In the paper the data-dependent search for the Maximum Time Interval Error (MTIE) is described. In the first section the authors introduce the problem of time effective MTIE assessment. Then the data-independent method of MTIE assessment based on the estimator formula is described. In the next section the time effective data-dependent process of MTIE search is described. The results of the calculation experiment proved the time effectiveness of the proposed method.

Surge wave diagnostics is based on the principle of discharging two identical capacitors (highfrequency surge) into two loads (windings), and subsequent displaying resonant damped processes on loads by means of the two-channel oscilloscope. To increase the ability to identify failures, this signal must be, however, digitised and analysed by means of a mathematical tool. Generally, it has been stated that through this method, one of ten turn-to-turn short circuits can be identified without digitising the signal; after signal digitising, the identification of failures being improved approximately tenfold.

A common solution to measure electrical power is through the use of systems that digitise voltage and current signals. However, several errors can affect the accuracy of such systems, namely transducer errors, sampling errors [1] and analogue-to-digital conversion errors. Sampling errors can be very important especially when low-cost solutions for digitalisation are considered. In this case, besides truncation errors caused by spectral leakage, non-simultaneous sampling of voltage and current signals, due to the absence of sample-and-hold-circuits, can also introduce large amplitude errors. In the present paper, an easy solution to minimise the last type of errors is proposed and some simulation and experiment results are presented to validate that solution.

A Supervisory Control and Data Acquisition (SCADA) based system for monitoring and control of the energy supply and the peak load in industry plant has been designed and algorithm for short-term energy forecast was implemented. The paper describes design and implementation of Energy Management System (EMS) consisted of cost effective elements combined with SCADA software application, which makes platform for supporting the economical energy management of industrial businesses. Trend SCADA screen with necessary on-line data for operator peak load limiting action was designed and real time data for control automatic power limiting system was prepared. System was tested and is in use more than three years in chemical industry plant with 1200 kW average power peak load. Such plant was representative sample for Eastern Europe common mid-size industry energy consumer and it was concluded that implemented energy monitoring system indicate investment turn back in less than six months.

In this paper, we present new auto-scaling field sensors based on the magnetostrictive delay line (MDL) technique. The principle of operation is based on the variation of the magneto-elastic response of an array of MDLs with respect to the applied input, which depends on the composition and the annealing history of the material.