Flicker prediction techniques for sawmills

• Main Author: Jeffries, Ismail
• Language: en
• Published: Cape Technikon 2012
• Subjects: Sawmills; Flicker prediction > Techniques; Electrical engineering
• Online Access: http://hdl.handle.net/20.500.11838/1126

Thesis (MTech (Electrical Engineering))--Cape Technikon, Cape Town, 2003 === The aim of the thesis is to investigate and develop a technique for predicting the flicker emission of sawmill loads. The technique makes use of an empirical formula to calculate the characteristic coefficient of a sawmill motor (Ksm) and depends upon the short term flicker severity level (Ps,), load size and fault level.Three types of sawmill loads are commonly found in South Afiican plants, namely the Circular, Multi-rip, and Frame Saws. A sawmill plant was selected as a benchmark and Ksm factors for these types of saws were calculated by application of the empirical formula. These Ksm factors are required for predicting the flicker emitted by similar saws at other sawmill plants.A flicker meter was used to measure the flicker values (PsI) for these saws. Fault levels were calculated for various sawmill sites investigated. Load sizes were determined and the empirical formula used to calculate the Ksm factors. These Ksm factors were then compared to those calculated at the benchmark sawmill in order to determine the accuracy of the empirical formula.Nine case studies were conducted. The sawmills selected for these investigations were in different geographical forest areas in South Afiica. Different Ksm factors were found and this can be attributed to the differences in the density and hardness of the wood in the various areas. It can also be attributed to the mechanical variables of the saws. However, a comparative analysis of the Ksm factors comparison reveal that many Ksm factors fall within a similar range and for planning purposes 88,19 and 111 can be used for the Circular, Multi-rip, and Frame Saws, respectively.The results obtained demonstrate that the developed flicker emission prediction technique for sawmills is an effective analytical tool to be used for planning the network to ensure that the flicker levels will remain within acceptable limits.