Investigation of Degradative Signals on Outdoor Solid Insulators Using Continuous Wavelet Transform

Most outdoor solid insulators may suffer from surface degradations due to non-stationary currents that flow on the insulator surface. These currents may be classified as leakage, discharge and tracking currents due to their disturbing potencies respectively. The magnitude of these currents depends on the degree of the contamination of surface. The leakage signals are followed by discharge signals and tracking signals which are capable of forming carbonized tracking paths on the surface between high voltage. and earth contacts (surface tracking). Surface tracking is one of the most breakdown mechanisms observed on the solid insulators, especially polymers which may cause severely reduced lifetime. In this study the degradations observed on polyester resin based insulators are investigated according to the IEC 587 Inclined Plane Test Standard. The signals are monitored and recorded during tests until surface tracking initiated. In order to prevent total breakdown of an insulator, early detection of tracking signals is vital. Continuous Wavelet Transform (CWT) is proposed for classification of signals and their energy levels observed on the surface. The application of CWT for processing and classification of the surface signals which are prone to display high frequency oscillations can facilitate real time monitoring of the system for diagnosis

A Comparative Study of Empirical and Variational Mode Decomposition on High Voltage Discharges

Signal quality is the key issue for maintaining effective power transmission in electrical networks. In most cases, a high voltage (HV) is transmitted in power systems to decrease power loss. Power quality disturbances are monitored by observing the noise degradation of HV signals. Increased oscillations and high-frequency components of power signals exhibit nonstationary signal characteristics. In this study, a comparative analysis of empirical mode decomposition (EMD) and variational mode decomposition (VMD) was conducted on noisy discharge signals. These techniques were used for adaptive signal decomposition in the time domain, facilitating the evaluation of deeper characteristics of the investigated signal.The HV discharges were obtained using 0.4/40 kV and 8 kVA transformers in a laboratory, and all the current and voltage signal waveforms were recorded using high-frequency current and high-voltage probes.The results demonstrate distinct calculations of EMD and VMD techniques in terms of signal decomposition and extracting intrinsic mode functions (IMFs), which define low- and high-frequency components

Adaptive detection of chaotic oscillations in ferroresonance using modified extended Kalman filter

Power quality and power disturbances have become an important factor for power systems. Chaotic ferroresonance is one of the disturbances that may cause overvoltages and overcurrents; hence, it can endanger the system reliability and continuous safe operating. A power system that generates chaotic oscillations is a dynamic system, which can be modeled with a Duffing equation. This paper introduces the application of a modified extended Kalman filter for improving the detection of chaotic behavior of power system signals. A modification algorithm is used to increase the estimation performance of the former casual extended Kalman filter. The proposed method is employed to distinguish the abnormalities from a signal contaminated with chaotic ferroresonance for promoting efficiency in power system characteristics detection

MODELLING OF CHAOTIC SURFACE TRACKING ON THE POLYMERIC INSULATORS WITH HIDDEN MARKOV MODELS

In this study, chaotic surface tracking patterns observed on polymeric high voltage (HV) outdoor insulation materials were investigated and simulated The polymeric samples are tested according to the IEC 587 Inclined Plane Tracking Test Standard Since the chaotic surface tracking patterns manifests smutty and disordered images, they are preprocessed and purified by image processing tools. Internal and external effects may severely decrease insulation performance. In order to examine external effects, samples are subjected to moisture and vibration effect Polymer samples are investigated by their fractal dimension which is a prominent tool for analyzing chaotic images. To simulate these chaotic surface tracking patterns Hidden Markov Models (HMM) are use

Analysis of frequency characteristics of electrical arcs on the insulating sheath of the ADSS fiber optic cables

The insulating outer-sheath of ADSS (All dielectric self supporting) cables used on high voltage transmission lines are often subjected to various environmental effects. The ageing process of cable sheath can be investigated by using the dry-band arcing test method under laboratory conditions. Dry-band arcing is the most common technique to determine the ageing period of insulating materials. Environmental effects such as rain, humidity, dew and ice produce various amounts of wet regions on the cable surface. Electrical arcs and hence degradations are occurred on the cable surface due to the enhanced electrical field with formation of wet regions. In this study, the ageing process of ADSS cables was investigated by using the dry band arcing test method (IEEE 1222 Electrical surface degradation). Rainfall intensity determines the wet regions on the cable surface which affects the ageing process of the cable. During tests electrical arc signals were investigated by analyzing wet region scope versus amplitude and frequency spectrum variations via the FFT method. It is possible to claim that the proposed EFT analysis clearly identifies the ageing period of the ADSS cable which was subjected to different rainfall intensities by monitoring frequency spectrum of the arc signals

Electrical Distribution Network's Failure Analysis Based on Weather Conditions

The failure detection and response time for failures in electrical distribution networks are key elements for proper power management in distribution companies. The reliability of electrical distribution is strictly related with weather conditions especially in overhead lines. Severe weather conditions can rapidly increase failure rates in distribution networks where company responses for failures may delayed consequently. In this study, electrical distribution network statistics of Bedas Company for Gaziosmanpasa district which contains highest overhead line population in Istanbul are investigated. These statistics are collected from failure management system in Bedas Distribution Company between 2014 and 2016. Especially electrical connector and oxidation failure rates are analyzed for different weather conditions. These statistics are compared with first four months of year 2017 which exhibit severe weather conditions and heavy falls. This study reveals the relationship between different weather conditions and failures in electrical distribution network which can be utilized for predictive management for distribution companies in terms of failure elimination and quick failure response

Fractal Dimension Analysis of Uroflowmetry Signals

The Uroflowmetry test is a commonly used method, which evaluates urine flow rates and volumetric analysis of patients. Flow rates and volumetric analysis are employed for assessing various urinary disorders such as Urethral Stricture, Bladder control problems, prostate etc. In this study, ten different Uroflowmetry signals of both abnormal and normal patients are processed. The Higuchi's fractal dimension computation is proposed for analyzing and investigating the characteristics of these signals. The Higuchi's method is an effective tool for measurement of fractal dimension of self-affine signals which is proposed for online monitoring of Uroflowmetry signals of patients and hence accelerated diagnose of urinary disorders

The Electrical Characteristics of Electroconductive Gels Used in Biomedical Applications

Electroconductive gels are widely used in biomedical applications for a proper transmission of produced signals to related body points of patients. During the transmission the biomedical gels play vital role in terms of relatively small signal loss and hence effective treatment. In some cases, disposable electrodes with self-gel attachments are used for quick application, however there are several critical cases in which additional gel application is required such as electrocardiogram (ECG), electroencephalogram (EEG), Ultrasound, Transcutaneous Electrical Nerve Stimulation (TENS) and etc. The electrode gel and skin combination structure simulates a circuit equivalent which contains capacity and a series resistive. In this study the electrical characteristics of electroconductive gels are investigated based on this equivalent circuit. Five different commercially available electroconductive gels are used as dielectric material between copper plates constructed for simulating biomedical electrodes which operate as a capacitor. During the tests the capacitance and dissipation factors of the conductive gels are measured. Also conductivity and TDS (Total Dissolved Solids) values are obtained for gel samples. A comparison of these characteristics may facilitate proper gel choice in biomedical application

Location estimation of partial discharge-based electromagnetic source using multilateration with time difference of arrival method

In high-voltage systems partial discharges (PD) may occur due to the degradation of insulation materials in addition to different scenarios such as material properties, construction, setup and operation conditions. Especially for a power transformer, the degradation of inner insulation may prevent regular operation and hence cause failure. In a long time period even low-level PD activity may cause degradation on the insulator. If the deterioration caused by the PD is detected in an early phase, potential damage may be prevented. Due to the complex and close structure of power transformers and other high-voltage systems, it is not easy to estimate the exact location of a PD. This study proposes a novel approach to detect and analyze an artificial PD in a laboratory room setup, which is especially designed for simulation of possible PD source in a large scale structure such as power transformer. Electromagnetic (EM) PD sensors are commonly used to detect electromagnetic pulses emitted from PD sources. In this work, the time differences of arrivals (TDOA) which are obtained from PD signals are subjected to multilateration technique to estimate the exact location. A novel energy level method is introduced to overcome correct TDOA extraction problem. Cramer-Rao bound (CRB) is used for calculation of the minimum achievable estimation error of proposed method. In order to display the accuracy of location estimation, CRB and the mean square error graphics of the estimated location parameters are given for the comparison

Electrical Distribution Network's Failure Analysis Based on Weather Conditions

5th International Conference on Electrical and Electronics Engineering (ICEEE) -- MAY 03-05, 2018 -- Istanbul, TURKEYThe failure detection and response time for failures in electrical distribution networks are key elements for proper power management in distribution companies. The reliability of electrical distribution is strictly related with weather conditions especially in overhead lines. Severe weather conditions can rapidly increase failure rates in distribution networks where company responses for failures may delayed consequently. In this study, electrical distribution network statistics of Bedas Company for Gaziosmanpasa district which contains highest overhead line population in Istanbul are investigated. These statistics are collected from failure management system in Bedas Distribution Company between 2014 and 2016. Especially electrical connector and oxidation failure rates are analyzed for different weather conditions. These statistics are compared with first four months of year 2017 which exhibit severe weather conditions and heavy falls. This study reveals the relationship between different weather conditions and failures in electrical distribution network which can be utilized for predictive management for distribution companies in terms of failure elimination and quick failure response.IEE