Magneettinostimen demagnetointifunktio

There is a need to move heavy metal parts in industry and machine shops. The heavy parts are often moved using various cranes. The metal parts can be sheet metal plates or otherwise hard to attach to the crane using traditional hoisting attachments. Different kinds of gripping devices have been developed for sheet metal and round parts. One type of a gripping device is a lifting magnet. There are two major types of lifting magnets: permanent magnet based and electromagnetic ones. The electromagnetic lifters can be battery powered or connected to the mains voltage. This Master's thesis investigates the demagnetization functionality of a battery operated magnetic lifter. Electrically the lifting magnet is a coil. The body of the lifting coil is made out of steel and it acts as a core material. To lift an object a battery voltage is applied to the coil. After finishing the lifting operation the voltage is switched off. Depending of the material of the lifted object, there may be various amount of residual magnetism in the lifted object. The residual magnetism might make the detaching of the lifted object hard and cause problems later during processing. The simplest way to reduce the residual magnetism is to drive a short opposite polarity pulse to the lifting coil. The pulse removes a major part of the residual magnetism. On most of the applications this is sufficient. For the certain applications, a lower residual magnetism level is needed. For example engine parts are not allowed to have high residual magnetism level when assembled. To further reduce the residual magnetism, a demagnetization sequence is needed. The demagnetization is done by driving alternating polarity pulses to the lifting coil and reducing the duration of the pulses continuously. This reduces the residual magnetism of the lifted object. The demagnetization algorithm can be implemented using a fixed timer sequence. In this Master's thesis an adaptive demagnetization algorithm is developed and implemented. The algorithm uses the measured magnetization value as a feedback. The adaptive demagnetization algorithm is developed using simulations and measurements. As a result, a functional demagnetization algorithm was implemented. The algorithm optimizes the duration of the demagnetization based on the properties of the demagnetized material