Riddhi Ghosh

A method for the localization of partial discharge sources using partial discharge pulse information from acoustic emissions

Partial discharge (PD) localization employing acoustic emission technique is commonly done by estimating the time difference of arrival (TDOA) between signals captured at multiple acoustic sensors placed on the walls of the transformer tank. The localization accuracy of PD sources depends on the accuracy with which the TDOA is estimated. Hence it is important to accurately estimate the TDOA as far as possible. This paper presents a novel approach for the estimation of TDOA which is based on the source-filter model of acoustic theory. The TDOA is estimated by extraction of the excitation source signal from the acoustic signals in the form of an estimation of the PD pulse. The PD pulse serves as the excitation source signal for the acoustic detection system, whereas the acoustic path through the transformer tank and oil constitutes the physical system, which when excited by the PD pulse, gives rise to the acoustic pressure waves. The source-filter model extracts an estimation of the excitation source (PD pulse) by isolating it from the acoustic response of the tank-oil system. The extracted PD pulse information gives a sharp estimate of the instant of appearance of the PD pulse at each sensor. Hence, the TDOA between any two sensors determined from the cross-correlation function between the PD pulse estimates at the respective sensors gives a high estimation accuracy.

A method for unambiguous identification of on-field recorded insulator leakage current waveforms portraying electrical activity on the surface

The measurement of insulator leakage current in the field is necessary to have a better understanding of the electrical phenomena on the insulator surface. Since this electrical activity cannot be anticipated in advance, long term monitoring and storage of actual waveforms is necessary. This leads to significant accumulation of data. The presence of field noise in leakage current measurement further aggravates the problem of data size. The storage of noisy waveforms consumes available storage space without adding any significant information regarding the insulator condition. Therefore, it must be ensured that only the on-field recorded waveforms which reflect significant electrical activity on the surface are recorded. In this paper, the authors have proposed the use of Short- Time Modified Hilbert Transform (STMHT) to enhance the local characteristics of the field-recorded waveforms. It has been shown that the magnitude of the STMHT of a waveform at any instant has a good correlation with the slope of the waveform at that instant. Using this property, the proposed method is able to segregate the different types of field noise from waveforms portraying significant electrical activity. It is expected that this paper will contribute to the development of efficient devices for field monitoring of insulators.

A Novel Leakage Current Index for the Field Monitoring of Overhead Insulators Under Harmonic Voltage

Leakage current measurement is the most reliable and effective method for condition monitoring of overhead insulators deployed in the field. However, a major challenge in the leakage current based insulator monitoring is to interpret the indices extracted from the leakage current measurements under varying harmonic content in system voltage. This paper reports the possibility of employing the instantaneous value of time-integral of leakage current as a low-sensitive parameter for the monitoring of leakage current in overhead insulators in the presence of voltage harmonics. It has been shown that any change in the harmonic content of the system voltage has a significant influence on the harmonic characteristics of the leakage current, but has a comparatively less severe effect on the time-integral. The monitoring technique has been validated through laboratory recorded experimental data and incorporated in an online measurement device that has been tested in the laboratory.

Investigations on the effect of voltage harmonics on leakage current for condition monitoring in insulators

Leakage current pattern and its harmonic content are widely known to be excellent monitoring indices for condition assessment of overhead line insulators. Whenever there is a change in the contamination severity on the insulator surface, a corresponding change in the leakage current is observed. Traditionally, it has been assumed that the changes in leakage current pattern are entirely due to the changes in surface condition of insulators. However, in real-time online monitoring, the system voltage and its harmonic content will also have a certain effect on the leakage current pattern. Changes in the harmonic content of system voltage may also produce changes in the leakage current pattern. This may lead to incorrect interpretation of the obtained results where systems are prone to harmonic distortions. In such cases, there is no way of knowing whether the change in leakage current pattern is entirely due to changes in surface condition of insulators or on account of harmonics in the applied voltage. Keeping this in mind, this work investigates for the first time the effect of presence of harmonics in voltage waveform on the leakage current pattern in overhead insulators. The purpose of this paper is to present the preliminary results on the degree of influence of voltage harmonics on the leakage current pattern, and demonstrate the importance of more detailed research on the topic.

Remote monitoring of power frequency electrical signals employing GSM network

Mobile phones are the backbone of modern day communication system and have undergone an immense growth in recent years. The use of mobile phones is no longer limited only to the traditional applications of call and messaging. Current research trends indicate that mobile phones are being used for a variety of innovative applications such as mobile-based sensing and data communication. With this in mind, and with such widespread availability of mobile towers and ready infrastructure, a unique application of the mobile network can be to communicate technical information regarding the condition of an electrical system. Thus, this paper proposes a method, whereby it is possible to transmit power frequency electrical signals over the GSM voice channel. as a means for low cost, yet state of the art, remote condition monitoring system.

Remote condition monitoring of high voltage insulators employing GSM network

Remote condition monitoring of power apparatus is a much sought after research area at present. With the existing power network about to be upgraded to a smart grid system in the near future, remote condition monitoring will soon become a critical aspect of the power network. With this in mind, a technique has been proposed in this paper, whereby it is possible to transmit insulator leakage current signal over the GSM voice channel as a means for low cost, yet state of the art, remote condition monitoring system. The scheme proposed in this paper is developed in such a way that it is flexible enough to be applicable to condition monitoring of various power apparatus which employ power frequency signals as analysis tools.

Localisation of single and multiple partial discharge sources based on sequence of arrival and levels of peak amplitude of acoustic emissions

Partial Discharge (PD) is one of the most critical electrical phenomena affecting the life of electrical equipment. Repetitive PD can lead to gradual deterioration of the insulation, which may further lead to complete failure of the electrical insulation. Hence, detection and localization of PD inside electrical equipment is necessary for early detection of impending failure. Keeping this in mind, this paper proposes a methodology to localize single and multiple PD sources based on acoustic signals emanated from such sources. The localization has been done based on sequence of arrival and levels of peak amplitude of acoustic waves. The proposed approach makes use of a low complexity methodology for PD localization without the use of complex classification tools. The results show that this developed methodology is able to localize the single and multiple PD events with considerable accuracy.

Identification and localization of series and shunt faults along a transformer winding using a rough set classifier aided with S-transform

In this paper, a Rough Set based approach aided with S-Transform features have been proposed for classification of short circuit faults during impulse test of a transformer. The required winding current waveforms are acquired by emulating short circuit faults across different disc positions in the analog model of a 33 kV winding of a 3 MVA transformer using developed analog fault simulator. Significant features are extracted for identification of various fault characteristics. It was found that the features extracted from S-transform data were sufficient for efficient classification of different fault cases and also application of Rough sets with a minor modification helps in improving the classification accuracy percentage.

A new method for the estimation of time difference of arrival for localization of partial discharge sources using acoustic detection technique

In an acoustic partial discharge (PD) detection system, estimation of time difference of arrival (TDOA) between acoustic signals arriving at a sensor array is an important criterion for accurate localization of PD sources inside a transformer. The localization accuracy can be improved by improving the accuracy of estimation of TDOA between sensors. The estimation of TDOA is a challenging task because acoustic signals are corrupted by noise, reverberation, echo and reflection of acoustic signals inside the transformer tank. Keeping this in mind, this paper presents a technique for the accurate estimation of TDOA by extraction of an estimate of the PD pulse from the recorded acoustic signals. The TDOA between two sensors is then calculated by finding the cross-correlation function between the two sensors. The acoustic path through the transformer tank and oil constitutes the physical system, which when excited by the PD pulse, gives rise to the acoustic pressure waves. An estimate of the PD pulse, which generates the acoustic pressure waves, may therefore be obtained by separating the acoustic response of the tank-oil physical system from the acoustic signal. The extracted PD pulse information gives an estimate of the instant of appearance of the PD pulse at each sensor, which makes the accurate estimation of TDOA possible.

A low-complexity method based on compressed sensing for long term field measurement of insulator leakage current

Field measurements of insulator leakage current are necessary for long term data storage for research purposes and condition-based maintenance. Long term monitoring and storage of actual waveform are required since the electrical activity on the insulator surface cannot be predicted in advance. This leads to the accumulation of large amount of data. One solution is to optimize the local storage space usage by implementing mathematical tools to eliminate noise and data with low information content. However, the method is computationally intensive and large scale deployment of devices based on such methods is costly. Proper condition-based maintenance cannot be guaranteed without large-scale use of monitoring devices in the field. Thus, the authors propose the use of an alternate low-complexity approach based on compressed sensing that addresses the issue of data size in field measurements. The compressed sensing based technique is perfectly suitable for large-scale deployment of leakage current measurement devices in the context of field monitoring in insulators. The method is structured to deploy low computational burden in the monitoring devices by shifting the entire computational load from the monitoring device in the field to the decoder at the central monitoring station. Different categories of field measured waveforms have been used to demonstrate the performance of the proposed method. It is expected that this paper will contribute to the development of efficient field monitoring devices in insulators.