Uncertainty evaluation in the measurement of power frequency electric and magnetic fields from AC overhead power lines

ARTIFICIAL NEURAL NETWORK MODELS FOR ESTIMATION OF ELECTRIC FIELD INTENSITY AND MAGNETIC FLUX DENSITY IN THE PROXIMITY OF OVERHEAD TRANSMISSION LINE

This paper considers the application of artificial neural network (ANN) models for electric field intensity and magnetic flux density estimation in the proximity of overhead transmission lines. Specifically, two distinct ANN models are used to facilitate independent estimation of electric field intensity and magnetic flux density in the proximity of overhead transmission lines. The considered ANN approach is systematically evaluated under different scenarios. An example of an overhead transmission line with horizontal phase conductor configuration is used to enable a direct comparison of the electric field intensity and magnetic flux density estimates generated by the two ANN models to measurement results obtained over the lateral profile. Further investigation of ANN models involves an extensive study whereby 13 different overhead transmission lines of horizontal configurations are used as the basis for comparing measurement results to estimates provided by the ANN models. In this study, the performance analysis of the ANN models was evaluated using coefficient of determination and root mean square error. The obtained results demonstrate that the considered ANN approach can be used to estimate the electric field intensity and magnetic flux density in the proximity of overhead transmission lines.

Occupational exposure to electromagnetic fields. The situation in Greece

PURPOSE

The management of the occupational exposure to electromagnetic fields (EMF), an Occupational Health and Safety (OHS) issue of great scientific, social and economic significance, was under intense negotiations at European level over the last twenty years; the Directive 2013/35/EU is the new legislative tool. The presented study deals with the practical aspects of the Directive's implementation.

METHODS

The appropriate, extensive measurements and the overall EMF exposure assessments (i.e. exposure mapping, identification of hot spots, proposition of solutions) were conducted in specific workplaces, including power production, railway, broadcasting, clinical Magnetic Resonance Imaging (MRI) systems, industrial and research sites, as well as common office workplaces.

RESULTS

The vast majority of the performed EMF assessments did not reveal occupational overexposures; moreover in most of the cases, even the general public exposure limits (in the above occupational areas) were not exceeded. The very few localized overexposures detected, were manageable on the basis of the technical and organizational OHS principles. On the contrary, the maintenance procedures of the EMF emitting equipment, as recorded in this survey, presented overexposures revealing a challenging field.

CONCLUSIONS

This study lays a firm basis for the clarification of the occupational EMF environment, where potential exposures might be high. The proper risk assessment demands precise exposure identification and deep understanding of the EMF nature and hazards. Misconceptions range from the common exposure overestimation to the rarer case of the maintenance hazards underestimation, while attention is needed concerning the proper application of the complex limiting system of the Directive.

Adaptive framework for uncertainty analysis in electromagnetic field measurements

Misinterpretation of uncertainty in the measurement of the electromagnetic field (EMF) strength may lead to an underestimation of exposure risk or an overestimation of required measurements. The Guide to the Expression of Uncertainty in Measurement (GUM) has internationally been adopted as a de facto standard for uncertainty assessment. However, analyses under such an approach commonly assume unrealistic static models or neglect relevant prior information, resulting in non-robust uncertainties. This study proposes a principled and systematic framework for uncertainty analysis that fuses information from current measurements and prior knowledge. Such a framework dynamically adapts to data by exploiting a likelihood function based on kernel mixtures and incorporates flexible choices of prior information by applying importance sampling. The validity of the proposed techniques is assessed from measurements performed with a broadband radiation meter and an isotropic field probe. The developed framework significantly outperforms GUM approach, achieving a reduction of 28% in measurement uncertainty.

No effects of power line frequency extremely low frequency electromagnetic field exposure on selected neurobehavior tests of workers inspecting transformers and distribution line stations versus controls

We aimed to evaluate the interference of 50 Hz extremely low frequency electromagnetic field (ELF-EMF) occupational exposure on the neurobehavior tests of workers performing tour-inspection close to transformers and distribution power lines. Occupational short-term "spot" measurements were carried out. 310 inspection workers and 300 logistics staff were selected as exposure and control. The neurobehavior tests were performed through computer-based neurobehavior evaluation system, including mental arithmetic, curve coincide, simple visual reaction time, visual retention, auditory digit span and pursuit aiming. In 500 kV areas electric field intensity at 71.98% of total measured 590 spots were above 5 kV/m (national occupational standard), while in 220 kV areas electric field intensity at 15.69% of total 701 spots were above 5 kV/m. Magnetic field flux density at all the spots was below 1,000 μT (ICNIRP occupational standard). The neurobehavior score changes showed no statistical significance. Results of neurobehavior tests among different age, seniority groups showed no significant changes. Neurobehavior changes caused by daily repeated ELF-EMF exposure were not observed in the current study.