Purpose  A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal mental and workload overhead on surgeons working without a monitor and dedicated pointing tools. Methods  Three components were developed: a registration tool (Rhinospider), a hybrid magneto-optic-tracked robotic feedback control scheme and a modified robotic end-effector. Rhinospider optimizes registration of patient and preoperative CT data by excluding user errors in fiducial localization with magnetic tracking. The hybrid controller uses an integrated microscope HD camera for robotic control with a guidance beam shining on a dual plate setup avoiding magnetic field distortions. A robotic needle insertion platform (iSYS Medizintechnik GmbH, Austria) was modified to position a laser beam with high precision in a surgical scene compatible to microscopic surgery. Results  System accuracy was evaluated quantitatively at various target positions on a phantom. The accuracy found is 1.2 mm ± 0.5 mm. Errors are primarily due to magnetic tracking. This application accuracy seems suitable for most surgical procedures in the lateral skull base. The system was evaluated quantitatively during a mastoidectomy of an anatomic head specimen and was judged useful by the surgeon. Conclusion  A hybrid robotic laser guidance system with direct visual feedback is proposed for navigated drilling and intraoperative structure localization. The system provides visual cues directly on/in the patient anatomy, reducing the standard limitations of AR visualizations like depth perception. The custom- built end-effector for the iSYS robot is transparent to using surgical microscopes and compatible with magnetic tracking. The cadaver experiment showed that guidance was accurate and that the end-effector is unobtrusive. This laser guidance has potential to aid the surgeon in finding the optimal mastoidectomy trajectory in more difficult interventions.

The paper presents an advanced concept for a computer model of partial discharge (PD) in insulation. The advanced model concept is based on a well-known model, using condensers for modeling of electrical network and the cavity where discharge occurs. The fundamental advancement is the modeling of initial conditions of each discharge event by introducing a controlled voltage source and modeling its control, the modeling of parameters of PD current pulse, and advanced modeling of all circuit elements. The paper presents basic analysis of PD processes and the analysis of basic shortcomings of the well-known model. The elements of the advanced model are established, and the way to implement it. It is shown that commercial software packages for electric circuits analysis are indeed suitable for PD modeling. Physical and electrical parameters of PD pulse are established, as well as the response of observed object's electric network to the ensuing excitation. The results of the model show the possibility of modeling of PD current pulse in a wide range of parameters.

SUMMARY The paper deals with thermal modelling of transformers with automatic control of the cooling system. The case study was done on 725 MVA transformer with OFAF cooling, having eight compact coolers, each of them with their own pump and hysteresis control: four coolers, when top oil temperature drops below 30 °C, and six coolers, when top oil temperature rises above 45 °C. The consequence of operation with different number of coolers is change of thermal characteristics of the transformer. Additional phenomenon causing change of thermal characteristics is fouling of the coolers. These variable thermal characteristics are included in mathematical models used for the calculation of top oil and hot‐spot temperatures in all applications of such calculation algorithms: protection, monitoring, estimation of overload capability, calculation of thermal ageing, etc. Copyright © 2012 John Wiley & Sons, Ltd.

Due to the large number of power transformers (ETs) in the distribution system, there is a need for a relatively simple representation of the status of each unit in order to more easily determine where and how to allocate the budget for preventive and corrective maintenance. In recent years, the concept of the transformer health index (HI) as an integral part of resource management was adopted for the condition assessment and ranking of ETs. HI algorithms take different forms and can be determined based on a large number of specific parameters. However, the main problem in HI methodology or any modern diagnostic technique is the existence of regular measurements and inspections and accurate test results. The paper proposes a solution in the form of the upgraded HI and the novel methodology for ET ranking including the value of available information to describe ET current state. The confidence to the measurement results is calculated using evidential reasoning (ER) algorithm based on Dempster–Shafer theory. The contribution to the ER methodology is the calculation of the initial degrees of belief using Markov chains. The aging process of an ET and transition probabilities from state to state are modelled using the statistical data for the population of 300 ETs and 20 years monitoring data. The proposed methodology is tested on the real data for 110/35 kV transformer, and in the second case, compared to the sample of 30 110/x kV transformers with traditional HI calculation.

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