Abstract: A surface scanner for surface defect detection of a cable comprises a measuring part and an analysis part, the measuring part comprises non-contact distance measurement sensors, the cable is positionable between the sensors such that beams of the sensors are directable to the outer surface of the cable to sample areas at a circumference of the cable for a length of the outer surface (L) of the cable in a run direction (x) of the cable for providing measurement data, and the analysis part comprises a receiver for the measurement data, a processor for processing the measurement data providing defect detection data and a continuous 3D topographic map of the outer surface of the cable, the analysis part comprising a neural network trained for detecting surface defects of the cable and outputting surface defects detection data. The invention also relates to an arrangement and a method for surface defect detection of a cable.

Abstract: According to an aspect, there is provided a method for monitoring quality of loose tube fiber optic cable during manufacture in a secondary coating line. Initially, a trained machine-learning algorithm for calculating expected values of one or more quality metrics of manufactured loose tube fiber optic cable based on values of the one or more production process parameters of the secondary coating line is maintained in a machine-learning database. A computing system monitors one or more values of the one or more production process parameters during miming of the secondary coating line and calculates, in real-time during the monitoring, one or more expected values of the one or more quality metrics using the trained machine-learning algorithm with the monitored values of the one or more production process parameters as input. The computing system outputs at least the one or more expected values of the one or more quality metrics to a user device.

Abstract: A surface scanner for surface defect detection of a cable comprises a measuring part and an analysis part, the measuring part comprises non-contact distance measurement sensors, the cable is positionable between the sensors such that beams of the sensors are directable to the outer surface of the cable to sample areas at a circumference of the cable for a length of the outer surface (L) of the cable in a run direction (x) of the cable for providing measurement data, and the analysis part comprises a receiver for the measurement data, a processor for processing the measurement data providing defect detection data and a continuous 3D topographic map of the outer surface of the cable, the analysis part comprising a neural network trained for detecting surface defects of the cable and outputting surface defects detection data. The invention also relates to an arrangement and a method for surface defect detection of a cable.

Abstract: The invention relates to method in a process for preparing extruded articles by flowing heat plastified stream of extrudable resinous thermoplastic material through an extrusion orifice. The invention relates further to an extrusion process and an apparatus. In the invention the stream can be separated into a central core stream and at least one boundary stream on the outside of the core stream. Modifying additives are added to the boundary streams while maintaining physical separation of the core and boundary streams. The streams are recombined prior expelling the material out of the extrusion orifice, said boundary streams being applied as a relatively thin surface layer having altered properties between the core layer and the surfaces of the extrusion orifice. The additives can alternatively be added directly to the surface portion of the material stream without any physical separation step.