Abstract: Disclosed is a method and system for detecting surface deformation of a production asset. The method and system may include receiving a point cloud for a surface of the production asset; determining a model surface for the production asset from the point cloud, the model surface being an estimate of a deformation free representation of the surface of the production asset, the model surface being determined from points in the point cloud including points representing a surface deformation; determining a distance between at least one point in the point cloud and the model surface; and outputting the distance.

Abstract: Disclosed is a system and method for determining a degree of surface degradation for one or more artificial objects. The system and method may include receiving a non-planar point cloud, generated from a plurality of viewpoints, for the one or more artificial objects, each point in the point cloud having associated data; determining a degree of degradation, using the associated data, for each point in the point cloud, the degree of degradation being a measure of degradation for a coating of the one or more artificial objects; and determining a degree of surface degradation according to the degree of degradation of each point in the point cloud.

Abstract: A computer can operated, including detecting defects, or other physical features, of artificial objects. Image data is received of one or more artificial objects, and applying an image segmentation process to the image data to detect predetermined defects of the one or more artificial objects. The image segmentation process identifies one or more regions of the image data determined to have a likelihood of showing one or more of the predetermined defects. The identified one or more regions is output. The image segmentation process determines severity metrics for the defects in the one or more regions, wherein a severity metric represents a severity or significance of a defect. The image segmentation process further determines a confidence factor for each region of the one or more regions, wherein the confidence factor represents a likelihood of the presence of a predetermined defect in the region.

Abstract: A signature collating machine having a plurality of sequentially situated signature supply stations whose common floor rises via an electronic sensor to maintain signature stacks at operable heights. Above each supply station is a suction delivery assembly, each of said assemblies having a suction port housing and a suction port extending therefrom for engagement with a signature. The machine further has traveling collector rods which sequentially gather signatures engaged with respective suction ports. An actuator is provided which causes upward movement of a suction delivery assembly, and consequent positioning of a signature for subsequent collating, upon suction port engagement with a signature. Circuitry is provided which causes collector rod travel to cease if any suction port ahead of a collector rod is not engaged with a signature, thus eliminating accidental non-inclusion of a signature.