Abstract: An improved circuit board inspection system incorporates self learning techniques for accurate determination of Z-axis elevations of electrical connections. A Delta Z, referenced to a laser range finder generated surface map of the circuit board, is automatically determined from a series of cross sectional images of the electrical connections for each electrical connection on the circuit board. The Delta Z values for each electrical connection are stored in a data base from which customized Delta Z values for specifically defined board views may be calculated.

Abstract: An improved circuit board inspection system incorporates self learning techniques for accurate determination of Z-axis elevations of electrical connections. A Delta Z, referenced to a laser range finder generated surface map of the circuit board, is automatically determined from a series of cross sectional images of the electrical connections for each electrical connection on the circuit board. The Delta Z values for each electrical connection are stored in a data base from which customized Delta Z values for specifically defined board views may be calculated.

Abstract: Systems and methods for analyzing for images in an x-ray inspection system are provided. One embodiment is a system for analyzing images in an x-ray inspection system. Briefly described, one such system comprises: a means for receiving an image of an object that is generated by an x-ray inspection system, the image of the object having a first field of view (FOV); a means for determining whether the first FOV associated with the image of the object matches a reference FOV corresponding to design data that models the object being inspected by the x-ray inspection system; and a means for modifying the design data based on the difference between the first FOV and the reference FOV.

Abstract: An improved circuit board inspection system incorporates self learning techniques for accurate determination of Z-axis elevations of electrical connections. A Delta Z, referenced to a laser range finder generated surface map of the circuit board, is automatically determined from a series of cross sectional images of the electrical connections for each electrical connection on the circuit board. The Delta Z values for each electrical connection are stored in a data base from which customized Delta Z values for specifically defined board views may be calculated.

Abstract: Systems and methods for analyzing for images in an x-ray inspection system are provided. One embodiment is a system for analyzing images in an x-ray inspection system. Briefly described, one such system comprises: a means for receiving an image of an object that is generated by an x-ray inspection system, the image of the object having a first field of view (FOV); a means for determining whether the first FOV associated with the image of the object matches a reference FOV corresponding to design data that models the object being inspected by the x-ray inspection system; and a means for modifying the design data based on the difference between the first FOV and the reference FOV.

Abstract: An improved circuit board inspection system incorporates electrically controlled selection of Z-axis position for generation of laminographic images of electrical connections. Analysis of the laminographic images is performed by comparing the laminographic images to the CAD data representing the area of the circuit board in the image. The CAD data based on a reference Z-axis level is converted on-the-fly to compensate for changes in the field of view, magnification factors, etc. for non-reference Z-axis levels. Thus, laminographic images at the reference Z-axis level are compared directly to the reference level CAD data while laminographic images at non-reference Z-axis levels are compared to the on-the-fly modified non-reference level CAD data.

Abstract: An improved circuit board inspection system incorporates self learning techniques for accurate determination of Z-axis elevations of electrical connections. A Delta Z, referenced to a laser range finder generated surface map of the circuit board, is automatically determined from a series of cross sectional images of the electrical connections for each electrical connection on the circuit board. The Delta Z values for each electrical connection are stored in a data base from which customized Delta Z values for specifically defined board views may be calculated.

Abstract: An improved circuit board inspection system incorporates self learning techniques for accurate determination of Z-axis elevations of electrical connections. A Delta Z, referenced to a laser range finder generated surface map of the circuit board, is automatically determined from a series of cross sectional images of the electrical connections for each electrical connection on the circuit board. The Delta Z values for each electrical connection are stored in a data base from which customized Delta Z values for specifically defined board views may be calculated.

Abstract: A method and apparatus which incorporate self learning techniques for the detection of solder defects and for statistical process control of solding operations on printed circuit board assemblies (PCBA) are disclosed. The invention includes learning techniques which are used during the inspection of cross-sectional X-ray images of solder joints. These learning techniques improve measurement accuracy by accounting for localized shading effects, which can occur when inspecting double-sided printed circuit board assemblies. Two specific examples are discussed. The first is a method for detection of solder short defects. The second method utilizes learning to improve the accuracy of statistical process control (SPC) measurements.