by means of the descriptor and the crack data. The invention further relates to a method and a device for crack detection. |
