Provided is an automatic doffing communication method, a control system, a communication system and a network device. The method includes: receiving a doffing monitoring image from a terminal device; sending the doffing monitoring image to a text recognition system; receiving an automatic doffing scheduling task from an automatic doffing system; wherein the automatic doffing scheduling task comprises a task generated by the automatic doffing system according to a recognition result of the doffing monitoring image by the text recognition system; and sending the automatic doffing scheduling task to an automatic doffing device.

Systems and methods for inspecting wound optical fiber to detect and characterize defects are disclosed. The method includes illuminating the wound optical fiber with light from a light source and capturing a digital image based on measurement light that is redirected by the wound optical fiber to a digital camera. The method also includes processing the digital image with a computer to detect and characterize the defects. The types of defects that can be detected using the systems and methods disclosed herein include bubbles, abrasions, punctures, scratches, surface contamination, winding errors, periodic dimensional errors, aperiodic dimensional errors and dents.

A device for detecting the presence of abnormalities in a reel includes an image capturing module for capturing images of the reel including at least one camera, a displacer for displacing the reel in a field of view of the at least one camera, an analyzer for analyzing the images captured by the at least one camera and detecting the presence of abnormalities. The image capturing module including an upper capturer and lower capturer, the upper capturer fixed on a movable support arranged for being movable with respect to lower capturer, the upper capturer and/or the lower capturer including at least one three dimension camera arranged for providing a three dimension image of the reel.

An electronic device for locates a functional disorder within a spinning and winding section of a spinning by receive spinning parameters from spinning machines related to production of yarn delivery bobbins at the spinning machines, and receiving winding parameters from winding machines related to production of yarn bobbins at the winding machines. For the yarn bobbins, the electronic device compares a winding parameter with a normal state level value for the winding parameter to detect a winding abnormality at the respective winding machine that produced the yarn bobbin. Upon detection of the winding abnormality, the electronic device the yarn delivery bobbins used for production of the yarn bobbin and compares at least one of the spinning parameters of the identified yarn delivery bobbins with a normal state level value to locate the functional disorder within the spinning and winding section.

The computer-implemented method serves for efficiently trading yarn packages. A server computer system receives from a spinning mill having produced a yarn package a set of measured values for yarn-quality parameters measured for yarn on the yarn package and further information on the yarn package. It assigns a package identifier to the set of measured values and to the further information and stores them in a database. The server computer system receives from a client computer purchase request containing yarn specifications. It retrieves from the database sets of yarn packages such that the further information matches the yarn specifications for all packages of each set. It produces a ranking of the sets of yarn packages according to the sets of measured values. It transmits to the client computer information on sets of yarn packages best ranked in the produced ranking.

Provided is a yarn spindle coding method including: when determining that yarn spindles are fully wound, sleeving the yarn spindles in the winding machine sequentially outside a yarn connecting rod of a doffer, and updating the number of unloading times of the winding machine and recording first doffing time of each yarn spindle; generating a first information code of each yarn spindle based on identification information of the winding machine, the updated number of unloading times, the first doffing time and position information of each yarn spindle; and sending each first information code to the doffer, so that the doffer determines a corresponding target yarn spindle among the yarn spindles according to a matching degree between the first doffing time and second doffing time of each yarn spindle recorded by the doffer and code the information code on a corresponding target yarn spindle.

A winder for forming a yarn package can have a spindle axis. The winder can comprise a spindle that is configured to be rotatably driven about the spindle axis. A color probe can be positioned with respect to the spindle to measure a color value of yarn wound on the spindle.

A system including a platform, a drill connected to the platform, a power source, a cable connected to a cable reel and the drill, and a stinger. The stinger is configured to guide a position of the cable, relative to the platform, as the cable moves relative to the platform and relative to the stinger. An actuator is connected to the stinger and operable to move the stinger relative to the platform. A sensor is disposed to sense a physical parameter of at least one of the platform, the drill, the power source, the cable, and the stinger. A computer system is programmed to convert the physical parameter into a vector data structure and input the vector data structure to a classification machine learning model, which outputs a classification for the physical parameter. A control system is configured to control the actuator to move the stinger based on the classification.

A system including a platform, a drill connected to the platform, a power source, a cable connected to a cable reel and the drill, and a stinger. The stinger is configured to guide a position of the cable, relative to the platform, as the cable moves relative to the platform and relative to the stinger. An actuator is connected to the stinger and operable to move the stinger relative to the platform. A sensor is disposed to sense a physical parameter of at least one of the platform, the drill, the power source, the cable, and the stinger. A computer system is programmed to convert the physical parameter into a vector data structure and input the vector data structure to a classification machine learning model, which outputs a classification for the physical parameter. A control system is configured to control the actuator to move the stinger based on the classification.

A management device that manages a unit including a drum and a long object wound around the drum, the management device includes: a receiver that receives, from a user terminal, a captured image obtained by capturing an image of the unit; and a controller that accesses correspondence data obtained by associating each of image capture results, obtained by successively capturing images of the unit while winding the long object around the drum, with a corresponding winding amount of the long object wound around the drum at a time when the each of the image capture results was obtained. The controller determines a remaining amount of the long object based on the captured image and the correspondence data.