Analysis of electric arc furnaces efficiency via frequency spectrum-based arc coverage detection

Abstract

We introduce the analysis of variables measured outside a direct current electric arc furnace that are related to the arc coverage and its electric energy efficiency. We derive an on-line reference to the arc coverage suitable for control decisions. In order to do so, we study the furnace shell vibration frequency spectrum as structure-borne sound sensed by a microphone. The data is analysed using real time software tools to obtain the sound signal spectrum associated with arc coverage likewise related to the optimal performance of the furnace. A statistical test is performed to prove the relationship between sound and electric energy efficiency.

Electric Arc Coverage Indicator for AC Furnaces Using a Laser Vibrometer and Neural Networks

“…The inputs for the multivariable ANN can be any which provide relevant information about the conditions of the electric arc, the combination of electrical variables and vibration can be a good initial configuration. It should be noted that the number of inputs of the ANN can be increased, thus other variables such as the sound produced during the process 7) can be included in the processing to obtain a better arc coverage indication. These integration of variables is presently under research of other team working on the same project.…”

“…6) Nevertheless, the use of contact sensors in the shell is very problematic due to the hostile environment near the furnace. Other approach was proposed in 7) where the sound of a DC furnace was used to estimate the arc coverage level. It is expected that the sound emitted by the electric arc and the shell's vibrations present similar behaviors, however the use of sound can lead to measurement errors when two or more furnaces are working in the same steel shop.…”

On-line Detection Method of Power Quality Detection Device Based on High-precision Standard Time Synchronization Technology

“…NTP is originally designed and implemented by professor Mills from the university of Delaware in the United States. It has been developed for nearly 40 years since it is first proposed in 1982 [7][8]. The latest accuracy of NTPv4 has reached 200 milliseconds.…”