Determining whether power transformers are suffering from internal arcing or dangerous levels of partial discharge (PD) is important because failure without warning can result in damage to neighboring equipment, customer dissatisfaction, disruption to economic activity, and the imposition of regulatory fines. This paper provides an overview of the excitation of UHF signals by PD inside transformers. The use of externally mounted sensors has been outlined, and the structure of a dielectric window that can be constructed on an inspection hatch has been outlined. Attenuation of UHF signals propagating inside a transformer tank has been shown to be relatively low. A new approach to locating PD sources in three dimensions has been presented, based on using a numerical model of the transformer materials, which defines electromagnetic propagation velocities on a mesh of 5-cm sub-cells. The concepts of the propagation-velocity matrix (PVM) and the propagation-time matrix (PTM) were thereby introduced. Once the PD source has been located to a specific region of the transformer, the PVM might be used to index a database of physical descriptions of the transformer that could provide additional information to assist with diagnosis.

Partial discharge monitoring of power transformers using UHF sensors. Part I: sensors and signal interpretation

Partial discharges (PD) generate wideband radio frequency interference and, consequently, can be detected using radio receiving equipment. Due to the advances in ultra-high-speed sampling equipment, it is possible to accurately measure the propagation of the PD wavefront as it passes through a 4 element antenna array. From these measurements, the three-dimensional position of the PD source can be calculated using an iterative algorithm. The locating equipment is suitable for use within the vicinity of energized high-voltage plant and can locate sources up to 15 m from the array. Results are presented showing the location ability of the equipment under laboratory and field conditions. A significant advantage is the ability to detect PD sources in energized plant without the need for outages or electrical connections.

Radiometric location of partial discharge sources on energized high-Voltage plant

Online diagnostics and online condition monitoring are important functions within the operation and maintenance of power transformers. This paper describes how a multi-agent system (MAS) for transformer condition monitoring has been designed to employ the data generated by the ultra high frequency (UHF) monitoring of partial discharge activity. It describes the rationale behind the use of multi-agent techniques, and the problems overcome through this technology. Every aspect of the MAS design is discussed. In addition, the design and performance of the intelligent interpretation techniques are detailed.

The design of a multi-agent transformer condition monitoring system

Because of the large capital value of power transformers and their critical role in the electricity network, there is an increasing need for non-intrusive diagnostic and monitoring tools to assess their internal condition. The UHF technique is being applied increasingly to monitor partial discharges (PD) in power transformers and has been shown to be much more sensitive than acoustic techniques when the signal path passes through solid insulation. Field trials were performed on five power transformers ranging in size from 18 to 1000 MVA and in voltage from 25 to 400 kV. The results of PD tests on power transformers provide sufficient evidence to justify making provision for UHF sensors on new transformers to facilitate their monitoring when required during the service lifetime.

Partial discharge monitoring for power transformer using UHF sensors. Part 2: field experience

Wavelet analysis, being a popular time-frequency analysis method has been applied in various fields to analyze a wide range of signals covering biological signals, vibration signals, acoustic and ultrasonic signals, to name a few. With the capability to provide both time and frequency domains information, wavelet analysis is mainly for time-frequency analysis of signals, signal compression, signal denoising, singularity analysis and features extraction. The main challenge in using wavelet transform is to select the most optimum mother wavelet for the given tasks, as different mother wavelet applied on to the same signal may produces different results. This paper reviews on the mother wavelet selection methods with particular emphasis on the quantitative approaches. A brief description of the proposed new technique to determine the optimum mother wavelet specifically for machinery faults diagnosis is also presented in this paper.

Wavelet Analysis: Mother Wavelet Selection Methods

A new technique for analyzing partial discharge (PD) signals based on ultra-high frequency (UHF) measurements is presented, using results from site tests. Signals from simultaneously active discharge sources can be mapped according to their point of origin in a manner that will simplify the interpretation of phase-resolved discharge patterns. The scheme has the potential to allow automated location and tracking of multiple discharge sources in power transformers and other metal-clad high-voltage plants.

Applying UHF partial discharge detection to power transformers

Although the UHF technique is immune from electrical interference; communication noises, thermal noise from the detection system, and periodic pulse-shaped noise from thyristor operation are usually found in the UHF signal. In this paper, a method based on discrete wavelet transforms is introduced. Three steps in the de-noising process are studied and discussed. Hundreds of combinations involved in the process are compared. An artificial signal is created by mixing the specific noise with a 'clean' UHF signal. The optimal process and corresponding parameters are defined by comparing the 'clean' signal and the de-noised version of the artificial signal.

Denoising UHF signal for PD detection in transformers based on wavelet technique

Sensors operating in the ultra-high frequency (UHF) band have been used to detect internal discharges during site testing of a 1000 MVA oil-filled transformer. The transformer was operated at voltages exceeding normal levels by up to 15%. Two discharge sources were detected at both sensors using UHF test equipment. Discharge signals are analyzed in phase-resolved form and time-of-flight measurements are used to provide further information regarding their origin. The results indicate that the UHF method could prove very effective for transformer testing and online PD monitoring.

Power transformer monitoring using UHF sensors: site trials

Time delay estimation (TDE) is essential for PD location using the UHF technique. However, noise and effects of multi-path propagation are two main problems affecting the accuracy of the estimate. Comparing two methods, which are based on the cumulative energy curve and power curve respectively, a cross correlation based method is employed to achieve the estimation. A high-pass filter is applied to the UHF signal to eliminate operating noises. The phase characteristic of the filter is designed to be linear for making the time delay a constant in terms of frequency. A window in the time domain is selected to reduce the effect of multi-path propagation.

Time delay estimation for UHF signals in PD location of transformers [power transformers]

This paper describes an online monitoring system which detects both partial discharges and the underlying power frequency leakage current on an insulator surface. This could allow degradation of the insulator performance to be monitored remotely. The sensing element would be a metal band fitted around the insulator close to the earthed terminal. High and low frequency components of current are separated and recorded in order that trends can be observed. A pollution model was devised which replicated the deposition of surface contamination on insulators in a practical laboratory experiment. The effectiveness of the experimental technique for detecting pollution build up was studied using this arrangement.

C.J. Bennoch

Papers

Applying UHF partial discharge detection to power transformers

Denoising UHF signal for PD detection in transformers based on wavelet technique

Power transformer monitoring using UHF sensors: site trials

Time delay estimation for UHF signals in PD location of transformers [power transformers]

System for on-line monitoring of pollution levels on solid insulators