Discharge Pattern Recognition Research Articles

FoSSA Optimization-Based SVM Classifier for the Recognition of Partial Discharge Patterns in HV Cables

In order to enhance the classification accuracy and the generalization performance of the SVM classifier in cable partial discharge (PD) pattern recognition, a firefly optimized sparrow search algorithm (FoSSA) is proposed to optimize its kernel function parameters and penalty factors. First, the Circle-Gauss hybrid mapping model is employed in the population initialization stage of the sparrow search algorithm (SSA) to eliminate the uneven population distribution of random mapping. Sparrows tend to fall into local extremums during the search process, while the firefly algorithm has a fast optimization speed and strong local search ability. Thus, a firefly disturbance is added in the sparrow search process, and the fitness value is recalculated to update the sparrow position to enhance the sparrow's local optimization ability and accuracy. Finally, based on the SSA, a dynamic step-size strategy is adopted to make the step size dynamically decrease with the number of iterations and improve the accuracy of convergence. Six benchmark functions are employed to evaluate the optimization performance of the FoSSA quantitatively. Experiment results show that the recognition accuracy of the PD patterns using the SVM optimized by the FoSSA could reach 97.5%.

A digital procedure for ground water recharge and discharge pattern recognition and rate estimation.

A digital procedure to estimate recharge/discharge rates that requires relatively short preparation time and uses readily available data was applied to a setting in central Wisconsin. The method requires only measurements of the water table, fluxes such as stream baseflows, bottom of the system, and hydraulic conductivity to delineate approximate recharge/discharge zones and to estimate rates. The method uses interpolation of the water table surface, recharge/discharge mapping, pattern recognition, and a parameter estimation model. The surface interpolator used is based on the theory of radial basis functions with thin-plate splines. The recharge/discharge mapping is based on a mass-balance calculation performed using MODFLOW. The results of the recharge/discharge mapping are critically dependent on the accuracy of the water table interpolation and the accuracy and number of water table measurements. The recharge pattern recognition is performed with the help of a graphical user interface (GUI) program based on several algorithms used in image processing. Pattern recognition is needed to identify the recharge/discharge zonations and zone the results of the mapping method. The parameter estimation program UCODE calculates the parameter values that provide a best fit between simulated heads and flows and calibration head-and-flow targets. A model of the Buena Vista Ground Water Basin in the Central Sand Plains of Wisconsin is used to demonstrate the procedure.

Subspecies analysis of partial discharge data from a generator stator conductor

Partial discharge (PD) pattern recognition systems are often based on analysis of the data structure as a whole. This approach may not explain the underlying discharge processes. An alternative concept is proposed which is based on the examination and analysis of the subspecies identifiable in the data. PD data obtained from a generator stator conductor are used to demonstrate this approach. Using well-behaved data it is possible to identify two distinctive types of discharges originating from a generator stator conductor. One type has properties ascribable to surface discharges, whereas the other type exhibits properties akin to those from internal discharges. The approach allows ill-behaved PD data to be segmented in a supervised manner using knowledge about the likely behaviour of different types of PD. This permits individual PD generating mechanisms to be monitored, which may be difficult to achieve through analysis of the overall magnitude and phase distributions. Using the method, it is demonstrated that the surface discharges have a magnitude distribution whose shape is influenced by a multivalued relationship with the phase distribution. These relationships are obscured if magnitude distribution only is used for the analysis but are observable using subspecies analysis.

Discharge pattern recognition in high voltage equipment

The paper considers the diagnosis of HV constructions which suffer from partial discharge (PD). Using previously developed statistical techniques the properties of discharge patterns are quantified in a fingerprint. Through the analysis of different defects and their fingerprints in HV constructions, the practical implication of these techniques is discussed. Furthermore, different possibilities of developing a data bank for the recognition and diagnosis in HV components are shown.

New approach in partial discharge diagnosis and pattern recognition

Digital measuring techniques and diagnosis systems have been developed to assist the test engineer. The most common diagnostic tools are two- or three-dimensional distributions or histograms which exhibit the typical patterns of the partial discharge (PD) activity. The main disadvantage of all these graphs in PD diagnosis is the averaging effect of the statistics used. The authors show a graph of partial discharge activity without any averaging effect, which gives an overview of every single PD pulse of the whole measurement. In this diagram the parameters charge, phase, time and test voltage are included, so that it is possible to summarise all significant information on one computer printout. By seeing PD evolution from period to period, visual recognition and expert classification becomes practicable and the capabilities of an automated personal computer based PD-fault type recognition system is shown. Results of acoustical PD classification are presented and the influence of test voltage on electrical and acoustical PD-recognition is discussed. Additionally, a powerful method to localise the compartment with PD-source in gas-insulated switchgear (GIS) is derived.