Overhead cranes are a vital part of many manufacturing plants. They are versatile, provide high load capacity, and are relatively inexpensive. They are not easy to automate, however, and their swing dynamics requires a skilled operator for fast, precise operation. The discussed project uses machine vision and PLC control technology to continue the progress in this area made by previous scholars. The vision system is used for detecting the position of the hook from the top of the cable. It can also be used for identifying the desired target position for the hook by observing targets on the floor and on the objects to be hoisted. The motion of the top of the cable must be controlled in three directions, including height. The two horizontal motions are particularly important for controlling the swing of the cable. The command shaping algorithms have been used in the past for similar applications and will again be used here. The improvement of the machine vision system is a part of the project to automate an overhead crane. The project?s goal is to obtain reliable, real-time coordinate information about the crane hook and its environment.
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Overhead cranes are a vital part of many manufacturing plants. They are versatile, provide high load capacity, and are relatively inexpensive. They are not easy to automate, however, and their swing dynamics requires a skilled operator for fast, precise operation. The discussed project uses machine vision and PLC control technology to continue the progress in this area made by previous scholars. The vision system is used for detecting the position of the hook from the top of the cable. It can also be used for identifying the desired target position for the hook by observing targets on the floor and on the objects to be hoisted. The motion of the top of the cable must be controlled in three directions, including height. The two horizontal motions are particularly important for controlling the swing of the cable. The command shaping algorithms have been used in the past for similar applications and will again be used here. The improvement of the machine vision system is a part of the project to automate an overhead crane. The project's goal is to obtain reliable, real-time coordinate information about the crane hook and its environment.
Thorsten Schneider, Dipl.-Ing.(FH) in Applied Automation Technology, University of Lüneburg
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Schneider ThorstenThorsten Schneider, Dipl.-Ing.(FH) in Applied Automation Technology, University of LueneburgOverhead cranes are a vital part of many manufacturing plants. They are versatile, provide high load capacity, and are r. Bestandsnummer des Verkäufers 4965319
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Overhead cranes are a vital part of many manufacturing plants. They are versatile, provide high load capacity, and are relatively inexpensive. They are not easy to automate, however, and their swing dynamics requires a skilled operator for fast, precise operation. The discussed project uses machine vision and PLC control technology to continue the progress in this area made by previous scholars. The vision system is used for detecting the position of the hook from the top of the cable. It can also be used for identifying the desired target position for the hook by observing targets on the floor and on the objects to be hoisted. The motion of the top of the cable must be controlled in three directions, including height. The two horizontal motions are particularly important for controlling the swing of the cable. The command shaping algorithms have been used in the past for similar applications and will again be used here. The improvement of the machine vision system is a part of the project to automate an overhead crane. The project s goal is to obtain reliable, real-time coordinate information about the crane hook and its environment. Bestandsnummer des Verkäufers 9783639187458
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