Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions.
Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm OptimizationPublished: 01 March 2018 by MDPI in Sensors
The measurement of partial discharge (PD) signals in the radio frequency (RF) range has gained popularity among utilities and specialized monitoring companies in recent years. Unfortunately, in most of the occasions the data are hidden by noise and coupled interferences that hinder their interpretation and renders them useless especially in acquisition systems in the ultra high frequency (UHF) band where the signals of interest are weak. This paper is focused on a method that uses a selective spectral signal characterization to feature each signal, type of partial discharge or interferences/noise, with the power contained in the most representative frequency bands. The technique can be considered as a dimensionality reduction problem where all the energy information contained in the frequency components is condensed in a reduced number of UHF or high frequency (HF) and very high frequency (VHF) bands. In general, dimensionality reduction methods make the interpretation of results a difficult task because the inherent physical nature of the signal is lost in the process. The proposed selective spectral characterization is a preprocessing tool that facilitates further main processing. The starting point is a clustering of signals that could form the core of a PD monitoring system. Therefore, the dimensionality reduction technique should discover the best frequency bands to enhance the affinity between signals in the same cluster and the differences between signals in different clusters. This is done maximizing the minimum Mahalanobis distance between clusters using particle swarm optimization (PSO). The tool is tested with three sets of experimental signals to demonstrate its capabilities in separating noise and PDs with low signal-to-noise ratio and separating different types of partial discharges measured in the UHF and HF/VHF bands.
The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques for source localization, which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo-time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on the Newton–Raphson technique to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), the maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS, is further proposed in this paper. The performance of all algorithms is analysed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences, as well as including errors due to the effect of digital sampling of the time variables. It is shown that the most balanced algorithm, yielding better results than the other algorithms in terms of accuracy and short computational time, is the combined MLE-HLS algorithm.
<p>In the localization of electromagnetic or acoustic emitters, generally, when a pulse is radiated from a source, the wave will arrive to two receivers at different times. One of the advantages of measuring these time differences of arrival or TDOA is that it is not required a common clock as in other localization techniques based on the time of arrival of the pulse to the receiver. With only two sensors, all the possible points in the plane that would give the same TDOA describe a hyperbola. Using an independent third receiver and calculating the intersection of the three hyperbolas will give the position of the source. Therefore, planar localization of emitters using multilateration techniques can be solved at least with three receivers. This paper presents a method to locate sources in a plane with only two receivers reducing the number of acquisition channels and hence, the cost of the equipment. One of the receivers is in a fixed position and the other describes a circumference around the first one. The TDOA are measured at different angles completing a total turn and obtaining a periodic function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive this function analytically with the distance from the fixed receiver to the source and a bearing angle as parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements to obtain the parameters of the position of the source.</p>
To locate the positions of partial discharge sources in free space at least four RF antennas are arranged in a suitable spatial geometry to detect the radiated electromagnet energy from the discharge. The time-difference-of-arrival (TDOA) between the signals from each antenna are then used within multi-lateration equations to determine the position of the source. The iterative Hyperbolic Least Squares (HLS) method and the non-iterative Maximum Likelihood Estimator (MLE) method are two common techniques used in the literature to solve the multi-lateration equations. This paper investigates the ability of combining MLE and HLS to improve location accuracy and maintain fast location computation time. To this end HLS, MLE and the combined MLE-HLS method are evaluated in terms of location accuracy and computation performance for three spatial antenna configurations, namely Square, Pyramidal and Trapezoidal arrangements. The location accuracies for each method are evaluated for theoretical TDOA values and also for the case when a finite sampling rate of 10G samples-per-second is considered; the latter is implemented through appropriate rounding up of TDOA values by one sample time. It is shown that MLE-HLS produces improved location accuracy compared with HLS and MLE for both theoretical and finite sampled TDOA values. In addition, it is shown that MLE-HLS improves significantly the computation time over the iterative HLS method.
In biomechanical applications where an ultrasound signal is used to determine the position of a specific organ or tissue, like for example a bone, a so-called A-mode ultrasonography is used. A ultrasonic pulse is generated by a transducer, injected in the tissue to be examined, and then the echoes are received and processed. Echoes are generated by changes in acoustic impedance in the medium, like for example a change of tissue from muscle to bone. To determine the position of the reflecting interface, the time-of-flight is measured and, utilizing well-know values for the transmission speed, the distance or depth is computed. If the localization device is to be designed to be small, wearable, and low-power, it is expected that the signal will be of worse quality with respect to traditional ultrasonography systems, especially under the point of view of signal-to-noise ratio. In these conditions, the reliability of the algorithm that implement the time-of-flight calculation is of paramount importance. In this paper, a simulated soft tissue-bone interface (implemented with an ultrasound gel-pad) has been measured with intentionally low excitation signals and with the presence of imperfections similar to those expected in a physiological system. Several classic algorithms have been tested and benchmarked in this condition, and a new method with better reliability and repeatability is proposed.
Spatial study of the uncertainties in the localization of partial discharges for different antenna layoutsPublished: 01 May 2017 by Institute of Electrical and Electronics Engineers (IEEE) in 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
The maintenance of high-voltage equipment is paramount to avoid blackouts or the interruption of electrical service. One of the most reliable methods to know the status of insulation systems is the measurement of partial discharges (PD). This phenomenon occurs when the dielectric presents imperfections due to ageing and degradation processes. Partial discharges are sudden releases of charge that can emit energy in a wide band of frequencies even in UHF. Therefore, antennas can be used, not only to detect the occurrence of PD, but to locate the source of emission and, consequently, the damaged asset. The localization can be done using multilateration measuring the time-differences of arrival (TDOA) of the pulses to an array of antennas. However, the onset of the signal is difficult to define due to numerous issues, from low signal-to-noise ratio, to lack of line-of-sight or errors in the positioning of the antennas. Then, the position of the source may have large uncertainties that even can prevent finding the asset at stake. The configuration of the antenna layout can help to minimize the effect of the uncertainties in the measurement of the TDOA. It has been found that there are configurations that favour certain bearings when locating the source giving more accurate results. This paper explores three type of antenna layouts and devises a method to determine what directions are best to orient the array.
<span>The influence of antenna positioning errors on the radio-frequency localization of partial discharges sources</spa...Published: 14 November 2016 by MDPI AG in Proceedings
<p>Electrical insulation can have imperfections due to manufacturing or ageing. When the insulation is electrically stressed, discharges may happen in these inhomogeneous imperfect locations resulting in partial discharge (PD) which have very fast rise times and short time durations. Since charges are accelerated within PD activity, radiated electromagnetic energy across a wide bandwidth of frequencies can occur. The measurement of the radiated PD energy is widely employed to identify defective insulation within high voltage equipment. Based on assessment of the strength and nature of the emitted PD signals, determination is made to carry out predictive maintenance in order to prevent equipment breakdown. The location of emitted radiated PD signals may be determined using multi-lateration techniques using an array of at least 4 antennas. Depending on the relative position between the antennas and the PD source, the radiated emissions from the PD source arrive at each antenna at different times. The relative time differences of arrivals (TDOA) together with the antennas position are variables used to locate the PD source in 3D space. The effect on the location error of a PD source using TDOA calculations based on acquisition sample time errors is a topic which has previously been studied (see bibliography). This paper now investigates the accuracy on PD location as a consequence of error on the measured positions of the antennas. This paper evaluates the influence of positional antenna error on the possible accuracy of the localization of the PD source. This error is analyzed for 3 different antenna array layouts and for different vector directions from the arrays. Additionally, the least sensitive layout with regard to positioning errors is proposed to assist in improving the location accuracy of PD sources.</p>
Partial discharges are ionization processes inside or on the surface of dielectrics that can unveil insulation problems in electrical equipment. The charge accumulated is released under certain environmental and voltage conditions attacking the insulation both physically and chemically. The final consequence of a continuous occurrence of these events is the breakdown of the dielectric. The electron avalanche provokes a derivative of the electric field with respect to time, creating an electromagnetic impulse that can be detected with antennas. The localization of the source helps in the identification of the piece of equipment that has to be decommissioned. This can be done by deploying antennas and calculating the time difference of arrival (TDOA) of the electromagnetic pulses. However, small errors in this parameter can lead to great displacements of the calculated position of the source. Usually, four antennas are used to find the source but the array geometry has to be correctly deployed to have minimal errors in the localization. This paper demonstrates, by an analysis based on simulation and also experimentally, that the most common layouts are not always the best options and proposes a simple antenna layout to reduce the systematic error in the TDOA calculation due to the positions of the antennas in the array.
<p>Partial discharges are ionization processes inside or on the surface of dielectrics that can unveil insulation problems in electrical equipment. The charge accumulated in the dielectric is released under certain environmental and voltage conditions attacking the insulation both physically and chemically. The final consequence of a continuous occurrence of these events is the breakdown of the dielectric. The electron avalanche provokes a derivative of the electric field close to the damaged insulation creating an electromagnetic impulse that can be detected with antennas. The localization of the source of partial discharges helps in the identification of the piece of equipment that has to be decommissioned. This can be done deploying antennas in open-air substations and calculating the time difference of arrival (TDOA) of the electromagnetic pulses. This parameter is critical in the localization and small errors can lead to a great displacement of the calculated position of the source. Usually, four antennas are used to find the source in space but the array has to be correctly deployed to have minimal errors in the localization. This paper demonstrates theoretically and experimentally that the most common layouts are not the best option and proposes a simple antenna layout to reduce the systematic error in the TDOA calculation due to the positions of the antennas.</p>
The detection of partial discharges (PD) can help in early-warning detection systems to protect critical assets in power systems. The radio-frequency emission of these events can be measured with antennas even when the equipment is in service which reduces dramatically the maintenance costs and favours the implementation of condition-based monitoring systems. The drawback of these type of measurements is the difficulty of having a reference signal to study the events in a classical phase-resolved partial discharge pattern (PRPD). Therefore, in open-air substations and overhead lines where interferences from radio and TV broadcasting and mobile communications are important sources of noise and other pulsed interferences from rectifiers or inverters can be present, it is difficult to identify whether there is partial discharges activity or not. This paper proposes a robust method to separate the events captured with the antennas, identify which of them are partial discharges and localize the piece of equipment that is having problems. The separation is done with power ratio (PR) maps based on the spectral characteristics of the signal and the identification of the type of event is done localizing the source with an array of four antennas. Several classical methods to calculate the time differences of arrival (TDOA) of the emission to the antennas have been tested, and the localization is done using particle swarm optimization (PSO) to minimize a distance function.