On-line Partial Discharge Monitoring Research Articles

Novel inductive sensor solutions for on-line partial discharge and power quality monitoring

Networks of medium voltage have spread over a long distance through underground cables. The aim to prolong the life span of existing network assets increases the need for condition monitoring to prevent unplanned and long lasting interruptions. Continuous on-line partial discharge (PD) measurement is an excellent way to determine the overall health of the medium voltage (MV) components and to detect developing faults in underground cables. A sensor is an essential part of the PD monitoring system which measures the high frequency PD signals. PD sensors can be used to measure power frequency current and harmonic currents on the MV side to estimate the thermal loading of transformer or incoming cable provided that the sensors have a suitable frequency response for measuring low frequency signals as well. A novel inductive sensor is described in this paper which allows both PD measurements as well as power quality (PQ) measurements at frequency range below 2.5 kHz. Authors did experiments on different ferrite cores in order to design the best possible sensor which can be used for both PD and PQ measurement. Characteristics of the sensors, including sensitivity, saturation current, and frequency bandwidth, as well as relative errors are provided and analyzed under laboratory conditions. At the end, developed sensors are compared with a commercial HFCT sensor, the Rogowski coil and power quality current sensors to show the capability of the sensors to be used for PD and PQ measurements.

SDMF based interference rejection and PD interpretation for simulated defects in HV cable diagnostics

Partial Discharge (PD) in cable systems causes deterioration and failure, identifying the presence of PD is crucial to Asset Management. This paper presents methods for interference signals rejection and for PD interpretation for five types of artificial defect in 11 kV ethylene-propylene rubber (EPR) cable. Firstly, the physical parameters of the artificial defects used for PD signal generation are introduced. Thereafter, the sample stress regime, PD testing and detection systems, including IEC 60270 measurement system and High Frequency Current Transformer (HFCT), are outlined. Following on, a novel Synchronous Detection and Multi-information Fusion (SDMF) based signal identification method is developed, to separate PD and interference signals within raw data. Finally, a comparative PD analysis of two detection systems is carried out and several characteristics of insulation related PD signals of EPR cables are reported. The SDMF based data pre-processing and the comparative PD activity analysis contribute to improvement of PD pattern recognition and assist in on-line PD monitoring systems.

Moisture Migration in an Oil-Paper Insulation System in Relation to Online Partial Discharge Monitoring of Power Transformers

Most power transformers operating in a power system possess oil-paper insulation. A serious defect of this type of insulation, which is associated with long operation time, is an increase in the moisture content. Moisture introduces a number of threats to proper operation of the transformer, e.g., ignition of partial discharges (PDs). Due to the varying temperature of the insulation system during the unit’s normal operation, a dynamic change (migration of water) takes place, precipitating the oil-paper system from a state of hydrodynamic equilibrium. This causes the PDs to be variable in time, and they may intensify or extinguish. Studies on model objects have been conducted to determine the conditions (temperature, humidity, time) that will have an impact on the ignition and intensity of the observed phenomenon of PDs. The conclusions of this study will have a practical application in the evaluation of measurements conducted in the field, especially in relation to the registration of an online PD monitoring system.

A New Directional Coupler Type Partial Discharge Sensor Installed on the Power Lead of Rotating Machine

For on-line partial discharge (PD) monitoring of rotating machines, a novel sensor is proposed, which can be installed on the power lead inside the terminal box of the machine. The sensor has been designed to have high capacitance, and minimal reflection of measured pulses. As a sensitivity of the sensor, transfer impedance Zt has been measured and compared to conventional coupler-type sensors. A simple method is presented for measuring Zt of coupler sensors, using a vector network analyzer and a practical lead-cable of rotating machine. Through this method, it became possible to measure the Zt of coupler sensors including the installation environment of them. The Zt of the proposed sensor is higher than that of same sized other conventional couplers at frequencies between 30 and 92 MHz. Another sensitivity test has been performed using a PD calibrator as a test pulse source. The proposed sensor has higher measured peak voltage than the conventional coupler type sensors when the same charges were input.

Comparison of pd detection methods for power transformers - their sensitivity and characteristics in time and frequency domain

Partial discharge (PD) detection is an important method for detecting defects in power transformers, and several PD detection methods reported in literature have their respective advantage and disadvantages. In this paper, a simplified PD coupler attached to the tap of the bushing, whose reliability is verified by the EMTP simulation, is proposed in order to extend the application of on-site tap PD detection. Experiments were carried out on 110 kV transformer models to compare the sensitivity of the sensor with some other popular PD detection methods. The characteristics of the detected signals suggest that the proposed coupler has satisfactory sensitivity as well as potential to solve some on-site noise-rejection problems by introduction of ultra-high frequency amplifiers, and thus could be suitable in future for online PD monitoring applications in substations.

Rough set theory applied to pattern recognition of Partial Discharge in noise affected cable data

This paper presents an effective, Rough Set (RS) based, pattern recognition method for rejecting interference signals and recognising Partial Discharge (PD) signals from different sources. Firstly, RS theory is presented in terms of Information System, Lower and Upper Approximation, Signal Discretisation, Attribute Reduction and a flowchart of the RS based pattern recognition method. Secondly, PD testing of five types of artificial defect in ethylene-propylene rubber (EPR) cable is carried out and data pre-processing and feature extraction are employed to separate PD and interference signals. Thirdly, the RS based PD signal recognition method is applied to 4000 samples and is proven to have 99% accuracy. Fourthly, the RS based PD recognition method is applied to signals from five different sources and an accuracy of more than 93% is attained when a combination of signal discretisation and attribute reduction methods are applied. Finally, Back-propagation Neural Network (BPNN) and Support Vector Machine (SVM) methods are studied and compared with the developed method. The proposed RS method is proven to have higher accuracy than SVM and BPNN and can be applied for on-line PD monitoring of cable systems after training with valid sample data.

On Line Monitoring of Partial Discharge in High Voltage Cables

Now China vigorously develop urban underground cable, the scale of the underground power grid is gradually expanding, the voltage level of the high voltage cable from the original 23 35kV to kV, and then to 110kV and even 220kV rising. In cable trench, different levels of voltage cable mixed, ditch perennially humid, even perennial water and power cable trench no monitoring equipment for use, thus for on-line monitoring caused a lot of difficulties. On line detection of the key technologies for signal extraction and anti interference technology. In this paper, a scheme of real-time partial discharge on-line monitoring for high voltage cables is designed.

An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers

Ultra-high-frequency (UHF) partial discharge (PD) online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intelligent sensor is qualified for the UHF PD online monitoring of power transformers. Additionally, three methods to improve the performance of intelligent sensors were proposed according to the principle of the level scanning method.

Investigation of Partial Discharges at the High Voltage Electric Motor Bars

It is well known the use of on-line partial discharge (PD) measurements as an indicator of stator winding insulation condition. The scheduled PD measurements could be used as a test to evaluate the quality of the equipment. The test results could help to diagnose the insulation problems in motors and generators for corresponding action before failure occurs. Although a number of PD measurement methods exists, but the tests results of on operating rotating machines can be influenced by conditions such as humidity, temperature, terminal voltage, and load. This paper describes the development of PD imitation mathematical model in stator insulation. The experimental investigation with physical model was performed for adequacy assessment. The capacitive sensor was used for PD online monitoring. DOI: http://dx.doi.org/10.5755/j01.eie.22.2.6983

Relative ability of UHF antenna and VHF capacitor methods to detect partial discharge in turbine generator stator windings

On-line partial discharge (PD) monitoring is widely used to detect stator winding insulation deterioration. The most common type of on-line PD sensor for turbine generators is the 80 pF capacitive coupler installed at the machine terminals which detects the PD in the very high frequency (VHF) range. More recently, ultra high frequency (UHF) antennae have also been used to detect stator winding PD in large turbine generators. Both types of sensors have been installed in 16 turbine generators. This paper discusses the results from near simultaneous measurements from both types of sensors on the same machines. It was expected that the UHF sensors would have stronger discrimination of the electrical disturbances internal to the machine compared to the VHF sensors, but the VHF sensors would be more sensitive to PD. As expected, the VHF sensors were generally more corrupted by electrical disturbances. However, in about half of the machines investigated here, the UHF sensors were significantly more sensitive than the VHF sensors. Many examples of phase-resolved PD patterns that illustrate these findings are presented.

Ultra-broadband phase-sensitive optical time-domain reflectometry with a temporally sequenced multi-frequency source.

A phase-sensitive optical time-domain reflectometry (Φ-OTDR) with a temporally sequenced multi-frequency (TSMF) source is proposed. This technique can improve the system detection bandwidth without the sensing range decreasing. Up to 0.5 MHz detection bandwidth over 9.6 km is experimentally demonstrated as an example. To the best of our knowledge, this is the first time that such a high detection bandwidth over such a long sensing range is reported in Φ-OTDR-based distributed vibration sensing. The technical issues of TSMF Φ-OTDR are discussed in this Letter. This technique will help Φ-OTDR find new important foreground in long-haul distributed broadband-detection applications, such as structural-health monitoring and partial-discharge online monitoring of high voltage power cables.

Feature parameters extraction of gis partial discharge signal with multifractal detrended fluctuation analysis

Ultra-high frequency (UHF) method is widely used in gas-insulated switchgear (GIS) partial discharge (PD) online monitoring because this technique has excellent anti-interference ability and high sensitivity. GIS PD pattern recognition is based on effective features acquired from UHF PD signals. Therefore, this paper proposes a new feature extraction method that is based on multifractal detrended fluctuation analysis (MFDFA). UHF PD signals of four typical GIS discharge models that were collected in a laboratory were analyzed. In addition, the multifractal feature of these signals was investigated. The single-scale shortcoming of traditional detrended fluctuation analysis and its sensitivity to interference information trends were overcame. Thus, the proposed method was able to effectively characterized the multi-scaling behavior and nonlinear characteristics of UHF PD signals. With the use of the shape and distribution difference of the multifractal spectrum, seven feature parameters with clear physical meanings were extracted as feature quantity for pattern recognition and input to the support vector machine for classification. Results showed that the feature extraction method based on MFDFA could effectively identify four kinds of insulation defects even with strong background noise. The overall average recognition rate exceeded 90%, which is significantly better than that of wavelet packet-based feature extraction.

Hybrid method on signal de‐noising and representation for online partial discharge monitoring of power transformers at substations

To ensure reliable operations of power transformers, online condition monitoring needs to be performed. However, extensive noise can be coupled into measured signals and cause ambiguities in evaluating transformers' conditions. This study proposes a hybrid method, which combines pre-whitening and blind equalisation for de-noising the signals obtained from online partial discharge (PD) measurements of transformers. A measured signal is first gone through a pre-whitening process for initial noise reduction and then processed by blind equalisation. Finally, an equalised signal that can reveal PD source in a transformer is converted to a kurtogram for an accurate PD pattern representation. The proposed method has been applied to signals obtained from laboratory experiments and online measurements of transformers at substations. Results show that the method can effectively de-noise PD signals contaminated by severe noise and consistently represent PD patterns induced by different PD sources.

A novel on-line cable pd localisation method based on cable transfer function and detected pd pulse rise-time

This paper presents a novel Partial Discharge (PD) localisation method, based on PD pulse Rise-Time and Transfer Function (RTTF), for use in on-line cable PD monitoring systems. This is based on the change in rise time as a function of cable length along which a PD pulse has propagated. A comparison with four other well-known location techniques, i.e. Time-Domain Reflectometry (TDR), Phase difference, Arrival Time Analysis (ATA) and Amplitude-Frequency (AF) mapping has been made and presented. Analysis shows that the TDR and Phase difference methods, although requiring a single measurement point, are only applicable to short length cable systems as both incident pulse and reflected pulse should be observable when it reaches the detection point. On the other hand, the ATA and AF mapping, which can be applied to longer cable systems, need to install detectors at multiple points and detect synchronously. In comparison, PD localisation by the proposed RTTF method, which requires detection of the incident pulse at only one measurement point, can be used to localise a PD source which is further away from the PD detection point than other methods and can be used in on-line PD monitoring systems. As on-line PD monitoring sensors commonly comprise of a high frequency current transformer (HFCT) and a high-pass filter, the rise time of detected PD pulses depends on the attenuation of the cable, the HFCT used and the filter applied. Simulations of pulse propagation in a cable and PD monitoring system are performed, based on analyses in the frequency domain using the concept of transfer functions. Results of RTTF from the simulations have been verified by laboratory experiments and on-site PD measurements, which provide evidence that the RTTF method is a very valuable and useful PD localisation technique.

A New Method for Suppressing Periodic Narrowband Interference Based on the Chaotic van der Pol Oscillator

The chaotic van der Pol oscillator is a powerful tool for detecting defects in electric systems by using online partial discharge (PD) monitoring. This paper focuses on realizing weak PD signal detection in the strong periodic narrowband interference by using high sensitivity to the periodic narrowband interference signals and immunity to white noise and PD signals of chaotic systems. A new approach to removing the periodic narrowband interference by using a van der Pol chaotic oscillator is described by analyzing the motion characteristic of the chaotic oscillator on the basis of the van der Pol equation. Furthermore, the Floquet index for measuring the amplitude of periodic narrowband signals is redefined. The denoising signal processed by the chaotic van der Pol oscillators is further processed by wavelet analysis. Finally, the denoising results verify that the periodic narrowband and white noise interference can be removed efficiently by combining the theory of the chaotic van der Pol oscillator and wavelet analysis.

An efficient PD data mining method for power transformer defect models using SOM technique

Abstract Suggestion and application of a set of new features for on-line Partial Discharge (PD) monitoring, where there is no information about the type of PD is a challenging task for condition assessment of power equipments, such as a power transformer. This is looked for in this paper. So far, in past various techniques have been employed to develop a comprehensive PD monitoring system, however limited success has been achieved. One of the challenging issues in this field is the discovering of proper features capable of differentiating the involvement of possible types of PD sources. In order to examine the efficiency of the method established in this paper, which is based on application of a set of new feature spaces, texture feature analysis, followed by application of principal component analysis (PCA) and self-organizing map (SOM) is used to analyze and interpret the time-domain-captured PD data. The results of this work demonstrate the capabilities of the aforementioned features space to be used as a supplementary knowledge-base to help experts making their decisions confidently.

Continuous Remote Online Partial Discharge Monitoring of HV Ex/ATEX Motors in the Oil and Gas Industry

This paper presents results from the continued application of a new technique for the remote online partial discharge (OLPD) testing and monitoring of in-service high-voltage (HV) explosive atmosphere (Ex)/atmosphere-explosive (ATEX) motors operating in hazardous gas zones. The technique employs high-current wideband high-frequency current transformer sensors located remotely from the motor under test, at the switchboard end of the HV feeder cable. Significant cost and operational benefits can be gained from this remote monitoring technique as the stator winding condition of these motors can be monitored without having to enter the hazardous gas (Ex/ATEX) zone. The work described in this paper is a continuation of that carried out by the same authors, as reported at the 2012 IEEE Petroleum and Chemical Industry Technical Conference, and includes the development of proposed condition guidelines for assessing the condition of the stator winding insulation systems of large populations of aged HV motors, based on an OLPD “league-table” database. Two case studies are presented wherein the HV stator insulation condition and reliability of in-service motors, operating in hazardous gas zones, and HV generators were assessed using both online and offline partial discharge (PD) testing and monitoring techniques. The case studies emphasize the importance of carrying out extended continuous OLPD monitoring of in-service rotating HV machines to detect underlying trends in PD activity over time. This paper concludes with how condition monitoring data can support reliability-centered maintenance and condition-based management regimes.

High-Voltage Rotating Machines: A New Technique for Remote Partial Discharge Monitoring of the Stator Insulation Condition

In this article, a new technique is presented for the remote online partial discharge (OLPD) monitoring of the stator insulation condition of in-service, high-voltage (HV) rotating machines with a focus on the Ex/ATEX HV motors used in the petrochemical industry. The technique applies wideband, ferrite-based high-frequency current transformer (HFCT) sensors and high-resolution measurement technology. This remote PD monitoring technique has significant advantages when monitoring motors located in Ex/ATEX hazardous gas zones in oil and gas and petrochemical facilities.

Functions and Theoretical Basis of Partial Discharge On-Line Monitoring System for High-Voltage Cables

A partial discharge (PD) on-line monitoring and positioning system for high-voltage cables based on double-ended testing technology is developed. The hardware of this system includes a high-frequency current sensor, site PD signal acquisition and PD monitoring server. In order to achieve real-time monitoring and remote diagnostics of the XLPE cable partial discharge status, the designed software system is divided into front-end control system and remote diagnostic system. And finally, the correctness and effectiveness of the system is verified by XLPE cable partial discharge testing.

The Hardware Design of Partial Discharge On-Line Monitoring System in High Voltage Cable

This article is one of the series of papers about research and development of partial discharge monitoring and positioning systems in cross-linked polyethylene(XLPE) cable. We discuss the design of hardware principle diagram which belongs to partial discharge on-line monitoring and positioning system in XLPE cable in terms of the system block diagram, power management module and control processing module and so on, the operation effect of partial discharge on-line monitoring and positioning system in XLPE cable shows the correctness and effectiveness of the above methods.